WorldWideScience

Sample records for waterjet mining machine

  1. A waterjet mining machine for use in room and pillar mining operations

    Energy Technology Data Exchange (ETDEWEB)

    Summers, D.A.

    1990-06-01

    A new mining machine is constructed for use in room and pillar mining operations. This machine uses the action of computer controlled, centrally located high pressure cutting lances to cut deep slots in a coal face. These slots stress relieve the coal ahead of the machine and outline blocks of coal. The movement forward of the machine then wedges up the lower block of coal. This wedging action is assisted by the gathering arms of the loader section of the machine, and by underlying oscillating waterjets which create a slot ahead of the loading wedge as it advances. Finally the top section of coal is brought down by the sequential advance of wedge faced roof support members, again assisted by the waterjet action from the central cutting arms. The machine is designed to overcome major disadvantages of existing room and pillar mining machines in regard to a reduction in respirable dust, the creation of an immediate roof support, and an increase in product size, with concomitant reduction in cleaning costs.

  2. A waterjet mining machine for use in room and pillar mining operations. [Final report

    Energy Technology Data Exchange (ETDEWEB)

    Summers, D.A.

    1990-06-01

    A new mining machine is constructed for use in room and pillar mining operations. This machine uses the action of computer controlled, centrally located high pressure cutting lances to cut deep slots in a coal face. These slots stress relieve the coal ahead of the machine and outline blocks of coal. The movement forward of the machine then wedges up the lower block of coal. This wedging action is assisted by the gathering arms of the loader section of the machine, and by underlying oscillating waterjets which create a slot ahead of the loading wedge as it advances. Finally the top section of coal is brought down by the sequential advance of wedge faced roof support members, again assisted by the waterjet action from the central cutting arms. The machine is designed to overcome major disadvantages of existing room and pillar mining machines in regard to a reduction in respirable dust, the creation of an immediate roof support, and an increase in product size, with concomitant reduction in cleaning costs.

  3. Spray Deflector For Water-Jet Machining

    Science.gov (United States)

    Cawthon, Michael A.

    1989-01-01

    Disk on water-jet-machining nozzle protects nozzle and parts behind it from erosion by deflected spray. Consists of stainless-steel backing with neoprene facing deflecting spray so it does not reach nut or other vital parts of water-jet apparatus.

  4. CNC water-jet machining and cutting center

    Energy Technology Data Exchange (ETDEWEB)

    Bartlett, D.C.

    1991-09-01

    CNC water-jet machining was investigated to determine the potential applications and cost-effectiveness that would result by establishing this capability in the engineering shops of Allied-Signal Inc., Kansas City Division (KCD). Both conductive and nonconductive samples were machined at KCD on conventional machining equipment (a three-axis conversational programmed mill and a wire electrical discharge machine) and on two current-technology water-jet machines at outside vendors. These samples were then inspected, photographed, and evaluated. The current-technology water-jet machines were not as accurate as the conventional equipment. The resolution of the water-jet equipment was only {plus minus}0.005 inch, as compared to {plus minus}0.0002 inch for the conventional equipment. The principal use for CNC water-jet machining would be as follows: Contouring to near finished shape those items made from 300 and 400 series stainless steels, titanium, Inconel, aluminum, glass, or any material whose fabrication tolerance is less than the machine resolution of {plus minus}0.005 inch; and contouring to finished shape those items made from Kevlar, rubber, fiberglass, foam, aluminum, or any material whose fabrication specifications allow the use of a machine with {plus minus}0.005 inch tolerance. Additional applications are possible because there is minimal force generated on the material being cut and because the water-jet cuts without generating dust. 12 figs.

  5. WATER-JET CUTTING MACHINE NOW AVAILABLE FROM THE CERN RAW MATERIALS STORES

    CERN Multimedia

    2007-01-01

    The CERN Raw Materials Stores has recently acquired a new water-jet cutting machine. The machine is capable of cutting all types and shapes of materials up to 70 mm in thickness, with an accuracy of +/- 0.1mm/m. For the time being, users requiring materials to be cut should supply drawings in DXF, DWG or IGES (AutoCad) file format. The machine will be operational as of 1st October 2007. The Stores Team Paulo Dos Santos FI-LS-MM 72308

  6. Characterization of nanoparticles from abrasive waterjet machining and electrical discharge machining processes.

    Science.gov (United States)

    Ling, Tsz Yan; Pui, David Y H

    2013-11-19

    Abrasive Waterjet Machining (AWM) and Electrical Discharge Machining (EDM) processes are found to produce nanoparticles during operation. Impacts of engineered nanoparticles released to the environment and biological system have caused much concern. Similarly, the nanoparticles unintentionally produced by the AWM and EDM can lead to comparable effects. By application of the Nanoparticle Tracking Analysis (NTA) technique, the size distribution and concentration of nanoparticles in the water used in AWM and EDM were measured. The particles generally have a peak size of 100-200 nm. The filtration systems of the AWM and EDM processes were found to remove 70% and 90% the nanoparticles present, respectively. However, the particle concentration of the filtered water from the AWM was still four times higher than that found in regular tap water. These nanoparticles are mostly agglomerated, according to the microscopy analysis. Using the electron dispersive spectroscopy (EDS) technique, the particles are confirmed to come from the debris of the materials cut with the equipment. Since AWM and EDM are widely used, the handling and disposal of used filters collected with nanoparticles, release of nanoparticles to the sewer, and potential use of higher performance filters for these processes will deserve further consideration.

  7. Experimental Investigations into Abrasive Waterjet Machining of Carbon Fiber Reinforced Plastic

    Directory of Open Access Journals (Sweden)

    Prasad D. Unde

    2015-01-01

    Full Text Available Abrasive waterjet machining (AWJM is an emerging machining process in which the material removal takes place due to abrasion. A stream of abrasive particles mixed with filtered water is subjected to the work surface with high velocity. The present study is focused on the experimental research and evaluation of the abrasive waterjet machining process in order to evaluate the technological factors affecting the machining quality of CFRP laminate using response surface methodology. The standoff distance, feed rate, and jet pressure were found to affect kerf taper, delamination, material removal rate, and surface roughness. The material related parameter, orientation of fiber, has been also found to affect the machining performance. The kerf taper was found to be 0.029 for 45° fiber orientation whereas it was 0.036 and 0.038 for 60° and 90°, respectively. The material removal rate is 18.95 mm3/sec for 45° fiber orientation compared to 18.26 mm3/sec for 60° and 17.4 mm3/sec for 90° fiber orientation. The Ra value for 45° fiber orientation is 4.911 µm and for 60° and 90° fiber orientation it is 4.927 µm and 4.974 µm, respectively. Delamination factor is found to be more for 45° fiber orientation, that is, 2.238, but for 60° and 90° it is 2.029 and 2.196, respectively.

  8. Integration of an industrial robot and a CNC machine in waterjet cutting application.

    OpenAIRE

    Jozko, Mateusz; Rykaczewski, Jaroslaw; Tupaj, Maciej

    2014-01-01

    The main goal of this work is to create a flexible manufacturing system for the waterjet cutting application. This kind of process is a high-risk activity with possible injuries if details are removed manually. To avoid this problem, a system can be fully automatized excluding presence of human interaction. Moreover, it could possibly decrease the total operating time for waterjet cutting of multiple details from one sheet of material, by removing details automatically from the waterjet cutti...

  9. Performance Enhancement of Abrasive Waterjet Cutting

    NARCIS (Netherlands)

    Karpuschewski, B.

    Abrasive Waterjet (AWJ) Machining is a recent non-traditional machining process. This technology is widely used in industry for cutting difficult-to-machine-materials, milling slots, polishing hard materials etc. AWJ machining has many advantages, e.g. it can cut net-shape parts, no heat is

  10. Performance Enhancement of Abrasive Waterjet Cutting

    NARCIS (Netherlands)

    2008-01-01

    Abrasive Waterjet (AWJ) Machining is a recent non-traditional machining process. This technology is widely used in industry for cutting difficult-to-machine-materials, milling slots, polishing hard materials etc. AWJ machining has many advantages, e.g. it can cut net-shape parts, no heat is

  11. Development and evaluation of ultra high pressure waterjet cutting

    NARCIS (Netherlands)

    Susuzlu, T.

    2008-01-01

    Abrasive waterjet (AWJ) cutting is a machining process to cut wide range of materials from soft materials such as rubber, leather to hard materials such as metals by means of a high-velocity slurry jet, formed as a result of injecting abrasive particles into a waterjet. The machining action is the

  12. Sandstone Turning by Abrasive Waterjet

    Czech Academy of Sciences Publication Activity Database

    Hlaváček, Petr; Cárach, J.; Hloch, Sergej; Vasilko, K.; Klichová, Dagmar; Klich, Jiří; Lehocká, D.

    2015-01-01

    Roč. 48, č. 6 (2015), s. 2489-2493 ISSN 0723-2632 R&D Projects: GA MŠk ED2.1.00/03.0082; GA MŠk(CZ) LO1406 Institutional support: RVO:68145535 Keywords : turning away from the jet * conventional turning towards the jet * sandstone * abrasive water jet Subject RIV: JQ - Machines ; Tools Impact factor: 2.386, year: 2015 http://www.springerprofessional.de/sandstone-turning-by-abrasive-waterjet/6038028.html

  13. 76 FR 70075 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Science.gov (United States)

    2011-11-10

    ... Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health Administration, Labor. ACTION... addressing Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines. This... Continuous Mining Machines in Underground Coal Mines. MSHA conducted hearings on October 18, October 20...

  14. High pressure water jet mining machine

    Science.gov (United States)

    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.

  15. Breakthrough Energy Savings with Waterjet Technology

    Energy Technology Data Exchange (ETDEWEB)

    Lee W. Saperstein; R. Larry Grayson; David A. Summers; Jorge Garcia-Joo; Greg Sutton; Mike Woodward; T.P. McNulty

    2007-05-15

    processing of the product in a cavitation chamber. Subsequent testing is also planned, to determine preferred methods for separating ore minerals from the waste. Tests with this system have included both the galena samples, and copper ores from Poland. The development of this tool lies within an expanding market for the use of high-pressure waterjet equipment across a broad spectrum of applications. As the industry develops new tools, it is anticipated that the research team will investigate the development of a prototype machine based on these tools, since this will simplify and speed up equipment development. It is hoped that once this is developed that can be taken into an active mine. Such a machine should be able to produce large enough samples to allow assessment of optimal operating conditions.

  16. Bidirectional, Automatic Coal-Mining Machine

    Science.gov (United States)

    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.

  17. Abrasives and possibilities of increase in efficiency of abrasive waterjets

    Czech Academy of Sciences Publication Activity Database

    Sitek, Libor; Martinec, Petr

    2016-01-01

    Roč. 9, March 2016 (2016), s. 877-881 ISSN 1805-0476 R&D Projects: GA MŠk(CZ) LO1406; GA MŠk ED2.1.00/03.0082 Institutional support: RVO:68145535 Keywords : high-speed waterjets * abrasive waterjets * abrasives * garnet * zirconia Subject RIV: JQ - Machines ; Tools http://www.mmscience.eu/content/file/archives/MM_Science_201603.pdf

  18. Data Mining Practical Machine Learning Tools and Techniques

    CERN Document Server

    Witten, Ian H; Hall, Mark A

    2011-01-01

    Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

  19. 76 FR 63238 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Science.gov (United States)

    2011-10-12

    ... Part 75 RIN 1219-AB65 Proximity Detection Systems for Continuous Mining Machines in Underground Coal... hearing. SUMMARY: The Mine Safety and Health Administration (MSHA) is announcing [[Page 63239

  20. Surface mining machines problems of maintenance and modernization

    CERN Document Server

    Rusiński, Eugeniusz; Moczko, Przemysław; Pietrusiak, Damian

    2017-01-01

    This unique volume imparts practical information on the operation, maintenance, and modernization of heavy performance machines such as lignite mine machines, bucket wheel excavators, and spreaders. Problems of large scale machines (mega machines) are highly specific and not well recognized in the common mechanical engineering environment. Prof. Rusiński and his co-authors identify solutions that increase the durability of these machines as well as discuss methods of failure analysis and technical condition assessment procedures. "Surface Mining Machines: Problems in Maintenance and Modernization" stands as a much-needed guidebook for engineers facing the particular challenges of heavy performance machines and offers a distinct and interesting demonstration of scale-up issues for researchers and scientists from across the fields of machine design and mechanical engineering.

  1. Water spray ventilator system for continuous mining machines

    Science.gov (United States)

    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.

  2. Robust Design Based Optimisation of Waterjet Cutting

    Directory of Open Access Journals (Sweden)

    Deaconescu Tudor

    2016-01-01

    Full Text Available The most important input quantities of waterjet cutting are the jet pressure, feed speed, stand-off distance, abrasive graining, mass flow, etc. Other quantities contributing to machining efficiency are the type of utilized abrasive or the tilt of the jet. Each of these quantities can be assigned different set points. The roughness of the machined surfaces and the thickness of the cut part are output quantities of the system, their values depending on the input parameters and the influence of various disturbing factors (noises. The paper discusses surface roughness obtained consequently to abrasive jet cutting. Optimisation of the machining system was achieved by intervening on five selected input quantities (factors, with two set points considered for each. Upon applying Taguchi methods, eventually the combination of factor set points was determined that ensures robust behaviour of the system.

  3. 76 FR 54163 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Science.gov (United States)

    2011-08-31

    ... pinned by the machine. Proximity detection is a technology that uses electronic sensors to detect motion... also observed the Booyco Collision Warning System (CWS) being used on continuous mining machines. The... further analysis due to its potential to force machine operators out of previously safe areas into...

  4. Long hole waterjet assisted drilling for gas drainage

    Energy Technology Data Exchange (ETDEWEB)

    Paul Dunn; M. Stockwell; T. Meyer [CMTE Development Ltd. (Australia)

    2000-02-01

    In an effort to improve longwall productivity and address current safety issues associated with methane drainage the CMTE has been investigating the applicability of high pressure (HP) water (20 - 40 MPa) for assisting conventional rotary drilling at both Appin (BHPC) and Dartbrook (Shell) mines. The C6028 ACARP project has allowed the development of the cross panel waterjet rotary drilling technology to be finalised following C5028 project. The project objective was to produce a long hole drilling system that has the accuracy of down hole motor drilling and the productivity of rotary drilling, while minimising the loss of expensive equipment down hole. The ultimate aim of the project was to drill holes of up to 1 km and beyond. During the C6028 project it was not possible to fully demonstrate horizontal azimuth control of the borehole trajectory, using high pressure waterjets to erode the coal preferentially. Problems with drill rod failures and those associated with conducting trials underground, where test time is limited due to production requirements, meant that insufficient testing over long hole lengths (> 300 metres) was conducted. Although a long demonstration hole was not achieved during the project, the authors believe that the technology has now been developed to a stage that a long hole drilling system is possible. Further testing will be required before rotary waterjet drilling can be extended to long holes. Waterjet drilling field trials into a highwall on surface would allow the required testing and development of the horizontal azimuth control before demonstrating the technology underground.

  5. Advances in Machine Learning and Data Mining for Astronomy

    Science.gov (United States)

    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.

  6. Experiment and simulation study of laser dicing silicon with water-jet

    Energy Technology Data Exchange (ETDEWEB)

    Bao, Jiading; Long, Yuhong, E-mail: longyuhong@guet.edu.cn; Tong, Youqun; Yang, Xiaoqing; Zhang, Bin; Zhou, Zupeng

    2016-11-30

    Highlights: • The explosive melt expulsion could be a dominant process for the laser ablating silicon in liquids with ns-pulsed laser of 1064 nm irradiating. • Self-focusing phenomenon was found and its causes are analyzed. • SPH modeling technique was employed to understand the effect of water and water-jet on debris removal during water-jet laser machining. - Abstract: Water-jet laser processing is an internationally advanced technique, which combines the advantages of laser processing with water jet cutting. In the study, the experiment of water-jet laser dicing are conducted with ns pulsed laser of 1064 nm irradiating, and Smooth Particle Hydrodynamic (SPH) technique by AUTODYN software was modeled to research the fluid dynamics of water and melt when water jet impacting molten material. The silicon surface morphology of the irradiated spots has an appearance as one can see in porous formation. The surface morphology exhibits a large number of cavities which indicates as bubble nucleation sites. The observed surface morphology shows that the explosive melt expulsion could be a dominant process for the laser ablating silicon in liquids with nanosecond pulse laser of 1064 nm irradiating. Self-focusing phenomenon was found and its causes are analyzed. Smooth Particle Hydrodynamic (SPH) modeling technique was employed to understand the effect of water and water-jet on debris removal during water-jet laser machining.

  7. 30 CFR 75.1719-4 - Mining machines, cap lamps; requirements.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining machines, cap lamps; requirements. 75.1719-4 Section 75.1719-4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... Mining machines, cap lamps; requirements. (a) Paint used on exterior surfaces of mining machines shall...

  8. Edu-mining: A Machine Learning Approach

    Science.gov (United States)

    Srimani, P. K.; Patil, Malini M.

    2011-12-01

    Mining Educational data is an emerging interdisciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions. The educational data is referred as Edu-DATA. Queries related to Edu-DATA are of practical interest as SQL approach is insufficient and needs to be focused in a different way. The paper aims at developing a technique called Edu-MINING which converts raw data coming from educational institutions using data mining techniques into useful information. The discovered knowledge will have a great impact on the educational research and practices. Edu-MINING explores Edu-DATA, discovers new knowledge and suggests useful methods to improve the quality of education with regard to teaching-learning process. This is illustrated through a case study.

  9. 75 FR 17529 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

    Science.gov (United States)

    2010-04-06

    ... condition occurs. Ungrounded circuits include high-voltage transformers that power low- and medium-voltage... transformers in the power center. This will provide a safe means of de-energizing high-voltage circuits in the... machines in underground coal mines. It also revises MSHA's design requirements for approval of these mining...

  10. Advances in machine learning and data mining for astronomy

    CERN Document Server

    Way, Michael J

    2012-01-01

    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

  11. Modeling of Cavitating Flow through Waterjet Propulsors

    Science.gov (United States)

    2015-02-18

    OCT-11 -31-DEC-14 To) 4. TITLE AND SUBTITLE Modeling of Cavitating Flow through Waterjet Propulsors 5a. CONTRACT NUMBER 5b. GRANT NUMBER N00014-12...239-18 Modeling of Cavitating Flow through Waterjet Propulsors Jules W. Lindau The Pennsylvania State University, Applied Research Laboratory, State...flow nature, waterjets are expected to maintain resistance to cavitation , are amenable to ad- vanced concepts such as thrust vectoring, should

  12. Anticorrosion protection of mining machines and equipment (part 4)

    Energy Technology Data Exchange (ETDEWEB)

    Plucinski, J.

    1980-08-01

    This article dicusses efficient methods of preventing corrosion of machines and equipment used in underground black coal mines under conditions of high humidity, relatively high temperature and presence of mine waters with high salt content. Advantages and disadvantages of using various anticorrosion coatings are evaluated and information is given on which coatings can be used for various parts of mining machines. The following coatings are described: I. lacquer protection (oil cover, synthetic resins, chlorinated rubber, epoxide, polyvinyl cover, bitumic, polyester, polyurethane, silicones), II. electroplated protection (cathodic protection using copper, chromium, tin, silver, gold or nickel, or anodic protection using: zinc, aluminium, cadmium), III. chemical protection (oxide covers, phosphate coating, chromate covers), IV. plastic and synthetic resin protection (polyethylene, polyvinyl chloride, vinylidene chloride, polypropylene), V. metal covers (flame spraying, immersion plating, chemical plating, vacuum sublimation).

  13. Machine Learning and Data Mining Methods in Diabetes Research.

    Science.gov (United States)

    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.

  14. Machine Learning and Data Mining Methods in Diabetes Research

    Directory of Open Access Journals (Sweden)

    Ioannis Kavakiotis

    2017-01-01

    Full Text Available 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.

  15. Waterjet processes for coating removal

    Science.gov (United States)

    Burgess, Fletcher; Cosby, Steve; Hoppe, David

    1995-01-01

    USBI and NASA have been testing and investigating the use of high pressure water for coating removal for approximately the past 12 years at the Automated TPS (Thermal Protection System - ablative materials used for thermal protection during ascent and descent of the solid rocket boosters) Removal Facility located in the Productivity Enhancement Complex at Marshall Space Flight Center. Originally the task was to develop and automate the removal process and transfer the technology to a production facility at Kennedy Space Center. Since that time more and more applications and support roles for the waterjet technology have been realized. The facility has become a vital part of development activities ongoing at MSFC. It supports the development of environmentally compliant insulations, sealants, and coatings. It also supports bonding programs, test motors, and pressure vessels. The most recent role of the cell is supporting Thiokol Corporation's solid rocket motor program in the development of waterjet degreasing and paint stripping methods. Currently vapor degreasing methods use 500,000 lbs. of ozone depleting chemicals per year. This paper describes the major cell equipment, test methods practiced, and coatings that have been removed.

  16. Data mining practical machine learning tools and techniques

    CERN Document Server

    Witten, Ian H

    2005-01-01

    As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same

  17. Weka-A Machine Learning Workbench for Data Mining

    Science.gov (United States)

    Frank, Eibe; Hall, Mark; Holmes, Geoffrey; Kirkby, Richard; Pfahringer, Bernhard; Witten, Ian H.; Trigg, Len

    The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License.

  18. Increasing reliability of braking systems in mine hoisting machines

    Energy Technology Data Exchange (ETDEWEB)

    Shapovalov, N.I.; Kurchenko, E.M.

    1980-05-01

    This article reviews the braking systems used in hoisting machines in vertical and inclined shafts in coal mines. Braking systems used in hoisting machines can generally be divided into two groups: lack of pressure in the braking system cylinder turns on the brakes, or lack of pressure turns the brakes off. Manual operation of the braking system can sometimes create problems as sudden movement of the brake lever into position, i.e. braking, causes intensive braking with all its negative consequences for the installation. Therefore, an electric device is presented which can be included in the electric circuit of the braking system. A scheme of the apparatus is shown. When the proposed apparatus is included in the electric control system of the brakes, moving the lever into position i.e. braking, causes gradual changes in the flow of electric current, and therefore braking is smoother. (In Russian)

  19. Mining the Galaxy Zoo Database: Machine Learning Applications

    Science.gov (United States)

    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.

  20. Current Developments in Machine Learning Techniques in Biological Data Mining.

    Science.gov (United States)

    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.

  1. 30 CFR 18.54 - High-voltage continuous mining machines.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false High-voltage continuous mining machines. 18.54... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high-voltage components from lower voltage components. In each motor-starter enclosure, barriers, partitions...

  2. Archetypal analysis for machine learning and data mining

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2012-01-01

    of the observed data. We further demonstrate that the aa model is relevant for feature extraction and dimensionality reduction for a large variety of machine learning problems taken from computer vision, neuroimaging, chemistry, text mining and collaborative filtering leading to highly interpretable......Archetypal analysis (aa) proposed by Cutler and Breiman (1994) [7] estimates the principal convex hull (pch) of a data set. As such aa favors features that constitute representative ‘corners’ of the data, i.e., distinct aspects or archetypes. We currently show that aa enjoys the interpretability...... representations of the dynamics in the data. Matlab code for the derived algorithms is available for download from www.mortenmorup.dk....

  3. Study of quality of nine aluminium alloys surfaces created using abrasiv waterjet

    Czech Academy of Sciences Publication Activity Database

    Klichová, Dagmar; Klich, Jiří; Gurková, Lucie

    2016-01-01

    Roč. 2016, March 2016 (2016), s. 892-895 ISSN 1805-0476 R&D Projects: GA MŠk(CZ) LO1406; GA MŠk ED2.1.00/03.0082 Institutional support: RVO:68145535 Keywords : abrasive waterjet * aluminium alloy * optical profilometer Subject RIV: JQ - Machines ; Tools http://www.mmscience.eu/content/file/archives/MM_Science_201608.pdf

  4. Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Gatis Špats

    2016-07-01

    Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

  5. Use of IT platform in determination of efficiency of mining machines

    Directory of Open Access Journals (Sweden)

    Brodny Jarosław

    2018-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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)

  7. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce

    2011-01-01

    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  8. Long hole waterjet drilling for gas drainage

    Energy Technology Data Exchange (ETDEWEB)

    Matt Stockwell; M. Gledhill; S. Hildebrand; S. Adam; Tim Meyer [CMTE (Australia)

    2003-04-01

    In-seam drilling for gas drainage is now an essential part of operations at many Australian underground coalmines. The objective of this project is to develop and trial a new drilling method for the accurate and efficient installation of long inseam boreholes (>1000 metres). This involves the integration of pure water-jet drilling technology (i.e. not water-jet assisted rotary drilling) developed by CMTE with conventional directional drilling technology. The system was similar to conventional directional drilling methods, but instead of relying on a down-hole-motor (DHM) rotating a mechanical drill bit for cutting, high pressure water-jets were used. The testing of the system did not achieve the full objectives set down in the project plan. A borehole greater than 1000 metres was not achieved. The first trial site had coal that was weathered, oxidized and dry. These conditions significantly affected the ability of the drilling tool to stay 'in-seam'. Due to the poor conditions at the first trial, many experimental objectives were forwarded to the second field trial. In the second trial drilling difficulties were experienced, this was due to the interaction between the confinement of the borehole and the dimensions of the down hole drilling assembly. This ultimately reduced the productivity of the system and the distance that could be drilled within the specified trial periods. Testing in the first field trial did not show any indication that the system would have this difficulty.

  9. Machine Condition Monitoring Software Agent Using JADE and Data Mining

    Science.gov (United States)

    Anandan, R.

    2015-03-01

    In recent days there is a huge demand to increase the production of any mechanical components without any disturbance or mechanical faults in the machine. Therefore, to increase the productivity, it is necessary to monitor the running machine at regular intervals. To overcome such difficulties, a new machine condition monitoring software is designed using the multi agent software. This software is designed using the JADE framework and the data are analyzed using free open source Weka explorer for statistical calculations.

  10. Quantum machine learning what quantum computing means to data mining

    CERN Document Server

    Wittek, Peter

    2014-01-01

    Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine L

  11. An Evolutionary Machine Learning Framework for Big Data Sequence Mining

    Science.gov (United States)

    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…

  12. Information and diagnostic tools of objective control as means to improve performance of mining machines

    Science.gov (United States)

    Zvonarev, I. E.; Shishlyannikov, D. I.

    2017-02-01

    The paper justifies the relevance of developing and implementing automated onboard systems for operation data and maintenance recording in heading-and-winning machines. The analysis of advantages and disadvantages of existing automated onboard systems for operation data and maintenance recording in heading-and-winning machines for potassium mines are presented. The basic technical requirements for the design, operating algorithms and functions of recording systems of mining machines for potassium mines are formulated. A method of controlling operating parameters is presented; the concept of the onboard automated recording system for the Ural heading-and-winning machine is outlined. The results of experimental studies of variations in loading of the Ural-20R miner’s operating member drives, using the VATUR portable measuring complex, are given. It is proved that existing means of objective control of operating parameters of the URAL-20R heading-and-winning machine do not assure its optimal operation. The authors present a technique of analyzing the data provided by parameter recorders that allow increasing efficiency of mechanical complexes by determining numerical values characterizing the technical and technological level of potassium ore production organization. The efficiency assessment criteria for engineering and maintenance departments of mining enterprises are advanced. A technology of continuous automated monitoring of potassium mine’s outburst hazard is described.

  13. Performance analysis of cutting graphite-epoxy composite using a 90,000psi abrasive waterjet

    Science.gov (United States)

    Choppali, Aiswarya

    Graphite-epoxy composites are being widely used in many aerospace and structural applications because of their properties: which include lighter weight, higher strength to weight ratio and a greater flexibility in design. However, the inherent anisotropy of these composites makes it difficult to machine them using conventional methods. To overcome the major issues that develop with conventional machining such as fiber pull out, delamination, heat generation and high tooling costs, an effort is herein made to study abrasive waterjet machining of composites. An abrasive waterjet is used to cut 1" thick graphite epoxy composites based on baseline data obtained from the cutting of ¼" thick material. The objective of this project is to study the surface roughness of the cut surface with a focus on demonstrating the benefits of using higher pressures for cutting composites. The effects of major cutting parameters: jet pressure, traverse speed, abrasive feed rate and cutting head size are studied at different levels. Statistical analysis of the experimental data provides an understanding of the effect of the process parameters on surface roughness. Additionally, the effect of these parameters on the taper angle of the cut is studied. The data is analyzed to obtain a set of process parameters that optimize the cutting of 1" thick graphite-epoxy composite. The statistical analysis is used to validate the experimental data. Costs involved in the cutting process are investigated in term of abrasive consumed to better understand and illustrate the practical benefits of using higher pressures. It is demonstrated that, as pressure increased, ultra-high pressure waterjets produced a better surface quality at a faster traverse rate with lower costs.

  14. Identifying child abuse through text mining and machine learning

    NARCIS (Netherlands)

    Amrit, Chintan; Paauw, Tim; Aly, Robin; Lavric, Miha

    2017-01-01

    In this paper, we describe how we used text mining and analysis to identify and predict cases of child abuse in a public health institution. Such institutions in the Netherlands try to identify and prevent different kinds of abuse. A significant part of the medical data that the institutions have on

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

    Science.gov (United States)

    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.

  16. Proposition of a Solution for the Setting of the Abrasive Waterjet Cutting Technology

    Czech Academy of Sciences Publication Activity Database

    Valíček, Jan; Harničárová, M.; Kušnerová, M.; Grznárik, R.; Zavadil, J.

    2013-01-01

    Roč. 13, č. 5 (2013), s. 279-285 ISSN 1335-8871 R&D Projects: GA MŠk ED2.1.00/03.0082 Institutional support: RVO:68145535 Keywords : abrasive waterjet cutting of materials * surface topography function * correlation relations * surface roughness * optimization of technology Subject RIV: JQ - Machines ; Tools Impact factor: 1.162, year: 2013 http://www.degruyter.com/view/j/msr.2013.13.issue-5/msr-2013-0041/msr-2013-0041. xml

  17. Which method predicts recidivism best?: A comparison of statistical, machine learning, and data mining predictive models

    OpenAIRE

    Tollenaar, N.; van der Heijden, P.G.M.

    2012-01-01

    Using criminal population conviction histories of recent offenders, prediction mod els are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining and machine learning provide an improvement in predictive performance over classical statistical methods, namely logistic regression and linear discrim inant analysis. These models are compared ...

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

    Science.gov (United States)

    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.

  19. 75 FR 20918 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

    Science.gov (United States)

    2010-04-22

    ... From the Federal Register Online via the Government Publishing Office ] DEPARTMENT OF LABOR Mine Safety and Health Administration 30 CFR Parts 18 and 75 RIN 1219-AB34 High-Voltage Continuous Mining... the table titled Table 10--HIGH VOLTAGE TRAILING CABLE AMPACITIES AND OUTSIDE DIAMETERS, the first...

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

    Science.gov (United States)

    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

  1. The effects of nozzle geometry on waterjet breakup at high Reynolds numbers

    Energy Technology Data Exchange (ETDEWEB)

    Vahedi Tafreshi, H.; Pourdeyhimi, B. [Nonwovens Cooperative Research Center, North Carolina State University, NC 27695-8301, Raleigh (United States)

    2003-10-01

    Waterjet breakup is traditionally considered to follow the Ohnesorge classification. In this classification, high Reynolds number waterjets are considered to atomize quickly after discharge. By generating a constricted waterjet where the water flow stays detached all the way through the nozzle, we have observed the first wind-induced breakup mode at high Reynolds numbers. Such a peculiar behavior, however, was not observed in non-constricted waterjets. Our results indicate that, constricted jets do not follow the Ohnesorge classification, in contrast to the non-constricted waterjets. We discuss the impact of nozzle geometry on the characteristics of waterjets and support our discussion by numerical simulations. (orig.)

  2. Vibration analysis of land mine detection using high-pressure water jets

    Science.gov (United States)

    Denier, Robert; Herrick, Thomas J.

    2000-08-01

    The goal of the waterjet-based mine location and identification project is to investigate the use of waterjets to locate and differentiate buried objects. When a buried object is struck with a high-pressure waterjet, the impact will cause characteristic vibrations in the object depending on the object's shape and composition. These vibrations will be transferred to the ground and then to the water stream that is hitting the object. Some of these vibrations will also be transferred to the air via the narrow channel the waterjet cuts in the ground.

  3. Machine learning approach for text and document mining

    OpenAIRE

    Bijalwan, Vishwanath; Kumari, Pinki; Pascual, Jordan; Semwal, Vijay Bhaskar

    2014-01-01

    Text Categorization (TC), also known as Text Classification, is the task of automatically classifying a set of text documents into different categories from a predefined set. If a document belongs to exactly one of the categories, it is a single-label classification task; otherwise, it is a multi-label classification task. TC uses several tools from Information Retrieval (IR) and Machine Learning (ML) and has received much attention in the last years from both researchers in the academia and ...

  4. Machine learning for a Toolkit for Image Mining

    Science.gov (United States)

    Delanoy, Richard L.

    1995-01-01

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

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

    Science.gov (United States)

    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.

  6. Diagnostics of the Technical State of Bearings of Mining Machines Base Assemblies

    Science.gov (United States)

    Gerike, Boris L.; Mokrushev, Andrey A.

    2017-10-01

    The article reviews the methods of technical diagnostics of equipment used during maintenance of mining machines in accordance with their actual technical state, and considers the basics of vibration parameters measuring. The classification of existing methods for diagnosing the technical condition of rolling bearings is given. The advantages and disadvantages of these methods are considered. The main defects of rolling bearings arising during manufacturing, transportation, storage, and operation are considered.

  7. A Cooperative Control Method for Fully Mechanized Mining Machines Based on Fuzzy Logic Theory and Neural Networks

    Directory of Open Access Journals (Sweden)

    Chao Tan

    2015-01-01

    Full Text Available In a fully mechanized mining face, the coordinated control of coal mining machines has a significant promoting effect to perfect the mining environment and improve the efficiency of coal production and has become a research focus all over the world. In this paper, a cooperative control method based on the integration of fuzzy logic theory and neural networks was proposed. The improved Elman neural network (ENN through a threshold strategy was presented to predict the running parameters of coal mining machines. On the basis of coupling analysis of coal mining machines, the expert knowledge base of scraper conveyor was established based on fuzzy logic theory. Furthermore, the probabilistic neural network (PNN was applied to evaluate the running status of scraper conveyor, and the cooperative control flow was designed and analyzed. Finally, a simulation example was provided and the comparison results illustrated that the proposed method was feasible and superior to the manual control.

  8. Analyzing Improvements for a Mine Maintenance System of Connected Equipment and Machines - The Value and Benefits of Data Sharing

    OpenAIRE

    Fröberg, Joakim; LARSSON, STIG; Marklund, Ulf

    2015-01-01

    A modern mine involves increasingly smart and connected products that are integrated in a mine automation system. Integration enable many possible applications that could substantially aid in achieving the goals of increased safety and productivity of the mine operation including the machine maintenance process. What data will be shared by the involved organizations and products, heavily affects how successful improvements of operation can be accommodated. We have devised a method to map ...

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

    Science.gov (United States)

    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

  10. Experimental Study of the Ultrasonic Vibration-Assisted Abrasive Waterjet Micromachining the Quartz Glass

    Directory of Open Access Journals (Sweden)

    Rongguo Hou

    2018-01-01

    Full Text Available The ultrasonic vibration is used to enhance the capability of the abrasive water micromachining glass. And, the ultrasonic vibration is activated on the abrasive waterjet nozzle. The quality of the flow is improved, and the velocity of the abrasive is increased because of the addition of the ultrasonic energy. The relevant experimental results indicate that the erosion depth and the material volume removal of the glass are obviously increased when ultrasonic vibration is working. As for the influence of process parameters on the material removal of the glass such as vibration amplitude, system pressure, distance of the standoff, and abrasive size, the experimental results indicate that the system pressure and vibration contribute greatly to the glass material removal. Also, the erosion depth and the volume of material removal are increased with the increase in the vibration amplitude and system pressure. There are some uplifts found at the edge of erosion pit. Then, it can be inferred that the plastic method is an important material removal method during the machining process of ultrasonic vibration-assisted abrasive waterjet.

  11. Simulation modeling and tracing optimal trajectory of robotic mining machine effector

    Science.gov (United States)

    Fryanov, VN; Pavlova, LD

    2017-02-01

    Within the framework of the robotic coal mine design for deep-level coal beds with the high gas content in the seismically active areas in the southern Kuzbass, the motion path parameters for an effector of a robotic mining machine are evaluated. The simulation model is meant for selection of minimum energy-based optimum trajectory for the robot effector, calculation of stresses and strains in a coal bed in a variable perimeter shortwall in the course of coal extraction, determination of coordinates of a coal bed edge area with the maximum disintegration of coal, and for choice of direction of the robot effector to get in contact with the mentioned area and to break coal at the minimum energy input. It is suggested to use the model in the engineering of the robot intelligence.

  12. Determining generalized indicator for vibroacoustic hazard at workplaces of mining machines

    Energy Technology Data Exchange (ETDEWEB)

    Rezniko, I.G.

    1986-10-01

    A method is presented for calculating vibroacoustic damage to operators which is based on measuring the noise and vibration levels which occur at the workplace. A value for this indicator is presented for several types of mining machines (e.g. drills, cutter loaders, excavators etc.). It is emonstrated that when an operator is subjected to the combined effect of hazardous factors, the permissible levels of noise and vibration should be 1 1/2 times lower than those established in health and safety standards. 6 references.

  13. Integral criterion of mining machines technical condition level at their operation

    Science.gov (United States)

    Ivanov, S. L.; Shishkin, P. V.

    2017-10-01

    Nowadays classification of systems of equipment maintenance and repair (M&R), in particular, mining machines, has a wide range. However, existing systems of maintenance and repair have their own disadvantages like resource-intensiveness and cost, lack of guarantees to prevent emergency failures. In order to reduce the costs for carrying out M&R, the service system CM&R (Conscientious Maintenance and Repair) was offered, which is focused on the tendency to achieve zero emergency failures, to reduce costs and to achieve the maximum possible effectiveness of the object functioning in actual operating conditions. A unified integrated indicator of the degree of object’s degradation has been offered.

  14. Surface integrity in tangential turning of hybrid MMC A359/B4C/Al2O3by abrasive waterjet

    Czech Academy of Sciences Publication Activity Database

    Srivastava, A. K.; Naga, A.; Dixita, A. R.; Tiwaric, S.; Ščučka, Jiří; Zeleňák, Michal; Hloch, Sergej; Hlaváček, Petr

    2017-01-01

    Roč. 28, č. 28 (2017), s. 11-20 ISSN 1526-6125 R&D Projects: GA MŠk(CZ) LO1406; GA MŠk ED2.1.00/03.0082 Institutional support: RVO:68145535 Keywords : metal matrix composite * abrasive waterjet turning * surface topography * surface roughness * residual stresses Subject RIV: JQ - Machines ; Tools Impact factor: 2.322, year: 2016 http://www.sciencedirect.com/science/article/pii/S1526612517301287

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

    Directory of Open Access Journals (Sweden)

    Joanna F Dipnall

    Full Text Available 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

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

    Directory of Open Access Journals (Sweden)

    Wodecki Jacek

    2018-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  18. Influence of Water-jet Nozzle Geometry on Cutting Ability of Soft Material

    Directory of Open Access Journals (Sweden)

    Irwansyah Irwansyah

    2012-06-01

    Full Text Available Hygiene is main reason for food processor to use waterjet cutting system. Traditionally food cutting process is low-quality, unsafe products, procedures and direct contact between product and labor. This paper introduced a low cost waterjet system for cutting soft material as identic food material. The low cost waterjet system has been developed by using a commercial pressure pump for cleaning purposes and modified nozzle. In order to enhance waterjet pressure for cutting products, a modified waterjet nozzle was designed. Paramater design of waterjet system was setup on nozzle orifice diameter 0.5 mm, standoff distance 15 mm, length of nozzle cylindrical tube 2.5 mm. Polycarbonate, polysterene, and polyethelene materials are used as sample product with thickness 2 mm, to represent similar properties with agriculture products. The experimental results indicate good possibilities of waterjet system to cut material in appropriate profile surface. The waterjet also can be used to improve cutting finished surface of food products. Therefore, utilizing a low cost commercial pump and modified nozzle for waterjet system reduces equipment price, operational cost and environmental hazards. It indicates viable technology applied to substitute traditional cutting technology in post harvest agriculture products. Keywords: cutting ability, modified nozzle, polymer material, water-jet system

  19. Analysis, design and testing of high pressure waterjet nozzles

    Science.gov (United States)

    Mazzoleni, Andre P.

    1996-01-01

    The Hydroblast Research Cell at MSFC is both a research and a processing facility. The cell is used to investigate fundamental phenomena associated with waterjets as well as to clean hardware for various NASA and contractor projects. In the area of research, investigations are made regarding the use of high pressure waterjets to strip paint, grease, adhesive and thermal spray coatings from various substrates. Current industrial methods of cleaning often use ozone depleting chemicals (ODC) such as chlorinated solvents, and high pressure waterjet cleaning has proven to be a viable alternative. Standard methods of waterjet cleaning use hand held or robotically controlled nozzles. The nozzles used can be single-stream or multijet nozzles, and the multijet nozzles may be mounted in a rotating head or arranged in a fan-type shape. We consider in this paper the use of a rotating, multijet, high pressure water nozzle which is robotically controlled. This method enables rapid cleaning of a large area, but problems such as incomplete coverage (e.g. the formation of 'islands' of material not cleaned) and damage to the substrate from the waterjet have been observed. In addition, current stripping operations require the nozzle to be placed at a standoff distance of approximately 2 inches in order to achieve adequate performance. This close proximity of the nozzle to the target to be cleaned poses risks to the nozzle and the target in the event of robot error or the striking of unanticipated extrusions on the target surface as the nozzle sweeps past. Two key motivations of this research are to eliminate the formation of 'coating islands' and to increase the allowable standoff distance of the nozzle.

  20. Mechanical characteristics of a double-fed machine in asynchronous mode and prospects of its application in the electric drive of mining machines

    Science.gov (United States)

    Ostrovlyanchik, V. Yu; Popolzin, I. Yu; Kubarev, V. A.; Marshev, D. A.

    2017-09-01

    The concept of a double-fed machine as an asynchronous motor with a phase rotor and a source of additional voltage is defined. Based on the analysis of a circuit replacing the double-fed machine, an expression is derived relating the moment, slip, amplitude and phase of additional voltage across the rotor. The conditions maximizing the moment with respect to amplitude and phase of additional voltage in the rotor circuit are also obtained, the phase surface of function of machine electromagnetic moment is constructed. The analysis of basic equation of electric drive motion in relation to electric drive of mine hoisting installations and the conclusion about the necessity of work in all four quadrants of coordinate plane “moment-slip” are made. Family of mechanical characteristics is constructed for a double-fed machine and its achievable speed control range in asynchronous mode is determined. Based on the type of mechanical characteristics and the calculated range of speed control, the conclusion is made about the suitability of using a dual-fed asynchronous machine for driving mine mechanisms with a small required speed control range and the need for organizing a combined operating mode for driving mine hoisting installations and other mechanisms with a large speed control range.

  1. Machine learning and data mining advance predictive big data analysis in precision animal agriculture.

    Science.gov (United States)

    Morota, G; Ventura, R V; Silva, F F; Koyama, M; Fernando, S C

    2018-01-29

    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 non-invasive 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. © American Society of Animal Science 2018.

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

    Science.gov (United States)

    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.

  3. Visualization and analysis of balancing of the slider-crank mechanism on an elastic foundation in the mining tunneling machines

    Science.gov (United States)

    Skachkova, L. A.; Isaeva, E. S.; Feh, A. I.; Safyannikova, V. I.

    2017-01-01

    The research rationale aimed at development and use of the slider-crank mechanism in the mining equipment is justified. The advantages, as well as functional, engineering and technological features are determined for the feeder in the tunneling machine. The development ways of the structural design solutions of the slider-crank mechanism in the mining machines are specified. The analysis for balancing of the mechanism on an elastic foundation with special pendulums attached to the crankshaft is done. The calculations to justify balancing using the pendulum are done. Modeling of the slider-crank mechanism is realized.

  4. A comparative study of machine learning algorithms applied to predictive toxicology data mining.

    Science.gov (United States)

    Neagu, Daniel C; Guo, Gongde; Trundle, Paul R; Cronin, Mark T D

    2007-03-01

    This paper reports results of a comparative study of widely used machine learning algorithms applied to predictive toxicology data mining. The machine learning algorithms involved were chosen in terms of their representability and diversity, and were extensively evaluated with seven toxicity data sets which were taken from real-world applications. Some results based on visual analysis of the correlations of different descriptors to the class values of chemical compounds, and on the relationships of the range of chosen descriptors to the performance of machine learning algorithms, are emphasised from our experiments. Some interesting findings relating to the data and the quality of the models are presented--for example, that no specific algorithm appears best for all seven toxicity data sets, and that up to five descriptors are sufficient for creating classification models for each toxicity data set with good accuracy. We suggest that, for a specific data set, model accuracy is affected by the feature selection method and model development technique. Models built with too many or too few descriptors are undesirable, and finding the optimal feature subset appears at least as important as selecting appropriate algorithms with which to build a final model.

  5. CONCEPTUAL DESIGN FOR A RADICALLY SMALLER, HIGHLY ADAPTIVE AND APPLICATION-FLEXIBLE MINING MACHINE FOR UTILITY AND DEVELOPMENT WORK

    Energy Technology Data Exchange (ETDEWEB)

    Andrew H. Stern

    2004-12-20

    The aim of this research project was to develop a preliminary ''conceptual design'' for a radically smaller, highly adaptive and application-flexible underground coal mining machine, for performing non-production utility work and/or also undertake limited production mining for the recovery of reserves that would otherwise be lost. Whereas historically, mining philosophies have reflected a shift to increasing larger mechanized systems [such as the continuous miner (CM)], specific mining operations that do not benefit from the economy of the large mining equipment are often ignored or addressed with significant inefficiencies. Developing this prototype concept will create a new class of equipment that can provide opportunities to re-think the very structure of the mining system across a broad range of possibilities, not able to be met by existing machinery. The approach involved pooling the collective input from mining professionals, using a structured listing of desired inputs in the form of a questionnaire, which was used to define the range of desired design specifications. From these inputs, a conceptual specification was blended, by the author, to embody the general concurrence of mission concepts for this machine.

  6. Quantification of histone modification ChIP-seq enrichment for data mining and machine learning applications

    Directory of Open Access Journals (Sweden)

    Bekiranov Stefan

    2011-08-01

    Full Text Available Abstract Background The advent of ChIP-seq technology has made the investigation of epigenetic regulatory networks a computationally tractable problem. Several groups have applied statistical computing methods to ChIP-seq datasets to gain insight into the epigenetic regulation of transcription. However, methods for estimating enrichment levels in ChIP-seq data for these computational studies are understudied and variable. Since the conclusions drawn from these data mining and machine learning applications strongly depend on the enrichment level inputs, a comparison of estimation methods with respect to the performance of statistical models should be made. Results Various methods were used to estimate the gene-wise ChIP-seq enrichment levels for 20 histone methylations and the histone variant H2A.Z. The Multivariate Adaptive Regression Splines (MARS algorithm was applied for each estimation method using the estimation of enrichment levels as predictors and gene expression levels as responses. The methods used to estimate enrichment levels included tag counting and model-based methods that were applied to whole genes and specific gene regions. These methods were also applied to various sizes of estimation windows. The MARS model performance was assessed with the Generalized Cross-Validation Score (GCV. We determined that model-based methods of enrichment estimation that spatially weight enrichment based on average patterns provided an improvement over tag counting methods. Also, methods that included information across the entire gene body provided improvement over methods that focus on a specific sub-region of the gene (e.g., the 5' or 3' region. Conclusion The performance of data mining and machine learning methods when applied to histone modification ChIP-seq data can be improved by using data across the entire gene body, and incorporating the spatial distribution of enrichment. Refinement of enrichment estimation ultimately improved accuracy

  7. Comparisons of Hydraulic Performance in Permanent Maglev Pump for Water-Jet Propulsion

    Directory of Open Access Journals (Sweden)

    Puyu Cao

    2014-08-01

    Full Text Available The operation of water-jet propulsion can generate nonuniform inflow that may be detrimental to the performance of the water-jets. To reduce disadvantages of the nonuniform inflow, a rim-driven water-jet propulsion was designed depending on the technology of passive magnetic levitation. Insufficient understanding of large performance deviations between the normal water-jets (shaft and permanent maglev water-jets (shaftless is a major problem in this paper. CFD was directly adopted in the feasibility and superiority of permanent maglev water-jets. Comparison and discussion of the hydraulic performance were carried out. The shaftless duct firstly has a drop in hydraulic losses (K1, since it effectively avoids the formation and evolution of the instability secondary vortex by the normalized helicity analysis. Then, the shaftless intake duct improves the inflow field of the water-jet pump, with consequencing the drop in the backflow and blocking on the blade shroud. So that the shaftless water-jet pump delivers higher flow rate and head to the propulsion than the shaft. Eventually, not only can the shaftless model increase the thrust and efficiency, but it has the ability to extend the working range and broaden the high efficiency region as well.

  8. Using Machine Learning Methods Jointly to Find Better Set of Rules in Data Mining

    Directory of Open Access Journals (Sweden)

    SUG Hyontai

    2017-01-01

    Full Text Available Rough set-based data mining algorithms are one of widely accepted machine learning technologies because of their strong mathematical background and capability of finding optimal rules based on given data sets only without room for prejudiced views to be inserted on the data. But, because the algorithms find rules very precisely, we may confront with the overfitting problem. On the other hand, association rule algorithms find rules of association, where the association resides between sets of items in database. The algorithms find itemsets that occur more than given minimum support, so that they can find the itemsets practically in reasonable time even for very large databases by supplying the minimum support appropriately. In order to overcome the problem of the overfitting problem in rough set-based algorithms, first we find large itemsets, after that we select attributes that cover the large itemsets. By using the selected attributes only, we may find better set of rules based on rough set theory. Results from experiments support our suggested method.

  9. Review of data mining applications for quality assessment in manufacturing industry: support vector machines

    Directory of Open Access Journals (Sweden)

    Rostami Hamidey

    2015-01-01

    Full Text Available In many modern manufacturing industries, data that characterize the manufacturing process are electronically collected and stored in databases. Due to advances in data collection systems and analysis tools, data mining (DM has widely been applied for quality assessment (QA in manufacturing industries. In DM, the choice of technique to be used in analyzing a dataset and assessing the quality depend on the understanding of the analyst. On the other hand, with the advent of improved and efficient prediction techniques, there is a need for an analyst to know which tool performs better for a particular type of dataset. Although a few review papers have recently been published to discuss DM applications in manufacturing for QA, this paper provides an extensive review to investigate the application of a special DM technique, namely support vector machine (SVM to deal with QA problems. This review provides a comprehensive analysis of the literature from various points of view as DM concepts, data preprocessing, DM applications for each quality task, SVM preliminaries, and application results. Summary tables and figures are also provided besides to the analyses. Finally, conclusions and future research directions are provided.

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

    Science.gov (United States)

    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.

  11. The analysis of human error as causes in the maintenance of machines: a case study in mining companies

    Directory of Open Access Journals (Sweden)

    Kovacevic, Srdja

    2016-12-01

    Full Text Available This paper describes the two-step method used to analyse the factors and aspects influencing human error during the maintenance of mining machines. The first step is the cause-effect analysis, supported by brainstorming, where five factors and 21 aspects are identified. During the second step, the group fuzzy analytic hierarchy process is used to rank the identified factors and aspects. A case study is done on mining companies in Serbia. The key aspects are ranked according to an analysis that included experts who assess risks in mining companies (a maintenance engineer, a technologist, an ergonomist, a psychologist, and an organisational scientist. Failure to follow technical maintenance instructions, poor organisation of the training process, inadequate diagnostic equipment, and a lack of understanding of the work process are identified as the most important causes of human error.

  12. Ergonomics in drivers' cabs on open-cast mining machines; Ergonomie bei Fuehrerstaenden auf Tagebaugeraeten

    Energy Technology Data Exchange (ETDEWEB)

    Vater, L. [Ergonomie/Gefahrstoffe, Vattenfall Europe Mining AG, Senftenberg (Germany)

    2004-08-12

    Ergonomically designed driver's cabs also contribute directly to the increase in safety at work. In the course of the electrical re-design of the open-cast mining machines new drivers' cabs, which eliminate ergonomic deficits, were used. Other important aspects in addition to the improvements in the environmental factors noise, vibration and dust, are in particular the visibility conditions, visualisation of process data and monitoring as well as operating concepts. Taking into account the different types of machine drivers' cabs with a modified basic design and bearing design are used. Optimisation of the installation of the monitors and the basic structuring of the control panels was carried out. In addition to the increase in the effectiveness of control another aim is to minimise faulty operation by the driver when changing machines frequently. (orig.)

  13. Waterjet and laser etching: the nonlinear inverse problem

    Science.gov (United States)

    Bilbao-Guillerna, A.; Axinte, D. A.; Billingham, J.; Cadot, G. B. J.

    2017-07-01

    In waterjet and laser milling, material is removed from a solid surface in a succession of layers to create a new shape, in a depth-controlled manner. The inverse problem consists of defining the control parameters, in particular, the two-dimensional beam path, to arrive at a prescribed freeform surface. Waterjet milling (WJM) and pulsed laser ablation (PLA) are studied in this paper, since a generic nonlinear material removal model is appropriate for both of these processes. The inverse problem is usually solved for this kind of process by simply controlling dwell time in proportion to the required depth of milling at a sequence of pixels on the surface. However, this approach is only valid when shallow surfaces are etched, since it does not take into account either the footprint of the beam or its overlapping on successive passes. A discrete adjoint algorithm is proposed in this paper to improve the solution. Nonlinear effects and non-straight passes are included in the optimization, while the calculation of the Jacobian matrix does not require large computation times. Several tests are performed to validate the proposed method and the results show that tracking error is reduced typically by a factor of two in comparison to the pixel-by-pixel approach and the classical raster path strategy with straight passes. The tracking error can be as low as 2-5% and 1-2% for WJM and PLA, respectively, depending on the complexity of the target surface.

  14. Feasibility of a continuous surface mining machine using impact breakers. Phase I report, 1 October 1979-31 March 1980

    Energy Technology Data Exchange (ETDEWEB)

    Fisk, A. T.; Simpson, R. J.

    1980-04-01

    This is the first phase report of the efforts to evaluate the feasibility of excavating coal and overburden from surface mines using impact breakers. Phase I is divided into four task groups. Those tasks are as follows: Selection of Field Sites for Parametric, Selection of Impact Hammers for Field, Design Test System, and Prepare Parametric Test Plan. A detailed description and accounting of each task is given in the body of this report. Included as appendices are the FMA internal reports on the individual mines visited. These reports are the basis of test site selection. The basic finding of this phase are that industry interest in the concept of impact mining tends toward the removal of multiple thin seams of coal and parting rather than deep coal or overburden and, while the intent of this contract is to explore the feasibility of impactors in a vertical array for use in a terraced mine plan, future design of a continuous mining machine should take industry acceptance into account.

  15. Effect of Tip Clearance on Hydraulic Performance of Water-jet Pump

    Science.gov (United States)

    Yang, Duo; Huang, Zuodong; Guo, Ang; Xu, Jiawei; Jiao, Lei

    2017-10-01

    The k-ω Shear Stress Transport (SST) turbulence model is adopted to study the hydrodynamic performance of the water-jet axial pump which is applied in Unmanned Surface Vehicle (USV). The numerical simulation of the whole passage of the water-jet pump is carried out for four different tip clearance with δ = 0.3 mm, δ = 0.8 mm, δ = 1 mm and δ = 1.4 mm. And the results, in term of external characteristics and internal flow field, show that, due to the tip leakage flow, the leakage vortex is formed behind the blade after the fluid flows over the impeller blades. Moreover, with the expansion of tip clearance, the head and efficiency of the water-jet pump will be affected, and this impact is weakened with the increase of the flow rate. Finally, the suggestion of structure optimization of water-jet pump can be made.

  16. Surface properties and fatigue failure analysis of alloy 718 surfaces milled by abrasive and plain waterjet

    OpenAIRE

    Rivero, A.; Alberdi, A.; T. de Artaza; Mendia, L.; Lamikiz, A.

    2017-01-01

    This work analyzes the surfaces obtained in alloy 718 when they are milled by abrasive waterjet (AWJ) at different conditions, and the effect of main process parameters on the characteristics of these surfaces. This analysis revealed that all surfaces have a homogeneous roughness in the transversal and the longitudinal directions, present embedded abrasive particles and have hardened about 50% with respect to the untreated bulk alloy 718. In addition, plain waterjet (PWJ) technology was used ...

  17. Recent advances in remote coal mining machine sensing, guidance, and teleoperation

    Energy Technology Data Exchange (ETDEWEB)

    Ralston, J.C.; Hainsworth, D.W.; Reid, D.C.; Anderson, D.L.; McPhee, R.J. [CSIRO Exploration & Minerals, Kenmore, Qld. (Australia)

    2001-10-01

    Some recent applications of sensing, guidance and telerobotic technology in the coal mining industry are presented. Of special interest is the development of semi or fully autonomous systems to provide remote guidance and communications for coal mining equipment. The use of radar and inertial based sensors are considered in an attempt to solve the horizontal and lateral guidance problems associated with mining equipment automation. Also described is a novel teleoperated robot vehicle with unique communications capabilities, called the Numbat, which is used in underground mine safety and reconnaissance missions.

  18. Data Mining and Machine Learning in Time-Domain Discovery and Classification

    Science.gov (United States)

    Bloom, Joshua S.; Richards, Joseph W.

    2012-03-01

    The changing heavens have played a central role in the scientific effort of astronomers for centuries. Galileo's synoptic observations of the moons of Jupiter and the phases of Venus starting in 1610, provided strong refutation of Ptolemaic cosmology. These observations came soon after the discovery of Kepler's supernova had challenged the notion of an unchanging firmament. In more modern times, the discovery of a relationship between period and luminosity in some pulsational variable stars [41] led to the inference of the size of the Milky way, the distance scale to the nearest galaxies, and the expansion of the Universe (see Ref. [30] for review). Distant explosions of supernovae were used to uncover the existence of dark energy and provide a precise numerical account of dark matter (e.g., [3]). Repeat observations of pulsars [71] and nearby main-sequence stars revealed the presence of the first extrasolar planets [17,35,44,45]. Indeed, time-domain observations of transient events and variable stars, as a technique, influences a broad diversity of pursuits in the entire astronomy endeavor [68]. While, at a fundamental level, the nature of the scientific pursuit remains unchanged, the advent of astronomy as a data-driven discipline presents fundamental challenges to the way in which the scientific process must now be conducted. Digital images (and data cubes) are not only getting larger, there are more of them. On logistical grounds, this taxes storage and transport systems. But it also implies that the intimate connection that astronomers have always enjoyed with their data - from collection to processing to analysis to inference - necessarily must evolve. Figure 6.1 highlights some of the ways that the pathway to scientific inference is now influenced (if not driven by) modern automation processes, computing, data-mining, and machine-learning (ML). The emerging reliance on computation and ML is a general one - a central theme of this book - but the time

  19. Acoustic Emission Characteristics of Sedimentary Rocks Under High-Velocity Waterjet Impingement

    Science.gov (United States)

    Tian, Shouceng; Sheng, Mao; Li, Zhaokun; Ge, Hongkui; Li, Gensheng

    2017-10-01

    The success of waterjet drilling technology requires further insight into the rock failure mechanisms under waterjet impingement. By combining acoustic emission (AE) sensing and underwater sound recording techniques, an online system for monitoring submerged waterjet drilling has been developed. For four types of sedimentary rocks, their AE characteristics and correlations to the drilling performance have been obtained through time-frequency spectrum analysis. The area under the power spectrum density curve has been used as the indicator of AE energy. The results show that AE signals from the fluid dynamics and the rock failure are in different ranges of signal frequency. The main frequencies of the rock failure are within the higher range of 100-200 kHz, while the frequencies of the fluid dynamics are below 50 kHz. Further, there is a linear relationship between the AE energy and the drilling depth irrespective of rock type. The slope of the linear relationship is proportional to the rock strength and debris size. Furthermore, the AE-specific energy is a good indicator of the critical depth drilled by the waterjet. In conclusion, the AE characteristics on the power density and dominant frequency are capable of identifying the waterjet drilling performance on the rock materials and are correlated with the rock properties, i.e., rock strength and cutting size.

  20. Mining

    Directory of Open Access Journals (Sweden)

    Khairullah Khan

    2014-09-01

    Full Text Available Opinion mining is an interesting area of research because of its applications in various fields. Collecting opinions of people about products and about social and political events and problems through the Web is becoming increasingly popular every day. The opinions of users are helpful for the public and for stakeholders when making certain decisions. Opinion mining is a way to retrieve information through search engines, Web blogs and social networks. Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually. Accordingly, efficient computational methods are needed for mining and summarizing the reviews from corpuses and Web documents. This study presents a systematic literature survey regarding the computational techniques, models and algorithms for mining opinion components from unstructured reviews.

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

    Science.gov (United States)

    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.

  2. Acoustic and Doppler radar detection of buried land mines using high-pressure water jets

    Science.gov (United States)

    Denier, Robert; Herrick, Thomas J.; Mitchell, O. Robert; Summers, David A.; Saylor, Daniel R.

    1999-08-01

    The goal of the waterjet-based mine location and identification project is to find a way to use waterjets to locate and differentiate buried objects. When a buried object is struck with a high-pressure waterjets, the impact will cause characteristic vibrations in the object depending on the object's shape and composition. These vibrations will be transferred to the ground and then to the water stream that is hitting the object. Some of these vibrations will also be transferred to the air via the narrow channel the waterjet cuts in the ground. Currently the ground vibrations are detected with Doppler radar and video camera sensing, while the air vibrations are detected with a directional microphone. Data is collected via a Labview based data acquisition system. This data is then manipulated in Labview to produce the associated power spectrums. These power spectra are fed through various signal processing and recognition routines to determine the probability of there being an object present under the current test location and what that object is likely to be. Our current test area consists of a large X-Y positioning system placed over approximately a five-foot circular test area. The positioning system moves both the waterjet and the sensor package to the test location specified by the Labview control software. Currently we are able to locate buried land mine models at a distance of approximately three inches with a high degree of accuracy.

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

    Science.gov (United States)

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

    2015-06-01

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

  4. Velocity Measurements Inside the Pump of the Gulf Coast Waterjet Tow Tank Model 5600

    National Research Council Canada - National Science Library

    Chesnakas, Christopher

    2003-01-01

    An internal, three-component LDV system was used to measure the flow ahead of the rotor and inside the nozzle of a waterjet installed in a model of the R/V Athena hull as part of a program to develop...

  5. Machine Learning and Data Mining for Comprehensive Test Ban Treaty Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Russell, S; Vaidya, S

    2009-07-30

    The Comprehensive Test Ban Treaty (CTBT) is gaining renewed attention in light of growing worldwide interest in mitigating risks of nuclear weapons proliferation and testing. Since the International Monitoring System (IMS) installed the first suite of sensors in the late 1990's, the IMS network has steadily progressed, providing valuable support for event diagnostics. This progress was highlighted at the recent International Scientific Studies (ISS) Conference in Vienna in June 2009, where scientists and domain experts met with policy makers to assess the current status of the CTBT Verification System. A strategic theme within the ISS Conference centered on exploring opportunities for further enhancing the detection and localization accuracy of low magnitude events by drawing upon modern tools and techniques for machine learning and large-scale data analysis. Several promising approaches for data exploitation were presented at the Conference. These are summarized in a companion report. In this paper, we introduce essential concepts in machine learning and assess techniques which could provide both incremental and comprehensive value for event discrimination by increasing the accuracy of the final data product, refining On-Site-Inspection (OSI) conclusions, and potentially reducing the cost of future network operations.

  6. Data mining PubChem using a support vector machine with the Signature molecular descriptor: classification of factor XIa inhibitors.

    Science.gov (United States)

    Weis, Derick C; Visco, Donald P; Faulon, Jean-Loup

    2008-11-01

    The amount of high-throughput screening (HTS) data readily available has significantly increased because of the PubChem project (http://pubchem.ncbi.nlm.nih.gov/). There is considerable opportunity for data mining of small molecules for a variety of biological systems using cheminformatic tools and the resources available through PubChem. In this work, we trained a support vector machine (SVM) classifier using the Signature molecular descriptor on factor XIa inhibitor HTS data. The optimal number of Signatures was selected by implementing a feature selection algorithm of highly correlated clusters. Our method included an improvement that allowed clusters to work together for accuracy improvement, where previous methods have scored clusters on an individual basis. The resulting model had a 10-fold cross-validation accuracy of 89%, and additional validation was provided by two independent test sets. We applied the SVM to rapidly predict activity for approximately 12 million compounds also deposited in PubChem. Confidence in these predictions was assessed by considering the number of Signatures within the training set range for a given compound, defined as the overlap metric. To further evaluate compounds identified as active by the SVM, docking studies were performed using AutoDock. A focused database of compounds predicted to be active was obtained with several of the compounds appreciably dissimilar to those used in training the SVM. This focused database is suitable for further study. The data mining technique presented here is not specific to factor XIa inhibitors, and could be applied to other bioassays in PubChem where one is looking to expand the search for small molecules as chemical probes.

  7. Use of barium-strontium carbonatite for flux welding and surfacing of mining machines

    Science.gov (United States)

    Kryukov, R. E.; Kozyrev, N. A.; Usoltsev, A. A.

    2017-09-01

    The results of application of barium-strontium carbonatite for modifying and refining iron-carbon alloys, used for welding and surfacing in ore mining and smelting industry, are generalized. The technology of manufacturing a flux additive containing 70 % of barium-strontium carbonatite and 30 % of liquid glass is proposed. Several compositions of welding fluxes based on silicomanganese slag were tested. The flux additive was introduced in an amount of 1, 3, 5 %. Technological features of welding with the application of the examined fluxes are determined. X-ray spectral analysis of the chemical composition of examined fluxes, slag crusts and weld metal was carried out, as well as metallographic investigations of welded joints. The principal possibility of applying barium-strontium carbonatite as a refining and gas-protective additive for welding fluxes is shown. The use of barium-strontium carbonatite reduces the contamination of the weld seam with nonmetallic inclusions: non-deforming silicates, spot oxides and brittle silicates, and increases the desulfurizing capacity of welding fluxes.

  8. Investigation on the Usage of Some Non-Almandine Garnet Minerals as Abrasive Material in Waterjet Cutting

    OpenAIRE

    Engin, Irfan Celal; Ozkan, Erkan; Kulaksiz, Seyfi

    2011-01-01

    In this study, some non-almandine garnet minerals were investigated in terms of their usage possibilities as alternate abrasive materials in waterjet cutting operations. For this purpose, garnet samples were taken from various deposits and mineralization zones in Turkey. These samples were crushed, ground, screened, concentrated and prepared as having desired particle size distribution, and then used in waterjet cutting practices performed on different materials. Cut surfaces were also invest...

  9. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.

    Directory of Open Access Journals (Sweden)

    Erico N de Souza

    Full Text Available A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM using vessel speed as observation variable. For longliners we have designed a Data Mining (DM approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.

  10. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.

    Science.gov (United States)

    de Souza, Erico N; Boerder, Kristina; Matwin, Stan; Worm, Boris

    2016-01-01

    A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.

  11. Influence of ergonomic design on trackless mining machines on the health and safety of the operators, drivers and workers.

    CSIR Research Space (South Africa)

    Mason, S

    1998-07-01

    Full Text Available optimising new vehicle ergonomics; mines specifying the ergonomics of new vehicles; and mines improving the ergonomics standards of their current vehicles by detailed risk assessment methodologies and cost-effective retrofit modifications....

  12. Investigation of submerged waterjet cavitation through surface property and flow information in ambient water

    Science.gov (United States)

    Kang, Can; Liu, Haixia; Zhang, Tao; Li, Qing

    2017-12-01

    To illuminate primary factors influencing the morphology of the surface impinged by submerged waterjet, experiments were performed at high jet pressures from 200 to 320 MPa. The cavitation phenomenon involved in the submerged waterjet was emphasized. Copper specimens were used as the targets enduring the impingement of high-pressure waterjets. The microhardness of the specimen was measured. Surface morphology was observed using an optical profiling microscope. Pressure fluctuations near the jet stream were acquired with miniature pressure transducers. The results show that microhardness increases with jet pressure and impingement time, and the hardening effect is restricted within a thin layer underneath the target surface. A synthetic effect is testified with the plastic deformation and cavities on the specimen surfaces. Characteristics of different cavitation erosion stages are illustrated by surface morphology. At the same jet pressure, the smallest standoff distance is not corresponding to the highest mass removal rate. Instead, there is an optimal standoff distance. With the increase of jet pressure, overall mass removal rate rises as well. Low-frequency components are predominant in the pressure spectra and the dual-peak pattern is typical. As the streamwise distance from the nozzle is enlarged, pressure amplitudes associated with cavitation bubble collapse are improved.

  13. Study of the Effect of Material Machinability on Quality of Surface Created by Abrasive Water Jet

    Czech Academy of Sciences Publication Activity Database

    Klichová, Dagmar; Klich, Jiří

    2016-01-01

    Roč. 149, č. 149 (2016), s. 177-182 E-ISSN 1877-7058. [International Conference on Manufacturing Engineering and Materials, ICMEM 2016. Nový Smokovec, 06.06.2016-10.06.2016] R&D Projects: GA MŠk(CZ) LO1406 Institutional support: RVO:68145535 Keywords : machinability * surface roughness * abrasive waterjet * study of quality * aluminium alloy * optical profilometer Subject RIV: JQ - Machines ; Tools http://www.sciencedirect.com/science/article/pii/S1877705816311614

  14. Tomographic particle image velocimetry of a water-jet for low volume harvesting of fat tissue for regenerative medicine

    Directory of Open Access Journals (Sweden)

    Drobek Christoph

    2015-09-01

    Full Text Available Particle Image Velocimetry (PIV measurements of a water-jet for water-assisted liposuction (WAL are carried out to investigate the distribution of velocity and therefore momentum and acting force on the human sub-cutaneous fat tissue. These results shall validate CFD simulations and force sensor measurements of the water-jet and support the development of a new WAL device that is able to harvest low volumes of fat tissue for regenerative medicine even gentler than regular WAL devices.

  15. Webinar of paper 2013, Which method predicts recidivism best? A comparison of statistical, machine learning and data mining predictive models

    NARCIS (Netherlands)

    Tollenaar, N.; Van der Heijden, P.G.M.|info:eu-repo/dai/nl/073087998

    2013-01-01

    Using criminal population criminal conviction history information, prediction models are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining

  16. New models for energy beam machining enable accurate generation of free forms.

    Science.gov (United States)

    Axinte, Dragos; Billingham, John; Bilbao Guillerna, Aitor

    2017-09-01

    We demonstrate that, despite differences in their nature, many energy beam controlled-depth machining processes (for example, waterjet, pulsed laser, focused ion beam) can be modeled using the same mathematical framework-a partial differential evolution equation that requires only simple calibrations to capture the physics of each process. The inverse problem can be solved efficiently through the numerical solution of the adjoint problem and leads to beam paths that generate prescribed three-dimensional features with minimal error. The viability of this modeling approach has been demonstrated by generating accurate free-form surfaces using three processes that operate at very different length scales and with different physical principles for material removal: waterjet, pulsed laser, and focused ion beam machining. Our approach can be used to accurately machine materials that are hard to process by other means for scalable applications in a wide variety of industries.

  17. New process for screen cutting: water-jet guided laser

    Science.gov (United States)

    Perrottet, Delphine; Amorosi, Simone; Richerzhagen, Bernold

    2005-07-01

    Today's OLED manufacturers need high-precision, fast tools to cut the metal screens used to deposit the electroluminescent layers onto the substrate. Conventional methods -tching and dry laser cutting - are not satisfying regarding the demands of high-definition OLED displays. A new micro machining technology, the water jet guided laser - a hybrid of laser and water jet technologies that has been actively used in recent years in the electronic and semiconductor field - is now available to OLED manufacturers. This technology represents a significant improvement in screen, mask and stencil cutting, as it combines high precision and high speed. It is able to cut small apertures with totally clean edges (no dross or slag), as the water jet removes the particles and a thin water film is maintained on the material surface during the process. Because the water jet cools the material between the laser pulses, the cut material is free of any thermal stress. The water jet guided laser is also a very fast process: as an example, rectangular slots can be cut in 30 to 50 microns thick stainless steel or nickel at a rate between 25'000 and 30'000 holes per hour.

  18. PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

    Directory of Open Access Journals (Sweden)

    Baskin Berivan

    2003-03-01

    Full Text Available Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. Results Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. Conclusions Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.

  19. Effect of Pulsed Waterjet Surface Preparation on the Adhesion Strength of Cold Gas Dynamic Sprayed Aluminum Coatings

    Science.gov (United States)

    Samson, T.; MacDonald, D.; Fernández, R.; Jodoin, B.

    2015-08-01

    It has been observed that the method of substrate surface preparation can have a profound effect on the adhesion strength of cold-sprayed metallic coatings. In this investigation, pure aluminum powder was sprayed onto aluminum alloy substrates using cold spray. The substrates used in this work had undergone a variety of surface preparations to impart varying degrees of surface roughness. The pulsed waterjet technique was used to increase the substrates' surface roughness beyond what can be achieved using traditional grit blasting procedures. Surfaces prepared using pulsed waterjet resulted in substantial increases in the pure aluminum coating adhesion strength. This increase may be the result of increased mechanical anchoring sites available as well as their favorable geometries. It is hypothesized that compressive residual stress may also contribute to increased adhesion strength.

  20. Numerical analysis of head degrade law under cavitation condition of contra-rotating axial flow waterjet pump

    Science.gov (United States)

    Huang, D.; Pan, Z. Y.

    2015-01-01

    In order to study the flow-head characteristic curve, the SST turbulence model, homogeneous multiphase model and Rayleigh-Plesset equation were applied to simulate the cavitation characteristics in contra-rotating axial flow waterjet pump under different conditions based on ANSYS CFX software. The distribution of cavity, pressure coefficient of the blade at the design point under different cavitation conditions were obtained. The analysis results of flow field show that the vapour volume distribution on the impeller indicates that the vapour first appears at the leading edge of blade and then extends to the outlet of impeller with the reduction of Net Positive Suction Head Allowance (NPSHA). The present study illustrates that the main reason for the decline of the pump performance is the development of cavitation, and the simulation can truly reflect the cavitation performance of the contra-rotating axial flow waterjet pump.

  1. Machine learning for prediction of 30-day mortality after ST elevation myocardial infraction: An Acute Coronary Syndrome Israeli Survey data mining study.

    Science.gov (United States)

    Shouval, Roni; Hadanny, Amir; Shlomo, Nir; Iakobishvili, Zaza; Unger, Ron; Zahger, Doron; Alcalai, Ronny; Atar, Shaul; Gottlieb, Shmuel; Matetzky, Shlomi; Goldenberg, Ilan; Beigel, Roy

    2017-11-01

    Risk scores for prediction of mortality 30-days following a ST-segment elevation myocardial infarction (STEMI) have been developed using a conventional statistical approach. To evaluate an array of machine learning (ML) algorithms for prediction of mortality at 30-days in STEMI patients and to compare these to the conventional validated risk scores. This was a retrospective, supervised learning, data mining study. Out of a cohort of 13,422 patients from the Acute Coronary Syndrome Israeli Survey (ACSIS) registry, 2782 patients fulfilled inclusion criteria and 54 variables were considered. Prediction models for overall mortality 30days after STEMI were developed using 6 ML algorithms. Models were compared to each other and to the Global Registry of Acute Coronary Events (GRACE) and Thrombolysis In Myocardial Infarction (TIMI) scores. Depending on the algorithm, using all available variables, prediction models' performance measured in an area under the receiver operating characteristic curve (AUC) ranged from 0.64 to 0.91. The best models performed similarly to the Global Registry of Acute Coronary Events (GRACE) score (0.87 SD 0.06) and outperformed the Thrombolysis In Myocardial Infarction (TIMI) score (0.82 SD 0.06, p<0.05). Performance of most algorithms plateaued when introduced with 15 variables. Among the top predictors were creatinine, Killip class on admission, blood pressure, glucose level, and age. We present a data mining approach for prediction of mortality post-ST-segment elevation myocardial infarction. The algorithms selected showed competence in prediction across an increasing number of variables. ML may be used for outcome prediction in complex cardiology settings. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  2. Intelligent Self-Powered Sensors in the State-of-the-Art Control Systems of Mining Machines

    Science.gov (United States)

    Jasiulek, Dariusz; Stankiewicz, Krzysztof; Woszczyński, Mariusz

    2016-12-01

    Perspectives of development of control system dedicated for areas threatened by methane and/or coal dust explosion hazard are presented. Development of self-powered sensors, dedicated for operation in wireless network is one of the development directions. Such a solution will complement typical control systems and it can be used in the places, where there is no possibility of using the typical sensors, in close vicinity to the machine - due to lack of wired connection. General concept of the self-powered sensors with use of two methods of power supply - piezoelectric energy harvester and thermoelectric generator, is given. Perspective of using the methods of artificial intelligence in automatic configuration of sensors network is suggested.

  3. Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study.

    Science.gov (United States)

    Cheng, Qijin; Li, Tim Mh; Kwok, Chi-Leung; Zhu, Tingshao; Yip, Paul Sf

    2017-07-10

    Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention. The aim of this study was to explore whether computerized language analysis methods can be utilized to assess one's suicide risk and emotional distress in Chinese social media. A Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants' Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors. A total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, Psocial media and can identify characteristics different from previous findings in the English literature. Some findings are leading to new hypotheses for future verification. Machine classifiers based on SC-LIWC features are promising but still require further optimization for application in real life.

  4. Evaluation of three state-of-the-art water-jet systems for cutting/removing concrete

    Science.gov (United States)

    Pace, C. E.

    1982-09-01

    This report documents a demonstration project to evaluate the capability of three waterjet systems for cutting or removing concrete or both. The Corps of Engineers is interested in the potential of this technology for such applications as rapid cutting of bomb-damaged selection of airfield pavement and removing of deteriorated sections of concrete structures at Civil Works projects. Because water-jet systems are capable of transmitting, without mechanical constraint, all of the available horsepower of their power sources into the concrete cutting/removing operation, they may prove to be an extremely efficient means of conducting such operations. The low-pressure water jets were able to cut a 6-in. slot in the concrete for a distance of 1-1/2 ft. in a period of 24 minutes (a rate of 6.4 ft. per hour). The relatively high-pressure water jet cut at rates of 9.6 ft. per hour for shallow cuts (less than 5 in.) and 3 ft. per hour for deeper cuts (greater than 5 in.). In addition, one of the low-pressure systems was used to remove some surface concrete. The results of this evaluation indicate that, although these water-jet systems did not demonstrate a capability for efficiently cutting concrete airfield pavements, the technology has potential. The low-pressure system demonstrated a capability for removing surface concrete efficiently.

  5. Analysis of changes in hardness of a metal surface layer in areas of high stress and methods of determining residual life of parts for mining machines

    Science.gov (United States)

    Zvonarev, I. E.; Ivanov, S. L.

    2016-02-01

    The methodological bases for determining the energy resource of mechanical transmissions details for mining machines are considered. Based on the analysis of the accumulation of damage in metal gears, a method of estimating residual life of coarse-toothed wheels by periodically measuring the hardness of the surface layer of the teeth is justified. The regularities in change of hardness of coarse-tooth gear, conditioned by a change in metal strength properties that take into account the micro- and macromechanisms of plastic and elastic deformation, distortion of the metal crystal lattice with formation and movement of vacancies and dislocations. Experimental setup was built and the results of laboratory experiments are given related to the process of destruction of non-standard samples under different loads. Comparison of dimensions and hardness values of the sample allows concluding that a larger deformation corresponds to a greater increase in hardness, their limit value for the material being in the fracture zone. It is established that the detected changes in the local hardness occurs in areas of increased stresses above the limit of proportionality and the work of fracture forces attributed to dislocations density adjacent to the fracture plane expressed in terms of hardness increment is constant.

  6. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

  7. Pengembangan Rancangan Nozzle Waterjet untuk Meningkatkan Kecepatan Renang pada Tank BMP-3F (Infantry Fighting Vehicle

    Directory of Open Access Journals (Sweden)

    Rozzaqi Anata

    2013-09-01

    Full Text Available Negara Kepulauan Republik Indonesia (NKRI memiliki wilayah  perairan yang luas, sehingga pertahanan negara di sektor perairan menjadi lebih dirapatkan. Strategi yang dibentuk adalah dengan memproduksi dan membeli kendaraan tempur. Salah satu kendaraan yang dibeli adalah tank amphibi BMP-3F buatan rusia. Kendaraan tank ini ketika dioperasikan di perairan hanya mencapai kecepatan 10 km/h, oleh karena itu akan dilakukan pengembangan perancangan nozzle waterjet untuk dapat meningkatkan kecepatan renang dari tank BMP-3F. Sehingga dilakukan beberapa modifikasi dari variasi nozzle yang akan dianalisa menggunakan SolidWorks yakni variasi diameter nozzle dari kondisi awal 140 mm hingga menjadi 110 mm, serta perbedaan sudut nozzle yang nantinya akan membentuk cone, dari 10 hingga 40, serta penambahan ulir pada sisi outlet water jet. Dari hasil analisa data dan perhitungan diperoleh untuk hasil thrust tertinggi dengan bentuk nozzle cone variasi 40 menghasilkan thrust sebesar 146,347 kN dengan kecepatan renang meningkat sebesar 89% dari kecepatan awal yakni menjadi 10,017 knot pada saat thrust deduction factor sebesar 0,3076.

  8. Numerical and Experimental Studies of Cavitation Behavior in Water-Jet Cavitation Peening Processing

    Directory of Open Access Journals (Sweden)

    H. Zhang

    2013-01-01

    Full Text Available Water-jet cavitation peening (WCP is a new technology for the surface modification of metallic materials. The cavitation behavior in this process involves complex and changeable physics phenomena, such as high speed, high pressure, multiple phases, phase transition, turbulence, and unstable features. Thus, the cavitation behavior and impact-pressure distribution in WCP have always been key problems in this field. Numerous factors affect the occurrence of cavitation. These factors include flow-boundary conditions, absolute pressure, flow velocity, flow viscosity, surface tension, and so on. Among these factors, pressure and vapor fraction are the most significant. Numerical simulations are performed to determine the flow-field characteristics of both inside and outside the cavitating nozzle of a submerged water jet. The factors that influence the cavitation intensity of pressure are simulated. Fujifilm pressure-sensitive paper is used to measure the distribution of impact pressure along the jet direction during the WCP process. The results show that submerged cavitation jets can induce cavitation both inside and outside a conical nozzle and a convergent-divergent nozzle when the inlet pressure is 32 MPa. Moreover, the shock wave pressure induced by the collapse of the bubble group reaches up to 300 MPa.

  9. Fluid structure interaction dynamic analysis of a mixed-flow waterjet pump

    Science.gov (United States)

    Pan, X. W.; Y Pan, Z.; Huang, D.; Shen, Z. H.

    2013-12-01

    In order to avoid resonance of a mixed-flow waterjet pump at run time and calculate the stress and deformation of the pump rotor in the flow field, a one-way fluid structure interaction method was applied to simulate the pump rotor using ANSYS CFX and ANSYS Workbench software. The natural frequencies and mode shapes of the pump rotor in the air and in the flow field were analyzed, and the stress and deformation of the impeller were obtained at different flow rates. The obtained numerical results indicated that the mode shapes were similar both in the air and in the flow field, but the pump rotor's natural frequency in the flow field was slightly smaller than that in the air; the difference of the pump rotor's natural frequency varied lightly at different flow rates, and all frequencies at different flow rates were higher than the safe frequency, the pump rotor under the effect of prestress rate did not occur resonance; The maximum stress was on the blade near the hub and the maximum deformation on the blade tip at different flow rates.

  10. Optimization of machining processes using pattern search algorithm

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2014-04-01

    Full Text Available Optimization of machining processes not only increases machining efficiency and economics, but also the end product quality. In recent years, among the traditional optimization methods, stochastic direct search optimization methods such as meta-heuristic algorithms are being increasingly applied for solving machining optimization problems. Their ability to deal with complex, multi-dimensional and ill-behaved optimization problems made them the preferred optimization tool by most researchers and practitioners. This paper introduces the use of pattern search (PS algorithm, as a deterministic direct search optimization method, for solving machining optimization problems. To analyze the applicability and performance of the PS algorithm, six case studies of machining optimization problems, both single and multi-objective, were considered. The PS algorithm was employed to determine optimal combinations of machining parameters for different machining processes such as abrasive waterjet machining, turning, turn-milling, drilling, electrical discharge machining and wire electrical discharge machining. In each case study the optimization solutions obtained by the PS algorithm were compared with the optimization solutions that had been determined by past researchers using meta-heuristic algorithms. Analysis of obtained optimization results indicates that the PS algorithm is very applicable for solving machining optimization problems showing good competitive potential against stochastic direct search methods such as meta-heuristic algorithms. Specific features and merits of the PS algorithm were also discussed.

  11. Text Mining Applications and Theory

    CERN Document Server

    Berry, Michael W

    2010-01-01

    Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning

  12. TENDENCY OF APPLYING LHD MEHANIZATION IN MINING WORKINGS

    Directory of Open Access Journals (Sweden)

    Vladimir Rendulić

    1995-12-01

    Full Text Available Changed working conditions in deep mining workings (underground rooms of a mine havc lead, by application of diesel driven mechanization to the tendency of introducing the eleetric LHD machines in mines. However, although the flexibilily of electric mining machines has been improved due to the efforts of factories producing mining machines, the diesel units are still more flexible in application, although their maintenance in pit drives is more exspensive (the paper is published in Croatian.

  13. Introducing Machine Learning Concepts with WEKA.

    Science.gov (United States)

    Smith, Tony C; Frank, Eibe

    2016-01-01

    This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorithms for other types of data mining problems, and provides suggestions about where to find additional information.

  14. Breast reconstruction de novo by water-jet assisted autologous fat grafting – a retrospective study

    Directory of Open Access Journals (Sweden)

    Hoppe, Delia Letizia

    2013-12-01

    Full Text Available [english] Background: Autologous fat grafting has become a frequent, simple, reproducible and low-risk technique for revisional or partial breast reconstruction. The presented European multicenter study describes an optimized treatment and follow-up protocol for the de novo breast reconstruction after total mastectomy by lipotransfer alone.Methods: A retrospective European multicenter trial included 135 procedures on 28 (35 breasts postmastectomy patients (mean 52.4 years. All women were treated with the water-jet assisted fat grafting method (BEAULI™ combined with additional procedures (NAC reconstruction, contralateral mastoplasty and evaluated with at least 6 months follow-up (mean 2.6 years. Sonography or mammography, clinical examination, patient questionnaire (10-point Likert scale and digital photographs were carried out.Results: On average the patients received 4 to 6 procedures each with a single volume of 159 ml (±61 ml over 21 months (range 9 months to 2.5 years. In total 1,020 ml (±515 ml fat were grafted till a complete breast reconstruction was achieved. Irradiated patients needed a significantly higher volume than non-irradiated (p<0.041. Main treatment complications were liponecrosis (2.59%, infection (0.74% and granuloma (0.74%. Patient satisfaction was overall high to very high (96% and confirmed the good aesthetic results (68% and the natural softness, contour and shape of the reconstructed breast.Conclusions: A complete breast reconstruction with large volume fat grafting is alternatively possible to standard techniques in selected cases. It takes at least 4 to 6 lipotransfers in the course of 2 years. Patients with prior radiotherapy may require even up to 8 sessions over nearly 3 years of treatment.

  15. Method for Virtual Prototyping of Cabins of Mining Machines Operators / Metoda Wirtualnego Prototypowania Kabin Operatorów Maszyn Górniczych

    Science.gov (United States)

    Tokarczyk, Jarosław

    2015-03-01

    Method for virtual prototyping of cabins of mining machines operators is presented in the light of anthropotechnical assessment criteria. Anthropotechnical criteria and design of models of anthropometric features, which are used for assessment of design solutions in the aspect of safety criterion, are divided and discussed. Developed virtual prototyping method for assessment of cabin of underground locomotive operator was used. Initial simulation was made with use of Finite Element Method. W artykule przedstawiono metodę wirtualnego prototypowania kabin operatorów maszyn górniczych w świetle antropotechnicznych kryteriów oceny. Dokonano podziału i omówiono kryteria antropotechniczne. Przedstawiono definicję kryterium urazu głowy HIC (ang. Head Injury Criterion) oraz prawdopodobieństwo wystąpienia urazu głowy w funkcji wartości parametru HIC. Zaprezentowano budowę modeli cech antropometrycznych, dedykowanych do oceny rozwiązań konstrukcyjnych w aspekcie kryterium bezpieczeństwa wraz z opisem statycznych i dynamicznych cech antropometrycznych. Omówiono proces tworzenia wirtualnego odpowiednika manekina do testów zderzeniowych, tzw. modelu ATB (ang. Articulated Total Body). Podano odniesienia do norm dotyczących konstrukcji chroniących operatorów przed spadającymi przedmiotami. Przedstawiono schemat metody wirtualnego prototypowania kabin operatorów w aspekcie kryterium bezpieczeństwa. Zastosowano opracowaną metodę wirtualnego prototypowania do oceny kabiny operatora lokomotywy dołowej. Omówiono główne elementy składowe modelu obliczeniowego. Zadanie rozwiązano przy użyciu metody elementów skończonych. Przedstawiono wstępne wyniki symulacji, tj. obliczono parametr HIC dla zadanych warunków brzegowych. W podsumowaniu zaprezentowano główne cele wirtualnego prototypowania kabin operatorów dla kryterium bezpieczeństwa. Zwrócono uwagę na uniwersalność zastosowanej metody.

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

    Science.gov (United States)

    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.

  17. Effect of Abrasive Waterjet Peening Surface Treatment of Steel Plates on the Strength of Single-Lap Adhesive Joints

    Directory of Open Access Journals (Sweden)

    Kamil Anasiewicz

    2017-09-01

    Full Text Available The paper presents results of comparative study of shear strength of single–lap adhesive joints, depending on the method of surface preparation of steel plates with increased corrosion resistance. The method of preparing adherend surfaces is often one of the most important factors determining the strength of adhesive joints. Appropriate geometric surface development and cleaning of the surface enhances adhesion forces between adherend material and adhesive. One of the methods of shaping engineering materials is waterjet cutting, which in the AWJP – abrasive waterjet peening variant, serves to shape flat surfaces of the material by changing the roughness and introducing stresses into the surface layer. These changes are valuable when preparing adhesive joints. In the study, surface roughness parameters obtained with AWJP treatment, were analyzed in direct relation to the strength of the adhesive joint. As a consequence of the experimental results analysis, the increase in the strength of the adhesive joints was observed in a certain range of parameters used for AWJP treatment. A decrease in shear strength of adhesive joint with the most modified topography of overlap surface was observed.

  18. Mechanism of the high efficiency of the cutting frozen food products using water-jet with polymer additions

    Directory of Open Access Journals (Sweden)

    A. Pogrebnyak

    2017-06-01

    Full Text Available The article to determine peculiarities of macromolecule deformation behavior under conditions of a jet-shaping head that would allow to solve the issue related to the mechanism of increasing water-jet cutting power with polymer additions. In converging polyethyleneoxide solution flow macromolecules are forced by a hydrodynamic field to rather strong stretching that causes the dynamic structure formation in solutions. There have been studied experimentally velocity fields and their gradients as well as the degree of macromolecule unrolling under pattern conditions of a jet-shaping head in poluyethyleneoxide solutions flow. In converging polymer solution flow macromolecules are forced by a hydrodynamic field to rather strong (~ 60 % and more stretching that causes the field restructuring. The determined regularities of macromolecules behavior in the flow under conditions of a jet-shaping head and manifested in this case effects of elastic deformations have paramount importance in understanding the mechanism of «anomalously» high cutting power of water-polymer jet. The work for the first time makes it possible to explain the nature of increased water-jet cutting power with polymer additions when cutting food products. Understanding the nature of increased cutting power of water-polymer jet will make it possible to develop recommendations on choosing regimes for water-polymer jet processing of food products by cutting.

  19. Data mining in bioinformatics using Weka

    National Research Council Canada - National Science Library

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

    2004-01-01

    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...

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

    Directory of Open Access Journals (Sweden)

    Dhanjee Kumar Chaudhary

    2015-12-01

    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.

  1. Higher education in mining in Austria

    Energy Technology Data Exchange (ETDEWEB)

    Pindera, M.

    1987-09-01

    Describes the curricula in Austrian higher education in mining. The first stage of study comprises fundamental subjects. The second is divided into mining, oil drilling and surveying, leading to the Master of Science degree in 10 semesters. The second stage of mining studies concentrates on mining, separation and cleaning, mining machines, science of deposits, and surveying. Describes the course of doctoral studies and the employment opportunities for graduates. 2 refs.

  2. Data mining theories, algorithms, and examples

    CERN Document Server

    Ye, Nong

    2013-01-01

    AN OVERVIEW OF DATA MINING METHODOLOGIESIntroduction to data mining methodologiesMETHODOLOGIES FOR MINING CLASSIFICATION AND PREDICTION PATTERNSRegression modelsBayes classifiersDecision treesMulti-layer feedforward artificial neural networksSupport vector machinesSupervised clusteringMETHODOLOGIES FOR MINING CLUSTERING AND ASSOCIATION PATTERNSHierarchical clusteringPartitional clusteringSelf-organized mapProbability distribution estimationAssociation rulesBayesian networksMETHODOLOGIES FOR MINING DATA REDUCTION PATTERNSPrincipal components analysisMulti-dimensional scalingLatent variable anal

  3. 30 CFR 18.97 - Inspection of machines; minimum requirements.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Inspection of machines; minimum requirements... 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...

  4. Data Stream Mining

    Science.gov (United States)

    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).

  5. Data mining mobile devices

    CERN Document Server

    Mena, Jesus

    2013-01-01

    With today's consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertaining to human social behavior. It explains how the integration of data mining and machine learning can enable the modeling of conversation context, proximity sensing, and geospatial location throughout large communities of mobile users

  6. Testing of Alternative Abrasives for Water-Jet Cutting at C Tank Farm

    Energy Technology Data Exchange (ETDEWEB)

    Krogstad, Eirik J.

    2013-08-01

    Legacy waste from defense-related activities at the Hanford Site has predominantly been stored in underground tanks, some of which have leaked; others may be at risk to do so. The U.S. Department of Energy’s goal is to empty the tanks and transform their contents into more stable waste forms. To do so requires breaking up, and creating a slurry from, solid wastes in the bottoms of the tanks. A technology developed for this purpose is the Mobile Arm Retrieval System. This system is being used at some of the older single shell tanks at C tank farm. As originally planned, access ports for the Mobile Arm Retrieval System were to be cut using a high- pressure water-jet cutter. However, water alone was found to be insufficient to allow effective cutting of the steel-reinforced tank lids, especially when cutting the steel reinforcing bar (“rebar”). The abrasive added in cutting the hole in Tank C-107 was garnet, a complex natural aluminosilicate. The hardness of garnet (Mohs hardness ranging from H 6.5 to 7.5) exceeds that of solids currently in the tanks, and was regarded to be a threat to Hanford Waste Treatment and Immobilization Plant systems. Olivine, an iron-magnesium silicate that is nearly as hard as garnet (H 6.5 to 7), has been proposed as an alternative to garnet. Pacific Northwest National Laboratory proposed to test pyrite (FeS2), whose hardness is slightly less (H 6 to 6.5) for 1) cutting effectiveness, and 2) propensity to dissolve (or disintegrate by chemical reaction) in chemical conditions similar to those of tank waste solutions. Cutting experiments were conducted using an air abrader system and a National Institute of Standards and Technology Standard Reference Material (SRM 1767 Low Alloy Steel), which was used as a surrogate for rebar. The cutting efficacy of pyrite was compared with that of garnet and olivine in identical size fractions. Garnet was found to be most effective in removing steel from the target; olivine and pyrite were less

  7. Large Mines and the Community

    International Development Research Centre (IDRC) Digital Library (Canada)

    However, as the community matures it is common for it to provide vehicle repair, machine shop services, welding, sheet metal work, plumbing, and electrical services. In areas with multiple mining projects, the next step for local business is complex construction projects. Finally, in major mining areas, production occurs of ...

  8. Multi-relational data mining

    NARCIS (Netherlands)

    A.J. Knobbe (Arno); H. Blockeel; A.P.J.M. Siebes (Arno); D.M.G. van der Wallen

    1999-01-01

    textabstractAn important aspect of data mining algorithms and systems is that they should scale well to large databases. A consequence of this is that most data mining tools are based on machine learning algorithms that work on data in attribute-value format. Experience has proven that such

  9. APPLICATION OF WATER-JET HORIZONTAL DRILLING TECHNOLOGY TO DRILL AND ACIDIZE HORIZONTAL DRAIN HOLES, TEDBIT (SAN ANDRES) FIELD, GAINES COUNTY, TEXAS

    Energy Technology Data Exchange (ETDEWEB)

    Michael W. Rose

    2005-09-22

    The San Andres Formation is one of the major hydrocarbon-producing units in the Permian Basin, with multiple reservoirs contained within the dolomitized subtidal portions of upward shoaling carbonate shelf cycles. The test well is located in Tedbit (San Andres) Field in northeastern Gaines County, Texas, in an area of scattered San Andres production associated with local structural highs. Selected on the basis of geological and historical data, the Oil and Gas Properties Wood No. 1 well is considered to be typical of a large number of San Andres stripper wells in the Permian Basin. Thus, successful completion of horizontal drain holes in this well would demonstrate a widely applicable enhanced recovery technology. Water-jet horizontal drilling is an emerging technology with the potential to provide significant economic benefits in marginal wells. Forecast benefits include lower recompletion costs and improved hydrocarbon recoveries. The technology utilizes water under high pressure, conveyed through small-diameter coiled tubing, to jet horizontal drain holes into producing formations. Testing of this technology was conducted with inconclusive results. Paraffin sludge and mechanical problems were encountered in the wellbore, initially preventing the water-jet tool from reaching the kick-off point. After correcting these problems and attempting to cut a casing window with the water-jet milling assembly, lateral jetting was attempted without success.

  10. Frequent pattern mining

    CERN Document Server

    Aggarwal, Charu C

    2014-01-01

    Proposes numerous methods to solve some of the most fundamental problems in data mining and machine learning Presents various simplified perspectives, providing a range of information to benefit both students and practitioners Includes surveys on key research content, case studies and future research directions

  11. 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.

    Science.gov (United States)

    Maroco, João; Silva, Dina; Rodrigues, Ana; Guerreiro, Manuela; Santana, Isabel; de Mendonça, Alexandre

    2011-08-17

    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. Press' Q test showed that all classifiers performed better than chance alone (p 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

  12. Application of multi-stage Monte Carlo method for solving machining optimization problems

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2014-08-01

    Full Text Available Enhancing the overall machining performance implies optimization of machining processes, i.e. determination of optimal machining parameters combination. Optimization of machining processes is an active field of research where different optimization methods are being used to determine an optimal combination of different machining parameters. In this paper, multi-stage Monte Carlo (MC method was employed to determine optimal combinations of machining parameters for six machining processes, i.e. drilling, turning, turn-milling, abrasive waterjet machining, electrochemical discharge machining and electrochemical micromachining. Optimization solutions obtained by using multi-stage MC method were compared with the optimization solutions of past researchers obtained by using meta-heuristic optimization methods, e.g. genetic algorithm, simulated annealing algorithm, artificial bee colony algorithm and teaching learning based optimization algorithm. The obtained results prove the applicability and suitability of the multi-stage MC method for solving machining optimization problems with up to four independent variables. Specific features, merits and drawbacks of the MC method were also discussed.

  13. Data Mining and Machine Learning Algorithms Using IL28B Genotype and Biochemical Markers Best Predicted Advanced Liver Fibrosis in Chronic Hepatitis C.

    Science.gov (United States)

    Shousha, Hend Ibrahim; Awad, Abubakr Hussein; Omran, Dalia Abdelhamid; Elnegouly, Mayada Mohamed; Mabrouk, Mahasen

    2018-01-23

    IL28B single nucleotide polymorphism (rs12979860) is an etiology-independent predictor of hepatitis C virus (HCV)-related hepatic fibrosis. Data mining is a method of predictive analysis which can explore tremendous volumes of information from health records to discover hidden patterns and relationships. The current study aims to evaluate and compare the prediction accuracy of scoring system like aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) index versus data mining for the prediction of HCV-related advanced fibrosis. This retrospective study included 427 patients with chronic hepatitis C. We used data mining analysis to construct a decision tree by reduced error (REP) technique, followed by Auto-WEKA tool to select the best classifier out of 39 algorithms to predict advanced fibrosis. APRI and FIB-4 had sensitivity-specificity parameters of 0.523-0.831 and 0.415-0.917, respectively. REPTree algorithm was able to predict advanced fibrosis with sensitivity of 0.749, specificity of 0.729, and receiver operating characteristic (ROC) area of 0.796. Out of the 16 attributes, IL28B genotype was selected by the REPTree as the best predictor for advanced fibrosis. Using Auto-WEKA, the multilayer perceptron (MLP) neural model was selected as the best predictive algorithm with sensitivity of 0.825, specificity of 0.811, and ROC area of 0.880. Thus, MLP is better than APRI, FIB-4, and REPTree for predicting advanced fibrosis for patients with chronic hepatitis C.

  14. Effects of edge grinding and sealing on mechanical properties of machine damaged laminate composites

    Science.gov (United States)

    Asmatulu, Ramazan; Yeoh, Jason; Alarifi, Ibrahim M.; Alharbi, Abdulaziz

    2016-04-01

    Fiber reinforced composites have been utilized for a number of different applications, including aircraft, wind turbine, automobile, construction, manufacturing, and many other industries. During the fabrication, machining (waterjet, diamond and band saws) and assembly of these laminate composites, various edge and hole delamination, fiber pullout and other micro and nanocracks can be formed on the composite panels. The present study mainly focuses on the edge grinding and sealing of the machine damaged fiber reinforced composites, such as fiberglass, plain weave carbon fiber and unidirectional carbon fiber. The MTS tensile test results confirmed that the composite coupons from the grinding process usually produced better and consistent mechanical properties compared to the waterjet cut samples only. In addition to these studies, different types of high strength adhesives, such as EPON 828 and Loctite were applied on the edges of the prepared composite coupons and cured under vacuum. The mechanical tests conducted on these coupons indicated that the overall mechanical properties of the composite coupons were further improved. These processes can lower the labor costs on the edge treatment of the composites and useful for different industrial applications of fiber reinforced composites.

  15. On the fatigue behavior of medical Ti6Al4V roughened by grit blasting and abrasiveless waterjet peening.

    Science.gov (United States)

    Lieblich, M; Barriuso, S; Ibáñez, J; Ruiz-de-Lara, L; Díaz, M; Ocaña, J L; Alberdi, A; González-Carrasco, J L

    2016-10-01

    Flat fatigue specimens of biomedical Ti6Al4V ELI alloy were surface-processed by high pressure waterjet peening (WJP) without abrasive particles using moderate to severe conditions that yield roughness values in the range of those obtained by commercial grit blasting (BL) with alumina particles. Fatigue behavior of WJP and BL specimens was characterized under cyclical uniaxial tension tests (R=0.1). The emphasis was put on a comparative analysis of the surface and subsurface induced effects and in their relevance on fatigue behavior. Within the experimental setup of this investigation it resulted that blasting with alumina particles was less harmful for fatigue resistance than abrasiveless WJP. BL specimens resulted in higher subsurface hardening and compressive residual stresses. Specimens treated with more severe WJP parameters presented much higher mass loss and lower compressive residual stresses. From the analysis performed in this work, it follows that, in addition to roughness, waviness emerges as another important topographic parameter to be taken into account to try to predict fatigue behavior. It is envisaged that optimization of WJP parameters with the aim of reducing waviness and mass loss should lead to an improvement of fatigue resistance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Mining software specifications methodologies and applications

    CERN Document Server

    Lo, David

    2011-01-01

    An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software Specifications: Methodologies and Applications describes recent approaches for mining specifications of software systems. Experts in the field illustrate how to apply state-of-the-art data mining and machine learning techniques to address software engineering concerns. In the first set of chapters, the book introduces a number of studies on mining finite

  17. Laser re-manufacturing of failure 18Cr2Ni4WA gear in low-speed heavy-load mining machine transmission

    Science.gov (United States)

    Chi, X. F.

    2017-10-01

    This article investigated laser re-manufacturing technology application in mining industry. The research focused on green re-manufacturing of failure spur. Leave the main gear body stay intact after the dirty, rust, fatigue and injured part were removed completely before the green re-manufacturing procedure begin. The optimized laser operating parameters paved the road for excellent mechanical properties and comparatively neat shape which often means less post processing. The laser re-manufactured gear surface was systematically examined, including microstructure observation, and dry wear test at room temperature. The test results were compared with new gear surface and used but not broken gear surface. Finally, it proved that the green re-manufactured gear surface displayed best comprehensive mechanical properties, followed the new gear surface. The resistance of dry wear properties of used but not broken gear surface was the worst.

  18. Unmanned Mine of the 21st Centuries

    Science.gov (United States)

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

    2017-11-01

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

  19. Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.

    Science.gov (United States)

    Shouval, Roni; Labopin, Myriam; Bondi, Ori; Mishan-Shamay, Hila; Shimoni, Avichai; Ciceri, Fabio; Esteve, Jordi; Giebel, Sebastian; Gorin, Norbert C; Schmid, Christoph; Polge, Emmanuelle; Aljurf, Mahmoud; Kroger, Nicolaus; Craddock, Charles; Bacigalupo, Andrea; Cornelissen, Jan J; Baron, Frederic; Unger, Ron; Nagler, Arnon; Mohty, Mohamad

    2015-10-01

    Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplantation-related mortality risk prediction. This work is a retrospective DM study on a cohort of 28,236 adult HSCT recipients from the AL registry of the European Group for Blood and Marrow Transplantation. The primary objective was prediction of overall mortality (OM) at 100 days after HSCT. Secondary objectives were estimation of nonrelapse mortality, leukemia-free survival, and overall survival at 2 years. Donor, recipient, and procedural characteristics were analyzed. The alternating decision tree machine learning algorithm was applied for model development on 70% of the data set and validated on the remaining data. OM prevalence at day 100 was 13.9% (n=3,936). Of the 20 variables considered, 10 were selected by the model for OM prediction, and several interactions were discovered. By using a logistic transformation function, the crude score was transformed into individual probabilities for 100-day OM (range, 3% to 68%). The model's discrimination for the primary objective performed better than the European Group for Blood and Marrow Transplantation score (area under the receiver operating characteristics curve, 0.701 v 0.646; P<.001). Calibration was excellent. Scores assigned were also predictive of secondary objectives. The alternating decision tree model provides a robust tool for risk evaluation of patients with AL before HSCT, and is available online (http://bioinfo.lnx.biu.ac.il/∼bondi/web1.html). It is presented as a continuous probabilistic score for the prediction of day 100 OM, extending prediction to 2 years. The DM method has proved useful for clinical prediction in HSCT. © 2015 by American Society of Clinical Oncology.

  20. Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis.

    Science.gov (United States)

    Vyas, Renu; Bapat, Sanket; Jain, Esha; Karthikeyan, Muthukumarasamy; Tambe, Sanjeev; Kulkarni, Bhaskar D

    2016-12-01

    In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein-protein interactions therefore assume significance. 1296 binary fingerprints that encode a combination of structural and geometric properties were developed using the crystallographic data of 15,000 protein complexes in the pdb server. In a case study, these fingerprints were created for proteins implicated in the Type 2 diabetes mellitus disease. The fingerprints were input into a SVM based model for discriminating disease proteins from non disease proteins yielding a classification accuracy of 78.2% (AUC value of 0.78) on an external data set composed of proteins retrieved via text mining of diabetes related literature. A PPI network was constructed and analysed to explore new disease targets. The integrated approach exemplified here has a potential for identifying disease related proteins, functional annotation and other proteomics studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. A novel behavioral model of the pasture-based dairy cow from GPS data using data mining and machine learning techniques.

    Science.gov (United States)

    Williams, M L; Mac Parthaláin, N; Brewer, P; James, W P J; Rose, M T

    2016-03-01

    A better understanding of the behavior of individual grazing dairy cattle will assist in improving productivity and welfare. Global positioning systems (GPS) applied to cows could provide a means of monitoring grazing herds while overcoming the substantial efforts required for manual observation. Any model of behavioral prediction using GPS needs to be accurate and robust by accounting for inter-cow variation as well as atmospheric effects. We evaluated the performance using a series of machine learning algorithms on GPS data collected from 40 pasture-based dairy cows over 4 mo. A feature extraction step was performed on the collected raw GPS data, which resulted in 43 different attributes. The evaluated behaviors were grazing, resting, and walking. Classifier learners were built using 10 times 10-fold cross validation and tested on an independent test set. Results were evaluated using a variety of statistical significance tests across all parameters. We found that final model selection depended upon level of performance and model complexity. The classifier learner deemed most suitable for this particular problem was JRip, a rule-based learner (classification accuracy=0.85; false positive rate=0.10; F-measure=0.76; area under the receiver operating curve=0.87). This model will be used in further studies to assess the behavior and welfare of pasture-based dairy cows. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  2. 30 CFR 18.49 - Connection boxes on machines.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Connection boxes on machines. 18.49 Section 18..., AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.49 Connection boxes on machines. Connection boxes used to facilitate replacement...

  3. Longwall mining

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-03-14

    As part of EIA`s program to provide information on coal, this report, Longwall-Mining, describes longwall mining and compares it with other underground mining methods. Using data from EIA and private sector surveys, the report describes major changes in the geologic, technological, and operating characteristics of longwall mining over the past decade. Most important, the report shows how these changes led to dramatic improvements in longwall mining productivity. For readers interested in the history of longwall mining and greater detail on recent developments affecting longwall mining, the report includes a bibliography.

  4. 30 CFR 18.96 - Preparation of machines for inspection; requirements.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Preparation of machines for inspection... 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...

  5. Machine Translation

    Institute of Scientific and Technical Information of China (English)

    张严心

    2015-01-01

    As a kind of ancillary translation tool, Machine Translation has been paid increasing attention to and received different kinds of study by a great deal of researchers and scholars for a long time. To know the definition of Machine Translation and to analyse its benefits and problems are significant for translators in order to make good use of Machine Translation, and helpful to develop and consummate Machine Translation Systems in the future.

  6. 30 CFR 18.80 - Approval of machines assembled with certified or explosion-proof components.

    Science.gov (United States)

    2010-07-01

    ... or explosion-proof components. 18.80 Section 18.80 Mineral Resources MINE SAFETY AND HEALTH... MINE EQUIPMENT AND ACCESSORIES Machines Assembled With Certified or Explosion-Proof Components, Field... assembled with certified or explosion-proof components. (a) A machine may be a new assembly, or a machine...

  7. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  8. A survey of temporal data mining

    Indian Academy of Sciences (India)

    Since temporal data mining brings together techniques from different fields such as statistics, machine learning and databases, the literature is scattered among many different sources. In this article, we present an overview of techniques of temporal data mining. We mainly concentrate on algorithms for pattern discovery in ...

  9. Otimização do corte de polipropileno com jato abrasivo Optimization of polypropylene waterjet cut

    Directory of Open Access Journals (Sweden)

    Wildor T. Hennies

    2004-09-01

    Full Text Available A tecnologia avançada de corte com jato de água pode ser usada em chapas de polipropileno. Os modernos sistemas são compostos por: bomba de alta pressão, mesa XY e computador. O corte no sistema cria uma ranhura com características próprias. A largura do sulco é maior na entrada que na saída do corte. No corte do polipropileno podem surgir rebarbas na base da chapa como pequenas fibras. Experiência adquirida na confecção de peneiras mostrou que o número de furos é decisivo no custo da peça. Ensaios preliminares simularam alternativas de corte com e sem abrasivo. A abertura de 900 furos numa área de 967 cm² revelou consumir 126 minutos para corte sem abrasivo, contra 201 no caso mais oneroso. A seguir, novos desenhos foram propostos diminuindo a malha, mas, preservando o índice de vazamento. Assim, 145, 218 ou 362 furos são possíveis. O corte de velocidade constante e com abrasivo mostrou-se o mais eficiente. Por outro lado, o modo de abrir o furo influi na qualidade da peneira. A seleção da alternativa adequada, os problemas surgidos durante a investigação e as soluções adotadas foram detalhadamente descritos no estudo.Advanced technology of waterjet cut can be used in polypropylene tableware. The modern systems comprise a high-pressure pump, XY table and computer as controller. The cutting process may lead to kerfs with specific characteristics. The kerf width is larger in the entrance than in the jet exit. In cutting polypropylene, burrs in the base of the plate can appear as small staple fibers. Experience acquired in the confection of sieves showed that the number of punctures is decisive in the cost of the part. Preliminary assays simulated cut alternatives with and without abrasive. The opening of 900 punctures in an area of 967 cm² consumes 126 minutes for cutting without abrasive, in contrast to 201 minutes in the most costly case. New drawings were then considered with the meshes being decreased, but preserving

  10. Text Mining.

    Science.gov (United States)

    Trybula, Walter J.

    1999-01-01

    Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

  11. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  12. Applied data mining for business and industry

    CERN Document Server

    Giudici, Paolo

    2009-01-01

    The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies a...

  13. Data Mining : A Prospective Approach for Digital Forensics

    OpenAIRE

    Smita M. Nirkhi; R.V.Dharaskar; V.M.Thakre

    2012-01-01

    Data mining is part of the interdisciplinary field of knowledge discovery in databases. Research on datamining began in the 1980s and grew rapidly in the 1990s.Specific techniques that have been developedwithin disciplines such as artificial intelligence, machine learning and pattern recognition have beensuccessfully employed in data mining. Data mining has been successfully introduced in many differentfields. An important application area for data mining techniques is the World Wide Web Rece...

  14. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  15. Permutation Machines.

    Science.gov (United States)

    Bhatia, Swapnil; LaBoda, Craig; Yanez, Vanessa; Haddock-Angelli, Traci; Densmore, Douglas

    2016-08-19

    We define a new inversion-based machine called a permuton of n genetic elements, which allows the n elements to be rearranged in any of the n·(n - 1)·(n - 2)···2 = n! distinct orderings. We present two design algorithms for architecting such a machine. We define a notion of a feasible design and use the framework to discuss the feasibility of the permuton architectures. We have implemented our design algorithms in a freely usable web-accessible software for exploration of these machines. Permutation machines could be used as memory elements or state machines and explicitly illustrate a rational approach to designing biological systems.

  16. Toward improved branch prediction through data mining.

    Energy Technology Data Exchange (ETDEWEB)

    Hemmert, K. Scott; Johnson, D. Eric (University of Texas at Austin)

    2009-09-01

    Data mining and machine learning techniques can be applied to computer system design to aid in optimizing design decisions, improving system runtime performance. Data mining techniques have been investigated in the context of branch prediction. Specifically, a comparison of traditional branch predictor performance has been made to data mining algorithms. Additionally, the possiblity of whether additional features available within the architectural state might serve to further improve branch prediction has been evaluated. Results show that data mining techniques indicate potential for improved branch prediction, especially when register file contents are included as a feature set.

  17. Sentinel Mining

    DEFF Research Database (Denmark)

    Middelfart, Morten

    into geography dimension) combined with a decrease in the money invested in customer support for laptop computers (drilldown into product dimension) is observed. The work leading to this thesis progressed from algorithms for regular sentinel mining with only one source and one target measure, into algorithms...... progression in the efficiency of sentinel mining, where the latest bitmap-based algorithms, that also take advantage of modern CPUs, are 3–4 orders of magnitude faster than the first SQL-based sentinel mining algorithm. This work also led to the industrial implementation of sentinel mining in the commercial...

  18. The Machine within the Machine

    CERN Multimedia

    Katarina Anthony

    2014-01-01

    Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

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

    Science.gov (United States)

    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.

  20. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M.

    1982-04-01

    Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

  1. Availability analysis of selected mining machinery

    Directory of Open Access Journals (Sweden)

    Brodny Jarosław

    2017-06-01

    Full Text Available Underground extraction of coal is characterized by high variability of mining and geological conditions in which it is conducted. Despite ever more effective methods and tools, used to identify the factors influencing this process, mining machinery, used in mining underground, work in difficult and not always foreseeable conditions, which means that these machines should be very universal and reliable. Additionally, a big competition, occurring on the coal market, causes that it is necessary to take action in order to reduce the cost of its production, e.g. by increasing the efficiency of utilization machines. To meet this objective it should be pro-ceed with analysis presented in this paper. The analysis concerns to availability of utilization selected mining machinery, conducted using the model of OEE, which is a tool for quantitative estimate strategy TPM. In this article we considered the machines being part of the mechanized longwall complex and the basis of analysis was the data recording by the industrial automation system. Using this data set we evaluated the availability of studied machines and the structure of registered breaks in their work. The results should be an important source of information for maintenance staff and management of mining plants, needed to improve the economic efficiency of underground mining.

  2. Perfecting management of operating mines. Sovershenstvovanie gornogo khozyaistva na deistvuyushchikh shakhtakh

    Energy Technology Data Exchange (ETDEWEB)

    Gorbachev, D.T.; Likal' ter, L.A.; Kaganovich, M.N.; Churilov, A.A.; Oparin, I.N. (IGD im. A.A. Skochinskogo (USSR))

    1988-01-01

    Analyzes operation of underground coal mines in the USSR from 1975 to 1985. The following aspects are evaluated: mining and geologic conditions, increasing mining depths, resource depletion, methods for deposit opening and development, role of longwall mining, equipment for longwall mining (shearer loaders, powered supports), use of support pillars, ventilation systems, mine haulage, mine drivage by heading machines or drilling and blasting, coal output per mine and effects of mine service life on its efficiency and mining cost, bottle-necks in mine operation in individual coal basins. Operation of longwall mining is analyzed: face dimensions, advance rates, coal panel dimensions, mean coal output per face, coal output per miner, reliability of face systems. Principles of the economic plan for 1986-1990 are discussed. Methods for eliminating bottle-necks in coal mining are reviewed. 4 refs.

  3. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  4. Monel Machining

    Science.gov (United States)

    1983-01-01

    Castle Industries, Inc. is a small machine shop manufacturing replacement plumbing repair parts, such as faucet, tub and ballcock seats. Therese Castley, president of Castle decided to introduce Monel because it offered a chance to improve competitiveness and expand the product line. Before expanding, Castley sought NERAC assistance on Monel technology. NERAC (New England Research Application Center) provided an information package which proved very helpful. The NASA database was included in NERAC's search and yielded a wealth of information on machining Monel.

  5. The modernisation of mining

    CSIR Research Space (South Africa)

    Ritchken, E

    2017-10-01

    Full Text Available This presentation discusses the modernisation of mining. The presentation focuses on the mining clusters, Mining Challenges, Compliance versus Collaboration, The Phakisa, The Mining Precinct & the Mining Hub also Win-Win Beneficiation: Iron...

  6. Biomarker Identification Using Text Mining

    Directory of Open Access Journals (Sweden)

    Hui Li

    2012-01-01

    Full Text Available Identifying molecular biomarkers has become one of the important tasks for scientists to assess the different phenotypic states of cells or organisms correlated to the genotypes of diseases from large-scale biological data. In this paper, we proposed a text-mining-based method to discover biomarkers from PubMed. First, we construct a database based on a dictionary, and then we used a finite state machine to identify the biomarkers. Our method of text mining provides a highly reliable approach to discover the biomarkers in the PubMed database.

  7. Emerging Paradigms in Machine Learning

    CERN Document Server

    Jain, Lakhmi; Howlett, Robert

    2013-01-01

    This  book presents fundamental topics and algorithms that form the core of machine learning (ML) research, as well as emerging paradigms in intelligent system design. The  multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.  The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.  Several chapters are devoted to computational learning models such as granular computing, rough sets and fuzzy sets An account of applications of well-known learning methods in biometrics, computational stylistics, multi-agent systems, spam classification including an extremely well-written survey on Bayesian networks shed light on the strengths and weaknesses of the methods. Practical studies yielding insight into challenging problems such as learning from incomplete and imbalanced data, pattern recognition of stochastic episodic events and on-line mining of non-stationary ...

  8. Process mining

    DEFF Research Database (Denmark)

    van der Aalst, W.M.P.; Rubin, V.; Verbeek, H.M.W.

    2010-01-01

    Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being executed or messages being exchanged) a process model is constructed. One of the essential problems in process mining is that one cannot assume to have seen all possible...... behavior. At best, one has seen a representative subset. Therefore, classical synthesis techniques are not suitable as they aim at finding a model that is able to exactly reproduce the log. Existing process mining techniques try to avoid such “overfitting” by generalizing the model to allow for more...

  9. 30 CFR 18.21 - Machines equipped with powered dust collectors.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Machines equipped with powered dust collectors... TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.21 Machines equipped with powered dust collectors. Powered dust...

  10. 30 CFR 18.22 - Boring-type machines equipped for auxiliary face ventilation.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Boring-type machines equipped for auxiliary..., DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Construction and Design Requirements § 18.22 Boring-type machines equipped for...

  11. Rapid prototyping of robotic platforms

    CSIR Research Space (South Africa)

    De Ronde, Willis

    2016-11-01

    Full Text Available of thickness up to 200mm can be cut to create prototype chassis/ bodies or even the final product. One of the few limitations is the cutting of certain laminated materials, as this tends to produce delaminated cutting edges or even fractures in the case... mine inspection robot (Shongololo). Shongololo’s frame is made from engineering plastics while the chassis of Dassie was made from aluminium and cut using abrasive waterjet machining. The advantage of using abrasive waterjet machining is the speed...

  12. Machine Protection

    CERN Document Server

    Zerlauth, Markus; Wenninger, Jörg

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

  13. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  14. Data Mining Solutions for the Business Environment

    Directory of Open Access Journals (Sweden)

    Ruxandra-Stefania PETRE

    2014-02-01

    Full Text Available Over the past years, data mining became a matter of considerable importance due to the large amounts of data available in the applications belonging to various domains. Data mining, a dynamic and fast-expanding field, that applies advanced data analysis techniques, from statistics, machine learning, database systems or artificial intelligence, in order to discover relevant patterns, trends and relations contained within the data, information impossible to observe using other techniques. The paper focuses on presenting the applications of data mining in the business environment. It contains a general overview of data mining, providing a definition of the concept, enumerating six primary data mining techniques and mentioning the main fields for which data mining can be applied. The paper also presents the main business areas which can benefit from the use of data mining tools, along with their use cases: retail, banking and insurance. Also the main commercially available data mining tools and their key features are presented within the paper. Besides the analysis of data mining and the business areas that can successfully apply it, the paper presents the main features of a data mining solution that can be applied for the business environment and the architecture, with its main components, for the solution, that would help improve customer experiences and decision-making

  15. FROM DATA MINING TO BEHAVIOR MINING

    OpenAIRE

    ZHENGXIN CHEN

    2006-01-01

    Knowledge economy requires data mining be more goal-oriented so that more tangible results can be produced. This requirement implies that the semantics of the data should be incorporated into the mining process. Data mining is ready to deal with this challenge because recent developments in data mining have shown an increasing interest on mining of complex data (as exemplified by graph mining, text mining, etc.). By incorporating the relationships of the data along with the data itself (rathe...

  16. Social big data mining

    CERN Document Server

    Ishikawa, Hiroshi

    2015-01-01

    Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

  17. Machine testning

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with a laboratory exercise of 3 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercise includes a series of tests carried out by the student on a conventional and a numerically controled lathe, respectively. This document...

  18. Representational Machines

    DEFF Research Database (Denmark)

    Petersson, Dag; Dahlgren, Anna; Vestberg, Nina Lager

    to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...

  19. Arabic Text Classification Using Support Vector Machines

    NARCIS (Netherlands)

    Gharib, Tarek F.; Habib, Mena B.; Fayed, Zaki T.

    2009-01-01

    Text classification (TC) is the process of classifying documents into a predefined set of categories based on their content. Arabic language is highly inflectional and derivational language which makes text mining a complex task. In this paper we applied the Support Vector Machines (SVM) model in

  20. GeoJetting. Development and operation of the maximum pressure water-jet drilling technology; GeoJetting. Entwicklung und Betrieb der Hoechstdruckwasserstrahl-Bohrtechnik

    Energy Technology Data Exchange (ETDEWEB)

    Bracke, Rolf [Bochum Univ. (Germany); GeothermieZentrum Bochum (GZB) (Germany); Wittig, Volker

    2009-03-15

    In the consideration of a geothermal total system - near the surface or deep being enough - the greatest amount of the plant costs are due to underground operation. Therefore, an emphasis of future technological developments in the geothermal heat also must lie in the underground; that means at innovative procedures for drilling and the reservoir development for efficient geothermal heat exchangers. At the geothermal centre on the campus of the University Bochum (Federal Republic of Germany) a new drilling procedure was developed in the years 2003 to 2007 with promotion of the Federal Ministry of Education and Research (BMBF, Berlin, Federal Republic of Germany) on the basis by maximum pressure water-jet cutting technology. The procedure is called 'GeoJetting'. The procedure needs clear water as the only propellant and thereby is compatible particularly with groundwater. The technology completely dissolves the rock with a water pressure of up to 1,000 bar in its solid matrix and transfers it in suspension. In comparison with drillings with conventional percussion hammers, this procedure permitted a threefold to fivefold higher drilling velocities in loose rocks and in small compressed sedimentary rocks.

  1. An Electrosurgical Endoknife with a Water-Jet Function (Flushknife Proves Its Merits in Colorectal Endoscopic Submucosal Dissection Especially for the Cases Which Should Be Removed En Bloc

    Directory of Open Access Journals (Sweden)

    Yoji Takeuchi

    2013-01-01

    Full Text Available Background. Previously, we reported that the Flushknife (electrosurgical endoknife with a water-jet function could reduce the operation time of colorectal endoscopic submucosal dissection (ESD however, suitable situation for the Flushknife was obscure. This subgroup analysis of a prospective randomized controlled trial was aimed to investigate the suitable situation for the Flushknife. Methods. A total of 48 superficial colorectal neoplasms that underwent ESD using either the Flexknife or the Flushknife in a referral center were enrolled. The differences of operation time between the Flexknife and the Flushknife groups in each subgroup (tumor size, location, and macroscopic type were analyzed. Results. Median (95% CI operation time calculated using survival curves was significantly shorter in the Flushknife group than in the Flexknife group (55.5 min [41, 78] versus 74.0 [57, 90] min; , Hazard Ratio HR: 0.53; 95% CI (0.29–0.97. In particular, the HR in patients with laterally spreading tumors-nongranular type (LST-NG in the Flushknife group was significantly smaller than in the Flexknife group (HR: 0.1650.17; 95% CI (0.04–0.66. There was a trend of decreasing HRs according to larger lesion size. Conclusions. The Flushknife proved its merits in colorectal ESD especially for the lesions which should be removed en bloc (LST-NG and large lesion.

  2. Software tool for data mining and its applications

    Science.gov (United States)

    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.

  3. Data Mining and Statistics for Decision Making

    CERN Document Server

    Tufféry, Stéphane

    2011-01-01

    Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized lin

  4. INTEGRATING DATA MINING INTO BUSINESS INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    Maria Cristina ENACHE

    2006-01-01

    Full Text Available Data Mining is a broad term often used to describe the process of using database technology, modeling techniques, statistical analysis, and machine learning to analyze large amounts of data in an automated fashion to discover hidden patterns and predictive information in the data. By building highly complex and sophisticated statistical and mathematical models, organizations can gain new insight into their activities. The purpose of this document is to provide users with a background of a few key data mining concepts and business intelligence and about benefits of integrating business intelligence and data mining.

  5. WIRELESS MINE-WIDE TELECOMMUNICATIONS TECHNOLOGY

    Energy Technology Data Exchange (ETDEWEB)

    Zvi H. Meiksin

    2004-03-01

    A comprehensive mine-wide, two-way wireless voice and data communication system for the underground mining industry was developed. The system achieves energy savings through increased productivity and greater energy efficiency in meeting safety requirements within mines. The mine-wide system is comprised of two interfaced subsystems: a through-the-earth communications system and an in-mine communications system. The mine-wide system permits two-way communication among underground personnel and between underground and surface personnel. The system was designed, built, and commercialized. Several systems are in operation in underground mines in the United States. The use of these systems has proven they result in considerable energy savings. A system for tracking the location of vehicles and people within the mine was also developed, built and tested successfully. Transtek's systems are being used by the National Institute of Occupational Safety and Health (NIOSH) in their underground mine rescue team training program. This project also resulted in a spin-off rescue team lifeline and communications system. Furthermore, the project points the way to further developments that can lead to a GPS-like system for underground mines allowing the use of autonomous machines in underground mining operations, greatly reducing the amount of energy used in these operations. Some products developed under this program are transferable to applications in fields other than mining. The rescue team system is applicable to use by first responders to natural, accidental, or terrorist-caused building collapses. The in-mine communications system can be installed in high-rise buildings providing in-building communications to security and maintenance personnel as well as to first responders.

  6. Data mining and marketing approach to track customer movements

    OpenAIRE

    SAMMOUR, George; SCHREURS, Jeanne; VANHOOF, Koen

    2009-01-01

    Many business problems are of interest to both data mining and marketing academic communities, such as market segmentation, direct marketing, targeted marketing, personalization/customization, cross selling, discovering customer lifetime value and customer behaviour. Yet, these two disciplines have very different approaches to analyzing these problems. Data mining research incorporates methodologies from various research disciplines such as statistics, machine learning, database technology, o...

  7. 30 CFR Appendix A to Subpart F of... - List of Permissible Electric Face Equipment Approved by the Bureau of Mines Prior to May 23, 1936

    Science.gov (United States)

    2010-07-01

    ... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY... 19, 1931. 287A March 12, 1935. 296A January 6, 1936. Chain Type 151 May 19, 1928. 209 December 2...-Moving Equipment, Miscellaneous Trucks, and Water Spray Supply Units mining machines Shortwall Machines...

  8. BOOK REVIEW EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS

    OpenAIRE

    Ozturk, Aylin

    2016-01-01

    Educational Data Mining (EDM) is a developing field based on data mining techniques. EDM emerged as a combination of areas such as machine learning, statistics, computer science, education, cognitive science, and psychometry. EDM focuses on learner characteristics, behaviors, academic achievements, process of learning, educational functionalities, domain knowledge content, assessments, and applications. Educational data mining is defined by Baker (2010) as ‘‘an emerging discipline, concerned ...

  9. Surface Mines, Other - Longwall Mining Panels

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Coal mining has occurred in Pennsylvania for over a century. A method of coal mining known as Longwall Mining has become more prevalent in recent decades. Longwall...

  10. Continuous respirable mine dust monitor development

    Energy Technology Data Exchange (ETDEWEB)

    Cantrell, B.K.; Williams, K.L.; Stein, S.W. [and others

    1996-12-31

    In June 1992, the Mine Safety and Health Administration (MSHA) published the Report of the Coal Mine Respirable Dust Task Group, Review of the Program to Control Respirable Coal Mine Dust in the United States. As one of its recommendations, the report called for the accelerated development of two mine dust monitors: (1) a fixed-site monitor capable of providing continuous information on dust levels to the miner, mine operator, and to MSHA, if necessary, and (2) a personal sampling device capable of providing both a short-term personal exposure measurement as well as a full-shift measurement. In response to this recommendation, the U.S. Bureau of Mines initiated the development of a fixed-site machine-mounted continuous respirable dust monitor. The technology chosen for monitor development is the Rupprecht and Patashnick Co., Inc. tapered element oscillating microbalance. Laboratory and in-mine tests have indicated that, with modification, this sensor can meet the humidity and vibration requirements for underground coal mine use. The U.S. Department of Energy Pittsburgh Research Center (DOE-PRC) is continuing that effort by developing prototypes of a continuous dust monitor based on this technology. These prototypes are being evaluated in underground coal mines as they become available. This effort, conducted as a joint venture with MSHA, is nearing completion with every promise of success.

  11. OPTIMASI DENGAN ALGORITMA RSM-CCD PADA EVAPORATOR VAKUM WATERJET DENGAN PENGENDALI SUHU FUZZY PADA PEMBUATAN PERMEN SUSU (RSM-CCD Algorithm for Optimizing Waterjet Vacuum Evaporator Using Fuzzy Temperature Control in The Milk Candy Production

    Directory of Open Access Journals (Sweden)

    Yusuf Hendrawan

    2016-10-01

    Full Text Available Milk candy is a product which has to be produced under a high temperature to achieve the caramelization process. The use of vacuum system during a food processing is one of the alternatives to engineer the value of a material’s boiling point. The temperature control system and the mixing speed in machine that produce the milk candy were expected to be able to prevent the formation of off-flavour in the final product. A smart control system based on fuzzy logic was applied in the temperature control within the double jacket vacuum evaporator machine that needs stable temperature in the cooking process. The objective of this research is developing vacuum evaporator for milk candy production using fuzzy temperature control. The result in machine and system planning showed that the process of milk candy production was going on well. The parameter optimization of water content and ash content purposed to acquire the temperature point parameter and mixing speed in milk candy production. The optimization method was response surface methodology (RSM, by using the model of central composite design (CCD. The optimization resulted 90.18oC for the temperature parameter and 512 RPM for the mixing speed, with the prediction about 4.69% of water content and 1.57% of ash content. Keywords: Optimization, vacuum evaporator, fuzzy, milk candy, response surface methodology ABSTRAK Permen susu merupakan salah satu produk yang diolah dengan suhu tinggi untuk mencapai proses karamelisasi. Pengolahan pangan dengan sistem vakum merupakan salah satu alternatif untuk merekayasa nilai titik didih suatu bahan. Sistem pengendalian suhu serta kecepatan pengadukan pada mesin produksi permen susu diharapkan dapat mencegah terbentuknya partikel hitam (off-flavour pada produk akhir. Sistem kontrol cerdas logika fuzzy diaplikasikan dalam pengendalian suhu pada mesin evaporator vakum double jacket yang membutuhkan tingkat stabilitas suhu pemasakan permen susu. Tujuan dari

  12. Fullerene Machines

    Science.gov (United States)

    Globus, Al; Saini, Subhash (Technical Monitor)

    1998-01-01

    Fullerenes possess remarkable properties and many investigators have examined the mechanical, electronic and other characteristics of carbon SP2 systems in some detail. In addition, C-60 can be functionalized with many classes of molecular fragments and we may expect the caps of carbon nanotubes to have a similar chemistry. Finally, carbon nanotubes have been attached to t he end of scanning probe microscope (Spill) tips. Spills can be manipulated with sub-angstrom accuracy. Together, these investigations suggest that complex molecular machines made of fullerenes may someday be created and manipulated with very high accuracy. We have studied some such systems computationally (primarily functionalized carbon nanotube gears and computer components). If such machines can be combined appropriately, a class of materials may be created that can sense their environment, calculate a response, and act. The implications of such hypothetical materials are substantial.

  13. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

    BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...

  14. Genesis machines

    CERN Document Server

    Amos, Martyn

    2014-01-01

    Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities. Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself.

  15. Data mining

    CERN Document Server

    Gorunescu, Florin

    2011-01-01

    The knowledge discovery process is as old as Homo sapiens. Until some time ago, this process was solely based on the 'natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since 'knowledge is power'. The goal of this book is to provide, in a friendly way

  16. Mining Review

    Science.gov (United States)

    ,

    2013-01-01

    In 2012, the estimated value of mineral production increased in the United States for the third consecutive year. Production and prices increased for most industrial mineral commodities mined in the United States. While production for most metals remained relatively unchanged, with the notable exception of gold, the prices for most metals declined. Minerals remained fundamental to the U.S. economy, contributing to the real gross domestic product (GDP) at several levels, including mining, processing and manufacturing finished products. Minerals’ contribution to the GDP increased for the second consecutive year.

  17. Data Mining at NASA: From Theory to Applications

    Science.gov (United States)

    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.

  18. Traffic Flow Management: Data Mining Update

    Science.gov (United States)

    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

  19. Annotating images by mining image search results

    NARCIS (Netherlands)

    Wang, X.J.; Zhang, L.; Li, X.; Ma, W.Y.

    2008-01-01

    Although it has been studied for years by the computer vision and machine learning communities, image annotation is still far from practical. In this paper, we propose a novel attempt at model-free image annotation, which is a data-driven approach that annotates images by mining their search

  20. mining activities.

    African Journals Online (AJOL)

    Eichhornia crassipes) is patchy. L2: Nyikonga, 02°48' 45.0"S,. 007.6"E. (M). Nyikonga area receives discharge from. Nyikonga River that drains Nyarugusu and other mining areas in Geita District. Shoreline vegetation includes Typha capensis ...

  1. Simulating Turing machines on Maurer machines

    NARCIS (Netherlands)

    Bergstra, J.A.; Middelburg, C.A.

    2008-01-01

    In a previous paper, we used Maurer machines to model and analyse micro-architectures. In the current paper, we investigate the connections between Turing machines and Maurer machines with the purpose to gain an insight into computability issues relating to Maurer machines. We introduce ways to

  2. Mining online community data

    DEFF Research Database (Denmark)

    Christensen, Kasper; Liland, Kristian Hovde; Kvaal, Knut

    2017-01-01

    to provide an answer to what is it that makes such automatic idea detection possible? Our study is based on two datasets from dialogue between members of two distinct online communities. The first community is related to beer. The second is related to Lego. We generate machine learning classifiers based......Ideas are essential for innovation and for the continuous renewal of a firm’s product offerings. Previous research has argued that online communities contain such ideas. Therefore, online communities such as forums, Facebook groups, blogs etc. are potential gold mines for innovative ideas that can...... be used for boosting the innovation performance of the firm. However, the nature of online community data makes idea detection labor intensive. As an answer to this problem, research has shown that it might be possible to detect ideas from online communities, automatically. Research is however, yet...

  3. Environmentally Friendly Machining

    CERN Document Server

    Dixit, U S; Davim, J Paulo

    2012-01-01

    Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

  4. Machine capability index evaluation of machining center

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Won Pyo [Korea Institute of Industrial Technology, Ansan (Korea, Republic of)

    2013-10-15

    Recently, there has been an increasing need to produce more precise products, with only the smallest deviations from a defined target value. Machine capability is the ability of a machine tool to produce parts within the tolerance interval. Capability indices are a statistical way of describing how well a product is machined compared to defined target values and tolerances. Currently, there is no standardized way to acquire a machine capability value. This paper describes how machine capability indices are evaluated in machining centers. After the machining of specimens, straightness, roundness and positioning accuracy were measured using CMM(coordinate measuring machine). These measured values and defined tolerances were used to evaluate the machine capability index. It will be useful for the industry to have standardized ways to choose and calculate machine capability indices.

  5. Archetypal Analysis for Machine Learning

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2010-01-01

    Archetypal analysis (AA) proposed by Cutler and Breiman in [1] estimates the principal convex hull of a data set. As such AA favors features that constitute representative ’corners’ of the data, i.e. distinct aspects or archetypes. We will show that AA enjoys the interpretability of clustering - ...... for K-means [2]. We demonstrate that the AA model is relevant for feature extraction and dimensional reduction for a large variety of machine learning problems taken from computer vision, neuroimaging, text mining and collaborative filtering....

  6. Perfecting technology and organization of development work in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Fisun, A.P.; Suslo, A.I.

    1980-02-01

    Mining-geological conditions are characterized in the Makeevugol mines, with mining depth over 800 m, methane hazard and rock burst hazard. In the Makeevugol' mines pillar mining predominates as it requires far less development work than a longwall system (detailed comparison is given). Methods of development work, i.e. blasting and heading machines, are described along with haulage systems (belt conveyors, rope haulage ways), and support systems. The article concentrates on development work under difficult conditions, slope up to 26 degrees and methane and rock burst hazard, where possibilities of mechanizing work are more limited than in horizontal and safe coal seams. Work efficiency per one miner in seams characterized by rock burst hazard is 26% lower than in other seams. In the Makeevugol' mines development work presents a serious hindrance to the mining process. (In Russian)

  7. 30 CFR 75.703 - Grounding offtrack direct-current machines and the enclosures of related detached components.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Grounding offtrack direct-current machines and the enclosures of related detached components. 75.703 Section 75.703 Mineral Resources MINE SAFETY AND...-UNDERGROUND COAL MINES Grounding § 75.703 Grounding offtrack direct-current machines and the enclosures of...

  8. Contract Mining versus Owner Mining

    African Journals Online (AJOL)

    Owner

    products affecting mining performance, usage rate above plan, etc.), people (e.g. skill deficiencies of key personnel, poor safety and environmental awareness), cost estimation (using incorrect unit costs in calculations, escalation of costs higher than revenue increases, changes in interest rates, change in exchange rates), ...

  9. Machine Protection

    CERN Document Server

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...

  10. Machine consciousness.

    Science.gov (United States)

    Aleksander, Igor

    2005-01-01

    The work from several laboratories on the modeling of consciousness is reviewed. This ranges, on one hand, from purely functional models where behavior is important and leads to an attribution of consciousness to, on the other hand, material work closely derived from the information about the anatomy of the brain. At the functional end of the spectrum, applications are described specifically directed at a job-finding problem, where the person being served should not discern between being served by a conscious human or a machine. This employs an implementation of global workspace theories. At the material end, attempts at modeling attentional brain mechanisms, and basic biochemical processes in children are discussed. There are also general prescriptions for functional schemas that facilitate discussions for the presence of consciousness in computational systems and axiomatic structures that define necessary architectural features without which it would be difficult to represent sensations. Another distinction between these two approaches is whether one attempts to model phenomenology (material end) or not (functional end). The former is sometimes called "synthetic phenomenology." The upshot of this chapter is that studying consciousness through the design of machines is likely to have two major outcomes. The first is to provide a wide-ranging computational language to express the concept of consciousness. The second is to suggest a wide-ranging set of computational methods for building competent machinery that benefits from the flexibility of conscious representations.

  11. Support Spinor Machine

    OpenAIRE

    Kanjamapornkul, Kabin; Pinčák, Richard; Chunithpaisan, Sanphet; Bartoš, Erik

    2017-01-01

    We generalize a support vector machine to a support spinor machine by using the mathematical structure of wedge product over vector machine in order to extend field from vector field to spinor field. The separated hyperplane is extended to Kolmogorov space in time series data which allow us to extend a structure of support vector machine to a support tensor machine and a support tensor machine moduli space. Our performance test on support spinor machine is done over one class classification o...

  12. Data mining and education.

    Science.gov (United States)

    Koedinger, Kenneth R; D'Mello, Sidney; McLaughlin, Elizabeth A; Pardos, Zachary A; Rosé, Carolyn P

    2015-01-01

    An emerging field of educational data mining (EDM) is building on and contributing to a wide variety of disciplines through analysis of data coming from various educational technologies. EDM researchers are addressing questions of cognition, metacognition, motivation, affect, language, social discourse, etc. using data from intelligent tutoring systems, massive open online courses, educational games and simulations, and discussion forums. The data include detailed action and timing logs of student interactions in user interfaces such as graded responses to questions or essays, steps in rich problem solving environments, games or simulations, discussion forum posts, or chat dialogs. They might also include external sensors such as eye tracking, facial expression, body movement, etc. We review how EDM has addressed the research questions that surround the psychology of learning with an emphasis on assessment, transfer of learning and model discovery, the role of affect, motivation and metacognition on learning, and analysis of language data and collaborative learning. For example, we discuss (1) how different statistical assessment methods were used in a data mining competition to improve prediction of student responses to intelligent tutor tasks, (2) how better cognitive models can be discovered from data and used to improve instruction, (3) how data-driven models of student affect can be used to focus discussion in a dialog-based tutoring system, and (4) how machine learning techniques applied to discussion data can be used to produce automated agents that support student learning as they collaborate in a chat room or a discussion board. © 2015 John Wiley & Sons, Ltd.

  13. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  14. Mining revival

    OpenAIRE

    Lusty, Paul

    2010-01-01

    In relation to its size the United Kingdom (UK) is remarkably well-endowed with mineral resources as a result of its complex geological history. Their extraction and use have played an important role in the development of the UK economy over many years and minerals are currently worked at some 2100 mine and quarry sites. Production is now largely confined to construction minerals, primarily aggregates, energy minerals and industrial minerals including salt, potash, kaolin and fluorspar, altho...

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

    Science.gov (United States)

    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.

  16. The market for large rigid haul trucks in surface mining

    Energy Technology Data Exchange (ETDEWEB)

    Gilewicz, P.

    2002-04-15

    Originally published in 2001 this updated report provides a definition of the market for large rigid haulers in surface mining. The analysis covers changes to the mining market segments buying these machines including the gains made by coal producers, retrenchment in copper mining, the consolidation taking place among gold mining companies, and the expansion of iron ore producers in Australia and Brazil. It includes a detailed accounting of 2001 truck shipments, and an analysis of trends in the Ultra-truck segment. It concludes with a revised forecast for shipments through 2006. 12 charts, 56 tabs., 2 apps.

  17. A Novel Framework for Agent-Based Production Remote Monitoring System Design: A Case Study of Injection Machines

    Directory of Open Access Journals (Sweden)

    Yun-Yao Chen

    2013-01-01

    Full Text Available Currently, many injection machine controllers in the market involve PC-based architecture, so engineers can conduct simple and quick operation on the controller via a human-machine interface. However, when there are too many machines in a factory, mining algorithms for multimachines and development of rear-end applications are often trivial and complicated. The operation systems of the machines in factories are different, and different machine models need different transfer protocols for data mining. Therefore, we need to develop different information platforms and machine production information mining systems for cross platform controllers. This research proposed an agent based remote monitoring system for injection machines to solve this problem. The agent-based production remote monitor system framework in this research has the following advantages. (1 It can transmit machine information cross platforms regard of constraints of different operating systems. Controlling frameworks can process data mining and transmission. (2 It can send back machine information actively to the manager without operation of machine operators, mine specific information effectively, and screen unnecessary machine information. (3 It can categorize the required information, filter extra information, and elicit data the user needs.

  18. Exploration and Mining Roadmap

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2002-09-01

    This Exploration and Mining Technology Roadmap represents the third roadmap for the Mining Industry of the Future. It is based upon the results of the Exploration and Mining Roadmap Workshop held May 10 ñ 11, 2001.

  19. Northern Trust Mines

    Science.gov (United States)

    The United States and the Navajo Nation entered into settlement agreements that provide funds to conduct investigations and any needed cleanup at 16 of the 46 priority mines, including six mines in the Northern Abandoned Uranium Mine Region.

  20. Coal Mine Permit Boundaries

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — ESRI ArcView shapefile depicting New Mexico coal mines permitted under the Surface Mining Control and Reclamation Act of 1977 (SMCRA), by either the NM Mining these...

  1. Ghana Mining Journal

    African Journals Online (AJOL)

    ... in the Ghana mining journal: Geology and Mineral Exploration, Mining, Quarrying, Geomechanics, Groundwater Studies, Hydrocarbon Development, Mineral Processing, Metallurgy, Material Science, Mineral Management Policies, Mineral Economics, Environmental Aspects, Computer Applications and Mining Education.

  2. Machine musicianship

    Science.gov (United States)

    Rowe, Robert

    2002-05-01

    The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.

  3. Addiction Machines

    Directory of Open Access Journals (Sweden)

    James Godley

    2011-10-01

    Full Text Available Entry into the crypt William Burroughs shared with his mother opened and shut around a failed re-enactment of William Tell’s shot through the prop placed upon a loved one’s head. The accidental killing of his wife Joan completed the installation of the addictation machine that spun melancholia as manic dissemination. An early encryptment to which was added the audio portion of abuse deposited an undeliverable message in WB. Wil- liam could never tell, although his corpus bears the in- scription of this impossibility as another form of pos- sibility. James Godley is currently a doctoral candidate in Eng- lish at SUNY Buffalo, where he studies psychoanalysis, Continental philosophy, and nineteenth-century litera- ture and poetry (British and American. His work on the concept of mourning and “the dead” in Freudian and Lacanian approaches to psychoanalytic thought and in Gothic literature has also spawned an essay on zombie porn. Since entering the Academy of Fine Arts Karlsruhe in 2007, Valentin Hennig has studied in the classes of Sil- via Bächli, Claudio Moser, and Corinne Wasmuht. In 2010 he spent a semester at the Dresden Academy of Fine Arts. His work has been shown in group exhibi- tions in Freiburg and Karlsruhe.

  4. Explanatory approach for evaluation of machine learning-induced knowledge.

    Science.gov (United States)

    Zorman, Milan; Verlic, M

    2009-01-01

    Progress in biomedical research has resulted in an explosive growth of data. Use of the world wide web for sharing data has opened up possibilities for exhaustive data mining analysis. Symbolic machine learning approaches used in data mining, especially ensemble approaches, produce large sets of patterns that need to be evaluated. Manual evaluation of all patterns by a human expert is almost impossible. We propose a new approach to the evaluation of machine learning-induced knowledge by introducing a pre-evaluation step. Pre-evaluation is the automatic evaluation of patterns obtained from the data mining phase, using text mining techniques and sentiment analysis. It is used as a filter for patterns according to the support found in online resources, such as publicly-available repositories of scientific papers and reports related to the problem. The domain expert can then more easily distinguish between patterns or rules that are potential candidates for new knowledge.

  5. 30 CFR 75.703-3 - Approved methods of grounding offtrack mobile, portable and stationary direct-current machines.

    Science.gov (United States)

    2010-07-01

    ..., portable and stationary direct-current machines. 75.703-3 Section 75.703-3 Mineral Resources MINE SAFETY... stationary direct-current machines. In grounding offtrack direct-current machines and the enclosures of their... requirements: (1) Installation of silicon diodes shall be restricted to electric equipment receiving power from...

  6. Laser machining of advanced materials

    CERN Document Server

    Dahotre, Narendra B

    2011-01-01

    Advanced materialsIntroductionApplicationsStructural ceramicsBiomaterials CompositesIntermetallicsMachining of advanced materials IntroductionFabrication techniquesMechanical machiningChemical Machining (CM)Electrical machiningRadiation machining Hybrid machiningLaser machiningIntroductionAbsorption of laser energy and multiple reflectionsThermal effectsLaser machining of structural ceramicsIntrodu

  7. Monte Carlo reliability simulation of coal shearer machine

    OpenAIRE

    Hoseinie, Hadi; Khalokakaie, Reza; Ataei, Mohammad A.; Ghodrati, Behzad; Kumar, Uday

    2013-01-01

    In this paper the Kamat-Riley (K-R) event-based Monte Carlo simulation method was used for reliability analysis of longwall shearer machine. Shearer machine consists of six subsystems; water, haulage, electrical, hydraulic, cutting arms and cable systems in a series network configuration. A shearer in the Tabas coal mine was selected as case study and its all failure data were collected and used for reliability analysis of subsystems. With negligible assumption of time to repair, a flowchart ...

  8. Mining ergonomics

    Energy Technology Data Exchange (ETDEWEB)

    McPhee, B.

    2007-02-15

    Changes in work practices and a drive for greater productivity have introduced a range of emerging issues in ergonomics in mining. Some of the practices appear to be at odds with the need to improve general occupational health and safety. Longer shift lengths and fatigue, mental overload and underload, intermittent heavy physical work, reduced task variation, sedentary work in fixed postures and whole-body vibration all have risks for health and safety. The increasing age of some of the workforce is of concern. There appears to be a need to recognise these as potential causes of health problems. The article gives a review of these problems are reports on research findings. 36 refs., 3 figs.

  9. The deleuzian abstract machines

    DEFF Research Database (Denmark)

    Werner Petersen, Erik

    2005-01-01

    To most people the concept of abstract machines is connected to the name of Alan Turing and the development of the modern computer. The Turing machine is universal, axiomatic and symbolic (E.g. operating on symbols). Inspired by Foucault, Deleuze and Guattari extended the concept of abstract...... machines to singular, non-axiomatic and diagrammatic machines. That is: Machines which constitute becomings. This presentation gives a survey of the development of the concept of abstract machines in the philosophy of Deleuze and Guatari and the function of these abstract machines in the creation of works...... of art. From Difference and Repetition to Anti-Oedipus, the machines are conceived as binary machines based on the exclusive or inclusive use respectively of the three syntheses: conexa, disjuncta and conjuncta. The machines have a twofold embedment: In the desiring-production and in the social...

  10. A generic mine model

    NARCIS (Netherlands)

    Veldhoven, J. van; Riet, M.W.G. van; Dol, H.S.; Mohamoud, A.A.; Keus, D.; Beckers, A.L.D.

    2009-01-01

    In the field of mine laying and of mine countermeasures, understanding of the actuation behaviour of influence mines is of vital importance. Modelling can enhance such understanding. In this paper, a flexible generic mine model is presented that allows the user to easily generate different computer

  11. South African mining experience

    Energy Technology Data Exchange (ETDEWEB)

    Buck, J.D. (British Coal Corporation (UK). North Selby Mine)

    1992-09-01

    The article details the author's visit to South Africa on the 1990 Institution of Mining Electrical and Mining Mechanical Engineers Travelling Scholarship. The author undertook to visit to six coal mines (including two opencast mines and one rail loading terminal), four local engineering manufacturers, three power stations, three gold mines, two diamond mines (both in Botswana), a steel and vanadium works, the 1990 Mining Electra exhibition and the head offices of the Anglo American Corporation of South Africa. 4 figs., 2 tabs.

  12. Modern jigging machines for coal enrichment

    Energy Technology Data Exchange (ETDEWEB)

    Rul' , A.S.; Bondarenko, A.P.

    1982-01-01

    Currently the most advanced are jigging machines with sublattice arrangement of the air chambers and with output up to 500 (OM, OMA, USSR), 650 (OMA-24-1, USSR), 350 T/h (''Tokub,'' Japan), 540 T/h (''Batak,'' FRG). The most advanced are air-distributor devices with value type pulsing devices and a system of control which guarantees change in fluctuation frequency and ratio of the duration of the cycle elements in a broad range. The machines manufactured in the USSR are formed of single-type rotary unloading devices with electronic automatic control system. Further trend for development of jigging requires the creation of highly productive jigging machines and complexes for single-flow systems with output of 1000-1500 T/h for run-of-mine coal.

  13. Introduction to machine learning for brain imaging.

    Science.gov (United States)

    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.

  14. Scalable Frequent Subgraph Mining

    KAUST Repository

    Abdelhamid, Ehab

    2017-06-19

    A graph is a data structure that contains a set of nodes and a set of edges connecting these nodes. Nodes represent objects while edges model relationships among these objects. Graphs are used in various domains due to their ability to model complex relations among several objects. Given an input graph, the Frequent Subgraph Mining (FSM) task finds all subgraphs with frequencies exceeding a given threshold. FSM is crucial for graph analysis, and it is an essential building block in a variety of applications, such as graph clustering and indexing. FSM is computationally expensive, and its existing solutions are extremely slow. Consequently, these solutions are incapable of mining modern large graphs. This slowness is caused by the underlying approaches of these solutions which require finding and storing an excessive amount of subgraph matches. This dissertation proposes a scalable solution for FSM that avoids the limitations of previous work. This solution is composed of four components. The first component is a single-threaded technique which, for each candidate subgraph, needs to find only a minimal number of matches. The second component is a scalable parallel FSM technique that utilizes a novel two-phase approach. The first phase quickly builds an approximate search space, which is then used by the second phase to optimize and balance the workload of the FSM task. The third component focuses on accelerating frequency evaluation, which is a critical step in FSM. To do so, a machine learning model is employed to predict the type of each graph node, and accordingly, an optimized method is selected to evaluate that node. The fourth component focuses on mining dynamic graphs, such as social networks. To this end, an incremental index is maintained during the dynamic updates. Only this index is processed and updated for the majority of graph updates. Consequently, search space is significantly pruned and efficiency is improved. The empirical evaluation shows that the

  15. FlexDM: Simple, parallel and fault-tolerant data mining using WEKA

    National Research Council Canada - National Science Library

    Flannery, Madison; Budden, David M; Mendes, Alexandre

    2015-01-01

    With the continued exponential growth in data volume, large-scale data mining and machine learning experiments have become a necessity for many researchers without programming or statistics backgrounds. WEKA...

  16. Sports Data Mining Technology Used in Basketball Outcome Prediction

    OpenAIRE

    Cao, Chenjie

    2012-01-01

    Driven by the increasing comprehensive data in sports datasets and data mining technique successfully used in different area, sports data mining technique emerges and enables us to find hidden knowledge to impact the sport industry. In many instances, predicting the outcomes of sporting events has always been a challenging and attractive work and is therefore drawing a wide concern to conduct research in this field. This project focuses on using machine learning algorithms to build a model fo...

  17. Chapter 16: text mining for translational bioinformatics.

    Science.gov (United States)

    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.

  18. Perfecting technology and organization of development work in coal mines of Leninskugol'

    Energy Technology Data Exchange (ETDEWEB)

    Kostromov, O.S.; Sidorenko, V.G.; Startsev, V.I.

    1980-02-01

    Organization of development work in coal mines of the Leninskugol' concern is discussed. The analysis takes into consideration: division of work among shifts (work cycles), division of work among brigades working simultaneously in a given section, division of work within a brigade. The importance of repair and maintenance work on heading machines and haulage systems is stressed. It is noted that repair work is one of the serious problems in the Leninskugol' mines. Examination shows that in the 7 Noyabrya coal mine 48% of the working time of the heading machine, loader and conveyor is lost: the mining machines stand idle as a result of the failure of one of the three units. Only 2% of idle time is caused by mining-geological conditions and 7% by poor work organization. (In Russian)

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

    Science.gov (United States)

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

    2017-01-01

    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. PMID:28936001

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

    Science.gov (United States)

    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.

  1. Machine tool structures

    CERN Document Server

    Koenigsberger, F

    1970-01-01

    Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

  2. HTS machine laboratory prototype

    DEFF Research Database (Denmark)

    High Temperature Superconducting (HTS) electrical machines have the potential to offer outstanding technical performance with regards to efficiency and power density. However, the industry needs to address a large number of challenges in the attempt to harvest the full potential of HTS machines...... machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...... details and experimental results are shown together with discussions about their implication for scaled up HTS machines....

  3. BOOK REVIEW EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS

    Directory of Open Access Journals (Sweden)

    Aylin OZTURK

    2016-04-01

    Full Text Available Educational Data Mining (EDM is a developing field based on data mining techniques. EDM emerged as a combination of areas such as machine learning, statistics, computer science, education, cognitive science, and psychometry. EDM focuses on learner characteristics, behaviors, academic achievements, process of learning, educational functionalities, domain knowledge content, assessments, and applications. Educational data mining is defined by Baker (2010 as ‘‘an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in’’. EDM is concerned with improving the learning process and environment.

  4. Simplifying RDF Data for Graph-Based Machine Learning.

    NARCIS (Netherlands)

    Bloem, P.; Wibisono, A.; de Vries, G.K.D

    2014-01-01

    From the perspective of machine learning and data mining applications, expressing data in RDF rather than a domain-specific for- mat can add complexity and obfuscate the internal structure. We in- vestigate and illustrate this issue with an example where bio-molecular graph datasets are expressed in

  5. RELIABILITY EVALUATION OF THE ACTIVATION MACHINE FOR THE ELECTRIC DETONATING CAPS-EKA 350

    Directory of Open Access Journals (Sweden)

    Ljubinka Radosavljević

    2007-09-01

    Full Text Available The machine - EKA 350 is designed for the activation of the serial or mixed connected electric detonating caps EK - 40 - 69 in explosive fillings at mining and demolition. For the analyzes of reliability it is important that the machine works in the three regimes of function: LOAD, FIRE and EMPTY. Modeling of reliability was executed for each of the mentioned regimes of the EKA 350 machine. In the machine are incorporated the components dedicated to the professional usage and satisfaction of the MIL standards. The machine is treated as it works in a single - stage mission which lasts 20 seconds.

  6. Reactive Turing machines

    National Research Council Canada - National Science Library

    Baeten, Jos; Luttik, Bas; Tilburg, P.J.A

    2013-01-01

    textabstractWe propose reactive Turing machines (RTMs), extending classical Turing machines with a process-theoretical notion of interaction, and use it to define a notion of executable transition system...

  7. Machining with abrasives

    CERN Document Server

    Jackson, Mark J

    2011-01-01

    Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

  8. Applied machining technology

    CERN Document Server

    Tschätsch, Heinz

    2010-01-01

    Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

  9. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

    The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

  10. Brain versus Machine Control.

    Directory of Open Access Journals (Sweden)

    Jose M Carmena

    2004-12-01

    Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface

  11. Tube Alinement for Machining

    Science.gov (United States)

    Garcia, J.

    1984-01-01

    Tool with stepped shoulders alines tubes for machining in preparation for welding. Alinement with machine tool axis accurate to within 5 mils (0.13mm) and completed much faster than visual setup by machinist.

  12. Influence of continuous mining arrangements on respirable dust exposures

    Science.gov (United States)

    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

  13. Electron cryomicroscopy of biological machines at subnanometer resolution.

    Science.gov (United States)

    Chiu, Wah; Baker, Matthew L; Jiang, Wen; Dougherty, Matthew; Schmid, Michael F

    2005-03-01

    Advances in electron cryomicroscopy (cryo-EM) have made possible the structural determination of large biological machines in the resolution range of 6-9 angstroms. Rice dwarf virus and the acrosomal bundle represent two distinct types of machines amenable to cryo-EM investigations at subnanometer resolutions. However, calculating the density map is only the first step, and much analysis remains to extract structural insights and the mechanism of action in these machines. This paper will review the computational and visualization methodologies necessary for analysis (structure mining) of the computed cryo-EM maps of these machines. These steps include component segmentation, averaging based on local symmetry among components, density connectivity trace, incorporation of bioinformatics analysis, and fitting of high-resolution component data, if available. The consequences of these analyses can not only identify accurately some of the secondary structure elements of the molecular components in machines but also suggest structural mechanisms related to their biological functions.

  14. Machine Learning-Based Sentimental Analysis for Twitter Accounts

    Directory of Open Access Journals (Sweden)

    Ali Hasan

    2018-02-01

    Full Text Available Growth in the area of opinion mining and sentiment analysis has been rapid and aims to explore the opinions or text present on different platforms of social media through machine-learning techniques with sentiment, subjectivity analysis or polarity calculations. Despite the use of various machine-learning techniques and tools for sentiment analysis during elections, there is a dire need for a state-of-the-art approach. To deal with these challenges, the contribution of this paper includes the adoption of a hybrid approach that involves a sentiment analyzer that includes machine learning. Moreover, this paper also provides a comparison of techniques of sentiment analysis in the analysis of political views by applying supervised machine-learning algorithms such as Naïve Bayes and support vector machines (SVM.

  15. Data mining in bioinformatics using Weka.

    Science.gov (United States)

    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.

  16. APCOM 87. Volume 1 - mining

    Energy Technology Data Exchange (ETDEWEB)

    Wade, L.; Kersten, R.W.O.; Cutland, J.R. (eds.)

    1987-01-01

    35 papers are presented in this volume under the following session headings: rock mechanics; shafts; mine planning theory; expert systems in mining; mine planning case studies; ventilation; computer applications in education; and control of mining operations.

  17. Automatic Inspection During Machining

    Science.gov (United States)

    Ransom, Clyde L.

    1988-01-01

    In experimental manufacturing process, numerically-controlled machine tool temporarily converts into inspection machine by installing electronic touch probes and specially-developed numerical-control software. Software drives probes in paths to and on newly machined parts and collects data on dimensions of parts.

  18. Finite Virtual State Machines

    OpenAIRE

    Senhadji Navarro, Raouf; García Vargas, Ignacio

    2012-01-01

    This letter proposes a new model of state machine called Finite Virtual State Machine (FVSM). A memory-based architecture and a procedure for generating FVSM implementations from Finite State Machines (FSMs) are presented. FVSM implementations provide advantages in speed over conventional RAM-based FSM implementations. The results of experiments prove the feasibility of this approach.

  19. Learning control system of lifting machine motors

    Directory of Open Access Journals (Sweden)

    V. I. Zimovets

    2016-12-01

    Full Text Available Process automation control by diagnostic electric motors in operation conditions allows to reduce to a minimum the damage from these consequences due to early detection of defects. The theory of diagnosticof lifting machine motors has not been completely developed yet. In practice, the control of technical state of the motors is mainly performed during scheduled maintenance, which does not reveal to detect originating defects and to prevent significant damage of motors up to their complete failure. The difficulty of obtaining diagnostic information is that the main functional units of electric motors are dependent. This means that physical damage in any unit results in malfunctions of other units. The main way of increasing the efficiency of the automated control system of lifting machine motors is giving it the properties of adaptability on the basis of ideas and methods of machine learning and pattern recognition. To increase the operational reliability and service life of a mine electric lifting machines the article offers an information and machine learning algorithm for extreme functional control systems with electric hyprnspherical classifier. Normalized Shannon entropy measure was used as a criterion for functional efficiency of leaning systems of the functional control.

  20. Mining robotics sensors

    CSIR Research Space (South Africa)

    Green, JJ

    2011-07-01

    Full Text Available causes of fatalities in underground narrow reef mining. Data are gathered and processed from multiple underground mine sources, and techniques such as surfel modeling and synthetic view generation are explored towards creating visualisations of the data...

  1. Mining robotics sensors

    CSIR Research Space (South Africa)

    Green, JJ

    2012-04-01

    Full Text Available causes of fatalities in underground narrow reef mining. Data are gathered and processed from multiple underground mine sources, and techniques such as surfel modeling and synthetic view generation are explored towards creating visualisations of the data...

  2. Mines and Mineral Resources

    Data.gov (United States)

    Department of Homeland Security — Mines in the United States According to the Homeland Security Infrastructure Program Tiger Team Report Table E-2.V.1 Sub-Layer Geographic Names, a mine is defined as...

  3. Role of illumination in reducing risk to health and safety in South African gold and platinum mines

    CSIR Research Space (South Africa)

    Rushworth, AM

    2001-11-01

    Full Text Available and other aids to improve the visual environment. 2. Dynamic Locations: changing areas of the mine, such as production and development areas, where installations would normally be temporary, semi-portable or mounted on machines. 3. Mobile Machines... fixtures, upgrading headlights/rear lights on mobile machines, improving the reflectance of walls, painting obstructions in highly contrasting colours, etc. • Potential improvements to sight lines, for example, modifications to the profile of machines...

  4. Mining in El Salvador

    DEFF Research Database (Denmark)

    Pacheco Cueva, Vladimir

    2014-01-01

    In this guest article, Vladimir Pacheco, a social scientist who has worked on mining and human rights shares his perspectives on a current campaign against mining in El Salvador – Central America’s smallest but most densely populated country.......In this guest article, Vladimir Pacheco, a social scientist who has worked on mining and human rights shares his perspectives on a current campaign against mining in El Salvador – Central America’s smallest but most densely populated country....

  5. Uranium mining: Saskatchewan status

    Energy Technology Data Exchange (ETDEWEB)

    Martin, V. [AREVA Resources Canada Inc., Saskatoon, Saskatchewan, Ontario (Canada)

    2012-07-01

    This paper gives the status of uranium mining by Areva in Saskatchewan. Uranium production now meets 85% of world demand for power generation. 80% of world production of uranium comes from top 5 countries: Kazakhstan, Canada, Australia, Niger and Namibia. Saskatchewan is currently the only Canadian province with active uranium mines and mills and the largest exploration programs. Several mine projects are going through the environmental assessment process. Public opinion is in favour of mining activities in Saskatchewan.

  6. Precision machine design

    CERN Document Server

    Slocum, Alexander H

    1992-01-01

    This book is a comprehensive engineering exploration of all the aspects of precision machine design - both component and system design considerations for precision machines. It addresses both theoretical analysis and practical implementation providing many real-world design case studies as well as numerous examples of existing components and their characteristics. Fast becoming a classic, this book includes examples of analysis techniques, along with the philosophy of the solution method. It explores the physics of errors in machines and how such knowledge can be used to build an error budget for a machine, how error budgets can be used to design more accurate machines.

  7. Quantum machine learning

    Science.gov (United States)

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-01

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  8. Asynchronized synchronous machines

    CERN Document Server

    Botvinnik, M M

    1964-01-01

    Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

  9. Coal Mining, Germany

    Science.gov (United States)

    2001-01-01

    This simulated natural color ASTER image in the German state of North Rhine Westphalia covers an area of 30 by 36 km, and was acquired on August 26, 2000. On the right side of the image are 3 enormous opencast coalmines. The Hambach opencast coal mine has recently been brought to full output capacity through the addition of the No. 293 giant bucket wheel excavator. This is the largest machine in the world; it is twice as long as a soccer field and as tall as a building with 30 floors. To uncover the 2.4 billion tons of brown coal (lignite) found at Hambach, five years were required to remove a 200-m-thick layer of waste sand and to redeposit it off site. The mine currently yields 30 million tons of lignite annually, with annual capacity scheduled to increase to 40 million tons in coming years.The image is centered at 51 degrees north latitude, 6.4 degrees east longitude. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of five Earth-observing instruments launched December 18, 1999, on NASA's Terra satellite. The instrument was built by Japan's Ministry of International Trade and Industry. A joint U.S./Japan science team is responsible for validation and calibration of the instrument and the data products. Dr. Anne Kahle at NASA's Jet Propulsion Laboratory, Pasadena, California, is the U.S. science team leader; Moshe Pniel of JPL is the project manager. ASTER is the only high-resolution imaging sensor on Terra. The primary goal of the ASTER mission is to obtain high-resolution image data in 14 channels over the entire land surface, as well as black and white stereo images. With revisit time of between 4 and 16 days, ASTER will provide the capability for repeat coverage of changing areas on Earth's surface.The broad spectral coverage and high spectral resolution of ASTER will provide scientists in numerous disciplines with critical information for surface mapping and monitoring dynamic conditions and temporal change. Examples of

  10. Mountaintop mining consequences

    Science.gov (United States)

    M.A. Palmer; E.S. Bernhardt; W.H. Schlesinger; K.N. Eshleman; E. Foufoula-Georgiou; M.S. Hendryx; A.D. Lemly; G.E. Likens; O.L. Loucks; M.E. Power; P.S. White; P.R. Wilcock

    2010-01-01

    There has been a global, 30-year increase in surface mining (1), which is now the dominant driver of land-use change in the central Appalachian ecoregion of the United States (2). One major form of such mining, mountaintop mining with valley fills (MTM/VF) (3), is widespread throughout eastern Kentucky, West Virginia (WV), and southwestern Virginia. Upper elevation...

  11. Mined Acid Forest

    African Journals Online (AJOL)

    USER

    Abstract. The quality of degraded mined soils can be restored through effective reclamation practices. In this study, we evaluated the impact of varying duration of land reclamation on soil quality at AngloGold Ashanti, Iduapriem mine. Ltd., Tarkwa, Ghana. Soil samples were taken from mined sites of the Company at various ...

  12. Ghana Mining Journal: Contact

    African Journals Online (AJOL)

    Principal Contact. Professor Daniel Mireku-Gyimah Editor-in-Chief University of Mines & Technology Ghana Mining Journal University of Mines & Technology P. O. BOX 237 Tarkwa Ghana Phone: +233 362 20280/20324. Fax: +233 362 20306. Email: dm.gyimah@umat.edu.gh ...

  13. Data Mining for CRM

    Science.gov (United States)

    Thearling, Kurt

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

  14. Uranium, mining and hydrogeology

    Energy Technology Data Exchange (ETDEWEB)

    Merkel, Broder J. [TU Bergakademie Freiberg (Germany). Inst. fuer Geologie; Hasche-Berger, Andrea (eds.) [TU Bergakademie Freiberg (Germany). Inst. fuer Geophysik

    2008-07-01

    Subject of the book is Uranium and its migration in aquatic environments. The following subjects are emphasised: Uranium mining, Phosphate mining, mine closure and remediation, Uranium in groundwater and in bedrock, biogeochemistry of Uranium, environmental behavior, and modeling. Particular results from the leading edge of international research are presented. (orig.)

  15. Exceptional model mining

    NARCIS (Netherlands)

    Duivesteijn, Wouter

    2013-01-01

    Finding subsets of a dataset that somehow deviate from the norm, i.e. where something interesting is going on, is a classical Data Mining task. In traditional local pattern mining methods, such deviations are measured in terms of a relatively high occurrence (frequent itemset mining), or an unusual

  16. Data Mining in Earth System Science (DMESS 2011)

    Science.gov (United States)

    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...

  17. CPM Signal for Machine to Machine Communications

    OpenAIRE

    Messai, Malek

    2015-01-01

    The analysis of communication evolution predicts an increase in the number of connected machines. This thesis aims to determine a multi-user communication system adapted to the material limitation of the machines and to the applications constraints. Power and cost efficient digital modulation is required for both economic and environmental reasons; the power consumption on the link should be as low as possible. Constant envelope modulation offers the possibility to use non-linear cost-effecti...

  18. Perspex machine: VII. The universal perspex machine

    Science.gov (United States)

    Anderson, James A. D. W.

    2006-01-01

    The perspex machine arose from the unification of projective geometry with the Turing machine. It uses a total arithmetic, called transreal arithmetic, that contains real arithmetic and allows division by zero. Transreal arithmetic is redefined here. The new arithmetic has both a positive and a negative infinity which lie at the extremes of the number line, and a number nullity that lies off the number line. We prove that nullity, 0/0, is a number. Hence a number may have one of four signs: negative, zero, positive, or nullity. It is, therefore, impossible to encode the sign of a number in one bit, as floating-point arithmetic attempts to do, resulting in the difficulty of having both positive and negative zeros and NaNs. Transrational arithmetic is consistent with Cantor arithmetic. In an extension to real arithmetic, the product of zero, an infinity, or nullity with its reciprocal is nullity, not unity. This avoids the usual contradictions that follow from allowing division by zero. Transreal arithmetic has a fixed algebraic structure and does not admit options as IEEE, floating-point arithmetic does. Most significantly, nullity has a simple semantics that is related to zero. Zero means "no value" and nullity means "no information." We argue that nullity is as useful to a manufactured computer as zero is to a human computer. The perspex machine is intended to offer one solution to the mind-body problem by showing how the computable aspects of mind and, perhaps, the whole of mind relates to the geometrical aspects of body and, perhaps, the whole of body. We review some of Turing's writings and show that he held the view that his machine has spatial properties. In particular, that it has the property of being a 7D lattice of compact spaces. Thus, we read Turing as believing that his machine relates computation to geometrical bodies. We simplify the perspex machine by substituting an augmented Euclidean geometry for projective geometry. This leads to a general

  19. Classification Of Complex UCI Datasets Using Machine Learning And Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Anuj Gupta

    2015-05-01

    Full Text Available Abstract Classification is an important data mining technique with broad applications. Classification is a gradual practice for allocating a given piece of input into any of the known category. The Data Mining refers to extracting or mining knowledge from huge volume of data. In this paper different classification techniques of Data Mining are compared using diverse datasets from University of California Irvine UCI Machine Learning Repository. Accuracy and time complexity for execution by each classifier is observed. . Finally different classifiers are also compared with the help of Confusion Matrix. Classification is used to classify each item in a set of data into one of predefined set of classes or groups

  20. Perfecting technology and organization of development work in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Rud' , A.M.

    1980-02-01

    Conditions of development work and panelling of coal deposits in Donetskugol' mines are characterized, with mining located 1000 m below the surface and coal seams liable to bursts and methane emission. Air cooling systems used in deep mines during developing and panelling are described. A scheme of a system cooling heading machine oil is given. Water used for cooling is later used for spraying the face to control air dust. Combines, loaders and haulage systems drivage is stressed and organization of work during high speed drivage is discussed. A table shows a comparison of number of miners working in various development headings driven by high speed methods, machines and support systems used, and the economic results of their work, i.e. advance of the heading in one month and labor productivity per miner. (In Russian)

  1. Grinding efficiency improvement of hydraulic cylinders parts for mining equipment

    Directory of Open Access Journals (Sweden)

    Korotkov Aleksandr

    2017-01-01

    Full Text Available The aim of the article is to find out ways to improve parts treatment and components of mining equipment on the example of hydraulic cylinders parts, used as pillars for mine roof supports, and other actuator mechanisms. In the course of the research work methods of machine retaining devices design were used, the scientific approaches for the selection of progressive grinding schemes were applied; theoretical and practical experience in the design and production of new constructions of grinding tools was used. As a result of this work it became possible to create a progressive construction of a machine retaining device for grinding of large parts of hydraulic cylinders, to apply an effective scheme of rotary abrasive treatment, to create and implement new design of grinding tools by means of grains with controllable shape and orientation. Implementation of the results obtained in practice will improve the quality and performance of repairing and manufacturing of mining equipment.

  2. Data mining in radiology.

    Science.gov (United States)

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

    2014-04-01

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

  3. An investigation on surface roughness of granite machined by ...

    Indian Academy of Sciences (India)

    Administrator

    submerged waterjet with a free jet operating in air for red granite cutting in terms of cut depth. Matsuki et al (1988) expanded the comparison considering the influence of the impinging angle and standoff distance on the cut depth in rock. Further, parameters such as rock temperature, physical properties of rock and process ...

  4. Privacy-preserving restricted boltzmann machine.

    Science.gov (United States)

    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.

  5. Privacy-Preserving Restricted Boltzmann Machine

    Directory of Open Access Journals (Sweden)

    Yu Li

    2014-01-01

    Full Text Available 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.

  6. SparkText: Biomedical Text Mining on Big Data Framework.

    Directory of Open Access Journals (Sweden)

    Zhan Ye

    Full Text Available 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.

  7. SparkText: Biomedical Text Mining on Big Data Framework.

    Science.gov (United States)

    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.

  8. SparkText: Biomedical Text Mining on Big Data Framework

    Science.gov (United States)

    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

  9. Perfecting technology and organization of development work in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Shmigol, A.V.

    1980-02-01

    Haulage systems used in fully mechanized development headings in the western part of the Donbass are evaluated. 97% of loading is mechanized, 95% of mine drivage is done by heading machines. Haulage systems used in horizontal seams are evaluated: electric locomotives and loading conveyors combined with heading machines (shown in a diagram). Haulage systems in inclined seams include: belt conveyors for haulage of rocks and rope haulage way for transporting materials (also depicted). Rocks are loaded on a belt conveyor by a short (30 m) conveyor suspended on a monorail and moving together with the heading machine. Another version of haulage in inclined seams is a rope haulage way used for hauling mined material and materials and a loading conveyor towed by a heading combine. The described haulage systems and their productivity are evaluated. (In Russian)

  10. Machining of titanium alloys

    CERN Document Server

    2014-01-01

    This book presents a collection of examples illustrating the resent research advances in the machining of titanium alloys. These materials have excellent strength and fracture toughness as well as low density and good corrosion resistance; however, machinability is still poor due to their low thermal conductivity and high chemical reactivity with cutting tool materials. This book presents solutions to enhance machinability in titanium-based alloys and serves as a useful reference to professionals and researchers in aerospace, automotive and biomedical fields.

  11. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  12. Machinability of advanced materials

    CERN Document Server

    Davim, J Paulo

    2014-01-01

    Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

  13. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  14. Nanocomposites for Machining Tools

    Directory of Open Access Journals (Sweden)

    Daria Sidorenko

    2017-10-01

    Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

  15. Rotating electrical machines

    CERN Document Server

    Le Doeuff, René

    2013-01-01

    In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

  16. Induction machine handbook

    CERN Document Server

    Boldea, Ion

    2002-01-01

    Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

  17. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2013-01-01

    Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

  18. Nanocomposites for Machining Tools

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

    2017-01-01

    . A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools......Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials......, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance....

  19. Nanocomposites for Machining Tools.

    Science.gov (United States)

    Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

    2017-10-13

    Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

  20. Electrical machines & drives

    CERN Document Server

    Hammond, P

    1985-01-01

    Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

  1. Tribology in machine design

    CERN Document Server

    Stolarski, Tadeusz

    1999-01-01

    ""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

  2. Nanocomposites for Machining Tools

    Science.gov (United States)

    Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

    2017-01-01

    Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926

  3. Machine vision and mechatronics in practice

    CERN Document Server

    Brett, Peter

    2015-01-01

    The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine.  Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be ac...

  4. Recent advances in environmental data mining

    Science.gov (United States)

    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

  5. Kohtla "majamasin" = Kohtla's Mining-Machine / Kaisa Kaer

    Index Scriptorium Estoniae

    Kaer, Kaisa

    2013-01-01

    Kohtla kaevanduspark Ida-Virumaal. Projekteerijad: Arden Arroval, Joonas Sarapuu / Innopolis Insenerid OÜ. Ekspositsiooni kujundus, sisekujundus ja asendiplaan: Margit Argus, Margit Aule / KAOS Arhitektid. 2014. a. valmib endise rikastusvabriku hoones maapealne külastuskeskus

  6. Device for limiting single phase ground fault of mining machines

    Science.gov (United States)

    Fediuk, R. S.; Stoyushko, N. Yu; Yevdokimova, Yu G.; Smoliakov, A. K.; Batarshin, V. O.; Timokhin, R. A.

    2017-10-01

    The paper shows the reasons and consequences of the single-phase ground fault. With all the variety of devices for limiting the current single-phase ground fault, it was found that the most effective are Peterson coils having different switching circuits. Measuring of the capacity of the network is of great importance in this case, a number of options capacitance measurement are presented. A closer look is taken at the device for limiting the current of single-phase short circuit, developed in the Far Eastern Federal University under the direction of Dr. G.E. Kuvshinov. The calculation of single-phase short-circuit currents in the electrical network, without compensation and with compensation of capacitive current is carried out. Simulation of a single-phase circuit in a network with the proposed device is conducted.

  7. Diamond machine tool face lapping machine

    Science.gov (United States)

    Yetter, H.H.

    1985-05-06

    An apparatus for shaping, sharpening and polishing diamond-tipped single-point machine tools. The isolation of a rotating grinding wheel from its driving apparatus using an air bearing and causing the tool to be shaped, polished or sharpened to be moved across the surface of the grinding wheel so that it does not remain at one radius for more than a single rotation of the grinding wheel has been found to readily result in machine tools of a quality which can only be obtained by the most tedious and costly processing procedures, and previously unattainable by simple lapping techniques.

  8. Coal mine site reclamation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-02-15

    Coal mine sites can have significant effects on local environments. In addition to the physical disruption of land forms and ecosystems, mining can also leave behind a legacy of secondary detrimental effects due to leaching of acid and trace elements from discarded materials. This report looks at the remediation of both deep mine and opencast mine sites, covering reclamation methods, back-filling issues, drainage and restoration. Examples of national variations in the applicable legislation and in the definition of rehabilitation are compared. Ultimately, mine site rehabilitation should return sites to conditions where land forms, soils, hydrology, and flora and fauna are self-sustaining and compatible with surrounding land uses. Case studies are given to show what can be achieved and how some landscapes can actually be improved as a result of mining activity.

  9. 2nd International Conference on Computational Intelligence in Data Mining

    CERN Document Server

    Mohapatra, Durga

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 – 6 December 2015. The two-volume Proceedings address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

  10. 1st International Conference on Computational Intelligence in Data Mining

    CERN Document Server

    Behera, Himansu; Mandal, Jyotsna; Mohapatra, Durga

    2015-01-01

    The contributed volume aims to explicate and address the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of relate...

  11. DATA MINING TECHNOLOGIES

    OpenAIRE

    Titrade Cristina-Maria

    2010-01-01

    Knowledge discovery and data mining software (Knowledge Discovery and Data Mining - KDD) as an interdisciplinary field emersion have been in rapid growth to merge databases, statistics, industries closely related to the desire to extract valuable information and knowledge in a volume as possible.There is a difference in understanding of "knowledge discovery" and "data mining." Discovery information (Knowledge Discovery) in the database is a process to identify patterns / templates of valid da...

  12. Mining local process models

    OpenAIRE

    Tax, Niek; Sidorova, Natalia; Haakma, Reinder; van der Aalst, Wil M.P.

    2016-01-01

    In this paper we describe a method to discover frequent behavioral patterns in event logs. We express these patterns as \\emph{local process models}. Local process model mining can be positioned in-between process discovery and episode / sequential pattern mining. The technique presented in this paper is able to learn behavioral patterns involving sequential composition, concurrency, choice and loop, like in process mining. However, we do not look at start-to-end models, which distinguishes ou...

  13. Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

    Science.gov (United States)

    Chang, Qingliang; Zhou, Huaqiang; Bai, Jianbiao

    2014-01-01

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

  14. Implementation of paste backfill mining technology in Chinese coal mines.

    Science.gov (United States)

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

    2014-01-01

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

  15. Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

    Directory of Open Access Journals (Sweden)

    Qingliang Chang

    2014-01-01

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

  16. Simple Machine Junk Cars

    Science.gov (United States)

    Herald, Christine

    2010-01-01

    During the month of May, the author's eighth-grade physical science students study the six simple machines through hands-on activities, reading assignments, videos, and notes. At the end of the month, they can easily identify the six types of simple machine: inclined plane, wheel and axle, pulley, screw, wedge, and lever. To conclude this unit,…

  17. Simple Machines Made Simple.

    Science.gov (United States)

    St. Andre, Ralph E.

    Simple machines have become a lost point of study in elementary schools as teachers continue to have more material to cover. This manual provides hands-on, cooperative learning activities for grades three through eight concerning the six simple machines: wheel and axle, inclined plane, screw, pulley, wedge, and lever. Most activities can be…

  18. Perpetual Motion Machine

    Directory of Open Access Journals (Sweden)

    D. Tsaousis

    2008-01-01

    Full Text Available Ever since the first century A.D. there have been relative descriptions of known devices as well as manufactures for the creation of perpetual motion machines. Although physics has led, with two thermodynamic laws, to the opinion that a perpetual motion machine is impossible to be manufactured, inventors of every age and educational level appear to claim that they have invented something «entirely new» or they have improved somebody else’s invention, which «will function henceforth perpetually»! However the fact of the failure in manufacturing a perpetual motion machine till now, it does not mean that countless historical elements for these fictional machines become indifferent. The discussion on every version of a perpetual motion machine on the one hand gives the chance to comprehend the inventor’s of each period level of knowledge and his way of thinking, and on the other hand, to locate the points where this «perpetual motion machine» clashes with the laws of nature and that’s why it is impossible to have been manufactured or have functioned. The presentation of a new «perpetual motion machine» has excited our interest to locate its weak points. According to the designer of it the machine functions with the work produced by the buoyant force

  19. Human Machine Learning Symbiosis

    Science.gov (United States)

    Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

    2017-01-01

    Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

  20. Semantics via Machine Translation

    Science.gov (United States)

    Culhane, P. T.

    1977-01-01

    Recent experiments in machine translation have given the semantic elements of collocation in Russian more objective criteria. Soviet linguists in search of semantic relationships have attempted to devise a semantic synthesis for construction of a basic language for machine translation. One such effort is summarized. (CHK)

  1. Machine Translation Project

    Science.gov (United States)

    Bajis, Katie

    1993-01-01

    The characteristics and capabilities of existing machine translation systems were examined and procurement recommendations were developed. Four systems, SYSTRAN, GLOBALINK, PC TRANSLATOR, and STYLUS, were determined to meet the NASA requirements for a machine translation system. Initially, four language pairs were selected for implementation. These are Russian-English, French-English, German-English, and Japanese-English.

  2. Approaches to Machine Learning.

    Science.gov (United States)

    Langley, Pat; Carbonell, Jaime G.

    1984-01-01

    Reviews approaches to machine learning (development of techniques to automate acquisition of new information, skills, and ways of organizing existing information) in symbolic domains. Four categorical tasks addressed in machine learning literature are examined: learning from examples, learning search heuristics, learning by observation, and…

  3. Reactive Turing machines

    NARCIS (Netherlands)

    J.C.M. Baeten (Jos); S.P. Luttik (Bas); P.J.A. van Tilburg

    2013-01-01

    textabstractWe propose reactive Turing machines (RTMs), extending classical Turing machines with a process-theoretical notion of interaction, and use it to define a notion of executable transition system. We show that every computable transition system with a bounded branching degree is simulated

  4. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2015-01-01

    Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

  5. Machining heavy plastic sections

    Science.gov (United States)

    Stalkup, O. M.

    1967-01-01

    Machining technique produces consistently satisfactory plane-parallel optical surfaces for pressure windows, made of plexiglass, required to support a photographic study of liquid rocket combustion processes. The surfaces are machined and polished to the required tolerances and show no degradation from stress relaxation over periods as long as 6 months.

  6. Stirling machine operating experience

    Energy Technology Data Exchange (ETDEWEB)

    Ross, B. [Stirling Technology Co., Richland, WA (United States); Dudenhoefer, J.E. [Lewis Research Center, Cleveland, OH (United States)

    1994-09-01

    Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that stirling machines are capable of reliable and lengthy operating lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and are not expected to operate for lengthy periods of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered. The record in this paper is not complete, due to the reluctance of some organizations to release operational data and because several organizations were not contacted. The authors intend to repeat this assessment in three years, hoping for even greater participation.

  7. Coordinate measuring machines

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...

  8. Microsoft Azure machine learning

    CERN Document Server

    Mund, Sumit

    2015-01-01

    The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

  9. Social networking mining, visualization, and security

    CERN Document Server

    Dehuri, Satchidananda; Wang, Gi-Nam

    2014-01-01

    With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques, and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining.  

  10. LHC Report: machine development

    CERN Multimedia

    Rogelio Tomás García for the LHC team

    2015-01-01

    Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

  11. Micro-machining.

    Science.gov (United States)

    Brinksmeier, Ekkard; Preuss, Werner

    2012-08-28

    Manipulating bulk material at the atomic level is considered to be the domain of physics, chemistry and nanotechnology. However, precision engineering, especially micro-machining, has become a powerful tool for controlling the surface properties and sub-surface integrity of the optical, electronic and mechanical functional parts in a regime where continuum mechanics is left behind and the quantum nature of matter comes into play. The surprising subtlety of micro-machining results from the extraordinary precision of tools, machines and controls expanding into the nanometre range-a hundred times more precise than the wavelength of light. In this paper, we will outline the development of precision engineering, highlight modern achievements of ultra-precision machining and discuss the necessity of a deeper physical understanding of micro-machining.

  12. A.M.T. Machine Tools Limited

    National Research Council Canada - National Science Library

    2005-01-01

    Hydromat Inc. - Rotary Transfer Machines, Trunnion Machines, Automatic Bar Feeders Maschinenfabrik Heinrich Muller HMP - Rotary Swaging Machines, Wire Straightening and Cutting Machines Turmatic Systems Inc...

  13. 15 CFR 700.31 - Metalworking machines.

    Science.gov (United States)

    2010-01-01

    ... Drilling and tapping machines Electrical discharge, ultrasonic and chemical erosion machines Forging machinery and hammers Gear cutting and finishing machines Grinding machines Hydraulic and pneumatic presses...

  14. 30 CFR 18.82 - Permit to use experimental electric face equipment in a gassy mine or tunnel.

    Science.gov (United States)

    2010-07-01

    ... MINE EQUIPMENT AND ACCESSORIES Machines Assembled With Certified or Explosion-Proof Components, Field... electric face equipment in a gassy mine or tunnel. (a) Application for permit. An application for a permit... submitted by the user of the equipment. The user shall submit a written application to the Assistant...

  15. Conveyor belt service machine

    National Research Council Canada - National Science Library

    1984-01-01

    ... in. and thicker that could reduce the time, cost and injury potential inherent in extending and retracting mine wide section belt conveyors while eliminating the need to use additional machinery in accomplishing such moves...

  16. Advances in independent component analysis and learning machines

    CERN Document Server

    Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

    2015-01-01

    In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

  17. The basic anaesthesia machine

    Directory of Open Access Journals (Sweden)

    C L Gurudatt

    2013-01-01

    Full Text Available After WTG Morton′s first public demonstration in 1846 of use of ether as an anaesthetic agent, for many years anaesthesiologists did not require a machine to deliver anaesthesia to the patients. After the introduction of oxygen and nitrous oxide in the form of compressed gases in cylinders, there was a necessity for mounting these cylinders on a metal frame. This stimulated many people to attempt to construct the anaesthesia machine. HEG Boyle in the year 1917 modified the Gwathmey′s machine and this became popular as Boyle anaesthesia machine. Though a lot of changes have been made for the original Boyle machine still the basic structure remains the same. All the subsequent changes which have been brought are mainly to improve the safety of the patients. Knowing the details of the basic machine will make the trainee to understand the additional improvements. It is also important for every practicing anaesthesiologist to have a thorough knowledge of the basic anaesthesia machine for safe conduct of anaesthesia.

  18. Machine Learning and Radiology

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

    In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

  19. Mining and the Environment

    International Development Research Centre (IDRC) Digital Library (Canada)

    In addition to CODELCO, a second state-owned mining company is La Empresa Nacional de Minería (ENAMI, national mining company). ...... The department came up with the Urgent Plan for Environmental Hygiene, which was intended to solve environmental problems in ENAMI's works relatively quickly and at a low cost ...

  20. Gold-Mining

    DEFF Research Database (Denmark)

    Raaballe, J.; Grundy, B.D.

    2002-01-01

      Based on standard option pricing arguments and assumptions (including no convenience yield and sustainable property rights), we will not observe operating gold mines. We find that asymmetric information on the reserves in the gold mine is a necessary and sufficient condition for the existence o...

  1. pubmed.mineR

    Indian Academy of Sciences (India)

    ... meaningful information from the text, and, thus makes the information contained in the text accessible to various data-mining algorithms. It is roughly equivalent to text analytics. An important facet of text- mining is extraction of patterns and trends, and R with its rich repertoire of statistical tools is well suited for this purpose.

  2. Mine reclamation in Arkansas

    Science.gov (United States)

    Floyd Durham; James G. Barnum

    1980-01-01

    Open cut mine land reclamation laws have only been effective since 1971 in Arkansas. Since that time all land affected by mining had to be reclaimed. To guarantee reclamation, the first law required a $500 per acre surety bond be posted with the Arkansas Department of Pollution Control and Ecology. The Arkansas Open Cut Land Reclamation Act of 1977 changed the bonding...

  3. Mining Glossary and Games.

    Science.gov (United States)

    National Energy Foundation, Salt Lake City, UT.

    This booklet was produced in an effort to increase the awareness and appreciation of young people for the Earth's resources. The Mining Education Glossary is intended to provide easy reference to mining terms which are used in the minerals recovery industry and as a useful resource for teaching basic learning skills. Accompanying the glossary are…

  4. A Universal Reactive Machine

    DEFF Research Database (Denmark)

    Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

    1997-01-01

    Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...... in the sense that, given an encoding of any CCS process, it behaves like this process up to weak bisimulation. This construction has arather non-constructive use of silent actions and we argue that this would be the case for any universal CCS process....

  5. Fundamentals of machine design

    CERN Document Server

    Karaszewski, Waldemar

    2011-01-01

    A forum of researchers, educators and engineers involved in various aspects of Machine Design provided the inspiration for this collection of peer-reviewed papers. The resultant dissemination of the latest research results, and the exchange of views concerning the future research directions to be taken in this field will make the work of immense value to all those having an interest in the topics covered. The book reflects the cooperative efforts made in seeking out the best strategies for effecting improvements in the quality and the reliability of machines and machine parts and for extending

  6. Machine Learning for Hackers

    CERN Document Server

    Conway, Drew

    2012-01-01

    If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyz

  7. Gaussian optical Ising machines

    Science.gov (United States)

    Clements, William R.; Renema, Jelmer J.; Wen, Y. Henry; Chrzanowski, Helen M.; Kolthammer, W. Steven; Walmsley, Ian A.

    2017-10-01

    It has recently been shown that optical parametric oscillator (OPO) Ising machines, consisting of coupled optical pulses circulating in a cavity with parametric gain, can be used to probabilistically find low-energy states of Ising spin systems. In this work, we study optical Ising machines that operate under simplified Gaussian dynamics. We show that these dynamics are sufficient for reaching probabilities of success comparable to previous work. Based on this result, we propose modified optical Ising machines with simpler designs that do not use parametric gain yet achieve similar performance, thus suggesting a route to building much larger systems.

  8. Analysis of synchronous machines

    CERN Document Server

    Lipo, TA

    2012-01-01

    Analysis of Synchronous Machines, Second Edition is a thoroughly modern treatment of an old subject. Courses generally teach about synchronous machines by introducing the steady-state per phase equivalent circuit without a clear, thorough presentation of the source of this circuit representation, which is a crucial aspect. Taking a different approach, this book provides a deeper understanding of complex electromechanical drives. Focusing on the terminal rather than on the internal characteristics of machines, the book begins with the general concept of winding functions, describing the placeme

  9. Machine Tool Software

    Science.gov (United States)

    1988-01-01

    A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

  10. Data mining for service

    CERN Document Server

    2014-01-01

    Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous, complex, distributed, etc. Data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering new information, and it is one of the most important steps to scientific analysis of the processes of services.  Data mining application in services requires a thorough understanding of the characteristics of each service and knowledge of the compatibility of data mining technology within each particular service, rather than knowledge only in calculation speed and prediction accuracy. Varied examples of services provided in this book will help readers understand the relation between services and data mining technology. This book is intended to stimulate interest among researchers and practitioners in the relation between data mining technology and its application to ...

  11. Opencast mining 1997

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-31

    The latest issue of this annual publication contains the following items on the United Kingdom`s opencast mining industry: `Challenging times for the Coal Authority`; `Coal - to be or not to be`; `Profits and progress: the major producers`; `Miller`s Tale` (about Miller Mining); `New Labour, New limits on opencast mining`; `On the right track`; `Coal exploration for the Millennium`; `A cleaner future for Houghton Main`; `Auger mining - an update`; `The application of virtual reality to risk management`; `Single suction submersible pumps for dewatering in mines`; and `Woodland - a natural after use`. It also contains a listing and map (insert) of UK opencast coal sites in production as at 1 November 1997, details of site operators, industry news, equipment news, a suppliers directory, site news, and site profiles (on Brynhenllys, East Balbeggie Farm, Herrington Colliery and Pegswood Moor Farm).

  12. Mechatronic design of a reconfigurable machining machine

    CSIR Research Space (South Africa)

    Xing, B

    2008-10-01

    Full Text Available can be applied to the design of RMM [4]. Researchers at the Carnegie Mellon University developed RMMS (Reconfigurable Modular Manipulator System) [5]. They identified the characteristics of reconfigurable machine design as a task based design... and developed a design methodology for reconfigurable manipulators from the kinematics task requirements [6] [7]. I.-M. Chen [8] applied the theory of graphs to the design of reconfigurable manipulators and proposed the concept of Assembly Incident Matrix...

  13. Introduction to AC machine design

    CERN Document Server

    Lipo, Thomas A

    2018-01-01

    AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

  14. International Conference on Computational Intelligence in Data Mining

    CERN Document Server

    Mohapatra, Durga

    2017-01-01

    The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science. .

  15. Evaluating machine learning classification for financial trading: An empirical approach

    OpenAIRE

    Gerlein, EA; McGinnity, TM; Belatreche, A; S Coleman

    2016-01-01

    Technical and quantitative analysis in financial trading use mathematical and statistical tools to help investors decide on the optimum moment to initiate and close orders. While these traditional approaches have served their purpose to some extent, new techniques arising from the field of computational intelligence such as machine learning and data mining have emerged to analyse financial information. While the main financial engineering research has focused on complex computational models s...

  16. Molecular Machines: Nanoscale gadgets

    Science.gov (United States)

    Garcia-Garibay, Miguel A.

    2008-06-01

    Meeting their biological counterparts halfway, artificial molecular machines embedded in liquid crystals, crystalline solids and mesoporous materials are poised to meet the demands of the next generation of functional materials.

  17. Machine Vision Handbook

    CERN Document Server

    2012-01-01

    The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

  18. Some relations between quantum Turing machines and Turing machines

    OpenAIRE

    Sicard, Andrés; Vélez, Mario

    1999-01-01

    For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

  19. Metalworking and machining fluids

    Science.gov (United States)

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

    Improved boron-based metal working and machining fluids. Boric acid and boron-based additives that, when mixed with certain carrier fluids, such as water, cellulose and/or cellulose derivatives, polyhydric alcohol, polyalkylene glycol, polyvinyl alcohol, starch, dextrin, in solid and/or solvated forms result in improved metalworking and machining of metallic work pieces. Fluids manufactured with boric acid or boron-based additives effectively reduce friction, prevent galling and severe wear problems on cutting and forming tools.

  20. Human-machine interactions

    Science.gov (United States)

    Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

    2009-04-28

    Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

  1. Contract Mining versus Owner Mining – The Way Forward | Suglo ...

    African Journals Online (AJOL)

    Mining involves many operations such as rock breakage, materials handling, equipment maintenance, mine design, scheduling and budgeting. At one stage or the other mine managements often have to decide whether to undertake a major mining operation using their own equipment and personnel or to contract the ...

  2. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  3. Text Mining for Protein Docking.

    Science.gov (United States)

    Badal, Varsha D; Kundrotas, Petras J; Vakser, Ilya A

    2015-12-01

    The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set

  4. Text Mining for Protein Docking.

    Directory of Open Access Journals (Sweden)

    Varsha D Badal

    2015-12-01

    Full Text Available The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking. Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu. The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound

  5. EVALUATION OF MACHINE TOOL QUALITY

    Directory of Open Access Journals (Sweden)

    Ivan Kuric

    2011-12-01

    Full Text Available Paper deals with aspects of quality and accuracy of machine tools. As the accuracy of machine tools has key factor for product quality, it is important to know the methods for evaluation of quality and accuracy of machine tools. Several aspects of diagnostics of machine tools are described, such as aspects of reliability.

  6. Gandy-Paun-Rozenberg Machines

    OpenAIRE

    Obtulowicz, Adam

    2010-01-01

    Gandy-Paun-Rozenberg machines are introduced as certain graph rewriting systems. A representation of Gandy-Paun-Rozenberg machines by Gandy machines is given. A construction of a Gandy-Paun-Rozenberg machine solving 3-SAT problem in a polynomial time is shown.

  7. Small Turing universal signal machines

    Directory of Open Access Journals (Sweden)

    Jérôme Durand-Lose

    2009-06-01

    Full Text Available This article aims at providing signal machines as small as possible able to perform any computation (in the classical understanding. After presenting signal machines, it is shown how to get universal ones from Turing machines, cellular-automata and cyclic tag systems. Finally a halting universal signal machine with 13 meta-signals and 21 collision rules is presented.

  8. Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

    OpenAIRE

    Qingliang Chang; Jianhang Chen; Huaqiang Zhou; Jianbiao Bai

    2014-01-01

    Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology a...

  9. Mine-Detecting Canines

    Science.gov (United States)

    1977-09-01

    affliction known as hip dysplasia which disables a majority of German Shepherds after age 5 to 7 years. b. Minimize the aggressive tendencies which cause...Sheet 33-34 7 Density of Dog Alerts As a Function of "Sit" Distance from Center of Mines 40 8 Detection Performance of Dogs 41 9 Detection Performance...by Time of Day 43 10 Detection Performance of Dog Groups 44 11 Mines Detected by Type of Mine 45 12 Detection Performance, Grouped by Handlers 46 13

  10. A Review of the State of the Art of Machine Learning on the Semantic Web

    OpenAIRE

    Price, SN

    2003-01-01

    This paper reviews the current state of the art of machine learning applied to the Semantic Web. It looks at the Semantic Web and its languages, including RDF and OWL, from a machine learning perspective. Trends in the Semantic Web are mentioned throughout and the relationship with Web Services is examined. Applications are discussed with recent examples and pointers to data sets. Finally, the emerging field of Semantic Web Mining is introduced. This paper reviews the current state of the ...

  11. Data Mining in Child Welfare.

    Science.gov (United States)

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

    2000-01-01

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

  12. Optimizing model to match mining equipment sets. [13 references

    Energy Technology Data Exchange (ETDEWEB)

    Otte, J.A.; Randolph, D.; Boehlje, M.D.

    1976-08-01

    High investment and operating cost require miners to make maximum utilization of equipment they select. To fully utilize equipment, individual units of the equipment set should be selected to attain the most profitable match ratio and interaction effficiency. A mining cost generator and machine matching program were developed to calculate production and owning and operating costs for individual machines and then determine cost per unit of output for each combination. The combination with the lowest cost per unit of output is optimal. The cost calculation reflects cost penalties for both under- and excess-capacity based on overtime operation and machine interaction efficiency. Hourly production, investment, and owning and operating cost per hour for each type of machine are the most important variables in determining cost per unit of output. The match ratio and interaction efficiency appear to become more important as the number of machines working in combination increases. The relative cost of under- and excess-capacity are determined by analyzing the impact on total cost and total production of a one machine increase or decrease of each type of unit in the combination, not by examining what that machine is theoretically capable of accomplishing by itself.

  13. Machining of Metal Matrix Composites

    CERN Document Server

    2012-01-01

    Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

  14. Seminal quality prediction using data mining methods.

    Science.gov (United States)

    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

  15. Non-conventional electrical machines

    CERN Document Server

    Rezzoug, Abderrezak

    2013-01-01

    The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

  16. Overcoming delivery difficulties to remote Malaysian mine site

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-05-01

    The Merit Pila coalfield in Sarawak, Malaysia is one of the largest in southeast Asia, but is very remote. It is being worked opencast with new equipment from Liebherr-Singapore and Euclid This machinery caused considerable delivery problems. The first stage of the journey was on a barge from Singapore, taking precautions to avoid pirates. The barge was then towed up river so far as Kapit, the nearest town to the mine. The equipment then began a 54 km walk up the dirt logging road to the minesite. The bridges were inadequate to take the load, and traffic from the mine and logging sites meant that travel had to take place at night. Days were spent preparing ford or dam crossings by the Liebherr PR751 dozer and R964 excavator, which were then quickly crossed by the equipment before riverbank restoration by the two machines. The trek took six days. The machines will in future be serviced on site. 4 figs.

  17. Data mining in Cloud Computing

    OpenAIRE

    Ruxandra-Ştefania PETRE

    2012-01-01

    This paper describes how data mining is used in cloud computing. Data Mining is used for extracting potentially useful information from raw data. The integration of data mining techniques into normal day-to-day activities has become common place. Every day people are confronted with targeted advertising, and data mining techniques help businesses to become more efficient by reducing costs. Data mining techniques and applications are very much needed in the cloud computing paradigm. The implem...

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

    OpenAIRE

    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 ...

  19. Mining the Moon

    National Research Council Canada - National Science Library

    Schmitt, Harrison H

    2004-01-01

    The author, a geologist who collected rocks on the Moon during the Apollo 19 mission, argues that the time is now ripe to return there, to mine the quantities of the isotope helium-3 found on the Moon...

  20. Data mining in agriculture

    CERN Document Server

    Mucherino, Antonio; Pardalos, Panos M

    2009-01-01

    Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009.

  1. Acid mine drainage

    Science.gov (United States)

    Bigham, Jerry M.; Cravotta, Charles A.

    2016-01-01

    Acid mine drainage (AMD) consists of metal-laden solutions produced by the oxidative dissolution of iron sulfide minerals exposed to air, moisture, and acidophilic microbes during the mining of coal and metal deposits. The pH of AMD is usually in the range of 2–6, but mine-impacted waters at circumneutral pH (5–8) are also common. Mine drainage usually contains elevated concentrations of sulfate, iron, aluminum, and other potentially toxic metals leached from rock that hydrolyze and coprecipitate to form rust-colored encrustations or sediments. When AMD is discharged into surface waters or groundwaters, degradation of water quality, injury to aquatic life, and corrosion or encrustation of engineered structures can occur for substantial distances. Prevention and remediation strategies should consider the biogeochemical complexity of the system, the longevity of AMD pollution, the predictive power of geochemical modeling, and the full range of available field technologies for problem mitigation.

  2. Protecting mine hoisting systems

    Energy Technology Data Exchange (ETDEWEB)

    Sidorenko, V.A.; Shatilo, A.N.

    1982-10-01

    The paper discusses problems associated with coal and rock hoisting in underground coal mines in the USSR. Design of standardized safety systems used in Soviet coal mines is described. Failures of control systems which determine hoisting speed are analyzed. When a cage approaches a loading level or ground level at excessive speed the bumping beams accept cage energy. Cage deformation, damage and hoisting rope damage are the result. Correcting cage position in relation to loading levels is a relatively complicated process. The electronic system for automatic control of cage speed and automatic braking when cage speed exceeds the maximum permissible speed in a mine shaft section is evaluated. System design is shown in a scheme. Its specifications are given. It consists of speed sensors, a system activating safety brakes and a system for cage positioning after safety braking. Use of the safety system in some coal mines is discussed.

  3. SME mining engineering handbook

    National Research Council Canada - National Science Library

    Darling, Peter

    2011-01-01

    ...) 948-4200 / (800) 763-3132 www.smenet.org SME advances the worldwide mining and minerals community through information exchange and professional development. With members in more than 70 countrie...

  4. Machinability evaluation of machinable ceramics with fuzzy theory

    Institute of Scientific and Technical Information of China (English)

    YU Ai-bing; ZHONG Li-jun; TAN Ye-fa

    2005-01-01

    The property parameters and machining output parameters were selected for machinability evaluation of machinable ceramics. Based on fuzzy evaluation theory, two-stage fuzzy evaluation approach was applied to consider these parameters. Two-stage fuzzy comprehensive evaluation model was proposed to evaluate machinability of machinable ceramic materials. Ce-ZrO2/CePO4 composites were fabricated and machined for evaluation of machinable ceramics. Material removal rates and specific normal grinding forces were measured. The parameters concerned with machinability were selected as alternative set. Five grades were chosen for the machinability evaluation of machnable ceramics. Machinability grades of machinable ceramics were determined through fuzzy operation. Ductile marks are observed on Ce-ZrO2/CePO4 machined surface. Five prepared Ce-ZrO2/CePO4 composites are classified as three machinability grades according to the fuzzy comprehensive evaluation results. The machinability grades of Ce-ZrO2/CePO4 composites are concerned with CePO4 content.

  5. MACHINE MOTION EQUATIONS

    Directory of Open Access Journals (Sweden)

    Florian Ion Tiberiu Petrescu

    2015-09-01

    Full Text Available This paper presents the dynamic, original, machine motion equations. The equation of motion of the machine that generates angular speed of the shaft (which varies with position and rotation speed is deduced by conservation kinetic energy of the machine. An additional variation of angular speed is added by multiplying by the coefficient dynamic D (generated by the forces out of mechanism and or by the forces generated by the elasticity of the system. Kinetic energy conservation shows angular speed variation (from the shaft with inertial masses, while the dynamic coefficient introduces the variation of w with forces acting in the mechanism. Deriving the first equation of motion of the machine one can obtain the second equation of motion dynamic. From the second equation of motion of the machine it determines the angular acceleration of the shaft. It shows the distribution of the forces on the mechanism to the internal combustion heat engines. Dynamic, the velocities can be distributed in the same way as forces. Practically, in the dynamic regimes, the velocities have the same timing as the forces. Calculations should be made for an engine with a single cylinder. Originally exemplification is done for a classic distribution mechanism, and then even the module B distribution mechanism of an Otto engine type.

  6. Mining water governance

    OpenAIRE

    Sosa Landeo, Milagros

    2017-01-01

    This thesis documents as well as questions how the presence of large mining operations in Andean regions of Peru alters social and natural landscapes. Taking conflicts over water as a useful entry-point for the analysis, it explores and unravels the dilemmas and challenges faced by the main conflicting actors: rural communities and mining companies. Through an in-depth analysis of how the actors navigate these challenges, focusing on those related to water, the thesis sets out to understand w...

  7. Applied data mining

    CERN Document Server

    Xu, Guandong

    2013-01-01

    Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest advances in newly emerging information services. It explores the extension of well-studied algorithms and approaches into these new research arenas.

  8. Data Mining with Clustering

    OpenAIRE

    Klímek, Petr

    2008-01-01

    One of the oppotunities in data mining is a use of clustering analysis. Clustering analysis belongs to unsupervised methods of data mining. We put here a focus on this method. Some basic principles are described in the second part of this paper. This method is examined on two examples from the marketing field. In the first example is used software Statgraphics 5.0Plus to solve clustering problem (nearest neighbour algorithm and Eucleidian distance); and in the second example is used Statistic...

  9. WEB STRUCTURE MINING

    Directory of Open Access Journals (Sweden)

    CLAUDIA ELENA DINUCĂ

    2011-01-01

    Full Text Available The World Wide Web became one of the most valuable resources for information retrievals and knowledge discoveries due to the permanent increasing of the amount of data available online. Taking into consideration the web dimension, the users get easily lost in the web’s rich hyper structure. Application of data mining methods is the right solution for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering and Web based data warehousing. In this paper, I provide an introduction of Web mining categories and I focus on one of these categories: the Web structure mining. Web structure mining, one of three categories of web mining for data, is a tool used to identify the relationship between Web pages linked by information or direct link connection. It offers information about how different pages are linked together to form this huge web. Web Structure Mining finds hidden basic structures and uses hyperlinks for more web applications such as web search.

  10. Mine Waste at The Kherzet Youcef Mine : Environmental Characterization

    Science.gov (United States)

    Issaad, Mouloud; Boutaleb, Abdelhak; Kolli, Omar

    2017-04-01

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

  11. Designing of innovative mining equipment for safe and successful work in mines

    Directory of Open Access Journals (Sweden)

    Trifonov Vladimir Alexandrovich

    2016-01-01

    Full Text Available The article analyses contemporary problems of economic development in Russia. An innovative approach to designing of industrial products based on the assessment of their performance and economic characteristics makes it possible to develop, manufacture and operate products with an optimal quality-toprice ratio, which is a priority for the well-being of the country, oriented to import substitution. The authors define some ways to improve competitive abilities of mining equipment manufactured in Russia and estimate the prospects of economic development in short-term by the example of Kemerovo region and LLC “Yurginsky Machine Engineering Plant”.

  12. Machines and Metaphors

    Directory of Open Access Journals (Sweden)

    Ángel Martínez García-Posada

    2016-10-01

    Full Text Available The edition La ley del reloj. Arquitectura, máquinas y cultura moderna (Cátedra, Madrid, 2016 registers the useful paradox of the analogy between architecture and technique. Its author, the architect Eduardo Prieto, also a philosopher, professor and writer, acknowledges the obvious distance from machines to buildings, so great that it can only be solved using strange comparisons, since architecture does not move nor are the machines habitable, however throughout the book, from the origin of the metaphor of the machine, with clarity in his essay and enlightening erudition, he points out with certainty some concomitances of high interest, drawing throughout history a beautiful cartography of the fruitful encounter between organics and mechanics.

  13. Artificial Molecular Machines.

    Science.gov (United States)

    Balzani; Credi; Raymo; Stoddart

    2000-10-02

    The miniaturization of components used in the construction of working devices is being pursued currently by the large-downward (top-down) fabrication. This approach, however, which obliges solid-state physicists and electronic engineers to manipulate progressively smaller and smaller pieces of matter, has its intrinsic limitations. An alternative approach is a small-upward (bottom-up) one, starting from the smallest compositions of matter that have distinct shapes and unique properties-namely molecules. In the context of this particular challenge, chemists have been extending the concept of a macroscopic machine to the molecular level. A molecular-level machine can be defined as an assembly of a distinct number of molecular components that are designed to perform machinelike movements (output) as a result of an appropriate external stimulation (input). In common with their macroscopic counterparts, a molecular machine is characterized by 1) the kind of energy input supplied to make it work, 2) the nature of the movements of its component parts, 3) the way in which its operation can be monitored and controlled, 4) the ability to make it repeat its operation in a cyclic fashion, 5) the timescale needed to complete a full cycle of movements, and 6) the purpose of its operation. Undoubtedly, the best energy inputs to make molecular machines work are photons or electrons. Indeed, with appropriately chosen photochemically and electrochemically driven reactions, it is possible to design and synthesize molecular machines that do work. Moreover, the dramatic increase in our fundamental understanding of self-assembly and self-organizational processes in chemical synthesis has aided and abetted the construction of artificial molecular machines through the development of new methods of noncovalent synthesis and the emergence of supramolecular assistance to covalent synthesis as a uniquely powerful synthetic tool. The aim of this review is to present a unified view of the field

  14. Chatter and machine tools

    CERN Document Server

    Stone, Brian

    2014-01-01

    Focussing on occurrences of unstable vibrations, or Chatter, in machine tools, this book gives important insights into how to eliminate chatter with associated improvements in product quality, surface finish and tool wear. Covering a wide range of machining processes, including turning, drilling, milling and grinding, the author uses his research expertise and practical knowledge of vibration problems to provide solutions supported by experimental evidence of their effectiveness. In addition, this book contains links to supplementary animation programs that help readers to visualise the ideas detailed in the text. Advancing knowledge in chatter avoidance and suggesting areas for new innovations, Chatter and Machine Tools serves as a handbook for those desiring to achieve significant reductions in noise, longer tool and grinding wheel life and improved product finish.

  15. Dynamics of cyclic machines

    CERN Document Server

    Vulfson, Iosif

    2015-01-01

    This book focuses on modern methods of oscillation analysis in machines, including cyclic action mechanisms (linkages, cams, steppers, etc.). It presents schematization techniques and mathematical descriptions of oscillating systems, taking into account the variability of the parameters and nonlinearities, engineering evaluations of dynamic errors, and oscillation suppression methods. The majority of the book is devoted to the development of new methods of dynamic analysis and synthesis for cyclic machines that form regular oscillatory systems with multiple duplicate modules.  There are also sections examining aspects of general engineering interest (nonlinear dissipative forces, systems with non-stationary constraints, impacts and pseudo-impacts in clearances, etc.)  The examples in the book are based on the widely used results of theoretical and experimental studies as well as engineering calculations carried out in relation to machines used in the textile, light, polygraphic and other industries. Particu...

  16. Machine Learning for Security

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Applied statistics, aka ‘Machine Learning’, offers a wealth of techniques for answering security questions. It’s a much hyped topic in the big data world, with many companies now providing machine learning as a service. This talk will demystify these techniques, explain the math, and demonstrate their application to security problems. The presentation will include how-to’s on classifying malware, looking into encrypted tunnels, and finding botnets in DNS data. About the speaker Josiah is a security researcher with HP TippingPoint DVLabs Research Group. He has over 15 years of professional software development experience. Josiah used to do AI, with work focused on graph theory, search, and deductive inference on large knowledge bases. As rules only get you so far, he moved from AI to using machine learning techniques identifying failure modes in email traffic. There followed digressions into clustered data storage and later integrated control systems. Current ...

  17. Advanced Analysis of Nontraditional Machining

    CERN Document Server

    Tsai, Hung-Yin

    2013-01-01

    Nontraditional machining utilizes thermal, chemical, electrical, mechanical and optical sources of energy to form and cut materials. Advanced Analysis of Nontraditional Machining explains in-depth how each of these advanced machining processes work, their machining system components, and process variables and industrial applications, thereby offering advanced knowledge and scientific insight. This book also documents the latest and frequently cited research results of a few key nonconventional machining processes for the most concerned topics in industrial applications, such as laser machining, electrical discharge machining, electropolishing of die and mold, and wafer processing for integrated circuit manufacturing. This book also: Fills the gap of the advanced knowledge of nonconventional machining between industry and research Documents latest and frequently cited research of key nonconventional machining processes for the most sought after topics in industrial applications Demonstrates advanced multidisci...

  18. Explaining and predicting workplace accidents using data-mining techniques

    Energy Technology Data Exchange (ETDEWEB)

    Rivas, T., E-mail: trivas@uvigo.e [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Paz, M., E-mail: mpaz.minas@gmail.co [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Martin, J.E., E-mail: jmartin@cippinternacional.co [CIPP International, S.L. Parque Tecnologico de Asturias, Parcela 43, Oficina 11, 33428 Llanera (Spain); Matias, J.M., E-mail: jmmatias@uvigo.e [Dpto. Estadistica e Investigacion Operativa, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Garcia, J.F., E-mail: jgarcia@cippinternacional.co [CIPP International, S.L. Parque Tecnologico de Asturias, Parcela 43, Oficina 11, 33428 Llanera (Spain); Taboada, J., E-mail: jtaboada@uvigo.e [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain)

    2011-07-15

    Current research into workplace risk is mainly conducted using conventional descriptive statistics, which, however, fail to properly identify cause-effect relationships and are unable to construct models that could predict accidents. The authors of the present study modelled incidents and accidents in two companies in the mining and construction sectors in order to identify the most important causes of accidents and develop predictive models. Data-mining techniques (decision rules, Bayesian networks, support vector machines and classification trees) were used to model accident and incident data compiled from the mining and construction sectors and obtained in interviews conducted soon after an incident/accident occurred. The results were compared with those for a classical statistical techniques (logistic regression), revealing the superiority of decision rules, classification trees and Bayesian networks in predicting and identifying the factors underlying accidents/incidents.

  19. Dust control in underground mining. Staubbekaempfung unter Tage

    Energy Technology Data Exchange (ETDEWEB)

    1983-01-01

    The book describes all of the 27 research projects in the field of underground-mining dust control which were carried out by the black-coal mining industry within the Federal German Government programme for the humanization of labour conditions (HLC). The following subject areas were covered: dust control in the face cavity by means of soaking, at coal-getting machines, at shield supports, with pneumatic packing; dust control in construction of headings with continuous miners and with concurrent cutting of headings by means of drum cutter-loaders; dust control in haulage roads, in the face/heading area, at crushers in coal delivery roads, at transfer points and belts; special dust control measures. A brief survey on dust control measures used in German black-coal mining is annexed.

  20. Data mining-aided materials discovery and optimization

    Directory of Open Access Journals (Sweden)

    Wencong Lu

    2017-09-01

    Full Text Available Recent developments in data mining-aided materials discovery and optimization are reviewed in this paper, and an introduction to the materials data mining (MDM process is provided using case studies. Both qualitative and quantitative methods in machine learning can be adopted in the MDM process to accomplish different tasks in materials discovery, design, and optimization. State-of-the-art techniques in data mining-aided materials discovery and optimization are demonstrated by reviewing the controllable synthesis of dendritic Co3O4 superstructures, materials design of layered double hydroxide, battery materials discovery, and thermoelectric materials design. The results of the case studies indicate that MDM is a powerful approach for use in materials discovery and innovation, and will play an important role in the development of the Materials Genome Initiative and Materials Informatics.

  1. Perpetual Motion Machine

    OpenAIRE

    D. Tsaousis

    2008-01-01

    Ever since the first century A.D. there have been relative descriptions of known devices as well as manufactures for the creation of perpetual motion machines. Although physics has led, with two thermodynamic laws, to the opinion that a perpetual motion machine is impossible to be manufactured, inventors of every age and educational level appear to claim that they have invented something «entirely new» or they have improved somebody else’s invention, which «will function henceforth perpetuall...

  2. New photolithography stepping machine

    Energy Technology Data Exchange (ETDEWEB)

    Hale, L.; Klingmann, J. [Lawrence Livermore National Lab., CA (United States); Markle, D. [Ultratech Stepper Inc. (United States)

    1995-03-08

    A joint development project to design a new photolithography steeping machine capable of 150 nanometer overlay accuracy was completed by Ultratech Stepper and the Lawrence Livermore National Laboratory. The principal result of the project is a next-generation product that will strengthen the US position in step-and-repeat photolithography. The significant challenges addressed and solved in the project are the subject of this report. Design methods and new devices that have broader application to precision machine design are presented in greater detail while project specific information serves primarily as background and motivation.

  3. Energy efficient quantum machines

    Science.gov (United States)

    Abah, Obinna; Lutz, Eric

    2017-05-01

    We investigate the performance of a quantum thermal machine operating in finite time based on shortcut-to-adiabaticity techniques. We compute efficiency and power for a paradigmatic harmonic quantum Otto engine by taking the energetic cost of the shortcut driving explicitly into account. We demonstrate that shortcut-to-adiabaticity machines outperform conventional ones for fast cycles. We further derive generic upper bounds on both quantities, valid for any heat engine cycle, using the notion of quantum speed limit for driven systems. We establish that these quantum bounds are tighter than those stemming from the second law of thermodynamics.

  4. Paradigms for machine learning

    Science.gov (United States)

    Schlimmer, Jeffrey C.; Langley, Pat

    1991-01-01

    Five paradigms are described for machine learning: connectionist (neural network) methods, genetic algorithms and classifier systems, empirical methods for inducing rules and decision trees, analytic learning methods, and case-based approaches. Some dimensions are considered along with these paradigms vary in their approach to learning, and the basic methods are reviewed that are used within each framework, together with open research issues. It is argued that the similarities among the paradigms are more important than their differences, and that future work should attempt to bridge the existing boundaries. Finally, some recent developments in the field of machine learning are discussed, and their impact on both research and applications is examined.

  5. Man - Machine Communication

    CERN Document Server

    Petersen, Peter; Nielsen, Henning

    1984-01-01

    This report describes a Man-to-Machine Communication module which together with a STAC can take care of all operator inputs from the touch-screen, tracker balls and mechanical buttons. The MMC module can also contain a G64 card which could be a GPIB driver but many other G64 cards could be used. The soft-ware services the input devices and makes the results accessible from the CAMAC bus. NODAL functions for the Man Machine Communication is implemented in the STAC and in the ICC.

  6. The Machine Translation Leaderboard

    Directory of Open Access Journals (Sweden)

    Matt Post

    2014-09-01

    Full Text Available Much of an instructor's time is spent on the management and grading of homework. We present the Machine Translation Leaderboard, a platform for managing, displaying, and automatically grading homework assignments. It runs on Google App Engine, which provides hosting and user management services. Among its many features are the ability to easily define new assignments, manage submission histories, maintain a development / test set distinction, and display a leaderboard. An entirely new class can be set up in minutes with minimal configuration. It comes pre-packaged with five assignments used in a graduate course on machine translation.

  7. Refrigerating machine oil

    Energy Technology Data Exchange (ETDEWEB)

    Nozawa, K.

    1981-03-17

    Refrigerating machine oil to be filled in a sealed motorcompressor unit constituting a refrigerating cycle system including an electric refrigerator, an electric cold-storage box, a small-scaled electric refrigerating show-case, a small-scaled electric cold-storage show-case and the like, is arranged to have a specifically enhanced property, in which smaller initial driving power consumption of the sealed motor-compressor and easier supply of the predetermined amount of the refrigerating machine oil to the refrigerating system are both guaranteed even in a rather low environmental temperature condition.

  8. Machine shop basics

    CERN Document Server

    Miller, Rex

    2004-01-01

    Use the right tool the right wayHere, fully updated to include new machines and electronic/digital controls, is the ultimate guide to basic machine shop equipment and how to use it. Whether you're a professional machinist, an apprentice, a trade student, or a handy homeowner, this fully illustrated volume helps you define tools and use them properly and safely. It's packed with review questions for students, and loaded with answers you need on the job.Mark Richard Miller is a Professor and Chairman of the Industrial Technology Department at Texas A&M University in Kingsville, T

  9. Electrical machines & their applications

    CERN Document Server

    Hindmarsh, J

    1984-01-01

    A self-contained, comprehensive and unified treatment of electrical machines, including consideration of their control characteristics in both conventional and semiconductor switched circuits. This new edition has been expanded and updated to include material which reflects current thinking and practice. All references have been updated to conform to the latest national (BS) and international (IEC) recommendations and a new appendix has been added which deals more fully with the theory of permanent-magnets, recognising the growing importance of permanent-magnet machines. The text is so arra

  10. Electrical machines diagnosis

    CERN Document Server

    Trigeassou, Jean-Claude

    2013-01-01

    Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

  11. Clojure for machine learning

    CERN Document Server

    Wali, Akhil

    2014-01-01

    A book that brings out the strengths of Clojure programming that have to facilitate machine learning. Each topic is described in substantial detail, and examples and libraries in Clojure are also demonstrated.This book is intended for Clojure developers who want to explore the area of machine learning. Basic understanding of the Clojure programming language is required, but thorough acquaintance with the standard Clojure library or any libraries are not required. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.

  12. Fast rule-based bioactivity prediction using associative classification mining

    Directory of Open Access Journals (Sweden)

    Yu Pulan

    2012-11-01

    Full Text Available Abstract Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM, which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR, classification based on multiple association rules (CMAR and classification based on association rules (CBA are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB, mutagenicity and hERG (the human Ether-a-go-go-Related Gene blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM methods, and produce highly interpretable models.

  13. Fast rule-based bioactivity prediction using associative classification mining.

    Science.gov (United States)

    Yu, Pulan; Wild, David J

    2012-11-23

    Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM), which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR), classification based on multiple association rules (CMAR) and classification based on association rules (CBA) are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB), mutagenicity and hERG (the human Ether-a-go-go-Related Gene) blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM) methods, and produce highly interpretable models.

  14. Design of rotating electrical machines

    CERN Document Server

    Pyrhonen , Juha; Hrabovcova , Valeria

    2013-01-01

    In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

  15. Machine speech and speaking about machines

    Energy Technology Data Exchange (ETDEWEB)

    Nye, A. [Univ. of Wisconsin, Whitewater, WI (United States)

    1996-12-31

    Current philosophy of language prides itself on scientific status. It boasts of being no longer contaminated with queer mental entities or idealist essences. It theorizes language as programmable variants of formal semantic systems, reimaginable either as the properly epiphenomenal machine functions of computer science or the properly material neural networks of physiology. Whether or not such models properly capture the physical workings of a living human brain is a question that scientists will have to answer. I, as a philosopher, come at the problem from another direction. Does contemporary philosophical semantics, in its dominant truth-theoretic and related versions, capture actual living human thought as it is experienced, or does it instead reflect, regardless of (perhaps dubious) scientific credentials, pathology of thought, a pathology with a disturbing social history.

  16. ADAM: ADaptive Autonomous Machine

    NARCIS (Netherlands)

    van Oosten, Daan C.; Nijenhuis, Lucas F.J.; Bakkers, André; Vervoort, Wiek

    1996-01-01

    This paper describes a part of the development of an adaptive autonomous machine that is able to move in an unknown world extract knowledge out of the perceived data, has the possibility to reason, and finally has the capability to exchange experiences and knowledge with other agents. The agent is

  17. Machine Aids to Translation.

    Science.gov (United States)

    Brinkmann, Karl-Heinz

    1981-01-01

    Describes the TEAM Program System of the Siemens Language Services Department, particularly the main features of its terminology data bank. Discusses criteria to which stored terminology must conform and methods of data bank utilization. Concludes by summarizing the consequences that machine-aided translation development has had for the…

  18. Massively collaborative machine learning

    NARCIS (Netherlands)

    Rijn, van J.N.

    2016-01-01

    Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field of research that develops such techniques is called Machine Learning. Many research is devoted to develop

  19. War Machines and Ethics

    DEFF Research Database (Denmark)

    Nielsen, Thomas Galasz; Buhl, Kenneth Øhlenschlæger

    2018-01-01

    and save military lives. However, this opens up for discussions about ethical dilemmas about machines that autonomously are able to kill humans: What is an autonomous weapons system? What laws covers the use of fully autonomous weapons systems? Should it apply to International Humanitarian Law?...

  20. Turbulence and Flying Machines

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 11. Turbulence and Flying Machines. Rama Govindarajan. General Article Volume 4 Issue 11 November 1999 pp 54-62. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/004/11/0054-0062 ...

  1. Machine protection background

    OpenAIRE

    Romera Ramirez, I

    2014-01-01

    The LHC Machine Protection System needs to adapt to the Run 2 operational requirements. In addition, important upgrades and consolidations have been implemented on the MPS backbone during the first long shutdown. This paper summarizes the changes affecting Beam Interlock System (BIS), Powering Interlock System (PIC), Fast Magnet Current Change Monitors (FMCM), Quench Protection System (QPS) and Software Interlock System (SIS).

  2. Laser machining of explosives

    Science.gov (United States)

    Perry, Michael D.; Stuart, Brent C.; Banks, Paul S.; Myers, Booth R.; Sefcik, Joseph A.

    2000-01-01

    The invention consists of a method for machining (cutting, drilling, sculpting) of explosives (e.g., TNT, TATB, PETN, RDX, etc.). By using pulses of a duration in the range of 5 femtoseconds to 50 picoseconds, extremely precise and rapid machining can be achieved with essentially no heat or shock affected zone. In this method, material is removed by a nonthermal mechanism. A combination of multiphoton and collisional ionization creates a critical density plasma in a time scale much shorter than electron kinetic energy is transferred to the lattice. The resulting plasma is far from thermal equilibrium. The material is in essence converted from its initial solid-state directly into a fully ionized plasma on a time scale too short for thermal equilibrium to be established with the lattice. As a result, there is negligible heat conduction beyond the region removed resulting in negligible thermal stress or shock to the material beyond a few microns from the laser machined surface. Hydrodynamic expansion of the plasma eliminates the need for any ancillary techniques to remove material and produces extremely high quality machined surfaces. There is no detonation or deflagration of the explosive in the process and the material which is removed is rendered inert.

  3. Electrical Discharge Machining.

    Science.gov (United States)

    Montgomery, C. M.

    The manual is for use by students learning electrical discharge machining (EDM). It consists of eight units divided into several lessons, each designed to meet one of the stated objectives for the unit. The units deal with: introduction to and advantages of EDM, the EDM process, basic components of EDM, reaction between forming tool and workpiece,…

  4. History of wood machining

    Science.gov (United States)

    Peter Koch

    1967-01-01

    The history of wood machining is closely tied to advanced in metallurgy and power sources. It has been strongly and continuously shaped by prevailing economic forces and the rise and decline of other contemporary industries. This paper sketches a few of the highlights, with emphasis on developments in North America.

  5. Financial heat machine

    Science.gov (United States)

    Khrennikov, Andrei

    2005-05-01

    We consider dynamics of financial markets as dynamics of expectations and discuss such a dynamics from the point of view of phenomenological thermodynamics. We describe a financial Carnot cycle and the financial analog of a heat machine. We see, that while in physics a perpetuum mobile is absolutely impossible, in economics such mobile may exist under some conditions.

  6. Of machines and men ...

    CERN Multimedia

    CERN; Daniel Boileau

    1990-01-01

    Engineering and construction at LEP. Committed work and physicists motivation to work on this type of machine. With Guido Altarelli Theory Division Physicist, Ugo Amaldi Delphi Experiment Spokesman, Oscar Barbalat Head of Industry and Technology Liaison Office, Jonathan Ellis Head of Theory Division.

  7. Making molecular machines work

    NARCIS (Netherlands)

    Browne, Wesley R.; Feringa, Ben L.

    2006-01-01

    In this review we chart recent advances in what is at once an old and very new field of endeavour the achievement of control of motion at the molecular level including solid-state and surface-mounted rotors, and its natural progression to the development of synthetic molecular machines. Besides a

  8. Hybrid machining processes perspectives on machining and finishing

    CERN Document Server

    Gupta, Kapil; Laubscher, R F

    2016-01-01

    This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

  9. Recent Advances on Permanent Magnet Machines

    Institute of Scientific and Technical Information of China (English)

    诸自强

    2012-01-01

    This paper overviews advances on permanent magnet(PM) brushless machines over last 30 years,with particular reference to new and novel machine topologies.These include current states and trends for surface-mounted and interior PM machines,electrically and mechanically adjusted variable flux PM machines including memory machine,hybrid PM machines which uniquely integrate PM technology into induction machines,switched and synchronous reluctance machines and wound field machines,Halbach PM machines,dual-rotor PM machines,and magnetically geared PM machines,etc.The paper highlights their features and applications to various market sectors.

  10. Progress in Documentation: Machine Translation and Machine-Aided Translation.

    Science.gov (United States)

    Hutchins, W. J.

    1978-01-01

    Discusses the prospects for fully automatic machine translation of good quality. Sections include history and background, operational and experimental machine translation systems of recent years, descriptions of interactive systems and machine-assisted translation, and a general survey of present problems and future possibilities. (VT)

  11. Visual measurement system for roadheaders pose detection in mines

    Science.gov (United States)

    Du, Yuxin; Tong, Minming; Liu, Ting; Dong, Haibo

    2016-10-01

    To satisfy the demand for automatic roadway drivage in mines, a real-time body pose detection system is proposed for the mine-used boom-type roadheader. Utilizing cross lasers and laser targets as information sources, this system first establishes a mathematical model to describe the machine position in space and realizes the precise localization of reference points on targets via the improved Retinex adaptive image enhancement algorithm and maximum wavelet transform module algorithm. It then sets up the machine body position calculating model and makes use of the space matrix transformation method to obtain the yaw, pitch, roll angles, and horizontal and vertical deviations of the roadheader, finally fulfilling the automatic machine pose detection in real time. Based on the preceding theoretical analysis, an experimental platform is built up in laboratory conditions for the purpose of simulating pose changes of the machine inside the tunnel and automatically detecting its position. The experimental results show that the measurement accuracy of angles is within 0.16 deg and the detection precision of displacements is higher than 10 mm, which can satisfy requirements of automatic, precise, and real-time positioning for the roadheader during the process of tunnel construction.

  12. String Mining in Bioinformatics

    Science.gov (United States)

    Abouelhoda, Mohamed; Ghanem, Moustafa

    Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

  13. New Applications of Learning Machines

    DEFF Research Database (Denmark)

    Larsen, Jan

    * Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection......* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection...

  14. Intelligent Mining Engineering Systems in the Structure of Industry 4.0

    Directory of Open Access Journals (Sweden)

    Rylnikova Marina

    2017-01-01

    Full Text Available 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.

  15. Intelligent Mining Engineering Systems in the Structure of Industry 4.0

    Science.gov (United States)

    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.

  16. Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier

    Directory of Open Access Journals (Sweden)

    C. V. Subbulakshmi

    2015-01-01

    Full Text Available Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning paradigm. This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO algorithm with the extreme learning machine (ELM classifier. As a recent off-line learning method, ELM is a single-hidden layer feedforward neural network (FFNN, proved to be an excellent classifier with large number of hidden layer neurons. In this research, PSO is used to determine the optimum set of parameters for the ELM, thus reducing the number of hidden layer neurons, and it further improves the network generalization performance. The proposed method is experimented on five benchmarked datasets of the UCI Machine Learning Repository for handling medical dataset classification. Simulation results show that the proposed approach is able to achieve good generalization performance, compared to the results of other classifiers.

  17. Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier.

    Science.gov (United States)

    Subbulakshmi, C V; Deepa, S N

    2015-01-01

    Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning paradigm. This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. As a recent off-line learning method, ELM is a single-hidden layer feedforward neural network (FFNN), proved to be an excellent classifier with large number of hidden layer neurons. In this research, PSO is used to determine the optimum set of parameters for the ELM, thus reducing the number of hidden layer neurons, and it further improves the network generalization performance. The proposed method is experimented on five benchmarked datasets of the UCI Machine Learning Repository for handling medical dataset classification. Simulation results show that the proposed approach is able to achieve good generalization performance, compared to the results of other classifiers.

  18. New developments in machining technologies

    OpenAIRE

    Blau, Peter; Hochmuth, Carsten; Busch, Katja; Stoll, Andrea

    2015-01-01

    Resource conservation is continuing to be a main task of society. It requires an increase in resource efficiency in production processes as well as during product operations. The challenges for mechanical machining rise due to trends of difficult-to-machine materials and improved qualities of components and surfaces. This contribution presents new developments of production technology. The focus lies on new machine concepts, including monitoring and simulation of machining processes, resultin...

  19. Machine Translation Effect on Communication

    DEFF Research Database (Denmark)

    Jensen, Mika Yasuoka; Bjørn, Pernille

    2011-01-01

    Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...

  20. The ethics of machine translation

    OpenAIRE

    Kenny, Dorothy

    2011-01-01

    In this paper I first describe the two main branches in machine translation research. I then go to discuss why the second of these, statistical machine translation, can cause some malaise among translation scholars. As some of the issues that arise are ethical in nature, I stop to ponder what an ethics of machine translation might involve, before considering the ethical stance adopted by some of the main protagonists in the development and popularisation of statistical machine translation, an...

  1. Data mining methods

    CERN Document Server

    Chattamvelli, Rajan

    2015-01-01

    DATA MINING METHODS, Second Edition discusses both theoretical foundation and practical applications of datamining in a web field including banking, e-commerce, medicine, engineering and management. This book starts byintroducing data and information, basic data type, data category and applications of data mining. The second chapterbriefly reviews data visualization technology and importance in data mining. Fundamentals of probability and statisticsare discussed in chapter 3, and novel algorithm for sample covariants are derived. The next two chapters give an indepthand useful discussion of data warehousing and OLAP. Decision trees are clearly explained and a new tabularmethod for decision tree building is discussed. The chapter on association rules discusses popular algorithms andcompares various algorithms in summary table form. An interesting application of genetic algorithm is introduced inthe next chapter. Foundations of neural networks are built from scratch and the back propagation algorithm is derived...

  2. Journey from Data Mining to Web Mining to Big Data

    OpenAIRE

    Gupta, Richa

    2014-01-01

    This paper describes the journey of big data starting from data mining to web mining to big data. It discusses each of this method in brief and also provides their applications. It states the importance of mining big data today using fast and novel approaches.

  3. Integrated mining and land reclamation planning

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-12-31

    The course was designed to explore: mine land development and start-up operations; impact of changes in mining laws and land use; successful mine planning and reclamation operations; opportunities for financing mining and reclamation projects; cost-effective water pollution control in mining; developing successful integrated mining and land reclamation; achieving a balance between mining reclamation and land use planning; and reclamation and land re-use opportunities - benefits to local communities and mining companies.

  4. Nine Universal Circular Post Machines

    Directory of Open Access Journals (Sweden)

    Artiom Alhazov

    2002-11-01

    Full Text Available We consider a new kind of computational device like Turing machine, so-called circular Post machines with a circular tape and moving in one direction only, introduced recently by the second and the third authors. Using 2-tag systems we construct new nine small universal machines of this kind.

  5. The Neural Support Vector Machine

    NARCIS (Netherlands)

    Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus

    2013-01-01

    This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a

  6. Soda pop vending machine injuries.

    Science.gov (United States)

    Cosio, M Q

    1988-11-11

    Fifteen male patients, 15 to 24 years of age, sustained injuries after rocking soda machines. The machines fell onto the victims, resulting in a variety of injuries. Three were killed. The remaining 12 required hospitalization for their injuries. Unless changes are made to safeguard these machines, people will continue to suffer severe and possibly fatal injuries from what are largely preventable accidents.

  7. Mining and the African Environment

    National Research Council Canada - National Science Library

    Edwards, David P; Sloan, Sean; Weng, Lingfei; Dirks, Paul; Sayer, Jeffrey; Laurance, William F

    2014-01-01

    Africa is on the verge of a mining boom. We review the environmental threats from African mining development, including habitat alteration, infrastructure expansion, human migration, bushmeat hunting, corruption, and weak governance...

  8. Databases for Data Mining

    OpenAIRE

    LANGOF, LADO

    2015-01-01

    This work is about looking for synergies between data mining tools and databa\\-se management systems (DBMS). Imagine a situation where we need to solve an analytical problem using data that are too large to be processed solely inside the main physical memory and at the same time too small to put data warehouse or distributed analytical system in place. The target area is therefore a single personal computer that is used to solve data mining problems. We are looking for tools that allows us to...

  9. Data mining for dummies

    CERN Document Server

    Brown, Meta S

    2014-01-01

    Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business''s entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn''t take a data scientist to gain

  10. Application of Machine Learning for Dragline Failure Prediction

    Directory of Open Access Journals (Sweden)

    Taghizadeh Amir

    2017-01-01

    Full Text Available Overburden stripping in open cast coal mines is extensively carried out by walking draglines. Draglines’ unavailability and unexpected failures result in delayed productions and increased maintenance and operating costs. Therefore, achieving high availability of draglines plays a crucial role for increasing economic feasibility of mining projects. Applications of methodologies which can forecast the failure type of dragline based on the available failure data not only help to reduce the maintenance and operating costs but also increase the availability and the production rate. In this study, Machine Learning approaches have been applied for data which has been gathered from an operating coal mine in Turkey. The study methodology consists of three algorithms as: i implementation of K-Nearest Neighbors, ii implementation of Multi-Layer Perceptron, and iii implementation of Radial Basis Function. The algorithms have been utilized for predicting the draglines’ failure types. In this sense, the input data, which are mean time-to-failure, and the output data, failure types, have been fed to the algorithms. The regression analysis of methodologies have been compared and showed the K- Nearest Neighbors has a higher rate of regression which is around 70 percent. Thus, the K-Nearest Neighbor algorithm can be applied in order to preventive components replacement which causes to minimized preventive and corrective cost parameters. The accurate prediction of failure type, indeed, causes to optimized number of inspections. The novelty of this study is application of machine learning approaches in draglines’ reliability subject for first time.

  11. A STUDY OF TEXT MINING METHODS, APPLICATIONS,AND TECHNIQUES

    OpenAIRE

    R. Rajamani*1 & S. Saranya2

    2017-01-01

    Data mining is used to extract useful information from the large amount of data. It is used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. Text mining also referred to text of data mining, it is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. T...

  12. Comparative Opinion Mining: A Review

    OpenAIRE

    Varathan, Kasturi Dewi; Giachanou, Anastasia; Crestani, Fabio

    2017-01-01

    Opinion mining refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in textual material. Opinion mining, also known as sentiment analysis, has received a lot of attention in recent times, as it provides a number of tools to analyse the public opinion on a number of different topics. Comparative opinion mining is a subfield of opinion mining that deals with identifying and extracting information that is exp...

  13. 30 CFR 75.1200 - Mine map.

    Science.gov (United States)

    2010-07-01

    ... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Maps § 75.1200 Mine map. The operator of a coal mine shall have...) Mines above or below; (j) Water pools above; and (k) Either producing or abandoned oil and gas wells...

  14. 30 CFR 75.373 - Reopening mines.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Reopening mines. 75.373 Section 75.373 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.373 Reopening mines. After a mine is abandoned...

  15. 30 CFR 77.1200 - Mine map.

    Science.gov (United States)

    2010-07-01

    ... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Maps § 77.1200 Mine...) Either producing or abandoned oil and gas wells located on the mine property; (f) The location and...

  16. Studies in Frequent Tree Mining

    NARCIS (Netherlands)

    de Knijf, J.|info:eu-repo/dai/nl/30483551X

    2008-01-01

    Employing Data mining techniques for structured data is particularly challenging, because it is commonly assumed that the structure of the data encodes part of its semantics. As a result are classical data mining techniques insufficient to analyze and mine these data. In this thesis we develop

  17. Introduction to Machine Protection

    CERN Document Server

    Schmidt, R

    2016-01-01

    Protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent, although there was one paper that discussed beam-induced damage for the SLAC linac (Stanford Linear Accelerator Center) as early as in 1967. It is related to the increasing beam power of high-power proton accelerators, to the emission of synchrotron light by electron-positron accelerators and to the increase of energy stored in the beam. Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping ...

  18. Machine Translation from Text

    Science.gov (United States)

    Habash, Nizar; Olive, Joseph; Christianson, Caitlin; McCary, John

    Machine translation (MT) from text, the topic of this chapter, is perhaps the heart of the GALE project. Beyond being a well defined application that stands on its own, MT from text is the link between the automatic speech recognition component and the distillation component. The focus of MT in GALE is on translating from Arabic or Chinese to English. The three languages represent a wide range of linguistic diversity and make the GALE MT task rather challenging and exciting.

  19. Superluminal Signaling and Time Machine

    CERN Document Server

    Shan Gao

    2003-01-01

    Recently, time machine becomes a hot topic in the physics community[1-7]. But it is still unclear whether or not time machine does exist. In this short paper, we will analyze the possible relation between superluminal signaling and time machine. It will be shown that the realization of superluminal signaling will exclude the existence of time machine, or vice versa. Furthermore, we denote that the usual proof for the possible existence of time machine may fail due to ignoring the limitation of relativity.

  20. Introduction: Minds, Bodies, Machines

    Directory of Open Access Journals (Sweden)

    Deirdre Coleman

    2008-10-01

    Full Text Available This issue of 19 brings together a selection of essays from an interdisciplinary conference on 'Minds, Bodies, Machines' convened last year by Birkbeck's Centre for Nineteenth-Century Studies, University of London, in partnership with the English programme, University of Melbourne and software developers Constraint Technologies International (CTI. The conference explored the relationship between minds, bodies and machines in the long nineteenth century, with a view to understanding the history of our technology-driven, post-human visions. It is in the nineteenth century that the relationship between the human and the machine under post-industrial capitalism becomes a pervasive theme. From Blake on the mills of the mind by which we are enslaved, to Carlyle's and Arnold's denunciation of the machinery of modern life, from Dickens's sooty fictional locomotive Mr Pancks, who 'snorted and sniffed and puffed and blew, like a little labouring steam-engine', and 'shot out […]cinders of principles, as if it were done by mechanical revolvency', to the alienated historical body of the late-nineteenth-century factory worker under Taylorization, whose movements and gestures were timed, regulated and rationalised to maximize efficiency; we find a cultural preoccupation with the mechanisation of the nineteenth-century human body that uncannily resonates with modern dreams and anxieties around technologies of the human.

  1. Behind the machines

    CERN Multimedia

    Laëtitia Pedroso

    2010-01-01

    One of the first things we think about when someone mentions physics is the machines. But behind the machines, there are the men and women who design, build and operate them. In an exhibition at the Thinktank planetarium’s art gallery in Birmingham (UK), Claudia Marcelloni and her husband Neal Hartman—she is a photographer and Outreach Officer for ATLAS, while he is an engineer working on the ATLAS pixel detector—explore the human side of scientists.   The exhibition at the Thinktank Planetarium art gallery, Birmingham (UK). It all began two years ago with the publication of Exploring the mystery of matter, a book about ATLAS. “A Norwegian physicist friend, Heidi Sandaker, saw my photographs and suggested that I display them in a museum. I thought this was an interesting idea, except that the photos consisted entirely of depictions of machinery, with human beings completely absent. For me, showing the people who are behind the machines and the fascination ...

  2. Structural Minimax Probability Machine.

    Science.gov (United States)

    Gu, Bin; Sun, Xingming; Sheng, Victor S

    2017-07-01

    Minimax probability machine (MPM) is an interesting discriminative classifier based on generative prior knowledge. It can directly estimate the probabilistic accuracy bound by minimizing the maximum probability of misclassification. The structural information of data is an effective way to represent prior knowledge, and has been found to be vital for designing classifiers in real-world problems. However, MPM only considers the prior probability distribution of each class with a given mean and covariance matrix, which does not efficiently exploit the structural information of data. In this paper, we use two finite mixture models to capture the structural information of the data from binary classification. For each subdistribution in a finite mixture model, only its mean and covariance matrix are assumed to be known. Based on the finite mixture models, we propose a structural MPM (SMPM). SMPM can be solved effectively by a sequence of the second-order cone programming problems. Moreover, we extend a linear model of SMPM to a nonlinear model by exploiting kernelization techniques. We also show that the SMPM can be interpreted as a large margin classifier and can be transformed to support vector machine and maxi-min margin machine under certain special conditions. Experimental results on both synthetic and real-world data sets demonstrate the effectiveness of SMPM.

  3. Architectures for intelligent machines

    Science.gov (United States)

    Saridis, George N.

    1991-01-01

    The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.

  4. Machine Learning in Medicine.

    Science.gov (United States)

    Deo, Rahul C

    2015-11-17

    Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games - tasks that would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in health care. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades, and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus, part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. © 2015 American Heart Association, Inc.

  5. Throughput centered prioritization of machines in transfer lines

    Energy Technology Data Exchange (ETDEWEB)

    Pascual, R., E-mail: rpascual@ing.puc.cl [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Godoy, D. [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Louit, D.M. [Komatsu Chile S.A., Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)

    2011-10-15

    In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: > We propose a graphical technique to prioritize machines in production lines. > The tool is called 'system efficiency influence diagram' (SEID). > It helps setting prioritized maintenance policies and/or redesign of buffers. > The SEID technique focuses on system efficiency and throughput. > We illustrate its applicability using three case studies.

  6. Development of a Workbench to Address the Educational Data Mining Bottleneck

    Science.gov (United States)

    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…

  7. Evaluating a cost-effective GPS system for on-mine navigation.

    African Journals Online (AJOL)

    equipment falling into excavated areas become a reality. A single incident where a machine falls into a collapsed working can amount to in excess of R1 .... manipulation of the signal at 55ᵒ vertical and 65ᵒ horizontal into the pit. Each of the mined seams are displayed with a different colour to prevent confusion. The plans ...

  8. Text mining for traditional Chinese medical knowledge discovery: a survey.

    Science.gov (United States)

    Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

    2010-08-01

    Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

  9. CNC electrical discharge machining centers

    Energy Technology Data Exchange (ETDEWEB)

    Jaggars, S.R.

    1991-10-01

    Computer numerical control (CNC) electrical discharge machining (EDM) centers were investigated to evaluate the application and cost effectiveness of establishing this capability at Allied-Signal Inc., Kansas City Division (KCD). In line with this investigation, metal samples were designed, prepared, and machined on an existing 15-year-old EDM machine and on two current technology CNC EDM machining centers at outside vendors. The results were recorded and evaluated. The study revealed that CNC EDM centers are a capability that should be established at KCD. From the information gained, a machine specification was written and a shop was purchased and installed in the Engineering Shop. The older machine was exchanged for a new model. Additional machines were installed in the Tool Design and Fabrication and Precision Microfinishing departments. The Engineering Shop machine will be principally used for the following purposes: producing deep cavities in small corner radii, machining simulated casting models, machining difficult-to-machine materials, and polishing difficult-to-hand polish mold cavities. 2 refs., 18 figs., 3 tabs.

  10. Lunabotics Mining Competition

    Science.gov (United States)

    Mueller, Rob; Murphy, Gloria

    2010-01-01

    This slide presentation describes a competition to design a lunar robot (lunabot) that can be controlled either remotely or autonomously, isolated from the operator, and is designed to mine a lunar aggregate simulant. The competition is part of a systems engineering curriculum. The 2010 competition winners in five areas of the competition were acknowledged, and the 2011 competition was announced.

  11. Novel mining methods

    CSIR Research Space (South Africa)

    Monchusi, B

    2012-10-01

    Full Text Available 2012 Slide 12 CSIR mine safety platform AR Drone Differential time-of-flight beacon Sampling ? CSIR 2012 Slide 13 Reef Laser-Induced Breakdown Spectroscopy (LIBS) head Scan X-Y Laser/Spectrometer/Computer Rock Breaking ? CSIR 2012 Slide...

  12. Grants Mining District

    Science.gov (United States)

    The Grants Mineral Belt was the focus of uranium extraction and production activities from the 1950s until the late 1990s. EPA is working with state, local, and federal partners to assess and address health risks and environmental effects of the mines

  13. Mining water governance

    NARCIS (Netherlands)

    Sosa Landeo, Milagros

    2017-01-01

    This thesis documents as well as questions how the presence of large mining operations in Andean regions of Peru alters social and natural landscapes. Taking conflicts over water as a useful entry-point for the analysis, it explores and unravels the dilemmas and challenges faced by the main

  14. Contextual Text Mining

    Science.gov (United States)

    Mei, Qiaozhu

    2009-01-01

    With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…

  15. Mining Together : Large-Scale Mining Meets Artisanal Mining, A Guide for Action

    OpenAIRE

    World Bank

    2009-01-01

    The present guide mining together-when large-scale mining meets artisanal mining is an important step to better understanding the conflict dynamics and underlying issues between large-scale and small-scale mining. This guide for action not only points to some of the challenges that both parties need to deal with in order to build a more constructive relationship, but most importantly it sh...

  16. Mechanical design of machine components

    CERN Document Server

    Ugural, Ansel C

    2015-01-01

    Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

  17. Soft computing in machine learning

    CERN Document Server

    Park, Jooyoung; Inoue, Atsushi

    2014-01-01

    As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

  18. Energy transfer during the hydroentanglement of fibres

    CSIR Research Space (South Africa)

    Moyo, D

    2012-10-01

    Full Text Available , and the resultant degree of fibre entanglement, determines the tensile strength of the nonwoven fabric as a consequence of the inter-fibre friction. Here, the relationship between hydroentangling energy from the waterjets and the changes it brings about... in the nonwoven fabric strength were studied. In the study, the energies of the waterjets transferred to every fabric sample as a function of the waterjet pressure, machine speed, machine efficiency and the web area weight were quantified, and the resultant...

  19. Multisource causal data mining

    Science.gov (United States)

    Woodley, Robert; Gosnell, Michael; Shallenberger, Kevin

    2012-06-01

    Analysts are faced with mountains of data, and finding that relevant piece of information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal relationships across multiple data sets are sorely needed. 21st Century Systems, Inc. (21CSi) has initiated research called Causal-View, a causal datamining visualization tool, to address this challenge. Causal-View is built on an agent-enabled framework. Much of the processing that Causal-View will do is in the background. When a user requests information, Data Extraction Agents launch to gather information. This initial search is a raw, Monte Carlo type search designed to gather everything available that may have relevance to an individual, location, associations, and more. This data is then processed by Data- Mining Agents. The Data-Mining Agents are driven by user supplied feature parameters. If the analyst is looking to see if the individual frequents a known haven for insurgents he may request information on his last known locations. Or, if the analyst is trying to see if there is a pattern in the individual's contacts, the mining agent can be instructed with the type and relevance of the information fields to look at. The same data is extracted from the database, but the Data Mining Agents customize the feature set to determine causal relationships the user is interested in. At this point, a Hypothesis Generation and Data Reasoning Agents take over to form conditional hypotheses about the data and pare the data, respectively. The newly formed information is then published to the agent communication backbone of Causal- View to be displayed. Causal-View provides causal analysis tools to fill the gaps in the causal chain. We present here the Causal-View concept, the initial research into data mining tools that assist in forming the causal relationships, and our initial findings.

  20. MineWolf Tiller Test and Evaluation

    Science.gov (United States)

    2007-11-01

    Croatie ont conduit ces essais en coopération. Le projet a été conduit conformément à la méthodologie spécifiée par « l’Accord du groupe de travail ... travail 15044 du CEN; essais et évaluation de machines de déminage » et a eu lieu en septembre 2006, au Centre antimines Croate (CROMAC), près de...interchangeable selon les conditions. Les ressources étant limitées, on a seulement évalué le sarcleur attelé au MineWolf. On a utilisé trois sols différents