Minehunting sonar system research and development

NASA Astrophysics Data System (ADS)

Ferguson, Brian

2002-05-01

Sea mines have the potential to threaten the freedom of the seas by disrupting maritime trade and restricting the freedom of maneuver of navies. The acoustic detection, localization, and classification of sea mines involves a sequence of operations starting with the transmission of a sonar pulse and ending with an operator interpreting the information on a sonar display. A recent improvement to the process stems from the application of neural networks to the computed aided detection of sea mines. The advent of ultrawideband sonar transducers together with pulse compression techniques offers a thousandfold increase in the bandwidth-time product of conventional minehunting sonar transmissions enabling stealth mines to be detected at longer ranges. These wideband signals also enable mines to be imaged at safe standoff distances by applying tomographic image reconstruction techniques. The coupling of wideband transducer technology with synthetic aperture processing enhances the resolution of side scan sonars in both the cross-track and along-track directions. The principles on which conventional and advanced minehunting sonars are based are reviewed and the results of applying novel sonar signal processing algorithms to high-frequency sonar data collected in Australian waters are presented.

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

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-08-01

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

Web Mining for Web Image Retrieval.

ERIC Educational Resources Information Center

Chen, Zheng; Wenyin, Liu; Zhang, Feng; Li, Mingjing; Zhang, Hongjiang

2001-01-01

Presents a prototype system for image retrieval from the Internet using Web mining. Discusses the architecture of the Web image retrieval prototype; document space modeling; user log mining; and image retrieval experiments to evaluate the proposed system. (AEF)

Assessment of the capability of remote sensing and GIS techniques for monitoring reclamation success in coal mine degraded lands.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan; Maiti, Subodh Kumar

2016-11-01

The objective of the present study is to monitor reclamation activity in mining areas. Monitoring of these reclaimed sites in the vicinity of mining areas and on closed Over Burden (OB) dumps is critical for improving the overall environmental condition, especially in developing countries where area around the mines are densely populated. The present study evaluated the reclamation success in the Block II area of Jharia coal field, India, using Landsat satellite images for the years 2000 and 2015. Four image processing methods (support vector machine, ratio vegetation index, enhanced vegetation index, and normalized difference vegetation index) were used to quantify the change in vegetation cover between the years 2000 and 2015. The study also evaluated the relationship between vegetation health and moisture content of the study area using remote sensing techniques. Statistical linear regression analysis revealed that Normalized Difference Vegetation Index (NDVI) coupled with Normalized Difference Moisture Index (NDMI) is the best method for vegetation monitoring in the study area when compared to other indices. A strong linear relationship (r(2) > 0.86) was found between NDVI and NDMI. An increase of 21% from 213.88 ha in 2000 to 258.9 ha in 2015 was observed in the vegetation cover of the reclaimed sites for an open cast mine, indicating satisfactory reclamation activity. NDVI results indicated that vegetation health also improved over the years. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

An AK-LDMeans algorithm based on image clustering

NASA Astrophysics Data System (ADS)

Chen, Huimin; Li, Xingwei; Zhang, Yongbin; Chen, Nan

2018-03-01

Clustering is an effective analytical technique for handling unmarked data for value mining. Its ultimate goal is to mark unclassified data quickly and correctly. We use the roadmap for the current image processing as the experimental background. In this paper, we propose an AK-LDMeans algorithm to automatically lock the K value by designing the Kcost fold line, and then use the long-distance high-density method to select the clustering centers to further replace the traditional initial clustering center selection method, which further improves the efficiency and accuracy of the traditional K-Means Algorithm. And the experimental results are compared with the current clustering algorithm and the results are obtained. The algorithm can provide effective reference value in the fields of image processing, machine vision and data mining.

Utility of hyperspectral imagers in the mining industry: Italy's gypsum reserves

NASA Astrophysics Data System (ADS)

Wilson, Janette H.; Greenberger, Rebecca N.

2014-05-01

The mining industry is plagued with socioeconomic and safety roadblocks with not many solutions in the midst of a demanding market. As more and more geologic research using hyperspectral technology has been performed, along with an affordable price point for commercial use of hyperspectral technology, the benefits of hyperspectral imaging to the mining industry has become apparent. This study identifies the key areas of use for hyperspectral imaging in the mining industry through a case study of gypsum mine samples obtained from a mine in central Tuscany.

Preliminary study of detection of buried landmines using a programmable hyperspectral imager

NASA Astrophysics Data System (ADS)

McFee, John E.; Ripley, Herb T.; Buxton, Roger; Thriscutt, Andrew M.

1996-05-01

Experiments were conducted to determine if buried mines could be detected by measuring the change in reflectance spectra of vegetation above mine burial sites. Mines were laid using hand methods and simulated mechanical methods and spectral images were obtained over a three month period using a casi hyperspectral imager scanned from a personnel lift. Mines were not detectable by measurement of the shift of the red edge of vegetative spectra. By calculating the linear correlation coefficient image, some mines in light vegetative cover (grass, grass/blueberries) were apparently detected, but mines buried in heavy vegetation cover (deep ferns) were not detectable. Due to problems with ground truthing, accurate probabilities of detection and false alarm rates were not obtained.

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

Constructing and Classifying Email Networks from Raw Forensic Images

DTIC Science & Technology

2016-09-01

data mining for sequence and pattern mining ; in medical imaging for image segmentation; and in computer vision for object recognition” [28]. 2.3.1...machine learning and data mining suite that is written in Python. It provides a platform for experiment selection, recommendation systems, and...predictivemod- eling. The Orange library is a hierarchically-organized toolbox of data mining components. Data filtering and probability assessment are at the

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

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)

Sensor feature fusion for detecting buried objects

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

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

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

Survey of Knowledge Representation and Reasoning Systems

DTIC Science & Technology

2009-07-01

processing large volumes of unstructured information such as natural language documents, email, audio , images and video [Ferrucci et al. 2006]. Using this...information we hope to obtain improved es- timation and prediction, data-mining, social network analysis, and semantic search and visualisation . Knowledge

Remote Detection and Mapping of Supergene Iron Oxides in the Cripple Creek Mining District, Colorado

NASA Technical Reports Server (NTRS)

Taranik, D. L.; Kruse, F. A.; Goetz, A. F. H.; Atkinson, W. W.

1990-01-01

The Geophysical and Environmental Research Imaging Spectrometer (GERIS) was flown over the Cripple Creek mining district in south-central Colorado to improve the geological understanding of the district. As part of the study, an airborne mapping technique was developed for the discrimination of the ferric iron minerals hematite, goethite, and jarosite, minerals often important indicators of the distribution of economic mineralization. A software technique was developed which uses the binary encoding of spectral slopes to identify the mineral hematite from the group goethite/jarosite. Mixtures of hematite and goethite can also be detected with GERIS data. The study included district-wide field mapping and spectral measurements to evaluate the accuracy of the image classifications. The ARC/INFO geographic information system (GIS) was a useful tool which allowed quantitative comparison of the field mapping and GERIS image data sets. The study results demonstrate the ability to discriminate individual iron minerals using imaging spectroscopy, and the development of a rapid mapping technique useful in the reconnaissance stage of minerals exploration.

Remote detection of buried land-mines and IEDs using LWIR polarimetric imaging.

PubMed

Gurton, Kristan P; Felton, Melvin

2012-09-24

We report results of an ongoing study designed to assess the ability for enhanced detection of recently buried land-mines and/or improvised explosive devices (IED) devices using passive long-wave infrared (LWIR) polarimetric imaging. Polarimetric results are presented for a series of field tests conducted at various locations and soil types. Well-calibrated Stokes images, S0, S1, S2, and the degree-of-linear-polarization (DoLP) are recorded for different line-of-sight (LOS) slant paths at varying distances. Results span a three-year time period in which three different LWIR polarimetric camera systems are used. All three polarimetric imaging platforms used a spinning-achromatic-retarder (SAR) design capable of achieving high polarimetric frame rates and good radiometric throughput without the loss of spatial resolution inherent in other optical designs. Receiver-operating-characteristic (ROC) analysis and a standardized contrast parameter are used to compare detectability between conventional LWIR thermal and polarimetric imagery. Results suggest improved detectability, regardless of geographic location or soil type.

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

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.

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

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

Information mining in remote sensing imagery

NASA Astrophysics Data System (ADS)

Li, Jiang

The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and fuzzy normalized difference vegetation index (NDVI) pattern mining. The study results show the effectiveness of the proposed system prototype and the potentials for other applications in remote sensing.

Poker Flats Mine - Div. of Mining, Land, and Water

Science.gov Websites

Lands Coal Regulatory Program Large Mine Permits Mineral Property and Rights Mining Index Land Fishery Water Resources Factsheets Forms banner image of landscape Poker Flats Mine Home Mining Coal Regulatory Program Poker Flats Mine Mining Coal Regulatory Program Info Chickaloon Chuit Watershed Chuitna

A new approach for fast indexing of hyperspectral image data for knowledge retrieval and mining

NASA Astrophysics Data System (ADS)

Clowers, Robert; Dua, Sumeet

2005-11-01

Multispectral sensors produce images with a few relatively broad wavelength bands. Hyperspectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow and adjacent spectral bands. These measurements make it possible to derive a continuous spectrum for each image cell, generating an image cube across multiple spectral components. Hyperspectral imaging has sound applications in a variety of areas such as mineral exploration, hazardous waste remediation, mapping habitat, invasive vegetation, eco system monitoring, hazardous gas detection, mineral detection, soil degradation, and climate change. This image has a strong potential for transforming the imaging paradigms associated with several design and manufacturing processes. In this paper, we describe a novel approach for fast indexing of multi-dimensional hyperspectral image data, especially for data mining applications. The index exploits the spectral and spatial relationships embedded in these image sets. The index will be employed for knowledge retrieval applications that require fast information interpretation approaches. The index can also be deployed in real-time mission-critical domains, as it is shown to exhibit speed with high degrees of dimensionality associated with the data. The strength of this index in terms of degree of false dismissals and false alarms will also be demonstrated. The paper will highlight some common applications of this imaging computational paradigm and will conclude with directions for future improvement and investigation.

Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

NASA Astrophysics Data System (ADS)

Gururaj, C.; Jayadevappa, D.; Tunga, Satish

2018-02-01

Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

NASA Astrophysics Data System (ADS)

Gururaj, C.; Jayadevappa, D.; Tunga, Satish

2018-06-01

Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

Orapa Diamond Mine, Botswana

NASA Image and Video Library

2015-11-16

This image from NASA Terra spacecraft shows the Orapa diamond mine, the world largest diamond mine by area. The mine is located in Botswana. It is the oldest of four mines operated by the same company, having begun operations in 1971. Orapa is an open pit style of mine, located on two kimberlite pipes. Currently, the Orapa mine annually produces approximately 11 million carats (2200 kg) of diamonds. The Letlhakane diamond mine is also an open pit construction. In 2003, the Letlhakane mine produced 1.06 million carats of diamonds. The Damtshaa diamond mine is the newest of four mines, located on top of four distinct kimberlite pipes of varying ore grade. The mine is forecast to produce about 5 million carats of diamond over the projected 31 year life of the mine. The image was acquired October 5, 2014, covers an area of 28 by 45 km, and is located at 21.3 degrees south, 25.4 degrees east. http://photojournal.jpl.nasa.gov/catalog/PIA20104

Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

ERIC Educational Resources Information Center

Chen, Xin

2012-01-01

Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

Imaging the state of the rock mass in the Kiirunavaara iron ore mine, Sweden, using local event tomography

NASA Astrophysics Data System (ADS)

Lund, Björn; Berglund, Karin; Tryggvason, Ari; Dineva, Savka; Jonsson, Linda

2017-04-01

Induced seismic events in a mining environment are a potential hazard, but they can be used to gain information about the rock mass in the mine which otherwise would be very difficult to obtain. In this study we use approximately 1.2 million mining induced seismic events in the Kiirunavaara iron ore mine in northernmost Sweden to image the rock mass using local event travel-time tomography. In addition, relocation of the events significantly improves the possibility to infer structural information and rock damage. The Kiirunavaara mine is one of the largest underground iron ore mines in the world. The ore body is a magnetite sheet of 4 km length, with an average thickness of 80 m, which dips approximately 55° to the east. Mining production is now at a depth of 785 - 855 m. During 2015 the seismic system in the mine recorded on average approximately 1,000 local seismic events per day. The events are of various origins such as shear slip on fractures, non-shear events and blasts, with magnitudes of up to 2.5. We use manually picked P- and S-waves in the tomography and we require that both phases are present as we found that events from the routine processing need screening for anomalous P- versus S-travel times, indicating occasional erroneous phase associations. For the tomography we use the 3D local earthquake tomography code PStomo_eq (Tryggvason et al., 2002), which we adjusted to the mining scale. The study volume is 1.2 x 1.8 x 1.8 km and the velocity model grid size is 10x10x10 meter. The tomographic images show clearly defined regions of high and low velocities. Low velocity zones are associated with mapped clay zones and areas of mined out ore, and also with the near-ore tunnel infrastructure in the foot-wall. We also see how the low S-velocity anomaly continues to depth below the current mining levels, following the inferred direction of the ore. The tomography shows higher P- and S-velocities in the foot-wall away from the areas of mine infrastructure. We relocate all 1.2 million events in the new 3D velocity model. The relocation significantly enhances the clarity of the event distribution in space and we can much more easily identify seismically active structures. One example of this is the clarity with which deformation of the ore-passes is correlated with the intensity and distribution of relocated seismic events. The relocations also show more structures in areas of the mine where rock stability is a significant problem. The large number of events makes it possible to do detailed studies of the temporal evolution of stability in the mine. We present preliminary results of time-lapse tomography in an area where a few events of magnitude 2+ occurred in September 2015.

Automated data mining of a proprietary database system for physician quality improvement.

PubMed

Johnstone, Peter A S; Crenshaw, Tim; Cassels, Diane G; Fox, Timothy H

2008-04-01

Physician practice quality improvement is a subject of intense national debate. This report describes using a software data acquisition program to mine an existing, commonly used proprietary radiation oncology database to assess physician performance. Between 2003 and 2004, a manual analysis was performed of electronic portal image (EPI) review records. Custom software was recently developed to mine the record-and-verify database and the review process of EPI at our institution. In late 2006, a report was developed that allowed for immediate review of physician completeness and speed of EPI review for any prescribed period. The software extracted >46,000 EPIs between 2003 and 2007, providing EPI review status and time to review by each physician. Between 2003 and 2007, the department EPI review improved from 77% to 97% (range, 85.4-100%), with a decrease in the mean time to review from 4.2 days to 2.4 days. The initial intervention in 2003 to 2004 was moderately successful in changing the EPI review patterns; it was not repeated because of the time required to perform it. However, the implementation in 2006 of the automated review tool yielded a profound change in practice. Using the software, the automated chart review required approximately 1.5 h for mining and extracting the data for the 4-year period. This study quantified the EPI review process as it evolved during a 4-year period at our institution and found that automation of data retrieval and review simplified and facilitated physician quality improvement.

Evaluation of longitudinal tracking and data mining for an imaging informatics-based multiple sclerosis e-folder (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ma, Kevin C.; Forsyth, Sydney; Amezcua, Lilyana; Liu, Brent J.

2017-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results to allow patient tracking. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system quantifies lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. We aim to evaluate the two most important features of the system, data mining and longitudinal lesion tracking, to demonstrate the MS eFolder's capability in improving clinical workflow efficiency and outcome analysis for research. In order to evaluate data mining capabilities, we have collected radiological and neurological data from 72 patients, 36 Caucasian and 36 Hispanic matched by gender, disease duration, and age. Data analysis on those patients based on ethnicity is performed, and analysis results are displayed by the system's web-based user interface. The data mining module is able to successfully separate Hispanic and Caucasian patients and compare their disease profiles. For longitudinal lesion tracking, we have collected 4 longitudinal cases and simulated different lesion growths over the next year. As a result, the eFolder is able to detect changes in lesion volume and identifying lesions with the most changes. Data mining and lesion tracking evaluation results show high potential of eFolder's usefulness in patientcare and informatics research for multiple sclerosis.

Detecting and monitoring UCG subsidence with InSAR

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

Mellors, R J; Foxall, W; Yang, X

2012-03-23

The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidencemore » related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness.« less

Improved close-in detection for the mine hunter/killer system

NASA Astrophysics Data System (ADS)

Bishop, Steven S.; Campana, Stephen B.; Duston, Brian M.; Lang, David A.; Wiggins, Carl M.

2001-10-01

The Close-In Detector (CID) is the vehicle-mounted multi-sensor anti-tank landmine detection technology for the Army CECOM Night Vision Electronic Sensors Directorate (NVESD) Mine Hunter-Killer (MH/K) Program. The CID includes two down-looking sensor arrays: a 20-antenna ground-penetrating radar (GPR) and a 16-coil metal detector (MD). These arrays span 3-meters in front of a high mobility, multipurpose wheeled vehicle (HMMWV). The CID also includes a roof-mounted, forward looking infrared (FLIR) camera that images a trapezoidal area of the road ahead of the vehicle. Signals from each of the three sensors are processed separately to detect and localize objects of interest. Features of candidate objects are integrated in a processor that uses them to discriminates between anti-tank (AT) mines and clutter and produces a list of suspected mine locations which are passed to the neutralization subsystem of MH/K. This paper reviews the current design and performance of the CID based on field test results on dirt and gravel mine test lanes. Improvements in CID performance for probability of detection, false alarm rate, target positional accuracy and system rate of advance over the past year and a half that meet most of the program goals are described. Sensor performances are compared, and the effectiveness of six different sensor fusion approaches are measured and compared.

Semi-automated based ground-truthing GUI for airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Lydic, Rich; Moore, Tim; Trang, Anh; Agarwal, Sanjeev; Tiwari, Spandan

2005-06-01

Over the past several years, an enormous amount of airborne imagery consisting of various formats has been collected and will continue into the future to support airborne mine/minefield detection processes, improve algorithm development, and aid in imaging sensor development. The ground-truthing of imagery is a very essential part of the algorithm development process to help validate the detection performance of the sensor and improving algorithm techniques. The GUI (Graphical User Interface) called SemiTruth was developed using Matlab software incorporating signal processing, image processing, and statistics toolboxes to aid in ground-truthing imagery. The semi-automated ground-truthing GUI is made possible with the current data collection method, that is including UTM/GPS (Universal Transverse Mercator/Global Positioning System) coordinate measurements for the mine target and fiducial locations on the given minefield layout to support in identification of the targets on the raw imagery. This semi-automated ground-truthing effort has developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division, Airborne Application Branch with some support by the University of Missouri-Rolla.

Validation of Airborne Visible-Infrared Imaging Spectrometer Data at Ray Mine, AZ

NASA Technical Reports Server (NTRS)

Lang, H.; Baloga, S.

1999-01-01

We validate 1997 Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) reflectance spectra covering 0.4 meu - 2.4 meu from a stable, flat mineralogically characterized man-made target at Ray Mine, AZ, the site for an EPA/NASA assessment of the utility of remote sensing for monitoring acid drainage from an active open pit mine.

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

NASA Astrophysics Data System (ADS)

Krawczyk, Artur; Grzybek, Radosław

2018-01-01

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

Using Local Event Tomography to Image Changes in the Rock Mass in the Kiirunavaara Iron Ore Mine, Northern Sweden

NASA Astrophysics Data System (ADS)

Lund, B.; Berglund, K.; Tryggvason, A.; Dineva, S.; Jonsson, L.

2017-12-01

Although induced seismic events in a mining environment are a potential hazard, they can be used to gain information about the rock mass in the mine which otherwise would be very difficult to obtain. In this study we use approximately 1.2 million mining induced seismic events in the Kiirunavaara iron ore mine in northernmost Sweden to image the rock mass using local event travel-time tomography. The Kiirunavaara mine is the largest underground iron ore mine in the world. The ore body is a magnetite sheet of 4 km length, with an average thickness of 80 m, which dips approximately 55° to the east. The events are of various origins such as shear slip on fractures, non-shear events and blasts, with magnitudes of up to 2.5. We use manually picked P- and S-wave arrival times from the routine processing in the tomography and we require that both phases are present at at least five geophones. For the tomography we use the 3D local earthquake tomography code PStomo_eq (Tryggvason et al., 2002), which we adjusted to the mining scale. The tomographic images show clearly defined regions of high and low velocities. Prominent low S-velocity zones are associated with mapped clay zones. Regions of ore where mining is ongoing and the near-ore tunnel infrastructure in the foot-wall also show generally low P- and S-velocities. The ore at depths below the current mining levels is imaged both as a low S-velocity zone but even more pronounced as a high Vp/Vs ratio zone. The tomography shows higher P- and S-velocities in the foot-wall away from the areas of mine infrastructure. We relocate all 1.2 million events in the new 3D velocity model. The relocation significantly enhances the clarity of the event distribution in space and we can much more easily identify seismically active structures, such as e.g. the deformation of the ore passes. The large number of events makes it possible to do detailed studies of the temporal evolution of stability in the mine. We present preliminary results of time-lapse tomography in an area where a few events of magnitude 2+ occurred in September 2015. We also image temporal velocity changes around the mining front at depth.

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.

Diavik Mine, Canada

NASA Image and Video Library

2017-04-13

This image from NASA Terra spacecraft shows the Diavik Mine in northern Canada.The largest diamond found in North America came from the Diavik Mine. The Foxfire diamond weighs an impressive 187 carats, and was discovered in August 2015; it has been displayed in several museums throughout North America. The Diavik mine is located on an island in Lac de Gras, within the Lac de Gras kimberlite field, among other diamond mines. The image was acquired September 23, 2016, covers an area of 13.8 by 19.4 km, and is located at 64.5 degrees north, 110.2 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA21536

Goldstrike Mine, Nevada

NASA Image and Video Library

2017-05-15

This image from NASA Terra spacecraft shows Goldstrike in northeast Nevada, the largest gold mine in North America. The mine complex, (including the Betze-Post-Screamer open-pit, and Meikle and Rodeo underground mines) is owned and operated by the world's largest gold mining company, Barrick Gold. Gold occurs as microscopically fine grains, with an average grade of 0.1 ounces per ton of ore. Estimates of reserves are as high as 35 million ounces of gold. The image was acquired September 25, 2010, covers an area of 15 by 15 km, and is located at 41 degrees north, 116.4 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA21665

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 incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Advances and considerations in technologies for growing, imaging, and analyzing 3-D root system architecture

USDA-ARS?s Scientific Manuscript database

The ability of a plant to mine the soil for nutrients and water is determined by how, where, and when roots are arranged in the soil matrix. The capacity of plant to maintain or improve its yield under limiting conditions, such as nutrient deficiency or drought, is affected by root system architectu...

The Canadian Forces ILDS: a militarily fielded multisensor vehicle-mounted teleoperated landmine detection system

NASA Astrophysics Data System (ADS)

McFee, John E.; Russell, Kevin L.; Chesney, Robert H.; Faust, Anthony A.; Das, Yogadhish

2006-05-01

The Improved Landmine Detection System (ILDS) is intended to meet Canadian military mine clearance requirements in rear area combat situations and peacekeeping on roads and tracks. The system consists of two teleoperated vehicles and a command vehicle. The teleoperated protection vehicle precedes, clearing antipersonnel mines and magnetic and tilt rod-fuzed antitank mines. It consists of an armoured personnel carrier with a forward looking infrared imager, a finger plow or roller and a magnetic signature duplicator. The teleoperated detection vehicle follows to detect antitank mines. The purpose-built vehicle carries forward looking infrared and visible imagers, a 3 m wide, down-looking sensitive electromagnetic induction detector array and a 3 m wide down-looking ground probing radar, which scan the ground in front of the vehicle. Sensor information is combined using navigation sensors and custom navigation, registration, spatial correspondence and data fusion algorithms. Suspicious targets are then confirmed by a thermal neutron activation detector. The prototype, designed and built by Defence R&D Canada, was completed in October 1997. General Dynamics Canada delivered four production units, based on the prototype concept and technologies, to the Canadian Forces (CF) in 2002. ILDS was deployed in Afghanistan in 2003, making the system the first militarily fielded, teleoperated, multi-sensor vehicle-mounted mine detector and the first with a fielded confirmation sensor. Performance of the prototype in Canadian and independent US trials is summarized and recent results from the production version of the confirmation sensor are discussed. CF operations with ILDS in Afghanistan are described.

Diamond Eye: a distributed architecture for image data mining

NASA Astrophysics Data System (ADS)

Burl, Michael C.; Fowlkes, Charless; Roden, Joe; Stechert, Andre; Mukhtar, Saleem

1999-02-01

Diamond Eye is a distributed software architecture, which enables users (scientists) to analyze large image collections by interacting with one or more custom data mining servers via a Java applet interface. Each server is coupled with an object-oriented database and a computational engine, such as a network of high-performance workstations. The database provides persistent storage and supports querying of the 'mined' information. The computational engine provides parallel execution of expensive image processing, object recognition, and query-by-content operations. Key benefits of the Diamond Eye architecture are: (1) the design promotes trial evaluation of advanced data mining and machine learning techniques by potential new users (all that is required is to point a web browser to the appropriate URL), (2) software infrastructure that is common across a range of science mining applications is factored out and reused, and (3) the system facilitates closer collaborations between algorithm developers and domain experts.

Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer

PubMed Central

Kothari, Sonal; Phan, John H.; Young, Andrew N.; Wang, May D.

2016-01-01

Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an “optimal” diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis PMID:28163980

Geophysical Technologies to Image Old Mine Works

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

Kanaan Hanna; Jim Pfeiffer

2007-01-15

ZapataEngineering, Blackhawk Division performed geophysical void detection demonstrations for the US Department of Labor Mine Safety and Health Administration (MSHA). The objective was to advance current state-of-practices of geophysical technologies for detecting underground mine voids. The presence of old mine works above, adjacent, or below an active mine presents major health and safety hazards to miners who have inadvertently cut into locations with such features. In addition, the presence of abandoned mines or voids beneath roadways and highway structures may greatly impact the performance of the transportation infrastructure in terms of cost and public safety. Roads constructed over abandoned minesmore » are subject to potential differential settlement, subsidence, sinkholes, and/or catastrophic collapse. Thus, there is a need to utilize geophysical imaging technologies to accurately locate old mine works. Several surface and borehole geophysical imaging methods and mapping techniques were employed at a known abandoned coal mine in eastern Illinois to investigate which method best map the location and extent of old works. These methods included: 1) high-resolution seismic (HRS) using compressional P-wave (HRPW) and S-wave (HRSW) reflection collected with 3-D techniques; 2) crosshole seismic tomography (XHT); 3) guided waves; 4) reverse vertical seismic profiling (RVSP); and 5) borehole sonar mapping. In addition, several exploration borings were drilled to confirm the presence of the imaged mine voids. The results indicated that the RVSP is the most viable method to accurately detect the subsurface voids with horizontal accuracy of two to five feet. This method was then applied at several other locations in Colorado with various topographic, geologic, and cultural settings for the same purpose. This paper presents the significant results obtained from the geophysical investigations in Illinois.« less

Data Mining: The Art of Automated Knowledge Extraction

NASA Astrophysics Data System (ADS)

Karimabadi, H.; Sipes, T.

2012-12-01

Data mining algorithms are used routinely in a wide variety of fields and they are gaining adoption in sciences. The realities of real world data analysis are that (a) data has flaws, and (b) the models and assumptions that we bring to the data are inevitably flawed, and/or biased and misspecified in some way. Data mining can improve data analysis by detecting anomalies in the data, check for consistency of the user model assumptions, and decipher complex patterns and relationships that would not be possible otherwise. The common form of data collected from in situ spacecraft measurements is multi-variate time series which represents one of the most challenging problems in data mining. We have successfully developed algorithms to deal with such data and have extended the algorithms to handle streaming data. In this talk, we illustrate the utility of our algorithms through several examples including automated detection of reconnection exhausts in the solar wind and flux ropes in the magnetotail. We also show examples from successful applications of our technique to analysis of 3D kinetic simulations. With an eye to the future, we provide an overview of our upcoming plans that include collaborative data mining, expert outsourcing data mining, computer vision for image analysis, among others. Finally, we discuss the integration of data mining algorithms with web-based services such as VxOs and other Heliophysics data centers and the resulting capabilities that it would enable.

Application of EREP imagery to fracture-related mine safety hazards in coal mining and mining-environmental problems in Indiana. [Indiana and Illinois

NASA Technical Reports Server (NTRS)

Wier, C. E. (Principal Investigator); Powell, R. L.; Amato, R. V.; Russell, O. R.; Martin, K. R.

1975-01-01

The author has identified the following significant results. This investigation evaluated the applicability of a variety of sensor types, formats, and resolution capabilities to the study of both fuel and nonfuel mined lands. The image reinforcement provided by stereo viewing of the EREP images proved useful for identifying lineaments and for mined lands mapping. Skylab S190B color and color infrared transparencies were the most useful EREP imagery. New information on lineament and fracture patterns in the bedrock of Indiana and Illinois extracted from analysis of the Skylab imagery has contributed to furthering the geological understanding of this portion of the Illinois basin.

Using imaging spectroscopy to map acidic mine waste

USGS Publications Warehouse

Swayze, G.A.; Smith, K.S.; Clark, R.N.; Sutley, S.J.; Pearson, R.M.; Vance, J.S.; Hageman, P.L.; Briggs, P.H.; Meier, A.L.; Singleton, M.J.; Roth, S.

2000-01-01

The process of pyrite oxidation at the surface of mine waste may produce acidic water that is gradually neutralized as it drains away from the waste, depositing different Fe-bearing secondary minerals in roughly concentric zones that emanate from mine-waste piles. These Fe-bearing minerals are indicators of the geochemical conditions under which they form. Airborne and orbital imaging spectrometers can be used to map these mineral zones because each of these Fe-bearing secondary minerals is spectrally unique. In this way, imaging spectroscopy can be used to rapidly screen entire mining districts for potential sources of surface acid drainage and to detect acid producing minerals in mine waste or unmined rock outcrops. Spectral data from the AVIRIS instrument were used to evaluate mine waste at the California Gulch Superfund Site near Leadville, CO. Laboratory leach tests of surface samples show that leachate pH is most acidic and metals most mobile in samples from the inner jarosite zone and that leachate pH is near-neutral and metals least mobile in samples from the outer goethite zone.

Analysis of Mining-Induced Subsidence Prediction by Exponent Knothe Model Combined with Insar and Leveling

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Liguo; Tang, Yixian; Zhang, Hong

2018-04-01

The principle of exponent Knothe model was introduced in detail and the variation process of mining subsidence with time was analysed based on the formulas of subsidence, subsidence velocity and subsidence acceleration in the paper. Five scenes of radar images and six levelling measurements were collected to extract ground deformation characteristics in one coal mining area in this study. Then the unknown parameters of exponent Knothe model were estimated by combined levelling data with deformation information along the line of sight obtained by InSAR technique. By compared the fitting and prediction results obtained by InSAR and levelling with that obtained only by levelling, it was shown that the accuracy of fitting and prediction combined with InSAR and levelling was obviously better than the other that. Therefore, the InSAR measurements can significantly improve the fitting and prediction accuracy of exponent Knothe model.

A spatiotemporal decomposition strategy for personal home video management

NASA Astrophysics Data System (ADS)

Yi, Haoran; Kozintsev, Igor; Polito, Marzia; Wu, Yi; Bouguet, Jean-Yves; Nefian, Ara; Dulong, Carole

2007-01-01

With the advent and proliferation of low cost and high performance digital video recorder devices, an increasing number of personal home video clips are recorded and stored by the consumers. Compared to image data, video data is lager in size and richer in multimedia content. Efficient access to video content is expected to be more challenging than image mining. Previously, we have developed a content-based image retrieval system and the benchmarking framework for personal images. In this paper, we extend our personal image retrieval system to include personal home video clips. A possible initial solution to video mining is to represent video clips by a set of key frames extracted from them thus converting the problem into an image search one. Here we report that a careful selection of key frames may improve the retrieval accuracy. However, because video also has temporal dimension, its key frame representation is inherently limited. The use of temporal information can give us better representation for video content at semantic object and concept levels than image-only based representation. In this paper we propose a bottom-up framework to combine interest point tracking, image segmentation and motion-shape factorization to decompose the video into spatiotemporal regions. We show an example application of activity concept detection using the trajectories extracted from the spatio-temporal regions. The proposed approach shows good potential for concise representation and indexing of objects and their motion in real-life consumer video.

Keynote Talk: Mining the Web 2.0 for Improved Image Search

NASA Astrophysics Data System (ADS)

Baeza-Yates, Ricardo

There are several semantic sources that can be found in the Web that are either explicit, e.g. Wikipedia, or implicit, e.g. derived from Web usage data. Most of them are related to user generated content (UGC) or what is called today the Web 2.0. In this talk we show how to use these sources of evidence in Flickr, such as tags, visual annotations or clicks, which represent the the wisdom of crowds behind UGC, to improve image search. These results are the work of the multimedia retrieval team at Yahoo! Research Barcelona and they are already being used in Yahoo! image search. This work is part of a larger effort to produce a virtuous data feedback circuit based on the right combination many different technologies to leverage the Web itself.

A REAL-TIME COAL CONTENT/ORE GRADE (C2OC) SENSOR

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

Rand Swanson

2005-04-01

This is the final report of a three year DOE funded project titled ''A real-time coal content/ore grade (C{sub 2}OG) sensor''. The sensor, which is based on hyperspectral imaging technology, was designed to give a machine vision assay of ore or coal. Sensors were designed and built at Resonon, Inc., and then deployed at the Stillwater Mining Company core room in southcentral Montana for analyzing platinum/palladium ore and at the Montana Tech Spectroscopy Lab for analyzing coal and other materials. The Stillwater sensor imaged 91' of core and analyzed this data for surface sulfides which are considered to be pathfindermore » minerals for platinum/palladium at this mine. Our results indicate that the sensor could deliver a relative ore grade provided tool markings and iron oxidation were kept to a minimum. Coal, talc, and titanium sponge samples were also imaged and analyzed for content and grade with promising results. This research has led directly to a DOE SBIR Phase II award for Resonon to develop a down-hole imaging spectrometer based on the same imaging technology used in the Stillwater core room C{sub 2}OG sensor. The Stillwater Mining Company has estimated that this type of imaging system could lead to a 10% reduction in waste rock from their mine and provide a $650,000 benefit per year. The proposed system may also lead to an additional 10% of ore tonnage, which would provide a total economic benefit of more than $3.1 million per year. If this benefit could be realized on other metal ores for which the proposed technology is suitable, the possible economic benefits to U.S. mines is over $70 million per year. In addition to these currently lost economic benefits, there are also major energy losses from mining waste rock and environmental impacts from mining, processing, and disposing of waste rock.« less

Change detection over Sokolov open-pit mining area, Czech Republic, using multi-temporal HyMAP data (2009-2010)

NASA Astrophysics Data System (ADS)

Adar, S.; Notesco, G.; Brook, A.; Livne, I.; Rojik, P.; Kopacková, V.; Zelenkova, K.; Misurec, J.; Bourguignon, A.; Chevrel, S.; Ehrler, C.; Fisher, C.; Hanus, J.; Shkolnisky, Y.; Ben Dor, E.

2011-11-01

Two HyMap images acquired over the same lignite open-pit mining site in Sokolov, Czech Republic, during the summers of 2009 and 2010 (12 months apart), were investigated in this study. The site selected for this research is one of three test sites (the others being in South Africa and Kyrgyzstan) within the framework of the EO-MINERS FP7 Project (http://www.eo-miners.eu). The goal of EO-MINERS is to "integrate new and existing Earth Observation tools to improve best practice in mining activities and to reduce the mining related environmental and societal footprint". Accordingly, the main objective of the current study was to develop hyperspectral-based means for the detection of small spectral changes and to relate these changes to possible degradation or reclamation indicators of the area under investigation. To ensure significant detection of small spectral changes, the temporal domain was investigated along with careful generation of reflectance information. Thus, intensive spectroradiometric ground measurements were carried out to ensure calibration and validation aspects during both overflights. The performance of these corrections was assessed using the Quality Indicators setup developed under a different FP7 project-EUFAR (http://www.eufar.net), which helped select the highest quality data for further work. This approach allows direct distinction of the real information from noise. The reflectance images were used as input for the application of spectral-based change-detection algorithms and indices to account for small and reliable changes. The related algorithms were then developed and applied on a pixel-by-pixel basis to map spectral changes over the space of a year. Using field spectroscopy and ground truth measurements on both overpass dates, it was possible to explain the results and allocate spatial kinetic processes of the environmental changes during the time elapsed between the flights. It was found, for instance, that significant spectral changes are capable of revealing mineral processes, vegetation status and soil formation long before these are apparent to the naked eye. Further study is being conducted under the above initiative to extend this approach to other mining areas worldwide and to improve the robustness of the developed algorithm.

Geospatial Image Mining For Nuclear Proliferation Detection: Challenges and New Opportunities

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

Vatsavai, Raju; Bhaduri, Budhendra L; Cheriyadat, Anil M

2010-01-01

With increasing understanding and availability of nuclear technologies, and increasing persuasion of nuclear technologies by several new countries, it is increasingly becoming important to monitor the nuclear proliferation activities. There is a great need for developing technologies to automatically or semi-automatically detect nuclear proliferation activities using remote sensing. Images acquired from earth observation satellites is an important source of information in detecting proliferation activities. High-resolution remote sensing images are highly useful in verifying the correctness, as well as completeness of any nuclear program. DOE national laboratories are interested in detecting nuclear proliferation by developing advanced geospatial image mining algorithms. Inmore » this paper we describe the current understanding of geospatial image mining techniques and enumerate key gaps and identify future research needs in the context of nuclear proliferation.« less

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

PubMed Central

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

Flight State Information Inference with Application to Helicopter Cockpit Video Data Analysis Using Data Mining Techniques

NASA Astrophysics Data System (ADS)

Shin, Sanghyun

The National Transportation Safety Board (NTSB) has recently emphasized the importance of analyzing flight data as one of the most effective methods to improve eciency and safety of helicopter operations. By analyzing flight data with Flight Data Monitoring (FDM) programs, the safety and performance of helicopter operations can be evaluated and improved. In spite of the NTSB's effort, the safety of helicopter operations has not improved at the same rate as the safety of worldwide airlines, and the accident rate of helicopters continues to be much higher than that of fixed-wing aircraft. One of the main reasons is that the participation rates of the rotorcraft industry in the FDM programs are low due to the high costs of the Flight Data Recorder (FDR), the need of a special readout device to decode the FDR, anxiety of punitive action, etc. Since a video camera is easily installed, accessible, and inexpensively maintained, cockpit video data could complement the FDR in the presence of the FDR or possibly replace the role of the FDR in the absence of the FDR. Cockpit video data is composed of image and audio data: image data contains outside views through cockpit windows and activities on the flight instrument panels, whereas audio data contains sounds of the alarms within the cockpit. The goal of this research is to develop, test, and demonstrate a cockpit video data analysis algorithm based on data mining and signal processing techniques that can help better understand situations in the cockpit and the state of a helicopter by efficiently and accurately inferring the useful flight information from cockpit video data. Image processing algorithms based on data mining techniques are proposed to estimate a helicopter's attitude such as the bank and pitch angles, identify indicators from a flight instrument panel, and read the gauges and the numbers in the analogue gauge indicators and digital displays from cockpit image data. In addition, an audio processing algorithm based on signal processing and abrupt change detection techniques is proposed to identify types of warning alarms and to detect the occurrence times of individual alarms from cockpit audio data. Those proposed algorithms are then successfully applied to simulated and real helicopter cockpit video data to demonstrate and validate their performance.

Study on multispectral imaging detection and recognition

NASA Astrophysics Data System (ADS)

Jun, Wang; Na, Ding; Gao, Jiaobo; Yu, Hu; Jun, Wu; Li, Junna; Zheng, Yawei; Fei, Gao; Sun, Kefeng

2009-07-01

Multispectral imaging detecting technology use target radiation character in spectral spatial distribution and relation between spectral and image to detect target and remote sensing measure. Its speciality is multi channel, narrow bandwidth, large amount of information, high accuracy. The ability of detecting target in environment of clutter, camouflage, concealment and beguilement is improved. At present, spectral imaging technology in the range of multispectral and hyperspectral develop greatly. The multispectral imaging equipment of unmanned aerial vehicle can be used in mine detection, information, surveillance and reconnaissance. Spectral imaging spectrometer operating in MWIR and LWIR has already been applied in the field of remote sensing and military in the advanced country. The paper presents the technology of multispectral imaging. It can enhance the reflectance, scatter and radiation character of the artificial targets among nature background. The targets among complex background and camouflage/stealth targets can be effectively identified. The experiment results and the data of spectral imaging is obtained.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Object-graphs for context-aware visual category discovery.

PubMed

Lee, Yong Jae; Grauman, Kristen

2012-02-01

How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

Better Pictures in a Snap

NASA Technical Reports Server (NTRS)

2002-01-01

Retinex Imaging Processing, winner of NASA's 1999 Space Act Award, is commercially available through TruView Imaging Company. With this technology, amateur photographers use their personal computers to improve the brightness, scene contrast, detail, and overall sharpness of images with increased ease. The process was originally developed for remote sensing of the Earth by researchers at Langley Research Center and Science and Technology Corporation (STC). It automatically enhances a digital image in terms of dynamic range compression, color independence from the spectral distribution of the scene illuminant, and color/lightness rendition. As a result, the enhanced digital image is much closer to the scene perceived by the human visual system, under all kinds and levels of lighting variations. TruView believes there are other applications for the software in medical imaging, forensics, security, recognizance, mining, assembly, and other industrial areas.

Assessing post-industrial land cover change at the Pine Point Mine, NWT, Canada using multi-temporal Landsat analysis and landscape metrics.

PubMed

LeClerc, Emma; Wiersma, Yolanda F

2017-04-01

This study investigates land cover change near the abandoned Pine Point Mine in Canada's Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine's closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.

Capturing pre-failure signs of slope instability using multi-temporal interferometry and Sentinel-1 data

NASA Astrophysics Data System (ADS)

Wasowski, Janusz; Bovenga, Fabio; Nitti, Davide Oscar; Tijani, Khalid; Morea, Alberto; Nutricato, Raffaele; Chiaradia, Maria Teresa

2017-04-01

The shorter repeat cycle (6 days since October 2016) and regularity of acquisitions of Sentinel-1A/B with respect to earlier European Space Agency (ESA) satellites with C-band sensors (ERS1/2, ENVISAT) represent the key advantages for the research-oriented and practical applications of multi-temporal interferometry (MTI). The applicability of the Interferometric Wide Swath acquisition mode of Sentinel-1 (images covering a 250 km swath on the ground) to regional scale slope instability detection through MTI has already been demonstrated, e.g., via studies of landslide-prone areas in Italy. Here we focus on the potential of Sentinel-1 data for local (site-specific), MTI-based monitoring and capturing pre-failure signs of slope instability, by exploiting the Persistent and Distributed Scatterers processing capability of the SPINUA algorithm. In particular, we present an example of a retrospective study of a large (over 2 km long) landslide, which took place in 2016 in an active open-cast coal mine in central Europe. This seemingly sudden failure caused destruction of the mining equipment, blocked the mining operations thereby resulting in significant economic losses. For the study, we exploited over 60 Sentinel-1A/B images acquired since November 2014. The MTI results furnished a valuable overview of the ground instability/stability conditions within and around the active mine, even though considerable spatial gaps in information were encountered due to surface disturbance by mining operations. Significantly, the ground surface displacement time series revealed that the 2016 slope failure was preceded by very slow (generally 1-3 cm/yr) creep-like deformations, already present in 2014. The MTI results also indicated that the slope experienced a phase of accelerated movement several weeks prior to the landslide event. Furthermore, the spatio-temporal analysis of interferometric coherence changes in the unstable area (mapped on Sentinel-2 Bottom Of Atmosphere reflectance images processed by using the ESA Sen2Cor processor), indicated a sharp coherence loss in the last few weeks before the slope collapse. The availability of more frequent measurements represents a key improvement for MTI-based ground surface displacement monitoring and this will better support research on slope destabilization processes over time and, ultimately, on slope failure forecasting. Acknowledgments We thank ESA for Sentinel-1 & Sentinel-2 images.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

Mining Very High Resolution INSAR Data Based On Complex-GMRF Cues And Relevance Feedback

NASA Astrophysics Data System (ADS)

Singh, Jagmal; Popescu, Anca; Soccorsi, Matteo; Datcu, Mihai

2012-01-01

With the increase in number of remote sensing satellites, the number of image-data scenes in our repositories is also increasing and a large quantity of these scenes are never received and used. Thus automatic retrieval of de- sired image-data using query by image content to fully utilize the huge repository volume is becoming of great interest. Generally different users are interested in scenes containing different kind of objects and structures. So its important to analyze all the image information mining (IIM) methods so that its easier for user to select a method depending upon his/her requirement. We concentrate our study only on high-resolution SAR images and we propose to use InSAR observations instead of only one single look complex (SLC) images for mining scenes containing coherent objects such as high-rise buildings. However in case of objects with less coherence like areas with vegetation cover, SLC images exhibits better performance. We demonstrate IIM performance comparison using complex-Gauss Markov Random Fields as texture descriptor for image patches and SVM relevance- feedback.

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

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

PubMed

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

Mineral Mapping with Imaging Spectroscopy: The Ray Mine, AZ

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Vance, J. Sam; Livo, K. Eric; Green, Robert O.

1998-01-01

Mineral maps generated for the Ray Mine, Arizona were analyzed to determine if imaging spectroscopy can provide accurate information for environmental management of active and abandoned mine regions. The Ray Mine, owned by the ASARCO Corporation, covers an area of 5700 acres and is situated in Pinal County, Arizona about 70 miles north of Tucson near Hayden, Arizona. This open-pit mine has been a major source of copper since 1911, producing an estimated 4.5 million tons of copper since its inception. Until 1955 mining was accomplished by underground block caving and shrinkage stope methods. (excavation by working in stepped series usually employed in a vertical or steeply inclined orebody) In 1955, the mine was completely converted to open pit method mining with the bulk of the production from sulfide ore using recovery by concentrating and smelting. Beginning in 1969 a significant production contribution has been from the leaching and solvent extraction-electrowinnowing method of silicate and oxide ores. Published reserves in the deposit as of 1992 are 1.1 billion tons at 0.6 percent copper. The Environmental Protection Agency, in conjunction with ASARCO, and NASA/JPL obtained AVIRIS data over the mine in 1997 as part of the EPA Advanced Measurement Initiative (AMI) (Tom Mace, Principal Investigator). This AVIRIS data set is being used to compare and contrast the accuracy and environmental monitoring capabilities of remote sensing technologies: visible-near-IR imaging spectroscopy, multispectral visible and, near-IR sensors, thermal instruments, and radar platforms. The goal of this effort is to determine if these various technologies provide useful information for envirorunental management of active and abandoned mine sites in the arid western United States. This paper focuses on the analysis of AVIRIS data for assessing the impact of the Ray Mine on Mineral Creek. Mineral Creek flows to the Gila River. This paper discusses our preliminary AVIRIS mineral mapping and environmental findings.

New public dataset for spotting patterns in medieval document images

NASA Astrophysics Data System (ADS)

En, Sovann; Nicolas, Stéphane; Petitjean, Caroline; Jurie, Frédéric; Heutte, Laurent

2017-01-01

With advances in technology, a large part of our cultural heritage is becoming digitally available. In particular, in the field of historical document image analysis, there is now a growing need for indexing and data mining tools, thus allowing us to spot and retrieve the occurrences of an object of interest, called a pattern, in a large database of document images. Patterns may present some variability in terms of color, shape, or context, making the spotting of patterns a challenging task. Pattern spotting is a relatively new field of research, still hampered by the lack of available annotated resources. We present a new publicly available dataset named DocExplore dedicated to spotting patterns in historical document images. The dataset contains 1500 images and 1464 queries, and allows the evaluation of two tasks: image retrieval and pattern localization. A standardized benchmark protocol along with ad hoc metrics is provided for a fair comparison of the submitted approaches. We also provide some first results obtained with our baseline system on this new dataset, which show that there is room for improvement and that should encourage researchers of the document image analysis community to design new systems and submit improved results.

Segmenting Images for a Better Diagnosis

NASA Technical Reports Server (NTRS)

2004-01-01

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Detection of buried objects by fusing dual-band infrared images

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

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

1993-11-01

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

Intelligent Scheduling for Underground Mobile Mining Equipment.

PubMed

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

2015-01-01

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

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

Using remote sensing imagery to monitoring sea surface pollution cause by abandoned gold-copper mine

NASA Astrophysics Data System (ADS)

Kao, H. M.; Ren, H.; Lee, Y. T.

2010-08-01

The Chinkuashih Benshen mine was the largest gold-copper mine in Taiwan before the owner had abandoned the mine in 1987. However, even the mine had been closed, the mineral still interacts with rain and underground water and flowed into the sea. The polluted sea surface had appeared yellow, green and even white color, and the pollutants had carried by the coast current. In this study, we used the optical satellite images to monitoring the sea surface. Several image processing algorithms are employed especial the subpixel technique and linear mixture model to estimate the concentration of pollutants. The change detection approach is also applied to track them. We also conduct the chemical analysis of the polluted water to provide the ground truth validation. By the correlation analysis between the satellite observation and the ground truth chemical analysis, an effective approach to monitoring water pollution could be established.

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…

Using Helicopter Electromagnetic Surveys to Identify Potential Hazards at Mine Waste Impoundments

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

Hammack, R.W.

2008-01-01

In July 2003, helicopter electromagnetic surveys were conducted at 14 coal waste impoundments in southern West Virginia. The purpose of the surveys was to detect conditions that could lead to impoundment failure either by structural failure of the embankment or by the flooding of adjacent or underlying mine works. Specifically, the surveys attempted to: 1) identify saturated zones within the mine waste, 2) delineate filtrate flow paths through the embankment or into adjacent strata and receiving streams, and 3) identify flooded mine workings underlying or adjacent to the waste impoundment. Data from the helicopter surveys were processed to generate conductivity/depthmore » images. Conductivity/depth images were then spatially linked to georeferenced air photos or topographic maps for interpretation. Conductivity/depth images were found to provide a snapshot of the hydrologic conditions that exist within the impoundment. This information can be used to predict potential areas of failure within the embankment because of its ability to image the phreatic zone. Also, the electromagnetic survey can identify areas of unconsolidated slurry in the decant basin and beneath the embankment. Although shallow, flooded mineworks beneath the impoundment were identified by this survey, it cannot be assumed that electromagnetic surveys can detect all underlying mines. A preliminary evaluation of the data implies that helicopter electromagnetic surveys can provide a better understanding of the phreatic zone than the piezometer arrays that are typically used.« less

Hyperspectral analysis for qualitative and quantitative features related to acid mine drainage at a remediated open-pit mine

NASA Astrophysics Data System (ADS)

Davies, G.; Calvin, W. M.

2015-12-01

The exposure of pyrite to oxygen and water in mine waste environments is known to generate acidity and the accumulation of secondary iron minerals. Sulfates and secondary iron minerals associated with acid mine drainage (AMD) exhibit diverse spectral properties in the ultraviolet, visible and near-infrared regions of the electromagnetic spectrum. The use of hyperspectral imagery for identification of AMD mineralogy and contamination has been well studied. Fewer studies have examined the impacts of hydrologic variations on mapping AMD or the unique spectral signatures of mine waters. Open-pit mine lakes are an additional environmental hazard which have not been widely studied using imaging spectroscopy. A better understanding of AMD variation related to climate fluctuations and the spectral signatures of contaminated surface waters will aid future assessments of environmental contamination. This study examined the ability of multi-season airborne hyperspectral data to identify the geochemical evolution of substances and contaminant patterns at the Leviathan Mine Superfund site. The mine is located 24 miles southeast of Lake Tahoe and contains remnant tailings piles and several AMD collection ponds. The objectives were to 1) distinguish temporal changes in mineralogy at a the remediated open-pit sulfur mine, 2) identify the absorption features of mine affected waters, and 3) quantitatively link water spectra to known dissolved iron concentrations. Images from NASA's AVIRIS instrument were collected in the spring, summer, and fall seasons for two consecutive years at Leviathan (HyspIRI campaign). Images had a spatial resolution of 15 meters at nadir. Ground-based surveys using the ASD FieldSpecPro spectrometer and laboratory spectral and chemical analysis complemented the remote sensing data. Temporal changes in surface mineralogy were difficult to distinguish. However, seasonal changes in pond water quality were identified. Dissolved ferric iron and chlorophyll-a concentrations were determined to be the major influences on pond water spectral variation.

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

NASA Astrophysics Data System (ADS)

Kadioglu, Selma; Kagan Kadioglu, Yusuf

2014-05-01

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

Underwater electro-optical system for mine identification

NASA Astrophysics Data System (ADS)

Strand, Michael P.

1995-06-01

The Electro-Optic Identification (EOID) Sensors project is developing a Laser Visual Iidentification Sensor (LVIS) for identification of proud, partially buried, and moored mines in shallow water/very shallow water. LVIS will be deployed in small diameter underwater vehicles, including unmanned underwater vehicles (UUVs). Since the mission is mine identification, LVIS must: a) deliver high quality images in turbid coastal waters, while b) being compatible with the size and power constraints imposed by the intended deployment platforms. This project is sponsored by the Office of Naval Research, as a part of the AOA Mine Reconnaissance/Hunter program. High quality images which retain target detail and contrast are required for mine identification. LVIS will be designed to produce images of minelike contacts (MLC) of sufficient quality to allow identification while operating in turbid coastal waters from a small diameter UUV. Technology goals for the first generation LVIS are a) identification range up to 40 feet for proud, partially buried, and moored MLCs under coastal water conditions; b) day/night operation from a UUV operating at speeds up to 4 knots; c) power consumption less than 500 watts, with 275 watts being typical; and d) packaged within a 32-inch long portion of a 21-inch diameter vehicle section.

Development of a data mining and imaging informatics display tool for a multiple sclerosis e-folder system

NASA Astrophysics Data System (ADS)

Liu, Margaret; Loo, Jerry; Ma, Kevin; Liu, Brent

2011-03-01

Multiple sclerosis (MS) is a debilitating autoimmune disease of the central nervous system that damages axonal pathways through inflammation and demyelination. In order to address the need for a centralized application to manage and study MS patients, the MS e-Folder - a web-based, disease-specific electronic medical record system - was developed. The e-Folder has a PHP and MySQL based graphical user interface (GUI) that can serve as both a tool for clinician decision support and a data mining tool for researchers. This web-based GUI gives the e-Folder a user friendly interface that can be securely accessed through the internet and requires minimal software installation on the client side. The e-Folder GUI displays and queries patient medical records--including demographic data, social history, past medical history, and past MS history. In addition, DICOM format imaging data, and computer aided detection (CAD) results from a lesion load algorithm are also displayed. The GUI interface is dynamic and allows manipulation of the DICOM images, such as zoom, pan, and scrolling, and the ability to rotate 3D images. Given the complexity of clinical management and the need to bolster research in MS, the MS e-Folder system will improve patient care and provide MS researchers with a function-rich patient data hub.

The exploration and prevention of mine water invasion in Feicheng area based on RS

NASA Astrophysics Data System (ADS)

Zheng, Yong-Guo; Wang, Ping; Ting, He

2004-10-01

Recently, when the ninth and tenth were mined in Feiching city mining area, several mine wells occurred on water invasion. Based on systematic interpretation of TMimages in Fei Cheng mining area, authors find that there are five zones of NS trending lineaments, which nearly distribute in radial in TM images. Image processing can be divided into three types, they are spectrum enhancement, spatial filtering and data fusion, the useful methods in this area are auto-adaptive enhancement, density slicing and K-L transform. With ninth and tenth seam coals mined, three mines of east area have broken out serious accidents of water. Statistical materials and the test of water quality drawing off five limestone indicates water-yielding zone near NS, NNE, and NW trending faults, or near intersection point of its and others. In order to solve the problem, using remote sensing and other techniques, we try to find some influential factors on mine flow. Further analyses, such as, the exploration of geology on earth, and microcosmic from rock slice, the authors find that there are some reasons which lead to water invasion such as geological structure, karsts, index and so on, in which the main reason might be north-south deep fracture which is the pathway of well water's distribution, migration and recharge of mine water. There being more complicate geologic structure in the west of mine area, at last, with RS authors point out important zone of mine water invasion which the prevention-control of hazards from mine water and some measures to avoid water blast in future.

A Study on regeneration cases with industrial Heritage in mining areas of Korea

NASA Astrophysics Data System (ADS)

Cho, Seungyeoun; Ji, Sangwoo; Yim, Giljae

2017-04-01

The mining areas have to face urban decline problem in population and aging after its closing. Many mines were shut down due to changes in industrial structure through 20 century. Central and local governments has been trying to solve urban decline of abandoned mine areas by enacting special acts or introducing support programs for decades. In the year of 1995, South Korean government also enacted "Special act on the assistance to the development of abandoned mine areas" to promote the economy of abandoned mine areas that is depressed following the decline of the coal industry and to help balanced regional development and to improve the living standard of the residents in such abandoned mine areas. Local authorities has been trying to revitalize the regional economy by attracting tourism industry under the financial support and deregulation by this special law. With this background, this study analysis 13 regeneration cases which are utilizing the industrial heritage of the abandoned area in S. Korea. Despite the importance of mining, negative images of abandon mine have been engraved due to environmental destruction. Most of abandoned mines were left without any action since its closing. Early stage of abandoned mine area regeneration, such as Sabuk, Munkyong, are focusing on adjacent land not on abandoned mine. Abandoned mines were restored its original state and theme park including hotels, casinos and other tourist facilities were developed on adjacent land. Eco-trails on some granite caves such as Jungsun were opened to the public as natural resources not industrial heritage. The industrial heritage was very restricted to making museums about history of mining industry. However, there has been a significant change in perception toward reusing industrial heritage for urban regeneration in recent years. From the viewpoint of urban regeneration, abandon mine areas and its facilities are receiving attention as important regional assets as industrial heritage to build vibrant cities. The recent urban regeneration projects in abandoned mine areas, such as Pocheon, Kwangmyong and Anyang, are utilizing mining facilities as industrial heritage more actively. They introduced eco-friendly restoration method and made environmental parks or experience centers on mining areas themselves. In conclusion, urban regenerations of abandoned mine areas has been changed from tourist development in neighbouring areas to eco-friendly regeneration in abandoned mine areas. However, there are still some constraints for eco-friendly regeneration. The mine operators have to restore abandoned mine areas to the original state after closing under the current law, "Mining damage prevention and restoration act". Thus lots of abandoned mine areas were left undeveloped or changed to forest. For promoting utilization of mine facilities as industrial heritage, the law have to allow reuse its infrastructure such as loads and subsidiary facilities for urban regeneration.

Modeling of information on the impact of mining exploitation on bridge objects in BIM

NASA Astrophysics Data System (ADS)

Bętkowski, Piotr

2018-04-01

The article discusses the advantages of BIM (Building Information Modeling) technology in the management of bridge infrastructure on mining areas. The article shows the problems with information flow in the case of bridge objects located on mining areas and the advantages of proper information management, e.g. the possibility of automatic monitoring of structures, improvement of safety, optimization of maintenance activities, cost reduction of damage removal and preventive actions, improvement of atmosphere for mining exploitation, improvement of the relationship between the manager of the bridge and the mine. Traditional model of managing bridge objects on mining areas has many disadvantages, which are discussed in this article. These disadvantages include among others: duplication of information about the object, lack of correlation in investments due to lack of information flow between bridge manager and mine, limited assessment possibilities of damage propagation on technical condition and construction resistance to mining influences.

Application of EREP imagery to fracture-related mine safety hazards and environmental problems in mining. [Indiana

NASA Technical Reports Server (NTRS)

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

1974-01-01

The author has identified the following significant results. All Skylab 2 imagery received to date has been analyzed manually and data related to fracture analysis and mined land inventories has been summarized on map-overlays. A comparison of the relative utility of the Skylab image products for fracture detection, soil tone/vegetation contrast mapping, and mined land mapping has been completed. Numerous fracture traces were detected on both color and black and white transparencies. Unique fracture trace data which will contribute to the investigator's mining hazards analysis were noted on the EREP imagery; these data could not be detected on ERTS-1 imagery or high altitude aircraft color infrared photography. Stream segments controlled by fractures or joint systems could be identified in more detail than with ERTS-1 imagery of comparable scale. ERTS-1 mine hazards products will be modified to demonstrate the value of this additional data. Skylab images were used successfully to update a mined land map of Indiana made in 1972. Changes in mined area as small as two acres can be identified. As the Energy Crisis increases the demand for coal, such demonstrations of the application of Skylab data to coal resources will take on new importance.

Mechanical Energy Propagation and Backscattering in Nominally Dry Soil: Imaging Buried Land Mines

NASA Astrophysics Data System (ADS)

Sen, Surajit

2003-04-01

The imaging of shallow buried objects in a complex medium, e.g., nominally dry sand, is an outstanding challenge. Such imaging is of relevance in connection with the detection and subsequent imaging of buried non-metallic anti-personnel land mines and in other applications. It has been shown that gentle mechanical impulses and low frequency sound waves with frequencies roughly between 150-350 Hz or so can penetrate distances of up to a foot in sand. Hence, such signals can potentially be useful in the detection and perhaps in the imaging of shallow buried objects. It is presently unclear whether high frequency signals can be effectively used to image shallow buried objects. Impulses can typically penetrate larger distances into sand and soil. Both impulses and continuous sound waves can be used for imaging shallow buried objects. The talk shall briefly review the state-of-the-art in low frequency sound propagation in soil and shall discuss the current understanding of impulse propagation and backscattering in nominally dry sand beds. It will be argued that impulse based imaging may have the potential to be a simple and fast way to detect and image small non-metallic mines. Research supported by the National Science Foundation Grant No. NSF-CMS 0070055.

Recognizing critical mine spoil health characteristics to design biochars for site improvement to promote stabilizing plant growth

EPA Science Inventory

Biochar can be used as an amendment to remediate metal-contaminated mine spoils for improved site phytostabilization. For successful phytostabilization to occur, biochar amendments must improve mine spoil health with respect to plant rooting plus uptake of water and nutrients. ...

Using 3D Reflection Seismics for Deep Platinum Mine Planning and Risk Mitigation: A Case Study from the Bushveld Complex, South Africa

NASA Astrophysics Data System (ADS)

Scheiber-Enslin, S. E.; Manzi, M. S.; Webb, S. J.

2017-12-01

Loss-of-ground in mining is a common problem. Using the integration of high resolution aeromagnetic and 3D reflection seismic data to delineate the causative geological features allows for more efficient mine planning and risk reduction. High resolution data from Impala Platinum mine in the western Bushveld Complex are used to image potholes, iron-rich ultramafic pegmatoids (IRUPs), faults, dykes and diapirs that may impact the economic horizons (UG2). Imaging of these structures was previously limited to outcrop, both on surface and underground, as well as 2D seismic data. These high resolution seismic data are able to resolve faults with throws as small as 10 m. A diapir is imaged in the southwest of the study area with a diameter of approximately 6 km. The diapir has a depth extend of around 4 km below the UG2 horizon and displaces the horizon by 350 m. It has been suggested that topographic highs in the Transvaal Supergroup basement initiate the formation of these diapirs as new magma is injected into the chamber. The origin of the diapir within the layered basement rocks, and disruption of layering within the complex is visible on the seismic section. In the north of the study area a large region of slumping or several merged potholes is identified that is up to 2.5 km in length, with up to 700 m of vertical displacement. Ductile deformation that formed the potholes is imaged on the seismic section, with the UG2 cutting down into the footwall. However, brittle deformation of the UG2 is also imaged with faulting at the edges of the regions of slumping. The edges of these slump regions are also characterised by the emplacement of iron-rich ultramafic pegmatoids (IRUPs), which show up as regions of diffuse reflectivity on the seismic data and magnetic highs. The proximity of these faults and IRUPs to the edges of the slump structure brings in to question whether they contribute to pothole formation. The diapir and slump structure displaces the economic UG2 horizon at the mining levels and cause faulting of the horizon. Imaging of these structures could be used for future mining planning and design to assess and mitigate the risks posed by these features during mining activities.

Intelligent Scheduling for Underground Mobile Mining Equipment

PubMed Central

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

2015-01-01

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

Knowledge Driven Image Mining with Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Oza, Nikunj

2004-01-01

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels; which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper, we present the theory of Mercer Kernels, describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Knowledge Driven Image Mining with Mixture Density Mercer Kernals

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Oza, Nikunj

2004-01-01

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper we present the theory of Mercer Kernels; describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

The future of European mining: What should our mining industry learn from the Skouries and Rosia Montana community gold conflicts

NASA Astrophysics Data System (ADS)

Hardy, Liam; Heller, Shaun; Faltyn, Rowan; Stefanaki, Anna; Economidou, Romina; Savin, Irina; Hood, Leo; Conway, Christopher

2017-04-01

The popular image of mining portrayed by media and by a majority of public opinion is a dominantly negative one. From worker's rights to environmental damages, disasters such as the Copiapó mine collapse (Chile), the acid mine drainage at Lousal (Portugal) and the Pb contamination of waters around the Tyndrum mines (Scotland) overshadow initiatives like the ICMM. Some companies receive little praise despite creating active community education and investment projects, while others simply build higher barbed wire fences and attempt to weather the protests, budgeting them into mine life assessments. This image problem, combined with the decentralised political segregation of Europe and the increased power of grass-roots protest initiatives (such as Antigold in Greece), has resulted in mining companies joining a long list of industries effected by the 'auto-protest' reaction in face of development, regardless of potential regional and national benefits, there is a pre-existing lack of trust in corporate and government powers to protect community interests. The poor management of existing licences is thus becoming a significant danger to future operations and the wider industry. Here we report on the Rosia Montana dispute (Romania) and the ongoing Skouries conflict (Greece). We then discuss how the European mining industry may need to significantly adapt its exploration and community engagement strategies to avoid future conflicts and, present a recent example of how effective suitably organised community engagement projects can be for local mining initiatives from Southern Portugal.

Buried mine detection using fractal geometry analysis to the LWIR successive line scan data image

NASA Astrophysics Data System (ADS)

Araki, Kan

2012-06-01

We have engaged in research on buried mine/IED detection by remote sensing method using LWIR camera. A IR image of a ground, containing buried objects can be assumed as a superimposed pattern including thermal scattering which may depend on the ground surface roughness, vegetation canopy, and effect of the sun light, and radiation due to various heat interaction caused by differences in specific heat, size, and buried depth of the objects and local temperature of their surrounding environment. In this cumbersome environment, we introduce fractal geometry for analyzing from an IR image. Clutter patterns due to these complex elements have oftentimes low ordered fractal dimension of Hausdorff Dimension. On the other hand, the target patterns have its tendency of obtaining higher ordered fractal dimension in terms of Information Dimension. Random Shuffle Surrogate method or Fourier Transform Surrogate method is used to evaluate fractional statistics by applying shuffle of time sequence data or phase of spectrum. Fractal interpolation to each line scan was also applied to improve the signal processing performance in order to evade zero division and enhance information of data. Some results of target extraction by using relationship between low and high ordered fractal dimension are to be presented.

Coastal Benthic Optical Properties Fluorescence Imaging Laser Line Scan Sensor

DTIC Science & Technology

2001-09-30

Acquisition of Electro - Optic Identification (EOID) sensors for MLC identification is currently underway to support both Air Mine Counter-Measures (AMCM) and Surface Mine Counter-Measures (SMCM) operations.

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Design of material management system of mining group based on Hadoop

NASA Astrophysics Data System (ADS)

Xia, Zhiyuan; Tan, Zhuoying; Qi, Kuan; Li, Wen

2018-01-01

Under the background of persistent slowdown in mining market at present, improving the management level in mining group has become the key link to improve the economic benefit of the mine. According to the practical material management in mining group, three core components of Hadoop are applied: distributed file system HDFS, distributed computing framework Map/Reduce and distributed database HBase. Material management system of mining group based on Hadoop is constructed with the three core components of Hadoop and SSH framework technology. This system was found to strengthen collaboration between mining group and affiliated companies, and then the problems such as inefficient management, server pressure, hardware equipment performance deficiencies that exist in traditional mining material-management system are solved, and then mining group materials management is optimized, the cost of mining management is saved, the enterprise profit is increased.

78 FR 79010 - Criteria to Certify Coal Mine Rescue Teams

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-27

... to Certify Coal Mine Rescue Teams AGENCY: Mine Safety and Health Administration, Labor. ACTION... updated the coal mine rescue team certification criteria. The Mine Improvement and New Emergency Response... mine operator to certify the qualifications of a coal mine rescue team is that team members are...

Comparative performance between compressed and uncompressed airborne imagery

NASA Astrophysics Data System (ADS)

Phan, Chung; Rupp, Ronald; Agarwal, Sanjeev; Trang, Anh; Nair, Sumesh

2008-04-01

The US Army's RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD), Countermine Division is evaluating the compressibility of airborne multi-spectral imagery for mine and minefield detection application. Of particular interest is to assess the highest image data compression rate that can be afforded without the loss of image quality for war fighters in the loop and performance of near real time mine detection algorithm. The JPEG-2000 compression standard is used to perform data compression. Both lossless and lossy compressions are considered. A multi-spectral anomaly detector such as RX (Reed & Xiaoli), which is widely used as a core algorithm baseline in airborne mine and minefield detection on different mine types, minefields, and terrains to identify potential individual targets, is used to compare the mine detection performance. This paper presents the compression scheme and compares detection performance results between compressed and uncompressed imagery for various level of compressions. The compression efficiency is evaluated and its dependence upon different backgrounds and other factors are documented and presented using multi-spectral data.

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

Earth Observations taken by the Expedition 13 crew

NASA Image and Video Library

2006-05-06

ISS013-E-14843 (6 May 2006) --- Calcite Quarry, Michigan is featured in this image photographed by an Expedition 13 crewmember on the International Space Station. While the Great Lakes region of North America is well known for its importance to shipping between the United States, Canada, and the Atlantic Ocean, it is also the location of an impressive structure in the continent's bedrock -- the Michigan Basin, NASA scientists point out. The Basin looks much like a large bull's-eye defined by the arrangement of exposed rock layers, which all tilt inwards towards the center forming a huge bowl-shaped structure. While this "bowl" is not readily apparent while on the ground, detailed mapping of the rock units on a regional scale revealed the structure to geologists. The outer layers of the Basin include thick deposits of carbonates (limestone and dolomite). These carbonate rocks are mined throughout the Great Lakes region using large open-pit mines. The largest carbonate mine in the world, Calcite Quarry, is depicted in this image. The mine has been active for over 85 years; the worked area (grey region in image center) measures approximately 7 kilometers long by 4 kilometers wide, and is crossed by several access roads (white) into various areas of the mine.

Naval sensor data database (NSDD)

NASA Astrophysics Data System (ADS)

Robertson, Candace J.; Tubridy, Lisa H.

1999-08-01

The Naval Sensor Data database (NSDD) is a multi-year effort to archive, catalogue, and disseminate data from all types of sensors to the mine warfare, signal and image processing, and sensor development communities. The purpose is to improve and accelerate research and technology. Providing performers with the data required to develop and validate improvements in hardware, simulation, and processing will foster advances in sensor and system performance. The NSDD will provide a centralized source of sensor data in its associated ground truth, which will support an improved understanding will be benefited in the areas of signal processing, computer-aided detection and classification, data compression, data fusion, and geo-referencing, as well as sensor and sensor system design.

Data-Mining Technologies for Diabetes: A Systematic Review

PubMed Central

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

2011-01-01

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

Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.

PubMed

Pan, Shaoming; Li, Yongkai; Xu, Zhengquan; Chong, Yanwen

2015-01-01

Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

Lithium Mining, Nevada

NASA Image and Video Library

2014-08-05

This image from NASA Terra spacecraft shows the once-abandoned mining town of Silver Peak, Nevada, which began to thrive again when Foote Mineral Company began extracting lithium from brine below the floor of Clayton Valley in 1966.

Ontology-guided organ detection to retrieve web images of disease manifestation: towards the construction of a consumer-based health image library.

PubMed

Chen, Yang; Ren, Xiaofeng; Zhang, Guo-Qiang; Xu, Rong

2013-01-01

Visual information is a crucial aspect of medical knowledge. Building a comprehensive medical image base, in the spirit of the Unified Medical Language System (UMLS), would greatly benefit patient education and self-care. However, collection and annotation of such a large-scale image base is challenging. To combine visual object detection techniques with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling effort. As a proof of concept, we first learnt five organ detectors on three detection scales for eyes, ears, lips, hands, and feet. Given a disease, we used information from the UMLS to select affected body parts, ran the pretrained organ detectors on web images, and combined the detection outputs to retrieve disease images. Compared with a supervised image retrieval approach that requires training images for every disease, our ontology-guided approach exploits shared visual information of body parts across diseases. In retrieving 2220 web images of 32 diseases, we reduced manual labeling effort to 15.6% while improving the average precision by 3.9% from 77.7% to 81.6%. For 40.6% of the diseases, we improved the precision by 10%. The results confirm the concept that the web is a feasible source for automatic disease image retrieval for health image database construction. Our approach requires a small amount of manual effort to collect complex disease images, and to annotate them by standard medical ontology terms.

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.

Faster tissue interface analysis from Raman microscopy images using compressed factorisation

NASA Astrophysics Data System (ADS)

Palmer, Andrew D.; Bannerman, Alistair; Grover, Liam; Styles, Iain B.

2013-06-01

The structure of an artificial ligament was examined using Raman microscopy in combination with novel data analysis. Basis approximation and compressed principal component analysis are shown to provide efficient compression of confocal Raman microscopy images, alongside powerful methods for unsupervised analysis. This scheme allows the acceleration of data mining, such as principal component analysis, as they can be performed on the compressed data representation, providing a decrease in the factorisation time of a single image from five minutes to under a second. Using this workflow the interface region between a chemically engineered ligament construct and a bone-mimic anchor was examined. Natural ligament contains a striated interface between the bone and tissue that provides improved mechanical load tolerance, a similar interface was found in the ligament construct.

A group filter algorithm for sea mine detection

NASA Astrophysics Data System (ADS)

Cobb, J. Tory; An, Myoung; Tolimieri, Richard

2005-06-01

Automatic detection of sea mines in coastal regions is a difficult task due to the highly variable sea bottom conditions present in the underwater environment. Detection systems must be able to discriminate objects which vary in size, shape, and orientation from naturally occurring and man-made clutter. Additionally, these automated systems must be computationally efficient to be incorporated into unmanned underwater vehicle (UUV) sensor systems characterized by high sensor data rates and limited processing abilities. Using noncommutative group harmonic analysis, a fast, robust sea mine detection system is created. A family of unitary image transforms associated to noncommutative groups is generated and applied to side scan sonar image files supplied by Naval Surface Warfare Center Panama City (NSWC PC). These transforms project key image features, geometrically defined structures with orientations, and localized spectral information into distinct orthogonal components or feature subspaces of the image. The performance of the detection system is compared against the performance of an independent detection system in terms of probability of detection (Pd) and probability of false alarm (Pfa).

Mega-precovery and data mining of near-Earth asteroids and other Solar System objects

NASA Astrophysics Data System (ADS)

Popescu, M.; Vaduvescu, O.; Char, F.; Curelaru, L.; Euronear Team

2014-07-01

The vast collection of CCD images and photographic plate archives available from the world-wide archives and telescopes is still insufficiently exploited. Within the EURONEAR project we designed two data mining software with the purpose to search very large collections of archives for images which serendipitously include known asteroids or comets in their field, with the main aims to extend the arc and improve the orbits. In this sense, ''Precovery'' (published in 2008, aiming to search all known NEAs in few archives via IMCCE's SkyBoT server) and ''Mega-Precovery'' (published in 2010, querying the IMCCE's Miriade server) were made available to the community via the EURONEAR website (euronear.imcce.fr). Briefly, Mega-Precovery aims to search one or a few known asteroids or comets in a mega-collection including millions of images from some of the largest observatory archives: ESO (15 instruments served by ESO Archive including VLT), NVO (8 instruments served by U.S. NVO Archive), CADC (11 instruments, including HST and Gemini), plus other important instrument archives: SDSS, CFHTLS, INT-WFC, Subaru-SuprimeCam and AAT-WFI, adding together 39 instruments and 4.3 million images (Mar 2014), and our Mega-Archive is growing. Here we present some of the most important results obtained with our data-mining software and some new planned search options of Mega-Precovery. Particularly, the following capabilities will be added soon: the ING archive (all imaging cameras) will be included and new search options will be made available (such as query by orbital elements and by observations) to be able to target new Solar System objects such as Virtual Impactors, bolides, planetary satellites, TNOs (besides the comets added recently). In order to better characterize the archives, we introduce the ''AOmegaA'' factor (archival etendue) proportional to the AOmega (etendue) and the number of images in an archive. With the aim to enlarge the Mega-Archive database, we invite the observatories (particularly those storing their images online and also those that own plate archives which could be scanned on request) to contact us in order to add their instrument archives (consisting of an ASCII file with telescope pointings in a simple format) to our Mega-Precovery open project. We intend for the future to synchronise our service with the Virtual Observatory.

Weipa, Queensland, Australia

NASA Image and Video Library

2014-08-21

This image from NASA Terra spacecraft shows the world largest bauxite mine found near Weipa, Queensland, Australia. The rich aluminum deposits were first recognized on the end of the Cape York Peninsula in 1955, and mining began in 1960.

Escondida Mine, Chile

NASA Technical Reports Server (NTRS)

2002-01-01

Full resolution visible and near-infrared image (1.4 MB) Full resolution shortwave infrared image (1.6 MB) This Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image covers 30 by 23 km (full images 30 x 37 km) in the Atacama Desert, Chile, and was acquired on April 23, 2000. The Escondida copper, gold, and silver open-pit mine is at an elevation of 3050 m, and began operations in 1990. Current capacity is 127,000 tons/day of ore; in 1999 production totaled 827,000 tons of copper, 150,000 ounces of gold, and 3.53 million ounces of silver. Primary concentrate of the ore is done on-site; the concentrate is then sent to the coast for further processing through a 170 km long, 9-inch pipe. Escondida is related geologically to three porphyry bodies intruded along the Chilean West Fissure Fault System. A high grade supergene cap overlies primary sulfide ore. The top image is a conventional 3-2-1 (near infrared, red, green) RGB composite. The bottom image displays shortwave infrared bands 4-6-8 (1.65um, 2.205um, 2.33um) in RGB, and highlights the different rock types present on the surface, as well as the changes caused by mining. Image courtesy NASA/GSFC/MITI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team

Discovering significant evolution patterns from satellite image time series.

PubMed

Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

2011-12-01

Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Designing biochars for in situ remediation of metal contaminated mine spoils

EPA Science Inventory

Biochar in conjunction with other soil amendments can be used for in situ remediation of metal-contaminated mine spoils for improved site phytostabilization. For successful phytostabilization to occur, biochar must improve mine spoil health with respect to plant rooting plus upt...

Designing biochars for in situ remediation of metal contaminated mine spoils.

EPA Science Inventory

Biochar in conjunction with other soil amendments can be used for in situ remediation of metal-contaminated mine spoils for improved site phytostabilization. For successful phytostabilization to occur, biochar must improve mine spoil health with respect to plant rooting plus upt...

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

Raymond, David W.; Gaither, Katherine N.; Polsky, Yarom

Sandia National Laboratories (Sandia) has a long history in developing compact, mobile, very high-speed drilling systems and this technology could be applied to increasing the rate at which boreholes are drilled during a mine accident response. The present study reviews current technical approaches, primarily based on technology developed under other programs, analyzes mine rescue specific requirements to develop a conceptual mine rescue drilling approach, and finally, proposes development of a phased mine rescue drilling system (MRDS) that accomplishes (1) development of rapid drilling MRDS equipment; (2) structuring improved web communication through the Mine Safety & Health Administration (MSHA) web site;more » (3) development of an improved protocol for employment of existing drilling technology in emergencies; (4) deployment of advanced technologies to complement mine rescue drilling operations during emergency events; and (5) preliminary discussion of potential future technology development of specialized MRDS equipment. This phased approach allows for rapid fielding of a basic system for improved rescue drilling, with the ability to improve the system over time at a reasonable cost.« less

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

Piezoelectric Composite Micromachined Multifrequency Transducers for High-Resolution, High-Contrast Ultrasound Imaging for Improved Prostate Cancer Assessment

DTIC Science & Technology

2016-10-01

abstracts. We have provided basic details in the attached text . Extensive additional data, discussion, and conclusions are included in the attached...are listed in blue, and the following black text details progress towards these tasks. Aim 1) Develop a new type of dual-frequency PC-MUT co...Proceedings of the IEEE International Ultrasonics Symposium, Honolulu, HI, USA, 4–7 December 1990; Volume 2, pp. 799–803. 85. Saitoh, S.; Izumi, M.; Mine

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Pipeline for illumination correction of images for high-throughput microscopy.

PubMed

Singh, S; Bray, M-A; Jones, T R; Carpenter, A E

2014-12-01

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Millennium Open Pit Mine, Alberta, Canada

NASA Image and Video Library

2007-11-26

Near Fort McMurray, Alberta, Canada, on the east bank of the Athabasca River, are found the Steepbank and Millennium open pit mines. These images were acquired by NASA Terra satellite on September 22, 2000 and July 31, 2007.

Remote mineral mapping using AVIRIS data at Summitville, Colorado and the adjacent San Juan Mountains

NASA Technical Reports Server (NTRS)

King, Trude V. V.; Clark, Roger N.; Ager, Cathy; Swayze, Gregg A.

1995-01-01

We have demonstrated the unique utility of imaging spectroscopy in mapping mineral distribution. In the Summitville mining region we have shown that the mine site does not contribute clay minerals to the Alamosa River, but does contribute Fe-bearing minerals. Such minerals have the potential to carry heavy metals. This application illustrates only one specific environmental application of imaging spectroscopy data. For instance, the types of minerals we can map with confidence are those frequently associated with environmental problems related to active and abandoned mine lands. Thus, the potential utility of this technology to the field of environmental science has yet to be fully explored.

Development of computerized stocktaking system in mine surveying for ore mineral volume calculation in covered storehouses

NASA Astrophysics Data System (ADS)

Valdman, V. V.; Gridnev, S. O.

2017-10-01

The article examines into the vital issues of measuring and calculating the raw stock volumes in covered storehouses at mining and processing plants. The authors bring out two state-of-the-art high-technology solutions: 1 - to use the ground-based laser scanning system (the method is reasonably accurate and dependable, but costly and time consuming; it also requires the stoppage of works in the storehouse); 2 - to use the fundamentally new computerized stocktaking system in mine surveying for the ore mineral volume calculation, based on the profile digital images. These images are obtained via vertical projection of the laser plane onto the surface of the stored raw materials.

Study of the crater deformation of the CODELCO/Andina mine using the satellite and ground data

NASA Astrophysics Data System (ADS)

Caverlotti-Silva, M. A.; Arellano-Baeza, A. A.

2011-12-01

The correct monitoring of the subsidence of the craters related to the underground mine exploitation is one of the most important endeavors of the satellite remote sensing. The ASTER and LANDSAT satellite images have been used to study the deformation of the crater of the CODELCO/Andina mine, Valparaiso Region, Chile. The high-resolution satellite images were used to detect changes in the lineament patterns related to the subsidence. These results were compared with the ground deformation extracted from the GPS and topography station networks. It was found that sudden changes in the lineament patterns appear when the ground deformation overcomes a definite threshold.

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.

76 FR 7868 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-11

... Special Emphasis Panel, Small Business: Computational Biology, Image Processing and Data Mining. Date... for Scientific Review Special Emphasis Panel, Quick Trial on Imaging and Image-Guided Intervention...

Data Mining Research with the LSST

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Earth observation taken by the Expedition 11 crew

NASA Image and Video Library

2005-06-25

ISS011-E-09620 (26 June 2005) --- Grasberg Mine, Indonesia is featured in this image photographed by an Expedition 11 crewmember on the International Space Station. Located in the Sudirman Mountains of the Irian Jaya province of Indonesia, the Grasberg complex (also known as the Freeport Mine) is one of the largest gold and copper mining operations in the world. The Sudirman Mountains form the western portion of the Maoke Range that extend across Irian Jaya from west to the east-southeast. According to scientists, these ranges were formed by ongoing collision of the northward-moving Australian and westward-moving Pacific tectonic plates. Intrusion of hot magma into sedimentary rock layers during uplift of the mountains resulted in the formation of copper- and gold-bearing ore bodies. Rich copper ore bodies were discovered in the area in 1936, and the Grasberg gold-bearing ore bodies were discovered in 1988. This image illustrates the approximately 4 kilometers-wide open-pit portion of the mine complex; there are also extensive underground mine workings. Access roads for trucks hauling ore and waste rock are visible along the sides of the pit.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Techniques of Photometry and Astrometry with APASS, Gaia, and Pan-STARRs Results (Abstract)

NASA Astrophysics Data System (ADS)

Green, W.

2017-12-01

(Abstract only) The databases with the APASS DR9, Gaia DR1, and the Pan-STARRs 3pi DR1 data releases are publicly available for use. There is a bit of data-mining involved to download and manage these reference stars. This paper discusses the use of these databases to acquire accurate photometric references as well as techniques for improving results. Images are prepared in the usual way: zero, dark, flat-fields, and WCS solutions with Astrometry.net. Images are then processed with Sextractor to produce an ASCII table of identifying photometric features. The database manages photometics catalogs and images converted to ASCII tables. Scripts convert the files into SQL and assimilate them into database tables. Using SQL techniques, each image star is merged with reference data to produce publishable results. The VYSOS has over 13,000 images of the ONC5 field to process with roughly 100 total fields in the campaign. This paper provides the overview for this daunting task.

Imaging mass spectrometry and genome mining reveal highly antifungal virulence factor of mushroom soft rot pathogen.

PubMed

Graupner, Katharina; Scherlach, Kirstin; Bretschneider, Tom; Lackner, Gerald; Roth, Martin; Gross, Harald; Hertweck, Christian

2012-12-21

Caught in the act: imaging mass spectrometry of a button mushroom infected with the soft rot pathogen Janthinobacterium agaricidamnosum in conjunction with genome mining revealed jagaricin as a highly antifungal virulence factor that is not produced under standard cultivation conditions. The structure of jagaricin was rigorously elucidated by a combination of physicochemical analyses, chemical derivatization, and bioinformatics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

PubMed

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

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…

Impacts of surface gold mining on land use systems in Western Ghana.

PubMed

Schueler, Vivian; Kuemmerle, Tobias; Schröder, Hilmar

2011-07-01

Land use conflicts are becoming increasingly apparent from local to global scales. Surface gold mining is an extreme source of such a conflict, but mining impacts on local livelihoods often remain unclear. Our goal here was to assess land cover change due to gold surface mining in Western Ghana, one of the world's leading gold mining regions, and to study how these changes affected land use systems. We used Landsat satellite images from 1986-2002 to map land cover change and field interviews with farmers to understand the livelihood implications of mining-related land cover change. Our results showed that surface mining resulted in deforestation (58%), a substantial loss of farmland (45%) within mining concessions, and widespread spill-over effects as relocated farmers expand farmland into forests. This points to rapidly eroding livelihood foundations, suggesting that the environmental and social costs of Ghana's gold boom may be much higher than previously thought.

Drakelands Mine, England

NASA Image and Video Library

2015-08-21

The Drakelands Mine (previously known as the Hemerdon Mine) is a historic tungsten and tin mine located northeast of Plymouth, England. Tin and tungsten deposits were discovered in 1867, and the mine operated until 1944. Last year work started to re-open the mine, as it hosts the fourth-largest tungsten and tin deposits in the world. Tungsten has innumerable uses due to its incredible density and high melting temperature. Yet more than 80% of world supply is controlled by China, who has imposed restriction on export of the metal. The image covers an area of 17 by 18.9 km, was acquired June 5, 2013, and is located at 50.4 degrees north, 4 degrees west. http://photojournal.jpl.nasa.gov/catalog/PIA19757

Changing requirements and solutions for unattended ground sensors

NASA Astrophysics Data System (ADS)

Prado, Gervasio; Johnson, Robert

2007-10-01

Unattended Ground Sensors (UGS) were first used to monitor Viet Cong activity along the Ho Chi Minh Trail in the 1960's. In the 1980's, significant improvement in the capabilities of UGS became possible with the development of digital signal processors; this led to their use as fire control devices for smart munitions (for example: the Wide Area Mine) and later to monitor the movements of mobile missile launchers. In these applications, the targets of interest were large military vehicles with strong acoustic, seismic and magnetic signatures. Currently, the requirements imposed by new terrorist threats and illegal border crossings have changed the emphasis to the monitoring of light vehicles and foot traffic. These new requirements have changed the way UGS are used. To improve performance against targets with lower emissions, sensors are used in multi-modal arrangements. Non-imaging sensors (acoustic, seismic, magnetic and passive infrared) are now being used principally as activity sensors to cue imagers and remote cameras. The availability of better imaging technology has made imagers the preferred source of "actionable intelligence". Infrared cameras are now based on un-cooled detector-arrays that have made their application in UGS possible in terms of their cost and power consumption. Visible light imagers are also more sensitive extending their utility well beyond twilight. The imagers are equipped with sophisticated image processing capabilities (image enhancement, moving target detection and tracking, image compression). Various commercial satellite services now provide relatively inexpensive long-range communications and the Internet provides fast worldwide access to the data.

Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data

NASA Astrophysics Data System (ADS)

Gibril, Mohamed Barakat A.; Idrees, Mohammed Oludare; Yao, Kouame; Shafri, Helmi Zulhaidi Mohd

2018-01-01

The growing use of optimization for geographic object-based image analysis and the possibility to derive a wide range of information about the image in textual form makes machine learning (data mining) a versatile tool for information extraction from multiple data sources. This paper presents application of data mining for land-cover classification by fusing SPOT-6, RADARSAT-2, and derived dataset. First, the images and other derived indices (normalized difference vegetation index, normalized difference water index, and soil adjusted vegetation index) were combined and subjected to segmentation process with optimal segmentation parameters obtained using combination of spatial and Taguchi statistical optimization. The image objects, which carry all the attributes of the input datasets, were extracted and related to the target land-cover classes through data mining algorithms (decision tree) for classification. To evaluate the performance, the result was compared with two nonparametric classifiers: support vector machine (SVM) and random forest (RF). Furthermore, the decision tree classification result was evaluated against six unoptimized trials segmented using arbitrary parameter combinations. The result shows that the optimized process produces better land-use land-cover classification with overall classification accuracy of 91.79%, 87.25%, and 88.69% for SVM and RF, respectively, while the results of the six unoptimized classifications yield overall accuracy between 84.44% and 88.08%. Higher accuracy of the optimized data mining classification approach compared to the unoptimized results indicates that the optimization process has significant impact on the classification quality.

Stability Analysis of Railway Subgrade in Mining Area Based on Dinsar

NASA Astrophysics Data System (ADS)

Xu, J.; Hu, J.; Ding, J.

2018-04-01

DInSAR technology have been applied to monitor the mining subsidence and the stability of the railway subgrade. A total of 10 Sentinel-1A images acquired from 2015/9/26 to 2016/2/23 were used in DInSAR analysis. The study mining area is about 13.4 km2. Mining have induced serious land subsidence involve a large area that causing different levels of damages to infrastructures on the land. There is an important railway near the mining area, the DInSAR technology is applied to analyse the subsidence near the railway, which can warn early the possible deformation that may occur during underground mining. The DInSAR results was verified by the field measurement. The results show that the mining did not cause subsidence of railway subgrade and did not affect the stability of railway subgrade.

Proceedings: Fourth Workshop on Mining Scientific Datasets

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

Kamath, C

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

A Review of Mine Rescue Ensembles for Underground Coal Mining in the United States.

PubMed

Kilinc, F Selcen; Monaghan, William D; Powell, Jeffrey B

The mining industry is among the top ten industries nationwide with high occupational injury and fatality rates, and mine rescue response may be considered one of the most hazardous activities in mining operations. In the aftermath of an underground mine fire, explosion or water inundation, specially equipped and trained teams have been sent underground to fight fires, rescue entrapped miners, test atmospheric conditions, investigate the causes of the disaster, or recover the dead. Special personal protective ensembles are used by the team members to improve the protection of rescuers against the hazards of mine rescue and recovery. Personal protective ensembles used by mine rescue teams consist of helmet, cap lamp, hood, gloves, protective clothing, boots, kneepads, facemask, breathing apparatus, belt, and suspenders. While improved technology such as wireless warning and communication systems, lifeline pulleys, and lighted vests have been developed for mine rescuers over the last 100 years, recent research in this area of personal protective ensembles has been minimal due to the trending of reduced exposure of rescue workers. In recent years, the exposure of mine rescue teams to hazardous situations has been changing. However, it is vital that members of the teams have the capability and proper protection to immediately respond to a wide range of hazardous situations. Currently, there are no minimum requirements, best practice documents, or nationally recognized consensus standards for protective clothing used by mine rescue teams in the United States (U.S.). The following review provides a summary of potential issues that can be addressed by rescue teams and industry to improve potential exposures to rescue team members should a disaster situation occur. However, the continued trending in the mining industry toward non-exposure to potential hazards for rescue workers should continue to be the primary goal. To assist in continuing this trend, the mining industry and regulatory agencies have been more restrictive by requiring additional post disaster information regarding atmospheric conditions and other hazards before exposing rescue workers and others in the aftermath of a mine disaster. In light of some of the more recent mine rescuer fatalities such as the Crandall Canyon Mine and Jim Walters Resources in the past years, the direction of reducing exposure is preferred. This review provides a historical perspective on ensembles used during mine rescue operations and summarizes environmental hazards, critical elements of mine rescue ensembles, and key problems with these elements. This study also identifies domains for improved mine rescue ensembles. Furthermore, field observations from several coal mine rescue teams were added to provide the information on the currently used mine rescue ensembles in the U.S.

A Review of Mine Rescue Ensembles for Underground Coal Mining in the United States

PubMed Central

Kilinc, F. Selcen; Monaghan, William D.; Powell, Jeffrey B.

2016-01-01

The mining industry is among the top ten industries nationwide with high occupational injury and fatality rates, and mine rescue response may be considered one of the most hazardous activities in mining operations. In the aftermath of an underground mine fire, explosion or water inundation, specially equipped and trained teams have been sent underground to fight fires, rescue entrapped miners, test atmospheric conditions, investigate the causes of the disaster, or recover the dead. Special personal protective ensembles are used by the team members to improve the protection of rescuers against the hazards of mine rescue and recovery. Personal protective ensembles used by mine rescue teams consist of helmet, cap lamp, hood, gloves, protective clothing, boots, kneepads, facemask, breathing apparatus, belt, and suspenders. While improved technology such as wireless warning and communication systems, lifeline pulleys, and lighted vests have been developed for mine rescuers over the last 100 years, recent research in this area of personal protective ensembles has been minimal due to the trending of reduced exposure of rescue workers. In recent years, the exposure of mine rescue teams to hazardous situations has been changing. However, it is vital that members of the teams have the capability and proper protection to immediately respond to a wide range of hazardous situations. Currently, there are no minimum requirements, best practice documents, or nationally recognized consensus standards for protective clothing used by mine rescue teams in the United States (U.S.). The following review provides a summary of potential issues that can be addressed by rescue teams and industry to improve potential exposures to rescue team members should a disaster situation occur. However, the continued trending in the mining industry toward non-exposure to potential hazards for rescue workers should continue to be the primary goal. To assist in continuing this trend, the mining industry and regulatory agencies have been more restrictive by requiring additional post disaster information regarding atmospheric conditions and other hazards before exposing rescue workers and others in the aftermath of a mine disaster. In light of some of the more recent mine rescuer fatalities such as the Crandall Canyon Mine and Jim Walters Resources in the past years, the direction of reducing exposure is preferred. This review provides a historical perspective on ensembles used during mine rescue operations and summarizes environmental hazards, critical elements of mine rescue ensembles, and key problems with these elements. This study also identifies domains for improved mine rescue ensembles. Furthermore, field observations from several coal mine rescue teams were added to provide the information on the currently used mine rescue ensembles in the U.S. PMID:27065231

Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA

USGS Publications Warehouse

Oliphant, Adam J.; Wynne, R.H.; Zipper, Carl E.; Ford, W. Mark; Donovan, P. F.; Li, Jing

2017-01-01

Invasive plants threaten native plant communities. Surface coal mines in the Appalachian Mountains are among the most disturbed landscapes in North America, but information about land cover characteristics of Appalachian mined lands is lacking. The invasive shrub autumn olive (Elaeagnus umbellata) occurs on these sites and interferes with ecosystem recovery by outcompeting native trees, thus inhibiting re-establishment of the native woody-plant community. We analyzed Landsat 8 satellite imagery to describe autumn olive’s distribution on post-mined lands in southwestern Virginia within the Appalachian coalfield. Eight images from April 2013 through January 2015 served as input data. Calibration and validation data obtained from high-resolution aerial imagery were used to develop a land cover classification model that identified areas where autumn olive was a primary component of land cover. Results indicate that autumn olive cover was sufficiently dense to enable detection on approximately 12.6 % of post-mined lands within the study area. The classified map had user’s and producer’s accuracies of 85.3 and 78.6 %, respectively, for the autumn olive coverage class. Overall accuracy was assessed in reference to an independent validation dataset at 96.8 %. Autumn olive was detected more frequently on mines disturbed prior to 2003, the last year of known plantings, than on lands disturbed by more recent mining. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in eastern USA can be mapped using Landsat 8 Operational Land Imager imagery; and that autumn olive occurrence is a significant landscape vegetation feature on former surface coal mines in the southwestern Virginia segment of the Appalachian coalfield.

Earth Observations taken by the Expedition 16 Crew

NASA Image and Video Library

2008-03-05

ISS016-E-031056 (3 March 2008) --- Cananea Copper Mine, Sonora, Mexico is featured in this image photographed by an Expedition 16 crewmember on the International Space Station. One of the largest open-pit copper mines in the world, the Cananea mine produced over 164,000 tons of copper in 2006. The mine is located approximately 40 kilometers south of the border between the USA (Arizona) and Mexico (Sonora). Copper and gold ores at Cananea are found in a porphyry copper deposit, a geological structure formed by crystal-rich magma moving upwards through pre-existing rock layers. A porphyry - an igneous rock with large crystals in a fine-grained matrix -- is formed as the magma cools and crystallizes. While crystallization is occurring, hot fluids can circulate through the magma and surrounding rocks via fractures. This hydrothermal alteration of the rocks typically forms copper-bearing and other minerals. Much of the Cananea mine's ore is concentrated in breccia pipes -- mineralized rod or chimney-shaped bodies that contain broken rock fragments. The active, two-kilometers-in-diameter Colorada Pit (top right) is recognizable in this image by the concentric steps or benches cut around its perimeter. These benches allow for access into the pit for extraction of ore and waste materials. Water (black) is visible filling the bottom of the pit, and several other basins in the surrounding area. The city of Cananea -- marked by its street grid -- is located to the northeast of the mine workings. A leachate reservoir is located to the east of the mine (lower left) for removal and evaporation of water pumped from the mine workings -- the bluish-white coloration of deposits near the reservoir suggests the high mineral content of the leachate. A worker strike halted mine operations in 2007.

Spatio-Temporal Mining of PolSAR Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Julea, A.; Meger, N.; Trouve, E.; Bolon, Ph.; Rigotti, C.; Fallourd, R.; Nicolas, J.-M.; Vasile, G.; Gay, M.; Harant, O.; Ferro-Famil, L.

2010-12-01

This paper presents an original data mining approach for describing Satellite Image Time Series (SITS) spatially and temporally. It relies on pixel-based evolution and sub-evolution extraction. These evolutions, namely the frequent grouped sequential patterns, are required to cover a minimum surface and to affect pixels that are sufficiently connected. These spatial constraints are actively used to face large data volumes and to select evolutions making sense for end-users. In this paper, a specific application to fully polarimetric SAR image time series is presented. Preliminary experiments performed on a RADARSAT-2 SITS covering the Chamonix Mont-Blanc test-site are used to illustrate the proposed approach.

EVIDENCE FOR METAL ATTENUATION IN ACID MINE WATER BY SULFATE REDUCTION, PENN MINE, CALAVERAS COUNTY, CALIFORNIA

EPA Science Inventory

The Penn Mine in Calaveras County, California, produced Cu from massive sulfide ores from 1861 to 1953. Mine wastes were removed to a landfill during the late 1990s, improving surface-water quality, but deep mine workings were not remediated and contain metalliferous water with p...

75 FR 62133 - Notice of Availability of Final Environmental Assessment (FINAL EA) and a Finding of No...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-07

... 507 acres of real estate containing the CDC/NIOSH's Lake Lynn Experimental Mine located in Springhill... mine tunnels servicing the Experimental Mine. The purpose and need of the proposed acquisition and construction improvements secures the currently leased Experimental Mine for the long-term continuation of mine...

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…

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

PubMed

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

2013-11-12

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

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

PubMed Central

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

2013-01-01

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

Numerical Study on 4-1 Coal Seam of Xiaoming Mine in Ascending Mining

PubMed Central

Tianwei, Lan; Hongwei, Zhang; Sheng, Li; Weihua, Song; Batugin, A. C.; Guoshui, Tang

2015-01-01

Coal seams ascending mining technology is very significant, since it influences the safety production and the liberation of dull coal, speeds up the construction of energy, improves the stability of stope, and reduces or avoids deep hard rock mining induced mine disaster. Combined with the Xiaoming ascending mining mine 4-1, by numerical calculation, the paper analyses ascending mining 4-1 factors, determines the feasibility of ascending mining 4-1 coalbed, and proposes roadway layout program about working face, which has broad economic and social benefits. PMID:25866840

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

ERIC Educational Resources Information Center

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

2018-01-01

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

Data mining and visualization of average images in a digital hand atlas

NASA Astrophysics Data System (ADS)

Zhang, Aifeng; Gertych, Arkadiusz; Liu, Brent J.; Huang, H. K.

2005-04-01

We have collected a digital hand atlas containing digitized left hand radiographs of normally developed children grouped accordingly by age, sex, and race. A set of features stored in a database reflecting patient's stage of skeletal development has been calculated by automatic image processing procedures. This paper addresses a new concept, "average" image in the digital hand atlas. The "average" reference image in the digital atlas is selected for each of the groups of normal developed children with the best representative skeletal maturity based on bony features. A data mining procedure was designed and applied to find the average image through average feature vector matching. It also provides a temporary solution for the missing feature problem through polynomial regression. As more cases are added to the digital hand atlas, it can grow to provide clinicians accurate reference images to aid the bone age assessment process.

The birthweight toll of mining pollution: evidence from the most contaminated mine site in the Andean region.

PubMed

Arrieta, A; Guillen, J

2018-04-26

To assess the effect of mining pollution on birthweight. A retrospective before-and-after study with an untreated comparison group. La Oroya, a mining town in the Peruvian Andes, considered the most contaminated town in the Andean region. All pregnant women who delivered in the social security healthcare system in years 2005, 2006, 2008 and 2009. A total of 214 983 births records were used, 957 from La Oroya and 214 026 from the rest of the country. A difference-in-difference estimation is used to assess the effect of mining pollution on birthweight before and after two business policy changes: a partial environmental improvement and a subsequent closure of smelter operations in La Oroya. Birthweight was compared with a group not affected by the environmental changes in La Oroya. Birthweight in grams. A steep reduction in mining pollution due to the closure of smelter operations in La Oroya showed an increased birthweight of 71.6 g after controlling for socio-economic and medical characteristics. None of the environmental improvements prior to the closure had a statistically significant effect on birthweight. Mining pollution in La Oroya had a negative impact on birthweight. Partial environmental improvements were not enough to improve birthweight. Only after the closure of all mining and smelter operations in La Oroya was a significant gain in birthweight shown. The closure of the most contaminated mine site in the Andean region increased birthweight by 72 g. © 2018 Royal College of Obstetricians and Gynaecologists.

High-resolution seismic imaging of the Kevitsa mafic-ultramafic Cu-Ni-PGE hosted intrusion, northern Finland

NASA Astrophysics Data System (ADS)

Malehmir, Alireza; Koivisto, Emilia; Wjins, Chris; Tryggvason, Ari; Juhlin, Christopher

2014-05-01

Kevitsa, in northern Finland, is a large nickel/copper ore body hosted by a massive mafic-ultramafic intrusion with measured and indicated resources of 240 million tons (cutoff 0.1%) grading 0.30% Ni and 0.41% Cu. Mining started in 2012 with an open pit that will extend down to about 550-600 m depth. The expected mine life is more than 20 years. Numerous boreholes are available in the area, but the majority of them are shallow and do not provide a comprehensive understanding of the dimensions of the intrusion. However, a number of boreholes do penetrate the basal contact of the intrusion. Most of these are also shallow and concentrated at the edge of the intrusion. A better knowledge of the geometry of the intrusion would provide a framework for near-mine and deep exploration in the area, but also a better understanding of the geology. Exact mapping of the basal contact of the intrusion would also provide an exploration target for the contact-type mineralization that is often more massive and richer in Ni-Cu than the disseminated mineralization away from the contact. With the objective of better characterizing the intrusion, a series of 2D profiles were acquired followed by a 3D reflection survey that covered an area of about 3 km by 3 km. Even though the geology is complex and the seismic P-wave velocity ranges between 5 to 8 km/s, conventional processing results show gently- to steeply-dipping reflections from depths of approximately 2 km to as shallow as 100 m. Many of these reflections are interpreted to originate from either fault systems or internal magmatic layering within the Kevitsa main intrusion. Correlations between the 3D surface seismic data and VSP data, based upon time shifts or phase changes along the reflections, support the interpretation that numerous faults are imaged in the volume. Some of these faults cross the planned open-pit mine at depths of about 300-500 m, and it is, therefore, critical to map them for mine planning. The seismic 3D volume better represents the geology around the mine and in the vicinity of the known deposit, while the 2D seismic profiles were designed to provide information on larger-scale structures in the area. Both the 2D and 3D seismic data were used to create a 3D lithological and structural model of the entire complex. Information on the dimensions of the ore-bearing Kevitsa intrusion can be used for more effective exploration in the area. The base of the intrusion is particularly clear in the northern and western sectors of the seismic data. Toward the east, the base is mostly defined by disruption of the reflectors internal to the intrusion. Recent tests using prestack migration methods on the 3D data show partial improvements in the image, especially at shallow depths. 3D seismic tomography has also been performed and the results indicate low velocity zones crossing the open pit that can be interpreted as zones of weakness. Future studies will focus on using the tomography results as the input velocity field for prestack depth migration of the 3D data and also improving the 3D geological model of the study area. Acknowledgments: FQM, GTK, HiSeis and Vibrometric

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

PubMed Central

Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.

2009-01-01

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147

Imaging near surface mineral targets with ambient seismic noise

NASA Astrophysics Data System (ADS)

Dales, P.; Audet, P.; Olivier, G.

2017-12-01

To keep up with global metal and mineral demand, new ore-deposits have to be discovered on a regular basis. This task is becoming increasingly difficult, since easily accessible deposits have been exhausted to a large degree. The typical procedure for mineral exploration begins with geophysical surveys followed by a drilling program to investigate potential targets. Since the retrieved drill core samples are one-dimensional observations, the many holes needed to interpolate and interpret potential deposits can lead to very high costs. To reduce the amount of drilling, active seismic imaging is sometimes used as an intermediary, however the active sources (e.g. large vibrating trucks or explosive shots) are expensive and unsuitable for operation in remote or environmentally sensitive areas. In recent years, passive seismic imaging using ambient noise has emerged as a novel, low-cost and environmentally sensitive approach for exploring the sub-surface. This technique dispels with active seismic sources and instead uses ambient seismic noise such as ocean waves, traffic or minor earthquakes. Unfortunately at this point, passive surveys are not capable of reaching the required resolution to image the vast majority of the ore-bodies that are being explored. In this presentation, we will show the results of an experiment where ambient seismic noise recorded on 60 seismic stations was used to image a near-mine target. The target consists of a known ore-body that has been partially exhausted by mining efforts roughly 100 years ago. The experiment examined whether ambient seismic noise interferometry can be used to image the intact and exhausted ore deposit. A drilling campaign was also conducted near the target which offers the opportunity to compare the two methods. If the accuracy and resolution of passive seismic imaging can be improved to that of active surveys (and beyond), this method could become an inexpensive intermediary step in the exploration process and result in a large decrease in the amount of drilling required to investigate and identify high-grade ore deposits.

Radiomics: Images Are More than Pictures, They Are Data

PubMed Central

Kinahan, Paul E.; Hricak, Hedvig

2016-01-01

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer. PMID:26579733

Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

NASA Astrophysics Data System (ADS)

Espinoza Molina, D.; Datcu, M.

2015-04-01

The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

Coal Mining, Germany

NASA Image and Video Library

2001-08-01

This simulated natural color ASTER image in the German state of North Rhine Westphalia covers an area of 30 by 36 km, and was acquired on August 26, 2000. On the right side of the image are 3 enormous opencast coalmines. The Hambach opencast coal mine has recently been brought to full output capacity through the addition of the No. 293 giant bucket wheel excavator. This is the largest machine in the world; it is twice as long as a soccer field and as tall as a building with 30 floors. To uncover the 2.4 billion tons of brown coal (lignite) found at Hambach, five years were required to remove a 200-m-thick layer of waste sand and to redeposit it off site. The mine currently yields 30 million tons of lignite annually, with annual capacity scheduled to increase to 40 million tons in coming years. The image is centered at 51 degrees north latitude, 6.4 degrees east longitude. http://photojournal.jpl.nasa.gov/catalog/PIA02676

South Africa, Namibia Diamond Deposits (close-up)

NASA Technical Reports Server (NTRS)

1998-01-01

This radar image shows a close up view of a portion of the Richtersveld National Park and Orange River (top of image) in the Northern Cape Province of the Republic of South Africa. The Orange River marks the boundary between South Africa to the south and Namibia to the north. This is an area of active mining for diamonds, which were washed downstream from the famous Kimberley Diamond Area, millions of years ago when the river was much larger. The mining is focused on ancient drainages of the Orange River which are currently buried by think layers of sand and gravel. Scientists are investigating whether these ancient drainages can be seen with the radar's ability to penetrate sand cover in extremely dry regions. A mine, shown in yellow, is on the southern bank of the river in an abandoned bend which is known as an 'oxbow.' The small bright circular areas (left edge of image) west of the mine circles are fields of a large ostrich farm that are being watered with pivot irrigation. The large dark area in the center of the image is the Kubus Pluton, a body of granite rock that broke through the surrounding rocks about 550 million years ago. North is toward the upper right. The area shown is about 35 by 25 kilometers (21.8 by 15.5 miles) centered at 28.4 degrees south latitude, 16.8 degrees east longitude. Colors are assigned to different radar frequencies and polarizations as follows: red is L-band horizontally transmitted and horizontally received; green is L-band horizontally transmitted and vertically received; blue is C-band horizontally transmitted and vertically received. The image was acquired on April 18, 1994 by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture (SIR-C/X-SAR) imaging radar when it flew aboard the space shuttle Endeavour. SIR-C/X-SAR is a joint mission of the U.S./German and Italian space agencies.

South Africa, Namibia Diamond Deposits

NASA Technical Reports Server (NTRS)

1998-01-01

This radar image covers a portion of the Richtersveld National Park and Orange River (top of image) in the Northern Cape Province of the Republic of South Africa. The Orange River marks the boundary between South Africa to the south and Namibia to the north. This is an area of active mining for diamonds, which were washed downstream from the famous Kimberley Diamond Area, millions of years ago when the river was much larger. The mining is focused on ancient drainages of the Orange River which are currently buried by think layers of sand and gravel. Scientists are investigating whether these ancient drainages can be seen with the radar's ability to penetrate sand cover in extremely dry regions. A mine, shown in yellow, is on the southern bank of the river in an abandoned bend which is known as an 'oxbow.' The small bright circular areas (left edge of image) west of the mine circles are fields of a large ostrich farm that are being watered with pivot irrigation. The large dark area in the center of the image is the Kubus Pluton, a body of granite rock that broke through the surrounding rocks about 550 million years ago. North is toward the upper right. The area shown is about 55 by 60 kilometers (34 by 37 miles) centered at 28.4 degrees south latitude, 16.8 degrees east longitude. Colors are assigned to different radar frequencies and polarizations as follows: red is L-band horizontally transmitted and horizontally received; green is L-band horizontally transmitted and vertically received; blue is C-band horizontally transmitted and vertically received. The image was acquired on April 18, 1994 by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture (SIR-C/X-SAR) imaging radar when it flew aboard the space shuttle Endeavour. SIR-C/X-SAR is a joint mission of the U.S./German and Italian space agencies.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

26 CFR 1.612-2 - Allowable capital additions in case of mines.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 7 2010-04-01 2010-04-01 true Allowable capital additions in case of mines. 1... in case of mines. (a) In general. Expenditures for improvements and for replacements, not including... the recession of the working faces of the mine and which: (1) Do not increase the value of the mine...

A semantic model for multimodal data mining in healthcare information systems.

PubMed

Iakovidis, Dimitris; Smailis, Christos

2012-01-01

Electronic health records (EHRs) are representative examples of multimodal/multisource data collections; including measurements, images and free texts. The diversity of such information sources and the increasing amounts of medical data produced by healthcare institutes annually, pose significant challenges in data mining. In this paper we present a novel semantic model that describes knowledge extracted from the lowest-level of a data mining process, where information is represented by multiple features i.e. measurements or numerical descriptors extracted from measurements, images, texts or other medical data, forming multidimensional feature spaces. Knowledge collected by manual annotation or extracted by unsupervised data mining from one or more feature spaces is modeled through generalized qualitative spatial semantics. This model enables a unified representation of knowledge across multimodal data repositories. It contributes to bridging the semantic gap, by enabling direct links between low-level features and higher-level concepts e.g. describing body parts, anatomies and pathological findings. The proposed model has been developed in web ontology language based on description logics (OWL-DL) and can be applied to a variety of data mining tasks in medical informatics. It utility is demonstrated for automatic annotation of medical data.

Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe.

PubMed

Luciani, Timothy Basil; Cherinka, Brian; Oliphant, Daniel; Myers, Sean; Wood-Vasey, W Michael; Labrinidis, Alexandros; Marai, G Elisabeta

2014-07-01

We introduce a web-based computing infrastructure to assist the visual integration, mining and interactive navigation of large-scale astronomy observations. Following an analysis of the application domain, we design a client-server architecture to fetch distributed image data and to partition local data into a spatial index structure that allows prefix-matching of spatial objects. In conjunction with hardware-accelerated pixel-based overlays and an online cross-registration pipeline, this approach allows the fetching, displaying, panning and zooming of gigabit panoramas of the sky in real time. To further facilitate the integration and mining of spatial and non-spatial data, we introduce interactive trend images-compact visual representations for identifying outlier objects and for studying trends within large collections of spatial objects of a given class. In a demonstration, images from three sky surveys (SDSS, FIRST and simulated LSST results) are cross-registered and integrated as overlays, allowing cross-spectrum analysis of astronomy observations. Trend images are interactively generated from catalog data and used to visually mine astronomy observations of similar type. The front-end of the infrastructure uses the web technologies WebGL and HTML5 to enable cross-platform, web-based functionality. Our approach attains interactive rendering framerates; its power and flexibility enables it to serve the needs of the astronomy community. Evaluation on three case studies, as well as feedback from domain experts emphasize the benefits of this visual approach to the observational astronomy field; and its potential benefits to large scale geospatial visualization in general.

Color machine vision in industrial process control: case limestone mine

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.; Lemstrom, Guy F.; Koskinen, Seppo

1994-11-01

An optical sorter technology has been developed to improve profitability of a mine by using color line scan machine vision technology. The new technology adapted longers the expected life time of the limestone mine and improves its efficiency. Also the project has proved that color line scan technology of today can successfully be applied to industrial use in harsh environments.

SU-E-T-235: Data Mining for Evaluating Treatment Performances Over a Large Quantity of Data to Monitor and Improve SBRT Workflow

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

Feng, W; Bayhealth Medical Center, Dover, DE; Chu, A

Purpose: To quality assure a large quantity of retrospective treatment cases for treatment performances by randomly sampling is inefficient. Here we provide a method to efficiently monitor and investigate the QA of SBRT workflow over Mosaiq. Methods: The code developed with Microsoft SQL Server Management Studio 2008R2 and VBA was used for retrieving and sorting data from Mosaiq (version 2.3–2.6 during 2012–2015). SBRT patients were filtered by fractional dose over 350cGy and total fraction number less than 6, which SBRT prescriptions were defined. The quality assurance on the SBRT workflow was focused on the treatment deliveries such as patient positioningmore » setup, CBCT indicated offsets and couch shifted corrections. The treatment delivery were done by Varian Truebeam systems and the record/verify by Mosaiq. Results: Total 82 SBRT patients corresponding to 103 courses and 854 CBCT images were found by the retrieval query. Most centers record daily pre-treatment (Pre-Tx: before treatment shift) image-guided shifts along treatment course for inter-fraction motion record, and it is useful to also verify it with post-treatment imaging (Post-Tx: after treatment CBCT verification) to verify intra-fraction motion. Analyzing the details of daily recorded shifts can reveals the information of patient-setup and staff’s record/verify behaviors. 3 examples were provided as solid evidences and on-going rectification for preventing future mistakes. Conclusions: The report gave feasible examples for inspector to verify a large amount of data during site investigation. This program can also be extended to a scheduled data mining with software to periodical analyze the timely records in Mosaiq, for example, a various control charts for different QA purposes. As the current trend of automation in radiation therapy field, the data mining would be a necessary tool in the future, just as the automatic plan quality evaluation has been under development in Eclipse.« less

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.

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

Estimation of in-situ Stress Magnitudes and Orientations in a Deep South African Gold Mine: Applications to Fault Mechanics and Mine Safety

NASA Astrophysics Data System (ADS)

Lucier, A. M.; Heesakkers, V.; Zoback, M. D.; Reches, Z.

2006-12-01

As part of the Natural Earthquake Laboratory in South African Mines (NELSAM) project, we are investigating the far-field in-situ stress state around the TauTona gold mine. The far-field stress state is used as a boundary condition to quantify the stresses within the active mining area, and to evaluate the potential for reactivation of existing faults (or creation of new faults) in the NELSAM study area. Our main goals are to gain insight into earthquake processes under induced faulting conditions and to guide mining practices in improving underground seismic safety. To characterize in-situ stresses, we use an integrated stress measurement strategy that incorporates rock properties with breakout and drilling-induced tensile fracture observations from camera log images of several boreholes in the NELSAM study area at a depth of 3.5 km below the ground surface. The quantification of the far-field in-situ stress state is based on breakouts observed in a sub-horizontal borehole that extends 418 m away from the mined region and intersects the Pretorius fault, the largest fault-zone in the mine. The location, width and orientation of these breakouts were interpreted along the length of the borehole. Breakouts occur along most of the length of the borehole, with widths ranging from 25-95 deg and orientations fluctuating up to 45 deg around the sidewalls of the borehole. The fluctuations in breakout orientations are presumably due to slip on fault segments, and modeling these fluctuations provides constraints on the far-field stress state. Rock properties (uniaxial compressive strength, Young's modulus and Poisson's ratio) from on-going laboratory experiments will further constrain the stress magnitudes. The results of the stress characterization in this long borehole have been compared with independent stress determinations made in several 10-40 m long boreholes within the mined region to ensure consistency between the modeled far-field stress magnitudes and the observed near-field stresses. Our preliminary results indicate a normal faulting to normal/strike-slip stress state. Once a final stress model has been obtained, we will use it to assess the potential for fault reactivation and to predict future stress changes associated with further mining operations. The study was supported by NSF Continental Dynamics grant 0409605.

STARR: shortwave-targeted agile Raman robot for the detection and identification of emplaced explosives

NASA Astrophysics Data System (ADS)

Gomer, Nathaniel R.; Gardner, Charles W.

2014-05-01

In order to combat the threat of emplaced explosives (land mines, etc.), ChemImage Sensor Systems (CISS) has developed a multi-sensor, robot mounted sensor capable of identification and confirmation of potential threats. The system, known as STARR (Shortwave-infrared Targeted Agile Raman Robot), utilizes shortwave infrared spectroscopy for the identification of potential threats, combined with a visible short-range standoff Raman hyperspectral imaging (HSI) system for material confirmation. The entire system is mounted onto a Talon UGV (Unmanned Ground Vehicle), giving the sensor an increased area search rate and reducing the risk of injury to the operator. The Raman HSI system utilizes a fiber array spectral translator (FAST) for the acquisition of high quality Raman chemical images, allowing for increased sensitivity and improved specificity. An overview of the design and operation of the system will be presented, along with initial detection results of the fusion sensor.

Biochar Improves Performance of Plants for Mine Soil Revegetation

EPA Science Inventory

Biochar (the solid by-product of pyrolysis of biomass), has the potential to improve plant performance for revegetation of mine soils by improving soil chemistry, fertility, moisture holding capacity and by binding heavy metals. We investigated the effect of gasified conifer sof...

Identification of mine collapses, explosions and earthquakes using INSAR: a preliminary investigation

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

Foxall, B; Sweeney, J J; Walter, W R

1998-07-07

Interferograms constmcted from satellite-borne synthetic aperture radar images have the capability of mapping sub-cm ground surface deformation over areas on the order of 100 x 100 km with a spatial resolution on the order of 10 meters. We investigate the utility of synthetic aperture radar interferomehy (InSAR) used in conjunction with regional seismic methods in detecting and discriminating different types of seismic events in the context of special event analysis for the CTBT. For this initial study, we carried out elastic dislocation modeling of underground explosions, mine collapses and small (M<5.5) shallow earthquakes to produce synthetic interferograms and then analyzedmore » satellite radar data for a large mine collapse. The synthetic modeling shows that, for a given magnitude each type of event produces a distinctive pattern of ground deformation that can be recognized in, and recovered from, the corresponding interferogram. These diagnostic characteristics include not only differences in the polarities of surface displacements but also differences in displacement amplitudes from the different sources. The technique is especially sensitive to source depth, a parameter that is crucial in discriminating earthquakes from the other event types but is often very poorly constrained by regional seismic data alone. The ERS radar data analyzed is from a M L 5.2 seismic event that occurred in southwestern Wyoming on February 3,1995. Although seismic data from the event have some characteristics of an underground explosion, based on seismological and geodetic data it has been identified as being caused by a large underground collapse in the Solvay Mine. Several pairs of before-collapse and after-collapse radar images were phase processed to obtain interferograms. The minimum time separation for a before-collapse and after-collapse pair was 548 days. Even with this long time separation, phase coherence between the image pairs was acceptable and a deformation map was successfully obtained. Two images, separated by 1 day and occurring after the mine collapse, were used to form a digital elevation map (DEM) that was used to correct for topography. The interferograms identify the large deformation at the Solvay Mine as well as some areas of lesser deformation near other mines in the area. The large amount of deformation at the Solvay Mine was identified, but (as predicted by our dislocation modeling) could not be quantified absolutely because of the incoherent interference pattern it produced« less

Noise-based body-wave seismic tomography in an active underground mine.

NASA Astrophysics Data System (ADS)

Olivier, G.; Brenguier, F.; Campillo, M.; Lynch, R.; Roux, P.

2014-12-01

Over the last decade, ambient noise tomography has become increasingly popular to image the earth's upper crust. The seismic noise recorded in the earth's crust is dominated by surface waves emanating from the interaction of the ocean with the solid earth. These surface waves are low frequency in nature ( < 1 Hz) and not usable for imaging smaller structures associated with mining or oil and gas applications. The seismic noise recorded at higher frequencies are typically from anthropogenic sources, which are short lived, spatially unstable and not well suited for constructing seismic Green's functions between sensors with conventional cross-correlation methods. To examine the use of ambient noise tomography for smaller scale applications, continuous data were recorded for 5 months in an active underground mine in Sweden located more than 1km below surface with 18 high frequency seismic sensors. A wide variety of broadband (10 - 3000 Hz) seismic noise sources are present in an active underground mine ranging from drilling, scraping, trucks, ore crushers and ventilation fans. Some of these sources generate favorable seismic noise, while others are peaked in frequency and not usable. In this presentation, I will show that the noise generated by mining activity can be useful if periods of seismic noise are carefully selected. Although noise sources are not temporally stable and not evenly distributed around the sensor array, good estimates of the seismic Green's functions between sensors can be retrieved for a broad frequency range (20 - 400 Hz) when a selective stacking scheme is used. For frequencies below 100 Hz, the reconstructed Green's functions show clear body-wave arrivals for almost all of the 153 sensor pairs. The arrival times of these body-waves are picked and used to image the local velocity structure. The resulting 3-dimensional image shows a high velocity structure that overlaps with a known ore-body. The material properties of the ore-body differ from the host rock and is likely the cause of the observed high velocity structure. For frequencies above 200 Hz, the seismic waves are multiply scattered by the tunnels and excavations and used to determine the scattering properties of the medium. The results of this study should be useful for future imaging and exploration projects in mining and oil and gas industries.

Earth Observations taken by the Expedition 13 crew

NASA Image and Video Library

2006-08-02

ISS013-E-63766 (2 Aug. 2006) --- Berkeley Pit and Butte, Montana are featured in this image photographed by an Expedition 13 crewmember on the International Space Station. The city of Butte, Montana has long been a center of mining activity. Underground mining of copper began in Butte in the 1870s, and by 1901 underground workings had extended to the groundwater table. Thus began the creation of an intricate complex of underground drains and pumps to lower the groundwater level and continue the extraction of copper. Water extracted from the mines was so rich in dissolved copper sulfate that it was also "mined" (by chemical precipitation) for the copper it contained. In 1955, the Anaconda Copper Mining Company began open-pit mining for copper in what is now know as the Berkeley Pit (dark oblong area in center). The mine took advantage of the existing subterranean drainage and pump network to lower groundwater until 1982, when the new owner ARCO suspended operations at the mine. The groundwater level swiftly rose, and today water in the Pit is more than 900 feet deep. Many features of the mine workings are visible in this image such as the many terraced levels and access roadways of the open mine pits (gray and tan sculptured surfaces). A large gray tailings pile of waste rock and an adjacent tailings pond are visible to the north of the Berkeley Pit. Color changes in the tailings pond are due primarily to changing water depth. The Berkeley Pit is listed as a federal Superfund site due to its highly acidic water, which contains high concentrations of metals such as copper and zinc. The Berkeley Pit receives groundwater flowing through the surrounding bedrock and acts as a "terminal pit" or sink for these heavy metal-laden waters. Ongoing efforts include regulation of water flow into the pit to reduce filling of the Pit and potential release of contaminated water into local aquifers or surface streams.

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

Application of high-resolution subsurface imaging techniques to water resource investigations. Final report

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

Sternberg, B.K.; Thomas, S.J.

1992-12-01

The overall objective of the project was to apply a new high-resolution imaging system to water resource investigations. This imaging system measures the ellipticity of received magnetic-field components. The source of the magnetic field is a long-line transmitter emitting frequencies from 30 Hz to 30 kHz. A new high-accuracy calibration method was used to enhance the resolution of the measurements. The specific objectives included: (1) refine the system hardware and software based on these investigations, (2) learn the limitations of this technology in practical water resource investigations, and (3) improve interpretation techniques to extract the highest possible resolution. Successful fieldmore » surveys were run at: (1) San Xavier Mine, Arizona - flow of injected fluid was monitored with the system. (2) Avra Valley, Arizona - subsurface stratigraphy was imaged. A survey at a third site was less successful; interpreted resistivity section does not agree with nearby well logs. Surveys are continuing at this site.« less

Parallel object-oriented data mining system

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2004-01-06

A data mining system uncovers patterns, associations, anomalies and other statistically significant structures in data. Data files are read and displayed. Objects in the data files are identified. Relevant features for the objects are extracted. Patterns among the objects are recognized based upon the features. Data from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) sky survey was used to search for bent doubles. This test was conducted on data from the Very Large Array in New Mexico which seeks to locate a special type of quasar (radio-emitting stellar object) called bent doubles. The FIRST survey has generated more than 32,000 images of the sky to date. Each image is 7.1 megabytes, yielding more than 100 gigabytes of image data in the entire data set.

Data Mining for CRM

NASA Astrophysics Data System (ADS)

Thearling, Kurt

Data Mining technology allows marketing organizations to better understand their customers and respond to their needs. This chapter describes how Data Mining can be combined with customer relationship management to help drive improved interactions with customers. An example showing how to use Data Mining to drive customer acquisition activities is presented.

Solar Data Mining at Georgia State University

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-28

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

Comparative Data Mining Analysis for Information Retrieval of MODIS Images: Monitoring Lake Turbidity Changes at Lake Okeechobee, Florida

EPA Science Inventory

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates mig...

The use of the DInSAR method in the monitoring of road damage caused by mining activities

NASA Astrophysics Data System (ADS)

Murdzek, Radosław; Malik, Hubert; Leśniak, Andrzej

2018-04-01

This paper reviews existing remote sensing methods of road damage detection and demonstrates the possibility of using DInSAR (Differential Interferometry SAR) method to identify endangered road sections. In this study two radar images collected by Sentinel-1 satellite have been used. Images were acquired with 24 days interval in 2015. The analysis allowed to estimate the scale of the post-mining deformation that occurred in Upper Silesia and to indicate areas where road infrastructure is particularly vulnerable to damage.

A review of EO image information mining

NASA Astrophysics Data System (ADS)

Quartulli, Marco; Olaizola, Igor G.

2013-01-01

We analyze the state of the art of content-based retrieval in Earth observation image archives focusing on complete systems showing promise for operational implementation. The different paradigms at the basis of the main system families are introduced. The approaches taken are considered, focusing in particular on the phases after primitive feature extraction. The solutions envisaged for the issues related to feature simplification and synthesis, indexing, semantic labeling are reviewed. The methodologies for query specification and execution are evaluated. Conclusions are drawn on the state of published research in Earth observation (EO) mining.

Multiple comparisons permutation test for image based data mining in radiotherapy.

PubMed

Chen, Chun; Witte, Marnix; Heemsbergen, Wilma; van Herk, Marcel

2013-12-23

: Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy.

MO-C-BRCD-03: The Role of Informatics in Medical Physics and Vice Versa.

PubMed

Andriole, K

2012-06-01

Like Medical Physics, Imaging Informatics encompasses concepts touching every aspect of the imaging chain from image creation, acquisition, management and archival, to image processing, analysis, display and interpretation. The two disciplines are in fact quite complementary, with similar goals to improve the quality of care provided to patients using an evidence-based approach, to assure safety in the clinical and research environments, to facilitate efficiency in the workplace, and to accelerate knowledge discovery. Use-cases describing several areas of informatics activity will be given to illustrate current limitations that would benefit from medical physicist participation, and conversely areas in which informaticists may contribute to the solution. Topics to be discussed include radiation dose monitoring, process management and quality control, display technologies, business analytics techniques, and quantitative imaging. Quantitative imaging is increasingly becoming an essential part of biomedicalresearch as well as being incorporated into clinical diagnostic activities. Referring clinicians are asking for more objective information to be gleaned from the imaging tests that they order so that they may make the best clinical management decisions for their patients. Medical Physicists may be called upon to identify existing issues as well as develop, validate and implement new approaches and technologies to help move the field further toward quantitative imaging methods for the future. Biomedical imaging informatics tools and techniques such as standards, integration, data mining, cloud computing and new systems architectures, ontologies and lexicons, data visualization and navigation tools, and business analytics applications can be used to overcome some of the existing limitations. 1. Describe what is meant by Medical Imaging Informatics and understand why the medical physicist should care. 2. Identify existing limitations in information technologies with respect to Medical Physics, and conversely see how Informatics may assist the medical physicist in filling some of the current gaps in their activities. 3. Understand general informatics concepts and areas of investigation including imaging and workflow standards, systems integration, computing architectures, ontologies, data mining and business analytics, data visualization and human-computer interface tools, and the importance of quantitative imaging for the future of Medical Physics and Imaging Informatics. 4. Become familiar with on-going efforts to address current challenges facing future research into and clinical implementation of quantitative imaging applications. © 2012 American Association of Physicists in Medicine.

75 FR 18500 - Guidance on Improving EPA Review of Appalachian Surface Coal Mining Operations under the Clean...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-12

... of Appalachian Surface Coal Mining Operations under the Clean Water Act, National Environmental... Appalachian Surface Coal Mining Operations under the Clean Water Act, National Environmental Policy Act, and... coal mining operations under the Clean Water Act, National Environmental Policy Act, and the...

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

PubMed Central

Chang, Qingliang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application. PMID:25258737

Implementation of paste backfill mining technology in Chinese coal mines.

PubMed

Chang, Qingliang; Chen, Jianhang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application.

Knight Hawk adapts highwall mining for Southern Illinois

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

Buchsbaum, L.

2007-10-15

A few years ago while planning their first underground operation and trying to decide how to mine shallow seams, Knight Hawk purchased a 'Superior Highwall Miner' (SHM). Since then this small innovative company has been pioneering the use of highwall mining in a trenching application in for example the Illinois Basin. Highwall mining is very suitable for contour mining in Appalachia. The article discusses the recent improvements and the advantages of SHM mining systems. 3 photos.

Tiny videos: a large data set for nonparametric video retrieval and frame classification.

PubMed

Karpenko, Alexandre; Aarabi, Parham

2011-03-01

In this paper, we present a large database of over 50,000 user-labeled videos collected from YouTube. We develop a compact representation called "tiny videos" that achieves high video compression rates while retaining the overall visual appearance of the video as it varies over time. We show that frame sampling using affinity propagation-an exemplar-based clustering algorithm-achieves the best trade-off between compression and video recall. We use this large collection of user-labeled videos in conjunction with simple data mining techniques to perform related video retrieval, as well as classification of images and video frames. The classification results achieved by tiny videos are compared with the tiny images framework [24] for a variety of recognition tasks. The tiny images data set consists of 80 million images collected from the Internet. These are the largest labeled research data sets of videos and images available to date. We show that tiny videos are better suited for classifying scenery and sports activities, while tiny images perform better at recognizing objects. Furthermore, we demonstrate that combining the tiny images and tiny videos data sets improves classification precision in a wider range of categories.

Seeing is believing: on the use of image databases for visually exploring plant organelle dynamics.

PubMed

Mano, Shoji; Miwa, Tomoki; Nishikawa, Shuh-ichi; Mimura, Tetsuro; Nishimura, Mikio

2009-12-01

Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Inference of strata separation and gas emission paths in longwall overburden using continuous wavelet transform of well logs and geostatistical simulation

NASA Astrophysics Data System (ADS)

Karacan, C. Özgen; Olea, Ricardo A.

2014-06-01

Prediction of potential methane emission pathways from various sources into active mine workings or sealed gobs from longwall overburden is important for controlling methane and for improving mining safety. The aim of this paper is to infer strata separation intervals and thus gas emission pathways from standard well log data. The proposed technique was applied to well logs acquired through the Mary Lee/Blue Creek coal seam of the Upper Pottsville Formation in the Black Warrior Basin, Alabama, using well logs from a series of boreholes aligned along a nearly linear profile. For this purpose, continuous wavelet transform (CWT) of digitized gamma well logs was performed by using Mexican hat and Morlet, as the mother wavelets, to identify potential discontinuities in the signal. Pointwise Hölder exponents (PHE) of gamma logs were also computed using the generalized quadratic variations (GQV) method to identify the location and strength of singularities of well log signals as a complementary analysis. PHEs and wavelet coefficients were analyzed to find the locations of singularities along the logs. Using the well logs in this study, locations of predicted singularities were used as indicators in single normal equation simulation (SNESIM) to generate equi-probable realizations of potential strata separation intervals. Horizontal and vertical variograms of realizations were then analyzed and compared with those of indicator data and training image (TI) data using the Kruskal-Wallis test. A sum of squared differences was employed to select the most probable realization representing the locations of potential strata separations and methane flow paths. Results indicated that singularities located in well log signals reliably correlated with strata transitions or discontinuities within the strata. Geostatistical simulation of these discontinuities provided information about the location and extents of the continuous channels that may form during mining. If there is a gas source within their zone of influence, paths may develop and allow methane movement towards sealed or active gobs under pressure differentials. Knowledge gained from this research will better prepare mine operations for potential methane inflows, thus improving mine safety.

Chiquicamata Mine, Chile

NASA Image and Video Library

2016-08-24

Chuquicamata, in Chile's Atacama Desert, is the largest open pit copper mine in the world, by excavated volume. The copper deposits were first exploited in pre-Hispanic times. Open pit mining began in the early 20th century when a method was developed to work low grade oxidized copper ores. The image was acquired September 2, 2007, covers an area of 19.5 by 29.3 km, and is located at 22.1 degrees south, 68.9 degrees west. http://photojournal.jpl.nasa.gov/catalog/PIA20973

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

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

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Monitoring of ground movement in open pit iron mines of Carajás Province (Amazon region) based on A-DInSAR techniques using TerraSAR-X data

NASA Astrophysics Data System (ADS)

Silva, Guilherme Gregório; Mura, José Claudio; Paradella, Waldir Renato; Gama, Fabio Furlan; Temporim, Filipe Altoé

2017-04-01

Persistent scatterer interferometry (PSI) analysis of a large area is always a challenging task regarding the removal of the atmospheric phase component. This work presents an investigation of ground movement measurements based on a combination of differential SAR interferometry time-series (DTS) and PSI techniques, applied on a large area of extent with open pit iron mines located in Carajás (Brazilian Amazon Region), aiming at detecting linear and nonlinear ground movement. These mines have presented a history of instability, and surface monitoring measurements over sectors of the mines (pit walls) have been carried out based on ground-based radar and total station (prisms). Using a priori information regarding the topographic phase error and a phase displacement model derived from DTS, temporal phase unwrapping in the PSI processing and the removal of the atmospheric phases can be performed more efficiently. A set of 33 TerraSAR-X (TSX-1) images, acquired during the period from March 2012 to April 2013, was used to perform this investigation. The DTS analysis was carried out on a stack of multilook unwrapped interferograms using an extension of SVD to obtain the least-square solution. The height errors and deformation rates provided by the DTS approach were subtracted from the stack of interferograms to perform the PSI analysis. This procedure improved the capability of the PSI analysis for detecting high rates of deformation, as well as increased the numbers of point density of the final results. The proposed methodology showed good results for monitoring surface displacement in a large mining area, which is located in a rain forest environment, providing very useful information about the ground movement for planning and risk control.

Monitoring of surface movement in a large area of the open pit iron mines (Carajás, Brazil) based on A-DInSAR techniques using TerraSAR-X data

NASA Astrophysics Data System (ADS)

Mura, José C.; Paradella, Waldir R.; Gama, Fabio F.; Silva, Guilherme G.

2016-10-01

PSI (Persistent Scatterer Interferometry) analysis of large area is always a challenging task regarding the removal of the atmospheric phase component. This work presents an investigation of ground deformation measurements based on a combination of DInSAR Time-Series (DTS) and PSI techniques, applied in a large area of open pit iron mines located in Carajás (Brazilian Amazon Region), aiming at detect high rates of linear and nonlinear ground deformation. These mines have presented a historical of instability and surface monitoring measurements over sectors of the mines (pit walls) have been carried out based on ground based radar and total station (prisms). By using a priori information regarding the topographic phase error and phase displacement model derived from DTS, temporal phase unwrapping in the PSI processing and the removal of the atmospheric phases can be performed more efficiently. A set of 33 TerraSAR-X-1 images, acquired during the period from March 2012 to April 2013, was used to perform this investigation. The DTS analysis was carried out on a stack of multi-look unwrapped interferogram using an extension of SVD to obtain the Least-Square solution. The height errors and deformation rates provided by the DTS approach were subtracted from the stack of interferogram to perform the PSI analysis. This procedure improved the capability of the PSI analysis to detect high rates of deformation as well as increased the numbers of point density of the final results. The proposed methodology showed good results for monitoring surface displacement in a large mining area, which is located in a rain forest environment, providing very useful information about the ground movement for planning and risks control.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Total Factor Productivity Growth, Technical Progress & Efficiency Change in Vietnam Coal Industry - Nonparametric Approach

NASA Astrophysics Data System (ADS)

Phuong, Vu Hung

2018-03-01

This research applies Data Envelopment Analysis (DEA) approach to analyze Total Factor Productivity (TFP) and efficiency changes in Vietnam coal mining industry from 2007 to 2013. The TFP of Vietnam coal mining companies decreased due to slow technological progress and unimproved efficiency. The decadence of technical efficiency in many enterprises proved that the coal mining industry has a large potential to increase productivity through technical efficiency improvement. Enhancing human resource training, technology and research & development investment could help the industry to improve efficiency and productivity in Vietnam coal mining industry.

Remediation of an acidic mine spoil: Miscanthus biochar and lime amendment affects metal availability, plant growth and soil enzymatic activity

USDA-ARS?s Scientific Manuscript database

Biochar is proposed as an amendment for mine spoil remediation; however, its effectiveness at achieving this goal remains unclear. Miscanthus (Miscanthus giganteus) biochar was tested for potentially improving acidic mine spoil (pH < 3; Formosa mine near Riddle, Oregon) health conditions by sequeste...

Combined DC resistivity and induced polarization (DC-IP) for mapping the internal composition of a mine waste rock pile in Nova Scotia, Canada

NASA Astrophysics Data System (ADS)

Power, Christopher; Tsourlos, Panagiotis; Ramasamy, Murugan; Nivorlis, Aristeidis; Mkandawire, Martin

2018-03-01

Mine waste rock piles (WRPs) can contain sulfidic minerals whose interaction with oxygen and water can generate acid mine drainage (AMD). Thus, WRPs can be a long-term source of environmental pollution. Since the generation of AMD and its release into the environment is dependent on the net volume and bulk composition of waste rock, effective characterization of WRPs is necessary for successful remedial design and monitoring. In this study, a combined DC resistivity and induced polarization (DC-IP) approach was employed to characterize an AMD-generating WRP in the Sydney Coalfield, Nova Scotia, Canada. Two-dimensional (2D) DC-IP imaging with 6 survey lines was performed to capture the full WRP landform. 2D DC results indicated a highly heterogeneous and moderately conductive waste rock underlain by a resistive bedrock containing numerous fractures. 2D IP (chargeability) results identified several highly-chargeable regions within the waste, with normalized chargeability delineating regions specific to waste mineralogy only. Three-dimensional (3D) DC-IP imaging, using 17 parallel lines on the plateau of the pile, was then used to focus on the composition of the waste rock. The full 3D inverted DC-IP distributions were used to identify coincident and continuous zones (isosurfaces) of low resistivity (<30 Ω-m) and high normalized chargeability (>0.4 mS/m) that were inferred as generated AMD (leachate) and stored AMD (sulfides), respectively. Integrated geological, hydrogeological and geochemical data increased confidence in the geoelectrical interpretations. Knowledge on the location of potentially more reactive waste material is extremely valuable for improved long-term AMD monitoring at the WRP.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-28

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-26

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

Content-Based Indexing and Teaching Focus Mining for Lecture Videos

ERIC Educational Resources Information Center

Lin, Yu-Tzu; Yen, Bai-Jang; Chang, Chia-Hu; Lee, Greg C.; Lin, Yu-Chih

2010-01-01

Purpose: The purpose of this paper is to propose an indexing and teaching focus mining system for lecture videos recorded in an unconstrained environment. Design/methodology/approach: By applying the proposed algorithms in this paper, the slide structure can be reconstructed by extracting slide images from the video. Instead of applying…

Mind your crossings: Mining GIS imagery for crosswalk localization.

PubMed

Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M; Mascetti, Sergio

2017-04-01

For blind travelers, finding crosswalks and remaining within their borders while traversing them is a crucial part of any trip involving street crossings. While standard Orientation & Mobility (O&M) techniques allow blind travelers to safely negotiate street crossings, additional information about crosswalks and other important features at intersections would be helpful in many situations, resulting in greater safety and/or comfort during independent travel. For instance, in planning a trip a blind pedestrian may wish to be informed of the presence of all marked crossings near a desired route. We have conducted a survey of several O&M experts from the United States and Italy to determine the role that crosswalks play in travel by blind pedestrians. The results show stark differences between survey respondents from the U.S. compared with Italy: the former group emphasized the importance of following standard O&M techniques at all legal crossings (marked or unmarked), while the latter group strongly recommended crossing at marked crossings whenever possible. These contrasting opinions reflect differences in the traffic regulations of the two countries and highlight the diversity of needs that travelers in different regions may have. To address the challenges faced by blind pedestrians in negotiating street crossings, we devised a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm can be improved by a final crowdsourcing validation. To this end, we developed a Pedestrian Crossing Human Validation (PCHV) web service, which supports crowdsourcing to rule out false positives and identify false negatives.

Mind your crossings: Mining GIS imagery for crosswalk localization

PubMed Central

Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M.; Mascetti, Sergio

2017-01-01

For blind travelers, finding crosswalks and remaining within their borders while traversing them is a crucial part of any trip involving street crossings. While standard Orientation & Mobility (O&M) techniques allow blind travelers to safely negotiate street crossings, additional information about crosswalks and other important features at intersections would be helpful in many situations, resulting in greater safety and/or comfort during independent travel. For instance, in planning a trip a blind pedestrian may wish to be informed of the presence of all marked crossings near a desired route. We have conducted a survey of several O&M experts from the United States and Italy to determine the role that crosswalks play in travel by blind pedestrians. The results show stark differences between survey respondents from the U.S. compared with Italy: the former group emphasized the importance of following standard O&M techniques at all legal crossings (marked or unmarked), while the latter group strongly recommended crossing at marked crossings whenever possible. These contrasting opinions reflect differences in the traffic regulations of the two countries and highlight the diversity of needs that travelers in different regions may have. To address the challenges faced by blind pedestrians in negotiating street crossings, we devised a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm can be improved by a final crowdsourcing validation. To this end, we developed a Pedestrian Crossing Human Validation (PCHV) web service, which supports crowdsourcing to rule out false positives and identify false negatives. PMID:28757907

Using optical flow for the detection of floating mines in IR image sequences

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Acheroy, Marc

2006-09-01

In the first Gulf War, unmoored floating mines proved to be a real hazard for shipping traffic. An automated system capable of detecting these and other free-floating small objects, using readily available sensors such as infra-red cameras, would prove to be a valuable mine-warfare asset, and could double as a collision avoidance mechanism, and a search-and-rescue aid. The noisy background provided by the sea surface, and occlusion by waves make it difficult to detect small floating objects using only algorithms based upon the intensity, size or shape of the target. This leads us to look at the sequence of images for temporal detection characteristics. The target's apparent motion is such a determinant, given the contrast between the bobbing motion of the floating object and the strong horizontal component present in the propagation of the wavefronts. We have applied the Proesmans optical flow algorithm to IR video footage of practice mines, in order to extract the motion characteristic and a threshold on the vertical motion characteristic is then imposed to detect the floating targets.

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.

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

PubMed

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

2013-08-01

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

Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

NASA Technical Reports Server (NTRS)

Krohn, M. Dennis

1986-01-01

The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

The influence of the scale of mining activity and mine site remediation on the contamination legacy of historical metal mining activity.

PubMed

Bird, Graham

2016-12-01

Globally, thousands of kilometres of rivers are degraded due to the presence of elevated concentrations of potentially harmful elements (PHEs) sourced from historical metal mining activity. In many countries, the presence of contaminated water and river sediment creates a legal requirement to address such problems. Remediation of mining-associated point sources has often been focused upon improving river water quality; however, this study evaluates the contaminant legacy present within river sediments and attempts to assess the influence of the scale of mining activity and post-mining remediation upon the magnitude of PHE contamination found within contemporary river sediments. Data collected from four exemplar catchments indicates a strong relationship between the scale of historical mining, as measured by ore output, and maximum PHE enrichment factors, calculated versus environmental quality guidelines. The use of channel slope as a proxy measure for the degree of channel-floodplain coupling indicates that enrichment factors for PHEs in contemporary river sediments may also be the highest where channel-floodplain coupling is the greatest. Calculation of a metric score for mine remediation activity indicates no clear influence of the scale of remediation activity and PHE enrichment factors for river sediments. It is suggested that whilst exemplars of significant successes at improving post-remediation river water quality can be identified; river sediment quality is a much more long-lasting environmental problem. In addition, it is suggested that improvements to river sediment quality do not occur quickly or easily as a result of remediation actions focused a specific mining point sources. Data indicate that PHEs continue to be episodically dispersed through river catchments hundreds of years after the cessation of mining activity, especially during flood flows. The high PHE loads of flood sediments in mining-affected river catchments and the predicted changes to flood frequency, especially, in many river catchments, provides further evidence of the need to enact effective mine remediation strategies and to fully consider the role of river sediments in prolonging the environmental legacy of historical mine sites.

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.

Categorizing biomedicine images using novel image features and sparse coding representation

PubMed Central

2013-01-01

Background Images embedded in biomedical publications carry rich information that often concisely summarize key hypotheses adopted, methods employed, or results obtained in a published study. Therefore, they offer valuable clues for understanding main content in a biomedical publication. Prior studies have pointed out the potential of mining images embedded in biomedical publications for automatically understanding and retrieving such images' associated source documents. Within the broad area of biomedical image processing, categorizing biomedical images is a fundamental step for building many advanced image analysis, retrieval, and mining applications. Similar to any automatic categorization effort, discriminative image features can provide the most crucial aid in the process. Method We observe that many images embedded in biomedical publications carry versatile annotation text. Based on the locations of and the spatial relationships between these text elements in an image, we thus propose some novel image features for image categorization purpose, which quantitatively characterize the spatial positions and distributions of text elements inside a biomedical image. We further adopt a sparse coding representation (SCR) based technique to categorize images embedded in biomedical publications by leveraging our newly proposed image features. Results we randomly selected 990 images of the JPG format for use in our experiments where 310 images were used as training samples and the rest were used as the testing cases. We first segmented 310 sample images following the our proposed procedure. This step produced a total of 1035 sub-images. We then manually labeled all these sub-images according to the two-level hierarchical image taxonomy proposed by [1]. Among our annotation results, 316 are microscopy images, 126 are gel electrophoresis images, 135 are line charts, 156 are bar charts, 52 are spot charts, 25 are tables, 70 are flow charts, and the remaining 155 images are of the type "others". A serial of experimental results are obtained. Firstly, each image categorizing results is presented, and next image categorizing performance indexes such as precision, recall, F-score, are all listed. Different features which include conventional image features and our proposed novel features indicate different categorizing performance, and the results are demonstrated. Thirdly, we conduct an accuracy comparison between support vector machine classification method and our proposed sparse representation classification method. At last, our proposed approach is compared with three peer classification method and experimental results verify our impressively improved performance. Conclusions Compared with conventional image features that do not exploit characteristics regarding text positions and distributions inside images embedded in biomedical publications, our proposed image features coupled with the SR based representation model exhibit superior performance for classifying biomedical images as demonstrated in our comparative benchmark study. PMID:24565470

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

NASA Astrophysics Data System (ADS)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Detecting Underground Mine Voids Using Complex Geophysical Techniques

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

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

2006-12-01

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

Data mining learning bootstrap through semantic thumbnail analysis

NASA Astrophysics Data System (ADS)

Battiato, Sebastiano; Farinella, Giovanni Maria; Giuffrida, Giovanni; Tribulato, Giuseppe

2007-01-01

The rapid increase of technological innovations in the mobile phone industry induces the research community to develop new and advanced systems to optimize services offered by mobile phones operators (telcos) to maximize their effectiveness and improve their business. Data mining algorithms can run over data produced by mobile phones usage (e.g. image, video, text and logs files) to discover user's preferences and predict the most likely (to be purchased) offer for each individual customer. One of the main challenges is the reduction of the learning time and cost of these automatic tasks. In this paper we discuss an experiment where a commercial offer is composed by a small picture augmented with a short text describing the offer itself. Each customer's purchase is properly logged with all relevant information. Upon arrival of new items we need to learn who the best customers (prospects) for each item are, that is, the ones most likely to be interested in purchasing that specific item. Such learning activity is time consuming and, in our specific case, is not applicable given the large number of new items arriving every day. Basically, given the current customer base we are not able to learn on all new items. Thus, we need somehow to select among those new items to identify the best candidates. We do so by using a joint analysis between visual features and text to estimate how good each new item could be, that is, whether or not is worth to learn on it. Preliminary results show the effectiveness of the proposed approach to improve classical data mining techniques.

The Application of LANDSAT Multi-Temporal Thermal Infrared Data to Identify Coal Fire in the Khanh Hoa Coal Mine, Thai Nguyen province, Vietnam

NASA Astrophysics Data System (ADS)

Trinh, Le Hung; Zablotskii, V. R.

2017-12-01

The Khanh Hoa coal mine is a surface coal mine in the Thai Nguyen province, which is one of the largest deposits of coal in the Vietnam. Numerous reasons such as improper mining techniques and policy, as well as unauthorized mining caused surface and subsurface coal fire in this area. Coal fire is a dangerous phenomenon which affects the environment seriously by releasing toxic fumes which causes forest fires, and subsidence of infrastructure surface. This article presents study on the application of LANDSAT multi-temporal thermal infrared images, which help to detect coal fire. The results obtained in this study can be used to monitor fire zones so as to give warnings and solutions to prevent coal fire.

InSAR Monitoring OF Landslides In Britain: BGS' Feasibility Map And First ISBAS Studies Over The South Wales Coalfield

NASA Astrophysics Data System (ADS)

Cigna, F.; Bateson, L.; Dashwood, C.; Jordan, C. J.; Sowter, A.; Boon, D.

2013-12-01

InSAR is an accepted method for monitoring ground motion, however its applicability in non-urban areas is generally limited except for rocky terrains. This paper investigates a new method for deriving improved results outside the urban environment. Topographic distortions to the ERS-1/2 and ENVISAT SAR acquisition modes are simulated based on high resolution DTMs of the landmass of Britain. Persistent Scatterers (PS) densities are predicted by calibrating the CORINE Land Cover 2006 dataset using PS data available via the ESA Terrafirma and EC FP7 PanGeo projects. The InSAR feasibility to monitor land motions is discussed for the South Wales Coalfield, and the Intermittent Small Baseline Subset (ISBAS) technique is tested over the Coalfield using 55 ERS-1/2 images (1992-1999). With unprecedented target coverage, ISBAS reveals up to 1cm/yr uplift in areas of former coal mining, likely associated with groundwater rebound following cessation of mine water pumping.

Remote Sensing Image Classification Applied to the First National Geographical Information Census of China

NASA Astrophysics Data System (ADS)

Yu, Xin; Wen, Zongyong; Zhu, Zhaorong; Xia, Qiang; Shun, Lan

2016-06-01

Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN) to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC) and Maximum Likelihood Classification Method (MLC) in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

An application of data mining in district heating substations for improving energy performance

NASA Astrophysics Data System (ADS)

Xue, Puning; Zhou, Zhigang; Chen, Xin; Liu, Jing

2017-11-01

Automatic meter reading system is capable of collecting and storing a huge number of district heating (DH) data. However, the data obtained are rarely fully utilized. Data mining is a promising technology to discover potential interesting knowledge from vast data. This paper applies data mining methods to analyse the massive data for improving energy performance of DH substation. The technical approach contains three steps: data selection, cluster analysis and association rule mining (ARM). Two-heating-season data of a substation are used for case study. Cluster analysis identifies six distinct heating patterns based on the primary heat of the substation. ARM reveals that secondary pressure difference and secondary flow rate have a strong correlation. Using the discovered rules, a fault occurring in remote flow meter installed at secondary network is detected accurately. The application demonstrates that data mining techniques can effectively extrapolate potential useful knowledge to better understand substation operation strategies and improve substation energy performance.

Improving machine operation management efficiency via improving the vehicle park structure and using the production operation information database

NASA Astrophysics Data System (ADS)

Koptev, V. Yu

2017-02-01

The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

Object-based image analysis for the assessment of mineral extraction in conflict regions - a case study in the Democratic Republic of the Congo

NASA Astrophysics Data System (ADS)

Kranz, Olaf; Schoepfer, Elisabeth; Spröhnle, Kristin; Lang, Stefan

2016-06-01

In this study object-based image analysis (OBIA) techniques were applied to assess land cover changes related to mineral extraction in a conflict-affected area of the eastern Democratic Republic of the Congo (DRC) over a period of five years based on very high resolution (VHR) satellite data of different sensors. Object-based approaches explicitly consider spatio-temporal aspects which allow extracting important information to document mining activities. The use of remote sensing data as an independent, up-to-date and reliable data source provided hints on the general development of the mining sector in relation to socio-economic and political decisions. While in early 2010, the situation was still characterised by an intensification of mineral extraction, a mining ban between autumn 2010 and spring 2011 marked the starting point for a continuous decrease of mining activities. The latter can be substantiated through a decrease in the extend of the mining area as well as of the number of dwellings in the nearby settlement. A following demilitarisation and the mentioned need for accountability with respect to the origin of certain minerals led to organised, more industrialized exploitation. This development is likewise visible on satellite imagery as typical clearings within forested areas. The results of the continuous monitoring in turn facilitate non-governmental organisations (NGOs) to further foster the mentioned establishment of responsible supply chains by the mining industry throughout the entire period of investigation.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Machine learning and data mining advance predictive big data analysis in precision animal agriculture.

PubMed

Morota, Gota; Ventura, Ricardo V; Silva, Fabyano F; Koyama, Masanori; Fernando, Samodha C

2018-04-14

Precision animal agriculture is poised to rise to prominence in the livestock enterprise in the domains of management, production, welfare, sustainability, health surveillance, and environmental footprint. Considerable progress has been made in the use of tools to routinely monitor and collect information from animals and farms in a less laborious manner than before. These efforts have enabled the animal sciences to embark on information technology-driven discoveries to improve animal agriculture. However, the growing amount and complexity of data generated by fully automated, high-throughput data recording or phenotyping platforms, including digital images, sensor and sound data, unmanned systems, and information obtained from real-time noninvasive computer vision, pose challenges to the successful implementation of precision animal agriculture. The emerging fields of machine learning and data mining are expected to be instrumental in helping meet the daunting challenges facing global agriculture. Yet, their impact and potential in "big data" analysis have not been adequately appreciated in the animal science community, where this recognition has remained only fragmentary. To address such knowledge gaps, this article outlines a framework for machine learning and data mining and offers a glimpse into how they can be applied to solve pressing problems in animal sciences.

Performance potential of the coal strip mining in the east of Russia

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

Cheskidov, V.I.

2007-07-15

The potentialities of the leading mining districts in Russia to improve coal production by strip mining are analyzed. The operational issues of the Erunakovskiy (Kuzbass), Kansko-Achinskiy and South Yakutia territorial production complexes are considered.

Longevity of acid discharges from underground mines located above the regional water table.

PubMed

Demchak, J; Skousen, J; McDonald, L M

2004-01-01

The duration of acid mine drainage flowing out of underground mines is important in the design of watershed restoration and abandoned mine land reclamation projects. Past studies have reported that acid water flows from underground mines for hundreds of years with little change, while others state that poor drainage quality may last only 20 to 40 years. More than 150 above-drainage (those not flooded after abandonment) underground mine discharges from Pittsburgh and Upper Freeport coal seams were located and sampled during 1968 in northern West Virginia, and we revisited 44 of those sites in 1999-2000 and measured water flow, pH, acidity, Fe, sulfate, and conductivity. We found no significant difference in flows between 1968 and 1999-2000. Therefore, we felt the water quality data could be compared and the data represented real changes in pollutant concentrations. There were significant water quality differences between year and coal seam, but no effect of disturbance. While pH was not significantly improved, average total acidity declined 79% between 1968 and 1999-2000 in Pittsburgh mines (from 66.8 to 14 mmol H+ L(-1)) and 56% in Upper Freeport mines (from 23.8 to 10.4 mmol H+ L(-1)). Iron decreased an average of about 80% across all sites (from an average of 400 to 72 mg L(-1)), while sulfate decreased between 50 and 75%. Pittsburgh seam discharge water was much worse in 1968 than Upper Freeport seam water. Twenty of our 44 sites had water quality information in 1980, which served as a midpoint to assess the slope of the decline in acidity and metal concentrations. Five of 20 sites (25%) showed an apparent exponential rate of decline in acidity and iron, while 10 of 20 sites (50%) showed a more linear decline. Drainage from five Upper Freeport sites increased in acidity and iron. While it is clear that surface mines and below-drainage underground mines improve in discharge quality relatively rapidly (20-40 years), above-drainage underground mines are not as easily predicted. In total, the drainage from 34 out of 44 (77%) above-drainage underground mines showed significant improvement in acidity over time, some exponentially and some linearly. Ten discharges showed no improvement and three of these got much worse.

Protective and control relays as coal-mine power-supply ACS subsystem

NASA Astrophysics Data System (ADS)

Kostin, V. N.; Minakova, T. E.

2017-10-01

The paper presents instantaneous selective short-circuit protection for the cabling of the underground part of a coal mine and central control algorithms as a Coal-Mine Power-Supply ACS Subsystem. In order to improve the reliability of electricity supply and reduce the mining equipment down-time, a dual channel relay protection and central control system is proposed as a subsystem of the coal-mine power-supply automated control system (PS ACS).

Applications of Subsurface Radar for Mine Detection

DTIC Science & Technology

1990-12-31

sofware routines for signal/image processing and image display, which are included in the Appendix along with examples of recent images obtained of the... maxima and minima. The case of the M19 shown a main backscattering lobe only 5* wide. These results demonstrate the realiability and consistency of

Safety Psychology Applicating on Coal Mine Safety Management Based on Information System

NASA Astrophysics Data System (ADS)

Hou, Baoyue; Chen, Fei

In recent years, with the increase of intensity of coal mining, a great number of major accidents happen frequently, the reason mostly due to human factors, but human's unsafely behavior are affected by insecurity mental control. In order to reduce accidents, and to improve safety management, with the help of application security psychology, we analyse the cause of insecurity psychological factors from human perception, from personality development, from motivation incentive, from reward and punishment mechanism, and from security aspects of mental training , and put forward countermeasures to promote coal mine safety production,and to provide information for coal mining to improve the level of safety management.

75 FR 63518 - Notice of Availability of Environmental Assessment and Finding of No Significant Impact for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-15

... Environmental Assessment and Finding of No Significant Impact for License Amendment No. 61 for Rio Algom Mining... amendment to Source Materials License SUA-1473 issued to Rio Algom Mining LLC (Rio Algom, or the Licensee... access the NRC's Agencywide Document Access and Management System (ADAMS), which provides text and image...

Biological responses to disturbance from simulated deep-sea polymetallic nodule mining.

PubMed

Jones, Daniel O B; Kaiser, Stefanie; Sweetman, Andrew K; Smith, Craig R; Menot, Lenaick; Vink, Annemiek; Trueblood, Dwight; Greinert, Jens; Billett, David S M; Arbizu, Pedro Martinez; Radziejewska, Teresa; Singh, Ravail; Ingole, Baban; Stratmann, Tanja; Simon-Lledó, Erik; Durden, Jennifer M; Clark, Malcolm R

2017-01-01

Commercial-scale mining for polymetallic nodules could have a major impact on the deep-sea environment, but the effects of these mining activities on deep-sea ecosystems are very poorly known. The first commercial test mining for polymetallic nodules was carried out in 1970. Since then a number of small-scale commercial test mining or scientific disturbance studies have been carried out. Here we evaluate changes in faunal densities and diversity of benthic communities measured in response to these 11 simulated or test nodule mining disturbances using meta-analysis techniques. We find that impacts are often severe immediately after mining, with major negative changes in density and diversity of most groups occurring. However, in some cases, the mobile fauna and small-sized fauna experienced less negative impacts over the longer term. At seven sites in the Pacific, multiple surveys assessed recovery in fauna over periods of up to 26 years. Almost all studies show some recovery in faunal density and diversity for meiofauna and mobile megafauna, often within one year. However, very few faunal groups return to baseline or control conditions after two decades. The effects of polymetallic nodule mining are likely to be long term. Our analyses show considerable negative biological effects of seafloor nodule mining, even at the small scale of test mining experiments, although there is variation in sensitivity amongst organisms of different sizes and functional groups, which have important implications for ecosystem responses. Unfortunately, many past studies have limitations that reduce their effectiveness in determining responses. We provide recommendations to improve future mining impact test studies. Further research to assess the effects of test-mining activities will inform ways to improve mining practices and guide effective environmental management of mining activities.

Biological responses to disturbance from simulated deep-sea polymetallic nodule mining

PubMed Central

Kaiser, Stefanie; Sweetman, Andrew K.; Smith, Craig R.; Menot, Lenaick; Vink, Annemiek; Trueblood, Dwight; Greinert, Jens; Billett, David S. M.; Arbizu, Pedro Martinez; Radziejewska, Teresa; Singh, Ravail; Ingole, Baban; Stratmann, Tanja; Simon-Lledó, Erik; Durden, Jennifer M.; Clark, Malcolm R.

2017-01-01

Commercial-scale mining for polymetallic nodules could have a major impact on the deep-sea environment, but the effects of these mining activities on deep-sea ecosystems are very poorly known. The first commercial test mining for polymetallic nodules was carried out in 1970. Since then a number of small-scale commercial test mining or scientific disturbance studies have been carried out. Here we evaluate changes in faunal densities and diversity of benthic communities measured in response to these 11 simulated or test nodule mining disturbances using meta-analysis techniques. We find that impacts are often severe immediately after mining, with major negative changes in density and diversity of most groups occurring. However, in some cases, the mobile fauna and small-sized fauna experienced less negative impacts over the longer term. At seven sites in the Pacific, multiple surveys assessed recovery in fauna over periods of up to 26 years. Almost all studies show some recovery in faunal density and diversity for meiofauna and mobile megafauna, often within one year. However, very few faunal groups return to baseline or control conditions after two decades. The effects of polymetallic nodule mining are likely to be long term. Our analyses show considerable negative biological effects of seafloor nodule mining, even at the small scale of test mining experiments, although there is variation in sensitivity amongst organisms of different sizes and functional groups, which have important implications for ecosystem responses. Unfortunately, many past studies have limitations that reduce their effectiveness in determining responses. We provide recommendations to improve future mining impact test studies. Further research to assess the effects of test-mining activities will inform ways to improve mining practices and guide effective environmental management of mining activities. PMID:28178346

Electrical Resistivity Imaging

EPA Science Inventory

Electrical resistivity imaging (ERI) is a geophysical method originally developed within the mining industry where it has been used for decades to explore for and characterize subsurface mineral deposits. It is one of the oldest geophysical methods with the first documented usag...

From chemical risk assessment to environmental resources management: the challenge for mining.

PubMed

Voulvoulis, Nikolaos; Skolout, John W F; Oates, Christopher J; Plant, Jane A

2013-11-01

On top of significant improvements and progress made through science and engineering in the last century to increase efficiency and reduce impacts of mining to the environment, risk assessment has an important role to play in further reducing such impacts and preventing and mitigating risks. This paper reflects on how risk assessment can improve planning, monitoring and management in mining and mineral processing operations focusing on the importance of better understanding source-pathway-receptor linkages for all stages of mining. However, in light of the ever-growing consumption and demand for raw materials from mining, the need to manage environmental resources more sustainably is becoming increasingly important. The paper therefore assesses how mining can form an integral part of wider sustainable resources management, with the need for re-assessing the potential of mining in the context of sustainable management of natural capital, and with a renewed focus on its the role from a systems perspective. The need for understanding demand and pressure on resources, followed by appropriate pricing that is inclusive of all environmental costs, with new opportunities for mining in the wastes we generate, is also discussed. Findings demonstrate the need for a life cycle perspective in closing the loop between mining, production, consumption and waste generation as the way forward.

Fracture mapping and strip mine inventory in the Midwest by using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wier, C. W.; Wobber, F. J.; Russell, O. R.; Amato, R. V.

1973-01-01

Analysis of the ERTS-1 imagery and high-altitude infrared photography indicates that useful fracture data can be obtained in Indiana and Illinois despite a glacial till cover. ERTS MSS bands 5 and 7 have proven most useful for fracture mapping in coal-bearing rocks in this region. Preliminary results suggest a reasonable correlation between image-detected fractures and mine roof-fall accidents. Information related to surface mined land, such as disturbed area, water bodies, and kind of reclamation, has been derived from the analysis of ERTS imagery.

Multiple comparisons permutation test for image based data mining in radiotherapy

PubMed Central

2013-01-01

Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy. PMID:24365155

Competition between agricultural, urban, and sand-mining areas at the Paraíba do Sul basin in southeastern Brazil

NASA Astrophysics Data System (ADS)

Ronquim, Carlos C.; Cordeiro, Guilherme P. L.; Amorim, Mariana de; de C. Teixeira, Antônio H.; Leivas, Janice F.; Galdino, Sergio

2017-10-01

This work was performed in the Paraíba do Sul basin, within the limits of the São Paulo state, southeastern Brazil, in order to assess the dynamics of the land-use and land-cover changes at the Paraíba do Sul river's floodplains between 1985 and 2016. We focused on investigating the development of agricultural areas used for the production of wetland rice and of areas featuring artificial lakes produced by sand mining. We mapped the land cover in 1985 using images made by the Landsat 5 satellite's Moderate Resolution Imaging Spectroradiometer (MODIS) and Thematic Mapper (TM) sensors, which were segmented to produce vectors featuring homogeneous characteristics, and which were classified by means of visual interpretation. Similarly, we applied the maximum likelihood classification and used spectral curve inserts and adjustments to study and analyze the same area using a Landsat 8's Operational Land Imager (OLI) image made in 2016. Our results show significant reduction of areas used for rice crops, and increase in areas featuring sandmining pits. The rice crop areas decreased approximately 43% from 24,131.4 ha in 1985 to 13,789.8 ha in 2016. Over this 30-year period, the area covered by sand-mining lakes increased from 615 ha to 3,876 ha (+ 630%), and the number of lakes increased from 54 to 316. Sand mining and urbanization are the main factors causing the reduction in wetland rice areas. The absence of environmental management actions at the basin interferes with the rice production, which depends on the Paraíba do Sul river's floodplains.

Mapping Weathering and Alteration Minerals in the Comstock and Geiger Grade Areas using Visible to Thermal Infrared Airborne Remote Sensing Data

NASA Technical Reports Server (NTRS)

Vaughan, Greg R.; Calvin, Wendy M.

2005-01-01

To support research into both precious metal exploration and environmental site characterization a combination of high spatial/spectral resolution airborne visible, near infrared, short wave infrared (VNIR/SWIR) and thermal infrared (TIR) image data were acquired to remotely map hydrothermal alteration minerals around the Geiger Grade and Comstock alteration regions, and map the mineral by-products of weathered mine dumps in Virginia City. Remote sensing data from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), SpecTIR Corporation's airborne hyperspectral imager (HyperSpecTIR), the MODIS-ASTER airborne simulator (MASTER), and the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) were acquired and processed into mineral maps based on the unique spectral signatures of image pixels. VNIR/SWIR and TIR field spectrometer data were collected for both calibration and validation of the remote data sets, and field sampling, laboratory spectral analyses and XRD analyses were made to corroborate the surface mineralogy identified by spectroscopy. The resulting mineral maps show the spatial distribution of several important alteration minerals around each study area including alunite, quartz, pyrophyllite, kaolinite, montmorillonite/muscovite, and chlorite. In the Comstock region the mineral maps show acid-sulfate alteration, widespread propylitic alteration and extensive faulting that offsets the acid-sulfate areas, in contrast to the larger, dominantly acid-sulfate alteration exposed along Geiger Grade. Also, different mineral zones within the intense acid-sulfate areas were mapped. In the Virginia City historic mining district the important weathering minerals mapped include hematite, goethite, jarosite and hydrous sulfate minerals (hexahydrite, alunogen and gypsum) located on mine dumps. Sulfate minerals indicate acidic water forming in the mine dump environment. While there is not an immediate threat to the community, there are clearly sources of acidic drainage that were identified remotely.

Germination of Blue Wildrye in Biochar Treated Mining Impacted Soils

EPA Science Inventory

Stabilization of mine sites with vegetation is an important management strategy to reduce metal movement off-site. Plant growth, however, is often hampered by poor soil conditions. Biochar is a novel soil amendment that may improve soil health conditions and improve plant growt...

Direct imaging of explosives.

PubMed

Knapp, E A; Moler, R B; Saunders, A W; Trower, W P

2000-01-01

Any technique that can detect nitrogen concentrations can screen for concealed explosives. However, such a technique would have to be insensitive to metal, both encasing and incidental. If images of the nitrogen concentrations could be captured, then, since form follows function, a robust screening technology could be developed. However these images would have to be sensitive to the surface densities at or below that of the nitrogen contained in buried anti-personnel mines or of the SEMTEX that brought down Pan Am 103, approximately 200 g. Although the ability to image in three-dimensions would somewhat reduce false positives, capturing collateral images of carbon and oxygen would virtually assure that nitrogenous non-explosive material like fertilizer, Melmac dinnerware, and salami could be eliminated. We are developing such an instrument, the Nitrogen Camera, which has met experimentally these criteria with the exception of providing oxygen images, which awaits the availability of a sufficiently energetic light source. Our Nitrogen Camera technique uses an electron accelerator to produce photonuclear reactions whose unique decays it registers. Clearly if our Nitrogen Camera is made mobile, it could be effective in detecting buried mines, either in an active battlefield situation or in the clearing of abandoned military munitions. Combat operations require that a swathe the width of an armored vehicle, 5 miles deep, be screened in an hour, which is within our camera's scanning speed. Detecting abandoned munitions is technically easier as it is free from the onerous speed requirement. We describe here our Nitrogen Camera and show its 180 pixel intensity images of elemental nitrogen in a 200 g mine simulant and in a 125 g stick of SEMTEX. We also report on our progress in creating a lorry transportable 70 MeV electron racetrack microtron, the principal enabling technology that will allow our Nitrogen Camera to be deployed in the field.

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

NASA Astrophysics Data System (ADS)

Baertlein, Brian A.; Liao, Wen-Jiao

2000-08-01

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

Temporal and spatial changes of land use and landscape in a coal mining area in Xilingol grassland

NASA Astrophysics Data System (ADS)

Guan, Chunzhu; Zhang, Baolin; Li, Jiannan; Zhao, Junling

2017-01-01

Coal mining, particularly surface mining, inevitably disturbs land. According to Landsat images acquired over Xilingol grassland in 2005, 2009 and 2015, land uses were divided into seven classes, i. e., open stope, stripping area, waste-dump area, mine industrial area, farmland, urban area and the original landscape (grassland), using supervised classification and human-computer interactive interpretation. The overall classification accuracies were 97.72 %, 98.43 % and 96.73 %, respectively; the Kappa coefficients were 0.95, 0.97 and 0.95, respectively. Analysis on LUCC (Land Use and Cover Change) showed that surface coal mining disturbed grassland ecosystem: grassland decreased by 8661.15 hm2 in 2005-2015. The area and proportion of mining operation areas (open stope, stripping area, waste-dump area, mine industrial field) increased, but those of grassland decreased continuously. Transfer matrix of land use changes showed that waste-dump had the largest impacts in mining disturbance, and that effective reclamation of waste-dump areas would mitigate eco-environment destruction, as would be of great significance to protect fragile grassland eco-system. Six landscape index showed that landscape fragmentation increased, and the influences of human activity on landscape was mainly reflected in the expansion of mining area and urban area. Remote sensing monitoring of coal surface mining in grassland would accurately demonstrate the dynamics and trend of LUCC, providing scientific supports for ecological reconstruction in surface mining area.

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.

Assessment of the environmental effects of mining using SPOT-Vegetation NDVI

NASA Astrophysics Data System (ADS)

Tote, C.; Swinnen, E.; Goossens, M.; Reusen, I.; Delalieux, S.

2012-04-01

Within the ImpactMin project, funded by the Framework Programme 7 of the European Commission, new methods for the environmental impact monitoring of mining operations are being developed. The objective of this study is to analyze the impact of mining on soil properties through assessment of the vegetation status using time series analysis of low resolution Normalized Difference Vegetation Index (NDVI) images derived from SPOT-Vegetation. The study focuses on the surroundings of mining areas in the Orenburg region in the Russian Urals. Karabash has been a centre for mining and metal production for well over 3000 years, and environmental impact of (historical) mining in the area is extremely severe. The area was characterized as an 'ecological disaster zone', based on chemical analysis of soil samples in the area [1]. The mining activities were intensified in the early to mid-20th century, but the old smelter was modernized in the 1990s. A time series of 10-daily NDVI images from SPOT-Vegetation (S10 April/1998-December/2010 at 1km2 resolution, http://www.vgt.vito.be/) is analyzed. Different land cover types clearly show different phenology. To remove seasonal vegetation changes and thus to facilitate the interpretation through the historical record, a Standardized Difference Vegetation Index (SDVI) was calculated for each pixel and for each record of the time series. The first results of trend analyses indicate a strong recovery of open forests in the Karabash region in the last decade. To what extent this can be related to reduced mining impact or climate factors, still needs to be assessed. Further research will also focus on the spatial heterogeneity of phenological parameters, in relation to distance to and wind direction of the smelters and soil properties. [1] V. Nestersnko, "Urban associations of elements- environmental pollutants in Karabash city (Chelyabinsk oblast) as a reflection of ore-chemical descriptions of mineral raw material", Proceedings of the Chelyabinsk Scientific Center, vol. 3, pp. 58-62, 2006.

Refocusing Space Technology

NASA Technical Reports Server (NTRS)

1994-01-01

This video presents two examples of NASA Technology Transfer. The first is a Downhole Video Logger, which uses remote sensing technology to help in mining. The second example is the use of satellite image processing technology to enhance ultrasound images taken during pregnancy.

Future Directions in Medical Physics

NASA Astrophysics Data System (ADS)

Jeraj, Robert

Medical Physics is a highly interdisciplinary field at the intersection between physics and medicine and biology. Medical Physics is aiming at development of novel applications of physical processes and techniques in various areas of medicine and biology. Medical Physics had and continues to have profound impact by developing improved imaging and treatment technologies, and helping to advance our understanding of the complexity of the disease. The general trend in medicine towards personalized therapy, and emphasis on accelerated translational research is having a profound impact on medical physics as well. In the traditional stronghold for medical physicists - radiation therapy - the new reality is shaping in the form of biologically conformal and combination therapies, as well as advanced particle therapy approaches, such as proton and ion therapies. Rapid increase in faster and more informative multi-modality medical imaging is bringing a wealth of information that is being complemented with data obtained from genomic profiling and other biomarkers. Novel data analysis and data mining approaches are proving grounds for employment of various artificial intelligence methods that will help further improving clinical decision making for optimization of various therapies as well as better understanding of the disease properties and disease evolution, ultimately leading to improved clinical outcomes.

The application of 3D image processing to studies of the musculoskeletal system

NASA Astrophysics Data System (ADS)

Hirsch, Bruce Elliot; Udupa, Jayaram K.; Siegler, Sorin; Winkelstein, Beth A.

2009-10-01

Three dimensional renditions of anatomical structures are commonly used to improve visualization, surgical planning, and patient education. However, such 3D images also contain information which is not readily apparent, and which can be mined to elucidate, for example, such parameters as joint kinematics, spacial relationships, and distortions of those relationships with movement. Here we describe two series of experiments which demonstrate the functional application of 3D imaging. The first concerns the joints of the ankle complex, where the usual description of motions in the talocrural joint is shown to be incomplete, and where the roles of the anterior talofibular and calcaneofibular ligaments are clarified in ankle sprains. Also, the biomechanical effects of two common surgical procedures for repairing torn ligaments were examined. The second series of experiments explores changes in the anatomical relationships between nerve elements and the cervical vertebrae with changes in neck position. They provide preliminary evidence that morphological differences may exist between asymptomatic subjects and patients with radiculopathy in certain positions, even when conventional imaging shows no difference.

An electromagnetic noncontacting sensor for thickness measurement in a dispersive medium

NASA Technical Reports Server (NTRS)

Chufo, Robert L.

1994-01-01

This paper describes a general purpose imaging technology developed by the U.S. Bureau of Mines (USBM) that, when fully implemented, will solve the general problem of 'seeing into the earth.' A first-generation radar coal thickness sensor, the RCTS-1, has been developed and field-tested in both underground and highwall mines. The noncontacting electromagnetic technique uses spatial modulation created by moving a simple sensor antenna in a direction along each axis to be measured while the complex reflection coefficient is measured at multiple frequencies over a two-to-one bandwidth. The antenna motion imparts spatial modulation to the data that enables signal processing to solve the problems of media, target, and antenna dispersion. Knowledge of the dielectric constant of the media is not necessary because the electrical properties of the media are determined automatically along with the distance to the target and thickness of each layer of the target. The sensor was developed as a navigation guidance sensor to accurately detect the coal/noncoal interface required for the USBM computer-assisted mining machine program. Other mining applications include the location of rock fractures, water-filled voids, and abandoned gas wells. These hazards can be detected in advance of the mining operation. This initiating technology is being expanded into a full three-dimensional (3-D) imaging system that will have applications in both the underground and surface environment.

Emerging technology becomes an opportunity for EOS

NASA Astrophysics Data System (ADS)

Fargion, Giulietta S.; Harberts, Robert; Masek, Jeffrey G.

1996-11-01

During the last decade, we have seen an explosive growth in our ability to collect and generate data. When implemented, NASA's Earth observing system data information system (EOSDIS) will receive about 50 gigabytes of remotely sensed image data per hour. This will generate an urgent need for new techniques and tools that can automatically and intelligently assist in transforming this abundance of data into useful knowledge. Some emerging technologies that address these challenges include data mining and knowledge discovery in databases (KDD). The most basic data mining application is a content-based search (examples include finding images of particular meteorological phenomena or identifying data that have been previously mined or interpreted). In order that these technologies be effectively exploited for EOSDIS development, a better understanding of data mining and the requirements for using this technology is necessary. The authors are currently undertaking a project exploring the requirements and options of content-based search and data mining for use on EOSDIS. The scope of the project is to develop a prototype with which to investigate user interface concepts, requirements, and designs relevant for EOSDIS core system (ECS) subsystem utilizing these techniques. The goal is to identify a generic handling of these functions. This prototype will help identify opportunities which the earth science community and EOSDIS can use to meet the challenges of collecting, searching, retrieving, and interacting with abundant data resources in highly productive ways.

Memorandum of Understanding on Surface Coal Mining Operations Resulting in Placement of Excess Spoil Fills in the Waters of the United States

EPA Pesticide Factsheets

MOU on Surface Coal Mining Operations establishes a process for improving coordination in the review of permit applications required for surface coal mining and reclamation in waters of the United States

Effective application of improved profit-mining algorithm for the interday trading model.

PubMed

Hsieh, Yu-Lung; Yang, Don-Lin; Wu, Jungpin

2014-01-01

Many real world applications of association rule mining from large databases help users make better decisions. However, they do not work well in financial markets at this time. In addition to a high profit, an investor also looks for a low risk trading with a better rate of winning. The traditional approach of using minimum confidence and support thresholds needs to be changed. Based on an interday model of trading, we proposed effective profit-mining algorithms which provide investors with profit rules including information about profit, risk, and winning rate. Since profit-mining in the financial market is still in its infant stage, it is important to detail the inner working of mining algorithms and illustrate the best way to apply them. In this paper we go into details of our improved profit-mining algorithm and showcase effective applications with experiments using real world trading data. The results show that our approach is practical and effective with good performance for various datasets.

Effective Application of Improved Profit-Mining Algorithm for the Interday Trading Model

PubMed Central

Wu, Jungpin

2014-01-01

Many real world applications of association rule mining from large databases help users make better decisions. However, they do not work well in financial markets at this time. In addition to a high profit, an investor also looks for a low risk trading with a better rate of winning. The traditional approach of using minimum confidence and support thresholds needs to be changed. Based on an interday model of trading, we proposed effective profit-mining algorithms which provide investors with profit rules including information about profit, risk, and winning rate. Since profit-mining in the financial market is still in its infant stage, it is important to detail the inner working of mining algorithms and illustrate the best way to apply them. In this paper we go into details of our improved profit-mining algorithm and showcase effective applications with experiments using real world trading data. The results show that our approach is practical and effective with good performance for various datasets. PMID:24688442

Mine Safety Education and Training Seminar. Proceedings: Bureau of Mines Technology Transfer Seminar (Pittsburgh, Pennsylvania, May 17, 1988; Beckley, West Virginia, May 19, 1988; St. Louis, Missouri, May 24, 1988; and Reno, Nevada, May 26, 1988). Information Circular 9185.

ERIC Educational Resources Information Center

Bureau of Mines (Dept. of Interior), Washington, DC.

This publication contains the papers presented at four technology transfer seminars on mine safety education and training. The papers highlight the Bureau of Mines' recent research aimed at improving the effectiveness of mine safety training in order to reduce workplace accidents. The following eight papers are included: "Effect of Training…

Expanding the Scope of an Automated Radiology Recommendation-Tracking Engine: Initial Experiences and Lessons Learned.

PubMed

Licurse, Mindy Y; Lalevic, Darco; Zafar, Hanna M; Schnall, Mitchell D; Cook, Tessa S

2017-04-01

An automated radiology recommendation-tracking engine for incidental focal masses in the liver, pancreas, kidneys, and adrenal glands was launched within our institution in July 2013. For 2 years, the majority of CT, MR, and US examination reports generated within our health system were mined by the engine. However, the need to expand the system beyond the initial four organs was soon identified. In July 2015, the second phase of the system was implemented and expanded to include additional anatomic structures in the abdomen and pelvis, as well as to provide non-radiology and non-imaging options for follow-up. The most frequent organs with incidental findings, outside of the original four, included the ovaries and the endometrium, which also correlated to the most frequently ordered imaging follow-up study of pelvic ultrasound and non-imaging follow-up study of endometrial biopsies, respectively. The second phase expansion has demonstrated new venues for augmenting and improving radiologist roles in optimal communication and management of incidental findings.

26 CFR 1.167(i)-1 - Depreciation of improvements in the case of mines, etc.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 2 2010-04-01 2010-04-01 false Depreciation of improvements in the case of... and Corporations § 1.167(i)-1 Depreciation of improvements in the case of mines, etc. Property used in... depreciation provided in section 611 shall be treated for all purposes of the Code as if it were property...

July 2011 Memorandum: Improving EPA Review of Appalachian Surface Coal Mining Operations Under the Clean Water Act, National Environmental Policy Act, and the Environmental Justice Executive Order

EPA Pesticide Factsheets

Memorandum: Improving EPA Review of Appalachian Surface Coal Mining Operations Under the Clean Water Act, National Environmental Policy Act, and the Environmental Justice Executive Order, July 21, 2011

Geospatiotemporal data mining in an early warning system for forest threats in the United States

Treesearch

F.M. Hoffman; R.T. Mills; J. Kumar; S.S. Vulli; W.W. Hargrove

2010-01-01

We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250 m Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study) for the conterminous United States as part of an early warning system to identify threats to forest ecosystems. Cluster...

Cluster Analysis-Based Approaches for Geospatiotemporal Data Mining of Massive Data Sets for Identification of Forest Threats

Treesearch

Richard Trans Mills; Forrest M Hoffman; Jitendra Kumar; William W. Hargrove

2011-01-01

We investigate methods for geospatiotemporal data mining of multi-year land surface phenology data (250 m2 Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectrometer (MODIS) in this study) for the conterminous United States (CONUS) as part of an early warning system for detecting threats to forest ecosystems. The...

An Account of the Founding of H.M. Inspectorate of Mines and the Work of the First Inspector Hugh Seymour Tremenheere

PubMed Central

Edmonds, O. P.; Edmonds, E. L.

1963-01-01

This paper refers briefly to the adverse environmental conditions in mines in the middle of the nineteenth century and the first attempts made by the central government to remedy them. The life, character, and contribution of Hugh Seymour Tremenheere, the first inspector, is described in some detail. Images PMID:14046158

Buried landmine detection using multivariate normal clustering

NASA Astrophysics Data System (ADS)

Duston, Brian M.

2001-10-01

A Bayesian classification algorithm is presented for discriminating buried land mines from buried and surface clutter in Ground Penetrating Radar (GPR) signals. This algorithm is based on multivariate normal (MVN) clustering, where feature vectors are used to identify populations (clusters) of mines and clutter objects. The features are extracted from two-dimensional images created from ground penetrating radar scans. MVN clustering is used to determine the number of clusters in the data and to create probability density models for target and clutter populations, producing the MVN clustering classifier (MVNCC). The Bayesian Information Criteria (BIC) is used to evaluate each model to determine the number of clusters in the data. An extension of the MVNCC allows the model to adapt to local clutter distributions by treating each of the MVN cluster components as a Poisson process and adaptively estimating the intensity parameters. The algorithm is developed using data collected by the Mine Hunter/Killer Close-In Detector (MH/K CID) at prepared mine lanes. The Mine Hunter/Killer is a prototype mine detecting and neutralizing vehicle developed for the U.S. Army to clear roads of anti-tank mines.

Monitoring coal mine changes and their impact on landscape patterns in an alpine region: a case study of the Muli coal mine in the Qinghai-Tibet Plateau.

PubMed

Qian, Dawen; Yan, Changzhen; Xing, Zanpin; Xiu, Lina

2017-10-14

The Muli coal mine is the largest open-cast coal mine in the Qinghai-Tibet Plateau, and it consists of two independent mining sites named Juhugeng and Jiangcang. It has received much attention due to the ecological problems caused by rapid expansion in recent years. The objective of this paper was to monitor the mining area and its surrounding land cover over the period 1976-2016 utilizing Landsat images, and the network structure of land cover changes was determined to visualize the relationships and pattern of the mining-induced land cover changes. In addition, the responses of the surrounding landscape pattern were analysed by constructing gradient transects. The results show that the mining area was increasing in size, especially after 2000 (increased by 71.68 km 2 ), and this caused shrinkage of the surrounding lands, including alpine meadow wetland (53.44 km 2 ), alpine meadow (6.28 km 2 ) and water (6.24 km 2 ). The network structure of the mining area revealed the changes in lands surrounding the mining area. The impact of mining development on landscape patterns was mainly distributed within a range of 1-6 km. Alpine meadow wetland was most affected in Juhugeng, while alpine meadow was most affected in Jiangcang. The results of this study provide a reference for the ecological assessment and restoration of the Muli coal mine land.

Informatics in radiology: automated structured reporting of imaging findings using the AIM standard and XML.

PubMed

Zimmerman, Stefan L; Kim, Woojin; Boonn, William W

2011-01-01

Quantitative and descriptive imaging data are a vital component of the radiology report and are frequently of paramount importance to the ordering physician. Unfortunately, current methods of recording these data in the report are both inefficient and error prone. In addition, the free-text, unstructured format of a radiology report makes aggregate analysis of data from multiple reports difficult or even impossible without manual intervention. A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention. As an intermediary step between the workstation and the reporting software, quantitative and descriptive data are converted into an extensible markup language (XML) file in a standardized format specified by the Annotation and Image Markup (AIM) project of the National Institutes of Health Cancer Biomedical Informatics Grid. The AIM standard was created to allow image annotation data to be stored in a uniform machine-readable format. These XML files containing imaging data can also be stored on a local database for data mining and analysis. This structured work flow solution has the potential to improve radiologist efficiency, reduce errors, and facilitate storage of quantitative and descriptive imaging data for research. Copyright © RSNA, 2011.

The application of LANDSAT-1 imagery for monitoring strip mines in the new river watershed in northeast Tennessee, part 2

NASA Technical Reports Server (NTRS)

Shahrokhi, F. (Principal Investigator); Sharber, L. A.

1977-01-01

The author has identified the following significant results. LANDSAT imagery and supplementary aircraft photography of the New River drainage basin were subjected to a multilevel analysis using conventional photointerpretation methods, densitometric techniques, multispectral analysis, and statistical tests to determine the accuracy of LANDSAT-1 imagery for measuring strip mines of common size. The LANDSAT areas were compared with low altitude measurements. The average accuracy over all the mined land sample areas mapped from LANDSAT-1 was 90%. The discrimination of strip mine subcategories is somewhat limited on LANDSAT imagery. A mine site, whether active or inactive, can be inferred by lack of vegetation, by shape, or image texture. Mine ponds are difficult or impossible to detect because of their small size and turbidity. Unless bordered and contrasted with vegetation, haulage roads are impossible to delineate. Preparation plants and refuge areas are not detectable. Density slicing of LANDSAT band 7 proved most useful in the detection of reclamation progress within the mined areas. For most state requirements for year-round monitoring of surface mined land, LANDSAT is of limited value. However, for periodic updating of regional surface maps, LANDSAT may provide sufficient accuracies for some users.

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.

Evaluation of airborne thermal infrared imagery for locating mine drainage sites in the Lower Youghiogheny River Basin, Pennsylvania, USA

USGS Publications Warehouse

Sams, James I.; Veloski, Garret; Ackman, T.E.

2003-01-01

Nighttime high-resolution airborne thermal infrared imagery (TIR) data were collected in the predawn hours during Feb 5-8 and March 11-12, 1999, from a helicopter platform for 72.4 km of the Youghiogheny River, from Connellsville to McKeesport, in southwestern Pennsylvania. The TIR data were used to identify sources of mine drainage from abandoned mines that discharge directly into the Youghiogheny River. Image-processing and geographic information systems (GIS) techniques were used to identify 70 sites within the study area as possible mine drainage sources. The combination of GIS datasets and the airborne TIR data provided a fast and accurate method to target the possible sources. After field reconnaissance, it was determined that 24 of the 70 sites were mine drainage. This paper summarizes: the procedures used to process the TIR data and extract potential mine-drainage sites; methods used for verification of the TIR data; a discussion of factors affecting the TIR data; and a brief summary of water quality.

Segmentation of fluorescence microscopy cell images using unsupervised mining.

PubMed

Du, Xian; Dua, Sumeet

2010-05-28

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu's threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu's threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications.

Analysis of Low-Light and Night-Time Stereo-Pair Images for Photogrammetric Reconstruction

NASA Astrophysics Data System (ADS)

Santise, M.; Thoeni, K.; Roncella, R.; Diotri, F.; Giacomini, A.

2018-05-01

Rockfalls and rockslides represent a significant risk to human lives and infrastructures because of the high levels of energy involved in the phenomena. Generally, these events occur in accordance to specific environmental conditions, such as temperature variations between day and night, that can contribute to the triggering of structural instabilities in the rock-wall and the detachment of blocks and debris. The monitoring and the geostructural characterization of the wall are required for reducing the potential hazard and to improve the management of the risk at the bottom of the slopes affected by such phenomena. In this context, close range photogrammetry is largely used for the monitoring of high-mountain terrains and rock walls in mine sites allowing for periodic survey of rockfalls and wall movements. This work focuses on the analysis of low-light and night-time images of a fixed-base stereo pair photogrammetry system. The aim is to study the reliability of the images acquired over the night to produce digital surface models (DSMs) for change detection. The images are captured by a high-sensitivity DLSR camera using various settings accounting for different values of ISO, aperture and time of exposure. For each acquisition, the DSM is compared to a photogrammetric reference model produced by images captured in optimal illumination conditions. Results show that, with high level of ISO and maintaining the same grade of aperture, extending the exposure time improves the quality of the point clouds in terms of completeness and accuracy of the photogrammetric models.

Calibration of the seismic velocity structure and understanding of the fault formation in the environs of the Orkney M5.5 earthquake, South Africa

NASA Astrophysics Data System (ADS)

Ogasawara, H.; Manzi, M. S.; Durrheim, R. J.; Ogasawara, H.

2017-12-01

In August 2014, the largest seismic event (M5.5) to occur in a South African gold mining district took place near Orkney. The M5.5 event and aftershocks were recorded by strainmeters installed at 3 km depth hundreds of meters above the M5.5 fault, 46 in-mine 4.5Hz triaxial geophone stations at depths of 2-3 km within a hypocentral radius of 2-3 km, and 17 surface strong motion stations (South African Seismograph Network; SANSN) within an epicentral radius of 25 km. Aftershocks were distributed on a nearly vertical plane striking NNW-SSE. The upper edge of this fault was hundreds of meters below the deepest level of the mine. ICDP approved a project "Drilling into seismogenic zones of M2.0-5.5 earthquakes in South African gold mines" to elucidate the details of the events (DSeis; Yabe et al. invited talk in S020 in this AGU). On 1 August 2017 drilling was within a few hundreds of meters of intersecting the M5.5 fault zone. To locate the drilling target accurately it is very important to determine the velocity structure between the seismic events and sensors. We do this by using the interval velocities used to migrate 3D-reflection seismic data that was previously acquired by a mining company to image the gold-bearing reef and any fault structures close to the mining horizon. Less attention was given to the velocities below the mining horizon, as accurate imaging of the geological structure was not as important and very little drilling information was available. We used the known depths of prominent reflectors above the mining horizon to derive the interval velocities needed to convert two-way-travel-time to depth. We constrain the velocity below the mining horizon by comparing the DSeis drilling results with the 3D seismic cube. The geometric data is crucial for the kinematic modeling that Ogasawara et al. (S018 in this AGU) advocates. The efforts will result in a better understanding of the main rupture and aftershocks.

26 CFR 1.611-5 - Depreciation of improvements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... (CONTINUED) INCOME TAXES (CONTINUED) Natural Resources § 1.611-5 Depreciation of improvements. (a) In general. Section 611 provides in the case of mines, oil and gas wells, other natural deposits, and timber that...). (b) Special rules for mines, oil and gas wells, other natural deposits and timber. (1) For principles...

Army Needs to Identify Government Purchase Card High-Risk Transactions

DTIC Science & Technology

2012-01-20

Purchase Card Program Data Mining Process Needs Improvement 11...Mining Process Needs Improvement The 17 transactions that were noncompliant occurred because cardholders ignored the GPC business rules so the...Scope and Methodology 16 Use of Computer- Processed Data 16 Use of Technical Assistance 17 Prior Coverage

The Necessity of Public Relations for Sustainable Mining Activities

NASA Astrophysics Data System (ADS)

Lee, Hyunbock; Ji, Sangwoo

2015-04-01

This paper reports research about the necessity of image making for sustainable mine developments in the Republic of Korea. One of the big risks in mining activities is mining area residents opposing mine developments and operations. Analysis of the media reports on disputes between mining companies and residents can determine causes of opposing mine developments, dispute process, and influences of disputes on processes of mining projects. To do this, civil complaints from 2009 to 2012 and 24 media reports since 2000 on opposing mining activities are analyzed. And, to analyze difficulties of mining companies, the survey is conducted to target to mining companies. 57 representatives of mining companies are participated in the survey. The result of analysis cited that the major reasons of anti-mining activities are environmental degradation and reduced agricultural productivity. And specifically because of water pollution (50%), crop damages (33%), and mining dust pollution (21%), communities of mining area are against mine developments and operations. However, 25% of residents have experience of the damage caused by mining activities and the remaining 75% of residents opposing mining activities simply have anxiety about mining pollution. In the past, construction-oriented, environment-unfriendly mining projects had lasted. And while mine reclamation had been postponed in abandoned mines, mining area residents had suffered from mining pollution. So, mining area residents are highly influenced by the prejudice that mining activities are harmful to mining area communities. Current mining projects in South Korea, unlike the past mining activity, focus on minimizing environmental damage and contributing to mining area communities financially. But, in many case of disputes between mining companies and mining area residents, the both cannot reach an agreements because of the negative prejudice. Moreover, some communities categorically refuse any mining activity. On the other hand, in the survey to determine what the greatest difficulties of the current mining activities, 54% of mining companies chose environmental regulations, 26% of mining companies chose conflicts between mine area residents and mining companies. Environmental regulations are may defined as the greatest difficulty of current mining activities. But most of environmental regulation's problems are caused by frictions with residents, because all of South Korean mines are very close to villages. So, the biggest difficulty of mining activities can be defined conflicts between residents and mining companies. Moreover, general people in South Korea including some mining engineers recognize the mining industry as a declined and pollution industry. Without clear understanding of mining activities, any mine developments and policies related to mining activities cannot be made by rational discussions. And, if their recognition is not formed in a rational way, it will be turned to extreme fear or blind hatred. Therefore, to understand mining activities correctly, the effective public relations strategy is necessary such as corporate advertisements or public advertisements.

Corporate social responsibility for regional sustainability after mine closure: a case study of mining company in Indonesia

NASA Astrophysics Data System (ADS)

Syarif, Andi Erwin; Hatori, Tsuyoshi

2017-06-01

Creating a soft-landing path for mine closure is key to the sustainability of the mining region. In this research, we presents a case of mine closure in Soroako, a small mining town in the north-east of South Sulawesi province, in the center of Sulawesi Island in Indonesia. Especially we investigates corporate social responsibility (CSR) programs of a mining company, PT Vale Indonesia Tbk (PTVI), towards a soft-landing of mine closure in this region. The data of the CSR programs are gathered from in-depth interviews, the annual reports and managerial reports. Furthermore we presents an integrated view of CSR to close mining in a sustainable manner. We then evaluate CSR strategies of the company and its performance from this viewpoint. Based on these steps, the way to improve the CSR mine closure scenario for enhancing the regional sustainability is discussed and recommended.

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.

Illustration Watermarking for Digital Images: An Investigation of Hierarchical Signal Inheritances for Nested Object-based Embedding

DTIC Science & Technology

2007-02-23

approach for signal-level watermark inheritance. 15. SUBJECT TERMS EOARD, Steganography , Image Fusion, Data Mining, Image ...in watermarking algorithms , a program interface and protocol has been de - veloped, which allows control of the embedding and retrieval processes by the...watermarks in an image . Watermarking algorithm (DLL) Watermarking editor (Delphi) - User marks all objects: ci - class information oi - object instance

Study on online community user motif using web usage mining

NASA Astrophysics Data System (ADS)

Alphy, Meera; Sharma, Ajay

2016-04-01

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

78 FR 40496 - Notice of availability of the Final Environmental Impact Statement for the Proposed Hollister...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... silver mining operation. Most of the infrastructure to support a mining operation was authorized and.... The Proposed Action consists of underground mining, constructing a new production shaft, improving.... Public comments resulted in the addition of clarifying text, but did not significantly change the...

Mapping mine wastes and analyzing areas affected by selenium-rich water runoff in southeast Idaho using AVIRIS imagery and digital elevation data

USGS Publications Warehouse

Mars, J.C.; Crowley, J.K.

2003-01-01

Remotely sensed hyperspectral and digital elevation data from southeastern Idaho are combined in a new method to assess mine waste contamination. Waste rock from phosphorite mining in the area contains selenium, cadmium, vanadium, and other metals. Toxic concentrations of selenium have been found in plants and soils near some mine waste dumps. Eighteen mine waste dumps and five vegetation cover types in the southeast Idaho phosphate district were mapped by using Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) imagery and field data. The interaction of surface water runoff with mine waste was assessed by registering the AVIRIS results to digital elevation data, enabling determinations of (1) mine dump morphologies, (2) catchment watershed areas above each mine dump, (3) flow directions from the dumps, (4) stream gradients, and (5) the extent of downstream wetlands available for selenium absorption. Watersheds with the most severe selenium contamination, such as the South Maybe Canyon watershed, are associated with mine dumps that have large catchment watershed areas, high stream gradients, a paucity of downstream wetlands, and dump forms that tend to obstruct stream flow. Watersheds associated with low concentrations of dissolved selenium, such as Angus Creek, have mine dumps with small catchment watershed areas, low stream gradients, abundant wetlands vegetation, and less obstructing dump morphologies. ?? 2002 Elsevier Science Inc. All rights reserved.

Characterization of Urban Landscape Using Super-Resolution UAS Data, Multiple Textural Scales and Data-Mining Techniques

NASA Astrophysics Data System (ADS)

Voss, M.; Blundell, B.

2015-12-01

Characterization of urban environments is a high priority for the U.S. Army as battlespaces have transitioned from the predominantly open spaces of the 20th century to urban areas where soldiers have reduced situational awareness due to the diversity and density of their surroundings. Creating high-resolution urban terrain geospatial information will improve mission planning and soldier effectiveness. In this effort, super-resolution true-color imagery was collected with an Altivan NOVA unmanned aerial system over the Muscatatuck Urban Training Center near Butlerville, Indiana on September 16, 2014. Multispectral texture analysis using different algorithms was conducted for urban surface characterization at a variety of scales. Training samples extracted from the true-color and texture images. These data were processed using a variety of meta-algorithms with a decision tree classifier to create a high-resolution urban features map. In addition to improving accuracy over traditional image classification methods, this technique allowed the determination of the most significant textural scales in creating urban terrain maps for tactical exploitation.

Supporting Solar Physics Research via Data Mining

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

Changes in the Extent of Surface Mining and Reclamation in the Central Appalachians Detected Using a 1976-2006 Landsat Time Series

NASA Technical Reports Server (NTRS)

Townsend, Philip A.; Helmers, David P.; Kingdon, Clayton C.; McNeil, Brenden E.; de Beurs, Kirsten M.; Eshleman, Keith N.

2009-01-01

Surface mining and reclamation is the dominant driver of land cover land use change (LCLUC) in the Central Appalachian Mountain region of the Eastern U.S. Accurate quantification of the extent of mining activities is important for assessing how this LCLUC affects ecosystem services such as aesthetics, biodiversity, and mitigation of flooding.We used Landsat imagery from 1976, 1987, 1999 and 2006 to map the extent of surface mines and mine reclamation for eight large watersheds in the Central Appalachian region of West Virginia, Maryland and Pennsylvania. We employed standard image processing techniques in conjunction with a temporal decision tree and GIS maps of mine permits and wetlands to map active and reclaimed mines and track changes through time. For the entire study area, active surface mine extent was highest in 1976, prior to implementation of the Surface Mine Control and Reclamation Act in 1977, with 1.76% of the study area in active mines, declining to 0.44% in 2006. The most extensively mined watershed, Georges Creek in Maryland, was 5.45% active mines in 1976, declining to 1.83% in 2006. For the entire study area, the area of reclaimed mines increased from 1.35% to 4.99% from 1976 to 2006, and from 4.71% to 15.42% in Georges Creek. Land cover conversion to mines and then reclaimed mines after 1976 was almost exclusively from forest. Accuracy levels for mined and reclaimed cover was above 85% for all time periods, and was generally above 80% for mapping active and reclaimed mines separately, especially for the later time periods in which good accuracy assessment data were available. Among other implications, the mapped patterns of LCLUC are likely to significantly affect watershed hydrology, as mined and reclaimed areas have lower infiltration capacity and thus more rapid runoff than unmined forest watersheds, leading to greater potential for extreme flooding during heavy rainfall events.

Analysis of alternative modifications for reducing backwater flooding at the Honey Creek coal strip-mine reclamation site in Henry County, Missouri. Water Resources Investigation

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

Alexander, T.W.

Studies to determine the hydrologic conditions in mined and reclaimed mine areas, as well as areas of proposed mining, have become necessary with the enactment of the Surface Mining Control and Reclamation Act of 1977. Honey Creek in Henry County, Missouri, has been re-routed to flow through a series of former strip mining pits which lie within the Honey Creek coal strip mine reclamation site. During intense or long duration rainfalls within the Honey Creek basin, surface runoff has caused flooding on agricultural land near the upstream boundary of the reclamation site. The calculated existing design discharge (3,050 cubic feetmore » per second) water-surface profile is compared to the expected water-surface profiles from three assumed alternative channel modifcations within the Honey Creek study area. The alternative channel modifications used in these analyses include (1) improvement of channel bottom slope, (2) relocation of spoil material, and (3) improved by-pass channel flow conditions. The alternative 1, 2, and 3 design discharge increase will reduce the agricultural field current (1990) frequency of backwater flooding from a 3-year to a 6.5-year event.« less

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.

Geometrical and optical calibration of a vehicle-mounted IR imager for land mine localization

NASA Astrophysics Data System (ADS)

Aitken, Victor C.; Russell, Kevin L.; McFee, John E.

2000-08-01

Many present day vehicle-mounted landmine detection systems use IR imagers. Information furnished by these imaging systems usually consists of video and the location of targets within the video. In multisensor systems employing data fusion, there is a need to convert sensor information to a common coordinate system that all sensors share.

Manual of good practices for sanitation in coal mining operations

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

Not Available

The purpose of the manual was to act as a guideline, setting reasonable recommendations relative to mine sanitation which will enable mines to install adequate facilities and make appropriate alterations conserving and improving the health and welfare of the mine worker. A systematic evaluation was undertaken of the sanitation facilities and maintenance at coal mines. Consideration was given to central facilities including building, floors, walls, partitions, ceilings, lockers, baskets and benches, showers, toilets, lavatories, lighting, ventilation and temperature control, and maintenance. Also discussed were food vending machines, water source, water quality, water treatment, water delivery systems for underground and surfacemore » mines, sanitary waste disposal, workplace toilets in underground and surface mines, refuse control and handling for underground and surface mines, and pest control.« less

Big data mining analysis method based on cloud computing

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Imaging and detection of mines from acoustic measurements

NASA Astrophysics Data System (ADS)

Witten, Alan J.; DiMarzio, Charles A.; Li, Wen; McKnight, Stephen W.

1999-08-01

A laboratory-scale acoustic experiment is described where a buried target, a hockey puck cut in half, is shallowly buried in a sand box. To avoid the need for source and receiver coupling to the host sand, an acoustic wave is generated in the subsurface by a pulsed laser suspended above the air-sand interface. Similarly, an airborne microphone is suspended above this interface and moved in unison with the laser. After some pre-processing of the data, reflections for the target, although weak, could clearly be identified. While the existence and location of the target can be determined by inspection of the data, its unique shape can not. Since target discrimination is important in mine detection, a 3D imaging algorithm was applied to the acquired acoustic data. This algorithm yielded a reconstructed image where the shape of the target was resolved.

30 CFR 18.47 - Voltage limitation.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements... safeguards for high-voltage equipment, or modify the requirements to recognize improved technology. ...

30 CFR 18.47 - Voltage limitation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements... safeguards for high-voltage equipment, or modify the requirements to recognize improved technology. ...

30 CFR 18.47 - Voltage limitation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements... safeguards for high-voltage equipment, or modify the requirements to recognize improved technology. ...

30 CFR 18.47 - Voltage limitation.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements... safeguards for high-voltage equipment, or modify the requirements to recognize improved technology. ...

30 CFR 18.47 - Voltage limitation.

Code of Federal Regulations, 2013 CFR

2013-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements... safeguards for high-voltage equipment, or modify the requirements to recognize improved technology. ...

Innovative Competencies of Mining engineers in Transition to the Sustainable Development

NASA Astrophysics Data System (ADS)

Krechetov, Andrey; Khoreshok, Alexey; Blumenstein, Valery

2017-11-01

The transition to the sustainable development posed new challenges to the system of mining higher education. They are determined by the acceleration of scientific and technological progress and widespread introduction of innovations, convergence of technologies from various industries. On the one hand, globalization and rapid technology development are constantly increasing quality requirements for the labor resources of the mineral and raw materials complex and constant improvement of their skills. On the other hand, the transition to the sustainable development provides the necessity for rational use of raw materials and environmental protection. This requires the improvement of staff support system for mining operations and the interaction of enterprises with universities training mining engineers, aimed at the innovative competencies development of future miners.

Mining algorithm for association rules in big data based on Hadoop

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

2018-04-01

In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

Asadi Haroni, Hooshang; Hassan Tabatabaei, Seyed

2016-04-01

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

Amending metal contaminated mine soil with biochars to sequester metals and improve plant growth cover

EPA Science Inventory

There are numerous mine spoil sites in the U.S. Pacific Northwest that contain highly acidic, heavy metal-laden soils, which limits establishment of a soil-stabilizing plant cover. Biochars may be a suitable soil amendment to reduce toxic metals, improve soil fertility, soil wa...

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

NASA Technical Reports Server (NTRS)

Tilton, James C.

2002-01-01

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

Student Privacy and Educational Data Mining: Perspectives from Industry

ERIC Educational Resources Information Center

Sabourin, Jennifer; Kosturko, Lucy; FitzGerald, Clare; McQuiggan, Scott

2015-01-01

While the field of educational data mining (EDM) has generated many innovations for improving educational software and student learning, the mining of student data has recently come under a great deal of scrutiny. Many stakeholder groups, including public officials, media outlets, and parents, have voiced concern over the privacy of student data…

78 FR 5055 - Pattern of Violations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-23

...The Mine Safety and Health Administration (MSHA) is revising the Agency's existing regulation for pattern of violations (POV). MSHA has determined that the existing regulation does not adequately achieve the intent of the Federal Mine Safety and Health Act of 1977 (Mine Act) that the POV provision be used to address mine operators who have demonstrated a disregard for the health and safety of miners. Congress included the POV provision in the Mine Act so that mine operators would manage health and safety conditions at mines and find and fix the root causes of significant and substantial (S&S) violations, protecting the health and safety of miners. The final rule simplifies the existing POV criteria, improves consistency in applying the POV criteria, and more effectively achieves the Mine Act's statutory intent. It also encourages chronic safety violators to comply with the Mine Act and MSHA's health and safety standards.

Microcomputer keeps watch at Emerald Mine

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

Not Available

1987-04-01

Where there's smoke, there's fire. Take the old adage a step further: ''Where there's carbon monoxide, there's likely to be a fire.'' That's the principle behind the mine monitoring system being used at the Emerald Mine operated by Emway Resources. Instead of watching for smoke or temperature rises, the system uses carbon monoxide (CO) sensors to detect fires - before they break out. CO, a gaseous product of incomplete combustion, is present in the early stages of a fire. Carried by the mine ventilation air, CO can be quickly traced by electrochemical gas sensors that are wired to a centralmore » computer. When preset levels are reached, alarms can alert mine personnel of the trouble. The Emerald Mine is located in southwestern Pennsylvania, near Waynesburg, and mines the Pittsburgh Seam, the nation's most heavily mined seam. Emerald is one of a number of progressive mines that are turning to computers to improve safety and productivity.« less

EU-FP7-iMARS: analysis of Mars multi-resolution images using auto-coregistration, data mining and crowd source techniques: A Mid-term Report

NASA Astrophysics Data System (ADS)

Muller, J.-P.; Yershov, V.; Sidiropoulos, P.; Gwinner, K.; Willner, K.; Fanara, L.; Waelisch, M.; van Gasselt, S.; Walter, S.; Ivanov, A.; Cantini, F.; Morley, J. G.; Sprinks, J.; Giordano, M.; Wardlaw, J.; Kim, J.-R.; Chen, W.-T.; Houghton, R.; Bamford, S.

2015-10-01

Understanding the role of different solid surface formation processes within our Solar System is one of the fundamental goals of planetary science research. There has been a revolution in planetary surface observations over the last 8 years, especially in 3D imaging of surface shape (down to resolutions of 10s of cms) and subsequent terrain correction of imagery from orbiting spacecraft. This has led to the potential to be able to overlay different epochs back to the mid-1970s. Within iMars, a processing system has been developed to generate 3D Digital Terrain Models (DTMs) and corresponding OrthoRectified Images (ORIs) fully automatically from NASA MRO HiRISE and CTX stereo-pairs which are coregistered to corresponding HRSC ORI/DTMs. In parallel, iMars has developed a fully automated processing chain for co-registering level-1 (EDR) images from all previous NASA orbital missions to these HRSC ORIs and in the case of HiRISE these are further co-registered to previously co-registered CTX-to-HRSC ORIs. Examples will be shown of these multi-resolution ORIs and the application of different data mining algorithms to change detection using these co-registered images. iMars has recently launched a citizen science experiment to evaluate best practices for future citizen scientist validation of such data mining processed results. An example of the iMars website will be shown along with an embedded Version 0 prototype of a webGIS based on OGC standards.

RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cook, Diane J.

2008-01-01

Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

Spatio-temporal pattern of eco-environmental parameters in Jharia coalfield, India

NASA Astrophysics Data System (ADS)

Saini, V.; Gupta, R. P.; Arora, M. K.

2015-10-01

Jharia coal-field holds unequivocal importance in the Indian context as it is the only source of prime coking coal in the country. The coalfield is also known for its infamous coal mine fires which have been burning since last more than a century. Haphazard mining over a century has led to eco-environmental changes to a large extent such as changes in vegetation distribution and widespread development of surface and subsurface fires. This article includes the spatiotemporal study of remote sensing derived eco-environmental parameters like vegetation index (NDVI), tasseled cap transformation (TCT) and temperature distribution in fire areas. In order to have an estimate of the temporal variations of NDVI over the years, a study has been carried out on two subsets of the Jharia coalfield using Landsat images of 1972 (MSS), 1992 (TM), 1999 (ETM+) and 2013 (OLI). To assess the changes in brightness and greenness over the year s, difference images have been calculated using the 1992 (TM) and 2013 (OLI) images. Radiance images derived from thermal bands have been used to calculate at-sensor brightness temperature over a 23 year period from 1991 to 2013. It has been observed that during the years 1972 to 2013, moderate to dense vegetation has decreased drastically due to the intense mining going on in the area. TCT images show the areas that have undergone changes in both brightness and greenness from 1992 to 2013. Surface temperature data obtained shows a constant increase from 1991 to 2013 apparently due to coal fires. The utility of remote sensing data in such EIA studies has been emphasized.

ASIST 2001. Information in a Networked World: Harnessing the Flow. Part III: Poster Presentations.

ERIC Educational Resources Information Center

Proceedings of the ASIST Annual Meeting, 2001

2001-01-01

Topics of Poster Presentations include: electronic preprints; intranets; poster session abstracts; metadata; information retrieval; watermark images; video games; distributed information retrieval; subject domain knowledge; data mining; information theory; course development; historians' use of pictorial images; information retrieval software;…

Imaging Preferential Flow Pathways of Contaminants from Passive Acid Mine Drainage Mitigation Sites Using Electrical Resistivity

NASA Astrophysics Data System (ADS)

Kelley, N.; Mount, G.; Terry, N.; Herndon, E.; Singer, D. M.

2017-12-01

The Critical Zone represents the surficial and shallow layer of rock, air, water, and soil where most interactions between living organisms and the Earth occur. Acid mine drainage (AMD) resulting from coal extraction can influence both biological and geochemical processes across this zone. Conservative estimates suggest that more than 300 million gallons of AMD are released daily, making this acidic solution of water and contaminants a common issue in areas with legacy or current coal extraction. Electrical resistivity imaging (ERI) provides a rapid and minimally invasive method to identify and monitor contaminant pathways from AMD remediation systems in the subsurface of the Critical Zone. The technique yields spatially continuous data of subsurface resistivity that can be inverted to determine electrical conductivity as a function of depth. Since elevated concentrations of heavy metals can directly influence soil conductivity, ERI data can be used to trace the flow pathways or perhaps unknown mine conduits and transport of heavy metals through the subsurface near acid mine drainage sources. This study aims to examine preferential contaminant migration from those sources through substrate pores, fractures, and shallow mine workings in the near subsurface surrounding AMD sites in eastern Ohio and western Pennsylvania. We utilize time lapse ERI measures during different hydrologic conditions to better understand the variability of preferential flow pathways in relation to changes in stage and discharge within the remediation systems. To confirm ERI findings, and provide constraint to geochemical reactions occurring in the shallow subsurface, we conducted Inductively Coupled Plasma (ICP) spectrometry analysis of groundwater samples from boreholes along the survey transects. Through these combined methods, we can provide insight into the ability of engineered systems to contain and isolate metals in passive acid mine drainage treatment systems.

Monitoring the growth or decline of vegetation on mine dumps

NASA Technical Reports Server (NTRS)

Gilbertson, B. P. (Principal Investigator)

1975-01-01

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

Comparative data mining analysis for information retrieval of MODIS images: monitoring lake turbidity changes at Lake Okeechobee, Florida

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Daranpob, Ammarin; Yang, Y. Jeffrey; Jin, Kang-Ren

2009-09-01

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates might be empirical regression, neural network model, support vector machine, genetic algorithm/genetic programming, analytical equation, etc. This paper compares three types of data mining techniques, including multiple non-linear regression, artificial neural networks, and genetic programming, for estimating multi-temporal turbidity changes following hurricane events at Lake Okeechobee, Florida. This retrospective analysis aims to identify how the major hurricanes impacted the water quality management in 2003-2004. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite imageries were used to retrieve the spatial patterns of turbidity distributions for comparison against the visual patterns discernible in the in-situ observations. By evaluating four statistical parameters, the genetic programming model was finally selected as the most suitable data mining tool for classification in which the MODIS band 1 image and wind speed were recognized as the major determinants by the model. The multi-temporal turbidity maps generated before and after the major hurricane events in 2003-2004 showed that turbidity levels were substantially higher after hurricane episodes. The spatial patterns of turbidity confirm that sediment-laden water travels to the shore where it reduces the intensity of the light necessary to submerged plants for photosynthesis. This reduction results in substantial loss of biomass during the post-hurricane period.

Earth Observation taken during the Expedition 37 mission

NASA Image and Video Library

2013-10-30

ISS037-E-022990 (30 Oct. 2013) --- This detailed image, photographed by an Expedition 37 crew member on the International Space Station, features the former US Borax mine located to the northwest of Boron, California. The mine, currently owned by the Rio Tinto Group, is the largest open-pit mine in California (covering approximately 54 square kilometers) and is among the largest borate mines in the world. Borates, chemical compounds that include the element boron (B), are important both as providers of an essential plant micronutrient, for metallurgical applications, and as components of specialized types of glass, anticorrosive coatings, fire retardants, and detergents (among other uses). Borate minerals such as borax, kernite, and ulexite are found in deposits at the Rio Tinto borax mine. The geologic setting is a structural, nonmarine basin ? a permanent shallow lake ? fed by thermal springs rich in sodium and boron that existed approximately 16 million years ago, according to scientists. The first mining claim in the area was filed in 1913, following discovery of boron-bearing nodules during well drilling. Much of the mine workings were underground until 1957, when US Borax changed to open-pit mining. The open pit is clearly visible at center; concentric benches along the pit wall are accentuated by shadows and mark successive levels of material extraction. Mine tailings are visible as stacked terraces along the northern boundary of the mine. Ore processing facilities occupy a relatively small percentage of the mine area, and are located directly to the west of the open pit. The Rio Tinto mine is one of the Earth?s richest borate deposits; together with mines in Argentina, they produce almost 40 percent of the world?s supply of industrial borate minerals.

Metal contamination and post-remediation recovery in the Boulder River watershed, Jefferson County, Montana

USGS Publications Warehouse

Unruh, Daniel M.; Church, Stanley E; Nimick, David A.; Fey, David L.

2009-01-01

The legacy of acid mine drainage and toxic trace metals left in streams by historical mining is being addressed by many important yet costly remediation efforts. Monitoring of environmental conditions frequently is not performed but is essential to evaluate remediation effectiveness, determine whether clean-up goals have been met, and assess which remediation strategies are most effective. Extensive pre- and post-remediation data for water and sediment quality for the Boulder River watershed in southwestern Montana provide an unusual opportunity to demonstrate the importance of monitoring. The most extensive restoration in the watershed occurred at the Comet mine on High Ore Creek and resulted in the most dramatic improvement in aquatic habitat. Removal of contaminated sediment and tailings, and stream-channel reconstruction reduced Cd and Zn concentrations in water such that fish are now present, and reduced metal concentrations in streambed sediment by a factor of c. 10, the largest improvement in the district. Waste removals at the Buckeye/Enterprise and Bullion mine sites produced limited or no improvement in water and sediment quality, and acidic drainage from mine adits continues to degrade stream aquatic habitat. Recontouring of hillslopes that had funnelled runoff into the workings of the Crystal mine substantially reduced metal concentrations in Uncle Sam Gulch, but did not eliminate all of the acidic adit drainage. Lead isotopic evidence suggests that the Crystal mine rather than the Comet mine is now the largest source of metals in streambed sediment of the Boulder River. The completed removal actions prevent additional contaminants from entering the stream, but it may take many years for erosional processes to diminish the effects of contaminated sediment already in streams. Although significant strides have been made, additional efforts to seal draining adits or treat the adit effluent at the Bullion and Crystal mines would need to be completed to achieve the desired restoration.

High-resolution topography along surface rupture of the 16 October 1999 Hector Mine, California (Mw 7.1) from airborne laser swath mapping

USGS Publications Warehouse

Hudnutt, K.W.; Borsa, A.; Glennie, C.; Minster, J.-B.

2002-01-01

In order to document surface rupture associated with the Hector Mine earthquake, in particular, the area of maximum slip and the deformed surface of Lavic Lake playa, we acquired high-resolution data using relatively new topographic-mapping methods. We performed a raster-laser scan of the main surface breaks along the entire rupture zone, as well as along an unruptured portion of the Bullion fault. The image of the ground surface produced by this method is highly detailed, comparable to that obtained when geologists make particularly detailed site maps for geomorphic or paleoseismic studies. In this case, however, for the first time after a surface-rupturing earthquake, the detailed mapping is along the entire fault zone rather than being confined to selected sites. These data are geodetically referenced, using the Global Positioning System, thus enabling more accurate mapping of the rupture traces. In addition, digital photographs taken along the same flight lines can be overlaid onto the precise topographic data, improving terrain visualization. We demonstrate the potential of these techniques for measuring fault-slip vectors.

Topic Model for Graph Mining.

PubMed

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Luo, Xiangfeng

2015-12-01

Graph mining has been a popular research area because of its numerous application scenarios. Many unstructured and structured data can be represented as graphs, such as, documents, chemical molecular structures, and images. However, an issue in relation to current research on graphs is that they cannot adequately discover the topics hidden in graph-structured data which can be beneficial for both the unsupervised learning and supervised learning of the graphs. Although topic models have proved to be very successful in discovering latent topics, the standard topic models cannot be directly applied to graph-structured data due to the "bag-of-word" assumption. In this paper, an innovative graph topic model (GTM) is proposed to address this issue, which uses Bernoulli distributions to model the edges between nodes in a graph. It can, therefore, make the edges in a graph contribute to latent topic discovery and further improve the accuracy of the supervised and unsupervised learning of graphs. The experimental results on two different types of graph datasets show that the proposed GTM outperforms the latent Dirichlet allocation on classification by using the unveiled topics of these two models to represent graphs.

Automatic detection of referral patients due to retinal pathologies through data mining.

PubMed

Quellec, Gwenolé; Lamard, Mathieu; Erginay, Ali; Chabouis, Agnès; Massin, Pascale; Cochener, Béatrice; Cazuguel, Guy

2016-04-01

With the increased prevalence of retinal pathologies, automating the detection of these pathologies is becoming more and more relevant. In the past few years, many algorithms have been developed for the automated detection of a specific pathology, typically diabetic retinopathy, using eye fundus photography. No matter how good these algorithms are, we believe many clinicians would not use automatic detection tools focusing on a single pathology and ignoring any other pathology present in the patient's retinas. To solve this issue, an algorithm for characterizing the appearance of abnormal retinas, as well as the appearance of the normal ones, is presented. This algorithm does not focus on individual images: it considers examination records consisting of multiple photographs of each retina, together with contextual information about the patient. Specifically, it relies on data mining in order to learn diagnosis rules from characterizations of fundus examination records. The main novelty is that the content of examination records (images and context) is characterized at multiple levels of spatial and lexical granularity: 1) spatial flexibility is ensured by an adaptive decomposition of composite retinal images into a cascade of regions, 2) lexical granularity is ensured by an adaptive decomposition of the feature space into a cascade of visual words. This multigranular representation allows for great flexibility in automatically characterizing normality and abnormality: it is possible to generate diagnosis rules whose precision and generalization ability can be traded off depending on data availability. A variation on usual data mining algorithms, originally designed to mine static data, is proposed so that contextual and visual data at adaptive granularity levels can be mined. This framework was evaluated in e-ophtha, a dataset of 25,702 examination records from the OPHDIAT screening network, as well as in the publicly-available Messidor dataset. It was successfully applied to the detection of patients that should be referred to an ophthalmologist and also to the specific detection of several pathologies. Copyright © 2016 Elsevier B.V. All rights reserved.

Mars methane analogue mission: Mission simulation and rover operations at Jeffrey Mine and Norbestos Mine Quebec, Canada

NASA Astrophysics Data System (ADS)

Qadi, A.; Cloutis, E.; Samson, C.; Whyte, L.; Ellery, A.; Bell, J. F.; Berard, G.; Boivin, A.; Haddad, E.; Lavoie, J.; Jamroz, W.; Kruzelecky, R.; Mack, A.; Mann, P.; Olsen, K.; Perrot, M.; Popa, D.; Rhind, T.; Sharma, R.; Stromberg, J.; Strong, K.; Tremblay, A.; Wilhelm, R.; Wing, B.; Wong, B.

2015-05-01

The Canadian Space Agency (CSA), through its Analogue Missions program, supported a microrover-based analogue mission designed to simulate a Mars rover mission geared toward identifying and characterizing methane emissions on Mars. The analogue mission included two, progressively more complex, deployments in open-pit asbestos mines where methane can be generated from the weathering of olivine into serpentine: the Jeffrey mine deployment (June 2011) and the Norbestos mine deployment (June 2012). At the Jeffrey Mine, testing was conducted over 4 days using a modified off-the-shelf Pioneer rover and scientific instruments including Raman spectrometer, Picarro methane detector, hyperspectral point spectrometer and electromagnetic induction sounder for testing rock and gas samples. At the Norbestos Mine, we used the research Kapvik microrover which features enhanced autonomous navigation capabilities and a wider array of scientific instruments. This paper describes the rover operations in terms of planning, deployment, communication and equipment setup, rover path parameters and instrument performance. Overall, the deployments suggest that a search strategy of “follow the methane” is not practical given the mechanisms of methane dispersion. Rather, identification of features related to methane sources based on image tone/color and texture from panoramic imagery is more profitable.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Greenhouse gas emissions from Australian open-cut coal mines: contribution from spontaneous combustion and low-temperature oxidation.

PubMed

Day, Stuart J; Carras, John N; Fry, Robyn; Williams, David J

2010-07-01

Spontaneous combustion and low-temperature oxidation of waste coal and other carbonaceous material at open-cut coal mines are potentially significant sources of greenhouse gas emissions. However, the magnitude of these emissions is largely unknown. In this study, emissions from spontaneous combustion and low-temperature oxidation were estimated for six Australian open-cut coal mines with annual coal production ranging from 1.7 to more than 16 Mt. Greenhouse emissions from all other sources at these mines were also estimated and compared to those from spontaneous combustion and low-temperature oxidation. In all cases, fugitive emission of methane was the largest source of greenhouse gas; however, in some mines, spontaneous combustion accounted for almost a third of all emissions. For one mine, it was estimated that emissions from spontaneous combustion were around 250,000 t CO(2)-e per annum. The contribution from low-temperature oxidation was generally less than about 1% of the total for all six mines. Estimating areas of spoil affected by spontaneous combustion by ground-based surveys was prone to under-report the area. Airborne infrared imaging appears to be a more reliable method.

Preservation and Enhancement of the Spacewatch Data Archives

NASA Technical Reports Server (NTRS)

Larsen, Jeffrey A.

2003-01-01

In March of 1998, the asteroid 1997 XF11 was announced to be potentially hazardous after being tracked over 90 days. A potential two year wait for confirming observations was shortened to under 24 hours because of the existence of archived photographic prediscovery images. Spacewatch was a pioneer in using CCD scanning and possesses a valuable digital archive of its scans. Unfortunately these data are aging on magnetic tape and will soon be lost. Since 1990, the Spacewatch project gathered some 1.5 Terabytes of scan data covering roughly 75,000 degrees of sky to a limiting magnitude of V = 21.5. The data have not yet been mined for all of their asteroids for scientific studies and orbit determination. Spacewatch's real-time motion detection program MODP was constrained by the computers of the era to use simplified image processing algorithms at a reduced efficiency. Jedicke and Herron estimated MODP's efficiency at finding asteroids to be approximately 60 percent to V=18 and improving somewhat thereafter. This lead to a substantial bias correction in their analyses. Larsen has developed a MODP replacement capable in excess of 90 percent efficiency in the same range and able to push a magnitude fainter in completeness. We propose a program of post-processing and re-archiving Spacewatch data. Our scans would be transferred from tape to CD-ROMs and converted to FITS images -- establishing a consistent data format and media for both past and future Spacewatch observations. Larsen's MODP replacement would mine these data for previously undetected motions, which would be made available to the Minor Planet Center and our ongoing asteroid population studies. A searchable observation record would be made generally available for prediscovery work. We estimate the net asteroid yield of this proposal is equivalent to three full years of Spacewatch operations.

The production of consumption: addressing the impact of mineral mining on tuberculosis in southern Africa

PubMed Central

Basu, Sanjay; Stuckler, David; Gonsalves, Gregg; Lurie, Mark

2009-01-01

Background Miners in southern Africa experience incident rates of tuberculosis up to ten times greater than the general population. Migration to and from mines may be amplifying tuberculosis epidemics in the general population. Discussion Migration to and from mineral mines contributes to HIV risks and associated tuberculosis incidence. Health and safety conditions within mines also promote the risk of silicosis (a tuberculosis risk factor) and transmission of tuberculosis bacilli in close quarters. In the context of migration, current tuberculosis prevention and treatment strategies often fail to provide sufficient continuity of care to ensure appropriate tuberculosis detection and treatment. Reports from Lesotho and South Africa suggest that miners pose transmission risks to other household or community members as they travel home undetected or inadequately treated, particularly with drug-resistant forms of tuberculosis. Reducing risky exposures on the mines, enhancing the continuity of primary care services, and improving the enforcement of occupational health codes may mitigate the harmful association between mineral mining activities and tuberculosis incidence among affected communities. Summary Tuberculosis incidence appears to be amplified by mineral mining operations in southern Africa. A number of immediately-available measures to improve continuity of care for miners, change recruitment and compensation practices, and reduce the primary risk of infection may critically mitigate the negative association between mineral mining and tuberculosis. PMID:19785769

Restoration of rare earth mine areas: organic amendments and phytoremediation.

PubMed

Zhou, Lingyan; Li, Zhaolong; Liu, Wen; Liu, Shenghong; Zhang, Limin; Zhong, Liyan; Luo, Ximei; Liang, Hong

2015-11-01

Overexploitation of rare earth mine has caused serious desertification and various environmental issues, and ecological restoration of a mining area is an important concern in China. In this study, experiments involving dry grass landfilling, chicken manure broadcasting, and plant cultivation were carried out to reclaim a rare earth mine area located in Heping County, Guangdong Province, China. The prime focus was to improve soil quality in terms of nutrients, microbial community, enzyme activity, and physicochemical properties so as to reclaim the land. After 2 years of restoration, an increase of organic matter (OM), available potassium (K), available phosphorus (P) levels, and acid phosphatase (ACP) activity and a reduction of the available nitrogen (N) level and urease (URE) activity in soil were achieved compared to the original mined land. The nutrients and enzyme activities in soil with 5 years of restoration were close to or surpass those in the unexploited land as control. The bulk density, total porosity, water holding capacity, pH, and electrical conductivity (EC) of soil were improved, and the number of cultivable microorganisms and the bacterial diversity in soil were greatly increased with time during ecological restoration, especially for surface soil. Furthermore, the artificial vegetation stably grew at the restored mining sites. The results indicated that organic amendments and phytoremediation could ecologically restore the rare earth mining sites and the mined land could finally be planted as farmland.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

Improving root-zone soil properties for Trembling Aspen in a reconstructed mine-site soil

NASA Astrophysics Data System (ADS)

Dyck, M. F.; Sabbagh, P.; Bockstette, S.; Landhäusser, S.; Pinno, B.

2014-12-01

Surface mining activities have significantly depleted natural tree cover, especially trembling aspen (Populus tremuloides), in the Boreal Forest and Aspen Parkland Natural Regions of Alberta. The natural soil profile is usually destroyed during these mining activities and soil and landscape reconstruction is typically the first step in the reclamation process. However, the mine tailings and overburden materials used for these new soils often become compacted during the reconstruction process because they are subjected to high amounts of traffic with heavy equipment. Compacted soils generally have low porosity and low penetrability through increased soil strength, making it difficult for roots to elongate and explore the soil. Compaction also reduces infiltration capacity and drainage, which can cause excessive runoff and soil erosion. To improve the pore size distribution and water transmission, subsoil ripping was carried out in a test plot at Genesee Prairie Mine, Alberta. Within the site, six replicates with two treatments each, unripped (compacted) and ripped (decompacted), were established with 20-m buffers between them. The main objective of this research was to characterize the effects of subsoil ripping on soil physical properties and the longevity of those effects.as well as soil water dynamics during spring snowmelt. Results showed improved bulk density, pore size distribution and water infiltration in the soil as a result of the deep ripping, but these improvements appear to be temporary.

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/.

Multisource geological data mining and its utilization of uranium resources exploration

NASA Astrophysics Data System (ADS)

Zhang, Jie-lin

2009-10-01

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

Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

ERIC Educational Resources Information Center

Tataw, Oben Moses

2013-01-01

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

Fabricating Synthetic Data in Support of Training for Domestic Terrorist Activity Data Mining Research

DTIC Science & Technology

2010-09-01

of Mannheim seeks to produce realistic digital images for student analysis ( Moch & Freiling, 2009). Using instructor generated scripts and the...laboratory. ACM Transactions on Information and System Security, (pp. 262-294). Moch , C., & Freiling, F. (2009). The forensic image generator

EU-FP7-iMars: Analysis of Mars Multi-Resolution Images using Auto-Coregistration, Data Mining and Crowd Source Techniques

NASA Astrophysics Data System (ADS)

Ivanov, Anton; Oberst, Jürgen; Yershov, Vladimir; Muller, Jan-Peter; Kim, Jung-Rack; Gwinner, Klaus; Van Gasselt, Stephan; Morley, Jeremy; Houghton, Robert; Bamford, Steven; Sidiropoulos, Panagiotis

Understanding the role of different planetary surface formation processes within our Solar System is one of the fundamental goals of planetary science research. There has been a revolution in planetary surface observations over the last 15 years, especially in 3D imaging of surface shape. This has led to the ability to be able to overlay different epochs back to the mid-1970s, examine time-varying changes (such as the recent discovery of boulder movement, tracking inter-year seasonal changes and looking for occurrences of fresh craters. Consequently we are seeing a dramatic improvement in our understanding of surface formation processes. Since January 2004, the ESA Mars Express has been acquiring global data, especially HRSC stereo (12.5-25 m nadir images) with 87% coverage with more than 65% useful for stereo mapping. NASA began imaging the surface of Mars, initially from flybys in the 1960s and then from the first orbiter with image resolution less than 100 m in the late 1970s from Viking Orbiter. The most recent orbiter, NASA MRO, has acquired surface imagery of around 1% of the Martian surface from HiRISE (at ≈20 cm) and ≈5% from CTX (≈6 m) in stereo. Within the iMars project (http://i-Mars.eu), a fully automated large-scale processing (“Big Data”) solution is being developed to generate the best possible multi-resolution DTM of Mars. In addition, HRSC OrthoRectified Images (ORI) will be used as a georeference basis so that all higher resolution ORIs will be co-registered to the HRSC DTMs (50-100m grid) products generated at DLR and, from CTX (6-20 m grid) and HiRISE (1-3 m grids) on a large-scale Linux cluster based at MSSL. The HRSC products will be employed to provide a geographic reference for all current, future and historical NASA products using automated co-registration based on feature points and initial results will be shown here. In 2015, many of the entire NASA and ESA orbital images will be co-registered and the updated georeferencing information employed to generate a time series of terrain relief with corrected ORIs back to 1977. Web-GIS using OGC protocols will be employed to allow visual exploration of changes to the surface. Data mining processing chains are being developed to search for changes in the Martian surface from 1971-2015 and the output of this data mining will be compared against the results from citizen scientists’ measurements in a specialized Zooniverse implementation. The final co-registered data sets will be distributed through both European and US channels in a manner to be decided towards the end of the project. Acknowledgements: The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement no. 607379.

A Meta-Analysis of Educational Data Mining on Improvements in Learning Outcomes

ERIC Educational Resources Information Center

AlShammari, Iqbal A.; Aldhafiri, Mohammed D.; Al-Shammari, Zaid

2013-01-01

A meta-synthesis study was conducted of 60 research studies on educational data mining (EDM) and their impacts on and outcomes for improving learning outcomes. After an overview, an examination of these outcomes is provided (Romero, Ventura, Espejo, & Hervas, 2008; Romero, "et al.", 2011). Then, a review of other EDM-related research…

Hydraulic hoisting and backfilling

NASA Astrophysics Data System (ADS)

Sauermann, H. B.

In a country such as South Africa, with its large deep level mining industry, improvements in mining and hoisting techniques could result in substantial savings. Hoisting techniques, for example, may be improved by the introduction of hydraulic hoisting. The following are some of the advantages of hydraulic hoisting as against conventional skip hoisting: (1) smaller shafts are required because the pipes to hoist the same quantity of ore hydraulically require less space in the shaft than does skip hoisting equipment; (2) the hoisting capacity of a mine can easily be increased without the necessity of sinking new shafts. Large savings in capital costs can thus be made; (3) fully automatic control is possible with hydraulic hoisting and therefore less manpower is required; and (4) health and safety conditions will be improved.

Web usage data mining agent

NASA Astrophysics Data System (ADS)

Madiraju, Praveen; Zhang, Yanqing

2002-03-01

When a user logs in to a website, behind the scenes the user leaves his/her impressions, usage patterns and also access patterns in the web servers log file. A web usage mining agent can analyze these web logs to help web developers to improve the organization and presentation of their websites. They can help system administrators in improving the system performance. Web logs provide invaluable help in creating adaptive web sites and also in analyzing the network traffic analysis. This paper presents the design and implementation of a Web usage mining agent for digging in to the web log files.

MGM - MS Reilly holds a container used in the MGM experiment

NASA Image and Video Library

1998-03-04

S89-E-5328 (27 Jan 1998) --- This Electronic Still Camera (ESC) image shows astronaut James F. Reilly, mission specialist, holding the Mechanics of Granular Materials (MGM) experiment. The MGM experiment is aimed at understanding the behavior of granular materials, such as sand or salt, under very low confining pressure. This pressure is the force that keeps a granular material ?sticking together?. The experiment has applications in a wide range of fields, including earthquake engineering; coastal and off-shore engineering; mining; transportation of granular materials; soil erosion; the handling of granular materials such as grains and powders; off-road vehicles; geology of the Earth; and planetary geology and exploration. Findings from the experiment may lead to improved selection and preparation of building sites, better management of undeveloped land, and improved handling of materials in chemical, agricultural and other industries.

Mapping Environmental Contaminants at Ray Mine, AZ

NASA Technical Reports Server (NTRS)

McCubbin, Ian; Lang, Harold

2000-01-01

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

Tree planting - strip-mined area in Maryland

Treesearch

Fred L. Bagley

1980-01-01

This report is written to elucidate some of the problems encountered in the planting of trees on strip-mined areas in Maryland. When problems are recognized, normally a solution (or at least, an improvement) can be instituted to alleviate the problem. The methods cited herein are those of experienced foresters engaged in strip-mine planting during the past seventeen...

Fusion of Local Statistical Parameters for Buried Underwater Mine Detection in Sonar Imaging

NASA Astrophysics Data System (ADS)

Maussang, F.; Rombaut, M.; Chanussot, J.; Hétet, A.; Amate, M.

2008-12-01

Detection of buried underwater objects, and especially mines, is a current crucial strategic task. Images provided by sonar systems allowing to penetrate in the sea floor, such as the synthetic aperture sonars (SASs), are of great interest for the detection and classification of such objects. However, the signal-to-noise ratio is fairly low and advanced information processing is required for a correct and reliable detection of the echoes generated by the objects. The detection method proposed in this paper is based on a data-fusion architecture using the belief theory. The input data of this architecture are local statistical characteristics extracted from SAS data corresponding to the first-, second-, third-, and fourth-order statistical properties of the sonar images, respectively. The interest of these parameters is derived from a statistical model of the sonar data. Numerical criteria are also proposed to estimate the detection performances and to validate the method.

Correlation Between Bulk Material Defects and Spectroscopic Response in Cadmium Zinc Telluride Detectors

NASA Technical Reports Server (NTRS)

Parker, Bradford H.; Stahle, C. M.; Barthelmy, S. D.; Parsons, A. M.; Tueller, J.; VanSant, J. T.; Munoz, B. F.; Snodgrass, S. J.; Mullinix, R. E.

1999-01-01

One of the critical challenges for large area cadmium zinc telluride (CdZnTe) detector arrays is obtaining material capable of uniform imaging and spectroscopic response. Two complementary nondestructive techniques for characterizing bulk CdZnTe have been developed to identify material with a uniform response. The first technique, infrared transmission imaging, allows for rapid visualization of bulk defects. The second technique, x-ray spectral mapping, provides a map of the material spectroscopic response when it is configured as a planar detector. The two techniques have been used to develop a correlation between bulk defect type and detector performance. The correlation allows for the use of infrared imaging to rapidly develop wafer mining maps. The mining of material free of detrimental defects has the potential to dramatically increase the yield and quality of large area CdZnTe detector arrays.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

Millennium Open Pit Mine, Alberta, Canada

NASA Technical Reports Server (NTRS)

2007-01-01

Near Fort McMurray, Alberta, Canada, on the east bank of the Athabasca River, are found the Steepbank and Millennium mines. These open pit mines produce oil sands that are processed to recover bitumen, and then upgrade it to refinery-ready raw crude oil, and diesel fuel.

The ASTER images were acquired September 22, 2000 and July 31, 2007, cover an area of 22.5 x 25.5 km, and are located near 57 degrees north latitude, 111.5 degrees west longitude.

The U.S. science team is located at NASA's Jet Propulsion Laboratory, Pasadena, Calif. The Terra mission is part of NASA's Science Mission Directorate.

Flooding at Iron-Ore Mine, SE Brazil

NASA Image and Video Library

2015-11-14

On Nov. 5, 2015, a dam at an iron-ore mine in southeastern Brazil burst, sending a wall of water, clay-red mud and debris downstream, overwhelming several villages in the path as seen by NASA Terra spacecraft. The Germano mine is near the town of Mariana in Minas Gerais state. The region is seen in this image from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument aboard NASA's Terra spacecraft was acquired Nov. 12, 2015, covers an area of 6.8 by 14.3 miles (11 by 23 kilometers), and is located at 20.2 degrees south, 43.5 degrees west. http://photojournal.jpl.nasa.gov/catalog/PIA20156

Intervention strategies to eliminate truck-related fatalities in surface coal mining in West Virginia.

PubMed

Zhang, Meng; Kecojevic, Vladislav

2016-01-01

The main objective of this review was to build upon a previous study on the root causes of truck-related fatalities in surface coal mining operations in West Virginia, and to develop intervention strategies to eliminate these fatalities. This review considers a two-pronged approach to accident prevention: one that is fundamental and traditional (safety regulations, training and education, and engineering of the work environment); and one that is innovative and creative (e.g., applying technological advances to better control and eliminate the root causes of accidents). Suggestions for improving current training and education system are proposed, and recommendations are provided on improving the safety of mine working conditions, specifically safety conditions on haul roads, dump sites, and loading areas. We also discuss various currently available technologies that can help prevent haul truck-related fatal accidents. The results of this review should be used by mine personnel to help create safer working conditions and decrease truck-related fatalities in surface coal mining.

Improvement of a method for positioning of pithead by considering motion of the surface water

NASA Astrophysics Data System (ADS)

Yi, H.; Lee, D. K.

2016-12-01

Underground mining has weakness compared with open pit mining in aspects of efficiency, economy and working environment. However, the method has applied for the development of a deep orebody. Development plan is established when the economic valuation and technical analysis of the deposits is completed through exploration of mineral resources. Development is a process to open a passage from the ground surface to the orebody as one of the steps of mining process. In the planning, there are details such as pithead positioning, mining method selection, and shaft design, etc. Among these, pithead positioning is implemented by considering infrastructures, watershed, geology, and economy. In this study, we propose a method to consider the motion of the surface waters in order to improve the existing pithead positioning techniques. The method contemplates the terrain around the mine and makes the surface water flow information. Then, the drainage treatment cost for each candidate location of pithead is suggested. This study covers the concept and design of the scheme.

Challenges with minimising mercury pollution in the small-scale gold mining sector: experiences from the Guianas.

PubMed

Hilson, Gavin; Vieira, Rickford

2007-12-01

This paper examines the barriers to mitigating mercury pollution at small-scale gold mines in the Guianas (Guyana, French Guiana and Suriname), and prescribes recommendations for overcoming these obstacles. Whilst considerable attention has been paid to analysing the environmental impacts of operations in the region, minimal research has been undertaken to identify appropriate policy and educational initiatives for addressing the mounting mercury problem. Findings from recent fieldwork and selected interviews with operators from Guyanese and Surinamese gold mining regions reveal that legislative incapacity, the region's varied industry policy stances, various technological problems, and low environmental awareness on the part of communities are impeding efforts to facilitate improved mercury management at small-scale gold mines in the Guianas. Marked improvements can be achieved, however, if legislation, particularly that pertaining to mercury, is harmonised in the region; educational seminars continue to be held in important mining districts; and additional outlets for disseminating environmental equipment and mercury-free technologies are provided.

The Role of Ground Truth in Improved Identification of Mining Explosion Signals Utilization of Calibration Explosions and Acoustic Signals

DTIC Science & Technology

2000-09-01

and the Porphyry Copper District (PCD) of east central Arizona and south west New Mexico were used in gathering ground truth ranging from mine records...previous studies of large coal cast blasting operations in Wyoming that trigger the IMS (Hedlin et al. 2000), the porphyry copper region of Arizona and...local mines producing the sources. Close cooperation has been developed with the Phelps Dodge mines in Morenci, Arizona and Tyrone, New Mexico where in

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.

Implicit prosody mining based on the human eye image capture technology

NASA Astrophysics Data System (ADS)

Gao, Pei-pei; Liu, Feng

2013-08-01

The technology of eye tracker has become the main methods of analyzing the recognition issues in human-computer interaction. Human eye image capture is the key problem of the eye tracking. Based on further research, a new human-computer interaction method introduced to enrich the form of speech synthetic. We propose a method of Implicit Prosody mining based on the human eye image capture technology to extract the parameters from the image of human eyes when reading, control and drive prosody generation in speech synthesis, and establish prosodic model with high simulation accuracy. Duration model is key issues for prosody generation. For the duration model, this paper put forward a new idea for obtaining gaze duration of eyes when reading based on the eye image capture technology, and synchronous controlling this duration and pronunciation duration in speech synthesis. The movement of human eyes during reading is a comprehensive multi-factor interactive process, such as gaze, twitching and backsight. Therefore, how to extract the appropriate information from the image of human eyes need to be considered and the gaze regularity of eyes need to be obtained as references of modeling. Based on the analysis of current three kinds of eye movement control model and the characteristics of the Implicit Prosody reading, relative independence between speech processing system of text and eye movement control system was discussed. It was proved that under the same text familiarity condition, gaze duration of eyes when reading and internal voice pronunciation duration are synchronous. The eye gaze duration model based on the Chinese language level prosodic structure was presented to change previous methods of machine learning and probability forecasting, obtain readers' real internal reading rhythm and to synthesize voice with personalized rhythm. This research will enrich human-computer interactive form, and will be practical significance and application prospect in terms of disabled assisted speech interaction. Experiments show that Implicit Prosody mining based on the human eye image capture technology makes the synthesized speech has more flexible expressions.

Improving surface stability of elevated spoil landforms using natural landform analogy and geological information

NASA Astrophysics Data System (ADS)

Emmerton, Bevan; Burgess, Jon; Esterle, Joan; Erskine, Peter; Baumgartl, Thomas

2017-04-01

Large-scale open cut mining in the Bowen Basin, Queensland, Australia has undergone an evolutionary process over the period of a few decades, transitioning from shallow mining depths, limited spoil elevation and pasture based rehabilitation to increased mining depths, escalating pre-stripping, elevated mesa-like landforms and native woody species rehabilitation. As a consequence of this development, the stabilisation of recent constructed landforms has to be assured through means other than the establishment of vegetative cover. Recent developments are the specific selection and partitioning of resilient fragmental spoil types for the construction of final landform surface. They can also be used as cladding resources for stabilizing steep erosive batters and this has been identified as a practical methodology that has the potential to significantly improve rehabilitation outcomes. Examples of improvements are an increase of the surface rock cover, roughness and infiltration and reducing inherent erodibility and runoff and velocity of surface flow. However, a thorough understanding of the properties and behavior of individual spoil materials disturbed during mining is required. Relevant information from published literature on the geological origins, lithology and weathering characteristics of individual strata within the Bowen Basin Coal Measures located in Queensland, Australia (and younger overlying weathered strata) has been studied, and related both to natural landforms and to the surface stability of major strata types when disturbed by mining. The resulting spoil classification developed from this study is based primarily on inherent geological characteristics and weathering behaviour of identifiable lithologic components, and as such describes the expected fragmental resilience likely within disturbed materials at Bowen Basin coal mines. The proposed classification system allows the allocation of spoil types to use categories which have application in pre-mine feasibility investigations, landform design and material selection and placement. It finds its application by practitioners who find encouragement in using this approach of a relatively easy usable classification system to improve the overall outcome of rehabilitation through selection of optimal substrates.

Rational Use of Land Resource During the Implementation of Transportless System of Coal Strata Surface Mining

NASA Astrophysics Data System (ADS)

Gvozdkova, T.; Tyulenev, M.; Zhironkin, S.; Trifonov, V. A.; Osipov, Yu M.

2017-01-01

Surface mining and open pits engineering affect the environment in a very negative way. Among other pollutions that open pits make during mineral deposits exploiting, particular problem is the landscape changing. Along with converting the land into pits, surface mining is connected with pilling dumps that occupy large ground. The article describes an analysis of transportless methods of several coal seams strata surface mining, applied for open pits of South Kuzbass coal enterprises (Western Siberia, Russia). To improve land-use management of open pit mining enterprises, the characteristics of transportless technological schemes for several coal seams strata surface mining are highlighted and observed. These characteristics help to systematize transportless open mining technologies using common criteria that characterize structure of the bottom part of a strata and internal dumping schemes. The schemes of transportless systems of coal strata surface mining implemented in South Kuzbass are given.

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

AMULET: A MUlti-cLuE Approach to Image Forensics

DTIC Science & Technology

2014-12-31

celebrities have been substituted in the other two pictures. 3.2.5 Choice of reliability properties Let us now apply the BBA mapping approach proposed in...Jiang, and L. Ma, “Ds evidence theory based digital image trustworthiness evaluation model,” in MINES 2009, International Conference on Multimedia

Intelligent ePR system for evidence-based research in radiotherapy: proton therapy for prostate cancer.

PubMed

Le, Anh H; Liu, Brent; Schulte, Reinhard; Huang, H K

2011-11-01

Proton therapy (PT) utilizes high energy particle proton beam to kill cancer cells at the target region for target cancer therapy. Due to the physical properties of the proton beam, PT delivers dose with higher precision and no exit dose compared to conventional radiotherapy. In PT, patient data are distributed among multiple systems, a hindrance to research on efficacy and effectiveness. A data mining method and a treatment plan navigator utilizing the infrastructure and data repository of a PT electronic patient record (ePR) was developed to minimize radiation toxicity and improve outcomes in prostate cancer treatment. MATERIALS/METHOD(S): The workflow of a proton therapy treatment in a radiation oncology department was reviewed, and a clinical data model and data flow were designed. A prototype PT ePR system with DICOM compliance was developed to manage prostate cancer patient images, treatment plans, and related clinical data. The ePR system consists of four main components: (1) Data Gateway; (2) ePR Server; (3) Decision Support Tools; and (4) Visualization and Display Tools. Decision support and visualization tools are currently developed based on DICOM images, DICOM-RT and DICOM-RT-ION objects data from prostate cancer patients treated with hypofractionation protocol proton therapy were used for evaluating ePR system effectiveness. Each patient data set includes a set of computed tomography (CT) DICOM images and four DICOM-RT and RT-ION objects. In addition, clinical outcomes data collected from PT cases were included to establish a knowledge base for outcomes analysis. A data mining search engine and an intelligent treatment plan navigator (ITPN) were developed and integrated with the ePR system. Evaluation was based on a data set of 39 PT patients and a hypothetical patient. The ePR system was able to facilitate the proton therapy workflow. The PT ePR system was feasible for prostate cancer patient treated with hypofractionation protocol in proton therapy. This ePR system improves efficiency in data collection and integration to facilitate outcomes analysis.

The effect of cap lamp lighting on postural control and stability

PubMed Central

Sammarco, John J.; Pollard, Jonisha P.; Porter, William L.; Dempsey, Patrick G.; Moore, Caitlin T.

2015-01-01

Researchers at the National Institute for Occupational Safety and Health (NIOSH) are conducting mine illumination research with the objective of improving miner safety. Slips, trips, and falls (STFs) are the second leading accident class (18.1%, n = 2,374) of nonfatal lost-time injuries at underground mines (MSHA, 2005–2009). Factors contributing to STFs include recognition of hazards as well as postural balance and age. Improved lighting may enable better hazard recognition and reduce the impact of postural balance and age. Previous research has shown that cap lamp technology that used light-emitting diodes (LEDs) has improved hazard detection. This study was an initial investigation to determine if cap lamp lighting significantly influences measures of static postural stability (displacement and velocity of center of pressure). Results of this investigation showed no significant differences in the balance measures of interest between cap lamps tested. However, balance was shown to significantly decline (p < 0.05) when tested in an underground coal mine compared to the laboratory testing condition. Relevance to industry: Underground coal mine workers wear cap lamps on their hard hats as their primary light source to illuminate nearby areas where their vision is directed. Proper illumination may improve miner safety by improving their STF hazard recognition and balance. PMID:26472917

Applying data mining techniques to improve diagnosis in neonatal jaundice.

PubMed

Ferreira, Duarte; Oliveira, Abílio; Freitas, Alberto

2012-12-07

Hyperbilirubinemia is emerging as an increasingly common problem in newborns due to a decreasing hospital length of stay after birth. Jaundice is the most common disease of the newborn and although being benign in most cases it can lead to severe neurological consequences if poorly evaluated. In different areas of medicine, data mining has contributed to improve the results obtained with other methodologies.Hence, the aim of this study was to improve the diagnosis of neonatal jaundice with the application of data mining techniques. This study followed the different phases of the Cross Industry Standard Process for Data Mining model as its methodology.This observational study was performed at the Obstetrics Department of a central hospital (Centro Hospitalar Tâmega e Sousa--EPE), from February to March of 2011. A total of 227 healthy newborn infants with 35 or more weeks of gestation were enrolled in the study. Over 70 variables were collected and analyzed. Also, transcutaneous bilirubin levels were measured from birth to hospital discharge with maximum time intervals of 8 hours between measurements, using a noninvasive bilirubinometer.Different attribute subsets were used to train and test classification models using algorithms included in Weka data mining software, such as decision trees (J48) and neural networks (multilayer perceptron). The accuracy results were compared with the traditional methods for prediction of hyperbilirubinemia. The application of different classification algorithms to the collected data allowed predicting subsequent hyperbilirubinemia with high accuracy. In particular, at 24 hours of life of newborns, the accuracy for the prediction of hyperbilirubinemia was 89%. The best results were obtained using the following algorithms: naive Bayes, multilayer perceptron and simple logistic. The findings of our study sustain that, new approaches, such as data mining, may support medical decision, contributing to improve diagnosis in neonatal jaundice.

Computational Analysis Supporting the Design of a New Beamline for the Mines Neutron Radiography Facility

NASA Astrophysics Data System (ADS)

Wilson, C.; King, J.

The Colorado School of Mines installed a neutron radiography system at the United States Geological Survey TRIGA reactor in 2012. An upgraded beamline could dramatically improve the imaging capabilities of this system. This project performed computational analyses to support the design of a new beamline, with the major goals of minimizing beam divergence and maximizing beam intensity. The new beamline will consist of a square aluminum tube with an 11.43 cm (4.5 in) inner side length and 0.635 cm (0.25 in) thick walls. It is the same length as the original beam tube (8.53 m) and is composed of 1.22 m (4 ft) and 1.52 m (5 ft) flanged sections which bolt together. The bottom 1.22 m of the beamline is a cylindrical aluminum pre-collimator which is 0.635 cm (0.25 in) thick, with an inner diameter of 5.08 cm (2 in). Based on Monte Carlo model results, when a pre-collimator is present, the use of a neutron absorbing liner on the inside surface of the beam tube has almost no effect on the angular distribution of the neutron current at the collimator exit. The use of a pre-collimator may result in a non-uniform flux profile at the image plane; however, as long as the collimator is at least three times longer than the pre-collimator, the flux distortion is acceptably low.

Improving Job Site Skills Project. Preliminary Report. Local 343 United Brotherhood of Carpenters & Joiners of America & Construction Labour Relations Association of Manitoba. Northern Industrial Job Site Visit Report. Environmental Improvement Project, Hudson Bay Mining and Smelting, Flin Flon, Manitoba.

ERIC Educational Resources Information Center

McKeag, Janis; Todd, Laurie

The Environmental Improvement Project at Hudson Bay Mining and Smelting in Flin Flon, Manitoba, presented a unique opportunity for field observation and assessment. Field observation of the approximately 70 carpenters employed with various companies provided information on the types of communication used and the circumstances in which the…

Complex Event Processing for Content-Based Text, Image, and Video Retrieval

DTIC Science & Technology

2016-06-01

NY): Wiley- Interscience; 2000. Feldman R, Sanger J. The text mining handbook: advanced approaches in analyzing unstructured data. New York (NY...ARL-TR-7705 ● JUNE 2016 US Army Research Laboratory Complex Event Processing for Content-Based Text , Image, and Video Retrieval...ARL-TR-7705 ● JUNE 2016 US Army Research Laboratory Complex Event Processing for Content-Based Text , Image, and Video Retrieval

Environmental Characterization of Mine Countermeasure Test Ranges: Hydrography and Water Column Optics

DTIC Science & Technology

2015-09-30

changes in near-shore water columns and support companion laser imaging system tests. The physical, biological and optical oceanographic data...developed under this project will be used as input to optical and environmental models to assess the performance characteristics of laser imaging systems...OBJECTIVES We proposed to characterize the physical, biological and optical fields present during deployments of the Streak Tube Imaging Lidar

Improving UXO Detection and Discrimination in Magnetic Environments

DTIC Science & Technology

2010-05-01

Krahenbuhl, Todd Meglich Center for Gravity, Electrical , & Magnetic Studies Department of Geophysics Colorado School of Mines Doug Oldenburg, Len...NAME(S) AND ADDRESS(ES) Colorado School of Mines,Department of Geophysics,Center for Gravity, Electrical , & Magnetic Studies,Golden,CO,80401 8...SERDP Project MM-1414 Improving UXO Detection and Discrimination in Magnetic Environments Final Report Center for Gravity, Electrical , & Magnetic Studies

Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains

ERIC Educational Resources Information Center

Liu, Ran; Koedinger, Kenneth R.

2017-01-01

As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…

Model architecture of intelligent data mining oriented urban transportation information

NASA Astrophysics Data System (ADS)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

Applied Behavior Analysis Is Ideal for the Development of a Land Mine Detection Technology Using Animals

ERIC Educational Resources Information Center

Jones, B. M.

2011-01-01

The detection and subsequent removal of land mines and unexploded ordnance (UXO) from many developing countries are slow, expensive, and dangerous tasks, but have the potential to improve the well-being of millions of people. Consequently, those involved with humanitarian mine and UXO clearance are actively searching for new and more efficient…

Functional Quality Criterion of Rock Handling Mechanization at Open-pit Mines

NASA Astrophysics Data System (ADS)

Voronov, Yuri; Voronov, Artyoni

2017-11-01

Overburden and mining operations at open-pit mines are performed mainly by powerful shovel-truck systems (STSs). One of the main problems of the STSs is a rather low level of their operating quality, mainly due to unjustified over-trucking. In this article, a functional criterion for assessing the qualify of the STS operation at open-pit mines is formulated, derived and analyzed. We introduce the rationale and general principles for the functional criterion formation, its general form, as well as variations for various STS structures: a mixed truck fleet and a homogeneous shovel fleet, a mixed shove! fleet and a homogeneous truck fleet, mixed truck and shovel fleets. The possibility of assessing the quality of the STS operation is of great importance for identifying the main directions for improving their operational performance and operating quality, optimizing the main performance indicators by the qualify criterion, and. as a result, for possible saving of material and technical resources for open-pit mining. Improvement of the quality of the STS operation also allows increasing the mining safety and decreasing the atmosphere pollution - by means of possible reducing of the number of the operating trucks.

Improving awareness of mercury pollution in small-scale gold mining communities: challenges and ways forward in rural Ghana.

PubMed

Hilson, Gavin; Hilson, Christopher J; Pardie, Sandra

2007-02-01

This paper critiques the approach taken by the Ghanaian Government to address mercury pollution in the artisanal and small-scale gold mining sector. Unmonitored releases of mercury-used in the gold-amalgamation process-have caused numerous environmental complications throughout rural Ghana. Certain policy, technological and educational initiatives taken to address the mounting problem, however, have proved marginally effective at best, having been designed and implemented without careful analysis of mine community dynamics, the organization of activities, operators' needs and local geological conditions. Marked improvements can only be achieved in this area through increased government-initiated dialogue with the now-ostracized illegal galamsey mining community; introducing simple, cost-effective techniques for the reduction of mercury emissions; and effecting government-sponsored participatory training exercises as mediums for communicating information about appropriate technologies and the environment.

A Closed Network Queue Model of Underground Coal Mining Production, Failure, and Repair

NASA Technical Reports Server (NTRS)

Lohman, G. M.

1978-01-01

Underground coal mining system production, failures, and repair cycles were mathematically modeled as a closed network of two queues in series. The model was designed to better understand the technological constraints on availability of current underground mining systems, and to develop guidelines for estimating the availability of advanced mining systems and their associated needs for spares as well as production and maintenance personnel. It was found that: mine performance is theoretically limited by the maintainability ratio, significant gains in availability appear possible by means of small improvements in the time between failures the number of crews and sections should be properly balanced for any given maintainability ratio, and main haulage systems closest to the mine mouth require the most attention to reliability.

a Hyperspectral Image Classification Method Using Isomap and Rvm

NASA Astrophysics Data System (ADS)

Chang, H.; Wang, T.; Fang, H.; Su, Y.

2018-04-01

Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes' ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.

Relocation of net-acid-generating waste to improve post-mining water chemistry.

PubMed

Morin, K A; Hutt, N M

2001-01-01

Acidic drainage and metal leaching are long-term environmental liabilities that can persist for many decades to millennia. One technique to improve the water chemistry and ecology of post-mining landscapes is to relocate and submerge net-acid-generating mine materials in a lake or water-retaining impoundment. One example of a carefully executed relocation of waste rock took place at the Eskay Creek Mine in Canada. Pre-relocation studies included an empirical relationship that related (1) the amount of acidity retained by the waste rock during past oxidation to (2) the amount of lime needed in each truckload for neutralization of the acidity and for suppression of metal release. During relocation, thousands of rinse pH measurements indicated net acidity varied significantly over short distances within the waste rock and that acidic rock could not be reliably segregated from near-netural rock. After relocation, water from the watershed continued to be acidic for a few years, then returned to near-neutral pH and near-background concentrations of metals. The chemistry of the lake where the waste rock was submerged remains near background conditions. Therefore, with careful planning and implementation, the relocation and submergence of net-acid-generating materials can greatly improve post-mining water chemistry.

Image analysis and machine learning in digital pathology: Challenges and opportunities.

PubMed

Madabhushi, Anant; Lee, George

2016-10-01

With the rise in whole slide scanner technology, large numbers of tissue slides are being scanned and represented and archived digitally. While digital pathology has substantial implications for telepathology, second opinions, and education there are also huge research opportunities in image computing with this new source of "big data". It is well known that there is fundamental prognostic data embedded in pathology images. The ability to mine "sub-visual" image features from digital pathology slide images, features that may not be visually discernible by a pathologist, offers the opportunity for better quantitative modeling of disease appearance and hence possibly improved prediction of disease aggressiveness and patient outcome. However the compelling opportunities in precision medicine offered by big digital pathology data come with their own set of computational challenges. Image analysis and computer assisted detection and diagnosis tools previously developed in the context of radiographic images are woefully inadequate to deal with the data density in high resolution digitized whole slide images. Additionally there has been recent substantial interest in combining and fusing radiologic imaging and proteomics and genomics based measurements with features extracted from digital pathology images for better prognostic prediction of disease aggressiveness and patient outcome. Again there is a paucity of powerful tools for combining disease specific features that manifest across multiple different length scales. The purpose of this review is to discuss developments in computational image analysis tools for predictive modeling of digital pathology images from a detection, segmentation, feature extraction, and tissue classification perspective. We discuss the emergence of new handcrafted feature approaches for improved predictive modeling of tissue appearance and also review the emergence of deep learning schemes for both object detection and tissue classification. We also briefly review some of the state of the art in fusion of radiology and pathology images and also combining digital pathology derived image measurements with molecular "omics" features for better predictive modeling. The review ends with a brief discussion of some of the technical and computational challenges to be overcome and reflects on future opportunities for the quantitation of histopathology. Copyright © 2016 Elsevier B.V. All rights reserved.

Russian thistle for soil mulch in coal mine reclamation

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

Day, A.D.; Tucker, T.C.; Thames, J.L.

1979-01-01

The effectiveness of Russian thistle mulch in reducing soil moisture loss from coal mine soil was gauged and compared with the effectiveness of barley straw mulch. The decrease in soil moisture loss after mulch addition was greater in a low temperature, high humidity environment. Russian thistle mulch was as effective as barley straw in reducing soil moisture loss in Red Mesa loam, unmined soil, and coal mine soil. Because Russian thistle can be grown on mine spoils and has a higher organic volume than barley straw mulch has, treatment of mine soil with thistle will improve soil characteristics and plantmore » growth. (14 references, 1 table)« less

Evaluation of airborne thermal infrared imagery for locating mine drainage sites in the Lower Kettle Creek and Cooks Run Basins, Pennsylvania, USA

USGS Publications Warehouse

Sams, James I.; Veloski, Garret

2003-01-01

High-resolution airborne thermal infrared (TIR) imagery data were collected over 90.6 km2 (35 mi2) of remote and rugged terrain in the Kettle Creek and Cooks Run Basins, tributaries of the West Branch of the Susquehanna River in north-central Pennsylvania. The purpose of this investigation was to evaluate the effectiveness of TIR for identifying sources of acid mine drainage (AMD) associated with abandoned coal mines. Coal mining from the late 1800s resulted in many AMD sources from abandoned mines in the area. However, very little detailed mine information was available, particularly on the source locations of AMD sites. Potential AMD sources were extracted from airborne TIR data employing custom image processing algorithms and GIS data analysis. Based on field reconnaissance of 103 TIR anomalies, 53 sites (51%) were classified as AMD. The AMD sources had low pH (<4) and elevated concentrations of iron and aluminum. Of the 53 sites, approximately 26 sites could be correlated with sites previously documented as AMD. The other 27 mine discharges identified in the TIR data were previously undocumented. This paper presents a summary of the procedures used to process the TIR data and extract potential mine drainage sites, methods used for field reconnaissance and verification of TIR data, and a brief summary of water-quality data.

Land use-based landscape planning and restoration in mine closure areas.

PubMed

Zhang, Jianjun; Fu, Meichen; Hassani, Ferri P; Zeng, Hui; Geng, Yuhuan; Bai, Zhongke

2011-05-01

Landscape planning and restoration in mine closure areas is not only an inevitable choice to sustain mining areas but also an important path to maximize landscape resources and to improve ecological function in mine closure areas. The analysis of the present mine development shows that many mines are unavoidably facing closures in China. This paper analyzes the periodic impact of mining activities on landscapes and then proposes planning concepts and principles. According to the landscape characteristics in mine closure areas, this paper classifies available landscape resources in mine closure areas into the landscape for restoration, for limited restoration and for protection, and then summarizes directions for their uses. This paper establishes the framework of spatial control planning and design of landscape elements from "macro control, medium allocation and micro optimization" for the purpose of managing and using this kind of special landscape resources. Finally, this paper applies the theories and methods to a case study in Wu'an from two aspects: the construction of a sustainable land-use pattern on a large scale and the optimized allocation of typical mine landscape resources on a small scale.

Unsupervised iterative detection of land mines in highly cluttered environments.

PubMed

Batman, Sinan; Goutsias, John

2003-01-01

An unsupervised iterative scheme is proposed for land mine detection in heavily cluttered scenes. This scheme is based on iterating hybrid multispectral filters that consist of a decorrelating linear transform coupled with a nonlinear morphological detector. Detections extracted from the first pass are used to improve results in subsequent iterations. The procedure stops after a predetermined number of iterations. The proposed scheme addresses several weaknesses associated with previous adaptations of morphological approaches to land mine detection. Improvement in detection performance, robustness with respect to clutter inhomogeneities, a completely unsupervised operation, and computational efficiency are the main highlights of the method. Experimental results reveal excellent performance.

Environmental Improvement Of Opencast Mining

NASA Astrophysics Data System (ADS)

Prokopenko, S.; Sushko, A.; Filatov, Yu; Kislyakov, M.; Kislyakov, I.

2017-01-01

Existing classifications of waste dumps in the quarries are given and their phenomenological nature is clarified. The need to identify the essence of the term "dump" is shown as well as the idea of "dump" as an artificial formation with everted and mixed rocks distanced from the quarry. Essential classification of man-made rock formations in quarries is developed. Characteristic of variations of man-made waste formations in quarries is developed. To reduce harmful effects of open-pit mining, dumps should be substituted with strat-lays - man-made structures relevant to natural stratification of litho-substances. Construction of strat-lays would improve ecological and technological culture of open cast mining.

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

Not Available

In fiscal 1982, the mine safety record improved in several categories over the previous year, but declined in others. There were 220 mining deaths in fiscal year 1982 compared to 222 fatalities in 1981. In coal mining, there were 160 fatalities in fiscal 1982 compared with 131 the previous year. In metal and nonmetal mining in fiscal 1982, there were 60 fatalities, compared to 91 deaths recorded in fiscal 1981. In coal mining, the fatality rate, which factors in employment variations, was .07 per 200,000 employee-hours worked in fiscal 1982 compared to a .06 rate during the previous year. Inmore » metal and nonmetal mining, the fatality rate per 200,000 employee-hours was .04 in fiscal 1982 compared with .03 the previous year. In both industries, the rates of all injuries declined. On Dec. 7, 1981, an underground coal mine dust explosion took the lives of eight miners at the Adkins Coal Co,'s No. 11 mine at Kite, Knott County, KY. A day later, Dec. 8, 1981, an underground coal mine explosion killed 13 miners at Grundy Mining Co.'s No. 21 mine at Whitwell, Marion County, Tenn. During the following month, on Jan. 20, 1982, another coal mine dust explosion killed seven underground coal miners at the RFH mine in Craynor, Floyd County, KY. 7 figs., 33 tabs.« less

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.

Mapping of the dilemma of mining against forest and conservation in the Lom and Djérem Division, Cameroon

NASA Astrophysics Data System (ADS)

Tchindjang, Mesmin; Voundi, Eric; Mbevo Fendoung, Philippes; Haman, Unusa; Saha, Frédéric; Casimir Njombissie Petcheu, Igor

2018-05-01

Mining practices in Cameroon began since the colonial period. The artisanal mining sector before independence contributed to 11-20 % of GDP. From 2000, the rich potential of the Cameroonian subsoil attract many foreign investors with over 600 research and mining permits already granted during the last decade. But, Cameroonian forests also have a long history from the colonial period to the pre-sent. However, mining activities in forest environments are governed by two different legal frameworks, including mining code i.e. Law No. 001 of 16 April 2001 organizing the mining industry and Law No. 94-01 of 20 January 1994 governing forests, wildlife and fisheries. Therefore, in the absence of detailed studies of these laws, there are conflicts of interests, rights and obligations that overlap, requiring research needs and taking appropriate decisions. The objective of this research in the Lom and Djérem division is to study, apart from the proliferation of mining li-censes and actors, the dilemma as well as the impact of the extension of mining activities on the degradation of forest cover. Using geospatial tools through multi-temporal and multisensor satellite images (Landsat from 1976 to 2015, IKONOS, GEOEYE, Google Earth) coupled with field investigations; we mapped the dynamic of different forms of land use (mining permits, FMU and protected areas of permanent forest estate) and highlighted paradoxically the conflict of land use. We came to the conclusion that the rhythm of issuing mining permits and authorizations in this forestall zone is so fast that one can wonder whether we still find a patch of forest within 50 years.

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

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Russell, O. R.; Martin, K. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Mined land reclamation analysis procedures developed within the Indiana portion of the Illinois Coal Basin were independently tested in Ohio utilizing 1:80,000 scale enlargements of ERTS-1 image 1029-15361-7 (dated August 21, 1972). An area in Belmont County was selected for analysis due to the extensive surface mining and the different degrees of reclamation occurring in this area. Contour mining in this area provided the opportunity to extend techniques developed for analysis of relatively flat mining areas in Indiana to areas of rolling topography in Ohio. The analysts had no previous experience in the area. Field investigations largely confirmed office analysis results although in a few areas estimates of vegetation percentages were found to be too high. In one area this error approximated 25%. These results suggest that systematic ERTS-1 analysis in combination with selective field sampling can provide reliable vegetation percentage estimates in excess of 25% accuracy with minimum equipment investment and training. The utility of ERTS-1 for practical and reasonably reliable update of mined lands information for groups with budget limitations is suggested. Many states can benefit from low cost updates using ERTS-1 imagery from public sources.

Using temporarily coherent point interferometric synthetic aperture radar for land subsidence monitoring in a mining region of western China

NASA Astrophysics Data System (ADS)

Fan, Hongdong; Xu, Qiang; Hu, Zhongbo; Du, Sen

2017-04-01

Yuyang mine is located in the semiarid western region of China where, due to serious land subsidence caused by underground coal exploitation, the local ecological environment has become more fragile. An advanced interferometric synthetic aperture radar (InSAR) technique, temporarily coherent point InSAR, is applied to measure surface movements caused by different mining conditions. Fifteen high-resolution TerraSAR-X images acquired between October 2, 2012, and March 27, 2013, were processed to generate time-series data for ground deformation. The results show that the maximum accumulated values of subsidence and velocity were 86 mm and 162 mm/year, respectively; these measurements were taken above the fully mechanized longwall caving faces. Based on the dynamic land subsidence caused by the exploitation of one working face, the land subsidence range was deduced to have increased 38 m in the mining direction with 11 days' coal extraction. Although some mining faces were ceased in 2009, they could also have contributed to a small residual deformation of overlying strata. Surface subsidence of the backfill mining region was quite small, the maximum only 21 mm, so backfill exploitation is an effective method for reducing the land subsidence while coal is mined.

Comparison of Landsat Thematic Mapper and Geophysical and Environmental Research Imaging Spectrometer data for the Cuprite mining district, Esmeralda, and Nye counties, Nevada

NASA Technical Reports Server (NTRS)

Kierein-Young, Kathryn S.; Kruse, Fred A.

1989-01-01

Landsat TM images and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data were analyzed for the Cuprite mining district and compared to available geologic and alteration maps of the area. The TM data, with 30 m resolution and 6 broadbands, allowed discrimination of general mineral groups. Clay minerals, playa deposits, and unaltered rocks were mapped as discrete spectral units using the TM data, but specific minerals were not determined, and definition of the individual alteration zones was not possible. The GERIS, with 15 m spatial resolution and 63 spectral bands, permitted construction of complete spectra and identification of specific minerals. Detailed spectra extracted from the images provided the ability to identify the minerals alunite, kaolinite, hematite, and buddingtonite by their spectral characteristics. The GERIS data show a roughly concentrically zoned hydrothermal system. The mineralogy mapped with the aircraft system conforms to previous field and multispectral image mapping. However, identification of individual minerals and spatial display of the dominant mineralogy add information that can be used to help determine the morphology and genetic origin of the hydrothermal system.

Fusion of radar and ultrasound sensors for concealed weapons detection

NASA Astrophysics Data System (ADS)

Felber, Franklin S.; Davis, Herbert T., III; Mallon, Charles E.; Wild, Norbert C.

1996-06-01

An integrated radar and ultrasound sensor, capable of remotely detecting and imaging concealed weapons, is being developed. A modified frequency-agile, mine-detection radar is intended to specify with high probability of detection at ranges of 1 to 10 m which individuals in a moving crowd may be concealing metallic or nonmetallic weapons. Within about 1 to 5 m, the active ultrasound sensor is intended to enable a user to identify a concealed weapon on a moving person with low false-detection rate, achieved through a real-time centimeter-resolution image of the weapon. The goal for sensor fusion is to have the radar acquire concealed weapons at long ranges and seamlessly hand over tracking data to the ultrasound sensor for high-resolution imaging on a video monitor. We have demonstrated centimeter-resolution ultrasound images of metallic and non-metallic weapons concealed on a human at ranges over 1 m. Processing of the ultrasound images includes filters for noise, frequency, brightness, and contrast. A frequency-agile radar has been developed by JAYCOR under the U.S. Army Advanced Mine Detection Radar Program. The signature of an armed person, detected by this radar, differs appreciably from that of the same person unarmed.

Contribution of Infrasound to IDC Reviewed Event Bulletin

NASA Astrophysics Data System (ADS)

Bittner, Paulina; Polich, Paul; Gore, Jane; Ali, Sherif Mohamed; Medinskaya, Tatiana; Mialle, Pierrick

2016-04-01

Until 2003 two waveform technologies, i.e. seismic and hydroacoustic were used to detect and locate events included in the International Data Centre (IDC) Reviewed Event Bulletin (REB). The first atmospheric event was published in the REB in 2003 but infrasound detections could not be used by the Global Association (GA) Software due to the unmanageable high number of spurious associations. Offline improvements of the automatic processing took place to reduce the number of false detections to a reasonable level. In February 2010 the infrasound technology was reintroduced to the IDC operations and has contributed to both automatic and reviewed IDC bulletins. The primary contribution of infrasound technology is to detect atmospheric events. These events may also be observed at seismic stations, which will significantly improve event location. Examples of REB events, which were detected by the International Monitoring System (IMS) infrasound network were fireballs (e.g. Bangkok fireball, 2015), volcanic eruptions (e.g. Calbuco, Chile 2015) and large surface explosions (e.g. Tjanjin, China 2015). Query blasts and large earthquakes belong to events primarily recorded at seismic stations of the IMS network but often detected at the infrasound stations. Presence of infrasound detection associated to an event from a mining area indicates a surface explosion. Satellite imaging and a database of active mines can be used to confirm the origin of such events. This presentation will summarize the contribution of 6 years of infrasound data to IDC bulletins and provide examples of events recorded at the IMS infrasound network. Results of this study may help to improve location of small events with observations on infrasound stations.

7. VIEW OF TIP TOP AND PHILLIPS MINES. PHOTO MADE ...

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

7. VIEW OF TIP TOP AND PHILLIPS MINES. PHOTO MADE FROM THE 'NOTTINGHAM' SADDLE VISIBLE IN PHOTOGRAPHS ID-31-3 AND ID-31-6. CAMERA POINTED NORTHEAST TIP TOP IS CLEARLY VISIBLE IN UPPER RIGHT; RUNNING A STRAIGHT EDGE THROUGH THE TRUNK LINE OF SMALL TREE IN LOWER RIGHT THROUGH TRUNK LINE OF LARGER TREE WILL DIRECT ONE TO LIGHT AREA WHERE TIP TOP IS LOCATED; BLACK SQUARE IS THE RIGHT WINDOW ON WEST SIDE (FRONT) OF STRUCTURE. PHILLIPS IS VISIBLE BY FOLLOWING TREE LINE DIAGONALLY THROUGH IMAGE TO FAR LEFT SIDE. SULLIVAN IS HIDDEN IN THE TREE TO THE RIGHT OF PHILLIPS. - Florida Mountain Mining Sites, Silver City, Owyhee County, ID

Practice-Relevant Pedagogy for Mining Software Engineering Curricula Assets

DTIC Science & Technology

2007-06-20

permits the application of the Lean methods by virtually grouping shared services into eWorkcenters to which only non-routine requests are routed...engineering can be applied to IT shared services improvement and provide precise system improvement methods to complement the ITIL best practice. This...Vertical� or internal service- chain of primary business functions and enabling shared services Framework results - Mined patterns that relate

Operating System Support for Shared Hardware Data Structures

DTIC Science & Technology

2013-01-31

Carbon [73] uses hardware queues to improve fine-grained multitasking for Recognition, Mining , and Synthesis. Compared to software ap- proaches...web transaction processing, data mining , and multimedia. Early work in database processors [114, 96, 79, 111] reduce the costs of relational database...assignment can be solved statically or dynamically. Static assignment deter- mines offline which data structures are assigned to use HWDS resources and at

Mine Burial Expert System for Change of MIW Doctrine

DTIC Science & Technology

2011-09-01

allowed the mine to move vertically and horizontally, as well as rotate about the y axis. The first of these second generation impact models was...bearing strength and use multilayered sediments. Although they improve the knowledge of mine movement in two dimensions and rotation in one direction...conditional independence. Bayesian networks were originally developed 24 to handle uncertainty in a quantitative manner. They are statistical models

Evaluating an HIV and AIDS Community Training Partnership Program in Five Diamond Mining Communities in South Africa

ERIC Educational Resources Information Center

Rispel, L. C.; Peltzer, K.; Nkomo, N.; Molomo, B.

2010-01-01

In 2006, De Beers Consolidated Diamond Mines in South Africa entered into a partnership, with the Soul City Institute for Health and Development Communications to implement an HIV and AIDS Community Training Partnership Program (CTPP), initially in five diamond mining areas in three provinces of South Africa. The aim of CTPP was to improve HIV…

Text-mining and information-retrieval services for molecular biology

PubMed Central

Krallinger, Martin; Valencia, Alfonso

2005-01-01

Text-mining in molecular biology - defined as the automatic extraction of information about genes, proteins and their functional relationships from text documents - has emerged as a hybrid discipline on the edges of the fields of information science, bioinformatics and computational linguistics. A range of text-mining applications have been developed recently that will improve access to knowledge for biologists and database annotators. PMID:15998455

Immersion Cooling of Electronics in DoD Installations

DTIC Science & Technology

2016-05-01

2012). Bitcoin Mining Electronics Cooling Development In January 2013, inventor/consultant Mark Miyoshi began development of a two-phase cooling...system using Novec 649 to be used for cooling bitcoin mining hardware. After a short trial period, hardware power supply and logic-board failures...are reports of bitcoin mining companies vertically stacking two-phase immersion baths to improve the floor space density, but this approach is likely

Common hyperspectral image database design

NASA Astrophysics Data System (ADS)

Tian, Lixun; Liao, Ningfang; Chai, Ali

2009-11-01

This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332

Automated image processing and analysis of cartilage MRI: enabling technology for data mining applied to osteoarthritis

PubMed Central

Tameem, Hussain Z.; Sinha, Usha S.

2011-01-01

Osteoarthritis (OA) is a heterogeneous and multi-factorial disease characterized by the progressive loss of articular cartilage. Magnetic Resonance Imaging has been established as an accurate technique to assess cartilage damage through both cartilage morphology (volume and thickness) and cartilage water mobility (Spin-lattice relaxation, T2). The Osteoarthritis Initiative, OAI, is a large scale serial assessment of subjects at different stages of OA including those with pre-clinical symptoms. The electronic availability of the comprehensive data collected as part of the initiative provides an unprecedented opportunity to discover new relationships in complex diseases such as OA. However, imaging data, which provides the most accurate non-invasive assessment of OA, is not directly amenable for data mining. Changes in morphometry and relaxivity with OA disease are both complex and subtle, making manual methods extremely difficult. This chapter focuses on the image analysis techniques to automatically localize the differences in morphometry and relaxivity changes in different population sub-groups (normal and OA subjects segregated by age, gender, and race). The image analysis infrastructure will enable automatic extraction of cartilage features at the voxel level; the ultimate goal is to integrate this infrastructure to discover relationships between the image findings and other clinical features. PMID:21785520

Automated image processing and analysis of cartilage MRI: enabling technology for data mining applied to osteoarthritis

NASA Astrophysics Data System (ADS)

Tameem, Hussain Z.; Sinha, Usha S.

2007-11-01

Osteoarthritis (OA) is a heterogeneous and multi-factorial disease characterized by the progressive loss of articular cartilage. Magnetic Resonance Imaging has been established as an accurate technique to assess cartilage damage through both cartilage morphology (volume and thickness) and cartilage water mobility (Spin-lattice relaxation, T2). The Osteoarthritis Initiative, OAI, is a large scale serial assessment of subjects at different stages of OA including those with pre-clinical symptoms. The electronic availability of the comprehensive data collected as part of the initiative provides an unprecedented opportunity to discover new relationships in complex diseases such as OA. However, imaging data, which provides the most accurate non-invasive assessment of OA, is not directly amenable for data mining. Changes in morphometry and relaxivity with OA disease are both complex and subtle, making manual methods extremely difficult. This chapter focuses on the image analysis techniques to automatically localize the differences in morphometry and relaxivity changes in different population sub-groups (normal and OA subjects segregated by age, gender, and race). The image analysis infrastructure will enable automatic extraction of cartilage features at the voxel level; the ultimate goal is to integrate this infrastructure to discover relationships between the image findings and other clinical features.

Land movement monitoring at the Mavropigi lignite mine using spaceborne D-InSAR

NASA Astrophysics Data System (ADS)

Papadaki, Eirini; Tripolitsiotis, Achilleas; Steiakakis, Chrysanthos; Agioutantis, Zacharias; Mertikas, Stelios; Partsinevelos, Panagiotis; Schilizzi, Pavlos

2013-08-01

This paper examines the capability of remote sensing radar interferometry to monitor land movements, as it varies with time, in areas close to open pit lignite mines. The study area is the "Mavropigi" lignite mine in Ptolemais, Northern Greece; whose continuous operation is of vital importance to the electric power supply of Greece. The mine is presently 100-120m deep while horizontal and vertical movements have been measured in the vicinity of the pit. Within the mine, ground geodetic monitoring has revealed an average rate of movement amounting to 10-20mm/day at the southeast slopes. In this work, differential interferometry (DInSAR), using 19 Synthetic Aperture Radar (SAR) images of ALOS satellite, has been applied to monitor progression of land movement caused my mining within the greater area of "Mavropigi" region. The results of this work show that DInSAR can be used effectively to capture ground movement information, well before signs of movements can be observed visually in the form of imminent fissures and tension cracks. The advantage of remote sensing interferometry is that it can be applied even in inaccessible areas where monitoring with ground equipment is either impossible or of high-cost (large areas).

Objective definition of rosette shape variation using a combined computer vision and data mining approach.

PubMed

Camargo, Anyela; Papadopoulou, Dimitra; Spyropoulou, Zoi; Vlachonasios, Konstantinos; Doonan, John H; Gay, Alan P

2014-01-01

Computer-vision based measurements of phenotypic variation have implications for crop improvement and food security because they are intrinsically objective. It should be possible therefore to use such approaches to select robust genotypes. However, plants are morphologically complex and identification of meaningful traits from automatically acquired image data is not straightforward. Bespoke algorithms can be designed to capture and/or quantitate specific features but this approach is inflexible and is not generally applicable to a wide range of traits. In this paper, we have used industry-standard computer vision techniques to extract a wide range of features from images of genetically diverse Arabidopsis rosettes growing under non-stimulated conditions, and then used statistical analysis to identify those features that provide good discrimination between ecotypes. This analysis indicates that almost all the observed shape variation can be described by 5 principal components. We describe an easily implemented pipeline including image segmentation, feature extraction and statistical analysis. This pipeline provides a cost-effective and inherently scalable method to parameterise and analyse variation in rosette shape. The acquisition of images does not require any specialised equipment and the computer routines for image processing and data analysis have been implemented using open source software. Source code for data analysis is written using the R package. The equations to calculate image descriptors have been also provided.

Development of near surface seismic methods for urban and mining applications

NASA Astrophysics Data System (ADS)

Malehmir, Alireza; Brodic, Bojan; Place, Joachim; Juhlin, Christopher; Bastani, Mehrdad

2014-05-01

There is a great need to improve our understanding of the geological conditions in the shallow subsurface. Direct observations of the subsurface are cumbersome and expensive, and sometimes impossible. Urban and mining areas are especially challenging due to various sources of noise such as from traffic, buildings, cars, city trains, trams, bridges and high-voltage power-lines. Access is also restricted both in time and space, which requires the equipment to be versatile, fast to set up and pack, and produces the least disruptions. However, if properly designed and implemented, geophysical methods are capable of imaging detailed subsurface structures and can successfully be used to provide crucial information for site characterizations, infrastructure planning, brown- and near-field exploration, and mine planning. To address some of these issues Uppsala University, in collaboration with a number of public authorities, research organizations and industry partners, has recently developed a prototype broadband (0-800 Hz based on digital sensors) multi-component seismic landstreamer system. The current configuration consists of three segments with twenty 3C-sensors each 2 m apart and an additional segment with twenty 3C-sensors each 4 m apart, giving a total streamer length of 200 m. These four segments can be towed in parallel or in series, which in combination with synchronized wireless and cabled sensors can address a variety of complex near surface problems. The system is especially geared for noisy environments and areas where high-resolution images of the subsurface are needed. The system has little sensitivity to electrical noise and measures sensor tilt, important in rough terrains, so it can immediately be corrected for during the acquisition. Thanks to the digital sensors, the system can also be used for waveform tomography and multi-channel analysis of surface waves (MASW). Both these methods require low frequencies and these are often sacrificed in traditional landstreamers, which are either constructed for refraction and MASW methods or for reflection seismic imaging purposes. The landstreamer system, assembled in 2013, has so far been tested against planted 10- and 28-Hz coil-based sensors. Two preliminary surveys were performed in 2013, one for imaging the shallow (< 50 m) crystalline basement that controls mineralization at a location in northern Sweden and another one for site characterization at a planned access tunnel in the city of Stockholm. The comparison test showed that the digital sensors on the streamer provided superior results (in terms of resolution and sensitivity to noise) than the planted geophones, suggesting that digital sensors are more suitable for urban and mining applications. In the Stockholm survey, the system was coupled to twelve 3C-digital wireless sensors to cover areas where the access was restricted due to road traffic and existing city infrastructures. The wireless sensors were used to collect data in a passive mode during the survey; these data were later harvested and merged with the active data using GPS time stamps (nanoseconds accuracy). The system thus also allows a combination of active and passive seismic data acquisition if required. Preliminary results for the mining application show successful imaging of the shallow crystalline basement as a high-velocity (> 4000 m/s) media. Clear refracted and reflected arrivals are present in raw shot gathers. Future efforts will be geared to (i) exploiting information recorded on the horizontal components in order to extract rock mechanic parameters and anisotropy information, (ii) the development and application of a multi-component source to complement the landstreamer system, and (iii) a number of tests at underground sites. Acknowledgments: Formas, SGU, BeFo, SBUF, Skanska, Boliden, FQM and NGI

Remote Sensing Extraction of Stopes and Tailings Ponds in AN Ultra-Low Iron Mining Area

NASA Astrophysics Data System (ADS)

Ma, B.; Chen, Y.; Li, X.; Wu, L.

2018-04-01

With the development of economy, global demand for steel has accelerated since 2000, and thus mining activities of iron ore have become intensive accordingly. An ultra-low-grade iron has been extracted by open-pit mining and processed massively since 2001 in Kuancheng County, Hebei Province. There are large-scale stopes and tailings ponds in this area. It is important to extract their spatial distribution information for environmental protection and disaster prevention. A remote sensing method of extracting stopes and tailings ponds is studied based on spectral characteristics by use of Landsat 8 OLI imagery and ground spectral data. The overall accuracy of extraction is 95.06 %. In addition, tailings ponds are distinguished from stopes based on thermal characteristics by use of temperature image. The results could provide decision support for environmental protection, disaster prevention, and ecological restoration in the ultra-low-grade iron ore mining area.

Data collection and simulation of high range resolution laser radar for surface mine detection

NASA Astrophysics Data System (ADS)

Steinvall, Ove; Chevalier, Tomas; Larsson, Håkan

2006-05-01

Rapid and efficient detection of surface mines, IED's (Improvised Explosive Devices) and UXO (Unexploded Ordnance) is of high priority in military conflicts. High range resolution laser radars combined with passive hyper/multispectral sensors offer an interesting concept to help solving this problem. This paper reports on laser radar data collection of various surface mines in different types of terrain. In order to evaluate the capability of 3D imaging for detecting and classifying the objects of interest a scanning laser radar was used to scan mines and surrounding terrain with high angular and range resolution. These data were then fed into a laser radar model capable of generating range waveforms for a variety of system parameters and combinations of different targets and backgrounds. We can thus simulate a potential system by down sampling to relevant pixel sizes and laser/receiver characteristics. Data, simulations and examples will be presented.

Case study of controlled recirculation at a Wyoming trona mine

PubMed Central

Pritchard, C.; Scott, D.; Frey, G.

2015-01-01

Controlled recirculation has been used in the metal/nonmetal mining industry for energy savings when heating and cooling air, in undersea mining and for increasing airflow to mining areas. For safe and effective use of controlled district recirculation, adequate airflow to dilute contaminants must exist prior to implementation, ventilation circuit parameters must be accurately quantified, ventilation network modeling must be up to date, emergency planning scenarios must be performed and effective monitoring and control systems must be installed and used. Safety and health issues that must be considered and may be improved through the use of controlled district recirculation include blasting fumes, dust, diesel emissions, radon and contaminants from mine fires. Controlled recirculation methods are expected to become more widely used as mines reach greater working depths, requiring that these health and safety issues be well understood. The U.S. National Institute for Occupational Safety and Health (NIOSH) conducted two controlled recirculation tests over three days at a Wyoming trona mine, utilizing an inline booster fan to improve airflow to a remote and difficult-to-ventilate development section. Test results were used to determine the effect that recirculation had on air qualities and quantities measured in that section and in other adjacent areas. Pre-test conditions, including ventilation quantities and pressures, were modeled using VnetPC. During each test, ventilation quantities and pressures were measured, as well as levels of total dust. Sulfur hexafluoride (SF6) tracer gas was used to simulate a mine contaminant to monitor recirculation wave cycles. Results showed good correlation between the model results and measured values for airflows, pressure differentials, tracer gas arrival times, mine gasses and dust levels. PMID:26251567

2006 SME annual meeting & 7th ICARD, March 26-29, 2006, St. Louis, Missouri. Pre-prints

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

NONE

2006-07-01

Subjects covered by the papers include: enhanced coalbed methane through carbon sequestration, application of laser surface coatings for raw coal screen wear resistance enhancement, application of cross-flow teeter-bed separator in the US coal industry, arsenic removal from drinking water, modelling of fire spread along combustibles in a mine entry, coal's role in sustaining society, real time characterisation of frother bubble thin films, diesel emissions, overcoming stress measurements form underground coal amines, dry jigging coal, estimation of roof strata strength, improving screen bowl centrifuge performance, installation of ventilation shaft at a New Mexico coal mine, evaluation of feasibility of CO{sub 2}more » sequestration in deep coal, robot-human control interaction in mining operations, small mine and contractor safety, coal dust explosibility meter, US coal mine fatalities versus age of mine, and water and slurry bulkheads in underground coal mines.« less

Dewatering of the Jenkins open pit uranium mine

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

Straskraba, V.; Kissinger, L.E.

Mining of low grade uranium sandstones in the Jenkins open pit mine in the Shirley Basin, Wyoming was troubled by slope failures and wet conditions in the pit. Since the mine was expanding toward a river, the possibility of drainage from this river into the mine raised serious concern during the mine planning. A baseline hydrogeologic study was performed and dewatering measures were designed with the help of a numerical mathematical model. A combination of dewatering wells installed from the surface around the perimeter of the pit and horizontal drains in areas of high slope failure potential substantially improved themore » mining conditions and slope stability. This procedure consequently led to the successful ore recovery from the highly saturated sandstone strata. The development of drawdown during the dewatering of two separated aquifers in the overburden was close to that predicted by the model.« less

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.

Automation of the longwall mining system

NASA Technical Reports Server (NTRS)

Zimmerman, W.; Aster, R. W.; Harris, J.; High, J.

1982-01-01

Cost effective, safe, and technologically sound applications of automation technology to underground coal mining were identified. The longwall analysis commenced with a general search for government and industry experience of mining automation technology. A brief industry survey was conducted to identify longwall operational, safety, and design problems. The prime automation candidates resulting from the industry experience and survey were: (1) the shearer operation, (2) shield and conveyor pan line advance, (3) a management information system to allow improved mine logistics support, and (4) component fault isolation and diagnostics to reduce untimely maintenance delays. A system network analysis indicated that a 40% improvement in productivity was feasible if system delays associated with all of the above four areas were removed. A technology assessment and conceptual system design of each of the four automation candidate areas showed that state of the art digital computer, servomechanism, and actuator technologies could be applied to automate the longwall system.

Space Radar Image of Baikal Lake, Russia

NASA Technical Reports Server (NTRS)

1994-01-01

This is an X-band black-and-white image of the forests east of the Baikal Forest in the Jablonowy Mountains of Russia. The image is centered at 52.5 degrees north latitude and 116 degrees east longitude near the mining town of Bukatschatscha. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on October 4, 1994, during the second flight of the spaceborne radar. This area is part of an international research project known as the Taiga Aerospace Investigation using Geographic Information System Applications.

Energy saving analysis on mine-water source heat pump in a residential district of Henan province, central China

NASA Astrophysics Data System (ADS)

Wang, Hong; Duan, Huanlin; Chen, Aidong

2018-02-01

In this paper, the mine-water source heat pump system is proposed in residential buildings of a mining community. The coefficient of performance (COP) and the efficiency of exergy are analyzed. The results show that the COP and exergy efficiency of the mine-water source heat pump are improved, the exergy efficiency of mine-water source heat pump is more than 10% higher than that of the air source heat pump.The electric power conservation measure of “peak load shifting” is also emphasized in this article. It shows that itis a very considerable cost in the electric saving by adopting the trough period electricity to produce hot water. Due to the proper temperature of mine water, the mine-watersource heat pump unit is more efficient and stable in performance, which further shows the advantage of mine-water source heat pump in energy saving and environmental protection. It provides reference to the design of similar heat pump system as well.

Blast optimization for improved dragline productivity

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

Humphreys, M.; Baldwin, G.

1994-12-31

A project aimed at blast optimization for large open pit coal mines is utilizing blast monitoring and analysis techniques, advanced dragline monitoring equipment, and blast simulation software, to assess the major controlling factors affecting both blast performance and subsequent dragline productivity. This has involved collaborative work between the explosives supplier, mine operator, monitoring equipment manufacturer, and a mining research organization. The results from trial blasts and subsequently monitored dragline production have yielded promising results and continuing studies are being conducted as part of a blast optimization program. It should be stressed that the optimization of blasting practices for improved draglinemore » productivity is a site specific task, achieved through controlled and closely monitored procedures. The benefits achieved at one location can not be simply transferred to another minesite unless similar improvement strategies are first implemented.« less

Investigation into the effect of infrastructure on fly-in fly-out mining workers.

PubMed

Perring, Adam; Pham, Kieu; Snow, Steve; Buys, Laurie

2014-12-01

To explore fly-in fly-out (FIFO) mining workers' attitudes towards the leisure time they spend in mining camps, the recreational and social aspects of mining camp culture, the camps' communal and recreational infrastructure and activities, and implications for health. In-depth semistructured interviews. Individual interviews at locations convenient for each participant. A total of seven participants, one female and six males. The age group varied within 20-59 years. Marital status varied across participants. A qualitative approach was used to interview participants, with responses thematically analysed. Findings highlight how the recreational infrastructure and activities at mining camps impact participants' enjoyment of the camps and their feelings of community and social inclusion. Three main areas of need were identified in the interviews, as follows: (i) on-site facilities and activities; (ii) the role of infrastructure in facilitating a sense of community; and (iii) barriers to social interaction. Recreational infrastructure and activities enhance the experience of FIFO workers at mining camps. The availability of quality recreational facilities helps promote social interaction, provides for greater social inclusion and improves the experience of mining camps for their temporary FIFO residents. The infrastructure also needs to allow for privacy and individual recreational activities, which participants identified as important emotional needs. Developing appropriate recreational infrastructure at mining camps would enhance social interactions among FIFO workers, improve their well-being and foster a sense of community. Introducing infrastructure to promote social and recreational activities could also reduce alcohol-related social exclusion. © 2014 National Rural Health Alliance Inc.

Quantifying Forest and Coastal Disturbance from Industrial Mining Using Satellite Time Series Analysis Under Very Cloudy Conditions

NASA Astrophysics Data System (ADS)

Alonzo, M.; Van Den Hoek, J.; Ahmed, N.

2015-12-01

The open-pit Grasberg mine, located in the highlands of Western Papua, Indonesia, and operated by PT Freeport Indonesia (PT-FI), is among the world's largest in terms of copper and gold production. Over the last 27 years, PT-FI has used the Ajkwa River to transport an estimated 1.3 billion tons of tailings from the mine into the so-called Ajkwa Deposition Area (ADA). The ADA is the product of aggradation and lateral expansion of the Ajkwa River into the surrounding lowland rainforest and mangroves, which include species important to the livelihoods of indigenous Papuans. Mine tailings that do not settle in the ADA disperse into the Arafura Sea where they increase levels of suspended particulate matter (SPM) and associated concentrations of dissolved copper. Despite the mine's large-scale operations, ecological impact of mine tailings deposition on the forest and estuarial ecosystems have received minimal formal study. While ground-based inquiries are nearly impossible due to access restrictions, assessment via satellite remote sensing is promising but hindered by extreme cloud cover. In this study, we characterize ridgeline-to-coast environmental impacts along the Ajkwa River, from the Grasberg mine to the Arafura Sea between 1987 and 2014. We use "all available" Landsat TM and ETM+ images collected over this time period to both track pixel-level vegetation disturbance and monitor changes in coastal SPM levels. Existing temporal segmentation algorithms are unable to assess both acute and protracted trajectories of vegetation change due to pervasive cloud cover. In response, we employ robust, piecewise linear regression on noisy vegetation index (NDVI) data in a manner that is relatively insensitive to atmospheric contamination. Using this disturbance detection technique we constructed land cover histories for every pixel, based on 199 image dates, to differentiate processes of vegetation decline, disturbance, and regrowth. Using annual reports from PT-FI, we show that the changing extent and spatial patterns of riparian vegetation disturbance directly correlate with yearly tailings production rates. While the rate of vegetation disturbance decreased after 1998, SPM levels along the Arafura coast increased, suggesting the failure of PT-FI to fully confine tailings to the ADA.

Multilevel image recognition using discriminative patches and kernel covariance descriptor

NASA Astrophysics Data System (ADS)

Lu, Le; Yao, Jianhua; Turkbey, Evrim; Summers, Ronald M.

2014-03-01

Computer-aided diagnosis of medical images has emerged as an important tool to objectively improve the performance, accuracy and consistency for clinical workflow. To computerize the medical image diagnostic recognition problem, there are three fundamental problems: where to look (i.e., where is the region of interest from the whole image/volume), image feature description/encoding, and similarity metrics for classification or matching. In this paper, we exploit the motivation, implementation and performance evaluation of task-driven iterative, discriminative image patch mining; covariance matrix based descriptor via intensity, gradient and spatial layout; and log-Euclidean distance kernel for support vector machine, to address these three aspects respectively. To cope with often visually ambiguous image patterns for the region of interest in medical diagnosis, discovery of multilabel selective discriminative patches is desired. Covariance of several image statistics summarizes their second order interactions within an image patch and is proved as an effective image descriptor, with low dimensionality compared with joint statistics and fast computation regardless of the patch size. We extensively evaluate two extended Gaussian kernels using affine-invariant Riemannian metric or log-Euclidean metric with support vector machines (SVM), on two medical image classification problems of degenerative disc disease (DDD) detection on cortical shell unwrapped CT maps and colitis detection on CT key images. The proposed approach is validated with promising quantitative results on these challenging tasks. Our experimental findings and discussion also unveil some interesting insights on the covariance feature composition with or without spatial layout for classification and retrieval, and different kernel constructions for SVM. This will also shed some light on future work using covariance feature and kernel classification for medical image analysis.

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.

SU-F-P-03: Management of Time to Treatment Inititation: Case for An Electronic Whiteboard

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

Adnani, N

2016-06-15

Purpose: To determine if data mining of an electronic whiteboard improves the management of the Time to Treatment Initiation (TTI) in radiation oncology. Methods: An electronic whiteboard designed to help in managing the planning workflow and improves communication regarding patient planning progress was used to record the dates at which each phase of the planning process began or completed. These are CT Sim date, Plan Start, Physician Review, Physicist Review, Approval for Treatment Delivery, Setup or Verification of Simulation. Results: During clinical implementation, the electronic whiteboard was able to fulfill its primary objective of providing a transparent account of themore » planning progress of each patient. Peer pressure also meant that individual tasks, such as contouring, were easily brought to the attention of the responsible party and prioritized accordingly. Data mining to analyze the electronic whiteboard per patient (figure 1), per diagnosis (figure 2), per treatment modality (figure 3), per physician (figure 4), per planner (figure 5), etc., added another sophisticated tool in the management of Time to Treatment Initiation without compromising quality of the plans being generated. A longer than necessary time between CT Sim and Plan Start can be discussed among the members of the treatment team as an indication of inadequate/outdated CT Simulator, Contouring Tools, Image Fusion Tools, Other Imaging Studies (MRI, PET/CT) performed, etc. The same for the Plan Start to Physician Review where an extended time than expected may be due unrealistic planning goals, limited planning system features, etc. Conclusion: An Electronic Whiteboard in radiation oncology is not only helping with organizing planning workflow, it is also a potent tool that can be used to reduce the Time to Treatment Initiation by providing the clinic with hard data about the duration of each phase treatment planning as a function of different variable affecting the planning process. The work is supported by the Global Medical Physics Institute.« less

Kyle Chamberlain | NREL

Science.gov Websites

Chamberlain placeholder image Kyle Chamberlain Post Graduate Researcher Kyle.Chamberlain@nrel.gov Economics (Candidate), Colorado School of Mines M.S., Sustainable Design, University of Texas at Austin B.S

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Intelligent Mining Engineering Systems in the Structure of Industry 4.0

NASA Astrophysics Data System (ADS)

Rylnikova, Marina; Radchenko, Dmitriy; Klebanov, Dmitriy

2017-11-01

The solution of the problem of improving the human environment and working conditions at mines is based on the provision of the rationale of parameters and conditions for the implementation of an environmentally balanced cycle of comprehensive development of mineral deposits on the basis of the design of mining engineering systems characterized by the minimization of the human factor effect in danger zones of mining operations. In this area, robotized technologies are being developed, machinery and mechanisms with the elements of artificial intelligence, and mining and transport system automatic controls are being put into service throughout the world. In the upcoming decades, mining machines and mechanisms will be virtually industrial robots. The article presents the results of zoning of open-pit and underground mine production areas, as well as mining engineering system of combined development depending on the fact and periodicity of human presence in zones of mining processes. As a surface geotechnology case study, the software structure based on a modular concept is described. The performance philosophy of mining and transport equipment with the elements of artificial intelligence is shown when it is put into service in an open pit.

Effects of surface mining on fish and wildlife in Appalachia

USGS Publications Warehouse

Boccardy, Joseph A.; Spaulding, William M.

1968-01-01

This report on the effects of strip and surface mining on the fish and wildlife resources in eight Appalachian States is based in part on observation made during a tour of strip and surface mined area by the authors, as members of a team of specialist from six Federal agencies. Surface mining has caused extensive damage to fish and wildlife habitats and populations. A total of 832,605 acres of land have been disturbed; 81 percent of these are in Ohio, Pennsylvania, and West Virginia. More than 5,000 miles of Appalachian streams and 13,800 acres of impoundments have been seriously contaminated by acid mine water, some of it from surface mining. Additional water acreage has been adversely affected by tremendous quantities of silt and sediment. Reclamation of mined lands is needed. Three of the eight states visited in 1965-66 had no law requiring restoration of strip-mined lands, and other States needed stronger laws and more enforcement (Virginia and Tennessee have since passed laws governing strip mining). Reclamation as currently practiced in the Appalachian region does not adequately restore mined lands to minimal standards necessary to protect and improve fish and wildlife resources.

Questa Baseline and Pre-Mining Ground-Water Quality Investigation. 1. Depth to Bedrock Determinations Using Shallow Seismic Data Acquired in the Straight Creek Drainage Near Red River, New Mexico

USGS Publications Warehouse

Powers, Michael H.; Burton, Bethany L.

2004-01-01

In late May and early June of 2002, the U.S. Geological Survey (USGS) acquired four P-wave seismic profiles across the Straight Creek drainage near Red River, New Mexico. The data were acquired to support a larger effort to investigate baseline and pre-mining ground-water quality in the Red River basin (Nordstrom and others, 2002). For ground-water flow modeling, knowledge of the thickness of the valley fill material above the bedrock is required. When curved-ray refraction tomography was used with the seismic first arrival times, the resulting images of interval velocity versus depth clearly show a sharp velocity contrast where the bedrock interface is expected. The images show that the interpreted buried bedrock surface is neither smooth nor sharp, but it is clearly defined across the valley along the seismic line profiles. The bedrock models defined by the seismic refraction images are consistent with the well data.

Escondida Mine, Chile

NASA Image and Video Library

2001-10-22

This ASTER image covers 30 by 37 km in the Atacama Desert, Chile and was acquired on April 23, 2000. The Escondida Cu-Au-Ag open-pit mine is at an elevation of 3050 m, and came on stream in 1990. Current capacity is 127,000 tons/day of ore; in 1999 production totaled 827,000 tons of copper, 150,000 ounces of gold and 3.53 million ounces of silver. Primary concentration of the ore is done on-site; the concentrate is then sent to the coast for further processing through a 170 km long, 9 pipe. Escondida is related geologically to three porphyry bodies intruded along the Chilean West Fissure Fault System. A high grade supergene cap overlies primary sulfide ore. This image is a conventional 3-2-1 RGB composite. Figure 1 displays SWIR bands 4-6-8 in RGB, and highlights lithologic and alteration differences of surface units. The image is located at 24.3 degrees south latitude and 69.1 degrees west longitude. http://photojournal.jpl.nasa.gov/catalog/PIA11090

Review of Lead-Zinc Mining Impact on Landscape in the Tri-State Mining District using Small Unmanned Aerial Vehicles.

NASA Astrophysics Data System (ADS)

Bhakta, K. D.; Yeboah-Forson, A.

2015-12-01

The Tri-State lead and zinc mining district in SW Missouri, SE Kansas, and NE Oklahoma encompasses nearly 2,500 sq. miles of land and at its peak accounted for half of the US zinc (23,000,000 tons) production that surpassed one billion dollars in economic value. Once these lead and zinc rich ores were extracted, mining and milling sites were abandoned leaving behind a new landscape with numerous environmental challenges. Since 1970, most of the sites have been targeted for remediation and reclamation by federal and state agencies including the EPA. In order to capture the full extent of the impact of lead and zinc mining in the Tri-State area, numerous geoscientific approaches including data from small unmanned aerial vehicle (UAV) were employed to investigate the influence of mining in the study area. The study presented here is focused on observational assessment of the existing landscape using multiple commercial high-definitions data from UAVs to study different sites across areas of concern in the three states. Primary results (images) gathered and analyzed DEM and GIS data from abandoned mines showed the potential to provide a quick snapshot of successful or unsuccessful remediated areas. Although research and remediation of the Tri-State mining district are a continuous process, evidence from this geomorphic study suggest that UAVs can provide a quick overview of the remediated landscape or serve as a primary background tool for a more detail site-specific environmental study.

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

International SUSMIN-project aims at sustainable gold mining in EU

NASA Astrophysics Data System (ADS)

Backnäs, Soile; Neitola, Raisa; Turunen, Kaisa; Lima, Alexandre; Fiúza, António; Szlachta, Malgorzata; Wójtowicz, Patryk; Maftei, Raluca; Munteanu, Marian; Alakangas, Lena; Baciu, Calin; Fernández, Dámaris

2015-04-01

Although the gold demand has been constantly increasing in past years, the commodity findings have been decreasing and the extraction of gold has complicated due to increasing complexity and decreasing grade of the ores. Additionally, even gold mining could increase economical development, it has also challenges in eco-efficiency and extraction methods (e.g. cyanide). Thus, the novel energy and resource-efficient methods and technologies for mineral processing should be developed to concentrate selectively different gold bearing minerals. Furthermore, technologies for efficient treatment of mine waters, sustainable management of wastes, and methods to diminish environmental and social impacts of mining are needed. These problems will be addressed by the three year long project SUSMIN. The SUSMIN-project identifies and evaluates environmental impacts and economical challenges of gold mining within EU. The objective of the project is to increase the transnational cooperation and to support environmentally, socially and economically sustainable viable gold production. The focus is to develop and test geophysical techniques for gold exploration, eco-efficient ore beneficiation methods and alternatives for cyanide leaching. Additionally, the research will improve treatment methods for mine waters by the development and testing of advanced adsorbents. The research on socio-economic issues pursues to develop tools for enhancing the mechanisms of the corporate social responsibility as well as community engagement and management of the relations with the stakeholders. Moreover, with the environmental risk assessment and better knowledge of the geochemistry and long-term transformation of the contaminants in mining wastes and mine waters, the mining companies are able to predict and prevent the impacts to the surrounding environment, resulting in an improved environmental management solution. The SUSMIN consortium led by Geological Survey of Finland (GTK) includes seven research partners from six EU member states Finland, Sweden, Portugal, Romania, Poland and Ireland. Additionally eight globally on mining industry working industry partners will contribute in the SUSMIN consortium, so implementation of results from the project will translate into direct and significant economic benefits.

Modelling Subjectivity in Visual Perception of Orientation for Image Retrieval.

ERIC Educational Resources Information Center

Sanchez, D.; Chamorro-Martinez, J.; Vila, M. A.

2003-01-01

Discussion of multimedia libraries and the need for storage, indexing, and retrieval techniques focuses on the combination of computer vision and data mining techniques to model high-level concepts for image retrieval based on perceptual features of the human visual system. Uses fuzzy set theory to measure users' assessments and to capture users'…

Application of LANDSAT data and digital image processing. [Ruhr Valley, Germany

NASA Technical Reports Server (NTRS)

Bodechtel, J. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Based on LANDSAT 1 and 2 data, applications in the fields of coal mining, lignite exploration, and thematic mapping in geology are demonstrated. The hybrid image processing system, its software, and its utilization for educational purposes is described. A pre-operational European satellite is proposed.

NEW IMPROVEMENTS TO MFIRE TO ENHANCE FIRE MODELING CAPABILITIES.

PubMed

Zhou, L; Smith, A C; Yuan, L

2016-06-01

NIOSH's mine fire simulation program, MFIRE, is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines, which has been used by U.S. and international companies to simulate fires for planning and response purposes. MFIRE is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence such as changes in ventilation parameters, external influences such as changes in temperature, and internal influences such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the Bureau of Mines in the 1970s, several updates have been released over the years. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE's outdated FORTRAN programming language was replaced with an object-oriented C++ language and packaged into a dynamic link library (DLL). However, the MFIRE 3.0 release made no attempt to change or improve the fire modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of fire source models of the t-squared fire and heat release rate curve data file, the addition of a moving fire source for conveyor belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke rollback phenomena. All the improvements discussed in this paper will be termed as MFIRE 3.1 and released by NIOSH in the near future.

Method of locating underground mines fires

DOEpatents

Laage, Linneas; Pomroy, William

1992-01-01

An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

Machine Learning in Medical Imaging.

PubMed

Giger, Maryellen L

2018-03-01

Advances in both imaging and computers have synergistically led to a rapid rise in the potential use of artificial intelligence in various radiological imaging tasks, such as risk assessment, detection, diagnosis, prognosis, and therapy response, as well as in multi-omics disease discovery. A brief overview of the field is given here, allowing the reader to recognize the terminology, the various subfields, and components of machine learning, as well as the clinical potential. Radiomics, an expansion of computer-aided diagnosis, has been defined as the conversion of images to minable data. The ultimate benefit of quantitative radiomics is to (1) yield predictive image-based phenotypes of disease for precision medicine or (2) yield quantitative image-based phenotypes for data mining with other -omics for discovery (ie, imaging genomics). For deep learning in radiology to succeed, note that well-annotated large data sets are needed since deep networks are complex, computer software and hardware are evolving constantly, and subtle differences in disease states are more difficult to perceive than differences in everyday objects. In the future, machine learning in radiology is expected to have a substantial clinical impact with imaging examinations being routinely obtained in clinical practice, providing an opportunity to improve decision support in medical image interpretation. The term of note is decision support, indicating that computers will augment human decision making, making it more effective and efficient. The clinical impact of having computers in the routine clinical practice may allow radiologists to further integrate their knowledge with their clinical colleagues in other medical specialties and allow for precision medicine. Copyright © 2018. Published by Elsevier Inc.

PlanMine--a mineable resource of planarian biology and biodiversity.

PubMed

Brandl, Holger; Moon, HongKee; Vila-Farré, Miquel; Liu, Shang-Yun; Henry, Ian; Rink, Jochen C

2016-01-04

Planarian flatworms are in the midst of a renaissance as a model system for regeneration and stem cells. Besides two well-studied model species, hundreds of species exist worldwide that present a fascinating diversity of regenerative abilities, tissue turnover rates, reproductive strategies and other life history traits. PlanMine (http://planmine.mpi-cbg.de/) aims to accomplish two primary missions: First, to provide an easily accessible platform for sharing, comparing and value-added mining of planarian sequence data. Second, to catalyze the comparative analysis of the phenotypic diversity amongst planarian species. Currently, PlanMine houses transcriptomes independently assembled by our lab and community contributors. Detailed assembly/annotation statistics, a custom-developed BLAST viewer and easy export options enable comparisons at the contig and assembly level. Consistent annotation of all transcriptomes by an automated pipeline, the integration of published gene expression information and inter-relational query tools provide opportunities for mining planarian gene sequences and functions. For inter-species comparisons, we include transcriptomes of, so far, six planarian species, along with images, expert-curated information on their biology and pre-calculated cross-species sequence homologies. PlanMine is based on the popular InterMine system in order to make the rich biology of planarians accessible to the general life sciences research community. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Phosphate Mines, Jordan

NASA Technical Reports Server (NTRS)

2008-01-01

Jordan's leading industry and export commodities are phosphate and potash, ranked in the top three in the world. These are used to make fertilizer. The Jordan Phosphate Mines Company is the sole producer, having started operations in 1935. In addition to mining activities, the company produces phosphoric acid (for fertilizers, detergents, pharmaceuticals), diammonium phosphate (for fertilizer), sulphuric acid (many uses), and aluminum fluoride (a catalyst to make aluminum and magnesium).

The image covers an area of 27.5 x 49.4 km, was acquired on September 17, 2005, and is located near 30.8 degrees north latitude, 36.1 degrees east longitude.

The U.S. science team is located at NASA's Jet Propulsion Laboratory, Pasadena, Calif. The Terra mission is part of NASA's Science Mission Directorate.

Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

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

Bush, Brian; Elmore, Ryan; Getman, Dan

This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).

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.

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.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Knowledge Exchange between Poland and Vietnam in Mining and Geology - the Status Quo and Future Development

NASA Astrophysics Data System (ADS)

Nguyen, Nga; Pham, Nguyet

2018-03-01

From the beginning of the 21st century, knowledge exchange between Poland and Vietnam in mining and geology has been focusing in technology, education and training. Since years, Polish academic and commercial partners have been developing a close collaboration with Vietnam National Coal - Mineral Industries Holding Corporation Limited. Major outcomes of the collaboration are installations and operation of mining equipments and machines in Vietnamese mining companies, and excellent training programs for graduate and post graduate students and mining staff for both countries, etc. From aspects of knowledge management in globalization, the article highlights the outstanding outcomes of knowledge exchanges between the two countries, outlines cultural and economic challenges for the exchange and proposes some improvement in the future.

30 CFR 42.10 - Tuition fees.

Code of Federal Regulations, 2010 CFR

2010-07-01

... REQUIREMENTS NATIONAL MINE HEALTH AND SAFETY ACADEMY Tuition Fees § 42.10 Tuition fees. The National Mine... attending Academy courses, except employees of Federal, State, or local governments, persons attending the... the Agency's judgment, contribute to improved conduct, supervision, or management of a function or...

Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI

NASA Astrophysics Data System (ADS)

Martinez-Torteya, Antonio; Treviño-Alvarado, Víctor; Tamez-Peña, José

2013-02-01

The accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) confers many clinical research and patient care benefits. Studies have shown that multimodal biomarkers provide better diagnosis accuracy of AD and MCI than unimodal biomarkers, but their construction has been based on traditional statistical approaches. The objective of this work was the creation of accurate AD and MCI diagnostic multimodal biomarkers using advanced bioinformatics tools. The biomarkers were created by exploring multimodal combinations of features using machine learning techniques. Data was obtained from the ADNI database. The baseline information (e.g. MRI analyses, PET analyses and laboratory essays) from AD, MCI and healthy control (HC) subjects with available diagnosis up to June 2012 was mined for case/controls candidates. The data mining yielded 47 HC, 83 MCI and 43 AD subjects for biomarker creation. Each subject was characterized by at least 980 ADNI features. A genetic algorithm feature selection strategy was used to obtain compact and accurate cross-validated nearest centroid biomarkers. The biomarkers achieved training classification accuracies of 0.983, 0.871 and 0.917 for HC vs. AD, HC vs. MCI and MCI vs. AD respectively. The constructed biomarkers were relatively compact: from 5 to 11 features. Those multimodal biomarkers included several widely accepted univariate biomarkers and novel image and biochemical features. Multimodal biomarkers constructed from previously and non-previously AD associated features showed improved diagnostic performance when compared to those based solely on previously AD associated features.

Soil quality assessment using weighted fuzzy association rules

USGS Publications Warehouse

Xue, Yue-Ju; Liu, Shu-Guang; Hu, Yue-Ming; Yang, Jing-Feng

2010-01-01

Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.

[Medical imaging in tumor precision medicine: opportunities and challenges].

PubMed

Xu, Jingjing; Tan, Yanbin; Zhang, Minming

2017-05-25

Tumor precision medicine is an emerging approach for tumor diagnosis, treatment and prevention, which takes account of individual variability of environment, lifestyle and genetic information. Tumor precision medicine is built up on the medical imaging innovations developed during the past decades, including the new hardware, new imaging agents, standardized protocols, image analysis and multimodal imaging fusion technology. Also the development of automated and reproducible analysis algorithm has extracted large amount of information from image-based features. With the continuous development and mining of tumor clinical and imaging databases, the radiogenomics, radiomics and artificial intelligence have been flourishing. Therefore, these new technological advances bring new opportunities and challenges to the application of imaging in tumor precision medicine.

Raster Images of Geologic Maps of Middle Proterozoic Belt strata in parts of Benewah, Bonner, Kootenai and Shoshone Counties, Idaho and Lincoln, Mineral and Sanders Counties, Montana

USGS Publications Warehouse

Boleneus, David E.; Appelgate, Larry M.; Joseph, Nancy L.; Brandt, Theodore R.

2001-01-01

Geologic maps of the western part of the Belt Basin of western Montana and northern Idaho were converted into digital raster (TIFF image) format to facilitate their manipulation in geographic information systems. The 85-mile x 100-mile map area mostly contains rocks belonging to the lower and middle Belt Supergroup. The area is of interest as these Middle Proterozoic strata contain vein-type lead-zinc-silver deposits in the Coeur d?Alene Mining District in the St. Regis and Revett formations and strata-bound copper-silver deposits, such as the Troy mine, within the Revett Formation. The Prichard Formation is also prospective for strata-bound lead-zinc deposits because equivalent Belt strata in southern British Columbia, Canada host the Sullivan lead-zinc deposit. Map data converted to digital images include 13 geological maps at scales ranging from 1:48,000 to 1:12,000. Geologic map images produced from these maps by color scanning were registered to grid tick coverages in a Universal Transverse Mercator (North American Datum of 1927, zone 11) projection using ArcView Image Analysis. Geo-registering errors vary from 10 ft to 114 ft.

Phosphate Mines, Jordan

NASA Image and Video Library

2008-04-21

Jordan leading industry and export commodities are phosphate and potash, ranked in the top three in the world. These are used to make fertilizer. This image was acquired by NASA Terra satellite on September 17, 2005.

Distributed communications and control network for robotic mining

NASA Technical Reports Server (NTRS)

Schiffbauer, William H.

1989-01-01

The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.

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.

Sinkhole formation and hydrogeological situation at the salt mining area of Solotvyno, Ukraine

NASA Astrophysics Data System (ADS)

Stoeckl, L.; Banks, V.

2017-12-01

In Solotvyno, Ukraine, several salt mines were unexpectedly flooded in the recent past. As a result, dozens of sinkholes formed and are still forming with diameters up to 250 m. A one month advisory mission by the European Commission was launched in fall 2016 to conduct a risk assessment. The former mining area is situated in close vicinity to the river Theiss, which is the largest contributory of the largest river in Europe: the Danube. As river contamination by the release of large quantities of saltwater would lead to an international disaster, hydrogeological measurements were taken on-site to study the system. Saturated (hyper-saline) water as well as fresh surface and groundwater were encountered in different locations of the former mining area. Water samples were analyzed for chemistry and stable isotopes at BGR revealing insight into groundwater flow dynamics. Satellite imaging and interferometric synthetic aperture radar (SAR) were applied to study ground movements and evaluate the risk of further collapses. A resulting conceptual model explains the processes of sinkhole formation as well as the natural restoration of the salt dome prior to mining operations. This study shows the advantage of an interdisciplinary approach to conduct a risk assessment in the case of large mine collapses.

Space Radar Image of Baikal Lake, Russia

NASA Image and Video Library

1999-05-01

This is an X-band black-and-white image of the forests east of the Baikal Forest in the Jablonowy Mountains of Russia. The image is centered at 52.5 degrees north latitude and 116 degrees east longitude near the mining town of Bukatschatscha. This image was acquired by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour on October 4, 1994, during the second flight of the spaceborne radar. This area is part of an international research project known as the Taiga Aerospace Investigation using Geographic Information System Applications. http://photojournal.jpl.nasa.gov/catalog/PIA01754

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

Earth Observations taken by the Expedition 22 Crew

NASA Image and Video Library

2009-12-09

ISS022-E-008282 (9 Dec. 2009) --- One of the world?s leading copper mines, Escondida, in the Atacama Desert of Chile, is featured in this image photographed by an Expedition 22 crew member on the International Space Station. The copper mining industry is a major part of the Chilean economy. The mine is located 170 kilometers southeast of Chile?s port city of Antofagasta, in the hyper arid northern Atacama Desert at an elevation of 3,050 meters (approximately 10,000 feet) above sea level. Escondida produces mainly copper concentrates; assisted by gravity, the concentrates are piped as slurry down to the smaller port of Coloso just south of Antofagasta where they are dewatered for shipping. The photograph features a large light tan and gray waste or ?spoil? materials impoundment area (center) of the mine complex. The copper-bearing waste, which is a large proportion of the material excavated from open pits to the north (not in frame), is poured into the impoundment area as a liquid (green region at photo?s center), and dries to the lighter-toned spoil seen in the image. The spoil is held behind a retaining dam, just a little more than one kilometer in length, visible as a straight line at lower left. ?Escondida? means ?hidden? in Spanish, and refers to the fact that the copper ore body was buried beneath hundreds of meters of barren rock and had to be located by a laborious drilling program following a geologic trend established from other copper occurrences.

Earth Observations taken by the Expedition 15 Crew

NASA Image and Video Library

2007-09-20

ISS015-E-29867 (20 Sept. 2007) --- Bingham Canyon Mine, Utah is featured in this image photographed by an Expedition 15 crewmember on the International Space Station. The Bingham Canyon Mine (center) located approximately 32 kilometers to the southeast of Salt Lake City, UT is one of the largest open-pit mines in the world, measuring over 4 kilometers wide and 1,200 meters deep. The mine exploits a porphyry copper, a type of geological structure formed by crystal-rich magma moving upwards through pre-existing rock layers. As the magma cools and crystallizes (forming an igneous rock with large crystals in a fine-grained matrix, known as a porphyry), hot fluids circulate through the magma and surrounding rocks via fractures. This process of hydrothermal alteration typically forms copper-bearing and other minerals in spatial patterns that a geologist recognizes as a potential porphyry copper deposit. Parallel benches (stepped terraces), visible along the western pit face (center left), range from 16 to 25 meters high - these provide access for equipment to work the rock face, as well as maintaining stability of the sloping pit walls. A dark, larger roadway is also visible directly below the benches. Brown to gray, flat topped hills of gangue (waste rock) surround the pit, and are thrown into sharp relief by shadows and the oblique viewing angle of this image. Leachate reservoirs associated with ore processing are visible to the south of the city of Bingham Canyon, UT (right).

Lamb wave detection of limpet mines on ship hulls.

PubMed

Bingham, Jill; Hinders, Mark; Friedman, Adam

2009-12-01

This paper describes the use of ultrasonic guided waves for identifying the mass loading due to underwater limpet mines on ship hulls. The Dynamic Wavelet Fingerprint Technique (DFWT) is used to render the guided wave mode information in two-dimensional binary images because the waveform features of interest are too subtle to identify in time domain. The use of wavelets allows both time and scale features from the original signals to be retained, and image processing can be used to automatically extract features that correspond to the arrival times of the guided wave modes. For further understanding of how the guided wave modes propagate through the real structures, a parallel processing, 3D elastic wave simulation is developed using the finite integration technique (EFIT). This full field, technique models situations that are too complex for analytical solutions, such as built up 3D structures. The simulations have produced informative visualizations of the guided wave modes in the structures as well as mimicking directly the output from sensors placed in the simulation space for direct comparison to experiments. Results from both drydock and in-water experiments with dummy mines are also shown.

An efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaque using bidimensional empirical mode decomposition technique.

PubMed

Molinari, Filippo; Raghavendra, U; Gudigar, Anjan; Meiburger, Kristen M; Rajendra Acharya, U

2018-02-23

Atherosclerosis is a type of cardiovascular disease which may cause stroke. It is due to the deposition of fatty plaque in the artery walls resulting in the reduction of elasticity gradually and hence restricting the blood flow to the heart. Hence, an early prediction of carotid plaque deposition is important, as it can save lives. This paper proposes a novel data mining framework for the assessment of atherosclerosis in its early stage using ultrasound images. In this work, we are using 1353 symptomatic and 420 asymptomatic carotid plaque ultrasound images. Our proposed method classifies the symptomatic and asymptomatic carotid plaques using bidimensional empirical mode decomposition (BEMD) and entropy features. The unbalanced data samples are compensated using adaptive synthetic sampling (ADASYN), and the developed method yielded a promising accuracy of 91.43%, sensitivity of 97.26%, and specificity of 83.22% using fourteen features. Hence, the proposed method can be used as an assisting tool during the regular screening of carotid arteries in hospitals. Graphical abstract Outline for our efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaques.

Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods.

PubMed

Patel, Tejal A; Puppala, Mamta; Ogunti, Richard O; Ensor, Joe E; He, Tiancheng; Shewale, Jitesh B; Ankerst, Donna P; Kaklamani, Virginia G; Rodriguez, Angel A; Wong, Stephen T C; Chang, Jenny C

2017-01-01

A key challenge to mining electronic health records for mammography research is the preponderance of unstructured narrative text, which strikingly limits usable output. The imaging characteristics of breast cancer subtypes have been described previously, but without standardization of parameters for data mining. The authors searched the enterprise-wide data warehouse at the Houston Methodist Hospital, the Methodist Environment for Translational Enhancement and Outcomes Research (METEOR), for patients with Breast Imaging Reporting and Data System (BI-RADS) category 5 mammogram readings performed between January 2006 and May 2015 and an available pathology report. The authors developed natural language processing (NLP) software algorithms to automatically extract mammographic and pathologic findings from free text mammogram and pathology reports. The correlation between mammographic imaging features and breast cancer subtype was analyzed using one-way analysis of variance and the Fisher exact test. The NLP algorithm was able to obtain key characteristics for 543 patients who met the inclusion criteria. Patients with estrogen receptor-positive tumors were more likely to have spiculated margins (P = .0008), and those with tumors that overexpressed human epidermal growth factor receptor 2 (HER2) were more likely to have heterogeneous and pleomorphic calcifications (P = .0078 and P = .0002, respectively). Mammographic imaging characteristics, obtained from an automated text search and the extraction of mammogram reports using NLP techniques, correlated with pathologic breast cancer subtype. The results of the current study validate previously reported trends assessed by manual data collection. Furthermore, NLP provides an automated means with which to scale up data extraction and analysis for clinical decision support. Cancer 2017;114-121. © 2016 American Cancer Society. © 2016 American Cancer Society.

The performance evaluation model of mining project founded on the weight optimization entropy value method

NASA Astrophysics Data System (ADS)

Mao, Chao; Chen, Shou

2017-01-01

According to the traditional entropy value method still have low evaluation accuracy when evaluating the performance of mining projects, a performance evaluation model of mineral project founded on improved entropy is proposed. First establish a new weight assignment model founded on compatible matrix analysis of analytic hierarchy process (AHP) and entropy value method, when the compatibility matrix analysis to achieve consistency requirements, if it has differences between subjective weights and objective weights, moderately adjust both proportions, then on this basis, the fuzzy evaluation matrix for performance evaluation. The simulation experiments show that, compared with traditional entropy and compatible matrix analysis method, the proposed performance evaluation model of mining project based on improved entropy value method has higher accuracy assessment.

Mining-impacted sources of metal loading to an alpine stream based on a tracer-injection study, Clear Creek County, Colorado

USGS Publications Warehouse

Fey, David L.; Wirt, Laurie

2007-01-01

The largest sources of copper and zinc to the creek were from surface inflows from the adit, diffuse inflows from wetland areas, and leaching of dispersed mill tailings. Major instream processes included mixing between mining- and non-mining-impacted waters and the attenuation of iron, aluminum, manganese, and othermetals by precipitation or sorption. One year after the rerouting, the Zn and Cu loads in Leavenworth Creek from the adit discharge versus those from leaching of a large volume of dispersed mill tailings were approximately equal to, if not greater than, those before. The mine-waste dump does not appear to be a major source of metal loading. Any improvement that may have resulted from the elimination of adit flow across the dump was masked by higher adit discharge attributed to a larger snow pack. Although many mine remediation activities commonly proceed without prior scientific studies to identify the sources and pathways of metal transport, such strategies do not always translate to water-quality improvements in the stream. Assessment of sources and pathways to gain better understanding of the system is a necessary investment in the outcome of any successful remediation strategy.

Analysis of alternatives for using cable bolts as primary support at two low-seam coal mines

PubMed Central

Esterhuizen, Gabriel S.; Tulu, Ihsan B.

2016-01-01

Cable bolts are sometimes used in low-seam coal mines to provide support in difficult ground conditions. This paper describes cable bolting solutions at two low-seam coal mines in similar ground conditions. Both mines used support systems incorporating cable bolts as part of the primary support system. Two original cable bolt based support systems as well as two modified systems are evaluated to estimate their ability to prevent large roof falls. One of the support systems incorporated passive cable bolts, while the other used pre-tensioned cable bolts. The results and experience at the mines showed that the modified systems provided improved stability over the original support systems. The presence of the cable bolts is the most important contribution to stability against large roof falls, rather than the details of the support pattern. It was also found that a heavy steel channel can improve the safety of the system because of the ‘sling’ action it provides. Additionally, the analysis showed that fully-grouted rebar bolts load much earlier than the cable bolts, and pre-tensioning of the cable bolts can result in a more uniform distribution of loading in the roof. PMID:27722019

Global demand for gold is another threat for tropical forests

NASA Astrophysics Data System (ADS)

Alvarez-Berríos, Nora L.; Aide, T. Mitchell

2015-01-01

The current global gold rush, driven by increasing consumption in developing countries and uncertainty in financial markets, is an increasing threat for tropical ecosystems. Gold mining causes significant alteration to the environment, yet mining is often overlooked in deforestation analyses because it occupies relatively small areas. As a result, we lack a comprehensive assessment of the spatial extent of gold mining impacts on tropical forests. In this study, we provide a regional assessment of gold mining deforestation in the tropical moist forest biome of South America. Specifically, we analyzed the patterns of forest change in gold mining sites between 2001 and 2013, and evaluated the proximity of gold mining deforestation to protected areas (PAs). The forest cover maps were produced using the Land Mapper web application and images from the MODIS satellite MOD13Q1 vegetation indices 250 m product. Annual maps of forest cover were used to model the incremental change in forest in ˜1600 potential gold mining sites between 2001-2006 and 2007-2013. Approximately 1680 km2 of tropical moist forest was lost in these mining sites between 2001 and 2013. Deforestation was significantly higher during the 2007-2013 period, and this was associated with the increase in global demand for gold after the international financial crisis. More than 90% of the deforestation occurred in four major hotspots: Guianan moist forest ecoregion (41%), Southwest Amazon moist forest ecoregion (28%), Tapajós-Xingú moist forest ecoregion (11%), and Magdalena Valley montane forest and Magdalena-Urabá moist forest ecoregions (9%). In addition, some of the more active zones of gold mining deforestation occurred inside or within 10 km of ˜32 PAs. There is an urgent need to understand the ecological and social impacts of gold mining because it is an important cause of deforestation in the most remote forests in South America, and the impacts, particularly in aquatic systems, spread well beyond the actual mining sites.

Evaluation of multispectral middle infrared aircraft images for lithologic mapping the East Tintic Mountains, Utah( USA).

USGS Publications Warehouse

Kahle, A.B.; Rowan, L.C.

1980-01-01

Six channels of moultispectral middle infrared (8 to 14 micrometres) aircraft scanner data were acquired over the East Tintic mining district, Utah. The digital image data were computer processed to create a color-composite image based on principal component transformations. When combined with a visible and near infrared color-composite image from a previous flight, with limited field checking, it is possible to discriminate quartzite, carbonate rocks, quartz latitic and quartz monzonitic rocks, latitic and monzonitic rocks, silicified altered rocks, argillized altered rocks, and vegetation. -from Authors

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

PubMed Central

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

2009-01-01

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

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

PubMed

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

2009-01-01

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

Costs of abandoned coal mine reclamation and associated recreation benefits in Ohio.

PubMed

Mishra, Shruti K; Hitzhusen, Frederick J; Sohngen, Brent L; Guldmann, Jean-Michel

2012-06-15

Two hundred years of coal mining in Ohio have degraded land and water resources, imposing social costs on its citizens. An interdisciplinary approach employing hydrology, geographic information systems, and a recreation visitation function model, is used to estimate the damages from upstream coal mining to lakes in Ohio. The estimated recreational damages to five of the coal-mining-impacted lakes, using dissolved sulfate as coal-mining-impact indicator, amount to $21 Million per year. Post-reclamation recreational benefits from reducing sulfate concentrations by 6.5% and 15% in the five impacted lakes were estimated to range from $1.89 to $4.92 Million per year, with a net present value ranging from $14.56 Million to $37.79 Million. A benefit costs analysis (BCA) of recreational benefits and coal mine reclamation costs provides some evidence for potential Pareto improvement by investing limited resources in reclamation projects. Copyright © 2012 Elsevier Ltd. All rights reserved.

The research of distributed interactive simulation based on HLA in coal mine industry inherent safety

NASA Astrophysics Data System (ADS)

Dou, Zhi-Wu

2010-08-01

To solve the inherent safety problem puzzling the coal mining industry, analyzing the characteristic and the application of distributed interactive simulation based on high level architecture (DIS/HLA), a new method is proposed for developing coal mining industry inherent safety distributed interactive simulation adopting HLA technology. Researching the function and structure of the system, a simple coal mining industry inherent safety is modeled with HLA, the FOM and SOM are developed, and the math models are suggested. The results of the instance research show that HLA plays an important role in developing distributed interactive simulation of complicated distributed system and the method is valid to solve the problem puzzling coal mining industry. To the coal mining industry, the conclusions show that the simulation system with HLA plays an important role to identify the source of hazard, to make the measure for accident, and to improve the level of management.

Escondida Mine, Chile

NASA Technical Reports Server (NTRS)

2001-01-01

[figure removed for brevity, see original site] Figure 1 Click on image for larger version

This ASTER image covers 30 by 37 km in the Atacama Desert, Chile and was acquired on April 23, 2000. The Escondida Cu-Au-Ag open-pit mine is at an elevation of 3050 m, and came on stream in 1990. Current capacity is 127,000 tons/day of ore; in 1999 production totaled 827,000 tons of copper, 150,000 ounces of gold and 3.53 million ounces of silver. Primary concentration of the ore is done on-site; the concentrate is then sent to the coast for further processing through a 170 km long, 9 pipe. Escondida is related geologically to three porphyry bodies intruded along the Chilean West Fissure Fault System. A high grade supergene cap overlies primary sulfide ore. This image is a conventional 3-2-1 RGB composite. Figure 1 displays SWIR bands 4-6-8 in RGB, and highlights lithologic and alteration differences of surface units. The image is located at 24.3 degrees south latitude and 69.1 degrees west longitude.

The U.S. science team is located at NASA's Jet Propulsion Laboratory, Pasadena, Calif. The Terra mission is part of NASA's Science Mission Directorate.

Brain tumor classification using AFM in combination with data mining techniques.

PubMed

Huml, Marlene; Silye, René; Zauner, Gerald; Hutterer, Stephan; Schilcher, Kurt

2013-01-01

Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in the technical histopathological procedures like staining protocols, and finally the individual experience of the diagnosing pathologist. Thus, to raise astrocytoma grading to a more objective standard, this paper proposes a methodology based on atomic force microscopy (AFM) derived images made from histopathological samples in combination with data mining techniques. By comparing AFM images with corresponding light microscopy images of the same area, the progressive formation of cavities due to cell necrosis was identified as a typical morphological marker for a computer-assisted analysis. Using genetic programming as a tool for feature analysis, a best model was created that achieved 94.74% classification accuracy in distinguishing grade II tumors from grade IV ones. While utilizing modern image analysis techniques, AFM may become an important tool in astrocytic tumor diagnosis. By this way patients suffering from grade II tumors are identified unambiguously, having a less risk for malignant transformation. They would benefit from early adjuvant therapies.

Data mining of near-Earth asteroids in the Subaru Suprime-Cam archive

NASA Astrophysics Data System (ADS)

Vaduvescu, O.; Conovici, M.; Popescu, M.; Sonka, A.; Paraschiv, A.; Lacatus, D.; Tudorica, A.; Hudin, L.; Curelaru, L.; Inceu, V.; Zavoianu, D.; Cornea, R.; Toma, R.; Asher, D. J.; Hadnett, J.; Cheallaigh, L. Ó.

2017-06-01

As part of the EURONEAR project, almost 70,000 mosaic Suprime-Cam images taken between 1999 and 2013 were data mined for about 9,800 near Earth asteroids (NEAs) known by 2013 May. Using our PRECOVERY server and the "Find Subaru CCD" tool, we scrutinized 4,186 candidate CCD images possibly holding 518 NEAs. We found 113 NEAs as faint as V<25 magnitude, their positions being measured in 589 images using Astrometrica, then reported to the Minor Planet Center. Among them, 18 objects represent encounters of previously single opposition NEAs, their orbital arcs being extended by up to 10 years. In the second part of this work we searched for unknown NEAs in 78 sequences (780 CCD fields) of 4-5 mosaic images selected from the same Suprime-Cam archive and totaling 16.6 sq.deg, with the aim to assess the faint NEA distribution observable with an 8-m class survey. A total of 2,018 moving objects were measured, from which we identified 18 better NEA candidates. Using the R_c filter in good weather conditions, mostly dark time and sky directions slightly biased towards the ecliptic, at least one NEA could be discovered in every 1 sq.deg surveyed.

Power System Transient Stability Based on Data Mining Theory

NASA Astrophysics Data System (ADS)

Cui, Zhen; Shi, Jia; Wu, Runsheng; Lu, Dan; Cui, Mingde

2018-01-01

In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.

An IPSO-SVM algorithm for security state prediction of mine production logistics system

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

2017-06-01

A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

A Hybrid Approach for Efficient Modeling of Medium-Frequency Propagation in Coal Mines

PubMed Central

Brocker, Donovan E.; Sieber, Peter E.; Waynert, Joseph A.; Li, Jingcheng; Werner, Pingjuan L.; Werner, Douglas H.

2015-01-01

An efficient procedure for modeling medium frequency (MF) communications in coal mines is introduced. In particular, a hybrid approach is formulated and demonstrated utilizing ideal transmission line equations to model MF propagation in combination with full-wave sections used for accurate simulation of local antenna-line coupling and other near-field effects. This work confirms that the hybrid method accurately models signal propagation from a source to a load for various system geometries and material compositions, while significantly reducing computation time. With such dramatic improvement to solution times, it becomes feasible to perform large-scale optimizations with the primary motivation of improving communications in coal mines both for daily operations and emergency response. Furthermore, it is demonstrated that the hybrid approach is suitable for modeling and optimizing large communication networks in coal mines that may otherwise be intractable to simulate using traditional full-wave techniques such as moment methods or finite-element analysis. PMID:26478686

Micron-size metal-binding hydrogel particles improve germination and radicle elongation of Australian metallophyte grasses in mine waste rock and tailings.

PubMed

Guterres, J; Rossato, L; Pudmenzky, A; Doley, D; Whittaker, M; Schmidt, S

2013-03-15

Metal contamination of landscapes as a result of mining and other industrial activities is a pervasive problem worldwide. Metal contaminated soils often lack effective vegetation cover and are prone to contaminant leaching and dispersion through erosion, leading to contamination of the environment. Metal-binding hydrogel particle amendments could ameliorate mine wastes prior to planting and enhance seedling emergence. In this study, micron-size thiol functional cross-linked acrylamide polymer hydrogel particles (X3) were synthesised and tested in laboratory-scale experiments on phytotoxic mine wastes to determine their capacity to: (i) increase substrate water holding capacity (WHC); (ii) reduce metal availability to plants to below the phytotoxicity threshold; and (iii) enhance germination characteristics and early radicle development of two Australian metallophyte grasses under limiting and non-limiting water conditions. Addition of X3 to mine wastes significantly increased their WHC and lowered toxic soluble metal concentrations in mine waste leachates. Germination percentages and radicle elongation of both grasses in wastes were significantly increased. Highest germination percentages and greater radicle development recorded in X3 amended wastes under water limited conditions suggests that X3 was able to ameliorate metal toxicity to radicles, and provide moisture, which improved the imbibition and consequent germination of the seeds. Copyright © 2013 Elsevier B.V. All rights reserved.

Reduction of Conflicts in Mining Development Using "Good Neighbor Agreements"

NASA Astrophysics Data System (ADS)

Masaitis, A.

2013-05-01

New environmental and social challenges for the mining industry in both developed and developing countries show the obvious need to implement "responsible" mining practices that include improved community involvement. Good Neighbor Agreements (GNA's) are a relatively new mechanism for improving communication and trust between a mining company and the community. The focus of a GNA will be to provide a written and enforceable agreement, negotiated between the concerned public and the respective mining company to respond to concerns from the public, and also provide a mechanism for conflict resolution, when there is mutual benefit to maintain a working relationship. Development of GNA's, a recently evolving process that promotes environmentally sound relationships between mines and the surrounding communities. Modify and apply the resulting GNA formulas to the developing countries and countries with transitional economies. This is particularly important for countries that have poorly functioning regulatory systems that cannot guarantee a healthy and safe environment for the communities. The fundamental questions addressed by this research. 1. This is a three-year research project started in August 2012 at the University of Nevada, Reno (UNR) to develop a Good Neighbor Agreements standards as well as to investigate the details of mine development. 2. Identify spheres of possible cooperation between mining companies, government organizations, and the Non-Governmental Organizations (NGO's). Use this cooperation to develop international standards for the GNA, to promote exchange of environmental information, and exchange of successful environmental, health, and safety practices between mining operations from different countries. Discussion: The Good Neighbor Agreement currently evolving will address the following: 1. Provide an economically viable mechanism for developing a partnership between mining operations and the local communities that will increase mining industry's accountability and provide higher levels of confidence for the community that a mine is operated in a safe and sustainable manner. 2. Increase the diversity of people benefiting from the results of this research by providing standards that could be adopted in developing countries. The goal of the GNA is to have open access for the public to the safety, health, and environmental information pertaining to the mining operation, as well as to educate the local communities about safe and sustainable mining practices that promote mutual acknowledgment of the need to build a relationship amenable to each other's needs. Frequent conflicts between mining companies and surrounding communities lead to work disruptions or even mine closures and show the necessity of a less confrontational approach to environmental and social justice. Because of the higher quality environmental standards already in place, this new approach perhaps should first be established in developed countries and then applied to other countries with less developed economies. The Good Neighbor Agreement is a unique way to provide the benefits for the both mining operations and local community to provide a mechanism for development of trust and communication that offer the potential to protect both mining and community interests, and can possibly reduce conflicts in resource development projects.

Big data in multiple sclerosis: development of a web-based longitudinal study viewer in an imaging informatics-based eFolder system for complex data analysis and management

NASA Astrophysics Data System (ADS)

Ma, Kevin; Wang, Ximing; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2015-03-01

In the past, we have developed and displayed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and disease tracking. This year, we have further developed the eFolder system to handle big data analysis and data mining in today's medical imaging field. The database has been updated to allow data mining and data look-up from DICOM-SR lesion analysis contents. Longitudinal studies are tracked, and any changes in lesion volumes and brain parenchyma volumes are calculated and shown on the webbased user interface as graphical representations. Longitudinal lesion characteristic changes are compared with patients' disease history, including treatments, symptom progressions, and any other changes in the disease profile. The image viewer is updated such that imaging studies can be viewed side-by-side to allow visual comparisons. We aim to use the web-based medical imaging informatics eFolder system to demonstrate big data analysis in medical imaging, and use the analysis results to predict MS disease trends and patterns in Hispanic and Caucasian populations in our pilot study. The discovery of disease patterns among the two ethnicities is a big data analysis result that will help lead to personalized patient care and treatment planning.

Pacific Research Platform - Creation of a West Coast Big Data Freeway System Applied to the CONNected objECT (CONNECT) Data Mining Framework for Earth Science Knowledge Discovery

NASA Astrophysics Data System (ADS)

Sellars, S. L.; Nguyen, P.; Tatar, J.; Graham, J.; Kawsenuk, B.; DeFanti, T.; Smarr, L.; Sorooshian, S.; Ralph, M.

2017-12-01

A new era in computational earth sciences is within our grasps with the availability of ever-increasing earth observational data, enhanced computational capabilities, and innovative computation approaches that allow for the assimilation, analysis and ability to model the complex earth science phenomena. The Pacific Research Platform (PRP), CENIC and associated technologies such as the Flash I/O Network Appliance (FIONA) provide scientists a unique capability for advancing towards this new era. This presentation reports on the development of multi-institutional rapid data access capabilities and data pipeline for applying a novel image characterization and segmentation approach, CONNected objECT (CONNECT) algorithm to study Atmospheric River (AR) events impacting the Western United States. ARs are often associated with torrential rains, swollen rivers, flash flooding, and mudslides. CONNECT is computationally intensive, reliant on very large data transfers, storage and data mining techniques. The ability to apply the method to multiple variables and datasets located at different University of California campuses has previously been challenged by inadequate network bandwidth and computational constraints. The presentation will highlight how the inter-campus CONNECT data mining framework improved from our prior download speeds of 10MB/s to 500MB/s using the PRP and the FIONAs. We present a worked example using the NASA MERRA data to describe how the PRP and FIONA have provided researchers with the capability for advancing knowledge about ARs. Finally, we will discuss future efforts to expand the scope to additional variables in earth sciences.

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

PubMed Central

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

2015-01-01

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

Introduction to the mining of clinical data.

PubMed

Harrison, James H

2008-03-01

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

Psycho-social aspects of productivity in underground coal mining

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

Akin, G.

1981-10-01

The psychosocial aspects of productivity in underground coal mining were investigated. The following topics were studied: (1) labor productivity in deep mines and the explanations for productivity changes; (2) current concepts and research on psychosocial factors in productivity; (3) a survey of experiments in productivity improvement (4) the impact of the introduction of new technology on the social system and the way that it accomplishes production (5) a clinical study of a coal mining operation, model described how production is actually accomplished by workers at the coal face; and (6) implications and recommendations for new technology design, implementation and ongoingmore » management.« less

Information surfing with the JHU/APL coherent imager

NASA Astrophysics Data System (ADS)

Ratto, Christopher R.; Shipley, Kara R.; Beagley, Nathaniel; Wolfe, Kevin C.

2015-05-01

The ability to perform remote forensics in situ is an important application of autonomous undersea vehicles (AUVs). Forensics objectives may include remediation of mines and/or unexploded ordnance, as well as monitoring of seafloor infrastructure. At JHU/APL, digital holography is being explored for the potential application to underwater imaging and integration with an AUV. In previous work, a feature-based approach was developed for processing the holographic imagery and performing object recognition. In this work, the results of the image processing method were incorporated into a Bayesian framework for autonomous path planning referred to as information surfing. The framework was derived assuming that the location of the object of interest is known a priori, but the type of object and its pose are unknown. The path-planning algorithm adaptively modifies the trajectory of the sensing platform based on historical performance of object and pose classification. The algorithm is called information surfing because the direction of motion is governed by the local information gradient. Simulation experiments were carried out using holographic imagery collected from submerged objects. The autonomous sensing algorithm was compared to a deterministic sensing CONOPS, and demonstrated improved accuracy and faster convergence in several cases.

The effects of acidic mine drainage from historical mines in the Animas River watershed, San Juan County, Colorado—What is being done and what can be done to improve water quality?

USGS Publications Warehouse

Church, Stanley E; Owen, J. Robert; Von Guerard, Paul; Verplanck, Philip L.; Kimball, Briant A.; Yager, Douglas B.

2006-01-01

Historical production of metals in the western United States has left a legacy of acidic drainage and toxic metals in many mountain watersheds that are a potential threat to human and ecosystem health. Studies of the effects of historical mining on surface water chemistry and riparian habitat in the Animas River watershed have shown that cost-effective remediation of mine sites must be carefully planned. Of the more than 5400 mine, mill, and prospect sites in the watershed, 80 sites account for more than 90% of the metal loads to the surface drainages. Much of the low pH water and some of the metal loads are the result of weathering of hydrothermally altered rock that has not been disturbed by historical mining. Some stream reaches in areas underlain by hydrothermally altered rock contained no aquatic life prior to mining. Scientific studies of the processes and metal-release pathways are necessary to develop effective remediation strategies, particularly in watersheds where there is little land available to build mine-waste repositories. Characterization of mine waste, development of runoff profiles, and evaluation of ground-water pathways all require rigorous study and are expensive upfront costs that land managers find difficult to justify. Tracer studies of water quality provide a detailed spatial analysis of processes affecting surface- and ground-water chemistry. Reactive transport models were used in conjunction with the best state-of-the-art engineering solutions to make informed and cost-effective remediation decisions. Remediation of 23% of the high-priority sites identified in the watershed has resulted in steady improvement in water quality. More than $12 million, most contributed by private entities, has been spent on remediation in the Animas River watershed. The recovery curve for aquatic life in the Animas River system will require further documentation and long-term monitoring to evaluate the effectiveness of remediation projects implemented.

The effects of acidic mine drainage from historical mines in the Animas River watershed, San Juan County, Colorado—What is being done and what can be done to improve water quality?

USGS Publications Warehouse

Church, Stanley E.; Owen, Robert J.; Von Guerard, Paul; Verplanck, Philip L.; Kimball, Briant A.; Yager, Douglas B.

2007-01-01

Historical production of metals in the western United States has left a legacy of acidic drainage and toxic metals in many mountain watersheds that are a potential threat to human and ecosystem health. Studies of the effects of historical mining on surface water chemistry and riparian habitat in the Animas River watershed have shown that cost-effective remediation of mine sites must be carefully planned. of the more than 5400 mine, mill, and prospect sites in the watershed, ∼80 sites account for more than 90% of the metal loads to the surface drainages. Much of the low pH water and some of the metal loads are the result of weathering of hydrothermally altered rock that has not been disturbed by historical mining. Some stream reaches in areas underlain by hydrothermally altered rock contained no aquatic life prior to mining.Scientific studies of the processes and metal-release pathways are necessary to develop effective remediation strategies, particularly in watersheds where there is little land available to build mine-waste repositories. Characterization of mine waste, development of runoff profiles, and evaluation of ground-water pathways all require rigorous study and are expensive upfront costs that land managers find difficult to justify. Tracer studies of water quality provide a detailed spatial analysis of processes affecting surface- and ground-water chemistry. Reactive transport models were used in conjunction with the best state-of-the-art engineering solutions to make informed and cost-effective remediation decisions.Remediation of 23% of the high-priority sites identified in the watershed has resulted in steady improvement in water quality. More than $12 million, most contributed by private entities, has been spent on remediation in the Animas River watershed. The recovery curve for aquatic life in the Animas River system will require further documentation and long-term monitoring to evaluate the effectiveness of remediation projects implemented.

High exposure to respirable dust and quartz in a labour-intensive coal mine in Tanzania.

PubMed

Mamuya, Simon H D; Bråtveit, Magne; Mwaiselage, Julius; Mashalla, Yohana J S; Moen, Bente E

2006-03-01

Labour-intensive mines are numerous in several developing countries, but dust exposure in such mines has not been adequately characterized. The aim of this study was to identify and quantify the determinants of respirable dust and quartz exposure among underground coal mine workers in Tanzania. Personal respirable dust samples (n = 134) were collected from 90 underground workers in June-August 2003 and July-August 2004. The development team had higher exposure to respirable dust and quartz (geometric means 1.80 and 0.073 mg m(-3), respectively) than the mining team (0.47 and 0.013 mg m(-3)), the underground transport team (0.14 and 0.006 mg m(-3)) and the underground maintenance team (0.58 and 0.016 mg m(-3)). The percentages of samples above the threshold limit values (TLVs) of 0.9 mg m(-3) for respirable bituminous coal dust and 0.05 mg m(-3) for respirable quartz, respectively, were higher in the development team (55 and 47%) than in the mining team (20 and 9%). No sample for the underground transport team exceeded the TLV. Drilling in the development was the work task associated with the highest exposure to respirable dust and quartz (17.37 and 0.611 mg m(-3), respectively). Exposure models were constructed using multiple regression model analysis, with log-transformed data on either respirable dust or quartz as the dependent variable and tasks performed as the independent variables. The models for the development section showed that blasting and pneumatic drilling times were major determinants of respirable dust and quartz, explaining 45.2 and 40.7% of the variance, respectively. In the mining team, only blasting significantly determined respirable dust. Immediate actions for improvements are suggested to include implementing effective dust control together with improved training and education programmes for the workers. Dust and quartz in this underground mine should be controlled by giving priority to workers performing drilling and blasting in the development sections of the mine.

Prediction of subsurface fracture in mining zone of Papua using passive seismic tomography based on Fresnel zone

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

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

Fracture prediction in a block cave of underground mine is very important to monitor the structure of the fracture that can be harmful to the mining activities. Many methods can be used to obtain such information, such as TDR (Time Domain Relectometry) and open hole. Both of them have limitations in range measurement. Passive seismic tomography is one of the subsurface imaging method. It has advantage in terms of measurements, cost, and rich of rock physical information. This passive seismic tomography studies using Fresnel zone to model the wavepath by using frequency parameter. Fresnel zone was developed by Nurhandoko inmore » 2000. The result of this study is tomography of P and S wave velocity which can predict position of fracture. The study also attempted to use sum of the wavefronts to obtain position and time of seismic event occurence. Fresnel zone tomography and the summation wavefront can predict location of geological structure of mine area as well.« less

Mechanistic insights of the Min oscillator via cell-free reconstitution and imaging

NASA Astrophysics Data System (ADS)

Mizuuchi, Kiyoshi; Vecchiarelli, Anthony G.

2018-05-01

The MinD and MinE proteins of Escherichia coli self-organize into a standing-wave oscillator on the membrane to help align division at mid-cell. When unleashed from cellular confines, MinD and MinE form a spectrum of patterns on artificial bilayers—static amoebas, traveling waves, traveling mushrooms, and bursts with standing-wave dynamics. We recently focused our cell-free studies on bursts because their dynamics recapitulate many features of Min oscillation observed in vivo. The data unveiled a patterning mechanism largely governed by MinE regulation of MinD interaction with membrane. We proposed that the MinD to MinE ratio on the membrane acts as a toggle switch between MinE-stimulated recruitment and release of MinD from the membrane. In this review, we summarize cell-free data on the Min system and expand upon a molecular mechanism that provides a biochemical explanation as to how these two ‘simple’ proteins can form the remarkable spectrum of patterns.

Study on perception and control layer of mine CPS with mixed logic dynamic approach

NASA Astrophysics Data System (ADS)

Li, Jingzhao; Ren, Ping; Yang, Dayu

2017-01-01

Mine inclined roadway transportation system of mine cyber physical system is a hybrid system consisting of a continuous-time system and a discrete-time system, which can be divided into inclined roadway signal subsystem, error-proofing channel subsystems, anti-car subsystems, and frequency control subsystems. First, to ensure stable operation, improve efficiency and production safety, this hybrid system model with n inputs and m outputs is constructed and analyzed in detail, then its steady schedule state to be solved. Second, on the basis of the formal modeling for real-time systems, we use hybrid toolbox for system security verification. Third, the practical application of mine cyber physical system shows that the method for real-time simulation of mine cyber physical system is effective.

Frontiers of biomedical text mining: current progress

PubMed Central

Zweigenbaum, Pierre; Demner-Fushman, Dina; Yu, Hong; Cohen, Kevin B.

2008-01-01

It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or ‘BioNLP’ in general, focusing primarily on papers published within the past year. PMID:17977867

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

Questa Baseline and Pre-Mining Ground-Water Quality Investigation. 24. Seismic Refraction Tomography for Volume Analysis of Saturated Alluvium in the Straight Creek Drainage and Its Confluence With Red River, Taos County, New Mexico

USGS Publications Warehouse

Powers, Michael H.; Burton, Bethany L.

2007-01-01

As part of a research effort directed by the New Mexico Environment Department to determine pre-mining water quality of the Red River at a molybdenum mining site in northern New Mexico, we used seismic refraction tomography to create subsurface compressional-wave velocity images along six lines that crossed the Straight Creek drainage and three that crossed the valley of Red River. Field work was performed in June 2002 (lines 1-4) and September 2003 (lines 5-9). We interpreted the images to determine depths to the water table and to the top of bedrock. Depths to water and bedrock in boreholes near the lines correlate well with our interpretations based on seismic data. In general, the images suggest that the alluvium in this area has a trapezoidal cross section. Using a U.S. Geological Survey digital elevation model grid of surface elevations of this region and the interpreted elevations to water table and bedrock obtained from the seismic data, we generated new models of the shape of the buried bedrock surface and the water table through surface interpolation and extrapolation. Then, using elevation differences between the two grids, we calculated volumes of dry and wet alluvium in the two drainages. The Red River alluvium is about 51 percent saturated, whereas the much smaller volume of alluvium in the tributary Straight Creek is only about 18 percent saturated. When combined with average ground-water velocity values, the information we present can be used to determine discharge of Straight Creek into Red River relative to the total discharge of Red River moving past Straight Creek. This information will contribute to more accurate models of ground-water flow, which are needed to determine the pre-mining water quality in the Red River.

30 CFR 282.28 - Environmental protection measures.

Code of Federal Regulations, 2010 CFR

2010-07-01

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