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...

78 FR 45972 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; High...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-30

... Coal Mines ACTION: Notice. SUMMARY: The Department of Labor (DOL) is submitting the Mine Safety and... Continuous Mining Machines Standards for Underground Coal Mines,'' to the Office of Management and Budget... continuous mining machines (HVCMM) in underground coal mines by requiring records of testing, examination and...

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…

75 FR 20918 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-22

... DEPARTMENT OF LABOR Mine Safety and Health Administration 30 CFR Parts 18 and 75 RIN 1219-AB34 High-Voltage Continuous Mining Machine Standard for Underground Coal Mines Correction In rule document 2010-7309 beginning on page 17529 in the issue of Tuesday, April 6, 2010, make the following correction...

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 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.

Horizontal EDNA miner

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

Justice, J.C.; Delli-Gatti, F.A.

1985-12-03

A mining machine is utilized for making original generally horizontal bores in coal seams, and for enlarging preexisting bores. A single cutting head is mounted for rotation about a first horizontal axis generally perpendicular to the dimension of elongation of the horizontal bore, and is pivotal about a second horizontal axis, parallel to the first axis, to change its cutting, vertical position within the bore. A non-rotatable body member, with side wall supports, is mounted posteriorly of the cutting head, and includes a conveyor mechanism and a power mechanism operatively connected to it. The machine can be sumped into amore » bore and then the cutting head rotated about the second axis to change the vertical position thereof, and then moved rearwardly, any cut material being continuously conveyed to the bore mouth by the conveyor mechanism. The amount of vertical movement during the pivoting action about the second axis is controlled in response to the automatic sensing of the thickness of the coal seam in which the machine operates.« less

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.

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

Molded Concrete Center Mine Wall

NASA Technical Reports Server (NTRS)

Lewis, E. V.

1987-01-01

Proposed semiautomatic system forms concrete-foam wall along middle of coal-mine passage. Wall helps support roof and divides passage into two conduits needed for ventilation of coal face. Mobile mold and concrete-foam generator form sections of wall in place.

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.

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.

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...

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.

New technologies of mining stratal minerals and their computation

NASA Astrophysics Data System (ADS)

Beysembayev, K. M.; Reshetnikova, O. S.; Nokina, Z. N.; Teliman, I. V.; Asmagambet, D. K.

2018-03-01

The paper considers the systems of flat and volumetric modeling of controlling long-wall faces for schemes with rock collapse of the immediate and main roof and smooth lowering of the remaining layers, as well as in forming a vault over the face. Stress distributions are obtained for the reference pressure zone. They are needed for recognizing the active state of the long-wall face in the feedback mode. The project of the system “support - lateral rocks” is represented by a multidimensional network base. Its connections reflect the elements of the system or rocks, workings, supports with nodes and parts. The connections reflect the logic of the operation of machines, assemblies and parts, and the types of their mechanical connections. At the nodes of the base, there are built-in systems of object-oriented programming languages. This allows combining spatial elements of the system into a simple neural network.

30 CFR 56.3130 - Wall, bank, and slope stability.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Wall, bank, and slope stability. 56.3130... Mining Methods § 56.3130 Wall, bank, and slope stability. Mining methods shall be used that will maintain wall, bank, and slope stability in places where persons work or travel in performing their assigned...

Method of lining a vertical mine shaft with concrete

DOEpatents

Eklund, James D.; Halter, Joseph M.; Rasmussen, Donald E.; Sullivan, Robert G.; Moffat, Robert B.

1981-01-01

The apparatus includes a cylindrical retainer form spaced inwardly of the wall of the shaft by the desired thickness of the liner to be poured and having overlapping edges which seal against concrete flow but permit the form to be contracted to a smaller circumference after the liner has hardened and is self-supporting. A curb ring extends downwardly and outwardly toward the shaft wall from the bottom of the retainer form to define the bottom surface of each poured liner section. An inflatable toroid forms a seal between the curb ring and the shaft wall. A form support gripper ring having gripper shoes laterally extendable under hydraulic power to engage the shaft wall supports the retainer form, curb ring and liner until the newly poured liner section becomes self-supporting. Adjusting hydraulic cylinders permit the curb ring and retainer form to be properly aligned relative to the form support gripper ring. After a liner section is self-supporting, an advancing system advances the retainer form, curb ring and form support gripper ring toward a shaft boring machine above which the liner is being formed. The advancing system also provides correct horizontal alignment of the form support gripper ring.

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.

30 CFR 18.38 - Leads through common walls.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Leads through common walls. 18.38 Section 18.38 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 Design...

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.

75 FR 17511 - Coal Mine Dust Sampling Devices

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

... Part III Department of Labor Mine Safety and Health Adminisration 30 CFR Parts 18, 74, and 75 Coal Mine Dust Sampling Devices; High-Voltage Continuous Mining Machine Standard for Underground Coal Mines...-AB61 Coal Mine Dust Sampling Devices AGENCY: Mine Safety and Health Administration, Labor. ACTION...

30 CFR 18.38 - Leads through common walls.

Code of Federal Regulations, 2014 CFR

2014-07-01

... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design... from one explosion-proof enclosure to another through conduit, tubing, piping, or other solid-wall...

30 CFR 18.38 - Leads through common walls.

Code of Federal Regulations, 2013 CFR

2013-07-01

... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design... from one explosion-proof enclosure to another through conduit, tubing, piping, or other solid-wall...

30 CFR 18.38 - Leads through common walls.

Code of Federal Regulations, 2011 CFR

2011-07-01

... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design... from one explosion-proof enclosure to another through conduit, tubing, piping, or other solid-wall...

30 CFR 18.38 - Leads through common walls.

Code of Federal Regulations, 2012 CFR

2012-07-01

... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design... from one explosion-proof enclosure to another through conduit, tubing, piping, or other solid-wall...

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.

Double Mine Building (N) wall showing clerestory slot windows opening ...

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

Double Mine Building (N) wall showing clerestory slot windows opening above level of main roof. Note structure is built on poured concrete foundation partly buried in hillside; view in southeast - Fort McKinley, Double Mine Building, East side of East Side Drive, approximately 125 feet south of Weymouth Way, Great Diamond Island, Portland, Cumberland County, ME

30 CFR 75.310 - Installation of main mine fans.

Code of Federal Regulations, 2011 CFR

2011-07-01

... that gives a signal at the mine when the fan either slows or stops. A responsible person designated by the operator shall always be at a surface location at the mine where the signal can be seen or heard... weak walls or explosion doors, or a combination of weak walls and explosion doors, located in direct...

30 CFR 75.310 - Installation of main mine fans.

Code of Federal Regulations, 2010 CFR

2010-07-01

... that gives a signal at the mine when the fan either slows or stops. A responsible person designated by the operator shall always be at a surface location at the mine where the signal can be seen or heard... weak walls or explosion doors, or a combination of weak walls and explosion doors, located in direct...

30 CFR 75.310 - Installation of main mine fans.

Code of Federal Regulations, 2013 CFR

2013-07-01

... that gives a signal at the mine when the fan either slows or stops. A responsible person designated by the operator shall always be at a surface location at the mine where the signal can be seen or heard... weak walls or explosion doors, or a combination of weak walls and explosion doors, located in direct...

30 CFR 75.310 - Installation of main mine fans.

Code of Federal Regulations, 2012 CFR

2012-07-01

... that gives a signal at the mine when the fan either slows or stops. A responsible person designated by the operator shall always be at a surface location at the mine where the signal can be seen or heard... weak walls or explosion doors, or a combination of weak walls and explosion doors, located in direct...

30 CFR 75.310 - Installation of main mine fans.

Code of Federal Regulations, 2014 CFR

2014-07-01

... that gives a signal at the mine when the fan either slows or stops. A responsible person designated by the operator shall always be at a surface location at the mine where the signal can be seen or heard... weak walls or explosion doors, or a combination of weak walls and explosion doors, located in direct...

Looking northeast at Machine Shop (Bldg. 163) south wall. Note ...

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

Looking northeast at Machine Shop (Bldg. 163) south wall. Note bridge crane at right and crane rail attached to building - Atchison, Topeka, Santa Fe Railroad, Albuquerque Shops, Machine Shop, 908 Second Street, Southwest, Albuquerque, Bernalillo County, NM

17. Interior detail, pilaster on transverse wall at the northeast ...

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

17. Interior detail, pilaster on transverse wall at the northeast end of the Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to northeast (90mm lens). Note the offset top of the pilaster, a feature common to all interior transverse wall pilasters. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

30 CFR 57.22308 - Methane monitors (III mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane monitors (III mines). 57.22308 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22308 Methane monitors (III mines). (a) Methane monitors shall be installed on continuous mining machines and longwall mining systems. (b) The...

30 CFR 57.22308 - Methane monitors (III mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane monitors (III mines). 57.22308 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22308 Methane monitors (III mines). (a) Methane monitors shall be installed on continuous mining machines and longwall mining systems. (b) The...

Detail of Machine Shop (Bldg. 163) south wall and crane ...

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

Detail of Machine Shop (Bldg. 163) south wall and crane rail. The overlapped tracks in foreground were used to store wheelsets - Atchison, Topeka, Santa Fe Railroad, Albuquerque Shops, Machine Shop, 908 Second Street, Southwest, Albuquerque, Bernalillo County, NM

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.

30 CFR 57.22306 - Methane monitors (I-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane monitors (I-A mines). 57.22306 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22306 Methane monitors (I-A mines). (a) Methane monitors shall be installed on continuous mining machines, longwall mining systems, and on loading...

30 CFR 57.22307 - Methane monitors (II-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane monitors (II-A mines). 57.22307 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22307 Methane monitors (II-A mines). (a) Methane monitors shall be installed on continuous mining machines, longwall mining systems, bench and face...

30 CFR 57.22306 - Methane monitors (I-A mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane monitors (I-A mines). 57.22306 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22306 Methane monitors (I-A mines). (a) Methane monitors shall be installed on continuous mining machines, longwall mining systems, and on loading...

30 CFR 57.22307 - Methane monitors (II-A mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane monitors (II-A mines). 57.22307 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22307 Methane monitors (II-A mines). (a) Methane monitors shall be installed on continuous mining machines, longwall mining systems, bench and face...

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.

Numerical simulation of the stress distribution in a coal mine caused by a normal fault

NASA Astrophysics Data System (ADS)

Zhang, Hongmei; Wu, Jiwen; Zhai, Xiaorong

2017-06-01

Luling coal mine was used for research using FLAC3D software to analyze the stress distribution characteristics of the two sides of a normal fault zone with two different working face models. The working faces were, respectively, on the hanging wall and the foot wall; the two directions of mining were directed to the fault. The stress distributions were different across the fault. The stress was concentrated and the influenced range of stress was gradually larger while the working face was located on the hanging wall. The fault zone played a negative effect to the stress transmission. Obviously, the fault prevented stress transmission, the stress concentrated on the fault zone and the hanging wall. In the second model, the stress on the two sides decreased at first, but then increased continuing to transmit to the hanging wall. The concentrated stress in the fault zone decreased and the stress transmission was obvious. Because of this, the result could be used to minimize roadway damage and lengthen the time available for coal mining by careful design of the roadway and working face.

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

PERMEABLE TREATMENT WALL EFFECTIVENESS MONITORING PROJECT, NEVADA STEWART MINE

EPA Science Inventory

This report summarizes the results of Mine Waste Technology Program (MWTP) Activity III, Project 39, Permeable Treatment Wall Effectiveness Monitoring Project, implemented and funded by the U.S. Environmental Protection Agency (EPA) and jointly administered by EPA and the U.S. De...

30 CFR 57.22309 - Methane monitors (V-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane monitors (V-A mines). 57.22309 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22309 Methane monitors (V-A mines). (a) Methane monitors shall be installed on continuous mining machines used in or beyond the last open crosscut...

30 CFR 57.22309 - Methane monitors (V-A mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane monitors (V-A mines). 57.22309 Section... Standards for Methane in Metal and Nonmetal Mines Equipment § 57.22309 Methane monitors (V-A mines). (a) Methane monitors shall be installed on continuous mining machines used in or beyond the last open crosscut...

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 agarose micro-confinement array and machine-learning-based classification for analyzing the patterned differentiation of mesenchymal stem cells

PubMed Central

Sato, Asako; Vogel, Viola; Tanaka, Yo

2017-01-01

The geometrical confinement of small cell colonies gives differential cues to cells sitting at the periphery versus the core. To utilize this effect, for example to create spatially graded differentiation patterns of human mesenchymal stem cells (hMSCs) in vitro or to investigate underpinning mechanisms, the confinement needs to be robust for extended time periods. To create highly repeatable micro-fabricated structures for cellular patterning and high-throughput data mining, we employed here a simple casting method to fabricate more than 800 adhesive patches confined by agarose micro-walls. In addition, a machine learning based image processing software was developed (open code) to detect the differentiation patterns of the population of hMSCs automatically. Utilizing the agarose walls, the circular patterns of hMSCs were successfully maintained throughout 15 days of cell culture. After staining lipid droplets and alkaline phosphatase as the markers of adipogenic and osteogenic differentiation, respectively, the mega-pixels of RGB color images of hMSCs were processed by the software on a laptop PC within several minutes. The image analysis successfully showed that hMSCs sitting on the more central versus peripheral sections of the adhesive circles showed adipogenic versus osteogenic differentiation as reported previously, indicating the compatibility of patterned agarose walls to conventional microcontact printing. In addition, we found a considerable fraction of undifferentiated cells which are preferentially located at the peripheral part of the adhesive circles, even in differentiation-inducing culture media. In this study, we thus successfully demonstrated a simple framework for analyzing the patterned differentiation of hMSCs in confined microenvironments, which has a range of applications in biology, including stem cell biology. PMID:28380036

3. Oblique view of southwest end, Roundhouse Machine Shop Extension, ...

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

3. Oblique view of southwest end, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to north showing the curvature of the end wall that was the common wall with the Roundhouse, and the large metal-clad doors through which steam locomotives were moved into the Machine Shop (135mm lens). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

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.

Ensuring the Environmental and Industrial Safety in Solid Mineral Deposit Surface Mining

NASA Astrophysics Data System (ADS)

Trubetskoy, Kliment; Rylnikova, Marina; Esina, Ekaterina

2017-11-01

The growing environmental pressure of mineral deposit surface mining and severization of industrial safety requirements dictate the necessity of refining the regulatory framework governing safe and efficient development of underground resources. The applicable regulatory documentation governing the procedure of ore open-pit wall and bench stability design for the stage of pit reaching its final boundary was issued several decades ago. Over recent decades, mining and geomechanical conditions have changed significantly in surface mining operations, numerous new software packages and computer developments have appeared, opportunities of experimental methods of source data collection and processing, grounding of the permissible parameters of open pit walls have changed dramatically, and, thus, methods of risk assessment have been perfected [10-13]. IPKON RAS, with the support of the Federal Service for Environmental Supervision, assumed the role of the initiator of the project for the development of Federal norms and regulations of industrial safety "Rules for ensuring the stability of walls and benches of open pits, open-cast mines and spoil banks", which contribute to the improvement of economic efficiency and safety of mineral deposit surface mining and enhancement of the competitiveness of Russian mines at the international level that is very important in the current situation.

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.

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...

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)

The research progress of perforating gun inner wall blind hole machining method

NASA Astrophysics Data System (ADS)

Wang, Zhe; Shen, Hongbing

2018-04-01

Blind hole processing method has been a concerned technical problem in oil, electronics, aviation and other fields. This paper introduces different methods for blind hole machining, focus on machining method for perforating gun inner wall blind hole processing. Besides, the advantages and disadvantages of different methods are also discussed, and the development trend of blind hole processing were introduced significantly.

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...

Slope stability radar for monitoring mine walls

NASA Astrophysics Data System (ADS)

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

2001-11-01

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

Ventilation for an enclosure of a gas turbine and related method

DOEpatents

Schroeder, Troy Joseph; Leach, David; O'Toole, Michael Anthony

2002-01-01

A ventilation scheme for a rotary machine supported on pedestals within an enclosure having a roof, end walls and side walls with the machine arranged parallel to the side walls, includes ventilation air inlets located in a first end wall of the enclosure; a barrier wall located within the enclosure, proximate the first end wall to thereby create a plenum chamber. The barrier wall is constructed to provide a substantially annular gap between the barrier wall and a casing of the turbine to thereby direct ventilation air axially along the turbine; one or more ventilation air outlets located proximate a second, opposite end wall on the roof of the enclosure. In addition, one or more fans are provided for pulling ventilating air into said plenum chamber via the ventilation air inlets.

Behaviour of Masonry Walls under Horizontal Shear in Mining Areas

NASA Astrophysics Data System (ADS)

Kadela, Marta; Bartoszek, Marek; Fedorowicz, Jan

2017-12-01

The paper discusses behaviour of masonry walls constructed with small-sized elements under the effects of mining activity. It presents some mechanisms of damage occurring in such structures, its forms in real life and the behaviour of large fragments of masonry walls subjected to specific loads in FEM computational models. It offers a constitutive material model, which enables numerical analyses and monitoring of the behaviour of numerical models as regards elastic-plastic performance of the material, with consideration of its degradation. Results from the numerical analyses are discussed for isolated fragments of the wall subjected to horizontal shear, with consideration of degradation, impact of imposed vertical load as well as the effect of weakening of the wall, which was achieved by introducing openings in it, on the performance and deformation of the wall.

Real-Time Deflection Monitoring for Milling of a Thin-Walled Workpiece by Using PVDF Thin-Film Sensors with a Cantilevered Beam as a Case Study

PubMed Central

Luo, Ming; Liu, Dongsheng; Luo, Huan

2016-01-01

Thin-walled workpieces, such as aero-engine blisks and casings, are usually made of hard-to-cut materials. The wall thickness is very small and it is easy to deflect during milling process under dynamic cutting forces, leading to inaccurate workpiece dimensions and poor surface integrity. To understand the workpiece deflection behavior in a machining process, a new real-time nonintrusive method for deflection monitoring is presented, and a detailed analysis of workpiece deflection for different machining stages of the whole machining process is discussed. The thin-film polyvinylidene fluoride (PVDF) sensor is attached to the non-machining surface of the workpiece to copy the deflection excited by the dynamic cutting force. The relationship between the input deflection and the output voltage of the monitoring system is calibrated by testing. Monitored workpiece deflection results show that the workpiece experiences obvious vibration during the cutter entering the workpiece stage, and vibration during the machining process can be easily tracked by monitoring the deflection of the workpiece. During the cutter exiting the workpiece stage, the workpiece experiences forced vibration firstly, and free vibration exists until the amplitude reduces to zero after the cutter exits the workpiece. Machining results confirmed the suitability of the deflection monitoring system for machining thin-walled workpieces with the application of PVDF sensors. PMID:27626424

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

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

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

Zvi H. Meiksin

A temporary installation of Transtek's in-mine communications system in the Lake Lynn mine was used in the mine rescue training programs offered by NIOSH in April and May 2002. We developed and implemented a software program that permits point-to-point data transmission through our in-mine system. We also developed a wireless data transceiver for use in a PLC (programmed logic controller) to remotely control long-wall mining equipment.

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...

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.

30 CFR 57.22202 - Main fans (I-A, I-B, I-C, II-A, III, V-A, and V-B mines).

Code of Federal Regulations, 2012 CFR

2012-07-01

... mines, provided with an automatic signal device to give an alarm when the fan stops. The signal device... possible explosive forces; (2) Equipped with explosion-doors, a weak-wall, or other equivalent devices... or weak-wall shall be at least equivalent to the average cross-sectional area of the airway. (c) (1...

30 CFR 57.22202 - Main fans (I-A, I-B, I-C, II-A, III, V-A, and V-B mines).

Code of Federal Regulations, 2013 CFR

2013-07-01

... mines, provided with an automatic signal device to give an alarm when the fan stops. The signal device... possible explosive forces; (2) Equipped with explosion-doors, a weak-wall, or other equivalent devices... or weak-wall shall be at least equivalent to the average cross-sectional area of the airway. (c) (1...

30 CFR 57.22202 - Main fans (I-A, I-B, I-C, II-A, III, V-A, and V-B mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... mines, provided with an automatic signal device to give an alarm when the fan stops. The signal device... possible explosive forces; (2) Equipped with explosion-doors, a weak-wall, or other equivalent devices... or weak-wall shall be at least equivalent to the average cross-sectional area of the airway. (c) (1...

30 CFR 57.22202 - Main fans (I-A, I-B, I-C, II-A, III, V-A, and V-B mines).

Code of Federal Regulations, 2014 CFR

2014-07-01

... mines, provided with an automatic signal device to give an alarm when the fan stops. The signal device... possible explosive forces; (2) Equipped with explosion-doors, a weak-wall, or other equivalent devices... or weak-wall shall be at least equivalent to the average cross-sectional area of the airway. (c) (1...

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...

Adaptation and detoxification mechanisms of Vetiver grass (Chrysopogon zizanioides) growing on gold mine tailings.

PubMed

Melato, F A; Mokgalaka, N S; McCrindle, R I

2016-01-01

Vetiver grass (Chrysopogon zizanioides) was investigated for its potential use in the rehabilitation of gold mine tailings, its ability to extract and accumulate toxic metals from the tailings and its metal tolerant strategies. Vetiver grass was grown on gold mine tailings soil, in a hothouse, and monitored for sixteen weeks. The mine tailings were highly acidic and had high electrical conductivity. Vetiver grass was able to grow and adapt well on gold mine tailings. The results showed that Vetiver grass accumulated large amounts of metals in the roots and restricted their translocation to the shoots. This was confirmed by the bioconcentration factor of Zn, Cu, and Ni of >1 and the translocation factor of <1 for all the metals. This study revealed the defense mechanisms employed by Vetiver grass against metal stress that include: chelation of toxic metals by phenolics, glutathione S-tranferase, and low molecular weight thiols; sequestration and accumulation of metals within the cell wall that was revealed by the scanning electron microscopy that showed closure of stomata and thickened cell wall and was confirmed by high content of cell wall bound phenolics. Metal induced reactive oxygen species are reduced or eliminated by catalase, superoxide dismutase and peroxidase dismutase.

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

1. AIR/MANWAY SHAFT WALL AND FAN HOUSE FOUNDATION WALL FROM ...

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

1. AIR/MANWAY SHAFT WALL AND FAN HOUSE FOUNDATION WALL FROM NORTHWEST. AEROVANE FAN AT UPPER LEFT, SCAFFOLD AND LEPLEY VENTILATOR AT UPPER RIGHT. - Consolidation Coal Company Mine No. 11, Air-Manway Shaft, East side of State Route 936, Midlothian, Allegany County, MD

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

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.

10. DIAMOND MINE YARD FROM THE NORTH SHOWING A COMPRESSED ...

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

10. DIAMOND MINE YARD FROM THE NORTH SHOWING A COMPRESSED AIR PIPE AND TRESTLE IN THE LOWER LEFT, AND THE LORRY HOUSE. A PART OF A RETAINING WALL IS VISIBLE ABOVE THE RAILROAD CUT - Butte Mineyards, Diamond Mine, Butte, Silver Bow County, MT

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...

MINE WASTE TECHNOLOGY PROGRAM - SULFATE REDUCING BACTERIA REACTIVE WALL DEMO

EPA Science Inventory

Efforts reported in this document focused on the demonstration of a passive technology that could be used for remediation of
thousands of abandoned mines existing in the Western United States that emanate acid mine drainage (AMD). This passive remedial technology takes ad...

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

Whole-body Vibration Exposure of Drill Operators in Iron Ore Mines and Role of Machine-Related, Individual, and Rock-Related Factors.

PubMed

Chaudhary, Dhanjee Kumar; Bhattacherjee, Ashis; Patra, Aditya Kumar; Chau, Nearkasen

2015-12-01

This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration (m/s(2))], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient β = -0.052, standard error SE = 0.023), manufacturer (β = 1.093, SE = 0.227), rock hardness (β = 0.045, SE = 0.018), uniaxial compressive strength (β = 0.027, SE = 0.009), and density (β = -1.135, SE = 0.235). Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.

Whole-body Vibration Exposure of Drill Operators in Iron Ore Mines and Role of Machine-Related, Individual, and Rock-Related Factors

PubMed Central

Chaudhary, Dhanjee Kumar; Bhattacherjee, Ashis; Patra, Aditya Kumar; Chau, Nearkasen

2015-01-01

Background This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. Methods The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration (m/s2)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. Results More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient β = −0.052, standard error SE = 0.023), manufacturer (β = 1.093, SE = 0.227), rock hardness (β = 0.045, SE = 0.018), uniaxial compressive strength (β = 0.027, SE = 0.009), and density (β = –1.135, SE = 0.235). Conclusion Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system. PMID:26929838

Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm.

PubMed

Araki, Tadashi; Jain, Pankaj K; Suri, Harman S; Londhe, Narendra D; Ikeda, Nobutaka; El-Baz, Ayman; Shrivastava, Vimal K; Saba, Luca; Nicolaides, Andrew; Shafique, Shoaib; Laird, John R; Gupta, Ajay; Suri, Jasjit S

2017-01-01

Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque. Further, this paper presents a scientific validation system for stroke risk assessment. Both these innovations have never been presented before. The methodology consists of an automated segmentation system of the near wall and far wall regions in grayscale carotid B-mode ultrasound scans. Sixteen grayscale texture features are computed, and fed into the machine learning system. The training system utilizes the lumen diameter to create ground truth labels for the stratification of stroke risk. The cross-validation procedure is adapted in order to obtain the machine learning testing classification accuracy through the use of three sets of partition protocols: (5, 10, and Jack Knife). The mean classification accuracy over all the sets of partition protocols for the automated system in the far and near walls is 95.08% and 93.47%, respectively. The corresponding accuracies for the manual system are 94.06% and 92.02%, respectively. The precision of merit of the automated machine learning system when compared against manual risk assessment system are 98.05% and 97.53% for the far and near walls, respectively. The ROC of the risk assessment system for the far and near walls is close to 1.0 demonstrating high accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

North wall, central part, showing partial partition wall at left. ...

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

North wall, central part, showing partial partition wall at left. This area is labeled “Pioneering Research” on drawing copy NV-35-B-5 (submitted with HABS No. NV-35-B) (series 2 of 4) - Bureau of Mines Metallurgical Research Laboratory, Original Building, Date Street north of U.S. Highway 93, Boulder City, Clark County, NV

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...

29. Interior view, south end of the west (front) wall ...

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

29. Interior view, south end of the west (front) wall looking at the section between the door and southwestern corner, with scale (note remnants of the post-1915 fire plaster on wall) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

30 CFR 56.3131 - Pit or quarry wall perimeter.

Code of Federal Regulations, 2011 CFR

2011-07-01

... NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Ground Control... performing their assigned tasks, loose or unconsolidated material shall be sloped to the angle of repose or...

30 CFR 56.3131 - Pit or quarry wall perimeter.

Code of Federal Regulations, 2010 CFR

2010-07-01

... NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Ground Control... performing their assigned tasks, loose or unconsolidated material shall be sloped to the angle of repose or...

46. OFFICE INTERIOR FULL OF MACHINE PARTS, PAMPHLETS, AND ADVERTISEMENTS, ...

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

46. OFFICE INTERIOR FULL OF MACHINE PARTS, PAMPHLETS, AND ADVERTISEMENTS, HARDWARE STORED IN SHELVES ALONG STUD WALLS-LOOKING WEST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

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...

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.

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.

Loads from Compressive Strain Caused by Mining Activity Illustrated with the Example of Two Buildings in Silesia

NASA Astrophysics Data System (ADS)

Kadela, Marta; Chomacki, Leszek

2017-10-01

The soil’s load on retention walls or underground elements of engineering structures consists of three basic types of pressure: active pressure (p a ), passive pressure (p b ) and at-rest pressure (p 0 ). In undisturbed areas without any mining, due to lack of activity in the soil, specific forces from the soil are stable and unchanging throughout the structure’s life. Mining activity performed at a certain depth activates the soil. Displacements take place in the surface layer of the rock mass, which begins to act on the structure embedded in it, significantly changing the original stress distribution. Deformation of the subgrade, mainly horizontal strains, becomes a source of significant additional actions in the contact zone between the structure and the soil, constituting an additional load for the structure. In order to monitor the mining influence in the form of compressive load on building walls, an observation line was set up in front of two buildings located in Silesia (in Mysłowice). In 2013, some mining activity took place directly under those buildings, with expected horizontal strains of εx = -5.8 mm/m. The measurement results discussed in this paper showed that, as predicted, the buildings were subjected only to horizontal compressive strains with the values parallel to the analysed wall being less than -4.0 ‰ for first building and -1.5‰ for second building, and values perpendicular to the analysed wall being less than -6.0‰ for first building and -4.0‰ for second building (the only exception was the measurement in line 8-13, where εx = -17.04‰ for first building and -4.57‰ for second building). The horizontal displacement indicate that the impact of mining activity was greater on first building. This is also confirmed by inspections of the damage.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

The static breaking technique for sustainable and eco-environmental coal mining.

PubMed

Bing-yuan, Hao; Hui, Huang; Zi-jun, Feng; Kai, Wang

2014-01-01

The initiating explosive devices are prohibited in rock breaking near the goaf of the highly gassy mine. It is effective and applicable to cracking the hard roof with static cracking agent. By testing the static cracking of cubic limestone (size: 200 × 200 × 200 mm) with true triaxial rock mechanics testing machine under the effect of bidirectional stress and by monitoring the evolution process of the cracks generated during the acoustic emission experiment of static cracking, we conclude the following: the experiment results of the acoustic emission show that the cracks start from the lower part of the hole wall until they spread all over the sample. The crack growth rate follows a trend of "from rapidness to slowness." The expansion time is different for the two bunches of cracks. The growth rates can be divided into the rapid increasing period and the rapid declining period, of which the growth rate in declining period is less than that in the increasing period. Also, the growth rate along the vertical direction is greater than that of the horizontal direction. Then the extended model for the static cracking is built according to the theories of elastic mechanics and fracture mechanics. Thus the relation formula between the applied forces of cracks and crack expansion radius is obtained. By comparison with the test results, the model proves to be applicable. In accordance with the actual geological situation of Yangquan No. 3 Mine, the basic parameters of manpower manipulated caving breaking with static crushing are settled, which reaps bumper industrial effects.

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).

Mapping extent and change in surface mines within the United States for 2001 to 2006

USGS Publications Warehouse

Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.; Parker, Owen P.

2016-01-01

A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi-automated procedure to map the country's mining footprint (30-m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate-to-large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km2 of surface mines were mapped. The footprint increased to 9,181 km2 in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall-to-wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country. 

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

75 FR 17529 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

..., requires manufacturers to provide safeguards against corona on all 4,160-volt circuits in explosion-proof enclosures. Corona is a luminous discharge that occurs around electric conductors that are subject to high electric stresses. Corona can cause premature breakdown of insulating materials in explosion-proof...

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...

Proceedings of the 92nd regular meeting of the Rocky Mountain Coal Mining Institute

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

Finnie, D.G.

1996-12-31

The proceedings of the 92nd Regular Meeting of the Rocky Mountain Coal Mining Institute held June 29-July 2, 1996 in Durango, CO. are presented. Attention was focused on the following areas: plots, plans, and partnerships in US mining; partnerships at McKinley; deregulation of the electric utility industry; environmental partnerships; Federal Mine Safety and Health Act; injury prevention in the coal mining industry; new trend in back injury prevention; and automated high wall mining. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

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.

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.

31. Interior view, north end of the west wall looking ...

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

31. Interior view, north end of the west wall looking at the section between the front door and the northwestern corner of the building, with scale (note position of post fire partition wall and floor joists as recorded in the brickwork) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

33. SOUTHWEST CORNER OF BUILDING 232 (MINE SHOP) IN ASSEMBLY ...

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

33. SOUTHWEST CORNER OF BUILDING 232 (MINE SHOP) IN ASSEMBLY AREA WITH INDEPENDENT BLAST WALL AT LEFT. - Loring Air Force Base, Weapons Storage Area, Northeastern corner of base at northern end of Maine Road, Limestone, Aroostook County, ME

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 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

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.

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...

Implementation of visual data mining for unsteady blood flow field in an aortic aneurysm.

PubMed

Morizawa, Seiichiro; Shimoyama, Koji; Obayashi, Shigeru; Funamoto, Kenichi; Hayase, Toshiyuki

2011-12-01

This study was performed to determine the relations between the features of wall shear stress and aneurysm rupture. For this purpose, visual data mining was performed in unsteady blood flow simulation data for an aortic aneurysm. The time-series data of wall shear stress given at each grid point were converted to spatial and temporal indices, and the grid points were sorted using a self-organizing map based on the similarity of these indices. Next, the results of cluster analysis were mapped onto the real space of the aortic aneurysm to specify the regions that may lead to aneurysm rupture. With reference to previous reports regarding aneurysm rupture, the visual data mining suggested specific hemodynamic features that cause aneurysm rupture. GRAPHICAL ABSTRACT:

Mapping alteration minerals at prospect, outcrop and drill core scales using imaging spectrometry

PubMed Central

Kruse, Fred A.; L. Bedell, Richard; Taranik, James V.; Peppin, William A.; Weatherbee, Oliver; Calvin, Wendy M.

2011-01-01

Imaging spectrometer data (also known as ‘hyperspectral imagery’ or HSI) are well established for detailed mineral mapping from airborne and satellite systems. Overhead data, however, have substantial additional potential when used together with ground-based measurements. An imaging spectrometer system was used to acquire airborne measurements and to image in-place outcrops (mine walls) and boxed drill core and rock chips using modified sensor-mounting configurations. Data were acquired at 5 nm nominal spectral resolution in 360 channels from 0.4 to 2.45 μm. Analysis results using standardized hyperspectral methodologies demonstrate rapid extraction of representative mineral spectra and mapping of mineral distributions and abundances in map-plan, with core depth, and on the mine walls. The examples shown highlight the capabilities of these data for mineral mapping. Integration of these approaches promotes improved understanding of relations between geology, alteration and spectral signatures in three dimensions and should lead to improved efficiency of mine development, operations and ultimately effective mine closure. PMID:25937681

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.

Application of soil nails to the stability of mine waste slopes

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

Tant, C.R.; Drumm, E.C.; Mauldon, M.

1996-12-31

The traditional soil nailed structure incorporates grouted or driven nails, and a wire mesh reinforced shotcrete facing to increase the stability of a slope or wall. This paper describes the construction and monitoring of a full-scale demonstration of nailing to stabilize coal mine spoil. The purpose of the investigation is to evaluate the performance of nailed slopes in mine spoil using methods proven for the stabilization of soil walls and slopes. The site in eastern Tennessee is a 12 meter high slope of dumped fill, composed of weathered shale chips, sandstone, and coal. The slope was formed by {open_quotes}pre-regulatory{close_quotes} contourmore » surface mining operations and served as a work bench during mining. The material varies in size from silt to boulders, and has a small amount of cohesion. Portions of the mine spoil slope have experienced slope instability and erosion which have hampered subsequent reclamation activities. Three different nail spacings and three different nail lengths were used in the design. The 12 meter high structure is instrumented to permit measurement of nail strain, and vertical inclinometer readings and survey measurements will be used for the detection of ground movement. The results of this study will aid in the development of design recommendations and construction guidelines for the application of soil nailing to stabilize mine spoil.« less

Method of fabricating a prestressed cast iron vessel

DOEpatents

Lampe, Robert F.

1982-01-01

A method of fabricating a prestressed cast iron vessel wherein double wall cast iron body segments each have an arcuate inner wall and a spaced apart substantially parallel outer wall with a plurality of radially extending webs interconnecting the inner wall and the outer wall, the bottom surface and the two exposed radial side surfaces of each body segment are machined and eight body segments are formed into a ring. The top surfaces and outer surfaces of the outer walls are machined and keyways are provided across the juncture of adjacent end walls of the body segments. A liner segment complementary in shape to a selected inner wall of one of the body segments is mounted to each of the body segments and again formed into a ring. The liner segments of each ring are welded to form unitary liner rings and thereafter the cast iron body segments are prestressed to complete the ring assembly. Ring assemblies are stacked to form the vessel and adjacent unitary liner rings are welded. A top head covers the top ring assembly to close the vessel and axially extending tendons retain the top and bottom heads in place under pressure.

Mechanical design of walking machines.

PubMed

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

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

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.

Prediction of blast fragmentation of underground stopes for in situ leaching

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

Stagg, M.S.; Otterness, R.E.; Djahanguiri, F.

1994-12-31

The US Bureau of Mines (USBM) evaluated empirical equations that predict fragmentation from underground stope rounds. Controlled blasting is necessary for creating leaching stopes that maximize the recovery and minimize backbreak of the perimeter wall. This paper presents the fragmentation results from one of the three drop-raise blasts used to develop a reduced-scale cylindrical stope, 1.8 m in diameter and 6 m in height. The stope is located in the Colorado School of Mines Experimental Mine (Edgar Mine) in Idaho Springs, Colorado. This stope is part of a USBM research effort to determine the feasibility of incorporating in situ leachingmore » of rubblized stopes into active underground metal and nonmetal mines. All the material from the first blast, 14 mtons was sieved. The resulting distribution was compared to the distribution predicted from empirical equations. The best fit was found with a USBM equation developed from over 50 sieved, reduced-scale (1- to 2-m) high wall blasts. Modifications to the equations were made to account for the observed differences due to breakout angle, shot geometry, initiation timing, decoupling, rock fracture toughness and explosive energy.« less

Lunar construction/mining equipment

NASA Technical Reports Server (NTRS)

Ozdemir, Levent

1990-01-01

For centuries, mining has utilized drill and blast as the primary method of rock excavation. Although this technique has undergone significant improvements, it still remains a cyclic, labor intensive operation with inherent safety hazards. Other drawbacks include damage to the surrounding ground, creation of blast vibrations, rough excavation walls resulting in increased ventilation requirements, and the lack of selective mining ability. Perhaps the most important shortcoming of drill and blast is that it is not conducive to full implementation of automation or robotics technologies. Numerous attempts have been made in the past to automate drill and blast operations to remove personnel from the hazardous work environment. Although most of the concepts devised look promising on paper, none of them was found workable on a sustained production basis. In particular, the problem of serious damage to equipment during the blasting cycle could not be resolved regardless of the amount of charge used in excavation. Since drill and blast is not capable of meeting the requirements of a fully automated rock fragmentation method, its role is bound to gradually decrease. Mechanical excavation, in contrast, is highly suitable to automation because it is a continuous process and does not involve any explosives. Many of the basic principles and trends controlling the design of an earth-based mechanical excavator will hold in an extraterrestrial environment such as on the lunar surface. However, the economic and physical limitations for transporting materials to space will require major rethinking of these machines. In concept, then, a lunar mechanical excavator will look and perform significantly different from one designed for use here on earth. This viewgraph presentation gives an overview of such mechanical excavator systems.

Tectonic fault monitoring at open pit mine at Zarnitsa Kimberlite Pipe

NASA Astrophysics Data System (ADS)

Vostrikov, VI; Polotnyanko, NS; Trofimov, AS; Potaka, AA

2018-03-01

The article describes application of Karier instrumentation designed at the Institute of Mining to study fracture formation in rocks. The instrumentation composed of three sensors was used to control widening of a tectonic fault intersecting an open pit mine at Zarnitsa Kimberlite Pipe in Yakutia. The monitoring between 28 November and 28 December in 2016 recorded convergence of the fault walls from one side of the open pit mine and widening from the other side. After production blasts, the fault first grows in width and then recovers.

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.

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...

Research status and future trends on surface pre-grouting technology in reforming wall rock of vertical shafts in coal mines in China

NASA Astrophysics Data System (ADS)

Wang, Hua

2018-02-01

In the mine construction, the surface pre-grouting technology is an important method to prevent water blast in excavation process of vertical shaft when the shaft must pass through the thick, water-rich and high water-pressure bedrock aquifer. It has been nearly 60 years since the technology was used to reform wall rock of vertical shaft in coal mine in China for the first time, and the existing technology can basically meet the needs of constructing 1000m deep vertical shaft. Firstly, the article introduces that in view of Magg’s spherical seepage theory and Karol’s spherical seepage theory, Chinese scholars found that the diffusion of grout from borehole into the surrounding strata in horizontal direction is irregular through a lot of research and engineering practice of using the surface pre-grouting technology to reform wall rock of vertical shafts, and put forward the selecting principles of grout’s effective diffusion radius in one grouting engineering; Secondly, according to the shape of the grouting boreholes, surface pre-grouting technology of vertical shaft is divided into two stages: vertical borehole stage and S-type borehole stage. Thirdly, the development status of grouting materials and grouting equipment for the technology is introduced. Fourthly, grouting mode, stage height and pressure of the technology are introduced. Finally, it points out that with the increasing depth of coal mining in China, the technology of reforming wall rock of 1000~2000m deep vertical shafts will face many problems, such as grouting theory, grouting equipment, grouting finishing standard, testing and evaluation of grouting effect, and so on. And it put forward a preliminary approach to solving these problems. This paper points out future research directions of the surface pre-grouting technology in China.

37. PATTERNS HANGING FROM CEILING AND OFFICE WALL, NOTE CRAFTSMANSHIP ...

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

37. PATTERNS HANGING FROM CEILING AND OFFICE WALL, NOTE CRAFTSMANSHIP OF CURVE-LOOKING NORTHWEST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

33. FOUNDRY WALL SHOWING WOOD PATTERNS OF STEAMER GRATES, WHEELS, ...

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

33. FOUNDRY WALL SHOWING WOOD PATTERNS OF STEAMER GRATES, WHEELS, AND CRANE TRACKS-LOOKING NORTH. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

123. BENCH SHOP, SOUTH WALL SHOWING TOOL SHARPENER ON LEFT ...

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

123. BENCH SHOP, SOUTH WALL SHOWING TOOL SHARPENER ON LEFT AND WOOD BORING MACHINE ON RIGHT. - Gruber Wagon Works, Pennsylvania Route 183 & State Hill Road at Red Bridge Park, Bernville, Berks County, PA

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.

A comparison RSM and ANN surface roughness models in thin-wall machining of Ti6Al4V using vegetable oils under MQL-condition

NASA Astrophysics Data System (ADS)

Mohruni, Amrifan Saladin; Yanis, Muhammad; Sharif, Safian; Yani, Irsyadi; Yuliwati, Erna; Ismail, Ahmad Fauzi; Shayfull, Zamree

2017-09-01

Thin-wall components as usually applied in the structural parts of aeronautical industry require significant challenges in machining. Unacceptable surface roughness can occur during machining of thin-wall. Titanium product such Ti6Al4V is mostly applied to get the appropriate surface texture in thin wall designed requirements. In this study, the comparison of the accuracy between Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) in the prediction of surface roughness was conducted. Furthermore, the machining tests were carried out under Minimum Quantity Lubrication (MQL) using AlCrN-coated carbide tools. The use of Coconut oil as cutting fluids was also chosen in order to evaluate its performance when involved in end milling. This selection of cutting fluids is based on the better performance of oxidative stability than that of other vegetable based cutting fluids. The cutting speed, feed rate, radial and axial depth of cut were used as independent variables, while surface roughness is evaluated as the dependent variable or output. The results showed that the feed rate is the most significant factors in increasing the surface roughness value followed by the radial depth of cut and lastly the axial depth of cut. In contrary, the surface becomes smoother with increasing the cutting speed. From a comparison of both methods, the ANN model delivered a better accuracy than the RSM model.

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

Application of kinematic vorticity and gold mineralization for the wall rock alterations of shear zone at Dungash gold mining, Central Eastern Desert, Egypt

NASA Astrophysics Data System (ADS)

Kassem, Osama M. K.; Abd El Rahim, Said H.; El Nashar, EL Said R.; AL Kahtany, Kaled M.

2016-11-01

The use of porphyroclasts rotating in a flowing matrix to estimate mean kinematic vorticity number (Wm) is important for quantifying the relative contributions of pure and simple shear in wall rocks alterations of shear zone at Dungash gold mine. Furthermore, it shows the relationship between the gold mineralization and deformation and also detects the orientation of rigid objects during progressive deformation. The Dungash gold mine area is situated in an EW-trending quartz vein along a shear zone in metavolcanic and metasedimentary host rocks in the Eastern Desert of Egypt. These rocks are associated with the major geologic structures which are attributed to various deformational stages of the Neoproterozoic basement rocks. We conclude that finite strain in the deformed rocks is of the same order of magnitude for all units of metavolcano-sedimentary rocks. The kinematic vorticity number for the metavolcanic and metasedimentary samples in the Dungash area range from 0.80 to 0.92, and together with the strain data suggest deviations from simple shear. It is concluded that nappe stacking occurred early during the underthrusting event probably by brittle imbrication and that ductile strain was superimposed on the nappe structure during thrusting. Furthermore, we conclude that disseminated mineralization, chloritization, carbonatization and silicification of the wall rocks are associated with fluids migrating along shearing, fracturing and foliation of the metamorphosed wall rocks.

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.

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.

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.

Ageing of structural materials in tokamaks: TEXTOR liner study

NASA Astrophysics Data System (ADS)

Weckmann, A.; Petersson, P.; Rubel, M.; Fortuna-Zaleśna, E.; Zielinski, W.; Romelczyk-Baishya, B.; Grigore, E.; Ruset, C.; Kreter, A.

2017-12-01

After the final shut-down of the tokamak TEXTOR, all of its machine parts became accessible for comprehensive studies. This unique opportunity enabled the study of the Inconel 625 liner by a wide range of methods. The aim was to evaluate eventual alteration of surface and bulk characteristics from recessed wall elements that may influence the machine performance. The surface was covered with stratified layers consisting mainly of boron, carbon, oxygen, and in some cases also silicon. Wall conditioning and limiter materials hence predominantly define deposition on the liner. Deposited layers on recessed wall elements reach micrometre thickness within decades, peel off and may contribute to the dust inventory in tokamaks. Deuterium content was about 4,7 at% on average most probably due to wall conditioning with deuterated gas, and very low concentration in the Inconel substrate. Inconel 625 retained its mechanical strength despite 26 years of cyclic heating, stresses and particle bombardment.

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.

Acoustic emission and ultrasonic-velocity methods used to characterise the excavation disturbance associated with deep tunnels in hard rock

NASA Astrophysics Data System (ADS)

Falls, Stephen D.; Young, R. Paul

1998-04-01

Acoustic emission (AE) and ultrasonic-velocity monitoring studies have been undertaken at both the Atomic Energy of Canada Limited (AECL) Underground Research Laboratory (URL) and at the Swedish Nuclear Fuel Waste Management Company (SKB) Hard Rock Laboratory (HRL). At both locations the excavations were tunnels in granitic material at approximately 420 m depth. However, the stress regime was more severe at the URL Mine-by tunnel site than the HRL ZEDEX tunnel. Different parts of the ZEDEX tunnel were created using different excavation techniques. Using AE and ultrasonic techniques to study these tunnels we have been able to examine the nature of the excavation-disturbed zone around the tunnel, as well as examining the effects of different stress regimes and excavation techniques. Studies were undertaken both during and after the Mine-by tunnel excavation and during excavation in the ZEDEX tunnel. AE monitoring in the wall of the Mine-by tunnel during excavation showed that some activity occurred in the sidewall regions, but the spatial density of AE hypocentres increased toward the regions in the floor and roof of the tunnel where breakout notches formed. This sidewall activity was clustered primarily within 0.5 m of the tunnel wall. AE monitoring in the floor of the tunnel showed that small numbers of AE continued to occur in the notch region in the floor of the tunnel over 2 years after excavation was completed. This activity became more acute as the rock was heated, imposing thermally induced stresses on the volume. Ultrasonic-velocity studies both in the floor and the wall of the tunnel showed that the velocity is strongly anisotropic with the direction of slowest velocity orthogonal to the tunnel surface. The velocity increased with distance into the rock from the tunnel surface. In the floor, this effect was seen up to 2 m from the tunnel surface. Most of the change occurred within the first 0.5 m from the tunnel perimeter. At the lower-stress HRL, most of the AE again occur very close to the tunnel surface. The occurrence of AE under relatively low stress conditions suggests that the regions experiencing AE activity were damaged during the excavation process, thereby reducing their strength. The section of tunnel excavated by a tunnel-boring machine had fewer events, clustered much closer to the tunnel surface, than the sections excavated using drill and blast excavation techniques. P-wave velocity changes of only about 0.1% were experienced due to the tunnel excavation for ray paths within zero to 2 m from the tunnel surface indicating that crack damage was relatively low.

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.

41. Interior view of roof and wall below, looking to ...

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

41. Interior view of roof and wall below, looking to the east from the second floor landing at the junction of the common rafters to the raising plate, or false plate (note the false plate does not rest on the brick wall, instead is lapped over tie beams that support the floor & framing of the second level) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

Gene Mining for Proline Based Signaling Proteins in Cell Wall of Arabidopsis thaliana

PubMed Central

Ihsan, Muhammad Z.; Ahmad, Samina J. N.; Shah, Zahid Hussain; Rehman, Hafiz M.; Aslam, Zubair; Ahuja, Ishita; Bones, Atle M.; Ahmad, Jam N.

2017-01-01

The cell wall (CW) as a first line of defense against biotic and abiotic stresses is of primary importance in plant biology. The proteins associated with cell walls play a significant role in determining a plant's sustainability to adverse environmental conditions. In this work, the genes encoding cell wall proteins (CWPs) in Arabidopsis were identified and functionally classified using geneMANIA and GENEVESTIGATOR with published microarrays data. This yielded 1605 genes, out of which 58 genes encoded proline-rich proteins (PRPs) and glycine-rich proteins (GRPs). Here, we have focused on the cellular compartmentalization, biological processes, and molecular functioning of proline-rich CWPs along with their expression at different plant developmental stages. The mined genes were categorized into five classes on the basis of the type of PRPs encoded in the cell wall of Arabidopsis thaliana. We review the domain structure and function of each class of protein, many with respect to the developmental stages of the plant. We have then used networks, hierarchical clustering and correlations to analyze co-expression, co-localization, genetic, and physical interactions and shared protein domains of these PRPs. This has given us further insight into these functionally important CWPs and identified a number of potentially new cell-wall related proteins in A. thaliana. PMID:28289422

21. INTERIOR VIEW OF THE MACHINE SHOP LOOKING SOUTH. FROM ...

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

21. INTERIOR VIEW OF THE MACHINE SHOP LOOKING SOUTH. FROM LEFT TO RIGHT, PULLEY'S ABOVE FOR THE LATHE BELOW, ENTRANCE TO THE ELECTRICAL MOTOR ROOM, BORING MACHINE, PLANER, TOOL, BENCH AGAINST THE BACK WALL, DOORWAY INTO THE ANNEX, LONG LATHE. WOOD STOVE IN THE FOREGROUND RIGHT. - Standard Gold Mill, East of Bodie Creek, Northeast of Bodie, Bodie, Mono County, CA

Development of testing machine for tunnel inspection using multi-rotor UAV

NASA Astrophysics Data System (ADS)

Iwamoto, Tatsuya; Enaka, Tomoya; Tada, Keijirou

2017-05-01

Many concrete structures are deteriorating to dangerous levels throughout Japan. These concrete structures need to be inspected regularly to be sure that they are safe enough to be used. The inspection method for these concrete structures is typically the impact acoustic method. In the impact acoustic method, the worker taps the surface of the concrete with a hammer. Thus, it is necessary to set up scaffolding to access tunnel walls for inspection. Alternatively, aerial work platforms can be used. However, setting up scaffolding and aerial work platforms is not economical with regard to time or money. Therefore, we developed a testing machine using a multirotor UAV for tunnel inspection. This test machine flies by a plurality of rotors, and it is pushed along a concrete wall and moved by using rubber crawlers. The impact acoustic method is used in this testing machine. This testing machine has a hammer to make an impact, and a microphone to acquire the impact sound. The impact sound is converted into an electrical signal and is wirelessly transmitted to the computer. At the same time, the position of the testing machine is measured by image processing using a camera. The weight and dimensions of the testing machine are approximately 1.25 kg and 500 mm by 500 mm by 250 mm, respectively.

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 assembly including expanding wall segments of auger

DOEpatents

Treuhaft, Martin B.; Oser, Michael S.

1983-01-01

A mining auger comprises a cutting head carried at one end of a tubular shaft and a plurality of wall segments which in a first position thereof are disposed side by side around said shaft and in a second position thereof are disposed oblique to said shaft. A vane projects outwardly from each wall segment. When the wall segments are in their first position, the vanes together form a substantially continuous helical wall. A cutter is mounted on the peripheral edge of each of the vanes. When the wall segments are in their second position, the cutters on the vanes are disposed radially outward from the perimeter of the cutting head.

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...

Coordinated role of soluble and cell wall bound phenols is a key feature of the metabolic adjustment in a mining woody fleabane (Dittrichia viscosa L.) population under semi-arid conditions.

PubMed

López-Orenes, Antonio; Bueso, María C; Párraga-Aguado, Isabel M; Calderón, Antonio A; Ferrer, María A

2018-03-15

Environmental contamination by hazardous heavy metals/metalloids (metal(loid)s) is growing worldwide. To restrict the migration of toxic contaminants, the establishment of a self-sustainable plant cover is required. Plant growth in multi-polluted soils is a challenging issue not only by metal(loid) toxicities, but also by the co-occurrence of other stressors. Dittrichia viscosa is a pioneer Mediterranean species able to thrive in metal(loid)-enriched tailings in semi-arid areas. The aim of the present work was to examine the metabolic adjustments involved in the acclimation responses of this plant to conditions prevailing in mine-tailings during Mediterranean spring and summer. For this purpose, fully-expanded leaves, and rhizosphere soil of both mining and non-mining populations of D. viscosa grown spontaneously in south-eastern Spain were sampled in two consecutive years. Quantitative analysis of >50 biochemical, physiological and edaphic parameters were performed, including nutrient status, metal(loid) contents, leaf redox components, primary and secondary metabolites, salicylic acid levels, and soil physicochemical properties. Results showed that mining plants exhibited high foliar Zn/Pb co-accumulation capacity, without substantially affecting their photosynthetic metabolism or nutritional status even in the driest summer period. The comparison of the antioxidative/oxidative profile between mining and non-mining D. viscosa populations revealed no major seasonal changes in the content of primary antioxidants (ascorbate and GSH), or in the levels of ROS. Multivariate analysis showed that phenylalanine ammonia-lyase (PAL) and peroxidase (PRX) activities and soluble and cell wall-bound phenols were potential biomarkers for discriminating between both populations. During the dry season, a marked enhancement in the activity of both PAL and soluble PRX resulted in both a drop in the accumulation of soluble phenols and an increase of the strong metal chelator caffeic acid in the cell-wall fraction, supporting the view that the plasticity of phenylpropanoid metabolism provide an effective way to counteract the effects of stress combinations. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

44. DETAIL OF WALL SHOWING 1914 CALENDAR (DEPICTING PANAMA CANAL), ...

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

44. DETAIL OF WALL SHOWING 1914 CALENDAR (DEPICTING PANAMA CANAL), PATTERN FOR NARROW GAUGE RR WHEEL, AND AD-LOOKING SOUTHEAST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

Cornish Tin Mining and Smelting

ERIC Educational Resources Information Center

Gardner, Rebecca

2010-01-01

In this article, the author describes how Cornwall was once the world's leading producer of tin. Cornwall's industrial past is now a World Heritage Site alongside the Grand Canyon or the Great Wall of China. A hint is in the Cornish flag, a simple white cross against a black background, also known as Saint Piran's flag. At Geevor Tin Mine, one of…

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.

VIEW LOOKING EAST. THE NORTH WALL OF SETTLING RESERVOIR NO. ...

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

VIEW LOOKING EAST. THE NORTH WALL OF SETTLING RESERVOIR NO. 3 IS AT THE LEFT. THE BLAISDELL SLOW SAND FILTER WASHING MACHINE IS SEEN AT THE UPPER LEFT AND SETTLING RESERVOIR NO. 4 IS SEEN BEYOND THE EAST WALL OF SETTLING RESERVOIR NO. 3. - Yuma Main Street Water Treatment Plant, Jones Street at foot of Main Street, Yuma, Yuma County, AZ

Re-Shielding of Cobalt-60 Teletherapy Rooms for Tomotherapy and Conventional Linear Accelerators using Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Çeçen, Yiğit; Yazgan, Çağrı

2017-09-01

Purpose. Nearly all Cobalt-60 teletherapy machines were removed around the world during the last two decades. The remaining ones are being used for experimental purposes. However, the rooms of these teletherapy machines are valuable because of lack of space in radiotherapy clinics. In order to place a new technology treatment machine in one of these rooms, one should re-shield the room since it was designed only for 1.25 MeV gamma beams on average. Mostly, the vendor of the new machine constructs the new shielding of the room using their experience. However, every radiotherapy room has different surrounding work areas and it would be wise to shield the room considering these special conditions. Also, the shield design goal of the clinic may be much lower than the International Atomic Energy Agency (IAEA) or the local association accepts. The study shows re-shielding of a Cobalt-60 room, specific to the clinic, using Monte Carlo simulations. Materials & Methods: First, a 6 MV Tomotherapy machine, then a 10 MV conventional linear accelerator (LINAC) was placed inside the Cobalt-60 teletherapy room. The photon flux outside the room was simulated using Monte Carlo N-Particle (MCNP6.1) code before and after re-shielding. For the Tomotherapy simulation, flux distributions around the machine were obtained from the vendor and implemented as the source of the model. The LINAC model was more generic with the 10 MeV electron source, the tungsten target, first and secondary collimators. The aim of the model was to obtain the maximum (40x40 cm2) open field at the isocenter. Two different simulations were carried out for gantry angles 90o and 270o. The LINAC was placed in the room such that the primary walls were A' (Gantry 270o) and C' (Gantry 90o) (figure 1). The second part of the study was to model the re-shielding of the room for Tomotherapy and for the conventional LINAC, separately. The aim was to investigate the recommended shielding by the vendors. Left side of the room was adjacent to a LINAC room with 2 meters thick concrete wall (figure 1). No shielding was necessary for that wall. Behind wall A-A' there was an outdoors forbidden area; behind wall B-B' was the contouring room for the doctors; and the control room was behind wall C-C' (figure 1). After some modifications, the final shielding was designed. Results: The photon flux distributions outside the room before and after the re-shielding were compared. The re-shielding of Tomotherapy reduced the flux down to 1.89 % on average with respect to pre-shielding (table 1). For the conventional LINAC case; after re-shielding, the photon flux in the control room -which corresponds to gantry 90°- decreased down to 0.57% with respect to pre-shielding (table 2). The photon flux behind wall A' -which corresponds to gantry 270°- decreased down to 2.46%. Everybody was all safe behind wall B' even before re-shielding.

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.

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

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

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

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/).

Method and apparatus for tensile testing of metal foil

NASA Technical Reports Server (NTRS)

Wade, O. W. (Inventor)

1976-01-01

A method for obtaining accurate and reproducible results in the tensile testing of metal foils in tensile testing machines is described. Before the test specimen are placed in the machine, foil side edges are worked until they are parallel and flaw free. The specimen are also aligned between and secured to grip end members. An aligning apparatus employed in the method is comprised of an alignment box with a longitudinal bottom wall and two upright side walls, first and second removable grip end members at each end of the box, and a means for securing the grip end members within the box.

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

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.

Kinetics of bed fracturing around mine workings

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

Veksler, Yu.A.

1988-03-01

A failure of the bed near the walls of the workings of a mine away from the face occurs gradually over time and in this paper the authors take a kinetic approach to evaluating its development. The influence of certain mine engineering factors on the pattern of bed fracturing is discussed. The effect of the depth of mining is shown. Cracking occurs in the portion of the seam at the face near the ground at some distance from it on the interface between soft and hard coal. The density of the fractured rocks and their response affect the bed fracturingmore » near the stope face.« less

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

PubMed Central

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

2014-01-01

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

Using surface impedance for calculating wakefields in flat geometry

DOE PAGES

Bane, Karl; Stupakov, Gennady

2015-03-18

Beginning with Maxwell's equations and assuming only that the wall interaction can be approximated by a surface impedance, we derive formulas for the generalized longitudinal and transverse impedance in flat geometry, from which the wakefields can also be obtained. From the generalized impedances, by taking the proper limits, we obtain the normal longitudinal, dipole, and quad impedances in flat geometry. These equations can be applied to any surface impedance, such as the known dc, ac, and anomalous skin models of wall resistance, a model of wall roughness, or one for a pipe with small, periodic corrugations. We show that, formore » the particular case of dc wall resistance, the longitudinal impedance obtained here agrees with a known result in the literature, a result that was derived from a very general formula by Henke and Napoly. As an example, we apply our results to representative beam and machine parameters in the undulator region of LCLS-II and estimate the impact of the transverse wakes on the machine performance.« less

Wax Reinforces Honeycomb During Machining

NASA Technical Reports Server (NTRS)

Towell, Timothy W.; Fahringer, David T.; Vasquez, Peter; Scheidegger, Alan P.

1995-01-01

Method of machining on conventional metal lathe devised for precise cutting of axisymmetric contours on honeycomb cores made of composite (matrix/fiber) materials. Wax filling reinforces honeycomb walls against bending and tearing while honeycomb being contoured on lathe. Innovative method of machining on lathe involves preparation in which honeycomb is placed in appropriate fixture and the fixture is then filled with molten water-soluble wax. Number of different commercial waxes have been tried.

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.

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.

Influence of measuring algorithm on shape accuracy in the compensating turning of high gradient thin-wall parts

NASA Astrophysics Data System (ADS)

Wang, Tao; Wang, Guilin; Zhu, Dengchao; Li, Shengyi

2015-02-01

In order to meet the requirement of aerodynamics, the infrared domes or windows with conformal and thin-wall structure becomes the development trend of high-speed aircrafts in the future. But these parts usually have low stiffness, the cutting force will change along with the axial position, and it is very difficult to meet the requirement of shape accuracy by single machining. Therefore, on-machine measurement and compensating turning are used to control the shape errors caused by the fluctuation of cutting force and the change of stiffness. In this paper, on the basis of ultra precision diamond lathe, a contact measuring system with five DOFs is developed to achieve on-machine measurement of conformal thin-wall parts with high accuracy. According to high gradient surface, the optimizing algorithm is designed on the distribution of measuring points by using the data screening method. The influence rule of sampling frequency is analyzed on measuring errors, the best sampling frequency is found out based on planning algorithm, the effect of environmental factors and the fitting errors are controlled within lower range, and the measuring accuracy of conformal dome is greatly improved in the process of on-machine measurement. According to MgF2 conformal dome with high gradient, the compensating turning is implemented by using the designed on-machine measuring algorithm. The shape error is less than PV 0.8μm, greatly superior compared with PV 3μm before compensating turning, which verifies the correctness of measuring algorithm.

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

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

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

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.

1. DETAIL OF TUBE ICE MACHINE OUTLET AT SOUTHWEST CORNER ...

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

1. DETAIL OF TUBE ICE MACHINE OUTLET AT SOUTHWEST CORNER OF BUILDING 162; ICE MANUFACTURED INSIDE THE BUILDING WAS AUGURED THROUGH THE WALL AND DROPPED INTO COMPARTMENTS IN REFIGERATED RAIL CARS - Rath Packing Company, Cooler Building, Sycamore Street between Elm & Eighteenth Streets, Waterloo, Black Hawk County, IA

Evaluating the electrical discharge machining (EDM) parameters with using carbon nanotubes

NASA Astrophysics Data System (ADS)

Sari, M. M.; Noordin, M. Y.; Brusa, E.

2012-09-01

Electrical discharge machining (EDM) is one of the most accurate non traditional manufacturing processes available for creating tiny apertures, complex or simple shapes and geometries within parts and assemblies. Performance of the EDM process is usually evaluated in terms of surface roughness, existence of cracks, voids and recast layer on the surface of product, after machining. Unfortunately, the high heat generated on the electrically discharged material during the EDM process decreases the quality of products. Carbon nanotubes display unexpected strength and unique electrical and thermal properties. Multi-wall carbon nanotubes are therefore on purpose added to the dielectric used in the EDM process to improve its performance when machining the AISI H13 tool steel, by means of copper electrodes. Some EDM parameters such as material removal rate, electrode wear rate, surface roughness and recast layer are here first evaluated, then compared to the outcome of EDM performed without using nanotubes mixed to the dielectric. Independent variables investigated are pulse on time, peak current and interval time. Experimental evidences show that EDM process operated by mixing multi-wall carbon nanotubes within the dielectric looks more efficient, particularly if machining parameters are set at low pulse of energy.

Plasma Wall interaction in the IGNITOR machine

NASA Astrophysics Data System (ADS)

Ferro, C.

1998-11-01

One of the critical issues in ignited machines is the management of the heat and particle exhaust without degradation of the plasma quality (pollution and confinement time) and without damage of the material facing the plasma. The IGNITOR machine has been conceived as a ``limiter" device, i.e., with the plasma leaning nearly on the entire surface of the first wall. Peak heat loads can easily be maintained at values lower than 1.35 MW/m^2 even considering displacements of the plasma column^1. This ``limiter" choice is based on the operational performances of high density, high field machines which suggests that intrinsic physics processes in the edge of the plasma are effective in spreading heat loads and maintaining the plasma pollution at a low level. The possibility of these operating scenarios has been demonstrated recently by different machines both in limiter and divertor configurations. The basis for the different physical processes that are expected to influence the IGNITOR edge parameters ^2 are discussed and a comparison with the latest experimental results is given. ^1 C. Ferro, G. Franzoni, R. Zanino, ENEA Internal Report RT/ERG/FUS/94/14. ^2 C. Ferro, R. Zanino, J. Nucl. Mater. 543, 176 (1990).

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.

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).

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors

PubMed Central

Yang, Wei; You, Kaiming; Li, Wei; Kim, Young-il

2017-01-01

This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel’s global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point’s plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel. PMID:28141829

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors.

PubMed

Xu, Zirui; Yang, Wei; You, Kaiming; Li, Wei; Kim, Young-Il

2017-01-01

This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel's global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point's plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel.

BLAISDELL SLOW SAND FILTER WASHING MACHINE. VIEW LOOKING SOUTH. THE ...

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

BLAISDELL SLOW SAND FILTER WASHING MACHINE. VIEW LOOKING SOUTH. THE OUTSIDE FACE OF THE NORTH WALL OF SETTLING RESERVOIR NO. 3 IS SEEN AT THE RIGHT. THE SETTLING RESERVOIR IS ELEVATED ABOVE THE FILTERING RESERVOIR TO ACHIEVE GRAVITY WATER FLOW FROM THE SETTLING RESERVOIR INTO THE FILTERING RESERVOIR. - Yuma Main Street Water Treatment Plant, Blaisdell Slow Sand Filter Washing Machine, Jones Street at foot of Main Street, Yuma, Yuma County, AZ

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...

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...

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.

Optimization and application of blasting parameters based on the "pushing-wall" mechanism

NASA Astrophysics Data System (ADS)

Ren, Feng-yu; Sow, Thierno Amadou Mouctar; He, Rong-xing; Liu, Xin-rui

2012-10-01

The large structure parameter of a sublevel caving method was used in Beiminghe iron mine. The ores were generally lower than the medium hardness and easy to be drilled and blasted. However, the questions of boulder yield, "pushing-wall" accident rate, and brow damage rate were not effectively controlled in practical blasting. The model test of a similar material shows that the charge concentration of bottom blastholes in the sector is too high; the pushing wall is the fundamental reason for the poor blasting effect. One of the main methods to adjust the explosive distribution is to increase the length of charged blastholes. Therefore, the field tests with respect to increasing the length of uncharged blastholes were made in 12# stope of -95 subsection and 6# stope of Beiminghe iron mine. This paper took the test result of 12# stope as an example to analyze the impact of charge structure on blasting effect and design an appropriate blasting parameter that is to similar to No.12 stope.

30 CFR 57.22215 - Separation of intake and return air (I-A, II-A, III, and V-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... Separation of intake and return air (I-A, II-A, III, and V-A mines). Main intake and return air currents... for separation of air currents. Such wall or partition shall be constructed of reinforced concrete or... separation of main air currents in the same opening. Flexible ventilation tubing shall not exceed 250 feet in...

30 CFR 57.22215 - Separation of intake and return air (I-A, II-A, III, and V-A mines).

Code of Federal Regulations, 2011 CFR

2011-07-01

... Separation of intake and return air (I-A, II-A, III, and V-A mines). Main intake and return air currents... for separation of air currents. Such wall or partition shall be constructed of reinforced concrete or... separation of main air currents in the same opening. Flexible ventilation tubing shall not exceed 250 feet in...

Electrical machine

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

De Bock, Hendrik Pieter Jacobus; Alexander, James Pellegrino; El-Refaie, Ayman Mohamed Fawzi

2016-06-21

An apparatus, such as an electrical machine, is provided. The apparatus can include a rotor defining a rotor bore and a conduit disposed in and extending axially along the rotor bore. The conduit can have an annular conduit body defining a plurality of orifices disposed axially along the conduit and extending through the conduit body. The rotor can have an inner wall that at least partially defines the rotor bore. The orifices can extend through the conduit body along respective orifice directions, and the rotor and conduit can be configured to provide a line of sight along the orifice directionmore » from the respective orifices to the inner wall.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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.

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

Dowel pin

DOEpatents

Wojcik, Thaddeus A.

1978-01-01

Two abutting members are locked together by reaming a hole entirely through one member and at least partly through the other, machining a circular groove in each through hole just below the surface of the member, press fitting a dowel pin having a thin wall extension on at least one end thereof into the hole in both members, a thin wall extension extending into each through hole, crimping or snapping the thin wall extension into the grooves to positively lock the dowel pin in place and, if necessary, tack welding the end of the thin-wall extension in place.

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.

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm.

PubMed

Banchhor, Sumit K; Londhe, Narendra D; Araki, Tadashi; Saba, Luca; Radeva, Petia; Laird, John R; Suri, Jasjit S

2017-12-01

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk. This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases. The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively. The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hydraulic servo control spool valve

DOEpatents

Miller, Donald M.

1983-01-01

A servo operated spool valve having a fixed sleeve and axially movable spool. The sleeve is machined in two halves to form a long, narrow tapered orifice slot across which a transverse wall of the spool is positioned. The axial position of the spool wall along the slot regulates the open orifice area with extreme precision.

Characterization of Flow and Ohm's Law in the Rotating Wall Machine

NASA Astrophysics Data System (ADS)

Hannum, David; Brookhart, M.; Forest, C. B.; Kendrick, R.; Mengin, G.; Paz-Soldan, C.

2010-11-01

The rotating wall machine is a linear screw-pinch built to study the role of different electromagnetic boundary conditions on the Resistive Wall Mode (RWM). Its plasma is created by an array of electrostatic washer guns which can be biased to discharge up to 1 kA of current each. Individual flux ropes from the guns shear, merge, and expand into a 20 cm diameter, ˜1 m long plasma column. Langmuir (singletip) and tri-axial B-dot probes move throughout the column to measure radial and axial profiles of key plasma parameters. As the plasma current increases, more H2 fuel is ionized, raising ne to 5 x10^20 m-3 while Te stays at a constant 3 eV. The electron density expands to the wall while the current density (Jz) stays pinched to the central axis. E xB and diamagnetic drifts create radially and axially sheared plasma rotation. Plasma resistivity follows the Spitzer model in the core while exceeding it at the edge. These measurements improve the model used to predict the RWM growth rate.

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

Feasibility of CO2 Sequestration as a Closure Option for Underground Coal Mine

NASA Astrophysics Data System (ADS)

Ray, Sutapa; Dey, Kaushik

2018-04-01

The Kyoto Protocol, 1998, was signed by member countries to reduce greenhouse gas (GHG) emissions to a minimum acceptable level. India agreed to Kyoto Protocol since 2002 and started its research on GHG mitigation. Few researchers have carried out research work on CO2 sequestration in different rock formations. However, CO2 sequestration in abandoned mines has yet not drawn its attention largely. In the past few years or decades, a significant amount of research and development has been done on Carbon Capture and Storage (CCS) technologies, since it is a possible solution for assuring less emission of CO2 to the atmosphere from power plants and some other major industrial plants. CCS mainly involves three steps: (a) capture and compression of CO2 from source (power plants and industrial areas), (b) transportation of captured CO2 to the storage mine and (c) injecting CO2 into underground mine. CO2 is stored at an underground mine mainly in three forms: (1) adsorbed in the coals left as pillars of the mine, (2) absorbed in water through a chemical process and (3) filled in void with compressed CO2. Adsorption isotherm is a graph developed between the amounts of adsorbate adsorbed on the surface of adsorbent and the pressure at constant temperature. Various types of adsorption isotherms are available, namely, Freundlich, Langmuir and BET theory. Indian coal is different in origin from most of the international coal deposits and thus demands isotherm experiments of the same to arrive at the right adsorption isotherm. To carry out these experiments, adsorption isotherm set up is fabricated in the laboratory with a capacity to measure the adsorbed volume up to a pressure level of 100 bar. The coal samples are collected from the pillars and walls of the underground coal seam using a portable drill machine. The adsorption isotherm experiments have been carried out for the samples taken from a mine. From the adsorption isotherm experiments, Langmuir Equation is found to be more acceptable as compared to Freundlich's and BET adsorption isotherm models. CO2 is soluble in water and is reversibly formed carbonic acid. It is a weak acid since its ionization in water is incomplete. The CO2 solubility in water is estimated from the experimental results published by Wiebe and Gaddy. In most of the cases of abandoned mines, the chances of available air filled void space is limited as the level of operation is below the water table. So it is expected that the void would be completely filled with water. During this research investigation, the practical experimentation for CO2 sequestration was not within the scope. Thus, one operating mine was considered for the feasibility study. The sequestrated quantities of CO2 in terms of adsorbed volume and soluble volume were quantified. The cost of the CO2 was taken from the standard international literature. The sealing cost of the shaft was also considered. Costs of CO2 sequestration for different pressure were estimated for the mine.

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.

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

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.

An FMM-FFT Accelerated SIE Simulator for Analyzing EM Wave Propagation in Mine Environments Loaded With Conductors

PubMed Central

Sheng, Weitian; Zhou, Chenming; Liu, Yang; Bagci, Hakan; Michielssen, Eric

2018-01-01

A fast and memory efficient three-dimensional full-wave simulator for analyzing electromagnetic (EM) wave propagation in electrically large and realistic mine tunnels/galleries loaded with conductors is proposed. The simulator relies on Muller and combined field surface integral equations (SIEs) to account for scattering from mine walls and conductors, respectively. During the iterative solution of the system of SIEs, the simulator uses a fast multipole method-fast Fourier transform (FMM-FFT) scheme to reduce CPU and memory requirements. The memory requirement is further reduced by compressing large data structures via singular value and Tucker decompositions. The efficiency, accuracy, and real-world applicability of the simulator are demonstrated through characterization of EM wave propagation in electrically large mine tunnels/galleries loaded with conducting cables and mine carts. PMID:29726545

Sinkhole-type subsidence over abandoned coal mines in St. David, Illinois. Mine subsidence report, St. David, Illinois. A field survey and analysis of mine subsidence of abandoned coal mines in St. David, Illinois

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

Wildanger, E.G.; Mahar, J.; Nieto, A.

1980-01-01

This study examined the geologic data, mining history, and subsidence trends of the St. David region. Mine subsidence has occurred due to collapse of the abandoned mine workings. The known subsidence areas have been mapped and described. Results of the study include: (1) St. David has been undermined by both large shipping mines and smaller local mines; (2) sinkholes will continue to develop in this area in response to rock failure and roof collapse above the abandoned mine workings; (3) some primary factors that contribute to the sinkhole problems are the undermining and roof rock composition; (4) sinkholes will bemore » smaller in the future; (5) ten of the 63 sinkholes occurred close enough to structures to cause damage, and only six sinkholes caused damage; (6) ways to minimize potential damage to future homes from sinkhole subsidence are manageable; (7) threats to residents lie in the collapse of heavy walls, brick chimneys, breaks in gas, water, or electrical lines; and (8) location of future subsidence is not predictable. (DP)« less

A mechanism for high wall-rock velocities in rockbursts

USGS Publications Warehouse

McGarr, A.

1997-01-01

Considerable evidence has been reported for wall-rock velocities during rockbursts in deep gold mines that are substantially greater than ground velocities associated with the primary seismic events. Whereas varied evidence suggests that slip across a fault at the source of an event generates nearby particle velocities of, at most, several m/s, numerous observations, in nearby damaged tunnels, for instance, imply wall-rock velocities of the order of 10 m/s and greater. The common observation of slab buckling or breakouts in the sidewalls of damaged excavations suggests that slab flexure may be the mechanism for causing high rock ejection velocities. Following its formation, a sidewall slab buckles, causing the flexure to increase until the stress generated by flexure reaches the limit 5 that can be supported by the sidewall rock. I assume here that S is the uniaxial compressive strength. Once the flexural stress exceeds S, presumably due to the additional load imposed by a nearby seismic event, the slab fractures and unflexes violently. The peak wall-rock velocity v thereby generated is given by v=(3 + 1-??2/2)1 2 S/?????E for rock of density ??, Young's modulus E, and Poisson's ratio ??. Typical values of these rock properties for the deep gold mines of South Africa yield v= 26 m/s and for especially strong quartzites encountered in these same mines, v> 50m/s. Even though this slab buckling process leads to remarkably high ejection velocities and violent damage in excavations, the energy released during this failure is only a tiny fraction of that released in the primary seismic event, typically of magnitude 2 or greater.

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.

15. Detail view of the south elevation brick work at ...

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

15. Detail view of the south elevation brick work at the west end, with scale. (Note initials and date carved into the bricks and how the coursing does not line up. The end bricks could be an early repair to the masonry or be the result of replacing wood walls with brick and what is evident is how the new walls were keyed into the gable walls. In either scenario, the mortar has been poorly repointed and is a later change.) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

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.

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.

Method of controlling the side wall thickness of a turbine nozzle segment for improved cooling

DOEpatents

Burdgick, Steven Sebastian

2002-01-01

A gas turbine nozzle segment has outer and inner bands and a vane extending therebetween. Each band has a side wall, a cover and an impingement plate between the cover and nozzle wall defining two cavities on opposite sides of the impingement plate. Cooling steam is supplied to one cavity for flow through apertures of the impingement plate to cool the nozzle wall. The side wall of the band has an inturned flange defining with the nozzle wall an undercut region. The outer surface of the side wall is provided with a step prior to welding the cover to the side wall. A thermal barrier coating is applied in the step and, after the cover is welded to the side wall, the side wall is finally machined to a controlled thickness removing all, some or none of the coating.

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

Automated Composites Processing Technology: Film Module

NASA Technical Reports Server (NTRS)

Hulcher, A. Bruce

2004-01-01

NASA's Marshall Space Flight Center (MSFC) has developed a technology that combines a film/adhesive laydown module with fiber placement technology to enable the processing of composite prepreg tow/tape and films, foils or adhesives on the same placement machine. The development of this technology grew out of NASA's need for lightweight, permeation-resistant cryogenic propellant tanks. Autoclave processing of high performance composites results in thermally-induced stresses due to differences in the coefficients of thermal expansion of the fiber and matrix resin components. These stresses, together with the reduction in temperature due to cryogen storage, tend to initiate microcracking within the composite tank wall. One way in which to mitigate this problem is to introduce a thin, crack-resistant polymer film or foil into the tank wall. Investigation into methods to automate the processing of thin film or foil materials into composites led to the development of this technology. The concept employs an automated film supply and feed module that may be designed to fit existing fiber placement machines, or may be designed as integral equipment to new machines. This patent-pending technology can be designed such that both film and foil materials may be processed simultaneously, leading to a decrease in part build cycle time. The module may be designed having a compaction device independent of the host machine, or may utilize the host machine's compactor. The film module functions are controlled by a dedicated system independent of the fiber placement machine controls. The film, foil, or adhesive is processed via pre-existing placement machine run programs, further reducing operational expense.

Comparison of Distributed Acoustic Sensing (DAS) from Fiber-Optic Cable to Three Component Geophones in an Underground Mine

NASA Astrophysics Data System (ADS)

Speece, M. A.; Nesladek, N. J.; Kammerer, C.; Maclaughlin, M.; Wang, H. F.; Lord, N. E.

2017-12-01

We conducted experiments in the Underground Education Mining Center on the Montana Tech campus, Butte, Montana, to make a direct comparison between Digital Acoustic Sensing (DAS) and three-component geophones in a mining setting. The sources used for this project where a vertical sledgehammer, oriented shear sledgehammer, and blasting caps set off in both unstemmed and stemmed drillholes. Three-component Geospace 20DM geophones were compared with three different types of fiber-optic cable: (1) Brugg strain, (2) Brugg temperature, and (3) Optical Cable Corporation strain. We attached geophones to the underground mine walls and on the ground surface above the mine. We attached fiber-optic cables to the mine walls and placed fiber-optic cable in boreholes drilled through an underground pillar. In addition, we placed fiber-optic cables in a shallow trench at the surface of the mine. We converted the DAS recordings from strain rate to strain prior to comparison with the geophone data. The setup of the DAS system for this project led to a previously unknown triggering problem that compromised the early samples of the DAS traces often including the first-break times on the DAS records. Geophones clearly recorded the explosives; however, the large amount of energy and its close distance from the fiber-optic cables seemed to compromise the entire fiber loop. The underground hammer sources produced a rough match between the DAS records and the geophone records. However, the sources on the surface of the mine, specifically the sources oriented inline with the fiber-optic cables, produced a close match between the fiber-optic traces and the geophone traces. All three types of fiber-optic cable that were in the mine produced similar results, and one type did not clearly outperform the others. Instead, the coupling of the cable to rock appears to be the most important factor determining DAS data quality. Moreover, we observed the importance of coupling in the boreholes, where fiber-optic cables that were pressed against the rock face with a spacer outperformed fiber-optic cables that were fully embedded within the grout filling the inside of the borehole.

LONG-TERM PERFORMANCE MONITORING FOR A PERMEABLE REACTIVE BARRIER AT THE U.S. COAST GUARD SUPPORT CENTER, ELIZABETH CITY, NORTH CAROLINA

EPA Science Inventory

A continuous hanging iron wall was installed in June, 1996, at the U.S. Coast Guard (USCG) Support Center near Elizabeth City, NC, United States, to treat overlapping plumes of chromate and chlorinated solvent compounds. The wall was emplaced using a continuous trenching machine...

Traction sheave elevator, hoisting unit and machine space

DOEpatents

Hakala, Harri; Mustalahti, Jorma; Aulanko, Esko

2000-01-01

Traction sheave elevator consisting of an elevator car moving along elevator guide rails, a counterweight moving along counterweight guide rails, a set of hoisting ropes (3) on which the elevator car and counterweight are suspended, and a drive machine unit (6) driving a traction sheave (7) acting on the hoisting ropes (3) and placed in the elevator shaft. The drive machine unit (6) is of a flat construction. A wall of the elevator shaft is provided with a machine space with its open side facing towards the shaft, the essential parts of the drive machine unit (6) being placed in the space. The hoisting unit (9) of the traction sheave elevator consists of a substantially discoidal drive machine unit (6) and an instrument panel (8) mounted on the frame (20) of the hoisting unit.

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

Installation Restoration General Environmental Technology Development. Task 3. Guidelines for In-Place Closure of Dry Lagoons. Volume 2. Evaluation of In-Place Closure Technologies.

DTIC Science & Technology

1984-01-01

fac- turs are described as follows: (a) Basil stability -- Determination of horizontal movement in the slurry wall or the ground behind the wall...SG-l.2) M Acid mine drainage (FeSO4 pH 3) N Liqnin (in Ca++ solution) N Orqanic residues trom pesticide manutacture N Alcohol M/H asiqnificant

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.

Geochemical evolution of a high arsenic, alkaline pit-lake in the Mother Lode Gold District, California

USGS Publications Warehouse

Savage, Kaye S.; Ashley, Roger P.; Bird, Dennis K.

2009-01-01

The Harvard orebody at the Jamestown gold mine, located along the Melones fault zone in the southern Mother Lode gold district, California, was mined in an open-pit operation from 1987 to 1994. Dewatering during mining produced a hydrologic cone of depression; recovery toward the premining ground-water configuration produced a monomictic pit lake with alkaline Ca-Mg-HCO3-SO4–type pit water, concentrations of As up to 1,200 μg/L, and total dissolved solids (TDS) up to 2,000 mg/L. In this study, pit-wall rocks were mapped and chemically analyzed to provide a context for evaluating observed variability in the composition of the pit-lake waters in relationship to seasonal weather patterns. An integrated hydrogeochemical model of pit-lake evolution based on observations of pit-lake volume, water composition (samples collected between 1998–2000, 2004), and processes occurring on pit walls was developed in three stages using the computer code PHREEQC. Stage 1 takes account of seasonally variable water fluxes from precipitation, evaporation, springs, and ground water, as well as lake stratification and mixing processes. Stage 2 adds CO2fluxes and wall-rock interactions, and stage 3 assesses the predictive capability of the model.Two major geologic units in fault contact comprise the pit walls. The hanging wall is composed of interlayered slate, metavolcanic and metavolcaniclastic rocks, and schists; the footwall rocks are chlorite-actinolite and talc-tremolite schists generated by metasomatism of greenschist-facies mafic and ultramafic igneous rocks. Alteration in the ore zone provides evidence for mineralizing fluids that introduced CO2, S, and K2O, and redistributed SiO2. Arsenian pyrite associated with the alteration weathers to produce goethite and jarosite on pit walls and in joints, as well as copiapite and hexahydrite efflorescences that accumulate on wall-rock faces during dry California summers. All of these pyrite weathering products incorporate arsenic at concentrations from <100 up to 1,200 ppm. In the pit lake, pH and TDS reach seasonal highs in the summer epilimnion; pH is lowest in the summer hypolimnion. Arsenic and bicarbonate covary in the hypolimnion, rising as stratification proceeds and declining during winter rains. The computational model suggests that water fluxes alone do not account for this seasonal variability. Loss of CO2 to the atmosphere, interaction with pit walls including washoff of efflorescent salts during the first flush and seasonal rainfall, and arsenic sorption appear to contribute to the observed pit-lake characteristics.

62. SIXTEEN INCH GUN MOUNTED ON THE MACHINING LATHE; LOOKING ...

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

62. SIXTEEN INCH GUN MOUNTED ON THE MACHINING LATHE; LOOKING WSW. THE GUN ITSELF EXTENDS BEYOND THE BRICK ARCHES OF THE MAIN SHOP FLOOR'S W WALL AND INTO THE W AISLE. THE LATHE'S CUTTING HEAD CAN BE SEEN AT THE RIGHT CENTER OF THE VIEW. (Ryan) - Watervliet Arsenal, Building No. 110, Hagner Road between Schull & Whittemore Roads, Watervliet, Albany County, NY

45. WEST TO CIRCA 1900 SHEET METAL SHEAR, THE MACHINE ...

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

45. WEST TO CIRCA 1900 SHEET METAL SHEAR, THE MACHINE USED TO CUT SHEET METAL USED IN WINDMILLS AND WATER TANKS. IN THE BACKGROUND IS THE INTERIOR WEST WALL OF THE FACTORY, ITS SHELVES BEARING WATER PUMPS, PARTS FOR PUMPS AND WATER SUPPLY EQUIPMENT, AND NEW OLD STOCK MERCHANDISE. - Kregel Windmill Company Factory, 1416 Central Avenue, Nebraska City, Otoe County, NE

Technology Transfer at Edgar Mine: Phase 1; October 2016

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

Augustine, Chad R.; Bauer, Stephen; Nakagawa, Masami

The objective of this project is to study the flow of fluid through the fractures and to characterize the efficiency of heat extraction (heat transfer) from the test rock mass in the Edgar Mine, managed by Colorado School of Mines in Idaho Springs, CO. The experiment consists of drilling into the wall of the mine and fracturing the rock, characterizing the size and nature of the fracture network, circulating fluid through the network, and measuring the efficiency of heat extraction from the 'reservoir' by monitoring the temperature of the 'produced' fluid with time. This is a multi-year project performed asmore » a collaboration between the National Renewable Energy Laboratory, Colorado School of Mines and Sandia National Laboratories and carried out in phases. This report summarizes Phase 1: Selection and characterization of the location for the experiment, and outlines the steps for Phase 2: Circulation Experiments.« less

Impact resistance of guards on grinding machines.

PubMed

Mewes, Detlef; Mewes, Olaf; Herbst, Peter

2011-01-01

Guards on machine tools are meant to protect persons from injuries caused by parts ejected with high kinetic energy from the machine's working zone. With respect to stationary grinding machines, Standard No. EN 13218:2002, therefore, specifies minimum wall thicknesses for guards. These values are mainly based on estimations and experience instead of systematic experimental investigations. This paper shows to what extent simple impact tests with standardizable projectiles can be used as basis for the evaluation of the impact resistance of guards, provided that not only the kinetic energy of the projectiles used but also, among others, their geometry corresponds to the abrasive product fragments to be expected.

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...

Flooding at Iron-Ore Mine, SE Brazil

NASA Image and Video Library

2015-11-14

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

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.

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

PubMed

Saba, Luca; Jain, Pankaj K; Suri, Harman S; Ikeda, Nobutaka; Araki, Tadashi; Singh, Bikesh K; Nicolaides, Andrew; Shafique, Shoaib; Gupta, Ajay; Laird, John R; Suri, Jasjit S

2017-06-01

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.

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

Marine origin of pyritic sulfur in the Lower Bakerstown coal bed, Castleman coal field, Maryland (U.S.A.)

USGS Publications Warehouse

Lyons, P.C.; Whelan, J.F.; Dulong, F.T.

1989-01-01

The amount, kind, distribution, and genesis of pyrite in the Lower Bakerstown coal bed in a 150 ?? 15 m area of the Bettinger mine, Castleman coal field, Maryland, were studied by various analytical techniques. The mined coal, which had a nonmarine roof rock, contained 1.4-2.8 wt.% total sulfur, generally much lower than the high-sulfur coal (> 3.0 wt.% total S) to the north, which is associated with marine roof rocks. Small-scale systematic and nonsystematic variations in total sulfur and pyrite distribution were found in the mined area. In the column sample, most of the pyrite was found in the upper 9 cm of the 69-cm-thick mined coal and occurred mainly as a pyrite lens containing cell fillings in seed-fern tissue (coal ball). As-bearing pyrite was detected by laser microprobe techniques in the cell walls of this tissue but not elsewhere in the column sample. This may indicate that the As was derived from decomposition of organic matter in the cell walls. The sulfur isotopic composition and distribution of pyrite in the coal are consistent with introduction of marine sulfate shortly after peat deposition, followed by bacterial reduction and pyrite precipitation. Epigenetic cleat pyrite in the coal is isotopically heavy, implying that later aqueous sulfate was 34S-enriched. ?? 1989.

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.

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

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

DEM study of granular flow around blocks attached to inclined walls

NASA Astrophysics Data System (ADS)

Samsu, Joel; Zhou, Zongyan; Pinson, David; Chew, Sheng

2017-06-01

Damage due to intense particle-wall contact in industrial applications can cause severe problems in industries such as mineral processing, mining and metallurgy. Studying the flow dynamics and forces on containing walls can provide valuable feedback for equipment design and optimising operations to prolong the equipment lifetime. Therefore, solids flow-wall interaction phenomena, i.e. induced wall stress and particle flow patterns should be well understood. In this work, discrete element method (DEM) is used to study steady state granular flow in a gravity-fed hopper like geometry with blocks attached to an inclined wall. The effects of different geometries, e.g. different wall angles and spacing between blocks are studied by means of a 3D DEM slot model with periodic boundary conditions. The findings of this work include (i) flow analysis in terms of flow patterns and particle velocities, (ii) force distributions within the model geometry, and (iii) wall stress vs. model height diagrams. The model enables easy transfer of the key findings to other industrial applications handling granular materials.

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

Support Vector Machines for Multitemporal and Multisensor Change Detection in a Mining Area

NASA Astrophysics Data System (ADS)

Hecheltjen, Antje; Waske, Bjorn; Thonfeld, Frank; Braun, Matthias; Menz, Gunter

2010-12-01

Long-term change detection often implies the challenge of incorporating multitemporal data from different sensors. Most of the conventional change detection algorithms are designed for bi-temporal datasets from the same sensors detecting only the existence of changes. The labeling of change areas remains a difficult task. To overcome such drawbacks, much attention has been given lately to algorithms arising from machine learning, such as Support Vector Machines (SVMs). While SVMs have been applied successfully for land cover classifications, the exploitation of this approach for change detection is still in its infancy. Few studies have already proven the applicability of SVMs for bi- and multitemporal change detection using data from one sensor only. In this paper we demonstrate the application of SVM for multitemporal and -sensor change detection. Our study site covers lignite open pit mining areas in the German state North Rhine-Westphalia. The dataset consists of bi-temporal Landsat data and multi-temporal ERS SAR data covering two time slots (2001 and 2009). The SVM is conducted using the IDL program imageSVM. Change is deduced from one time slot to the next resulting in two change maps. In contrast to change detection, which is based on post-classification comparison, change detection is seen here as a specific classification problem. Thus, changes are directly classified from a layer-stack of the two years. To reduce the number of change classes, we created a change mask using the magnitude of Change Vector Analysis (CVA). Training data were selected for different change classes (e.g. forest to mining or mining to agriculture) as well as for the no-change classes (e.g. agriculture). Subsequently, they were divided in two independent sets for training the SVMs and accuracy assessment, respectively. Our study shows the applicability of SVMs to classify changes via SVMs. The proposed method yielded a change map of reclaimed and active mines. The use of ERS SAR data, however, did not add to the accuracy compared to Landsat data only. A great advantage compared to other change detection approaches are the labeled change maps, which are a direct output of the methodology. Our approach also overcomes the drawback of post-classification comparison, namely the propagation of classification inaccuracies.

United States Air Force Civil Engineering Additive Manufacturing Applications: Tools and Jigs

DTIC Science & Technology

2016-03-24

A faulty wheel design and tire inflation system on the Mine Resistant Ambush Protected Vehicle (MRAP) in theatre was identified, designed , and...hook (Figure 12). Walls on the four sides of the bracket would hold the sensors in place on the robot. As this was the initial design , satisfactory...be assembled prior to the printing process. Using squares placed at standardized distances across the bracket, walls were designed to slide into

Digital Family History Data Mining with Neural Networks: A Pilot Study.

PubMed

Hoyt, Robert; Linnville, Steven; Thaler, Stephen; Moore, Jeffrey

2016-01-01

Following the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, electronic health records were widely adopted by eligible physicians and hospitals in the United States. Stage 2 meaningful use menu objectives include a digital family history but no stipulation as to how that information should be used. A variety of data mining techniques now exist for these data, which include artificial neural networks (ANNs) for supervised or unsupervised machine learning. In this pilot study, we applied an ANN-based simulation to a previously reported digital family history to mine the database for trends. A graphical user interface was created to display the input of multiple conditions in the parents and output as the likelihood of diabetes, hypertension, and coronary artery disease in male and female offspring. The results of this pilot study show promise in using ANNs to data mine digital family histories for clinical and research purposes.

Data Mining Methods for Recommender Systems

NASA Astrophysics Data System (ADS)

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

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

Deformation and failure mechanism of secondary cell wall in Spruce late wood

NASA Astrophysics Data System (ADS)

Adusumalli, Ramesh-Babu; Raghavan, Rejin; Ghisleni, Rudy; Zimmermann, Tanja; Michler, Johann

2010-08-01

The deformation and failure of the secondary cell wall of Spruce wood was studied by in-situ SEM compression of micropillars machined by the focused ion beam technique. The cell wall exhibited yield strength values of approximately 160 MPa and large scale plasticity. High resolution SEM imaging post compression revealed bulging of the pillars followed by shear failure. With additional aid of cross-sectional analysis of the micropillars post compression, a model for deformation and failure mechanism of the cell wall has been proposed. The cell wall consists of oriented cellulose microfibrils with high aspect ratio embedded in a hemicellulose-lignin matrix. The deformation of the secondary wall occurs by asymmetric out of plane bulging because of buckling of the microfibrils. Failure of the cell wall following the deformation occurs by the formation of a shear or kink band.

Review of fire test methods and incident data for portable electric cables in underground coal mines

NASA Astrophysics Data System (ADS)

Braun, E.

1981-06-01

Electrically powered underground coal mining machinery is connected to a load center or distribution box by electric cables. The connecting cables used on mobile machines are required to meet fire performance requirements defined in the Code of Federal Regulations. This report reviews Mine Safety and Health Administration's (MSHA) current test method and compares it to British practices. Incident data for fires caused by trailing cable failures and splice failures were also reviewed. It was found that the MSHA test method is more severe than the British but that neither evaluated grouped cable fire performance. The incident data indicated that the grouped configuration of cables on a reel accounted for a majority of the fires since 1970.

Development of a kolanut peeling device.

PubMed

Kareem, I; Owolarafe, O K; Ajayi, O A

2014-10-01

A kolanut peeling machine was designed, constructed and evaluated for the postharvest processing of the seed. The peeling machine consists of a standing frame, peeling unit and hopper. The peeling unit consists of a special paddle, which mixes the kolanut, rubs them against one another and against the wall of the barrel and also conveys the kolanut to the outlet. The performance of the kolanut peeling machine was evaluated for its peeling efficiency at different moisture content (53.0, 57.6, 61.4 % w.b.) and speeds of operation of the machine. The result of the analysis of variance shows that the main factors and their interaction had significant effects (p < 0.05) on the peeling efficiency of the machine. The result also shows that the peeling efficiency of the machine increased as the moisture content increase and decreased with increase in machine speed. The highest efficiency of the machine was 60.3 % at a moisture content of 61.4 % w.b. and speed of 40 rpm.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Geology of the Ar Rahail ancient gold mine, Kingdom of Saudi Arabia

USGS Publications Warehouse

White, Willis H.; Samater, Rashid M.; Doebrich, Jeff L.

1987-01-01

Pre-existing northwest-trending faults, possibly re-opened by stock emplacement, were invaded by later fluids that precipitated barren quartz veins and, in the adjacent faulted wall rocks, anomalous gold and arsenic. Gold, however, is restricted to the narrow structures, and, although values as much as 4.2 g/t are present, the tonnages are inadequate for profitable mining. No further work is recommended, because the hoped for dissemination of gold between faults does not exist.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

Poux, F.; Hallot, P.; Neuville, R.; Billen, R.

2016-10-01

Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.

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

PubMed

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

2014-03-01

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

Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

PubMed

VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

2018-04-17

Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

KSC-2012-3070

NASA Image and Video Library

2012-05-22

CAPE CANAVERAL, Fla. – A team of competitors works with a robotic vehicle taking 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-2012-3093

NASA Image and Video Library

2012-05-26

CAPE CANAVERAL, Fla. – The team from the University of Alabama team took home the Joe Kosmo Award for Excellence for designing and operating the winning robotic vehicle during NASA's Lunabotics Mining Competition. 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

Theoretical prediction of gold vein location in deposits originated by a wall magma intrusion

NASA Astrophysics Data System (ADS)

Martin, Pablo; Maass-Artigas, Fernando; Cortés-Vega, Luis

2016-05-01

The isotherm time-evolution resulting from the intrusion of a hot dike in a cold rock is analized considering the general case of nonvertical walls. This is applied to the theoretical prediction of the gold veins location due to isothermal evolution. As in previous treatments earth surface effects are considered and the gold veins are determined by the envelope of the isotherms. The locations of the gold veins in the Callao mines of Venezuela are now well predicted. The new treatment is now more elaborated and complex that in the case of vertical walls, performed in previous papers, but it is more adequated to the real cases as the one in El Callao, where the wall is not vertical.

Anchoring of development workings in a zone of influence of mining in case of the level anchoring system

NASA Astrophysics Data System (ADS)

Demin, V. F.; Fofanov, O. B.; Demina, T. V.; Yavorskiy, V. V.

2017-02-01

Regularities of the change of the stress-strain state of coal containing rock masses, depending on mining-geological factors, were revealed. These factors allow establishing rational parameters of anchoring of wall rocks to enhance the stability of development workings. Specific conditions of the deflected mode, displays of rock pressure, terms of maintenance depending on technological parameters are investigated. Researches allowed determining the degree of their development influence on the efficiency of application of the anchoring of the hollow making and will allow a reasonable application of anchoring certificates, provide stability of the rocks mining and reduce expenses on its realization and maintenance.

Design and Development of E3 Antenna Container,

DTIC Science & Technology

1985-09-03

reinforced with square tubing. The walls and ceiling shall be insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the...ceiling shall be insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the Edgewater Machine & Fabricator’s facility...insulated with expanded polystyrene . TEST LOCATION - This test will be performed at the Edgewater Machine & Fabricator’s facility located at 200 N

An Analysis of Hardware-Assisted Virtual Machine Based Rootkits

DTIC Science & Technology

2014-06-01

certain aspects of TPM implementation just to name a few. HyperWall is an architecture proposed by Szefer and Lee to protect guest VMs from...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) The use of virtual machine (VM) technology has expanded rapidly since AMD and Intel implemented ...Intel VT-x implementations of Blue Pill to identify commonalities in the respective versions’ attack methodologies from both a functional and technical

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

NASA Astrophysics Data System (ADS)

Brescia, Massimo

2012-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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 75.825 - Power centers.

Code of Federal Regulations, 2014 CFR

2014-07-01

....825 Power centers. (a) Main disconnecting switch. The power center supplying high voltage power to the continuous mining machine must be equipped with a main disconnecting switch that, when in the open position... the main disconnecting switch required in paragraph (a) of this section, the power center must be...

30 CFR 75.825 - Power centers.

Code of Federal Regulations, 2012 CFR

2012-07-01

....825 Power centers. (a) Main disconnecting switch. The power center supplying high voltage power to the continuous mining machine must be equipped with a main disconnecting switch that, when in the open position... the main disconnecting switch required in paragraph (a) of this section, the power center must be...

30 CFR 75.825 - Power centers.

Code of Federal Regulations, 2013 CFR

2013-07-01

....825 Power centers. (a) Main disconnecting switch. The power center supplying high voltage power to the continuous mining machine must be equipped with a main disconnecting switch that, when in the open position... the main disconnecting switch required in paragraph (a) of this section, the power center must be...

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...

Author Detection on a Mobile Phone

DTIC Science & Technology

2011-03-01

handwriting , and to mine sales data for profitable trends. Two broad categories of machine learning are supervised learn- ing and unsupervised learning...evaluation,” AI 2006: Advances in Artificial Intelligence, p. 1015–1021, 2006. [23] “Gartner says worldwide mobile phone sales grew 17 per cent in first

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...

Development of ZL400 Mine Cooling Unit Using Semi-Hermetic Screw Compressor and Its Application on Local Air Conditioning in Underground Long-Wall Face

NASA Astrophysics Data System (ADS)

Chu, Zhaoxiang; Ji, Jianhu; Zhang, Xijun; Yan, Hongyuan; Dong, Haomin; Liu, Junjie

2016-12-01

Aiming at heat injuries occurring in the process of deep coal mining in China, a ZL400 mine-cooling unit employing semi-hermetic screw compressor with a cooling capacity of 400 kW is developed. This paper introduced its operating principle, structural characteristics and technical indexes. By using the self-built testing platform, some parameters for indication of its operation conditions were tested on the ground. The results show that the aforementioned cooling unit is stable in operation: cooling capacity of the unit was 420 kW underground-test conditions, while its COP (coefficient of performance) reached 3.4. To address the issue of heat injuries existing in No. 16305 U-shaped long-wall ventilation face of Jining No. 3 coal mine, a local air conditioning system was developed with ZL400 cooling unit as the system's core. The paper presented an analysis of characteristics of the air current flowing in the air-mixing and cooling mode of ZL400 cooling unit used in air intake way. Through i-d patterns we described the process of the airflow treatment, such as cooling, mixing and heating, etc. The cooling system decreased dry bulb temperature on working face by 3°C on average and 3.8°C at most, while lowered the web bulb temperature by 3.6°C on average and 4.8°C at most. At the same time, it reduced relative humidity by 5% on average and 8.6% at most. The field application of the ZL400 cooling unit had gain certain effects in air conditioning and provided support for the solution of mine heat injuries in China in terms of technology and equipment.

5. Detail view of the north end of the west ...

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

5. Detail view of the north end of the west elevation, looking at the window, with scale (note: repointing & condition of brick masonry wall) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

36. Interior view of the north end of the east ...

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

36. Interior view of the north end of the east (rear) wall looking at the section between the door and northeastern corner, with scale - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

Introduction to machine learning for brain imaging.

PubMed

Lemm, Steven; Blankertz, Benjamin; Dickhaus, Thorsten; Müller, Klaus-Robert

2011-05-15

Machine learning and pattern recognition algorithms have in the past years developed to become a working horse in brain imaging and the computational neurosciences, as they are instrumental for mining vast amounts of neural data of ever increasing measurement precision and detecting minuscule signals from an overwhelming noise floor. They provide the means to decode and characterize task relevant brain states and to distinguish them from non-informative brain signals. While undoubtedly this machinery has helped to gain novel biological insights, it also holds the danger of potential unintentional abuse. Ideally machine learning techniques should be usable for any non-expert, however, unfortunately they are typically not. Overfitting and other pitfalls may occur and lead to spurious and nonsensical interpretation. The goal of this review is therefore to provide an accessible and clear introduction to the strengths and also the inherent dangers of machine learning usage in the neurosciences. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

CANFAR + Skytree: Mining Massive Datasets as an Essential Part of the Future of Astronomy

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.

2013-01-01

The future study of large astronomical datasets, consisting of hundreds of millions to billions of objects, will be dominated by large computing resources, and by analysis tools of the necessary scalability and sophistication to extract useful information. Significant effort will be required to fulfil their potential as a provider of the next generation of science results. To-date, computing systems have allowed either sophisticated analysis of small datasets, e.g., most astronomy software, or simple analysis of large datasets, e.g., database queries. At the Canadian Astronomy Data Centre, we have combined our cloud computing system, the Canadian Advanced Network for Astronomical Research (CANFAR), with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing system for data mining in astronomy. This allows the full sophistication of the huge fields of data mining and machine learning to be applied to the hundreds of millions of objects that make up current large datasets. CANFAR works by utilizing virtual machines, which appear to the user as equivalent to a desktop. Each machine is replicated as desired to perform large-scale parallel processing. Such an arrangement carries far more flexibility than other cloud systems, because it enables the user to immediately install and run the same code that they already utilize for science on their desktop. We demonstrate the utility of the CANFAR + Skytree system by showing science results obtained, including assigning photometric redshifts with full probability density functions (PDFs) to a catalog of approximately 133 million galaxies from the MegaPipe reductions of the Canada-France-Hawaii Telescope Legacy Wide and Deep surveys. Each PDF is produced nonparametrically from 100 instances of the photometric parameters for each galaxy, generated by perturbing within the errors on the measurements. Hence, we produce, store, and assign redshifts to, a catalog of over 13 billion object instances. This catalog is comparable in size to those expected from next-generation surveys, such as Large Synoptic Survey Telescope. The CANFAR+Skytree system is open for use by any interested member of the astronomical community.

Super short term forecasting of photovoltaic power generation output in micro grid

NASA Astrophysics Data System (ADS)

Gong, Cheng; Ma, Longfei; Chi, Zhongjun; Zhang, Baoqun; Jiao, Ran; Yang, Bing; Chen, Jianshu; Zeng, Shuang

2017-01-01

The prediction model combining data mining and support vector machine (SVM) was built. Which provide information of photovoltaic (PV) power generation output for economic operation and optimal control of micro gird, and which reduce influence of power system from PV fluctuation. Because of the characteristic which output of PV rely on radiation intensity, ambient temperature, cloudiness, etc., so data mining was brought in. This technology can deal with large amounts of historical data and eliminate superfluous data, by using fuzzy classifier of daily type and grey related degree. The model of SVM was built, which can dock with information from data mining. Based on measured data from a small PV station, the prediction model was tested. The numerical example shows that the prediction model is fast and accurate.

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

PubMed

Marella, William M; Sparnon, Erin; Finley, Edward

2017-03-01

The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system. Potentially relevant cases were identified through a query of the Pennsylvania Patient Safety Reporting System. A random sample of cases were manually screened for relevance and divided into training, testing, and validation data sets to develop a machine learning model. This model was used to automate screening of remaining potentially relevant cases. Of the 4 algorithms tested, a naive Bayes kernel performed best, with an area under the receiver operating characteristic curve of 0.927 ± 0.023, accuracy of 0.855 ± 0.033, and F score of 0.877 ± 0.027. The machine learning model and text mining approach described here are useful tools for identifying and analyzing adverse event and near-miss reports. Although reporting systems are beginning to incorporate structured fields on health information technology and the EHR, these methods can identify related events that reporters classify in other ways. These methods can facilitate analysis of legacy safety reports by retrieving health information technology-related and EHR-related events from databases without fields and controlled values focused on this subject and distinguishing them from reports in which the EHR is mentioned only in passing. Machine learning and text mining are useful additions to the patient safety toolkit and can be used to semiautomate screening and analysis of unstructured text in safety reports from frontline staff.

Issues of Exploitation of Induction Motors in the Course of Underground Mining Operations

NASA Astrophysics Data System (ADS)

Gumula, Stanisław; Hudy, Wiktor; Piaskowska-Silarska, Malgorzata; Pytel, Krzysztof

2017-09-01

Mining industry is one of the most important customers of electric motors. The most commonly used in the contemporary mining industry is alternating current machines used for processing electrical energy into mechanical energy. The operating problems and the influence of qualitative interference acting on the inputs of individual regulators to field-oriented system in the course of underground mining operations has been presented in the publication. The object of controlling the speed is a slip-ring induction motor. Settings of regulators were calculated using an evolutionary algorithm. Examination of system dynamics was performed by a computer with the use of the MATLAB / Simulink software. According to analyzes, large distortion of input signals of regulators adversely affects the rotational speed that pursued by the control system, which may cause a large vibration of the whole system and, consequently, its much faster destruction. Designed system is characterized by a significantly better resistance to interference. The system is stable with the properly selected settings of regulators, which is particularly important during the operation of machinery used in underground mining.

Prediction of the Wall Factor of Arbitrary Particle Settling through Various Fluid Media in a Cylindrical Tube Using Artificial Intelligence

PubMed Central

Li, Mingzhong; Xue, Jianquan; Li, Yanchao; Tang, Shukai

2014-01-01

Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. Particles with various shapes were divided into three kinds: sphere, cylinder, and rectangular prism; feature parameters of each kind of particle were extracted; prediction models of sphere and cylinder using artificial neural network were established. Due to the little number of rectangular prism sample, support vector machine was used to predict the wall factor, which is more suitable for addressing the problem of small samples. The characteristic dimension was presented to describe the shape and size of the diverse particles and a comprehensive prediction model of particles with arbitrary shapes was established to cover all types of conditions. Comparisons were conducted between the predicted values and the experimental results. PMID:24772024

Prediction of the wall factor of arbitrary particle settling through various fluid media in a cylindrical tube using artificial intelligence.

PubMed

Li, Mingzhong; Zhang, Guodong; Xue, Jianquan; Li, Yanchao; Tang, Shukai

2014-01-01

Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. Particles with various shapes were divided into three kinds: sphere, cylinder, and rectangular prism; feature parameters of each kind of particle were extracted; prediction models of sphere and cylinder using artificial neural network were established. Due to the little number of rectangular prism sample, support vector machine was used to predict the wall factor, which is more suitable for addressing the problem of small samples. The characteristic dimension was presented to describe the shape and size of the diverse particles and a comprehensive prediction model of particles with arbitrary shapes was established to cover all types of conditions. Comparisons were conducted between the predicted values and the experimental results.

Semi-Supervised Clustering for High-Dimensional and Sparse Features

ERIC Educational Resources Information Center

Yan, Su

2010-01-01

Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

30 CFR 27.21 - Methane-monitoring system.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Methane-monitoring system. 27.21 Section 27.21... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.21 Methane-monitoring system. (a) A methane-monitoring system shall be so designed that any machine or equipment, which...

Generating a Spanish Affective Dictionary with Supervised Learning Techniques

ERIC Educational Resources Information Center

Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora

2016-01-01

Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…

The Technology Review 10: Emerging Technologies that Will Change the World.

ERIC Educational Resources Information Center

Technology Review, 2001

2001-01-01

Identifies 10 emerging areas of technology that will soon have a profound impact on the economy and on how people live and work: brain-machine interfaces; flexible transistors; data mining; digital rights management; biometrics; natural language processing; microphotonics; untangling code; robot design; and microfluidics. In each area, one…

30 CFR 27.21 - Methane-monitoring system.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Methane-monitoring system. 27.21 Section 27.21... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.21 Methane-monitoring system. (a) A methane-monitoring system shall be so designed that any machine or equipment, which...

30 CFR 27.21 - Methane-monitoring system.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Methane-monitoring system. 27.21 Section 27.21... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.21 Methane-monitoring system. (a) A methane-monitoring system shall be so designed that any machine or equipment, which...

30 CFR 27.21 - Methane-monitoring system.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Methane-monitoring system. 27.21 Section 27.21... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.21 Methane-monitoring system. (a) A methane-monitoring system shall be so designed that any machine or equipment, which...

30 CFR 27.21 - Methane-monitoring system.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Methane-monitoring system. 27.21 Section 27.21... APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Construction and Design Requirements § 27.21 Methane-monitoring system. (a) A methane-monitoring system shall be so designed that any machine or equipment, which...

Obtaining Accurate Probabilities Using Classifier Calibration

ERIC Educational Resources Information Center

Pakdaman Naeini, Mahdi

2016-01-01

Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

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

Code of Federal Regulations, 2010 CFR

2010-07-01

... feet or more apart shall be installed with a wooden crossbar at least 3 inches thick and 8 inches wide... less than 9 feet apart shall be installed with a wooden plank at least 2 inches thick and 8 inches wide...

Topic Models for Link Prediction in Document Networks

ERIC Educational Resources Information Center

Kataria, Saurabh

2012-01-01

Recent explosive growth of interconnected document collections such as citation networks, network of web pages, content generated by crowd-sourcing in collaborative environments, etc., has posed several challenging problems for data mining and machine learning community. One central problem in the domain of document networks is that of "link…

30. VIEW OF THE LOCKERS IN THE OLD PART OF ...

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

30. VIEW OF THE LOCKERS IN THE OLD PART OF THE ANSELMO DRY LOOKING WEST FROM WITHIN THE SHOWERS. THE LOCKERS ARE ALONG THE EAST WALL OF THE OLD SECTION - Butte Mineyards, Anselmo Mine, Butte, Silver Bow County, MT

30. Duplicate view of the south end of the west ...

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

30. Duplicate view of the south end of the west wall with light illuminating the dirt floor and showing the condition of the brick masonry, with scale - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

32. Interior view, encased fireplace and remains of the ...

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

32. Interior view, encased - fireplace and remains of the hearth against the north wall, with scale l(note: hole punched through plaster allows access to the flues) - Kiskiack, Naval Mine Depot, State Route 238 vicinity, Yorktown, York County, VA

40 CFR 63.462 - Batch cold cleaning machine standards.

Code of Federal Regulations, 2012 CFR

2012-07-01

... PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES... splashing against tank walls or parts being cleaned. (7) The owner or operator shall ensure that, when the...

40 CFR 63.462 - Batch cold cleaning machine standards.

Code of Federal Regulations, 2013 CFR

2013-07-01

... PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES... splashing against tank walls or parts being cleaned. (7) The owner or operator shall ensure that, when the...

40 CFR 63.462 - Batch cold cleaning machine standards.

Code of Federal Regulations, 2014 CFR

2014-07-01

... PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES... splashing against tank walls or parts being cleaned. (7) The owner or operator shall ensure that, when the...

40 CFR 63.462 - Batch cold cleaning machine standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES... splashing against tank walls or parts being cleaned. (7) The owner or operator shall ensure that, when the...

40 CFR 63.462 - Batch cold cleaning machine standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES... splashing against tank walls or parts being cleaned. (7) The owner or operator shall ensure that, when the...

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

PubMed

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

2017-09-01

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

Identification of Shearer Cutting Patterns Using Vibration Signals Based on a Least Squares Support Vector Machine with an Improved Fruit Fly Optimization Algorithm

PubMed Central

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Liu, Ze; Xu, Jing

2016-01-01

Shearers play an important role in fully mechanized coal mining face and accurately identifying their cutting pattern is very helpful for improving the automation level of shearers and ensuring the safety of coal mining. The least squares support vector machine (LSSVM) has been proven to offer strong potential in prediction and classification issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. In this paper, an improved fly optimization algorithm (IFOA) to optimize the parameters of LSSVM was presented and the LSSVM coupled with IFOA (IFOA-LSSVM) was used to identify the shearer cutting pattern. The vibration acceleration signals of five cutting patterns were collected and the special state features were extracted based on the ensemble empirical mode decomposition (EEMD) and the kernel function. Some examples on the IFOA-LSSVM model were further presented and the results were compared with LSSVM, PSO-LSSVM, GA-LSSVM and FOA-LSSVM models in detail. The comparison results indicate that the proposed approach was feasible, efficient and outperformed the others. Finally, an industrial application example at the coal mining face was demonstrated to specify the effect of the proposed system. PMID:26771615

New directions in biomedical text annotation: definitions, guidelines and corpus construction

PubMed Central

Wilbur, W John; Rzhetsky, Andrey; Shatkay, Hagit

2006-01-01

Background While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined. Results We have identified five qualitative dimensions that we believe characterize a broad range of scientific sentences, and are therefore useful for supporting a general approach to text-mining: focus, polarity, certainty, evidence, and directionality. We define these dimensions and describe the guidelines we have developed for annotating text with regard to them. To examine the effectiveness of the guidelines, twelve annotators independently annotated the same set of 101 sentences that were randomly selected from current biomedical periodicals. Analysis of these annotations shows 70–80% inter-annotator agreement, suggesting that our guidelines indeed present a well-defined, executable and reproducible task. Conclusion We present our guidelines defining a text annotation task, along with annotation results from multiple independently produced annotations, demonstrating the feasibility of the task. The annotation of a very large corpus of documents along these guidelines is currently ongoing. These annotations form the basis for the categorization of text along multiple dimensions, to support viable text mining for experimental results, methodology statements, and other forms of information. We are currently developing machine learning methods, to be trained and tested on the annotated corpus, that would allow for the automatic categorization of biomedical text along the general dimensions that we have presented. The guidelines in full detail, along with annotated examples, are publicly available. PMID:16867190

A Review of Lunar Regolith Excavation Robotic Device Prototypes

NASA Technical Reports Server (NTRS)

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

2011-01-01

The excavation of lunar regolith is desirable for use as a feedstock for oxygen production processes as well as civil engineering purposes and for the fabrication of parts and structures. This is known as In-Situ Resource Utilization (ISRU). More recently, there has been mounting evidence that water ice exists at the poles of the Moon, buried in the regolith where thermally stable conditions exist. This means that regolith excavation will be required to mine the water ice which is believed to be. mixed in with the regolith, or bonded to it. The mined water ice can then be electrolyzed to produce hydrogen and oxygen propellants which could form the basis of a cis-lunar transportation system using in-situ derived propellants. In 2007, the National Aeronautics & Space Administration (NASA) sponsored a Lunar Regolith Excavation Competition as part of its Centennial Challenges program, The competition was not won and it was held again in 2008 and 2009, when it was won by a university team. A $500,000 prize was awarded to the winning team by NASA. In 2010, NASA continued the competition as a spinoff of the Centennial Challenges, which is restricted to university participation only. This competition is known as the "Lunabotics Mining Competition" and is hosted by NASA at Kennedy Space Center. Twenty three American university teams competed in the 2010 Lunabotics Mining Competition. The competition was held again in May 2011 with over 60 teams registered, including international participation. The competition will be held again in May 2012 at Kennedy Space Center in Florida. . This paper contains a thorough review of the various regolith eX,cavation robotic device prototypes that competed in these NASA competitions, and will. classify the machines and their methods of excavation to document the variety of ideas that were spawned and built to compete at these events. It is hoped that documentation of these robots will serve to help future robotic excavation designers and provide a historical reference for future lunar mining machine endeavors.

Use of overburden rocks from open-pit coal mines and waste coals of Western Siberia for ceramic brick production with a defect-free structure

NASA Astrophysics Data System (ADS)

Stolboushkin, A. Yu; Ivanov, A. I.; Storozhenko, G. I.; Syromyasov, V. A.; Akst, D. V.

2017-09-01

The rational technology for the production of ceramic bricks with a defect-free structure from coal mining and processing wastes was developed. The results of comparison of physical and mechanical properties and the structure of ceramic bricks manufactured from overburden rocks and waste coal with traditional for semi-dry pressing mass preparation and according to the developed method are given. It was established that a homogeneous, defect-free brick texture obtained from overburden rocks of open-pit mines and waste coal improves the quality of ceramic wall materials produced by the method of compression molding by more than 1.5 times compared to the brick with a traditional mass preparation.

Extreme Access & Lunar Ice Mining in Permanently Shadowed Craters Project

NASA Technical Reports Server (NTRS)

Mueller, Robert P.

2014-01-01

Results from the recent LCROSS mission in 2010, indicate that H2O ice and other useful volatiles such as CO, He, and N are present in the permanently shadowed craters at the poles of the moon. However, the extreme topography and steep slopes of the crater walls make access a significant challenge. In addition temperatures have been measured at 40K (-233 C) so quick access and exit is desirable before the mining robot cold soaks. The Global Exploration Roadmap lists extreme access as a necessary technology for Lunar Exploration.

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.

A New Data Mining Scheme Using Artificial Neural Networks

PubMed Central

Kamruzzaman, S. M.; Jehad Sarkar, A. M.

2011-01-01

Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems. PMID:22163866

A new genome-mining tool redefines the lasso peptide biosynthetic landscape

PubMed Central

Tietz, Jonathan I.; Schwalen, Christopher J.; Patel, Parth S.; Maxson, Tucker; Blair, Patricia M.; Tai, Hua-Chia; Zakai, Uzma I.; Mitchell, Douglas A.

2016-01-01

Ribosomally synthesized and post-translationally modified peptide (RiPP) natural products are attractive for genome-driven discovery and re-engineering, but limitations in bioinformatic methods and exponentially increasing genomic data make large-scale mining difficult. We report RODEO (Rapid ORF Description and Evaluation Online), which combines hidden Markov model-based analysis, heuristic scoring, and machine learning to identify biosynthetic gene clusters and predict RiPP precursor peptides. We initially focused on lasso peptides, which display intriguing physiochemical properties and bioactivities, but their hypervariability renders them challenging prospects for automated mining. Our approach yielded the most comprehensive mapping of lasso peptide space, revealing >1,300 compounds. We characterized the structures and bioactivities of six lasso peptides, prioritized based on predicted structural novelty, including an unprecedented handcuff-like topology and another with a citrulline modification exceptionally rare among bacteria. These combined insights significantly expand the knowledge of lasso peptides, and more broadly, provide a framework for future genome-mining efforts. PMID:28244986

Ray Tracing and Modal Methods for Modeling Radio Propagation in Tunnels With Rough Walls

PubMed Central

Zhou, Chenming

2017-01-01

At the ultrahigh frequencies common to portable radios, tunnels such as mine entries are often modeled by hollow dielectric waveguides. The roughness condition of the tunnel walls has an influence on radio propagation, and therefore should be taken into account when an accurate power prediction is needed. This paper investigates how wall roughness affects radio propagation in tunnels, and presents a unified ray tracing and modal method for modeling radio propagation in tunnels with rough walls. First, general analytical formulas for modeling the influence of the wall roughness are derived, based on the modal method and the ray tracing method, respectively. Second, the equivalence of the ray tracing and modal methods in the presence of wall roughnesses is mathematically proved, by showing that the ray tracing-based analytical formula can converge to the modal-based formula through the Poisson summation formula. The derivation and findings are verified by simulation results based on ray tracing and modal methods. PMID:28935995

Privacy-preserving restricted boltzmann machine.

PubMed

Li, Yu; Zhang, Yuan; Ji, Yue

2014-01-01

With the arrival of the big data era, it is predicted that distributed data mining will lead to an information technology revolution. To motivate different institutes to collaborate with each other, the crucial issue is to eliminate their concerns regarding data privacy. In this paper, we propose a privacy-preserving method for training a restricted boltzmann machine (RBM). The RBM can be got without revealing their private data to each other when using our privacy-preserving method. We provide a correctness and efficiency analysis of our algorithms. The comparative experiment shows that the accuracy is very close to the original RBM model.

Privacy-Preserving Restricted Boltzmann Machine

PubMed Central

Li, Yu

2014-01-01

With the arrival of the big data era, it is predicted that distributed data mining will lead to an information technology revolution. To motivate different institutes to collaborate with each other, the crucial issue is to eliminate their concerns regarding data privacy. In this paper, we propose a privacy-preserving method for training a restricted boltzmann machine (RBM). The RBM can be got without revealing their private data to each other when using our privacy-preserving method. We provide a correctness and efficiency analysis of our algorithms. The comparative experiment shows that the accuracy is very close to the original RBM model. PMID:25101139

Pre-operative prediction of surgical morbidity in children: comparison of five statistical models.

PubMed

Cooper, Jennifer N; Wei, Lai; Fernandez, Soledad A; Minneci, Peter C; Deans, Katherine J

2015-02-01

The accurate prediction of surgical risk is important to patients and physicians. Logistic regression (LR) models are typically used to estimate these risks. However, in the fields of data mining and machine-learning, many alternative classification and prediction algorithms have been developed. This study aimed to compare the performance of LR to several data mining algorithms for predicting 30-day surgical morbidity in children. We used the 2012 National Surgical Quality Improvement Program-Pediatric dataset to compare the performance of (1) a LR model that assumed linearity and additivity (simple LR model) (2) a LR model incorporating restricted cubic splines and interactions (flexible LR model) (3) a support vector machine, (4) a random forest and (5) boosted classification trees for predicting surgical morbidity. The ensemble-based methods showed significantly higher accuracy, sensitivity, specificity, PPV, and NPV than the simple LR model. However, none of the models performed better than the flexible LR model in terms of the aforementioned measures or in model calibration or discrimination. Support vector machines, random forests, and boosted classification trees do not show better performance than LR for predicting pediatric surgical morbidity. After further validation, the flexible LR model derived in this study could be used to assist with clinical decision-making based on patient-specific surgical risks. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-08-01

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

[Characterization of severe acute occupational poisoning accidents related to asphyxiating gases in China between 1989 and 2003].

PubMed

Zhang, Min; Li, Tao; Wang, Huan-Qiang; Wang, Hong-Fei; Chen, Shu-Yang; Du, Xie-Yi; Qin, Jian; Zhang, Shuang; Ji, Li-Ying

2006-12-01

To analyze severe acute occupational poisoning accidents related to asphyxiating gases reported in China between 1989 and 2003, and to study the characteristics of severe acute occupational poisoning accidents and provide scientific evidences for prevention and control strategies. The data from the national occupational poisoning case reporting system were analyzed with descriptive methods. (1) There were 273 severe acute occupational poisoning accidents related to asphyxiating gases for 15 years with 1638 workers poisoned and 600 workers died, which accounted for 53.95% in total accidents and 35.17% of workers poisoned and 78.64% of workers died of all severe acute occupational poisoning accidents. The average poisoning age was (33.8 +/- 9.7) years old and the average death age was (36.6 +/- 10.0) years old. (2) Most of the accidents were caused by hydrogen sulfide, carbon monoxide and carbon dioxide respectively, and mainly occurred in chemical industry, mining, water disposal industry, paper making industry and brewing industry. The risk was higher in some jobs than others, such as cleanout, machine maintenance and repair, production, mine and digging. The poisoning accidents occurred more frequently from April to September each year and occurred in the confined space, in the basement and the mine, and workers died of poisoning mostly were men. (1) The severe acute occupational poisoning accidents related to asphyxiating gases are more dangerous than others. (2) The control of poisoning accidents related to hydrogen sulfide, carbon monoxide and carbon dioxide, which occurred easily in the confined space, should be paid more attention to, and good work practice should be developed on some posts, such as digging, cleanout, dredge, machine maintenance and repair and mine.