76 FR 37838 - Petitions for Modification of Application of Existing Mandatory Safety Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-28

... may include periodic tests of methane levels and limits on the minimum methane concentrations that may...) Methane monitor(s) will be calibrated on the longwall, continuous mining machine, or cutting machine and... petitioner will test for methane with a hand-held methane detector at least every 10 minutes from the time...

Microcomputer network for control of a continuous mining machine. Information circular/1993

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

Schiffbauer, W.H.

1993-01-01

The paper details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines, and installed on a Joy 14 continuous mining machine. The network consists of microcomputers that are connected together via a single twisted pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers in conjunction with the appropriate sensors provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and controlmore » the continuous mining machine. Although the network was installed on a Joy 14 continuous mining machine, its use extends beyond it. Its generic structure lends itself to installation onto most mining machine types.« less

Automation and robotics technology for intelligent mining systems

NASA Technical Reports Server (NTRS)

Welsh, Jeffrey H.

1989-01-01

The U.S. Bureau of Mines is approaching the problems of accidents and efficiency in the mining industry through the application of automation and robotics to mining systems. This technology can increase safety by removing workers from hazardous areas of the mines or from performing hazardous tasks. The short-term goal of the Automation and Robotics program is to develop technology that can be implemented in the form of an autonomous mining machine using current continuous mining machine equipment. In the longer term, the goal is to conduct research that will lead to new intelligent mining systems that capitalize on the capabilities of robotics. The Bureau of Mines Automation and Robotics program has been structured to produce the technology required for the short- and long-term goals. The short-term goal of application of automation and robotics to an existing mining machine, resulting in autonomous operation, is expected to be accomplished within five years. Key technology elements required for an autonomous continuous mining machine are well underway and include machine navigation systems, coal-rock interface detectors, machine condition monitoring, and intelligent computer systems. The Bureau of Mines program is described, including status of key technology elements for an autonomous continuous mining machine, the program schedule, and future work. Although the program is directed toward underground mining, much of the technology being developed may have applications for space systems or mining on the Moon or other planets.

30 CFR 75.205 - Installation of roof support using mining machines with integral roof bolters.

Code of Federal Regulations, 2011 CFR

2011-07-01

... machines with integral roof bolters. 75.205 Section 75.205 Mineral Resources MINE SAFETY AND HEALTH... Roof Support § 75.205 Installation of roof support using mining machines with integral roof bolters. When roof bolts are installed by a continuous mining machine with intregal roof bolting equipment: (a...

30 CFR 75.823 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... Sections 75.823 through 75.834 of this part are electrical safety standards applicable to 2,400 volt continuous mining machines and circuits. A “qualified person” as used in these sections means a person...

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.

Text mining approach to predict hospital admissions using early medical records from the emergency department.

PubMed

Lucini, Filipe R; S Fogliatto, Flavio; C da Silveira, Giovani J; L Neyeloff, Jeruza; Anzanello, Michel J; de S Kuchenbecker, Ricardo; D Schaan, Beatriz

2017-04-01

Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ 2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

EUROGRAM, September-October 1994

DTIC Science & Technology

1994-10-01

finished a comprehensive report on the characteristics of mining- at the Institute, induced seismicity. The Kolar Gold Fields were first mined by the...engineering applications. Spherics standard and jets, unsteady combustion, and fuel cells. A full listing of ball products are machined and finished from...can now be directly downloaded ELO§RJ3t #94-)5 tSep-Oct 94) It chemis.r, proc:essing. finishing protocol and applications for ceramic matrix

A microcomputer network for control of a continuous mining machine

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

Schiffbauer, W.H.

1993-12-31

This report details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines and installed on a continuous mining machine. The network consists of microcomputers that are connected together via a single twisted-pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers, in conjunction with the appropriate sensors, provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and control the continuous miningmore » machine. Because of the network`s generic structure, it can be installed on most mining machines.« less

Unmanned Mine of the 21st Centuries

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

Differential Diagnosis of Erythmato-Squamous Diseases Using Classification and Regression Tree

PubMed Central

Maghooli, Keivan; Langarizadeh, Mostafa; Shahmoradi, Leila; Habibi-koolaee, Mahdi; Jebraeily, Mohamad; Bouraghi, Hamid

2016-01-01

Introduction: Differential diagnosis of Erythmato-Squamous Diseases (ESD) is a major challenge in the field of dermatology. The ESD diseases are placed into six different classes. Data mining is the process for detection of hidden patterns. In the case of ESD, data mining help us to predict the diseases. Different algorithms were developed for this purpose. Objective: we aimed to use the Classification and Regression Tree (CART) to predict differential diagnosis of ESD. Methods: we used the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. For this purpose, the dermatology data set from machine learning repository, UCI was obtained. The Clementine 12.0 software from IBM Company was used for modelling. In order to evaluation of the model we calculate the accuracy, sensitivity and specificity of the model. Results: The proposed model had an accuracy of 94.84% ( Standard Deviation: 24.42) in order to correct prediction of the ESD disease. Conclusions: Results indicated that using of this classifier could be useful. But, it would be strongly recommended that the combination of machine learning methods could be more useful in terms of prediction of ESD. PMID:28077889

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection... place at which a field approval investigation will be conducted with respect to any machine, the...

Water spray ventilator system for continuous mining machines

DOEpatents

Page, Steven J.; Mal, Thomas

1995-01-01

The invention relates to a water spray ventilator system mounted on a continuous mining machine to streamline airflow and provide effective face ventilation of both respirable dust and methane in underground coal mines. This system has two side spray nozzles mounted one on each side of the mining machine and six spray nozzles disposed on a manifold mounted to the underside of the machine boom. The six spray nozzles are angularly and laterally oriented on the manifold so as to provide non-overlapping spray patterns along the length of the cutter drum.

Advances in Machine Learning and Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Web Mining: Machine Learning for Web Applications.

ERIC Educational Resources Information Center

Chen, Hsinchun; Chau, Michael

2004-01-01

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

The accident analysis of mobile mine machinery in Indian opencast coal mines.

PubMed

Kumar, R; Ghosh, A K

2014-01-01

This paper presents the analysis of large mining machinery related accidents in Indian opencast coal mines. The trends of coal production, share of mining methods in production, machinery deployment in open cast mines, size and population of machinery, accidents due to machinery, types and causes of accidents have been analysed from the year 1995 to 2008. The scrutiny of accidents during this period reveals that most of the responsible factors are machine reversal, haul road design, human fault, operator's fault, machine fault, visibility and dump design. Considering the types of machines, namely, dumpers, excavators, dozers and loaders together the maximum number of fatal accidents has been caused by operator's faults and human faults jointly during the period from 1995 to 2008. The novel finding of this analysis is that large machines with state-of-the-art safety system did not reduce the fatal accidents in Indian opencast coal mines.

High pressure water jet mining machine

DOEpatents

Barker, Clark R.

1981-05-05

A high pressure water jet mining machine for the longwall mining of coal is described. The machine is generally in the shape of a plowshare and is advanced in the direction in which the coal is cut. The machine has mounted thereon a plurality of nozzle modules each containing a high pressure water jet nozzle disposed to oscillate in a particular plane. The nozzle modules are oriented to cut in vertical and horizontal planes on the leading edge of the machine and the coal so cut is cleaved off by the wedge-shaped body.

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

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

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

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.

30 CFR 75.342 - Methane monitors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane monitors. 75.342 Section 75.342 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.342 Methane monitors. (a)(1) MSHA approved methane monitors shall be installed on all face cutting machines, continuous miners, longwall face...

30 CFR 56.6405 - Firing devices.

Code of Federal Regulations, 2010 CFR

2010-07-01

... HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Explosives Electric Blasting § 56... all electric detonators to be fired with the type of circuits used. Storage or dry cell batteries are not permitted as power sources. (b) Blasting machines shall be tested, repaired, and maintained in...

30 CFR 75.342 - Methane monitors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane monitors. 75.342 Section 75.342 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.342 Methane monitors. (a)(1) MSHA approved methane monitors shall be installed on all face cutting machines, continuous miners, longwall face...

30 CFR 56.14107 - Moving machine parts.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Moving machine parts. 56.14107 Section 56.14107 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE... Safety Devices and Maintenance Requirements § 56.14107 Moving machine parts. (a) Moving machine parts...

30 CFR 57.14107 - Moving machine parts.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Moving machine parts. 57.14107 Section 57.14107 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE... Equipment Safety Devices and Maintenance Requirements § 57.14107 Moving machine parts. (a) Moving machine...

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

NASA Astrophysics Data System (ADS)

Biały, Witold

2017-06-01

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

Use of IT platform in determination of efficiency of mining machines

NASA Astrophysics Data System (ADS)

Brodny, Jarosław; Tutak, Magdalena

2018-01-01

Determination of effective use of mining devices has very significant meaning for mining enterprises. High costs of their purchase and tenancy cause that these enterprises tend to the best use of possessed technical potential. However, specifics of mining production causes that this process not always proceeds without interferences. Practical experiences show that determination of objective measure of utilization of machine in mining enterprise is not simple. In the paper a proposition for solution of this problem is presented. For this purpose an IT platform and overall efficiency model OEE were used. This model enables to evaluate the machine in a range of its availability performance and quality of product, and constitutes a quantitative tool of TPM strategy. Adapted to the specificity of mining branch the OEE model together with acquired data from industrial automatic system enabled to determine the partial indicators and overall efficiency of tested machines. Studies were performed for a set of machines directly use in coal exploitation process. They were: longwall-shearer and armoured face conveyor, and beam stage loader. Obtained results clearly indicate that degree of use of machines by mining enterprises are unsatisfactory. Use of IT platforms will significantly facilitate the process of registration, archiving and analytical processing of the acquired data. In the paper there is presented methodology of determination of partial indices and total OEE together with a practical example of its application for investigated machines set. Also IT platform was characterized for its construction, function and application.

PMLB: a large benchmark suite for machine learning evaluation and comparison.

PubMed

Olson, Randal S; La Cava, William; Orzechowski, Patryk; Urbanowicz, Ryan J; Moore, Jason H

2017-01-01

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.

Service Modules for Coal Extraction

NASA Technical Reports Server (NTRS)

Gangal, M. D.; Lewis, E. V.

1985-01-01

Service train follows group of mining machines, paying out utility lines as machines progress into coal face. Service train for four mining machines removes gases and coal and provides water and electricity. Flexible, coiling armored carriers protect cables and hoses. High coal production attained by arraying row of machines across face, working side by side.

Machine learning approaches to analysing textual injury surveillance data: a systematic review.

PubMed

Vallmuur, Kirsten

2015-06-01

To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Systematic review. The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automated Coal-Mining System

NASA Technical Reports Server (NTRS)

Gangal, M. D.; Isenberg, L.; Lewis, E. V.

1985-01-01

Proposed system offers safety and large return on investment. System, operating by year 2000, employs machines and processes based on proven principles. According to concept, line of parallel machines, connected in groups of four to service modules, attacks face of coal seam. High-pressure water jets and central auger on each machine break face. Jaws scoop up coal chunks, and auger grinds them and forces fragments into slurry-transport system. Slurry pumped through pipeline to point of use. Concept for highly automated coal-mining system increases productivity, makes mining safer, and protects health of mine workers.

30 CFR 18.97 - Inspection of machines; minimum requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.97 Inspection of machines; minimum... shall be conducted by an electrical representative and such inspection shall include: (1) Examination of...

30 CFR 18.97 - Inspection of machines; minimum requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.97 Inspection of machines; minimum... shall be conducted by an electrical representative and such inspection shall include: (1) Examination of...

4. CARPENTER AND MACHINE SHOP AT EAST GREY ROCK MINE, ...

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

4. CARPENTER AND MACHINE SHOP AT EAST GREY ROCK MINE, LOOKING EAST. THIS IS SAID TO BE THE OLDEST MINE BUILDING LEFT ON BUTTE HILL. SHIV WHEELS FROM VARIOUS LOCATIONS AROUND THE HILL ARE ALSO VISIBLE - Butte Mineyards, Butte, Silver Bow County, MT

30 CFR 75.832 - Frequency of examinations; recordkeeping.

Code of Federal Regulations, 2010 CFR

2010-07-01

... machine examination. At least once every 7 days, a qualified person must examine each high-voltage continuous mining machine to verify that electrical protection, equipment grounding, permissibility, cable... least once every 7 days, and prior to tramming the high-voltage continuous mining machine, a qualified...

30 CFR 18.49 - Connection boxes on machines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Connection boxes on machines. 18.49 Section 18.49 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and...

30 CFR 18.61 - Final inspection of complete machine.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Final inspection of complete machine. 18.61 Section 18.61 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Inspections...

Bidirectional, Automatic Coal-Mining Machine

NASA Technical Reports Server (NTRS)

Collins, Earl R., Jr.

1986-01-01

Proposed coal-mining machine operates in both forward and reverse directions along mine face. New design increases efficiency and productivity, because does not stop cutting as it retreats to starting position after completing pass along face. To further increase efficiency, automatic miner carries its own machinery for crushing coal and feeding it to slurry-transport tube. Dual-drum mining machine cuts coal in two layers, crushes, mixes with water, and feeds it as slurry to haulage tube. At end of pass, foward drum raised so it becomes rear drum, and rear drum lowered, becoming forward drum for return pass.

Differential Diagnosis of Erythmato-Squamous Diseases Using Classification and Regression Tree.

PubMed

Maghooli, Keivan; Langarizadeh, Mostafa; Shahmoradi, Leila; Habibi-Koolaee, Mahdi; Jebraeily, Mohamad; Bouraghi, Hamid

2016-10-01

Differential diagnosis of Erythmato-Squamous Diseases (ESD) is a major challenge in the field of dermatology. The ESD diseases are placed into six different classes. Data mining is the process for detection of hidden patterns. In the case of ESD, data mining help us to predict the diseases. Different algorithms were developed for this purpose. we aimed to use the Classification and Regression Tree (CART) to predict differential diagnosis of ESD. we used the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. For this purpose, the dermatology data set from machine learning repository, UCI was obtained. The Clementine 12.0 software from IBM Company was used for modelling. In order to evaluation of the model we calculate the accuracy, sensitivity and specificity of the model. The proposed model had an accuracy of 94.84% (. 24.42) in order to correct prediction of the ESD disease. Results indicated that using of this classifier could be useful. But, it would be strongly recommended that the combination of machine learning methods could be more useful in terms of prediction of ESD.

Analysis of Availability of Longwall-Shearer Based On Its Working Cycle

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Effective use of any type of devices, particularly machines has very significant meaning for mining enterprises. High costs of their purchase and tenancy cause that these enterprises tend to the best use of own technical potential. However, characteristics of mining production causes that this process not always proceeds without interferences. Practical experiences show that determination of objective measure of utilization of machine in mining company is not simple. In the paper methodology allowing to solve this problem is presented. Longwall-shearer, as the most important machine between longwall mechanical complex. Also it was assumed that the most significant meaning for determination of effectiveness of longwall-shearer has its availability, i.e. its effective time of work related to standard time. Such an approach is conforming to OEE model. However, specification of mining branch causes that determined availability do not give actual state of longwall-shearer’s operation. Therefore, this availability was related to the operation cycle of longwall-shearer. In presented example a longwall-shearer works in unidirectional cycle of mining. It causes that in one direction longwall-shearer mines, moving with operating velocity, and in other direction it does not mine and moves with manoeuvre velocity. Such defined working cycle became a base for determinate availability of longwall-shearer. Using indications of industrial automatic system for each of working shift there were determined number of cycles of longwall-shearer and availability of each one. Accepted of such way of determination of availability of longwall-shearer enabled to perform accurate analysis of losses of its availability. These losses result from non-planned shutdowns of longwall-shearer. Thanks to performed analysis based on the operating cycle of longwall-shearer time of its standstill for particular phase of cycle were determined. Presented methodology of determination of longwall-shearer’s availability enables to obtain information which may be used for optimization of mining process. Knowledge of particular phases of longwall-shearer’s operation, in which reduced availability occurs, allows to direct the repairing actions exactly to these regions. Developed methodology and obtained results create great opportunities for practical application and improvement of effectiveness of underground exploitation.

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

ERIC Educational Resources Information Center

Chen, Hsinchun

2003-01-01

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

30 CFR 18.21 - Machines equipped with powered dust collectors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Machines equipped with powered dust collectors. 18.21 Section 18.21 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2011 CFR

2011-07-01

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

78 FR 49774 - Petitions for Modification of Application of Existing Mandatory Safety Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-15

... the well. (7) Calibrate the methane monitors on the longwall, continuous mining machine, or cutting..., test methane levels with a hand- held methane detector at least every 10 minutes from the time that... methane levels are less than 1.0 percent in all areas that will be exposed to flames and sparks from the...

Examination of redirected continuous miner scrubber discharge configurations for exhaust face ventilation systems

PubMed Central

Organiscak, J.A.; Beck, T.W.

2015-01-01

The U.S. National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) has recently studied several redirected scrubber discharge configurations in its full-scale continuous miner gallery for both dust and gas control when using an exhaust face ventilation system. Dust and gas measurements around the continuous mining machine in the laboratory showed that the conventional scrubber discharge directed outby the face with a 12.2-m (40-ft) exhaust curtain setback appeared to be one of the better configurations for controlling dust and gas. Redirecting all the air toward the face equally up both sides of the machine increased the dust and gas concentrations around the machine. When all of the air was redirected toward the face on the off-curtain side of the machine, gas accumulations tended to be reduced at the face, at the expense of increased dust levels in the return and on the curtain side of the mining machine. A 6.1-m (20-ft) exhaust curtain setback without the scrubber operating resulted in the lowest dust levels around the continuous mining machine, but this configuration resulted in some of the highest levels of dust in the return and gas on the off-curtain side of the mining face. Two field studies showed some similarities to the laboratory findings, with elevated dust levels at the rear corners of the continuous miner when all of the scrubber exhaust was redirected toward the face either up the off-tubing side or equally up both sides of the mining machine. PMID:26251566

30 CFR 18.93 - Application for field approval; filing procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... pursuant to individual written applications for each machine submitted in triplicate on MSHA Form No. 6-1481, by the owner-coal mine operator of the machine. (2) Except as provided in paragraph (b) of this... Mine Health and Safety District Manager for the District in which such machine will be employed. (b...

30 CFR 18.93 - Application for field approval; filing procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... pursuant to individual written applications for each machine submitted in triplicate on MSHA Form No. 6-1481, by the owner-coal mine operator of the machine. (2) Except as provided in paragraph (b) of this... Mine Health and Safety District Manager for the District in which such machine will be employed. (b...

30 CFR 18.93 - Application for field approval; filing procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... pursuant to individual written applications for each machine submitted in triplicate on MSHA Form No. 6-1481, by the owner-coal mine operator of the machine. (2) Except as provided in paragraph (b) of this... Mine Health and Safety District Manager for the District in which such machine will be employed. (b...

Underground coal mine instrumentation and test

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper.

PubMed

Luo, Gang

2017-12-01

For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic.

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper

PubMed Central

Luo, Gang

2017-01-01

For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

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.

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

PubMed

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

2016-01-01

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

Data Mining and Machine Learning in Astronomy

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Brunner, Robert J.

We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those in which data mining techniques directly contributed to improving science, and important current and future directions, including probability density functions, parallel algorithms, Peta-Scale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.

Electromagnetic Signal Feedback Control for Proximity Detection Systems

NASA Astrophysics Data System (ADS)

Smith, Adam K.

Coal is the most abundant fossil fuel in the United States and remains an essential source of energy. While more than half of coal production comes from surface mining, nearly twice as many workers are employed by underground operations. One of the key pieces of equipment used in underground coal mining is the continuous mining machine. These large and powerful machines are operated in confined spaces by remote control. Since 1984, 40 mine workers in the U. S. have been killed when struck or pinned by a continuous mining machine. It is estimated that a majority of these accidents could have been prevented with the application of proximity detection systems. While proximity detection systems can significantly increase safety around a continuous mining machine, there are some system limitations. Commercially available proximity warning systems for continuous mining machines use magnetic field generators to detect workers and establish safe work areas around the machines. Several environmental factors, however, can influence and distort the magnetic fields. To minimize these effects, a control system has been developed using electromagnetic field strength and generator current to stabilize and control field drift induced by internal and external environmental factors. A laboratory test set-up was built using a ferrite-core magnetic field generator to produce a stable magnetic field. Previous work based on a field-invariant magnetic flux density model, which generically describes the electromagnetic field, is expanded upon. The analytically established transferable shell-based flux density distribution model is used to experimentally validate the control system. By controlling the current input to the ferrite-core generator, a more reliable and consistent magnetic field is produced. Implementation of this technology will improve accuracy and performance of existing commercial proximity detection systems. These research results will help reduce the risk of traumatic injuries and improve overall safety in the mining workplace.

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

PubMed

Ruff, Todd; Coleman, Patrick; Martini, Laura

2011-03-01

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

Application of Elements of TPM Strategy for Operation Analysis of Mining Machine

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Total Productive Maintenance (TPM) strategy includes group of activities and actions in order to maintenance machines in failure-free state and without breakdowns thanks to tending limitation of failures, non-planned shutdowns, lacks and non-planned service of machines. These actions are ordered to increase effectiveness of utilization of possessed devices and machines in company. Very significant element of this strategy is connection of technical actions with changes in their perception by employees. Whereas fundamental aim of introduction this strategy is improvement of economic efficiency of enterprise. Increasing competition and necessity of reduction of production costs causes that also mining enterprises are forced to introduce this strategy. In the paper examples of use of OEE model for quantitative evaluation of selected mining devices were presented. OEE model is quantitative tool of TPM strategy and can be the base for further works connected with its introduction. OEE indicator is the product of three components which include availability and performance of the studied machine and the quality of the obtained product. The paper presents the results of the effectiveness analysis of the use of a set of mining machines included in the longwall system, which is the first and most important link in the technological line of coal production. The set of analyzed machines included the longwall shearer, armored face conveyor and cruscher. From a reliability point of view, the analyzed set of machines is a system that is characterized by the serial structure. The analysis was based on data recorded by the industrial automation system used in the mines. This method of data acquisition ensured their high credibility and a full time synchronization. Conclusions from the research and analyses should be used to reduce breakdowns, failures and unplanned downtime, increase performance and improve production quality.

A systematic review of data mining and machine learning for air pollution epidemiology.

PubMed

Bellinger, Colin; Mohomed Jabbar, Mohomed Shazan; Zaïane, Osmar; Osornio-Vargas, Alvaro

2017-11-28

Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets offer great potential, but also challenge traditional epidemiological methods. This has motivated the exploration of alternative methods to make predictions, find patterns and extract information. To this end, data mining and machine learning algorithms are increasingly being applied to air pollution epidemiology. We conducted a systematic literature review on the application of data mining and machine learning methods in air pollution epidemiology. We carried out our search process in PubMed, the MEDLINE database and Google Scholar. Research articles applying data mining and machine learning methods to air pollution epidemiology were queried and reviewed. Our search queries resulted in 400 research articles. Our fine-grained analysis employed our inclusion/exclusion criteria to reduce the results to 47 articles, which we separate into three primary areas of interest: 1) source apportionment; 2) forecasting/prediction of air pollution/quality or exposure; and 3) generating hypotheses. Early applications had a preference for artificial neural networks. In more recent work, decision trees, support vector machines, k-means clustering and the APRIORI algorithm have been widely applied. Our survey shows that the majority of the research has been conducted in Europe, China and the USA, and that data mining is becoming an increasingly common tool in environmental health. For potential new directions, we have identified that deep learning and geo-spacial pattern mining are two burgeoning areas of data mining that have good potential for future applications in air pollution epidemiology. We carried out a systematic review identifying the current trends, challenges and new directions to explore in the application of data mining methods to air pollution epidemiology. This work shows that data mining is increasingly being applied in air pollution epidemiology. The potential to support air pollution epidemiology continues to grow with advancements in data mining related to temporal and geo-spacial mining, and deep learning. This is further supported by new sensors and storage mediums that enable larger, better quality data. This suggests that many more fruitful applications can be expected in the future.

Methodology of selecting dozers for lignite open pit mines in Serbia

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

Stojanovic, D.; Ignjatovic, D.; Kovacevic, S.

1996-12-31

Apart from the main production processes (coal and overburden mining, rail conveyors transportation and storage of excavated masses) performed by great-capacity mechanization at open pit mines, numerous and different auxiliary works, that often have crucial influence on both the work efficiency of main equipment and the maintenance of optimum technical conditions of machines and plants covering technological system of open pit, are present. Successful realization of work indispensably requires a proper and adequate selection of auxiliary machines according to their type quantity, capacity, power etc. thus highly respecting specific conditions existing at each and every open pit mine. A dozermore » is certainly the most important and representative auxiliary machine at single open pit mine. It is widely used in numerous works that, in fact, are preconditions for successful work of the main mechanization and consequently the very selection of a dozer ranges among the most important operations when selecting mechanization. This paper presents the methodology of dozers selection when lignite open pit mines are concerned. A mathematical model defining the volume of work required for dozers to perform at open pit mines and consequently the number of necessary dozers was designed. The model underwent testing in practice at big open pit mines and can be used in design of future open pits mines.« less

Data Mining at NASA: From Theory to Applications

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.

2009-01-01

This slide presentation demonstrates the data mining/machine learning capabilities of NASA Ames and Intelligent Data Understanding (IDU) group. This will encompass the work done recently in the group by various group members. The IDU group develops novel algorithms to detect, classify, and predict events in large data streams for scientific and engineering systems. This presentation for Knowledge Discovery and Data Mining 2009 is to demonstrate the data mining/machine learning capabilities of NASA Ames and IDU group. This will encompass the work done re cently in the group by various group members.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2014-09-01

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

AstroML: Python-powered Machine Learning for Astronomy

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Mechanization for Optimal Landscape Reclamation

NASA Astrophysics Data System (ADS)

Vondráčková, Terezie; Voštová, Věra; Kraus, Michal

2017-12-01

Reclamation is a method of ultimate utilization of land adversely affected by mining or other industrial activity. The paper explains the types of reclamation and the term “optimal reclamation”. Technological options of the long-lasting process of mine dumps reclamation starting with the removal of overlying rocks, transport and backfilling up to the follow-up remodelling of the mine dumps terrain. Technological units and equipment for stripping flow division. Stripping flow solution with respect to optimal reclamation. We recommend that the application of logistic chains and mining simulation with follow-up reclamation to open-pit mines be used for the implementation of optimal reclamation. In addition to a database of local heterogeneities of the stripped soil and reclaimed land, the flow of earths should be resolved in a manner allowing the most suitable soil substrate to be created for the restoration of agricultural and forest land on mine dumps. The methodology under development for the solution of a number of problems, including the geological survey of overlying rocks, extraction of stripping, their transport and backfilling in specified locations with the follow-up deployment of goal-directed reclamation. It will make possible to reduce the financial resources needed for the complex process chain by utilizing GIS, GPS and DGPS technologies, logistic tools and synergistic effects. When selecting machines for transport, moving and spreading of earths, various points of view and aspects must be taken into account. Among such aspects are e.g. the kind of earth to be operated by the respective construction machine, the kind of work activities to be performed, the machine’s capacity, the option to control the machine’s implement and economic aspects and clients’ requirements. All these points of view must be considered in the decision-making process so that the selected machine is capable of executing the required activity and that the use of an unsuitable machine is eliminated as it would result in a delay and increase in the project costs. Therefore, reclamation always includes extensive earth-moving work activities restoring the required relief of the land being reclaimed. Using the earth-moving machine capacity, the kind of soil in mine dumps, the kind of the work activity performed and the machine design, a SW application has been developed that allows the most suitable machine for the respective work technology to be selected with a view to preparing the land intended for reclamation.

Comparison of Automated and Manual Recording of Brief Episodes of Intracranial Hypertension and Cerebral Hypoperfusion and Their Association with Outcome After Severe Traumatic Brain Injury

DTIC Science & Technology

2017-03-01

neuro ICP care beyond trauma care. 15. SUBJECT TERMS Advanced machine learning techniques, intracranial pressure, vital signs, monitoring...death and disability in combat casualties [1,2]. Approximately 2 million head injuries occur annually in the United States, resulting in more than...editor. Machine learning and data mining in pattern recognition. Proceedings of the 8th International Workshop on Machine Learning and Data Mining in

Chapter 16: text mining for translational bioinformatics.

PubMed

Cohen, K Bretonnel; Hunter, Lawrence E

2013-04-01

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

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2012 CFR

2012-07-01

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

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2014 CFR

2014-07-01

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

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2013 CFR

2013-07-01

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

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-06-29

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

30 CFR 77.401 - Stationary grinding machines; protective devices.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Stationary grinding machines; protective... OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment § 77.401 Stationary grinding machines; protective devices. (a) Stationary grinding machines other than special bit grinders shall be equipped with...

30 CFR 77.401 - Stationary grinding machines; protective devices.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Stationary grinding machines; protective... OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment § 77.401 Stationary grinding machines; protective devices. (a) Stationary grinding machines other than special bit grinders shall be equipped with...

Kernel Methods for Mining Instance Data in Ontologies

NASA Astrophysics Data System (ADS)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Development and Sliding Wear Response of Epoxy Composites Filled with Coal Mine Overburden Material

NASA Astrophysics Data System (ADS)

Das, Prithika; Satapathy, Alok; Mishra, M. K.

2018-03-01

The paper reports on development and characterization of epoxy based composites filled with micro-sized mine overburden material. Coal mine overburden material is typically highly heterogeneous and is considered as waste material. For excavating each ton of coal, roughly 5 tons of overburden materials are removed and is dumped nearby occupying large space. Gainful utilization of this waste is a major challenge. In the present work, this material is used as filler materials in making a new class of epoxy matrix composites. Composites with different weight proportions of fillers (0, 10, 20, 30 and 40) wt. % are prepared by hand layup technique. Compression tests are performed as per corresponding ASTM standards to assess the compressive strength of these composites. Further, dry sliding tests are performed following ASTM G99 standards using a pin on disk machine. A design of experiment approach based on Taguchi’s L16 orthogonal arrays is adopted. Tests are performed at different sliding velocities for multiple sliding distances under varying normal loads. Specific wear rates of the composites under different test conditions are obtained. The analysis of the test results revealed that the filler content and the sliding velocity are the most predominant control factors affecting the wear rate. This work thus, opens up a new avenue for the value added utilization of coal mine overburden material.

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

NASA Astrophysics Data System (ADS)

Matetic, Rudy J.

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

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Determining Underground Mining Work Postures Using Motion Capture and Digital Human Modeling

PubMed Central

Lutz, Timothy J.; DuCarme, Joseph P.; Smith, Adam K.; Ambrose, Dean

2017-01-01

According to Mine Safety and Health Administration (MSHA) data, during 2008–2012 in the U.S., there were, on average, 65 lost-time accidents per year during routine mining and maintenance activities involving remote-controlled continuous mining machines (CMMs). To address this problem, the National Institute for Occupational Safety and Health (NIOSH) is currently investigating the implementation and integration of existing and emerging technologies in underground mines to provide automated, intelligent proximity detection (iPD) devices on CMMs. One research goal of NIOSH is to enhance the proximity detection system by improving its capability to track and determine identity, position, and posture of multiple workers, and to selectively disable machine functions to keep workers and machine operators safe. Posture of the miner can determine the safe working distance from a CMM by way of the variation in the proximity detection magnetic field. NIOSH collected and analyzed motion capture data and calculated joint angles of the back, hips, and knees from various postures on 12 human subjects. The results of the analysis suggests that lower body postures can be identified by observing the changes in joint angles of the right hip, left hip, right knee, and left knee. PMID:28626796

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

NASA Astrophysics Data System (ADS)

Prabakaran, S.; Mitra, Shilpa

2018-04-01

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

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Boring-type machines equipped for auxiliary... AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for auxiliary face ventilation. Each boring-type continuous-mining machine that is submitted for approval shall...

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Boring-type machines equipped for auxiliary... AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for auxiliary face ventilation. Each boring-type continuous-mining machine that is submitted for approval shall...

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Boring-type machines equipped for auxiliary... AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for auxiliary face ventilation. Each boring-type continuous-mining machine that is submitted for approval shall...

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Boring-type machines equipped for auxiliary... AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for auxiliary face ventilation. Each boring-type continuous-mining machine that is submitted for approval shall...

30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Boring-type machines equipped for auxiliary... AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for auxiliary face ventilation. Each boring-type continuous-mining machine that is submitted for approval shall...

Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.

PubMed

Sun, Shiliang; Xie, Xijiong

2016-09-01

Semisupervised learning has been an active research topic in machine learning and data mining. One main reason is that labeling examples is expensive and time-consuming, while there are large numbers of unlabeled examples available in many practical problems. So far, Laplacian regularization has been widely used in semisupervised learning. In this paper, we propose a new regularization method called tangent space intrinsic manifold regularization. It is intrinsic to data manifold and favors linear functions on the manifold. Fundamental elements involved in the formulation of the regularization are local tangent space representations, which are estimated by local principal component analysis, and the connections that relate adjacent tangent spaces. Simultaneously, we explore its application to semisupervised classification and propose two new learning algorithms called tangent space intrinsic manifold regularized support vector machines (TiSVMs) and tangent space intrinsic manifold regularized twin SVMs (TiTSVMs). They effectively integrate the tangent space intrinsic manifold regularization consideration. The optimization of TiSVMs can be solved by a standard quadratic programming, while the optimization of TiTSVMs can be solved by a pair of standard quadratic programmings. The experimental results of semisupervised classification problems show the effectiveness of the proposed semisupervised learning algorithms.

Imrovement of operation stability of crucial parts and constructions when repairing dredges and other mining machines exploited in conditions of North

NASA Astrophysics Data System (ADS)

Broido, V. L.; Krasnoshtanov, S. U.

2018-03-01

The problems of a choice of rational technoloqy and materials for restoring crucial parts and large-sized welded constructions of dredges and other mining machines with use of methods of welding and surfasing are considered. Welding and surfacing occupy a significant share in the overall labor intensity of performing repair work at mining enterprises. Both manual arc welding and surfacing as well as mechanized methods are used, which ensure a 24-fold increase in productivity. The work shows examples of using the technology of restoring parts and structures at gold mining enterprises in Irkutsk region. Some marks of welding and surfasing materials are shown, which production is mastered by Irkutsk Heavy Engineering Plant (IZTM)

Machine Learning.

ERIC Educational Resources Information Center

Kirrane, Diane E.

1990-01-01

As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

Feasibility of high recovery highwall mining equipment. Final report

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

Not Available

1981-01-01

Three equipment systems exhibited significant promise: the RSV Miner, a surface longwall using standard underground equipment, and the variable angle auger. Other equipment systems showing considerable merit were the surface shortwall, and the two extended depth augers. Of the three most significant systems, the RSV Miner exhibits the greatest versatility and adaptability. It may be used competently in many surface mining applications and readily adapts to geologic anomalies and changing seam heights. The machine employs steering and guidance equipment and provides the necessary capabilities for extended depth operation. Safety is good, as no men are required to work underground. However,more » most important is the system's recovery factor of approximately 75% to 80% of the in-situ coal reserve within reach. The surface longwall system using standard underground equipment (preferably a ranging drum shearer in conjunction with shield supports) is most suited to either a trench mining or a modified area mining application. Both applications would allow the length of the face to be held constant. Another important consideration is legal requirements for a tailgate entry, which would necessitate additional equipment for development in a modified area mining application. When compared to surface shortwall, surface longwall exhibits higher productivity, a far greater equipment selection which allows system tailoring to geologic conditions, and greater roof control due to the significantly smaller section of overburden that must be supported. Recovery should approach, and possibly exceed, 90% of the coal in-place. The variable angle auger, which is currently only a concept, fills a very real need for which no other equipment is available at this time.« less

30 CFR 75.703 - Grounding offtrack direct-current machines and the enclosures of related detached components.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Grounding offtrack direct-current machines and...-UNDERGROUND COAL MINES Grounding § 75.703 Grounding offtrack direct-current machines and the enclosures of related detached components. [Statutory Provisions] The frames of all offtrack direct-current machines and...

30 CFR 75.703 - Grounding offtrack direct-current machines and the enclosures of related detached components.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Grounding offtrack direct-current machines and...-UNDERGROUND COAL MINES Grounding § 75.703 Grounding offtrack direct-current machines and the enclosures of related detached components. [Statutory Provisions] The frames of all offtrack direct-current machines and...

An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines

PubMed Central

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

2015-01-01

The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique) and CPM (Critical Path Method). If the delay of the critical operation (which is on a critical path) inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints. PMID:26062092

A Review of Extra-Terrestrial Mining Robot Concepts

NASA Technical Reports Server (NTRS)

Mueller, Robert P.; Van Susante, Paul J.

2011-01-01

Outer space contains a vast amount of resources that offer virtually unlimited wealth to the humans that can access and use them for commercial purposes. One of the key technologies for harvesting these resources is robotic mining of regolith, minerals, ices and metals. The harsh environment and vast distances create challenges that are handled best by robotic machines working in collaboration with human explorers. Humans will benefit from the resources that will be mined by robots. They will visit outposts and mining camps as required for exploration, commerce and scientific research, but a continuous presence is most likely to be provided by robotic mining machines that are remotely controlled by humans. There have been a variety of extra-terrestrial robotic mining concepts proposed over the last 100 years and this paper will attempt to summarize and review concepts in the public domain (government, industry and academia) to serve as an informational resource for future mining robot developers and operators. The challenges associated with these concepts will be discussed and feasibility will be assessed. Future needs associated with commercial efforts will also be investigated.

An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines.

PubMed

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

2015-01-01

The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique) and CPM (Critical Path Method). If the delay of the critical operation (which is on a critical path) inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints.

A Review of Extra-Terrestrial Mining Concepts

NASA Technical Reports Server (NTRS)

Mueller, R. P.; van Susante, P. J.

2012-01-01

Outer space contains a vast amount of resources that offer virtually unlimited wealth to the humans that can access and use them for commercial purposes. One of the key technologies for harvesting these resources is robotic mining of regolith, minerals, ices and metals. The harsh environment and vast distances create challenges that are handled best by robotic machines working in collaboration with human explorers. Humans will benefit from the resources that will be mined by robots. They will visit outposts and mining camps as required for exploration, commerce and scientific research, but a continuous presence is most likely to be provided by robotic mining machines that are remotely controlled by humans. There have been a variety of extra-terrestrial robotic mining concepts proposed over the last 40 years and this paper will attempt to summarize and review concepts in the public domain (government, industry and academia) to serve as an informational resource for future mining robot developers and operators. The challenges associated with these concepts will be discussed and feasibility will be assessed. Future needs associated with commercial efforts will also be investigated.

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Code of Federal Regulations, 2011 CFR

2011-07-01

... approved, accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. 18.95 Section 18.95..., accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. Machines for which field approval... 2D, 2E, 2F, or 2G, shall be approved following a determination by the electrical representative that...

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Code of Federal Regulations, 2013 CFR

2013-07-01

... approved, accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. 18.95 Section 18.95..., accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. Machines for which field approval... 2D, 2E, 2F, or 2G, shall be approved following a determination by the electrical representative that...

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Code of Federal Regulations, 2010 CFR

2010-07-01

... approved, accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. 18.95 Section 18.95..., accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. Machines for which field approval... 2D, 2E, 2F, or 2G, shall be approved following a determination by the electrical representative that...

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Code of Federal Regulations, 2014 CFR

2014-07-01

... approved, accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. 18.95 Section 18.95..., accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. Machines for which field approval... 2D, 2E, 2F, or 2G, shall be approved following a determination by the electrical representative that...

30 CFR 18.95 - Approval of machines constructed of components approved, accepted or certified under Bureau of...

Code of Federal Regulations, 2012 CFR

2012-07-01

... approved, accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. 18.95 Section 18.95..., accepted or certified under Bureau of Mines Schedule 2D, 2E, 2F, or 2G. Machines for which field approval... 2D, 2E, 2F, or 2G, shall be approved following a determination by the electrical representative that...

Cutter-loader apparatus having overhung shearer drum

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

Groger, H.; Harms, E.E.

1984-05-01

A longwall mining machine includes a drum cutter-loader and face conveyor wherein the drum cutter-loader is overhung and is supported by a support arm adjacent to the mine face. Nozzles direct high pressure liquid jets against the forward edge of the support arm to cut away the mining face and permit the face side support arm to advance as the mining machine advances. In one embodiment the nozzles are provided along an inclined cutting edge at the forward end of the support arm. Such nozzles may be fixed or oscillating. In an alternative embodiment the nozzles are provided in themore » cylindrical edge zone of the shearer drum and direct the high pressure fluid jets against the cutter edge at the forward end of the support arm.« less

Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

PubMed

Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

2017-12-01

Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

Influence of continuous mining arrangements on respirable dust exposures

PubMed Central

Beck, T. W.; Organiscak, J. A.; Pollock, D. E.; Potts, J. D.; Reed, W. R.

2017-01-01

In underground continuous mining operations, ventilation, water sprays and machine-mounted flooded-bed scrubbers are the primary means of controlling respirable dust exposures at the working face. Changes in mining arrangements — such as face ventilation configuration, orientation of crosscuts mined in relation to the section ventilation and equipment operator positioning — can have impacts on the ability of dust controls to reduce occupational respirable dust exposures. This study reports and analyzes dust concentrations measured by the Pittsburgh Mining Research Division for remote-controlled continuous mining machine operators as well as haulage operators at 10 U.S. underground mines. The results of these respirable dust surveys show that continuous miner exposures varied little with depth of cut but are significantly higher with exhaust ventilation. Haulage operators experienced elevated concentrations with blowing face ventilation. Elevated dust concentrations were observed for both continuous miner operators and haulage operators when working in crosscuts driven into or counter to the section airflow. Individual cuts are highlighted to demonstrate instances of minimal and excessive dust exposures attributable to particular mining configurations. These findings form the basis for recommendations for lowering face worker respirable dust exposures. PMID:28529441

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Mining protein function from text using term-based support vector machines

PubMed Central

Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

2005-01-01

Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

30 CFR 18.8 - Date for conducting investigation and tests.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General... determine the order of precedence for investigation and testing. If an electrical machine component or...

30 CFR 18.10 - Notice of approval or disapproval.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General... assembly of an electrical machine or accessory, MSHA will issue to the applicant either a written notice of...

Fabrication and testing of a prototype longwall face alignment system

NASA Technical Reports Server (NTRS)

1981-01-01

Fabrication and testing of a laser system for instantaneous location of a longwall shearer are summarized. Calculations and measurements for the design of a laser based system for monitoring and controlling the trajectory of the shearing machine as it progresses along the longwall face are reported. An early version was fabricated by employing simple mechanical contrivances and a standard miners lamp. It is concluded that the advantages of the early version is the ability to test the longwall face without approval from the Mine Safety and Health Administration.

An Evolutionary Machine Learning Framework for Big Data Sequence Mining

ERIC Educational Resources Information Center

Kamath, Uday Krishna

2014-01-01

Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Preparation of machines for inspection... Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection; requirements. (a) Upon receipt of written notice from the Health and Safety District Manager of the time and...

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Preparation of machines for inspection... Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection; requirements. (a) Upon receipt of written notice from the Health and Safety District Manager of the time and...

30 CFR 18.96 - Preparation of machines for inspection; requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Preparation of machines for inspection... Field Approval of Electrically Operated Mining Equipment § 18.96 Preparation of machines for inspection; requirements. (a) Upon receipt of written notice from the Health and Safety District Manager of the time and...

30 CFR 18.99 - Notice of approval or disapproval; letters of approval and approval plates.

Code of Federal Regulations, 2010 CFR

2010-07-01

... approval or disapproval of the machine. (a) If the qualified electrical representative recommends field..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.99 Notice of approval or...

30 CFR 18.99 - Notice of approval or disapproval; letters of approval and approval plates.

Code of Federal Regulations, 2011 CFR

2011-07-01

... approval or disapproval of the machine. (a) If the qualified electrical representative recommends field..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.99 Notice of approval or...

2. GENERAL VIEW LOOKING NORTHEAST, SHOWING COKE MACHINE (CENTER), INTERMEDIATE ...

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

2. GENERAL VIEW LOOKING NORTHEAST, SHOWING COKE MACHINE (CENTER), INTERMEDIATE TIPPLE (RIGHT), AND OVENS - Shoaf Mine & Coke Works, East side of Shoaf, off Township Route 472, Shoaf, Fayette County, PA

On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.

PubMed

Oronoz, Maite; Gojenola, Koldo; Pérez, Alicia; de Ilarraza, Arantza Díaz; Casillas, Arantza

2015-08-01

The advances achieved in Natural Language Processing make it possible to automatically mine information from electronically created documents. Many Natural Language Processing methods that extract information from texts make use of annotated corpora, but these are scarce in the clinical domain due to legal and ethical issues. In this paper we present the creation of the IxaMed-GS gold standard composed of real electronic health records written in Spanish and manually annotated by experts in pharmacology and pharmacovigilance. The experts mainly annotated entities related to diseases and drugs, but also relationships between entities indicating adverse drug reaction events. To help the experts in the annotation task, we adapted a general corpus linguistic analyzer to the medical domain. The quality of the annotation process in the IxaMed-GS corpus has been assessed by measuring the inter-annotator agreement, which was 90.53% for entities and 82.86% for events. In addition, the corpus has been used for the automatic extraction of adverse drug reaction events using machine learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach

PubMed Central

Bigdely-Shamlo, Nima; Makeig, Scott; Robbins, Kay A.

2016-01-01

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain–computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a “containerized” approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data “Levels,” each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org). PMID:27014048

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

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

PubMed

Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

2017-08-14

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

PubMed

Armañanzas, Rubén; Alonso-Nanclares, Lidia; Defelipe-Oroquieta, Jesús; Kastanauskaite, Asta; de Sola, Rafael G; Defelipe, Javier; Bielza, Concha; Larrañaga, Pedro

2013-01-01

Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE). Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery.

Machine Learning Approach for the Outcome Prediction of Temporal Lobe Epilepsy Surgery

PubMed Central

DeFelipe-Oroquieta, Jesús; Kastanauskaite, Asta; de Sola, Rafael G.; DeFelipe, Javier; Bielza, Concha; Larrañaga, Pedro

2013-01-01

Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE). Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery. PMID:23646148

Continuous Rating for Diggability Assessment in Surface Mines

NASA Astrophysics Data System (ADS)

IPHAR, Melih

2016-10-01

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

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Morris, Robert A.; Strawa, Anthony; Kurklu, Elif; Keely, Leslie

2008-01-01

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Pulsed, Hydraulic Coal-Mining Machine

NASA Technical Reports Server (NTRS)

Collins, Earl R., Jr.

1986-01-01

In proposed coal-cutting machine, piston forces water through nozzle, expelling pulsed jet that cuts into coal face. Spring-loaded piston reciprocates at end of travel to refill water chamber. Machine a onecylinder, two-cycle, internal-combustion engine, fueled by gasoline, diesel fuel, or hydrogen. Fuel converted more directly into mechanical energy of water jet.

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

Novel diesel exhaust filters for underground mining vehicles

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

Bickel, K.L.; Taubert, T.R.

1995-12-31

The U.S. Bureau of Mines (USBM) pioneered the development of disposable filters for reducing diesel particulate emissions from permissible mining machines. The USBM is now evaluating filter media that can withstand the high exhaust temperatures on nonpermissible machines. The goal of the evaluation is to find an inexpensive medium that can be cleaned or disposed of after use, and will reduce particulate emissions by 50 % or more. This report summarizes the results from screening tests of a lava rock and woven fiberglass filter media. The lava rock media exhibited low collection efficiencies, but with very low increases in exhaustmore » back pressure. Preliminary results indicate a collection efficiency exceeding 80 % for the woven fiber media. Testing of both media is continuing.« less

30 CFR 18.97 - Inspection of machines; minimum requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... all electrical components for materials, workmanship, design, and construction; (2) Examination of all components of the machine which have been approved or certified under Bureau of Mines Schedule 2D, 2E, 2F, or...

30 CFR 18.97 - Inspection of machines; minimum requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... all electrical components for materials, workmanship, design, and construction; (2) Examination of all components of the machine which have been approved or certified under Bureau of Mines Schedule 2D, 2E, 2F, or...

30 CFR 18.97 - Inspection of machines; minimum requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... all electrical components for materials, workmanship, design, and construction; (2) Examination of all components of the machine which have been approved or certified under Bureau of Mines Schedule 2D, 2E, 2F, or...

Mining machines effectiveness and OEE Indicator

NASA Astrophysics Data System (ADS)

Korski, Jacek; Tobór-Osadnik, Katarzyna; Wyganowska, Małgorzata

2017-11-01

The situation in the hard coal industry in Poland is forcing the identification of effectual and practical indicators of the effectiveness of machinery and equipment. In the article, the authors discuss the possible use of the OEE indicator for the evaluation of production processes in hard-coal mines. In summary, recommendations are made to enable efficiency assessment of mining machinery using the OEE.

SparkText: Biomedical Text Mining on Big Data Framework.

PubMed

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

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

SparkText: Biomedical Text Mining on Big Data Framework

PubMed Central

He, Karen Y.; Wang, Kai

2016-01-01

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

Coal Mining Machinery Development As An Ecological Factor Of Progressive Technologies Implementation

NASA Astrophysics Data System (ADS)

Efremenkov, A. B.; Khoreshok, A. A.; Zhironkin, S. A.; Myaskov, A. V.

2017-01-01

At present, a significant amount of energy spent for the work of mining machines and coal mining equipment on coal mines and open pits goes to the coal grinding in the process of its extraction in mining faces. Meanwhile, the increase of small fractions in mined coal does not only reduce the profitability of its production, but also causes a further negative impact on the environment and degrades labor conditions for miners. The countermeasure to the specified processes is possible with the help of coal mining equipment development. However, against the background of the technological decrease of coal mine equipment applied in Russia the negative impact on the environment is getting reinforced.

Automated annotation of functional imaging experiments via multi-label classification

PubMed Central

Turner, Matthew D.; Chakrabarti, Chayan; Jones, Thomas B.; Xu, Jiawei F.; Fox, Peter T.; Luger, George F.; Laird, Angela R.; Turner, Jessica A.

2013-01-01

Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text. PMID:24409112

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

DTIC Science & Technology

2016-06-01

research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

Mining Health-Related Issues in Consumer Product Reviews by Using Scalable Text Analytics

PubMed Central

Torii, Manabu; Tilak, Sameer S.; Doan, Son; Zisook, Daniel S.; Fan, Jung-wei

2016-01-01

In an era when most of our life activities are digitized and recorded, opportunities abound to gain insights about population health. Online product reviews present a unique data source that is currently underexplored. Health-related information, although scarce, can be systematically mined in online product reviews. Leveraging natural language processing and machine learning tools, we were able to mine 1.3 million grocery product reviews for health-related information. The objectives of the study were as follows: (1) conduct quantitative and qualitative analysis on the types of health issues found in consumer product reviews; (2) develop a machine learning classifier to detect reviews that contain health-related issues; and (3) gain insights about the task characteristics and challenges for text analytics to guide future research. PMID:27375358

Mining Health-Related Issues in Consumer Product Reviews by Using Scalable Text Analytics.

PubMed

Torii, Manabu; Tilak, Sameer S; Doan, Son; Zisook, Daniel S; Fan, Jung-Wei

2016-01-01

In an era when most of our life activities are digitized and recorded, opportunities abound to gain insights about population health. Online product reviews present a unique data source that is currently underexplored. Health-related information, although scarce, can be systematically mined in online product reviews. Leveraging natural language processing and machine learning tools, we were able to mine 1.3 million grocery product reviews for health-related information. The objectives of the study were as follows: (1) conduct quantitative and qualitative analysis on the types of health issues found in consumer product reviews; (2) develop a machine learning classifier to detect reviews that contain health-related issues; and (3) gain insights about the task characteristics and challenges for text analytics to guide future research.

Machine Learning and Data Mining Methods in Diabetes Research.

PubMed

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

2017-01-01

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

Intelligent excavator control system for lunar mining system

NASA Astrophysics Data System (ADS)

Lever, Paul J. A.; Wang, Fei-Yue

1995-01-01

A major benefit of utilizing local planetary resources is that it reduces the need and cost of lifting materials from the Earth's surface into Earth orbit. The location of the moon makes it an ideal site for harvesting the materials needed to assist space activities. Here, lunar excavation will take place in the dynamic unstructured lunar environment, in which conditions are highly variable and unpredictable. Autonomous mining (excavation) machines are necessary to remove human operators from this hazardous environment. This machine must use a control system structure that can identify, plan, sense, and control real-time dynamic machine movements in the lunar environment. The solution is a vision-based hierarchical control structure. However, excavation tasks require force/torque sensor feedback to control the excavation tool after it has penetrated the surface. A fuzzy logic controller (FLC) is used to interpret the forces and torques gathered from a bucket mounted force/torque sensor during excavation. Experimental results from several excavation tests using the FLC are presented here. These results represent the first step toward an integrated sensing and control system for a lunar mining system.

Drilling side holes from a borehole

NASA Technical Reports Server (NTRS)

Collins, E. R., Jr.

1980-01-01

Machine takes long horizontal stratum samples from confines of 21 cm bore hole. Stacked interlocking half cylindrical shells mate to form rigid thrust tube. Drive shaft and core storage device is flexible and retractable. Entire machine fits in 10 meter length of steel tube. Machine could drill drainage or ventilation holes in coal mines, or provide important information for geological, oil, and geothermal surveys.

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2013 CFR

2013-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2012 CFR

2012-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

42 CFR 84.97 - Test for carbon dioxide in inspired gas; open- and closed-circuit apparatus; maximum allowable...

Code of Federal Regulations, 2014 CFR

2014-10-01

... machine. An acceptable method for measuring the concentration of carbon dioxide is described in Bureau of Mines Report of Investigations 6865, A Machine-Test Method for Measuring Carbon Dioxide in the Inspired... of 10.5 liters. (3) A sedentary breathing machine cam will be used. (4) The apparatus will be tested...

Control system of mutually coupled switched reluctance motor drive of mining machines in generator mode

NASA Astrophysics Data System (ADS)

Ivanov, A. S.; Kalanchin, I. Yu; Pugacheva, E. E.

2017-09-01

One of the first electric motors, based on the use of electromagnets, was a reluctance motor in the XIX century. Due to the complexities in the implementation of control system the development of switched reluctance electric machines was repeatedly initiated only in 1960 thanks to the development of computers and power electronic devices. The main feature of these machines is the capacity to work both in engine mode and in generator mode. Thanks to a simple and reliable design in which there is no winding of the rotor, commutator, permanent magnets, a reactive gate-inductor electric drive operating in the engine mode is actively being introduced into various areas such as car industry, production of household appliances, wind power engineering, as well as responsible production processes in the oil and mining industries. However, the existing shortcomings of switched reluctance electric machines, such as nonlinear pulsations of electromagnetic moment, the presence of three or four phase supply system and sensor of rotor position prevent wide distribution of this kind of electric machines.

30 CFR 18.45 - Cable reels.

Code of Federal Regulations, 2014 CFR

2014-07-01

... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...

30 CFR 18.45 - Cable reels.

Code of Federal Regulations, 2013 CFR

2013-07-01

... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...

30 CFR 18.45 - Cable reels.

Code of Federal Regulations, 2012 CFR

2012-07-01

... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...

30 CFR 18.45 - Cable reels.

Code of Federal Regulations, 2010 CFR

2010-07-01

... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...

30 CFR 18.45 - Cable reels.

Code of Federal Regulations, 2011 CFR

2011-07-01

... constitute an integral part of a circuit for transmitting electrical energy. (d) Cable reels for shuttle cars... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.45 Cable reels. (a) A self-propelled machine, that receives electrical energy through a portable...

Development of sensitized pick coal interface detector system

NASA Technical Reports Server (NTRS)

Burchill, R. F.

1979-01-01

One approach for detection of the coal interface is measurement of the pick cutting hoads and shock through the use of pick strain gage load cells and accelerometers. The cutting drum of a long wall mining machine contains a number of cutting picks. In order to measure pick loads and shocks, one pick was instrumented and telementry used to transmit the signals from the drum to an instrument-type tape recorder. A data system using FM telemetry was designed to transfer cutting bit load and shock information from the drum of a longwall shearer coal mining machine to a chassis mounted data recorder.

Calculation of parameters of technological equipment for deep-sea mining

NASA Astrophysics Data System (ADS)

Yungmeister, D. A.; Ivanov, S. E.; Isaev, A. I.

2018-03-01

The actual problem of extracting minerals from the bottom of the world ocean is considered. On the ocean floor, three types of minerals are of interest: iron-manganese concretions (IMC), cobalt-manganese crusts (CMC) and sulphides. The analysis of known designs of machines and complexes for the extraction of IMC is performed. These machines are based on the principle of excavating the bottom surface; however such methods do not always correspond to “gentle” methods of mining. The ecological purity of such mining methods does not meet the necessary requirements. Such machines require the transmission of high electric power through the water column, which in some cases is a significant challenge. The authors analyzed the options of transportation of the extracted mineral from the bottom. The paper describes the design of machines that collect IMC by the method of vacuum suction. In this method, the gripping plates or drums are provided with cavities in which a vacuum is created and individual IMC are attracted to the devices by a pressure drop. The work of such machines can be called “gentle” processing technology of the bottom areas. Their environmental impact is significantly lower than mechanical devices that carry out the raking of IMC. The parameters of the device for lifting the IMC collected on the bottom are calculated. With the use of Kevlar ropes of serial production up to 0.06 meters in diameter, with a cycle time of up to 2 hours and a lifting speed of up to 3 meters per second, a productivity of about 400,000 tons per year can be realized for IMC. The development of machines based on the calculated parameters and approbation of their designs will create a unique complex for the extraction of minerals at oceanic deposits.

A systematic mapping study of process mining

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

In Praise of Robots

ERIC Educational Resources Information Center

Sagan, Carl

1975-01-01

The author of this article believes that human survival depends upon the ability to develop and work with machines of high artificial intelligence. He lists uses of such machines, including terrestrial mining, outer space exploration, and other tasks too dangerous, too expensive, or too boring for human beings. (MA)

[Effect of vibration, noise, physical exertion and unfavorable microclimate on carbohydrate metabolism in workers engaged into mining industry and machine building].

PubMed

Lapko, I V; Kir'iakov, V A; Antoshina, L I; Pavlovskaia, N A; Kondratovich, S V

2014-01-01

The authors studied influence of vibration, noise, physical overexertion and microclimate on carbohydrates metabolism and insulin resistance in metal mining industry workers. Findings are that vibration disease appeared to have maximal effect on insulin resistance test results and insulin level. The authors suggested biomarkers for early diagnosis of insulin resistance disorders in metal mining industry workers.

Data Stream Mining

NASA Astrophysics Data System (ADS)

Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali

Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

Current Developments in Machine Learning Techniques in Biological Data Mining.

PubMed

Dumancas, Gerard G; Adrianto, Indra; Bello, Ghalib; Dozmorov, Mikhail

2017-01-01

This supplement is intended to focus on the use of machine learning techniques to generate meaningful information on biological data. This supplement under Bioinformatics and Biology Insights aims to provide scientists and researchers working in this rapid and evolving field with online, open-access articles authored by leading international experts in this field. Advances in the field of biology have generated massive opportunities to allow the implementation of modern computational and statistical techniques. Machine learning methods in particular, a subfield of computer science, have evolved as an indispensable tool applied to a wide spectrum of bioinformatics applications. Thus, it is broadly used to investigate the underlying mechanisms leading to a specific disease, as well as the biomarker discovery process. With a growth in this specific area of science comes the need to access up-to-date, high-quality scholarly articles that will leverage the knowledge of scientists and researchers in the various applications of machine learning techniques in mining biological data.

Deploying and sharing U-Compare workflows as web services.

PubMed

Kontonatsios, Georgios; Korkontzelos, Ioannis; Kolluru, Balakrishna; Thompson, Paul; Ananiadou, Sophia

2013-02-18

U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare's components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform.

Deploying and sharing U-Compare workflows as web services

PubMed Central

2013-01-01

Background U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare’s components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. Results We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. Conclusions The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform. PMID:23419017

AstroML: "better, faster, cheaper" towards state-of-the-art data mining and machine learning

NASA Astrophysics Data System (ADS)

Ivezic, Zeljko; Connolly, Andrew J.; Vanderplas, Jacob

2015-01-01

We present AstroML, a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib, and astropy, and distributed under an open license. AstroML contains a growing library of statistical and machine learning routines for analyzing astronomical data in Python, loaders for several open astronomical datasets (such as SDSS and other recent major surveys), and a large suite of examples of analyzing and visualizing astronomical datasets. AstroML is especially suitable for introducing undergraduate students to numerical research projects and for graduate students to rapidly undertake cutting-edge research. The long-term goal of astroML is to provide a community repository for fast Python implementations of common tools and routines used for statistical data analysis in astronomy and astrophysics (see http://www.astroml.org).

Traffic Flow Management: Data Mining Update

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.

2012-01-01

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

30 CFR 18.48 - Circuit-interrupting devices.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and.... Such a switch shall be designed to prevent electrical connection to the machine frame when the cable is... motor in the event the belt is stopped, or abnormally slowed down. Note: Short transfer-type conveyors...

Selected water-quality data for the Standard Mine, Gunnison County, Colorado, 2006-2007

USGS Publications Warehouse

Verplanck, Philip L.; Manning, Andrew H.; Mast, M. Alisa; Wanty, Richard B.; McCleskey, R. Blaine; Todorov, Todor I.; Adams, Monique

2007-01-01

Mine drainage and underground water samples were collected for analysis of inorganic solutes as part of a 1-year, hydrogeologic investigation of the Standard Mine and vicinity. The U.S. Environmental Protection Agency has listed the Standard Mine in the Elk Creek drainage near Crested Butte, Colorado, as a Superfund Site because discharge from the Standard Mine enters Elk Creek, contributing dissolved and suspended loads of zinc, cadmium, copper, and other metals to Coal Creek, which is the primary drinking-water supply for the town of Crested Butte. Water analyses are reported for mine-effluent samples from Levels 1 and 5 of the Standard Mine, underground samples from Levels 3 and 5 of the Standard Mine, mine effluent from an adit located on the Elk Lode, and two spring samples that emerged from waste-rock material below Level 5 of the Standard Mine and the adit located on the Elk Lode. Reported analyses include field parameters (pH, specific conductance, water temperature, dissolved oxygen, and redox potential) and major constituents and trace elements.

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

PubMed Central

Men, Hong; Shi, Yan; Fu, Songlin; Jiao, Yanan; Qiao, Yu; Liu, Jingjing

2017-01-01

Multi-sensor data fusion can provide more comprehensive and more accurate analysis results. However, it also brings some redundant information, which is an important issue with respect to finding a feature-mining method for intuitive and efficient analysis. This paper demonstrates a feature-mining method based on variable accumulation to find the best expression form and variables’ behavior affecting beer flavor. First, e-tongue and e-nose were used to gather the taste and olfactory information of beer, respectively. Second, principal component analysis (PCA), genetic algorithm-partial least squares (GA-PLS), and variable importance of projection (VIP) scores were applied to select feature variables of the original fusion set. Finally, the classification models based on support vector machine (SVM), random forests (RF), and extreme learning machine (ELM) were established to evaluate the efficiency of the feature-mining method. The result shows that the feature-mining method based on variable accumulation obtains the main feature affecting beer flavor information, and the best classification performance for the SVM, RF, and ELM models with 96.67%, 94.44%, and 98.33% prediction accuracy, respectively. PMID:28753917

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.

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)

PubMed Central

Lechevalier, D.; Ak, R.; Ferguson, M.; Law, K. H.; Lee, Y.-T. T.; Rachuri, S.

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain. PMID:29202125

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML).

PubMed

Park, J; Lechevalier, D; Ak, R; Ferguson, M; Law, K H; Lee, Y-T T; Rachuri, S

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain.

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

Translations on North Korea No. 622

DTIC Science & Technology

1978-10-13

Pyongyang Power Station 5 July Electric Factory Hamhung Machine Tool Factory Kosan Plastic Pipe Factory Sog’wangea Plastic Pipe Factory 8...August Factory Double Chollima Hamhung Disabled Veterans’ Plastic Goods Factory Mangyongdae Machine Tool Factory Kangso Coal Mine Tongdaewon Garment...21 Jul 78 p 4) innovating in machine tool production (NC 21 Jul 78 p 2) in 40 days of the 蔴 days of combat" raised coal production 10 percent

30 CFR 820.11 - Performance standards: Anthracite mines in Pennsylvania.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Pennsylvania. 820.11 Section 820.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... STANDARDS-ANTHRACITE MINES IN PENNSYLVANIA § 820.11 Performance standards: Anthracite mines in Pennsylvania. Anthracite mines in Pennsylvania, as specified in section 529 of the Act, shall comply with its approved...

30 CFR 27.24 - Power-shutoff component.

Code of Federal Regulations, 2010 CFR

2010-07-01

... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.24 Power... the machine or equipment when actuated by the methane detector at a methane concentration of 2.0... actuated by the methane detector, cause a control circuit to shut down the machine or equipment on which it...

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

What happened to the TSM

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

Brezovec, D.

1983-11-01

A new coal mining machine that was going to pull some 40 million tons of coal from the Appalachian coalfields by 1986 has had more than its share of start-up problems. The machine, known as the Thin Seam Miner (TSM), is a $2.7-million auger-type mining machine that is designed to bore 220 ft into new or abandoned highwalls (CA 5/82 p. 106). Gamma-ray sensors located near the continuous drum miner-type cutter head monitor for rock and other sensors monitor for methane. The machines are designed to produce about 425 tons per shift from a 36-in.-thick coal seam. The machines weremore » introduced officially to the American coal industry at a luncheon Aug. 19, 1981, in a ballroom at the Lexington, Ky., Hyatt Regency Hotel. At the luncheon, some 200 coal industry executives and others sipped champagne and listened to glowing reports of how 24 of the machines would produce 2.2 million tons of coal by the end of 1981 and 64 of the machines would produce 6.6 million tons by the end of 1982. The machines would be built in Holland by RijnSchelde-Verolme (RSV), a major Dutch shipbuilder, and managed in the United States by Advanced Coal Management (ACM), a company formed for the purpose by James D. Stacy, a colorful, cigar-smoking stock car owner whose experience in the coal business dated from only the mid-1970s.« less

Development and testing of a computer assisted remote-control system for the compact loader-trammer. Report of Investigations/1992

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

Ruff, T.M.

1992-01-01

A prototype mucking machine designed to operate in narrow vein stopes was developed by Foster-Miller, Inc., Waltham, MA, under contract with the U.S. Bureau of Mines. The machine, called a compact loader/trammer, or minimucker, was designed to replace slusher muckers in narrow-vein underground mines. The minimucker is a six-wheel-drive, skid-steered, load-haul-dump machine that loads muck at the front with a novel slide-bucket system and ejects it out the rear so that the machine does not have to be turned around. To correct deficiencies of the tether remote control system, a computer-based, radio remote control was retrofitted to the minimucker. Initialmore » tests indicated a need to assist the operator in guiding the machine in narrow stopes and an automatic guidance system that used ultrasonic ranging sensors and a wall-following algorithm was installed. Additional tests in a simulated test stope showed that these changes improved the operation of the minimucker. The design and functions of the minimucker and its computer-based, remote control system are reviewed, and an ultrasonic, sensor-based guidance system is described.« less

Review of smoothing methods for enhancement of noisy data from heavy-duty LHD mining machines

NASA Astrophysics Data System (ADS)

Wodecki, Jacek; Michalak, Anna; Stefaniak, Paweł

2018-01-01

Appropriate analysis of data measured on heavy-duty mining machines is essential for processes monitoring, management and optimization. Some particular classes of machines, for example LHD (load-haul-dump) machines, hauling trucks, drilling/bolting machines etc. are characterized with cyclicity of operations. In those cases, identification of cycles and their segments or in other words - simply data segmentation is a key to evaluate their performance, which may be very useful from the management point of view, for example leading to introducing optimization to the process. However, in many cases such raw signals are contaminated with various artifacts, and in general are expected to be very noisy, which makes the segmentation task very difficult or even impossible. To deal with that problem, there is a need for efficient smoothing methods that will allow to retain informative trends in the signals while disregarding noises and other undesired non-deterministic components. In this paper authors present a review of various approaches to diagnostic data smoothing. Described methods can be used in a fast and efficient way, effectively cleaning the signals while preserving informative deterministic behaviour, that is a crucial to precise segmentation and other approaches to industrial data analysis.

Automated Assessment of Patients' Self-Narratives for Posttraumatic Stress Disorder Screening Using Natural Language Processing and Text Mining.

PubMed

He, Qiwei; Veldkamp, Bernard P; Glas, Cees A W; de Vries, Theo

2017-03-01

Patients' narratives about traumatic experiences and symptoms are useful in clinical screening and diagnostic procedures. In this study, we presented an automated assessment system to screen patients for posttraumatic stress disorder via a natural language processing and text-mining approach. Four machine-learning algorithms-including decision tree, naive Bayes, support vector machine, and an alternative classification approach called the product score model-were used in combination with n-gram representation models to identify patterns between verbal features in self-narratives and psychiatric diagnoses. With our sample, the product score model with unigrams attained the highest prediction accuracy when compared with practitioners' diagnoses. The addition of multigrams contributed most to balancing the metrics of sensitivity and specificity. This article also demonstrates that text mining is a promising approach for analyzing patients' self-expression behavior, thus helping clinicians identify potential patients from an early stage.

Contribution of individual components of a job cycle on overall severity of whole-body vibration exposure: a study in Indian mines.

PubMed

Mandal, Bibhuti B; Mansfield, Neil J

2016-01-01

Drivers of earth-moving machines are exposed to whole-body vibration (WBV). In mining operations there can be a combination of relatively high magnitudes of vibration and long exposure times. Effective risk mitigation requires understanding of the main aspects of a task that pose a hazard to health. There are very few published studies of WBV exposure from India. This paper reports on a study that considered the contribution of the component phases of dumper operations, on the overall vibration exposure of the drivers. It shows that vibration magnitudes are relatively high, and that haulage tasks are the main contributor to the exposure. It is recommended that driver speed, haul road surfaces and vehicle maintenance/selection are optimized to ensure minimization of vibration. If this is not sufficient, operation times might need to be reduced in order to ensure that the health guidance caution zone from Standard No. ISO 2631-1:1997 is not exceeded.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

PubMed Central

Jo, ByungWan

2018-01-01

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

PubMed

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

CANFAR+Skytree: A Cloud Computing and Data Mining System for Astronomy

NASA Astrophysics Data System (ADS)

Ball, N. M.

2013-10-01

This is a companion Focus Demonstration article to the CANFAR+Skytree poster (Ball 2013, this volume), demonstrating the usage of the Skytree machine learning software on the Canadian Advanced Network for Astronomical Research (CANFAR) cloud computing system. CANFAR+Skytree is the world's first cloud computing system for data mining in astronomy.

Data Mining in Finance: Using Counterfactuals To Generate Knowledge from Organizational Information Systems.

ERIC Educational Resources Information Center

Dhar, Vasant

1998-01-01

Shows how counterfactuals and machine learning methods can be used to guide exploration of large databases that addresses some of the fundamental problems that organizations face in learning from data. Discusses data mining, particularly in the financial arena; generating useful knowledge from data; and the evaluation of counterfactuals. (LRW)

Data Mining in Earth System Science (DMESS 2011)

Treesearch

Forrest M. Hoffman; J. Walter Larson; Richard Tran Mills; Bhorn-Gustaf Brooks; Auroop R. Ganguly; William Hargrove; et al

2011-01-01

From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques—such as cluster analysis, singular value decomposition, block entropy, Fourier and...

Mining the Galaxy Zoo Database: Machine Learning Applications

NASA Astrophysics Data System (ADS)

Borne, Kirk D.; Wallin, J.; Vedachalam, A.; Baehr, S.; Lintott, C.; Darg, D.; Smith, A.; Fortson, L.

2010-01-01

The new Zooniverse initiative is addressing the data flood in the sciences through a transformative partnership between professional scientists, volunteer citizen scientists, and machines. As part of this project, we are exploring the application of machine learning techniques to data mining problems associated with the large and growing database of volunteer science results gathered by the Galaxy Zoo citizen science project. We will describe the basic challenge, some machine learning approaches, and early results. One of the motivators for this study is the acquisition (through the Galaxy Zoo results database) of approximately 100 million classification labels for roughly one million galaxies, yielding a tremendously large and rich set of training examples for improving automated galaxy morphological classification algorithms. In our first case study, the goal is to learn which morphological and photometric features in the Sloan Digital Sky Survey (SDSS) database correlate most strongly with user-selected galaxy morphological class. As a corollary to this study, we are also aiming to identify which galaxy parameters in the SDSS database correspond to galaxies that have been the most difficult to classify (based upon large dispersion in their volunter-provided classifications). Our second case study will focus on similar data mining analyses and machine leaning algorithms applied to the Galaxy Zoo catalog of merging and interacting galaxies. The outcomes of this project will have applications in future large sky surveys, such as the LSST (Large Synoptic Survey Telescope) project, which will generate a catalog of 20 billion galaxies and will produce an additional astronomical alert database of approximately 100 thousand events each night for 10 years -- the capabilities and algorithms that we are exploring will assist in the rapid characterization and classification of such massive data streams. This research has been supported in part through NSF award #0941610.

30 CFR 57.22102 - Smoking (I-C mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22102 Smoking (I-C mines). (a...

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

76 FR 54163 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-31

... analysis of fatalities and non-fatal accidents during the 1984 through 2010 period indicates that many of... under 30 CFR 18.82 and issued an experimental permit on May 30, 2003. After several revisions, the... Geosteering Tramguard TM System, which MSHA tested in June 2005 under an experimental permit on a remote...

Development of a Workbench to Address the Educational Data Mining Bottleneck

ERIC Educational Resources Information Center

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

2012-01-01

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

Management Perspectives Pertaining to Root Cause Analyses of Nunn-McCurdy Breaches. Volume 4

DTIC Science & Technology

2013-01-01

the FY2012 NDAA, the Army revised its initial budget request, allocating money from the purchase of new M2 .50 caliber machine guns to the...Quick-change machine gun barrel Explosive reactive armor Linear demolition charge system Full width, surface mine ploughs On-board vehicle power...Quantity Oversight of ACAT II Programs 45 for a restart to the program citing a “critical shortage of serviceable machine guns for our Soldiers who

30 CFR Appendix I to Subpart C of... - National Consensus Standards

Code of Federal Regulations, 2010 CFR

2010-07-01

... Subpart C of Part 56 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Fire... Standards Mine operators seeking further information in the area of fire prevention and control may consult...

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

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

40 CFR 434.55 - New source performance standards (NSPS).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false New source performance standards (NSPS... PERFORMANCE STANDARDS Post-Mining Areas § 434.55 New source performance standards (NSPS). The following new source performance standards shall apply to the post-mining areas of all new source coal mines: (a...

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.

Method and apparatus for monitoring the thickness of a coal rib during rib formation

DOEpatents

Mowrey, Gary L.; Ganoe, Carl W.; Monaghan, William D.

1996-01-01

Apparatus for monitoring the position of a mining machine cutting a new entry in a coal seam relative to an adjacent, previously cut entry to determine the distance between a near face of the adjacent previously cut entry and a new face adjacent thereto of a new entry being cut by the mining machine which together define the thickness of a coal rib being formed between the new entry and the adjacent previously cut entry during the new entry-cutting operation. The monitoring apparatus; includes a transmit antenna mounted on the mining machine and spaced inwardly from the new face of the coal rib for transmitting radio energy towards the coal rib so that one portion of the radio energy is reflected by the new face which is defined at an air-coal interface between the new entry and the coal rib and another portion of the radio energy is reflected by the near face of the coal rib which is defined at an air-coal interface between the coal rib and the adjacent previously cut entry. A receive antenna mounted on the mining machine and spaced inwardly of the new face of the coal rib receives the one portion of the radio energy reflected by the new face and also receives the another portion of the radio energy reflected by the near face. A processor determines a first elapsed time period equal to the time required for the one portion of the radio energy reflected by the new face to travel between the transmit antenna and the receive antenna and also determines a second elapsed time period equal to the time required for the another portion of the radio energy reflected by the near face to travel between the transmit antenna and the receive antenna and thereafter calculates the thickness of the coal rib being formed as a function of the difference between the first and second elapsed time periods.

Alkahest NuclearBLAST : a user-friendly BLAST management and analysis system

PubMed Central

Diener, Stephen E; Houfek, Thomas D; Kalat, Sam E; Windham, DE; Burke, Mark; Opperman, Charles; Dean, Ralph A

2005-01-01

Background - Sequencing of EST and BAC end datasets is no longer limited to large research groups. Drops in per-base pricing have made high throughput sequencing accessible to individual investigators. However, there are few options available which provide a free and user-friendly solution to the BLAST result storage and data mining needs of biologists. Results - Here we describe NuclearBLAST, a batch BLAST analysis, storage and management system designed for the biologist. It is a wrapper for NCBI BLAST which provides a user-friendly web interface which includes a request wizard and the ability to view and mine the results. All BLAST results are stored in a MySQL database which allows for more advanced data-mining through supplied command-line utilities or direct database access. NuclearBLAST can be installed on a single machine or clustered amongst a number of machines to improve analysis throughput. NuclearBLAST provides a platform which eases data-mining of multiple BLAST results. With the supplied scripts, the program can export data into a spreadsheet-friendly format, automatically assign Gene Ontology terms to sequences and provide bi-directional best hits between two datasets. Users with SQL experience can use the database to ask even more complex questions and extract any subset of data they require. Conclusion - This tool provides a user-friendly interface for requesting, viewing and mining of BLAST results which makes the management and data-mining of large sets of BLAST analyses tractable to biologists. PMID:15958161

20131201-1231_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-01-08

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

20131101-1130_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-12-02

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

20130416_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-04-24

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

20131001-1031_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-11-05

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

20140201-0228_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-03-03

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

20130801-0831_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-09-10

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

20140101-0131_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-02-03

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

20140430_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-05-05

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

20140301-0331_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-04-07

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

20140501-0531_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-06-02

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

20140601-0630_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-06-30

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

20140701-0731_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2014-07-31

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

20130901-0930_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Thibedeau, Joe

2013-10-25

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

Green Machine Florida Canyon Hourly Data 20130731

DOE Data Explorer

Vanderhoff, Alex

2013-08-30

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

20130501-20130531_Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-06-18

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

Green Machine Florida Canyon Hourly Data

DOE Data Explorer

Vanderhoff, Alex

2013-07-15

Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

KSC-2012-3081

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3076

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3080

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3079

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors works with its machine during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

30 CFR 48.7 - Training of miners assigned to a task in which they have had no previous experience; minimum...

Code of Federal Regulations, 2010 CFR

2010-07-01

... to new work tasks as mobile equipment operators, drilling machine operators, haulage and conveyor... protective measures a miner can take against these hazards, and the contents of the mine's HazCom program... operation in the mine, which require new or different operating procedures. (4) Such other courses as may be...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Permit to use experimental electric face... Modifications of Approved Machines, and Permits To Use Experimental Equipment § 18.82 Permit to use experimental... to use experimental electric face equipment in a gassy mine or tunnel will be considered only when...

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.

CFD analysis on gas distribution for different scrubber redirection configurations in sump cut.

PubMed

Zheng, Y; Organiscak, J A; Zhou, L; Beck, T W; Rider, J P

2015-01-01

The National Institute for Occupational Safety and Health's Office of Mine Safety and Health Research recently developed a series of models using computational fluid dynamics (CFD) to study the gas distribution around a continuous mining machine with various fan-powered flooded bed scrubber discharge configurations. CFD models using Species Transport Model without reactions in FLUENT were constructed to evaluate the redirection of scrubber discharge toward the mining face rather than behind the return curtain. The following scenarios are considered in this study: 100 percent of the discharge redirected back toward the face on the off-curtain side of the continuous miner; 100 percent of the discharge redirected back toward the face, but divided equally to both sides of the machine; and 15 percent of the discharge redirected toward the face on the off-curtain side of the machine, with 85 percent directed into the return. These models were compared against a model with a conventional scrubber discharge, where air is directed away from the face into the return. The CFD models were calibrated and validated based on experimental data and accurately predicted sulfur hexafluoride (SF 6 ) gas levels at four gas monitoring locations. One additional prediction model was simulated to consider a different scrubber discharge angle for the 100 percent redirected, equally divided case. These models identified relatively high gassy areas around the continuous miner, which may not warrant their use in coal mines with medium to high methane liberation rates. This paper describes the methodology used to develop the CFD models, and the validation of the models based on experimental data.

30 CFR 57.22106 - Dust containing volatile matter (I-C mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22106...

19 CFR 10.530 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... of the following processes: Welding, flame spraying, surface machining, knurling, plating, sleeving...” means a person who grows, raises, mines, harvests, fishes, traps, hunts, manufactures, processes...

Raising quality of maintenance and control of metallic structures in large-load technological machines

NASA Astrophysics Data System (ADS)

Drygin, M. Yu; Kuryshkin, N. P.

2018-01-01

Active growth of coal extraction and underinvestment of coal mining in Russia lead to the fact that technical state of more than 86% of technological machines at opencast coal mines is unacceptable. One of the most significant problems is unacceptable state of supporting metallic structures of excavators and mine dump trucks. The analysis has shown that defects in these metallic structures had been accumulated for a long time. Their removal by the existing method of repair welding was not effective - the flaws reappeared in 2-6 months of technological machines’ service. The authors detected the prime causes that did not allow to make a good repair welding joint. A new technology of repair welding had been tested and endorsed, and this allowed to reduce the number of welded joints’ flaws by 85% without additional raising welders’ qualification. As a result the number of flaws in metallic structures of the equipment had been reduced by 35 % as early as in the first year of using the new technology.

40 CFR 434.55 - New source performance standards (NSPS).

Code of Federal Regulations, 2014 CFR

2014-07-01

... performance standards shall be achieved for the discharge of any acid or ferruginous mine drainage subject to... following new source performance standards shall apply to the post-mining areas of all new source coal mines... new source coal mines until SMCRA bond release. Except as provided in 40 CFR 401.17 and §§ 434.61 and...

40 CFR 434.55 - New source performance standards (NSPS).

Code of Federal Regulations, 2011 CFR

2011-07-01

... standards shall be achieved for the discharge of any acid or ferruginous mine drainage subject to this... source performance standards shall apply to the post-mining areas of all new source coal mines: (a... coal mines until SMCRA bond release. Except as provided in 40 CFR 401.17 and §§ 434.61 and 434.63 (d)(2...

40 CFR 434.55 - New source performance standards (NSPS).

Code of Federal Regulations, 2012 CFR

2012-07-01

... performance standards shall be achieved for the discharge of any acid or ferruginous mine drainage subject to... following new source performance standards shall apply to the post-mining areas of all new source coal mines... new source coal mines until SMCRA bond release. Except as provided in 40 CFR 401.17 and §§ 434.61 and...

Effect of Temporal Relationships in Associative Rule Mining for Web Log Data

PubMed Central

Mohd Khairudin, Nazli; Mustapha, Aida

2014-01-01

The advent of web-based applications and services has created such diverse and voluminous web log data stored in web servers, proxy servers, client machines, or organizational databases. This paper attempts to investigate the effect of temporal attribute in relational rule mining for web log data. We incorporated the characteristics of time in the rule mining process and analysed the effect of various temporal parameters. The rules generated from temporal relational rule mining are then compared against the rules generated from the classical rule mining approach such as the Apriori and FP-Growth algorithms. The results showed that by incorporating the temporal attribute via time, the number of rules generated is subsequently smaller but is comparable in terms of quality. PMID:24587757

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 57.22105 - Smoking and open flames (IV mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... Section 57.22105 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22105 Smoking and open...

30 CFR 57.22104 - Open flames (I-C mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

....22104 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22104 Open flames (I-C...

Machine learning and medicine: book review and commentary.

PubMed

Koprowski, Robert; Foster, Kenneth R

2018-02-01

This article is a review of the book "Master machine learning algorithms, discover how they work and implement them from scratch" (ISBN: not available, 37 USD, 163 pages) edited by Jason Brownlee published by the Author, edition, v1.10 http://MachineLearningMastery.com . An accompanying commentary discusses some of the issues that are involved with use of machine learning and data mining techniques to develop predictive models for diagnosis or prognosis of disease, and to call attention to additional requirements for developing diagnostic and prognostic algorithms that are generally useful in medicine. Appendix provides examples that illustrate potential problems with machine learning that are not addressed in the reviewed book.

Development Of Knowledge Systems For Trouble Shooting Complex Production Machinery

NASA Astrophysics Data System (ADS)

Sanford, Richard L.; Novak, Thomas; Meigs, James R.

1987-05-01

This paper discusses the use of knowledge base system software for microcomputers to aid repairmen in diagnosing electrical failures in complex mining machinery. The knowledge base is constructed to allow the user to input initial symptoms of the failed machine, and the most probable cause of failure is traced through the knowledge base, with the software requesting additional information such as voltage or resistance measurements as needed. Although the case study presented is for an underground mining machine, results have application to any industry using complex machinery. Two commercial expert-system development tools (M1 TM and Insight 2+TM) and an Al language (Turbo PrologTM) are discussed with emphasis on ease of application and suitability for this study.

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

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

Caudle, R.D.; Lall, V.

1985-07-01

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

Where tunneling equipment is heading

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

Singhal, R.K.

1984-02-01

A variety of equipment is being used for roadheading and tunneling in the mining industry. This includes hydraulic/rotary precussive drills for use in conventional drill and blast, drum-type continuous miners, roadheaders, mini-and midi-full facers for small size openings, soft rock shielded tunnel boring machines, and hard rock tunnel boring machines. The availability, performance, and specifications for tunneling equipment are discussed.

30 CFR 57.22101 - Smoking (I-A, II-A, III, and V-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22101...

Measuring mine roof bolt strains

DOEpatents

Steblay, Bernard J.

1986-01-01

A mine roof bolt and a method of measuring the strain in mine roof bolts of this type are disclosed. According to the method, a flat portion on the head of the mine roof bolt is first machined. Next, a hole is drilled radially through the bolt at a predetermined distance from the bolt head. After installation of the mine roof bolt and loading, the strain of the mine roof bolt is measured by generating an ultrasonic pulse at the flat portion. The time of travel of the ultrasonic pulse reflected from the hole is measured. This time of travel is a function of the distance from the flat portion to the hole and increases as the bolt is loaded. Consequently, the time measurement is correlated to the strain in the bolt. Compensation for various factors affecting the travel time are also provided.

Cutting sound enhancement system for mining machines

DOEpatents

Leigh, Michael C.; Kwitowski, August J.

1992-01-01

A cutting sound enhancement system (10) for transmitting an audible signal from the cutting head (101) of a piece of mine machinery (100) to an operator at a remote station (200), wherein, the operator using a headphone unit (14) can monitor the difference in sounds being made solely by the cutting head (101) to determine the location of the roof, floor, and walls of a coal seam (50).

30 CFR 75.829 - Tramming continuous mining machines in and out of the mine and from section to section.

Code of Federal Regulations, 2011 CFR

2011-07-01

... accordance with movement requirements of high-voltage power centers and portable transformers (§ 75.812) and... transformer. A step-up transformer is a transformer that steps up the low or medium voltage to high voltage... supplying low or medium voltage to the step-up transformer must meet the applicable requirements of 30 CFR...

30 CFR 75.829 - Tramming continuous mining machines in and out of the mine and from section to section.

Code of Federal Regulations, 2013 CFR

2013-07-01

... accordance with movement requirements of high-voltage power centers and portable transformers (§ 75.812) and... transformer. A step-up transformer is a transformer that steps up the low or medium voltage to high voltage... supplying low or medium voltage to the step-up transformer must meet the applicable requirements of 30 CFR...

30 CFR 75.829 - Tramming continuous mining machines in and out of the mine and from section to section.

Code of Federal Regulations, 2012 CFR

2012-07-01

... accordance with movement requirements of high-voltage power centers and portable transformers (§ 75.812) and... transformer. A step-up transformer is a transformer that steps up the low or medium voltage to high voltage... supplying low or medium voltage to the step-up transformer must meet the applicable requirements of 30 CFR...

30 CFR 75.829 - Tramming continuous mining machines in and out of the mine and from section to section.

Code of Federal Regulations, 2010 CFR

2010-07-01

... accordance with movement requirements of high-voltage power centers and portable transformers (§ 75.812) and... transformer. A step-up transformer is a transformer that steps up the low or medium voltage to high voltage... supplying low or medium voltage to the step-up transformer must meet the applicable requirements of 30 CFR...

30 CFR 75.829 - Tramming continuous mining machines in and out of the mine and from section to section.

Code of Federal Regulations, 2014 CFR

2014-07-01

... accordance with movement requirements of high-voltage power centers and portable transformers (§ 75.812) and... transformer. A step-up transformer is a transformer that steps up the low or medium voltage to high voltage... supplying low or medium voltage to the step-up transformer must meet the applicable requirements of 30 CFR...

Development of minimum standards for hardwoods used in producing underground coal mine timbers

Treesearch

Floyd G. Timson

1978-01-01

This note presents minimum standards for raw material used in the production of sawn, split, and round timbers for the underground mining industry. The standards are based on a summary of information gathered from many mine-timber producers.

30 CFR 816.79 - Protection of underground mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Protection of underground mining. 816.79 Section 816.79 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS PERMANENT PROGRAM PERFORMANCE STANDARDS-SURFACE MINING...

30 CFR 816.79 - Protection of underground mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Protection of underground mining. 816.79 Section 816.79 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS PERMANENT PROGRAM PERFORMANCE STANDARDS-SURFACE MINING...

Ten quick tips for machine learning in computational biology.

PubMed

Chicco, Davide

2017-01-01

Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.

30 CFR 57.22002 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in... delay connectors. [A copy of Title 49 is available at any Metal and Nonmetal Mine Safety and Health...

30 CFR 57.22002 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in... delay connectors. [A copy of Title 49 is available at any Metal and Nonmetal Mine Safety and Health...

30 CFR 57.22002 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in... delay connectors. [A copy of Title 49 is available at any Metal and Nonmetal Mine Safety and Health...

30 CFR 57.22002 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in... delay connectors. [A copy of Title 49 is available at any Metal and Nonmetal Mine Safety and Health...

30 CFR 819.11 - Auger mining: General.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Auger mining: General. 819.11 Section 819.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS SPECIAL PERMANENT PROGRAM PERFORMANCE STANDARDS-AUGER MINING § 819...

30 CFR 819.11 - Auger mining: General.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: General. 819.11 Section 819.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS SPECIAL PERMANENT PROGRAM PERFORMANCE STANDARDS-AUGER MINING § 819...

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

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

PubMed Central

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

2014-01-01

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

On-line Machine Learning and Event Detection in Petascale Data Streams

NASA Astrophysics Data System (ADS)

Thompson, David R.; Wagstaff, K. L.

2012-01-01

Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data mining. This talk describes research performed at the Jet Propulsion Laboratory, California Institute of Technology. Copyright 2012, All Rights Reserved. U.S. Government support acknowledged.

30 CFR 937.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Performance standards-underground mining activities. 937.817 Section 937.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 937.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Performance standards-underground mining activities. 937.817 Section 937.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 937.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Performance standards-surface mining activities. 937.816 Section 937.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 937.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Performance standards-surface mining activities. 937.816 Section 937.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2013 CFR

2013-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2012 CFR

2012-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2014 CFR

2014-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 912.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 912.817 Section 912.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO...

30 CFR 910.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 910.817 Section 910.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA...

30 CFR 947.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 947.817 Section 947.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON...

30 CFR 903.816 - Performance standards-Surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-Surface mining activities. 903.816 Section 903.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA...

30 CFR 939.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 939.817 Section 939.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE...

30 CFR 942.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-Auger mining. 942.819 Section 942.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE TENNESSEE...

30 CFR 937.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 937.817 Section 937.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 912.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 912.816 Section 912.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO...

30 CFR 921.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 921.817 Section 921.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE...

30 CFR 903.817 - Performance standards-Underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-Underground mining activities. 903.817 Section 903.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA...

30 CFR 933.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 933.816 Section 933.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 905.817 - Peformance standards-Underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Peformance standards-Underground mining activities. 905.817 Section 905.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE CALIFORNIA...

30 CFR 910.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 910.816 Section 910.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA...

30 CFR 947.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 947.819 Section 947.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON...

30 CFR 933.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 933.817 Section 933.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 922.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 922.817 Section 922.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

30 CFR 921.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 921.816 Section 921.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE...

30 CFR 937.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 937.816 Section 937.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 922.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 922.819 Section 922.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

30 CFR 933.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 933.819 Section 933.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 905.816 - Performance standards-Surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-Surface mining activities. 905.816 Section 905.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE CALIFORNIA...

30 CFR 941.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 941.816 Section 941.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH...

30 CFR 921.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 921.819 Section 921.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MASSACHUSETTS...

30 CFR 922.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 922.816 Section 922.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

30 CFR 939.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-surface mining activities. 939.816 Section 939.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE...

30 CFR 905.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-Auger mining. 905.819 Section 905.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE CALIFORNIA...

30 CFR 941.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Performance standards-underground mining activities. 941.817 Section 941.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH...

30 CFR 912.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 912.817 Section 912.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO...

30 CFR 933.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 933.816 Section 933.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 947.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 947.817 Section 947.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON...

30 CFR 903.817 - Performance standards-Underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-Underground mining activities. 903.817 Section 903.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA...

30 CFR 922.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 922.819 Section 922.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

30 CFR 921.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 921.819 Section 921.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MASSACHUSETTS...

30 CFR 912.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 912.816 Section 912.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO...

30 CFR 910.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 910.817 Section 910.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA...

30 CFR 947.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 947.816 Section 947.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON...

30 CFR 910.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 910.816 Section 910.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA...

30 CFR 939.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 939.816 Section 939.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE...

30 CFR 937.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 937.817 Section 937.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 905.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-Auger mining. 905.819 Section 905.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE CALIFORNIA...

30 CFR 939.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 939.817 Section 939.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE...

30 CFR 921.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 921.817 Section 921.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE...

30 CFR 933.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 933.819 Section 933.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 941.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 941.817 Section 941.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH...

30 CFR 941.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 941.816 Section 941.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH...

30 CFR 922.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 922.817 Section 922.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

30 CFR 942.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-Auger mining. 942.819 Section 942.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE TENNESSEE...

30 CFR 921.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 921.816 Section 921.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE...

30 CFR 903.816 - Performance standards-Surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-Surface mining activities. 903.816 Section 903.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA...

30 CFR 933.817 - Performance standards-underground mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-underground mining activities. 933.817 Section 933.817 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE NORTH...

30 CFR 937.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 937.816 Section 937.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 947.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 947.819 Section 947.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON...

30 CFR 922.816 - Performance standards-surface mining activities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Performance standards-surface mining activities. 922.816 Section 922.816 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN...

Evaluation of a disposable diesel exhaust filter for permissible mining machines

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

Ambs, J.L.; Cantrell, B.K.; Watts, W.F.

1994-01-01

The US Bureau of Mines (USBM) Diesel Research Program emphasizes the development and evaluation of emission control devices to reduce exposure of miners to diesel exhaust pollutants. Studies by the USBM have shown that diesel exhaust aerosol (DEA) contributes a substantial portion of the respirable aerosol in underground coal mines using diesel equipment not equipped with emission controls. The USBM and the Donaldson Co., Inc., Minneapolis, MN, have developed a low-temperature, disposable diesel exhaust filter (DDEF) for use on permissible diesel haulage vehicles equipped with waterbath exhaust conditioners. These were evaluated in three underground mines to determine their effectiveness inmore » reducing DEA concentrations. The DDEF reduced DEA concentrations from 70 to 90% at these mines. The usable life of the filter ranged from 10 to 32 h, depending on factors that affect DEA output, such as mine altitude, engine type, and duty-cycle. Cost per filter is approximately $40.« less

Using support vector machines to detect medical fraud and abuse.

PubMed

Francis, Charles; Pepper, Noah; Strong, Homer

2011-01-01

This paper examines the architecture and efficacy of Quash, an automated medical bill processing system capable of bill routing and abuse detection. Quash is designed to be used in conjunction with human auditors and a standard bill review software platform to provide a complete cost containment solution for medical claims. The primary contribution of Quash is to provide a real world speed up for medical fraud detection experts in their work. There will be a discussion of implementation details and preliminary experimental results. In this paper we are entirely focused on medical data and billing patterns that occur within the United States, though these results should be applicable to any financial transaction environment in which structured coding data can be mined.

Smart material screening machines using smart materials and controls

NASA Astrophysics Data System (ADS)

Allaei, Daryoush; Corradi, Gary; Waigand, Al

2002-07-01

The objective of this product is to address the specific need for improvements in the efficiency and effectiveness in physical separation technologies in the screening areas. Currently, the mining industry uses approximately 33 billion kW-hr per year, costing 1.65 billion dollars at 0.05 cents per kW-hr, of electrical energy for physical separations. Even though screening and size separations are not the single most energy intensive process in the mining industry, they are often the major bottleneck in the whole process. Improvements to this area offer tremendous potential in both energy savings and production improvements. Additionally, the vibrating screens used in the mining processing plants are the most costly areas from maintenance and worker health and safety point of views. The goal of this product is to reduce energy use in the screening and total processing areas. This goal is accomplished by developing an innovative screening machine based on smart materials and smart actuators, namely smart screen that uses advanced sensory system to continuously monitor the screening process and make appropriate adjustments to improve production. The theory behind the development of Smart Screen technology is based on two key technologies, namely smart actuators and smart Energy Flow ControlT (EFCT) strategies, developed initially for military applications. Smart Screen technology controls the flow of vibration energy and confines it to the screen rather than shaking much of the mass that makes up the conventional vibratory screening machine. Consequently, Smart Screens eliminates and downsizes many of the structural components associated with conventional vibratory screening machines. As a result, the surface area of the screen increases for a given envelope. This increase in usable screening surface area extends the life of the screens, reduces required maintenance by reducing the frequency of screen change-outs and improves throughput or productivity.

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format. PMID:25472549

Literature Mining of Pathogenesis-Related Proteins in Human Pathogens for Database Annotation

DTIC Science & Technology

2009-10-01

person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control...submission and for literature mining result display with automatically tagged abstracts. I. Literature data sets for machine learning algorithm training...mass spectrometry) proteomics data from Burkholderia strains. • Task1 ( M13 -15): Preliminary analysis of the Burkholderia proteomic space

Discriminative and informative features for biomolecular text mining with ensemble feature selection.

PubMed

Van Landeghem, Sofie; Abeel, Thomas; Saeys, Yvan; Van de Peer, Yves

2010-09-15

In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions. However, feature selection (FS) is capable of identifying the most relevant features in any supervised learning setting, providing insight into the specific properties of the classification algorithm. This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results. We show that our FS methodology successfully discards a large fraction of machine-generated features, improving classification performance of state-of-the-art text mining algorithms. Furthermore, we illustrate how FS can be applied to gain understanding in the predictions of a framework for biomolecular event extraction from text. We include numerous examples of highly discriminative features that model either biological reality or common linguistic constructs. Finally, we discuss a number of insights from our FS analyses that will provide the opportunity to considerably improve upon current text mining tools. The FS algorithms and classifiers are available in Java-ML (http://java-ml.sf.net). The datasets are publicly available from the BioNLP'09 Shared Task web site (http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/SharedTask/).

Trends of Occupational Fatalities Involving Machines, United States, 1992–2010

PubMed Central

Marsh, Suzanne M.; Fosbroke, David E.

2016-01-01

Background This paper describes trends of occupational machine-related fatalities from 1992–2010. We examine temporal patterns by worker demographics, machine types (e.g., stationary, mobile), and industries. Methods We analyzed fatalities from Census of Fatal Occupational Injuries data provided by the Bureau of Labor Statistics to the National Institute for Occupational Safety and Health. We used injury source to identify machine-related incidents and Poisson regression to assess trends over the 19-year period. Results There was an average annual decrease of 2.8% in overall machine-related fatality rates from 1992 through 2010. Mobile machine-related fatality rates decreased an average of 2.6% annually and stationary machine-related rates decreased an average of 3.5% annually. Groups that continued to be at high risk included older workers; self-employed; and workers in agriculture/forestry/fishing, construction, and mining. Conclusion Addressing dangers posed by tractors, excavators, and other mobile machines needs to continue. High-risk worker groups should receive targeted information on machine safety. PMID:26358658

30 CFR 937.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Special performance standards-auger mining. 937.819 Section 937.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937...

30 CFR 937.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Special performance standards-auger mining. 937.819 Section 937.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937...

30 CFR 912.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 912.819 Section 912.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO § 912...

30 CFR 939.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 939.819 Section 939.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE ISLAND...

30 CFR 941.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 941.819 Section 941.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH DAKOTA...

30 CFR 937.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 937.819 Section 937.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937...

30 CFR 903.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-Auger mining. 903.819 Section 903.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA § 903...

30 CFR 910.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Special performance standards-auger mining. 910.819 Section 910.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA § 910...

30 CFR 939.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 939.819 Section 939.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE RHODE ISLAND...

30 CFR 912.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 912.819 Section 912.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO § 912...

30 CFR 937.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 937.819 Section 937.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937...

30 CFR 941.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 941.819 Section 941.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE SOUTH DAKOTA...

30 CFR 910.819 - Special performance standards-auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-auger mining. 910.819 Section 910.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA § 910...

30 CFR 903.819 - Special performance standards-Auger mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Special performance standards-Auger mining. 903.819 Section 903.819 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE ARIZONA § 903...

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.

Exploiting Recurring Structure in a Semantic Network

NASA Technical Reports Server (NTRS)

Wolfe, Shawn R.; Keller, Richard M.

2004-01-01

With the growing popularity of the Semantic Web, an increasing amount of information is becoming available in machine interpretable, semantically structured networks. Within these semantic networks are recurring structures that could be mined by existing or novel knowledge discovery methods. The mining of these semantic structures represents an interesting area that focuses on mining both for and from the Semantic Web, with surprising applicability to problems confronting the developers of Semantic Web applications. In this paper, we present representative examples of recurring structures and show how these structures could be used to increase the utility of a semantic repository deployed at NASA.

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.

Simulation of switching overvoltages in the mine electric power supply system

NASA Astrophysics Data System (ADS)

Ivanchenko, D. I.; Novozhilov, N. G.

2017-02-01

Overvoltages occur in mine power supply systems during switching off consumers with high inductive load, such as transformers, reactors and electrical machines. Overvoltages lead to an increase of insulation degradation rate and may cause electric faults, power outage, fire and explosion of methane and coal dust. This paper is dedicated to simulation of vacuum circuit breaker switching overvoltages in a mine power supply system by means of Simulink MATLAB. The model of the vacuum circuit breaker implements simulation of transient recovery voltage, current chopping and an electric arc. Obtained results were compared to available experimental data.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

30 CFR 70.101 - Respirable dust standard when quartz is present.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Respirable dust standard when quartz is present. When the respirable dust in the mine atmosphere of the... concentration of respirable dust in the mine atmosphere during each shift to which each miner in the active... average concentration of respirable dust in the mine atmosphere associated with that mechanized mining...

30 CFR 70.101 - Respirable dust standard when quartz is present.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Respirable dust standard when quartz is present. When the respirable dust in the mine atmosphere of the... concentration of respirable dust in the mine atmosphere during each shift to which each miner in the active... average concentration of respirable dust in the mine atmosphere associated with that mechanized mining...

30 CFR 70.101 - Respirable dust standard when quartz is present.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Respirable dust standard when quartz is present. When the respirable dust in the mine atmosphere of the... concentration of respirable dust in the mine atmosphere during each shift to which each miner in the active... average concentration of respirable dust in the mine atmosphere associated with that mechanized mining...

30 CFR 70.101 - Respirable dust standard when quartz is present.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Respirable dust standard when quartz is present. When the respirable dust in the mine atmosphere of the... concentration of respirable dust in the mine atmosphere during each shift to which each miner in the active... average concentration of respirable dust in the mine atmosphere associated with that mechanized mining...

a Contemporary Approach for Evaluation of the best Measurement Capability of a Force Calibration Machine

NASA Astrophysics Data System (ADS)

Kumar, Harish

The present paper discusses the procedure for evaluation of best measurement capability of a force calibration machine. The best measurement capability of force calibration machine is evaluated by a comparison through the precision force transfer standards to the force standard machines. The force transfer standards are calibrated by the force standard machine and then by the force calibration machine by adopting the similar procedure. The results are reported and discussed in the paper and suitable discussion has been made for force calibration machine of 200 kN capacity. Different force transfer standards of nominal capacity 20 kN, 50 kN and 200 kN are used. It is found that there are significant variations in the .uncertainty of force realization by the force calibration machine according to the proposed method in comparison to the earlier method adopted.

Data Mining Citizen Science Results

NASA Astrophysics Data System (ADS)

Borne, K. D.

2012-12-01

Scientific discovery from big data is enabled through multiple channels, including data mining (through the application of machine learning algorithms) and human computation (commonly implemented through citizen science tasks). We will describe the results of new data mining experiments on the results from citizen science activities. Discovering patterns, trends, and anomalies in data are among the powerful contributions of citizen science. Establishing scientific algorithms that can subsequently re-discover the same types of patterns, trends, and anomalies in automatic data processing pipelines will ultimately result from the transformation of those human algorithms into computer algorithms, which can then be applied to much larger data collections. Scientific discovery from big data is thus greatly amplified through the marriage of data mining with citizen science.

Effect of the 2.0 mg/m3 coal mine dust standard on underground environmental dust levels.

PubMed

Parobeck

1975-08-01

The 1969 Federal Coal Mine Health and Safety Act established environmental dust standards for underground coal mines. The Act requires that the average concentration of respirable dust in the active workings of a mine be maintained at or below 3.0 mg/m3; and, that effective December 30, 1972, the 3.0 mg/m3 standard be reduced to 2.0 mg/m3. This paper discusses the current status of dust levels in our underground coal mines, the effect of the 2.0 mg/m3 standard on underground dust levels, and associates the current levels with specific operations and occupations. The comparison is made between current levels and those existing prior to December 30, 1972.

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.

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

Not Available

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

30 CFR 20.0 - Compliance with the requirements necessary for obtaining approval.

Code of Federal Regulations, 2010 CFR

2010-07-01

... LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP... MSHA for any electric mine lamps other than standard cap lamps a manufacturer must comply with the...

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

PubMed

Jimeno Yepes, Antonio; Berlanga, Rafael

2015-02-01

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

Fusion of multiple quadratic penalty function support vector machines (QPFSVM) for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-08-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. The Quadratic Penalty Function Support Vector Machine (QPFSVM) algorithm to aid in the automated detection and classification of sea mines is introduced in this paper. The QPFSVM algorithm is easy to train, simple to implement, and robust to feature space dimension. Outputs of successive SVM algorithms are cascaded in stages (fused) to improve the Probability of Classification (Pc) and reduce the number of false alarms. Even though our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to fusion of any D/C problem (e.g., automated medical diagnosis or automatic target recognition for ballistic missile defense).

9. VIEW UPRIVER SHOWING BARGE AND CONSOLIDATED COAL'S DILWORTH MINELOOKING ...

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

9. VIEW UPRIVER SHOWING BARGE AND CONSOLIDATED COAL'S DILWORTH MINE-LOOKING NORTHEAST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

30 CFR 46.8 - Annual refresher training.

Code of Federal Regulations, 2010 CFR

2010-07-01

... measures a miner can take against these hazards, and the contents of the mine's HazCom program... protection; and working around moving objects (machine guarding). [64 FR 53130, Sept. 30, 1999, as amended at...

Development of sensitized pick coal interface detector system

NASA Technical Reports Server (NTRS)

Burchill, R. F.

1982-01-01

One approach for detection of the coal interface is measurement of pick cutting loads and shock through the use of pick strain gage load cells and accelerometers. The cutting drum of a long wall mining machine contains a number of cutting picks. In order to measure pick loads and shocks, one pick was instrumented and telemetry used to transmit the signals from the drum to an instrument-type tape recorder. A data system using FM telemetry was designed to transfer cutting bit load and shock information from the drum of a longwall shearer coal mining machine to a chassis mounted data recorder. The design of components in the test data system were finalized, the required instruments were assembled, the instrument system was evaluated in an above-ground simulation test, and an underground test series to obtain tape recorded sensor data was conducted.

Transfer Learning beyond Text Classification

NASA Astrophysics Data System (ADS)

Yang, Qiang

Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. While much has been done in transfer learning in text classification and reinforcement learning, there has been a lack of documented success stories of novel applications of transfer learning in other areas. In this invited article, I will argue that transfer learning is in fact quite ubiquitous in many real world applications. In this article, I will illustrate this point through an overview of a broad spectrum of applications of transfer learning that range from collaborative filtering to sensor based location estimation and logical action model learning for AI planning. I will also discuss some potential future directions of transfer learning.

30 CFR 74.9 - Quality assurance.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH COAL MINE... registration under ISO Q9001-2000, American National Standard, Quality Management Systems-Requirements... ISO Q9001-2000, American National Standard, Quality Management Systems-Requirements. The Director of...

30 CFR Appendix I to Subpart T of... - Standard Applicability by Category or Subcategory

Code of Federal Regulations, 2010 CFR

2010-07-01

... Subcategory I Appendix I to Subpart T of Part 57 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Pt. 57, Subpt. T, App. I Appendix I to Subpart T of Part 57—Standard Applicability by Category or Subcategory Subcategory I-A 57...

30 CFR Appendix I to Subpart T of... - Standard Applicability by Category or Subcategory

Code of Federal Regulations, 2011 CFR

2011-07-01

... Subcategory I Appendix I to Subpart T of Part 57 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Pt. 57, Subpt. T, App. I Appendix I to Subpart T of Part 57—Standard Applicability by Category or Subcategory Subcategory I-A 57...

13 CFR 121.510 - What is the size standard for leasing of Government land for uranium mining?

Code of Federal Regulations, 2012 CFR

2012-01-01

... 13 Business Credit and Assistance 1 2012-01-01 2012-01-01 false What is the size standard for leasing of Government land for uranium mining? 121.510 Section 121.510 Business Credit and Assistance... standard for leasing of Government land for uranium mining? A concern is small for this purpose if it...

13 CFR 121.510 - What is the size standard for leasing of Government land for uranium mining?

Code of Federal Regulations, 2011 CFR

2011-01-01

... 13 Business Credit and Assistance 1 2011-01-01 2011-01-01 false What is the size standard for leasing of Government land for uranium mining? 121.510 Section 121.510 Business Credit and Assistance... standard for leasing of Government land for uranium mining? A concern is small for this purpose if it...

13 CFR 121.510 - What is the size standard for leasing of Government land for uranium mining?

Code of Federal Regulations, 2014 CFR

2014-01-01

... 13 Business Credit and Assistance 1 2014-01-01 2014-01-01 false What is the size standard for leasing of Government land for uranium mining? 121.510 Section 121.510 Business Credit and Assistance... standard for leasing of Government land for uranium mining? A concern is small for this purpose if it...

13 CFR 121.510 - What is the size standard for leasing of Government land for uranium mining?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false What is the size standard for leasing of Government land for uranium mining? 121.510 Section 121.510 Business Credit and Assistance... standard for leasing of Government land for uranium mining? A concern is small for this purpose if it...

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.

Adaption of Machine Fluid Analysis for Manufacturing - Final Report

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

Pardini, Allan F.

2005-08-16

Pacific Northwest National Laboratory (PNNL: Operated by Battelle Memorial Institute for the Department of Energy) is working with the Department of Energy (DOE) to develop technology for the US mining industry. Filtration and lubricant suppliers to the pulp and paper industry had noted the recent accomplishments by PNNL and its industrial partners in the DOE OIT Mining Industry of the Future Program, and asked for assistance in adapting this DOE-funded technology to the pulp and paper industry.

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.

30 CFR 819.21 - Auger mining: Protection of underground mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: Protection of underground mining. 819.21 Section 819.21 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... STANDARDS-AUGER MINING § 819.21 Auger mining: Protection of underground mining. Auger holes shall not extend...

Evaluation of a disposable diesel exhaust filter for permissible mining machines. Report of investigations/1994

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

Ambs, J.L.; Cantrell, B.K.; Watts, W.F.

1994-01-01

The U.S. Bureau of Mines (USBM) Diesel Research Program emphasizes the development and evaluation of emission control devices to reduce exposure of miners to diesel exhaust pollutants. Studies by the USBM have shown that diesel exhaust aerosol (DEA) contributes a substantial portion of the respirable aerosol in underground coal mining using diesel equipment not equipped with emission controls. The USBM and the Donaldson Co., Inc., Minneapolis, MN, have developed a low-temperature, disposable diesel exhaust filter (DDEF) for use on permissible diesel haulage vehicles equipped with waterban exhaust conditioners. These were evaluated in three underground mines to determine their effectiveness inmore » reducing DEA concentrations. The DDEF reduced DEA concentrations from 70 to 90 pct at these mines. The usable life of the filter ranged from 10 to 32 h, depending on factors that affect DEA output, such as mine altitude, engine type, and duty-cycle. Cost per filter is approximately $40.« less

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Practical skills of the future innovator

NASA Astrophysics Data System (ADS)

Kaurov, Vitaliy

2015-03-01

Physics graduates face and often are disoriented by the complex and turbulent world of startups, incubators, emergent technologies, big data, social network engineering, and so on. In order to build the curricula that foster the skills necessary to navigate this world, we will look at the experiences at the Wolfram Science Summer School that gathers annually international students for already more than a decade. We will look at the examples of projects and see the development of such skills as innovative thinking, data mining, machine learning, cloud technologies, device connectivity and the Internet of things, network analytics, geo-information systems, formalized computable knowledge, and the adjacent applied research skills from graph theory to image processing and beyond. This should give solid ideas to educators who will build standard curricula adapted for innovation and entrepreneurship education.

Toward Usable Interactive Analytics: Coupling Cognition and Computation

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

Endert, Alexander; North, Chris; Chang, Remco

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less

Spiced-up ANFO mixture leads to super blasts for casting

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

Chironis, N.P.

1984-05-01

There is one problem common to many coal operators in the mountainous regions of western Pennsylvania. As coal seams nearer the crop lines of their mine sites are removed, the overburden heights and stripping ratios increase to about 20-to-1, the range where coal becomes uneconomical to mine. Faced with this situation, a mine operator usually pursues one of four options: 1. Drive a drift mine, which means switching to underground operations with all the complexity and costs involved; 2. Purchase a larger dragline, which involves huge capital expenditures; 3. Bring in an augering machine to auger the exposed seams, amore » technique effective only for a very limited distance into the highwalls; 4. Discontinue operations, the route most operators take.« less

Private and social costs of surface mine reforestation performance criteria.

PubMed

Sullivan, Jay; Amacher, Gregory S

2010-02-01

We study the potentially unnecessary costs imposed by strict performance standards for forest restoration of surface coal mines in the Appalachian region under the Surface Mining Control and Reclamation Act of 1977 (SMCRA) that can vary widely across states. Both the unnecessary private costs to the mine operator and costs to society (social costs) are reported for two performance standards, a ground cover requirement, and a seedling survival target. These standards are examined using numerical analyses under a range of site productivity class and market conditions. We show that a strict (90%) ground cover standard may produce an unnecessary private cost of more than $700/ha and a social cost ranging from $428/ha to $710/ha, as compared with a 70% standard. A strict tree survival standard of 1235 trees/ha, as compared with the more typical 1087 trees/ha standard, may produce an unnecessary private cost of approximately $200/ha, and a social cost in the range of $120 to $208/ha. We conclude that strict performance standards may impose substantial unnecessary private costs and social costs, that strict performance standards may be discouraging the choice of forestry as a post-mining land use, and that opportunities exist for reform of reforestation performance standards. Our study provides a basis for evaluating tradeoffs between regulatory efficiency and optimal reforestation effort.

30 CFR 57.22002 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Definitions. 57.22002 Section 57.22002 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in...

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class.

PubMed

Aguiar, G F M; Batista, B L; Rodrigues, J L; Silva, L R S; Campiglia, A D; Barbosa, R M; Barbosa, F

2012-12-01

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Spinoff 2013

NASA Technical Reports Server (NTRS)

2014-01-01

Topics covered include: Innovative Software Tools Measure Behavioral Alertness; Miniaturized, Portable Sensors Monitor Metabolic Health; Patient Simulators Train Emergency Caregivers; Solar Refrigerators Store Life-Saving Vaccines; Monitors Enable Medication Management in Patients' Homes; Handheld Diagnostic Device Delivers Quick Medical Readings; Experiments Result in Safer, Spin-Resistant Aircraft; Interfaces Visualize Data for Airline Safety, Efficiency; Data Mining Tools Make Flights Safer, More Efficient; NASA Standards Inform Comfortable Car Seats; Heat Shield Paves the Way for Commercial Space; Air Systems Provide Life Support to Miners; Coatings Preserve Metal, Stone, Tile, and Concrete; Robots Spur Software That Lends a Hand; Cloud-Based Data Sharing Connects Emergency Managers; Catalytic Converters Maintain Air Quality in Mines; NASA-Enhanced Water Bottles Filter Water on the Go; Brainwave Monitoring Software Improves Distracted Minds; Thermal Materials Protect Priceless, Personal Keepsakes; Home Air Purifiers Eradicate Harmful Pathogens; Thermal Materials Drive Professional Apparel Line; Radiant Barriers Save Energy in Buildings; Open Source Initiative Powers Real-Time Data Streams; Shuttle Engine Designs Revolutionize Solar Power; Procedure-Authoring Tool Improves Safety on Oil Rigs; Satellite Data Aid Monitoring of Nation's Forests; Mars Technologies Spawn Durable Wind Turbines; Programs Visualize Earth and Space for Interactive Education; Processor Units Reduce Satellite Construction Costs; Software Accelerates Computing Time for Complex Math; Simulation Tools Prevent Signal Interference on Spacecraft; Software Simplifies the Sharing of Numerical Models; Virtual Machine Language Controls Remote Devices; Micro-Accelerometers Monitor Equipment Health; Reactors Save Energy, Costs for Hydrogen Production; Cameras Monitor Spacecraft Integrity to Prevent Failures; Testing Devices Garner Data on Insulation Performance; Smart Sensors Gather Information for Machine Diagnostics; Oxygen Sensors Monitor Bioreactors and Ensure Health and Safety; Vision Algorithms Catch Defects in Screen Displays; and Deformable Mirrors Capture Exoplanet Data, Reflect Lasers.

Teleoperated control system for underground room and pillar mining

DOEpatents

Mayercheck, William D.; Kwitowski, August J.; Brautigam, Albert L.; Mueller, Brian K.

1992-01-01

A teleoperated mining system is provided for remotely controlling the various machines involved with thin seam mining. A thin seam continuous miner located at a mining face includes a camera mounted thereon and a slave computer for controlling the miner and the camera. A plurality of sensors for relaying information about the miner and the face to the slave computer. A slave computer controlled ventilation sub-system which removes combustible material from the mining face. A haulage sub-system removes material mined by the continuous miner from the mining face to a collection site and is also controlled by the slave computer. A base station, which controls the supply of power and water to the continuous miner, haulage system, and ventilation systems, includes cable/hose handling module for winding or unwinding cables/hoses connected to the miner, an operator control module, and a hydraulic power and air compressor module for supplying air to the miner. An operator controlled host computer housed in the operator control module is connected to the slave computer via a two wire communications line.

Specification for Teaching Machines and Programmes (Interchangeability of Programmes). Part 1, Linear Machines and Programmes.

ERIC Educational Resources Information Center

British Standards Institution, London (England).

To promote interchangeability of teaching machines and programs, so that the user is not so limited in his choice of programs, the British Standards Institute has offered a standard. Part I of the standard deals with linear teaching machines and programs that make use of the roll or sheet methods of presentation. Requirements cover: spools,…

Economic baselines for current underground coal mining technology

NASA Technical Reports Server (NTRS)

Mabe, W. B.

1979-01-01

The cost of mining coal using a room pillar mining method with continuous miner and a longwall mining system was calculated. Costs were calculated for the years 1975 and 2000 time periods and are to be used as economic standards against which advanced mining concepts and systems will be compared. Some assumptions were changed and some internal model stored data was altered from the original calculations procedure chosen, to obtain a result that more closely represented what was considered to be a standard mine. Coal seam thicknesses were varied from one and one-half feet to eight feet to obtain the cost of mining coal over a wide range. Geologic conditions were selected that had a minimum impact on the mining productivity.

KSC-2012-3092

NASA Image and Video Library

2012-05-26

CAPE CANAVERAL, Fla. – Teams taking part in NASA's Lunabotics Mining Competition were eligible for unique trophies such as this. The competition challenged university students to build machines that could collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dug soil that simulated lunar material. The event was judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Jim Grossmann

KSC-2012-3072

NASA Image and Video Library

2012-05-22

CAPE CANAVERAL, Fla. – Participants watch NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

Open Research Challenges with Big Data - A Data-Scientist s Perspective

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

Sukumar, Sreenivas R

In this paper, we discuss data-driven discovery challenges of the Big Data era. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny and evaluation for gleaning insights from the data than ever before. In that context, we pose and debate the question - Are data mining algorithms scaling with the ability to store and compute? If yes, how? If not, why not? We survey recent developments in the state-of-the-art to discuss emergingmore » and outstanding challenges in the design and implementation of machine learning algorithms at scale. We leverage experience from real-world Big Data knowledge discovery projects across domains of national security, healthcare and manufacturing to suggest our efforts be focused along the following axes: (i) the data science challenge - designing scalable and flexible computational architectures for machine learning (beyond just data-retrieval); (ii) the science of data challenge the ability to understand characteristics of data before applying machine learning algorithms and tools; and (iii) the scalable predictive functions challenge the ability to construct, learn and infer with increasing sample size, dimensionality, and categories of labels. We conclude with a discussion of opportunities and directions for future research.« less

Research on the factors influencing the price of commercial housing based on support vector machine (SVM)

NASA Astrophysics Data System (ADS)

Xiaoyang, Zhong; Hong, Ren; Jingxin, Gao

2018-03-01

With the gradual maturity of the real estate market in China, urban housing prices are also better able to reflect changes in market demand and the commodity property of commercial housing has become more and more obvious. Many scholars in our country have made a lot of research on the factors that affect the price of commercial housing in the city and the number of related research papers increased rapidly. These scholars’ research results provide valuable wealth to solve the problem of urban housing price changes in our country. However, due to the huge amount of literature, the vast amount of information is submerged in the library and cannot be fully utilized. Text mining technology has been widely concerned and developed in the field of Humanities and Social Sciences in recent years. But through the text mining technology to obtain the influence factors on the price of urban commercial housing is still relatively rare. In this paper, the research results of the existing scholars were excavated by text mining algorithm based on support vector machine in order to further make full use of the current research results and to provide a reference for stabilizing housing prices.

Comparative Characterization of Crofelemer Samples Using Data Mining and Machine Learning Approaches With Analytical Stability Data Sets.

PubMed

Nariya, Maulik K; Kim, Jae Hyun; Xiong, Jian; Kleindl, Peter A; Hewarathna, Asha; Fisher, Adam C; Joshi, Sangeeta B; Schöneich, Christian; Forrest, M Laird; Middaugh, C Russell; Volkin, David B; Deeds, Eric J

2017-11-01

There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example, products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cutoffs combined with incubation for different times at different temperatures. The 2 preceding articles describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples. In this work, we use data mining techniques such as principal component analysis and mutual information scores to help visualize the data and determine discriminatory regions within these large data sets. The mutual information score identifies chemical signatures that differentiate crofelemer samples. These signatures, in many cases, would likely be missed by traditional data analysis tools. We also found that supervised learning classifiers robustly discriminate samples with around 99% classification accuracy, indicating that mathematical models of these physicochemical data sets are capable of identifying even subtle differences in crofelemer samples. Data mining and machine learning techniques can thus identify fingerprint-type attributes of complex mixture drugs that may be used for comparative characterization of products. Copyright © 2017 American Pharmacists Association®. All rights reserved.

30 CFR 75.830 - Splicing and repair of trailing cables.

Code of Federal Regulations, 2011 CFR

2011-07-01

... high-voltage trailing cable within 35 feet of the continuous mining machine is prohibited. (2) Only four (4) splices will be allowed at any one time for the portion of the trailing cable that extends...

30 CFR 75.830 - Splicing and repair of trailing cables.

Code of Federal Regulations, 2013 CFR

2013-07-01

... high-voltage trailing cable within 35 feet of the continuous mining machine is prohibited. (2) Only four (4) splices will be allowed at any one time for the portion of the trailing cable that extends...

Mining machine with adjustable jib

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

Hart, D.

1987-05-26

A mining machine is described having a pair of crawler tracks, a means for individually driving each of the crawler tracks, a frame mounted on the crawler tracks, an elongated jib carrying a sprocket at each end, an endless cutting chain supported on the sprockets, cutters and loading flights mounted on the endless cutting chain, and means on the frame supporting the elongated jib. The means support the elongated jib consisting of a bridge on the frame, at least one scissors linkage pivotally mounted on the bridge, and arm having a first end attached to the scissors linkage, a frontmore » plate mounted on the second end of the arm and means adjustably mounting the elongated jib on the front plate. The means adjustably mount the elongated jib on the front plate including a first means for rotating the elongated jib between a vertical position and a horizontal position.« less

In-line drivetrain and four wheel drive work machine using same

DOEpatents

Hoff, Brian

2008-08-05

A four wheel drive articulated mine loader is powered by a fuel cell and propelled by a single electric motor. The drivetrain has the first axle, second axle, and motor arranged in series on the work machine chassis. Torque is carried from the electric motor to the back differential via a pinion meshed with the ring gear of the back differential. A second pinion oriented in an opposite direction away from the ring gear is coupled to a drive shaft to transfer torque from the ring gear to the differential of the front axle. Thus, the ring gear of the back differential acts both to receive torque from the motor and to transfer torque to the forward axle. The in-line drive configuration includes a single electric motor and a single reduction gear to power the four wheel drive mine loader.

Algorithm of probabilistic assessment of fully-mechanized longwall downtime

NASA Astrophysics Data System (ADS)

Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.

2017-09-01

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.

Examining the relation between rock mass cuttability index and rock drilling properties

NASA Astrophysics Data System (ADS)

Yetkin, Mustafa E.; Özfırat, M. Kemal; Yenice, Hayati; Şimşir, Ferhan; Kahraman, Bayram

2016-12-01

Drilling rate is a substantial index value in drilling and excavation operations at mining. It is not only a help in determining physical and mechanical features of rocks, but also delivers strong estimations about instantaneous cutting rates. By this way, work durations to be finished on time, proper machine/equipment selection and efficient excavation works can be achieved. In this study, physical and mechanical properties of surrounding rocks and ore zones are determined by investigations carried out on specimens taken from an underground ore mine. Later, relationships among rock mass classifications, drillability rates, cuttability, and abrasivity have been investigated using multi regression analysis. As a result, equations having high regression rates have been found out among instantaneous cutting rates and geomechanical properties of rocks. Moreover, excavation machine selection for the study area has been made at the best possible interval.

78 FR 35974 - Proposed Information Collection; Comment Request; Coal Mine Rescue Teams; Arrangements for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-14

... Request; Coal Mine Rescue Teams; Arrangements for Emergency Medical Assistance and Transportation for... Part 49, Mine Rescue Teams, Subpart B--Mine Rescue Teams for Underground Coal Mines, sets standards related to the availability of mine rescue teams; alternate mine rescue capability for small and remote...

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 13: Laser Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 3: Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Coal face measurement system for underground use

NASA Technical Reports Server (NTRS)

1981-01-01

A measurement system was developed for the Eickhoff longwall shearer to determine the contour of the coal face as it mines coal. Contour data are obtained by an indirect measurement technique based on evaluating the motion of the shearer during mining. Starting from a known location, points along the coal face are established through a knowledge of the machines' positions and yaw movements as it moves past the coal face. The hardware and system operation procedures are described. The tests of system performance and their results are reported.

20 CFR 718.203 - Establishing relationship of pneumoconiosis to coal mine employment.

Code of Federal Regulations, 2010 CFR

2010-04-01

... to coal mine employment. 718.203 Section 718.203 Employees' Benefits EMPLOYMENT STANDARDS ADMINISTRATION, DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED STANDARDS FOR DETERMINING COAL MINERS' TOTAL DISABILITY OR DEATH DUE TO PNEUMOCONIOSIS Determining Entitlement to Benefits...

78 FR 64538 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; Safety...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-29

... for OMB Review; Comment Request; Safety Standards for Underground Coal Mine Ventilation--Belt Entry... the Mine Safety and Health Administration (MSHA) sponsored information collection request (ICR) titled, ``Safety Standards for Underground Coal Mine Ventilation--Belt Entry Used as an Intake Air Course to...

76 FR 69764 - Petitions for Modification of Application of Existing Mandatory Safety Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-09

... DEPARTMENT OF LABOR Mine Safety and Health Administration Petitions for Modification of Application of Existing Mandatory Safety Standards AGENCY: Mine Safety and Health Administration, Labor. ACTION: Notice. SUMMARY: Section 101(c) of the Federal Mine Safety and Health Act of 1977 and 30 CFR part...

30 CFR 57.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... The purpose of these standards is the protection of life, the promotion of health and safety, and the... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES General § 57.1 Purpose and scope...

30 CFR 56.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... standards is the protection of life, the promotion of health and safety, and the prevention of accidents. ... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES General § 56.1 Purpose and scope...

Ringo: Interactive Graph Analytics on Big-Memory Machines

PubMed Central

Perez, Yonathan; Sosič, Rok; Banerjee, Arijit; Puttagunta, Rohan; Raison, Martin; Shah, Pararth; Leskovec, Jure

2016-01-01

We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads. PMID:27081215

Ringo: Interactive Graph Analytics on Big-Memory Machines.

PubMed

Perez, Yonathan; Sosič, Rok; Banerjee, Arijit; Puttagunta, Rohan; Raison, Martin; Shah, Pararth; Leskovec, Jure

2015-01-01

We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges between the objects denoting interactions (friendships, physical interactions, links). Mining graphs provides valuable insights about individual objects as well as the relationships among them. In building Ringo, we take advantage of the fact that machines with large memory and many cores are widely available and also relatively affordable. This allows us to build an easy-to-use interactive high-performance graph analytics system. Graphs also need to be built from input data, which often resides in the form of relational tables. Thus, Ringo provides rich functionality for manipulating raw input data tables into various kinds of graphs. Furthermore, Ringo also provides over 200 graph analytics functions that can then be applied to constructed graphs. We show that a single big-memory machine provides a very attractive platform for performing analytics on all but the largest graphs as it offers excellent performance and ease of use as compared to alternative approaches. With Ringo, we also demonstrate how to integrate graph analytics with an iterative process of trial-and-error data exploration and rapid experimentation, common in data mining workloads.

Recent advances in environmental data mining

NASA Astrophysics Data System (ADS)

Leuenberger, Michael; Kanevski, Mikhail

2016-04-01

Due to the large amount and complexity of data available nowadays in geo- and environmental sciences, we face the need to develop and incorporate more robust and efficient methods for their analysis, modelling and visualization. An important part of these developments deals with an elaboration and application of a contemporary and coherent methodology following the process from data collection to the justification and communication of the results. Recent fundamental progress in machine learning (ML) can considerably contribute to the development of the emerging field - environmental data science. The present research highlights and investigates the different issues that can occur when dealing with environmental data mining using cutting-edge machine learning algorithms. In particular, the main attention is paid to the description of the self-consistent methodology and two efficient algorithms - Random Forest (RF, Breiman, 2001) and Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. Despite the fact that they are based on two different concepts, i.e. decision trees vs artificial neural networks, they both propose promising results for complex, high dimensional and non-linear data modelling. In addition, the study discusses several important issues of data driven modelling, including feature selection and uncertainties. The approach considered is accompanied by simulated and real data case studies from renewable resources assessment and natural hazards tasks. In conclusion, the current challenges and future developments in statistical environmental data learning are discussed. References - Breiman, L., 2001. Random Forests. Machine Learning 45 (1), 5-32. - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

Seminal quality prediction using data mining methods.

PubMed

Sahoo, Anoop J; Kumar, Yugal

2014-01-01

Now-a-days, some new classes of diseases have come into existences which are known as lifestyle diseases. The main reasons behind these diseases are changes in the lifestyle of people such as alcohol drinking, smoking, food habits etc. After going through the various lifestyle diseases, it has been found that the fertility rates (sperm quantity) in men has considerably been decreasing in last two decades. Lifestyle factors as well as environmental factors are mainly responsible for the change in the semen quality. The objective of this paper is to identify the lifestyle and environmental features that affects the seminal quality and also fertility rate in man using data mining methods. The five artificial intelligence techniques such as Multilayer perceptron (MLP), Decision Tree (DT), Navie Bayes (Kernel), Support vector machine+Particle swarm optimization (SVM+PSO) and Support vector machine (SVM) have been applied on fertility dataset to evaluate the seminal quality and also to predict the person is either normal or having altered fertility rate. While the eight feature selection techniques such as support vector machine (SVM), neural network (NN), evolutionary logistic regression (LR), support vector machine plus particle swarm optimization (SVM+PSO), principle component analysis (PCA), chi-square test, correlation and T-test methods have been used to identify more relevant features which affect the seminal quality. These techniques are applied on fertility dataset which contains 100 instances with nine attribute with two classes. The experimental result shows that SVM+PSO provides higher accuracy and area under curve (AUC) rate (94% & 0.932) among multi-layer perceptron (MLP) (92% & 0.728), Support Vector Machines (91% & 0.758), Navie Bayes (Kernel) (89% & 0.850) and Decision Tree (89% & 0.735) for some of the seminal parameters. This paper also focuses on the feature selection process i.e. how to select the features which are more important for prediction of fertility rate. In this paper, eight feature selection methods are applied on fertility dataset to find out a set of good features. The investigational results shows that childish diseases (0.079) and high fever features (0.057) has less impact on fertility rate while age (0.8685), season (0.843), surgical intervention (0.7683), alcohol consumption (0.5992), smoking habit (0.575), number of hours spent on setting (0.4366) and accident (0.5973) features have more impact. It is also observed that feature selection methods increase the accuracy of above mentioned techniques (multilayer perceptron 92%, support vector machine 91%, SVM+PSO 94%, Navie Bayes (Kernel) 89% and decision tree 89%) as compared to without feature selection methods (multilayer perceptron 86%, support vector machine 86%, SVM+PSO 85%, Navie Bayes (Kernel) 83% and decision tree 84%) which shows the applicability of feature selection methods in prediction. This paper lightens the application of artificial techniques in medical domain. From this paper, it can be concluded that data mining methods can be used to predict a person with or without disease based on environmental and lifestyle parameters/features rather than undergoing various medical test. In this paper, five data mining techniques are used to predict the fertility rate and among which SVM+PSO provide more accurate results than support vector machine and decision tree.

Hydrogeochemical Investigation of the Standard Mine Vicinity, Upper Elk Creek Basin, Colorado

USGS Publications Warehouse

Manning, Andrew H.; Verplanck, Philip L.; Mast, M. Alisa; Wanty, Richard B.

2008-01-01

Ground- and surface-water samples were collected in the vicinity of the Standard Mine in west-central Colorado in order to characterize the local ground-water flow system, determine metal concentrations in local ground water, and better understand factors controlling the discharge of metal-rich waters from the mine. The sampling program included a one-time sampling of springs, mine adits, and exploration pits in Elk Basin and Redwell Basin; repeated sampling throughout one year of Standard Mine Level 1 discharge and Elk Creek near its confluence with Coal Creek; and a one-time sampling of underground sites in Levels 3 and 5 of the Standard Mine. Samples were analyzed for major ions and trace elements, stable isotopes of hydrogen (2H/1H) and oxygen (18O/16O), strontium isotopes, and tritium and dissolved noble gases (including helium isotopes) for tritium/helium-3 age dating. No clear correlations were observed between natural ground-water discharge locations and map-scale faults and lithology. Surface observations and the location of ground-water discharge suggest that simple topography, rather than large-scale geologic features, primarily controls the occurrence and flow of shallow ground water in Elk Basin. Discrete inflows from cross faults or other features were not observed in Levels 3 and 5 of the Standard Mine. Instead, water entered the mine as relatively persistent dripping from gouge and breccia within the Standard fault, which both tunnels follow. Therefore, the Standard fault itself is probably the main pathway of ground-water flow from the shallow subsurface to the mine workings. Low pH (as low as 3.2) and elevated concentrations of zinc, lead, cadmium, copper, and manganese (commonly exceeding water-quality standards for Elk Creek) were measured in samples located within or immediately downgradient of areas where sulfides are abundant, including the Standard fault, the Elk Lode portal, and the breccia pipe in Redwell Basin. Concentrations of these metals were typically low and pH values were circumneutral at surrounding locations. Metal concentrations in samples collected from underground workings in the Standard Mine were also generally higher than in samples collected at aboveground sites located outside of sulfide-rich areas. Metal concentrations in discharge from the Level 1 tunnel were among the highest measured in Elk Basin. All of these observations suggest that sulfide-rich mineralized rock is the primary control on dissolved metal concentrations and pH in ground water in the Standard Mine vicinity. Waste-rock piles apparently exert another major control on metal concentrations and pH; the lowest pH and highest metal concentrations typically are found in discharge from waste-rock piles. Concentrations of several chemical constituents along with strontium isotope data indicate that none of the sampled waters could have been the primary source of metals in discharge from Level 1. Therefore, this study did not identify the primary source location for metals in Level 1 discharge. Possible sources must be located below Levels 3 and 5 or farther back into the mountainside than the ends of Levels 3 and 5. Apparent tritium/helium-3 ground-water ages ranged from 0 to 9 yr, and a considerable majority were <1 yr. Tritium data and computed initial tritium values (measured tritium plus measured tritiogenic helium-3) suggest that much of the ground water in the Standard Mine vicinity was weeks to months old rather than years old. Tritium, d2H, and d18O data from water entering into and discharging from the Standard Mine displayed spatial and temporal patterns indicating that these tracers were influenced by seasonal variations in their concentration in precipitation. The tracer data therefore suggest that ground water entering into and discharging from the Standard Mine was largely composed of water <1 yr old. Pronounced seasonal variations in geochemistry in Level 1 discharge also are consistent with short r

Gravimetric surveys for assessing rock mass condition around a mine shaft

NASA Astrophysics Data System (ADS)

Madej, Janusz

2017-06-01

The fundamentals of use of vertical gravimetric surveying method in mine shafts are presented in the paper. The methods of gravimetric measurements and calculation of interval and complex density are discussed in detail. The density calculations are based on an original method accounting for the gravity influence of the mine shaft thus guaranteeing closeness of calculated and real values of density of rocks beyond the shaft lining. The results of many gravimetric surveys performed in shafts are presented and interpreted. As a result, information about the location of heterogeneous zones of work beyond the shaft lining is obtained. In many cases, these zones used to threaten the safe operation of machines and utilities in the shaft.

30 CFR 75.1908 - Nonpermissible diesel-powered equipment; categories.

Code of Federal Regulations, 2013 CFR

2013-07-01

... the mine fire fighting and evacuation plan under § 75.1502. [61 FR 55527, Oct. 25, 1996; 70 FR 36347... such machine or device, which job site is occupied by a miner. (d) Diesel-powered ambulances and fire...

CESAR research in intelligent machines

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

Weisbin, C.R.

1986-01-01

The Center for Engineering Systems Advanced Research (CESAR) was established in 1983 as a national center for multidisciplinary, long-range research and development in machine intelligence and advanced control theory for energy-related applications. Intelligent machines of interest here are artificially created operational systems that are capable of autonomous decision making and action. The initial emphasis for research is remote operations, with specific application to dexterous manipulation in unstructured dangerous environments where explosives, toxic chemicals, or radioactivity may be present, or in other environments with significant risk such as coal mining or oceanographic missions. Potential benefits include reduced risk to man inmore » hazardous situations, machine replication of scarce expertise, minimization of human error due to fear or fatigue, and enhanced capability using high resolution sensors and powerful computers. A CESAR goal is to explore the interface between the advanced teleoperation capability of today, and the autonomous machines of the future.« less

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

Ken L. Stratton

The objective of this project is to investigate the applicability of a combined Global Positioning System and Inertial Measurement Unit (GPS/IMU) for information based displays on earthmoving machines and for automated earthmoving machines in the future. This technology has the potential of allowing an information-based product like Caterpillar's Computer Aided Earthmoving System (CAES) to operate in areas with satellite shading. Satellite shading is an issue in open pit mining because machines are routinely required to operate close to high walls, which reduces significantly the amount of the visible sky to the GPS antenna mounted on the machine. An inertial measurementmore » unit is a product, which provides data for the calculation of position based on sensing accelerations and rotation rates of the machine's rigid body. When this information is coupled with GPS it results in a positioning system that can maintain positioning capability during time periods of shading.« less

30 CFR 75.389 - Mining into inaccessible areas.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining into inaccessible areas. 75.389 Section 75.389 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.389 Mining into...

30 CFR 75.389 - Mining into inaccessible areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Mining into inaccessible areas. 75.389 Section 75.389 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.389 Mining into...

30 CFR 816.42 - Hydrologic balance: Water quality standards and effluent limitations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Hydrologic balance: Water quality standards and effluent limitations. 816.42 Section 816.42 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND... STANDARDS-SURFACE MINING ACTIVITIES § 816.42 Hydrologic balance: Water quality standards and effluent...

30 CFR 817.42 - Hydrologic balance: Water quality standards and effluent limitations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Hydrologic balance: Water quality standards and effluent limitations. 817.42 Section 817.42 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND... STANDARDS-UNDERGROUND MINING ACTIVITIES § 817.42 Hydrologic balance: Water quality standards and effluent...

30 CFR 817.42 - Hydrologic balance: Water quality standards and effluent limitations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Hydrologic balance: Water quality standards and effluent limitations. 817.42 Section 817.42 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND... STANDARDS-UNDERGROUND MINING ACTIVITIES § 817.42 Hydrologic balance: Water quality standards and effluent...

30 CFR 816.42 - Hydrologic balance: Water quality standards and effluent limitations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Hydrologic balance: Water quality standards and effluent limitations. 816.42 Section 816.42 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND... STANDARDS-SURFACE MINING ACTIVITIES § 816.42 Hydrologic balance: Water quality standards and effluent...

KSC-2012-3069

NASA Image and Video Library

2012-05-22

CAPE CANAVERAL, Fla. – A robotic vehicle takes part in NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3075

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors prepares for a turn in NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3077

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors prepares for a turn in NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3074

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A team of competitors waits for a turn in NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3078

NASA Image and Video Library

2012-05-25

CAPE CANAVERAL, Fla. – A videogame simulates driving excavators during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

KSC-2012-3071

NASA Image and Video Library

2012-05-22

CAPE CANAVERAL, Fla. – A robotic mascot moves among participants during NASA's Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. The competition challenges university students to build machines that can collect soil such as the material found on the moon. Working inside the Caterpillar LunArena, the robotic craft dig soil that simulates lunar material. The event is judged by a machine's abilities to collect the soil, its design and operation, size, dust tolerance and its level of autonomy. Photo credit: NASA/Glenn Benson

30 CFR Appendix I to Subpart C of... - National Consensus Standards

Code of Federal Regulations, 2010 CFR

2010-07-01

... Subpart C of Part 57 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Fire Prevention and Control Pt. 57, Subpt. C., App. I Appendix I to Subpart C of Part 57—National...

30 CFR 20.0 - Compliance with the requirements necessary for obtaining approval.

Code of Federal Regulations, 2011 CFR

2011-07-01

... LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.0 Compliance with the requirements necessary for obtaining approval. To receive approval of MSHA for any electric mine lamps other than standard cap lamps a manufacturer must comply with the...

30 CFR 20.0 - Compliance with the requirements necessary for obtaining approval.

Code of Federal Regulations, 2013 CFR

2013-07-01

... LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.0 Compliance with the requirements necessary for obtaining approval. To receive approval of MSHA for any electric mine lamps other than standard cap lamps a manufacturer must comply with the...

30 CFR 20.0 - Compliance with the requirements necessary for obtaining approval.

Code of Federal Regulations, 2012 CFR

2012-07-01

... LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.0 Compliance with the requirements necessary for obtaining approval. To receive approval of MSHA for any electric mine lamps other than standard cap lamps a manufacturer must comply with the...

30 CFR 20.0 - Compliance with the requirements necessary for obtaining approval.

Code of Federal Regulations, 2014 CFR

2014-07-01

... LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.0 Compliance with the requirements necessary for obtaining approval. To receive approval of MSHA for any electric mine lamps other than standard cap lamps a manufacturer must comply with the...

Collaborative Data Mining

NASA Astrophysics Data System (ADS)

Moyle, Steve

Collaborative Data Mining is a setting where the Data Mining effort is distributed to multiple collaborating agents - human or software. The objective of the collaborative Data Mining effort is to produce solutions to the tackled Data Mining problem which are considered better by some metric, with respect to those solutions that would have been achieved by individual, non-collaborating agents. The solutions require evaluation, comparison, and approaches for combination. Collaboration requires communication, and implies some form of community. The human form of collaboration is a social task. Organizing communities in an effective manner is non-trivial and often requires well defined roles and processes. Data Mining, too, benefits from a standard process. This chapter explores the standard Data Mining process CRISP-DM utilized in a collaborative setting.

30 CFR 77.1000-1 - Filing of plan.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Ground..., with the MSHA Coal Mine Safety and Health district office for the district in which the mine is located...

30 CFR 77.1708 - Safety program; instruction of persons employed at the mine.

Code of Federal Regulations, 2010 CFR

2010-07-01

... at the mine. 77.1708 Section 77.1708 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Miscellaneous § 77.1708 Safety program; instruction of persons...

Geochemistry of Standard Mine Waters, Gunnison County, Colorado, July 2009

USGS Publications Warehouse

Verplanck, Philip L.; Manning, Andrew H.; Graves, Jeffrey T.; McCleskey, R. Blaine; Todorov, Todor I.; Lamothe, Paul J.

2009-01-01

In many hard-rock-mining districts water flowing from abandoned mine adits is a primary source of metals to receiving streams. Understanding the generation of adit discharge is an important step in developing remediation plans. In 2006, the U.S. Environmental Protection Agency listed the Standard Mine in the Elk Creek drainage basin near Crested Butte, Colorado as a superfund site because drainage from the Standard Mine enters Elk Creek, contributing dissolved and suspended loads of zinc, cadmium, copper, and other metals to the stream. Elk Creek flows into Coal Creek, which is a source of drinking water for the town of Crested Butte. In 2006 and 2007, the U.S. Geological Survey undertook a hydrogeologic investigation of the Standard Mine and vicinity and identified areas of the underground workings for additional work. Mine drainage, underground-water samples, and selected spring water samples were collected in July 2009 for analysis of inorganic solutes as part of a follow-up study. Water analyses are reported for mine-effluent samples from Levels 1 and 5 of the Standard Mine, underground samples from Levels 2 and 3 of the Standard Mine, two spring samples, and an Elk Creek sample. Reported analyses include field measurements (pH, specific conductance, water temperature, dissolved oxygen, and redox potential), major constituents and trace elements, and oxygen and hydrogen isotopic determinations. Overall, water samples collected in 2009 at the same sites as were collected in 2006 have similar chemical compositions. Similar to 2006, water in Level 3 did not flow out the portal but was observed to flow into open workings to lower parts of the mine. Many dissolved constituent concentrations, including calcium, magnesium, sulfate, manganese, zinc, and cadmium, in Level 3 waters substantially are lower than in Level 1 effluent. Concentrations of these dissolved constituents in water samples collected from Level 2 approach or exceed concentrations of Level 1 effluent suggesting that water-rock interaction between Levels 3 and 1 can account for the elevated concentration of metals and other constituents in Level 1 portal effluent. Ore minerals (sphalerite, argentiferous galena, and chalcopyrite) are the likely sources of zinc, cadmium, lead, and copper and are present within the mine in unmined portions of the vein system, within plugged ore chutes, and in muck piles.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

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

30 CFR 75.1719-4 - Mining machines, cap lamps; requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... or reflecting tape shall have an area of not less than 10 square inches. (c) Each person who goes... of 6 square inches of reflecting tape or equivalent paint or material on each side and back. [41 FR...

30 CFR 75.1719-4 - Mining machines, cap lamps; requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... or reflecting tape shall have an area of not less than 10 square inches. (c) Each person who goes... of 6 square inches of reflecting tape or equivalent paint or material on each side and back. [41 FR...

30 CFR 75.1719-4 - Mining machines, cap lamps; requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... or reflecting tape shall have an area of not less than 10 square inches. (c) Each person who goes... of 6 square inches of reflecting tape or equivalent paint or material on each side and back. [41 FR...

Methods and costs of thin-seam mining. Final report, 25 September 1977-24 January 1979. [Thin seam in association with a thick seam

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

Finch, T.E.; Fidler, E.L.

1981-02-01

This report defines the state of the art (circa 1978) in removing thin coal seams associated with vastly thicker seams found in the surface coal mines of the western United States. New techniques are evaluated and an innovative method and machine is proposed. Western states resource recovery regulations are addressed and representative mining operations are examined. Thin seam recovery is investigated through its effect on (1) overburden removal, (2) conventional seam extraction methods, and (3) innovative techniques. Equations and graphs are used to accommodate the variable stratigraphic positions in the mining sequence on which thin seams occur. Industrial concern andmore » agency regulations provided the impetus for this study of total resource recovery. The results are a compendium of thin seam removal methods and costs. The work explains how the mining industry recovers thin coal seams in western surface mines where extremely thick seams naturally hold the most attention. It explains what new developments imply and where to look for new improvements and their probable adaptability.« less

Application of data mining approaches to drug delivery.

PubMed

Ekins, Sean; Shimada, Jun; Chang, Cheng

2006-11-30

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.

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

PubMed

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

2012-08-01

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

41 CFR 50-204.36 - Radiation standards for mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Radiation standards for mining. 50-204.36 Section 50-204.36 Public Contracts and Property Management Other Provisions Relating to Public Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Radiation Standards § 50...

41 CFR 50-204.36 - Radiation standards for mining.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 41 Public Contracts and Property Management 1 2012-07-01 2009-07-01 true Radiation standards for mining. 50-204.36 Section 50-204.36 Public Contracts and Property Management Other Provisions Relating to Public Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Radiation Standards § 50...

41 CFR 50-204.36 - Radiation standards for mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 41 Public Contracts and Property Management 1 2011-07-01 2009-07-01 true Radiation standards for mining. 50-204.36 Section 50-204.36 Public Contracts and Property Management Other Provisions Relating to Public Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 204-SAFETY AND HEALTH STANDARDS FOR FEDERAL SUPPLY CONTRACTS Radiation Standards § 50...

jCompoundMapper: An open source Java library and command-line tool for chemical fingerprints

PubMed Central

2011-01-01

Background The decomposition of a chemical graph is a convenient approach to encode information of the corresponding organic compound. While several commercial toolkits exist to encode molecules as so-called fingerprints, only a few open source implementations are available. The aim of this work is to introduce a library for exactly defined molecular decompositions, with a strong focus on the application of these features in machine learning and data mining. It provides several options such as search depth, distance cut-offs, atom- and pharmacophore typing. Furthermore, it provides the functionality to combine, to compare, or to export the fingerprints into several formats. Results We provide a Java 1.6 library for the decomposition of chemical graphs based on the open source Chemistry Development Kit toolkit. We reimplemented popular fingerprinting algorithms such as depth-first search fingerprints, extended connectivity fingerprints, autocorrelation fingerprints (e.g. CATS2D), radial fingerprints (e.g. Molprint2D), geometrical Molprint, atom pairs, and pharmacophore fingerprints. We also implemented custom fingerprints such as the all-shortest path fingerprint that only includes the subset of shortest paths from the full set of paths of the depth-first search fingerprint. As an application of jCompoundMapper, we provide a command-line executable binary. We measured the conversion speed and number of features for each encoding and described the composition of the features in detail. The quality of the encodings was tested using the default parametrizations in combination with a support vector machine on the Sutherland QSAR data sets. Additionally, we benchmarked the fingerprint encodings on the large-scale Ames toxicity benchmark using a large-scale linear support vector machine. The results were promising and could often compete with literature results. On the large Ames benchmark, for example, we obtained an AUC ROC performance of 0.87 with a reimplementation of the extended connectivity fingerprint. This result is comparable to the performance achieved by a non-linear support vector machine using state-of-the-art descriptors. On the Sutherland QSAR data set, the best fingerprint encodings showed a comparable or better performance on 5 of the 8 benchmarks when compared against the results of the best descriptors published in the paper of Sutherland et al. Conclusions jCompoundMapper is a library for chemical graph fingerprints with several tweaking possibilities and exporting options for open source data mining toolkits. The quality of the data mining results, the conversion speed, the LPGL software license, the command-line interface, and the exporters should be useful for many applications in cheminformatics like benchmarks against literature methods, comparison of data mining algorithms, similarity searching, and similarity-based data mining. PMID:21219648

30 CFR 75.1907 - Diesel-powered equipment intended for use in underground coal mines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... underground coal mines. 75.1907 Section 75.1907 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1907 Diesel-powered equipment intended for use in underground coal mines. (a) As of...

30 CFR 75.1907 - Diesel-powered equipment intended for use in underground coal mines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... underground coal mines. 75.1907 Section 75.1907 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1907 Diesel-powered equipment intended for use in underground coal mines. (a) As of...

30 CFR 72.800 - Single, full-shift measurement of respirable coal mine dust.

Code of Federal Regulations, 2014 CFR

2014-07-01

... coal mine dust. 72.800 Section 72.800 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH HEALTH STANDARDS FOR COAL MINES Miscellaneous § 72.800 Single, full-shift measurement of respirable coal mine dust. The Secretary will use a single, full-shift...

30 CFR 75.1907 - Diesel-powered equipment intended for use in underground coal mines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... underground coal mines. 75.1907 Section 75.1907 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1907 Diesel-powered equipment intended for use in underground coal mines. (a) As of...

30 CFR 75.1907 - Diesel-powered equipment intended for use in underground coal mines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... underground coal mines. 75.1907 Section 75.1907 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1907 Diesel-powered equipment intended for use in underground coal mines. (a) As of...

30 CFR 77.1200 - Mine map.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Maps § 77.1200 Mine... elevation of any body of water dammed or held back in any portion of the mine: Provided, however, Such bodies of water may be shown on overlays or tracings attached to the mine maps; (g) All prospect drill...

75 FR 28227 - National Emission Standards for Hazardous Air Pollutants: Gold Mine Ore Processing and Production...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-20

... published a proposed rule for mercury emissions from the gold mine ore processing and production area source... proposed rule (75 FR 22470). Several parties requested that EPA extend the comment period. EPA has granted...-AP48 National Emission Standards for Hazardous Air Pollutants: Gold Mine Ore Processing and Production...

78 FR 58567 - Criteria to Certify Coal Mine Rescue Teams

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-24

... to Certify Coal Mine Rescue Teams AGENCY: Mine Safety and Health Administration, Labor. ACTION...) is requesting comments on revised instruction guides for coal mine rescue team training. MSHA prescribes training materials through the issuance of instruction guides. Existing standards for coal mine...

General geology and mines of the East Tintic mining district, Utah and Juab counties, Utah, with sections on the geology of the Burgin mine and the geology of the Trixie mine

USGS Publications Warehouse

Morris, H.T.; Lovering, Thomas Seward; Mogensen, A.P.; Shepard, W.M.; Perry, L.I.; Smith, S.M.

1979-01-01

This report is a study of the rocks, geologic structures, and mines of a highly productive silver, gold, and base-metal mining district in the east-central Great Basin. The East Tintic mining district is in the east-central part of the East Tintic Mountains, near the east margin of the Basin and Range province in Utah and Juab Counties, Utah. The district occupies the northeastern part of the Eureka quadrangle and is about 5 mi (8 km) wide and 6 mi (9.7 km) long. Officially it is within the designated boundaries of the Tintic mining district, but it generally though erroneously has been regarded as a separate district since the late 1800's.Prospecting was first undertaken in East Tintic in 1870; although small quantities of ore were produced in 1899 and from 1909 to 1913, the district first achieved prominence in 1916 with the discovery of the totally concealed Central ore body of the Tintic Standard mine. Within a few years of this discovery, the Tintic Standard became one of the most productive silver mines in the world. Additional discoveries of important concealed ore deposits have continued to be made in the district, including the North Lily mine in 1927, the Eureka Lilly and Eureka Standard mines in 1928, the Burgin mine in 1958, and the Trixie mine in 1969.To December 31, 1975, the East Tintic mining district has yielded approximately 4.83 million short tons (4.38 million tonnes) of silver, gold, and base-metal ores, largely from concealed deposits overlain by many hundreds of feet of barren rocks. These ores have a gross valuation of approximately $231 million. The district first achieved prominence in 1916 with the discovery of the ore bodies of the Tintic Standard mine, which for a time was the world's richest silver producer (Lindgren, 1933, p. 588). By 1946 this deposit and a number of other deposits discovered and developed nearby had been exhausted, and the district became dormant. A dramatic revival of, mining activities in the East Tintic district began in 1956 after the discovery and subsequent development of the concealed Burgin ore bodies in an area 1 mile (1.6 km) southeast of the Tintic Standard that previously had been only superficially prospected. As in the earlier history of the district, the Burgin development has led to the discovery of other concealed deposits, focusing international attention on the revitalization of a nearly abandoned mining district by the application of geologic and geochemical techniques.

Survey of Machine Learning Methods for Database Security

NASA Astrophysics Data System (ADS)

Kamra, Ashish; Ber, Elisa

Application of machine learning techniques to database security is an emerging area of research. In this chapter, we present a survey of various approaches that use machine learning/data mining techniques to enhance the traditional security mechanisms of databases. There are two key database security areas in which these techniques have found applications, namely, detection of SQL Injection attacks and anomaly detection for defending against insider threats. Apart from the research prototypes and tools, various third-party commercial products are also available that provide database activity monitoring solutions by profiling database users and applications. We present a survey of such products. We end the chapter with a primer on mechanisms for responding to database anomalies.

Paradox in AI - AI 2.0: The Way to Machine Consciousness

NASA Astrophysics Data System (ADS)

Palensky, Peter; Bruckner, Dietmar; Tmej, Anna; Deutsch, Tobias

Artificial Intelligence, the big promise of the last millennium, has apparently made its way into our daily lives. Cell phones with speech control, evolutionary computing in data mining or power grids, optimized via neural network, show its applicability in industrial environments. The original expectation of true intelligence and thinking machines lies still ahead of us. Researchers are, however, optimistic as never before. This paper tries to compare the views, challenges and approaches of several disciplines: engineering, psychology, neuroscience, philosophy. It gives a short introduction to Psychoanalysis, discusses the term consciousness, social implications of intelligent machines, related theories, and expectations and shall serve as a starting point for first attempts of combining these diverse thoughts.

The Empirical Relationship between Mining Industry Development and Environmental Pollution in China.

PubMed

Li, Gerui; Lei, Yalin; Ge, Jianping; Wu, Sanmang

2017-03-02

This study uses a vector autoregression (VAR) model to analyze changes in pollutants among different mining industries and related policy in China from 2001 to 2014. The results show that: (1) because the pertinence of standards for mining waste water and waste gas emissions are not strong and because the maximum permissible discharge pollutant concentrations in these standards are too high, ammonia nitrogen and industrial sulfur dioxide discharges increased in most mining industries; (2) chemical oxygen demand was taken as an indicator of sewage treatment in environmental protection plans; hence, the chemical oxygen demand discharge decreased in all mining industries; (3) tax reduction policies, which are only implemented in coal mining and washing and extraction of petroleum and natural gas, decreased the industrial solid waste discharge in these two mining industries.

Standard surface grinder for precision machining of thin-wall tubing

NASA Technical Reports Server (NTRS)

Jones, A.; Kotora, J., Jr.; Rein, J.; Smith, S. V.; Strack, D.; Stuckey, D.

1967-01-01

Standard surface grinder performs precision machining of thin-wall stainless steel tubing by electrical discharge grinding. A related adaptation, a traveling wire electrode fixture, is used for machining slots in thin-walled tubing.

Standardized Curriculum for Machine Tool Operation/Machine Shop.

ERIC Educational Resources Information Center

Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.

Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…

An evaluation of the relative safety of U.S. mining explosion-protected equipment approval requirements versus international standards

PubMed Central

Calder, W.; Snyder, D.; Burr, J.F.

2018-01-01

This paper provides a determination of the equivalent level of protection of the international standards relative to similar criteria used by the U.S. Mine Safety and Health Administration (MSHA) to approve two-fault intrinsically safe (IS) stand-alone equipment. U.S. mining law requires such a determination for MSHA to use alternatives to existing standards. The primary issue is to demonstrate that the international standards for equipment evaluation will provide at least the same level of protection for miners as the document currently used by MSHA. PMID:29780219

Human Systems Integration (HSI) Associated Development Activities in Japan

DTIC Science & Technology

2008-06-12

machine learning and data mining methods. The continuous effort ( KAIZEN ) to improve the analysis phases are illustrated in Figure 14. Although there...model Extraction of a workflow Extraction of a control rule Variation analysis and improvement Plant operation KAIZEN Fig. 14

30 CFR 75.404 - Exemption of anthracite mines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Exemption of anthracite mines. 75.404 Section 75.404 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Combustible Materials and Rock Dusting...

30 CFR 75.404 - Exemption of anthracite mines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Exemption of anthracite mines. 75.404 Section 75.404 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Combustible Materials and Rock Dusting...

30 CFR 75.404 - Exemption of anthracite mines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Exemption of anthracite mines. 75.404 Section 75.404 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Combustible Materials and Rock Dusting...

30 CFR 75.404 - Exemption of anthracite mines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Exemption of anthracite mines. 75.404 Section 75.404 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Combustible Materials and Rock Dusting...

30 CFR 75.404 - Exemption of anthracite mines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Exemption of anthracite mines. 75.404 Section 75.404 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Combustible Materials and Rock Dusting...

30 CFR 57.22230 - Weekly testing (II-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 57.22230 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety... following locations: (1) Active mining faces and benches; (2) Main returns; (3) Returns from idle workings...

30 CFR 75.301 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.301 Definitions. In addition to the applicable... operator. The person(s), designated by the mine operator, who is located on the surface of the mine and...

40 CFR 440.54 - New source performance standards (NSPS).

Code of Federal Regulations, 2014 CFR

2014-07-01

... reduction attainable by the applications of the best available demonstrated technology (BADT): (a) The concentration of pollutants discharged in mine drainage from mines obtaining titanium ores from lode deposits...) The concentration of pollutants discharged in mine drainage from mines engaged in the dredge mining of...

30 CFR 75.301 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.301 Definitions. In addition to the applicable... operator. The person(s), designated by the mine operator, who is located on the surface of the mine and...