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

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Installation of roof support using mining... Roof Support § 75.205 Installation of roof support using mining machines with integral roof bolters. When roof bolts are installed by a continuous mining machine with intregal roof bolting equipment: (a...

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.

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...

Mining the Kepler Data using Machine Learning

Science.gov (United States)

Walkowicz, Lucianne; Howe, A. R.; Nayar, R.; Turner, E. L.; Scargle, J.; Meadows, V.; Zee, A.

2014-01-01

Kepler's high cadence and incredible precision has provided an unprecedented view into stars and their planetary companions, revealing both expected and novel phenomena and systems. Due to the large number of Kepler lightcurves, the discovery of novel phenomena in particular has often been serendipitous in the course of searching for known forms of variability (for example, the discovery of the doubly pulsating elliptical binary KOI-54, originally identified by the transiting planet search pipeline). In this talk, we discuss progress on mining the Kepler data through both supervised and unsupervised machine learning, intended to both systematically search the Kepler lightcurves for rare or anomalous variability, and to create a variability catalog for community use. Mining the dataset in this way also allows for a quantitative identification of anomalous variability, and so may also be used as a signal-agnostic form of optical SETI. As the Kepler data are exceptionally rich, they provide an interesting counterpoint to machine learning efforts typically performed on sparser and/or noisier survey data, and will inform similar characterization carried out on future survey datasets.

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

Science.gov (United States)

Ruff, Todd; Coleman, Patrick; Martini, Laura

2011-03-01

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

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

Oil sands mine pit wall design and performance at Syncrude

Energy Technology Data Exchange (ETDEWEB)

Cameron, R.; Danku, M; Purhar, G. [Syncrude Canada Ltd., Fort McMurray, AB (Canada)

2008-07-01

This study conducted slope stability analyses in order to compare pit performance at an oil sands mine with results from computerized simulations using conventionally known soil parameters. Ranges included fully-drained to fully-saturated piezometric conditions; full-peak strength conditions; fully-softened peak conditions; residual shear strength conditions; and undrained shear strength considerations. Pit wall designs were reviewed and a history of marine clay layers at the mine was presented. Assumed overburden fall-down limits were considered. Shovel overburden slope angles were calculated. An analysis of the review suggested that steeper pit walls provide less room for error and have a higher rate of failures. Incised pleistocene channels, joint and fracture areas as well as higher piezometric level areas also impacted on slope performance. Failed areas influenced ore volumes and led to productivity reductions below 50 per cent. It was concluded that the overburden portions of the oil sands mine ranged between 4H:1V to 5H:1V due to haul roads and the timing of top-bench pushbacks. Future plans for the mine must consider ore inventories, haul road requirements; running surface requirements; and ramping accesses. Future slopes at the oil sands mine will be buttressed with overburden and tailings storage areas, while longer-term slopes will be flattened. 6 refs., 2 tabs., 11 figs.

Operational analysis of the tailings bund wall drainage system at mirny ore mining and processing enterprise

Directory of Open Access Journals (Sweden)

Aniskin Nikolay Alekseevich

2016-12-01

Full Text Available Issues of environmental safety of tailings of ore mining and processing enterprises are considered; parameters of drainage of bund walls are of great significance for the environmental safety. Description of the bund wall of Mirny ore mining and processing enterprise and the tailings filling layouts are given. Results of field observation and model study of the tailings bund wall drainage system at Mirny ore mining and processing enterprise are presented. The drainage system rebuilding project analysis was performed. Proposals for its improvement were set forward.

Mineral mining machines

Energy Technology Data Exchange (ETDEWEB)

Mc Gaw, B H

1984-01-01

A machine for mining minerals is patented. It is a cutter loader with a drum actuating element of the worm type equipped with a multitude of cutting teeth reinforced with tungsten carbide. A feature of the patented machine is that all of the cutting teeth and holders on the drum have the identical design. This is achieved through selecting a slant angle for the cutting teeth which is the mean between the slant angle of the conventional radial teeth and the slant angle of the advance teeth. This, in turn, is provided thanks to the corresponding slant of the holders relative to the drum and (or) the slant of the cutting part of the teeth relative to their stems. Thus, the advance teeth projecting beyond the surface of the drum on the face side and providing upper and lateral clearances have the same angle of attack as the radial teeth, that is, from 20 to 35 degrees. A series of modifications of the cutting teeth is patented. One of the designs allows the cutting tooth to occupy a varying position relative to the drum, from the conventional vertical to an inverted, axially projecting position. In the last case the tooth in the extraction process provides the upper and lateral clearances for the drum on the face side. Among the different modifications of the cutting teeth, a design is proposed which provides for the presence of a stem which is shaped like a truncated cone. This particular stem is designed for use jointly with a wedge which unfastens the teeth and is placed in a holder. The latter is completed in a transverse slot thanks to which the rear end of the stem is compressed, which simplifies replacement of a tooth. Channels are provided in the patented machine for feeding water to the worm spiral, the holders and the cutting teeth themselves in order to deal with dust.

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.

Development of the cutting machine for the biological shield wall

International Nuclear Information System (INIS)

Yokota, Mitsuo; Hasegawa, Tetsuo; Kohyama, Kazunori.

1987-01-01

22 years have passed since the first commercial nuclear power plant operation in Japan. At present, there were 33 commercial nuclear power plants in operation, supplying about 25 percent of total electricity. Some of them are going to be terminated in the near future and enter into the decommissioning stage. Therefore, it is now necessary to developed decommissioning technologies, including dismantling techniques of these power plants. The development of a concrete cutting machine is one of the most important items applicable to dismantling biological shield walls of the plants. This paper describes the outline of the cutting machine developed for the biological shield wall demolition of the Japan Power Demonstration Reactor (JPDR) including actual decommissioning works tested. (author)

PERMEABLE TREATMENT WALL EFFECTIVENESS MONITORING PROJECT, NEVADA STEWART MINE

Science.gov (United States)

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

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.

Tritium decontamination of machine components and walls

International Nuclear Information System (INIS)

Hircq, B.; Wong, K.Y.; Jalbert, R.A.; Shmayda, W.T.

1991-01-01

Tritium decontamination techniques for machine components and their application at tritium handling facilities are reviewed. These include commonly used methods such as vacuuming, purging, thermal desorption and isotopic exchange as well as less common methods such as chemical/electrochemical etching, plasma discharge cleaning, and destructive methods. Problems associated with tritium contamination of walls and use of protective coatings are reviewed. Tritium decontamination considerations at fusion facilities are discussed

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

Methods and means for the in-house training of mining machine operators

Directory of Open Access Journals (Sweden)

Velikanov Vladimir

2017-01-01

Full Text Available This study investigates the quality issue of the in-house training process for mining machine operators. The authors prove the urgency of the designated problem. The changes in modern society, as well as the development of science and technology have a direct impact on the vocational education system. This paper describes the main aspects of the in-house training process of mining machine operators; define the essence, structure, contents, and main directions of its revitalization. The following solutions are proposed in order to improve the quality of the in-house training process: to use the original method based on a rating system of the operator knowledge evaluation, active and interactive forms of using modern training technologies. The authors conducted testing techniques in mining enterprises with the aim of confirming the adequacy of the suggested approaches. The results are given in the work. It was proposed that the methods and tools integration has a positive impact on professional training system.

Behaviour of Masonry Walls under Horizontal Shear in Mining Areas

Science.gov (United States)

Kadela, Marta; Bartoszek, Marek; Fedorowicz, Jan

2017-12-01

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

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.

A mineral quantification method for wall rocks at open pit mines, and application to the Martha Au-Ag mine, Waihi, New Zealand

International Nuclear Information System (INIS)

Castendyk, Devin N.; Mauk, Jeffrey L.; Webster, Jenny G.

2005-01-01

Pit lakes that result from open pit mining are potential water resources or potential environmental problems, depending on lake water quality. Wall rock mineralogy can affect lake chemistry if surface water inputs and/or groundwater inputs and/or lake water in contact with submerged wall rocks react with the wall rock minerals. This study presents a mineral quantification method to measure the distribution and concentration of wall rock minerals in open pit mines, and applies the method to the Martha epithermal Au-Ag mine, Waihi, New Zealand. Heterogeneous ore deposits, like Martha, require a large number of wall rock samples to accurately define mineral distributions. X-ray diffraction analyses of 125 wall rock samples identified the most abundant minerals in the wall rocks as quartz, adularia, albite, illite, chlorite, kaolinite, pyrite and calcite. Distribution maps of these minerals defined 8 relatively homogenous areas of wall rock referred to as 'mineral associations': weakly-altered, propylitic, fresh-argillic, weathered-argillic, oxidized, potassic, quartz veins, and post-mineralization deposits. X-ray fluorescence, Leco furnace, and neutron activation analyses of 46 representative samples produced the geochemical dataset used to assign quantities of elements to observed minerals, and to calculate average mineral concentrations in each association. Thin-section petrography and calcite concentrations from Sobek acid-digestions confirm the calculated mineralogy, providing validation for the method. Calcite and pyrite concentrations allowed advanced acid-base accounting for each mineral association, identifying 3 potential acid-producing associations and one potential acid-neutralizing association. The results target areas, where detailed hydrologic and kinetic tests would be valuable in the next stage of pit lake evaluation. Detailed understanding of wall rock mineralogy will help strengthen predictions of pit lake water quality

A mineral quantification method for wall rocks at open pit mines, and application to the Martha Au-Ag mine, Waihi, New Zealand

Energy Technology Data Exchange (ETDEWEB)

Castendyk, Devin N. [Environmental Science, SGES, University of Auckland, Tamaki Campus, Private Bag 92019, Auckland (New Zealand)]. E-mail: d.castendyk@auckland.ac.nz; Mauk, Jeffrey L. [Geology Department, University of Auckland, Private Bag 92019, Auckland (New Zealand); Webster, Jenny G. [Environmental Science, SGES, University of Auckland, Tamaki Campus, Private Bag 92019, Auckland (New Zealand)

2005-01-01

Pit lakes that result from open pit mining are potential water resources or potential environmental problems, depending on lake water quality. Wall rock mineralogy can affect lake chemistry if surface water inputs and/or groundwater inputs and/or lake water in contact with submerged wall rocks react with the wall rock minerals. This study presents a mineral quantification method to measure the distribution and concentration of wall rock minerals in open pit mines, and applies the method to the Martha epithermal Au-Ag mine, Waihi, New Zealand. Heterogeneous ore deposits, like Martha, require a large number of wall rock samples to accurately define mineral distributions. X-ray diffraction analyses of 125 wall rock samples identified the most abundant minerals in the wall rocks as quartz, adularia, albite, illite, chlorite, kaolinite, pyrite and calcite. Distribution maps of these minerals defined 8 relatively homogenous areas of wall rock referred to as 'mineral associations': weakly-altered, propylitic, fresh-argillic, weathered-argillic, oxidized, potassic, quartz veins, and post-mineralization deposits. X-ray fluorescence, Leco furnace, and neutron activation analyses of 46 representative samples produced the geochemical dataset used to assign quantities of elements to observed minerals, and to calculate average mineral concentrations in each association. Thin-section petrography and calcite concentrations from Sobek acid-digestions confirm the calculated mineralogy, providing validation for the method. Calcite and pyrite concentrations allowed advanced acid-base accounting for each mineral association, identifying 3 potential acid-producing associations and one potential acid-neutralizing association. The results target areas, where detailed hydrologic and kinetic tests would be valuable in the next stage of pit lake evaluation. Detailed understanding of wall rock mineralogy will help strengthen predictions of pit lake water quality.

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

Science.gov (United States)

Wang, Zhe; Shen, Hongbing

2018-04-01

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

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

Science.gov (United States)

Luo, Gang

2017-01-01

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

Mine drivage in hydraulic mines

Energy Technology Data Exchange (ETDEWEB)

Ehkber, B Ya

1983-09-01

From 20 to 25% of labor cost in hydraulic coal mines falls on mine drivage. Range of mine drivage is high due to the large number of shortwalls mined by hydraulic monitors. Reducing mining cost in hydraulic mines depends on lowering drivage cost by use of new drivage systems or by increasing efficiency of drivage systems used at present. The following drivage methods used in hydraulic mines are compared: heading machines with hydraulic haulage of cut rocks and coal, hydraulic monitors with hydraulic haulage, drilling and blasting with hydraulic haulage of blasted rocks. Mining and geologic conditions which influence selection of the optimum mine drivage system are analyzed. Standardized cross sections of mine roadways driven by the 3 methods are shown in schemes. Support systems used in mine roadways are compared: timber supports, roof bolts, roof bolts with steel elements, and roadways driven in rocks without a support system. Heading machines (K-56MG, GPKG, 4PU, PK-3M) and hydraulic monitors (GMDTs-3M, 12GD-2) used for mine drivage are described. Data on mine drivage in hydraulic coal mines in the Kuzbass are discussed. From 40 to 46% of roadways are driven by heading machines with hydraulic haulage and from 12 to 15% by hydraulic monitors with hydraulic haulage.

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)

Time cycle calculation procedure for the special crew during the mining mobile machine complex operation

International Nuclear Information System (INIS)

Shmurygin, V; Lukyanov, V; Maslovsky, A

2015-01-01

The relevance of the research is specified by the necessity to optimize the delft mobile tunneling equipment operation. Target of the research is tunneling time cycle justification for the special crew during the mining mobile machine complex operation. Methods of the research included the consideration of operation organization schemes in the drifting face and effective use of the mobile equipment during mine exploratory working operations. Time cycle calculation procedures for major processes have been considered. This has been done for the special crew during the mobile machine complex operations for several working faces and various organization schemes

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

Automated system of monitoring and positioning of functional units of mining technological machines for coal-mining enterprises

Directory of Open Access Journals (Sweden)

Meshcheryakov Yaroslav

2018-01-01

Full Text Available This article is show to the development of an automated monitoring and positioning system for functional nodes of mining technological machines. It describes the structure, element base, algorithms for identifying the operating states of a walking excavator; various types of errors in the functioning of microelectromechanical gyroscopes and accelerometers, as well as methods for their correction based on the Madgwick fusion filter. The results of industrial tests of an automated monitoring and positioning system for functional units on one of the opencast coal mines of Kuzbass are presented. This work is addressed to specialists working in the fields of the development of embedded systems and control systems, radio electronics, mechatronics, and robotics.

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

OpenAIRE

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

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted reg...

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.

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

Science.gov (United States)

Prabakaran, S.; Mitra, Shilpa

2018-04-01

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

Data Mining and Machine Learning Methods for Dementia Research.

Science.gov (United States)

Li, Rui

2018-01-01

Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, and demographic variables. Given the various sources of information, we can develop computerized methods that can be a great help to clinicians to discover hidden patterns in the data. The computerized methods often employ data mining and machine learning algorithms, lending themselves as the computer-aided diagnosis (CAD) tool that assists clinicians in making diagnostic decisions. In this chapter, we review state-of-the-art methods used in dementia research, and briefly introduce some recently proposed algorithms subsequently.

Porous reactive wall for prevention of acid mine drainage: Results of a full-scale field demonstration

International Nuclear Information System (INIS)

Benner, S.G.; Blowes, D.W.; Ptacek, C.J.

1997-01-01

A porous reactive wall was installed in August, 1995, to treat mine drainage flowing within an aquifer at the Nickel Rim mine site, near Sudbury, Ontario. The reactive mixture was designed to maximize removal of metals and acid generating capacity from the groundwater by enhancing sulfate reduction and metal sulfide precipitation. The installed structure, composed of a mixed organic substrate, is 15 meters long, 3.6 meters deep and the flow path length (wall width) is 4 meters. Results of sampling nine months after installation, indicate that sulfate reduction and metal sulfide precipitation is occurring. Comparing the chemistry of water entering the wall to treated water exiting the wall nine months after installation: SO 4 concentrations decrease by >50% (from 2400-4800 mg/L to 60-3600 mg/L), Fe concentrations decrease by >95% (from 260-1300 mg/L to 1.0-40 mg/L), pH increased from 5.8 to 7.0 and alkalinity increased from 0-60 mg/L to 700-3200 mg/L as CaCO 3 . After passing through the reactive wall, the net acid generating potential of the aquifer water was converted from acid producing to acid consuming

DIAGNOSIS OF THE WINDING MACHINE IN THE OLD SHAFT WITH SKIP IN LONEA MINING PLANT

Directory of Open Access Journals (Sweden)

Răzvan Bogdan ITU

2017-05-01

Full Text Available To study the operation of the winding machine in the Old Shaft with Skip in Lonea Mining Plant, the dynamic analysis of the driving wheel (Koepe wheel was performed, by resistive electric tensometry methods, acceleration measurements, and vibromechanical analysis on the bearings of Koepe driving wheels, on functioning cycles and vibromechanical analysis of the reduction gear. The paper presents aspects regarding vibromechanical measurements and resistive electric tensometry methods in the winding machine..

A Review of Machine Learning and Data Mining Approaches for Business Applications in Social Networks

OpenAIRE

Evis Trandafili; Marenglen Biba

2013-01-01

Social networks have an outstanding marketing value and developing data mining methods for viral marketing is a hot topic in the research community. However, most social networks remain impossible to be fully analyzed and understood due to prohibiting sizes and the incapability of traditional machine learning and data mining approaches to deal with the new dimension in the learning process related to the large-scale environment where the data are produced. On one hand, the birth and evolution...

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.

Analysis of Material Removal and Surface Characteristics in Machining Multi Walled Carbon Nanotubes Filled Alumina Composites by WEDM Process

Directory of Open Access Journals (Sweden)

Annebushan Singh Meinam

2017-01-01

Full Text Available The reinforcement of ceramic materials with electrically conductive particles increases the overall conductivity of the ceramic material. This allows the ceramic material to be more readily machined using wire electrical discharge machining process. The current work is an approach to identify the machinability of multi walled carbon nanotubes filled alumina composites in wire electrical discharge machining process. Alumina samples of 5 vol. % and 10 vol. % multi walled carbon nanotubes are machined and analysed for material removal rate and the surface characteristics. An increase in material removal rate is observed with increase in filler concentrations. At the same time, better surface roughness is observed. The surface characteristics of composite alumina are further compared with Monel 400 alloy. It has been observed that spalling action is the dominating material removal mechanism for alumina composites, while melting and evaporation is for the Monel 400 alloy.

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

Science.gov (United States)

Kumar, R; Ghosh, A K

2014-01-01

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

Diagnostic measurements on the great machines conditions of lignite surface mines

Energy Technology Data Exchange (ETDEWEB)

Helebrant, F.; Jurman, J.; Fries, J. [Technical University of Ostrava, Ostrava-Poruba (Czech Republic)

2005-07-01

An analysis of the diagnosis of loading and service dependability of a rail-mounted excavator used in surface lignite mining is described. Wheel power vibrations in electric motor bearings and electric motor input bearings to the gearbox were measured in situ, in horizontal, vertical, and axial directions. The data were analyzed using a mathematical relationship. The results are presented in a loading diagram that shows the deterioration and the acceptable lower bound of machine conditions over time. Work is continuing. 5 refs., 1 fig.

Automation and robotics technology for intelligent mining systems

Science.gov (United States)

Welsh, Jeffrey H.

1989-01-01

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

Extending mine life

International Nuclear Information System (INIS)

Anon.

1984-01-01

Mine layouts, new machines and techniques, research into problem areas of ground control and so on, are highlighted in this report on extending mine life. The main resources taken into account are coal mining, uranium mining, molybdenum and gold mining

Foreword for the special issue of selected papers from the 1st ECML/PKDD Workshop on Privacy and Security issues in Data Mining and Machine Learning

OpenAIRE

Aris Gkoulalas-Divanis; Yucel Saygin; Vassilios S. Verykios

2011-01-01

The first Workshop on Privacy and Security issues in Data Mining and Machine Learning (PSDML 2010) was organized on September 24, 2010 at Barcelona, Spain, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Privacy and security-related aspects of data mining and machine learning have been the topic of active research during the last decade due to the existence of numerous applications with privacy and/or...

Summary report for IAEA CRP on lifetime prediction for the first wall of a fusion machine (JAERI contribution)

International Nuclear Information System (INIS)

Suzuki, Satoshi; Araki, Masanori; Akiba, Masato

1993-03-01

IAEA Coordinated Research Program (CRP) on 'Lifetime Prediction for the First Wall of a Fusion Machine' was started in 1989. Five participants, Joint Research Centre (JRC-Ispra), The NET team, Kernforschungszentrum Karlsruhe (KfK), Russian Research Center and Japan Atomic Energy Research Institute, contributed in this activity. The purpose of the CRP is to evaluate the thermal fatigue behavior of the first wall of a next generation fusion machine by means of numerical methods and also to contribute the design activities for ITER (International Thermonuclear Experimental Reactor). Thermal fatigue experiments of a first wall mock-up which were carried out in JRC-Ispra were selected as a first benchmark exercise model. All participants performed finite element analyses with various analytical codes to predict the lifetime of the simulated first wall. The first benchmark exercise has successfully been finished in 1992. This report summarizes a JAERI's contribution for this first benchmark exercise. (author)

Technical improvement of arch setting machine for roadway drive. Kusshin kirihayo sewakuki no hensen

Energy Technology Data Exchange (ETDEWEB)

Fujino, T [Taiheiyo Coal Mining Co. Ltd., Tokyo (Japan)

1991-09-25

The following contents are described for a new type arch setting machine introduced to the Taiheiyo Coal Mining Co. (1) The excavation of drift in this coal mine is carried out by the excavating system combining the excavating machine (CM) and the transporter (SC) and the supporting method where arch type steel beams are used as the supporting material is used. (2) In order to automatize the arch setting work, this machine which combined the both functions of the arch lifter (developed in 1983) and the arch setting manipulator (ASM, developed in 1990). (3) This machine has the total weight of 1,500kg, is mounted on CM, and consists of the running part, the arm part, the boom part, and the end saucer part of steel arches. Further, simple fitting or removing can be made and the coal falling down is prevented by holding the coal wall during the arch setting work. (4) When this machine and the ASM were compared for the arch setting time in the working site, the former required about the half time period of the latter. 5 figs., 1 tab.

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.

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.

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.

Recovery process of wall condition in KSTAR vacuum vessel after temporal machine-vent for repair

Energy Technology Data Exchange (ETDEWEB)

Kim, Kwang Pyo, E-mail: kpkim@nfri.er.ke; Hong, Suk-Ho; Lee, Hyunmyung; Song, Jae-in; Jung, Nam-Yong; Lee, Kunsu; Chu, Yong; Kim, Hakkun; Park, Kaprai; Oh, Yeong-Kook

2015-10-15

Highlights: • Efforts have been made to obtain vacuum condition that is essential for the plasma experiments. • For example, the vacuum vessel should be vented to repair in-vessel components such as diagnostic shutter, and PFC damaged by high energy plasma. • Here, we present the recovery process of wall condition in KSTAR after temporal machine-vent for repair. • It is found that an acceptable vacuum condition has been achieved only by plasma based wall conditioning techniques such as baking, GDC, and boronization. • This study was that the proper recovering method of the vacuum condition should be developed according to the severity of the accident. - Abstract: Efforts have been made to obtain vacuum condition that is essential for the plasma experiments. Under certain situations, for example, the vacuum vessel should be vented to repair in-vessel components such as diagnostic shutter, exchange of window for diagnostic equipment, and PFC damaged by high energy plasma. For the quick restart of the campaign, a recovery process was established to make the vacuum condition acceptable for the plasma experiment. In this paper, we present the recovery process of wall condition in KSTAR after temporal machine-vent for repair. It is found that an acceptable vacuum condition has been achieved only by plasma based wall conditioning techniques such as baking, GDC, and boronization. This study was that the proper recovering method of the vacuum condition should be developed according to the severity of the accident.

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.)

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.

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

Science.gov (United States)

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

2010-12-01

Long-term change detection often implies the challenge of incorporating multitemporal data from different sensors. Most of the conventional change detection algorithms are designed for bi-temporal datasets from the same sensors detecting only the existence of changes. The labeling of change areas remains a difficult task. To overcome such drawbacks, much attention has been given lately to algorithms arising from machine learning, such as Support Vector Machines (SVMs). While SVMs have been applied successfully for land cover classifications, the exploitation of this approach for change detection is still in its infancy. Few studies have already proven the applicability of SVMs for bi- and multitemporal change detection using data from one sensor only. In this paper we demonstrate the application of SVM for multitemporal and -sensor change detection. Our study site covers lignite open pit mining areas in the German state North Rhine-Westphalia. The dataset consists of bi-temporal Landsat data and multi-temporal ERS SAR data covering two time slots (2001 and 2009). The SVM is conducted using the IDL program imageSVM. Change is deduced from one time slot to the next resulting in two change maps. In contrast to change detection, which is based on post-classification comparison, change detection is seen here as a specific classification problem. Thus, changes are directly classified from a layer-stack of the two years. To reduce the number of change classes, we created a change mask using the magnitude of Change Vector Analysis (CVA). Training data were selected for different change classes (e.g. forest to mining or mining to agriculture) as well as for the no-change classes (e.g. agriculture). Subsequently, they were divided in two independent sets for training the SVMs and accuracy assessment, respectively. Our study shows the applicability of SVMs to classify changes via SVMs. The proposed method yielded a change map of reclaimed and active mines. The use of ERS SAR

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.

Recent development in the design of hard rock tunnel boring machines for the mining industry

International Nuclear Information System (INIS)

Snyder, L.L.; Williams, R.I.

1991-01-01

Underground development for nuclear waste storage will possibly require tunnels to be excavated in a variety of rock conditions and configurations. Recent innovations in Tunnel Boring Machine (TBM) design have allowed for an evolved style of TBM which has distinct advantages over the standard machines. Present day conventional hard rock TBM's were developed primarily for the long, relatively straight tunnels of the civil construction industry, thereby making them for the most part, unsuitable for the sharp curves, turnouts, declines, inclines and ramps required in many underground environments. The five foot to 36 foot (1.52 to 11 m) diameter machines are capable of boring tunnels with curve radiuses as small as 40 to 90 feet (12.2 to 27.5 m) depending on size. These short turning radiuses can be accomplished while gripping the tunnel walls horizontally in the traditional manner or vertically as required when intersecting existing tunnels, or making turnouts from the tunnel that the machine has just bored. The machine's length is approximately half of a traditional machine's length while still employing a full measure of thrust, horsepower and rock cutting ability. The machine's short length, combined with a patented machine structure allows it to steer while boring without causing harmful eccentric loads on the cutterhead and main bearing assembly. The machine configuration is versatile and can be easily modified to operate in a wide variety of conditions

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

Science.gov (United States)

Dipnall, Joanna F.

2016-01-01

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

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

Machine Learning.

Science.gov (United States)

Kirrane, Diane E.

1990-01-01

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

DIAGNOSIS OF THE WINDING MACHINE IN THE OLD SHAFT WITH SKIP IN LONEA MINING PLANT

OpenAIRE

Răzvan Bogdan ITU; Vilhelm ITU

2017-01-01

To study the operation of the winding machine in the Old Shaft with Skip in Lonea Mining Plant, the dynamic analysis of the driving wheel (Koepe wheel) was performed, by resistive electric tensometry methods, acceleration measurements, and vibromechanical analysis on the bearings of Koepe driving wheels, on functioning cycles and vibromechanical analysis of the reduction gear. The paper presents aspects regarding vibromechanical measurements and resistive electric tensometry me...

Web Mining

Science.gov (United States)

Fürnkranz, Johannes

The World-Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. This chapter provides a brief overview of web mining techniques and research areas, most notably hypertext classification, wrapper induction, recommender systems and web usage mining.

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...

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

Science.gov (United States)

Wodecki, Jacek; Michalak, Anna; Stefaniak, Paweł

2018-01-01

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

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

Analytical study on U/G coal mine CPT and inferences

Energy Technology Data Exchange (ETDEWEB)

Dey, N.C.; Mukhopadhyay, S. [Bengal Engineering College, Howrath (India). Dept. of Mining and Geology

1999-08-01

The analytical aspects of underground CPT (coal mine cost per tonne), which varies from mine to mine due to the different weightages of various contributing factors, are described. The CPT is not only dictated by the increasing wages but also by the availability of man-hour and accountability of machine utilization. An optimal blend of labour-intensive and machine-intensive methods involving least investment and operating cost, is a challenge for the coal industry. Technology upgradation and implementation, higher skill and morale, excellence in planning and monitoring, optimization in capacity utilization, and better consumer acceptability of coal will consistently improve the financial health of the coal mining sector. Other factors which will help improve the financial health of coal mining industries are (1) cost propaganda like safety week celebration; (2) cost consciousness at all levels; (3) noticeboard comprising the cost of man-hour and machine- hour; (4) no idle time for men as well as machine; (5) care to increase the life of machines; (6) scope of target amendment in a year; (7) prior to introducing costly machines, due weightage to be given on coal grade, mine life, geo-mining conditions; and (8) award to most economic mine and punishment to others rated below the BEP (break- even point). 2 refs., 3 figs.

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

Science.gov (United States)

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

2015-01-01

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

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.

Machine technology: a survey

International Nuclear Information System (INIS)

Barbier, M.M.

1981-01-01

An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

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...

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.

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

Science.gov (United States)

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

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

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

Directory of Open Access Journals (Sweden)

ByungWan Jo

2018-03-01

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

Technological and mining analysis of mechanized systems used in roadways in Polish mines

Energy Technology Data Exchange (ETDEWEB)

Sikora, W; Giza, T; Siwiec, J [Politechnika Slaska, Gliwice (Poland). Instytut Mechanizacji Gornictwa

1987-01-01

Analyzes methods of mine drivage in Poland and materials handling systems. Of 1,620 km of roadways driven in 1982, 12% fell on roadways driven in coal and 88% on roadways driven in stone or stone and coal. Roadways driven in coal in most cases were situated at depths from 500 to 700 m. Roadway cross-section ranged from 12 to 18 m{sup 2}. Roadways in stone or stone and coal were driven by drilling and blasting. Loaders were used for stone handling. Roadways in coal were driven by heading machines. Advance rates of mine drivage by heading machines were 2 to 3 times higher than those by drilling and blasting with loaders for stone handling. Basic statistical data characterizing roadways and drivage methods are evaluated: roadway dimensions and depth advance rate depending on drivage methods and mining condition, types of heading machines and loaders.

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...

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

Method of Automatic Ontology Mapping through Machine Learning and Logic Mining

Institute of Scientific and Technical Information of China (English)

王英林

2004-01-01

Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.

Proceedings. Fourth international symposium on mine mechanisation and automation

Energy Technology Data Exchange (ETDEWEB)

Gurgenci, H.; Hood, M. [eds.

1997-12-31

Papers in the first volume are presented under the following session headings: drilling; mining robotics; machine monitoring; mine automation systems; reliability and maintenance; mine automation - communications mechanical excavation of medium-strength rock; and new mining equipment technologies. The second volume covers: mechanical excavation of hard rock; autonomous vehicles; mechanical excavation industry experience; machine guidance; applications of rock mechanics, mine planning management and scheduling; orebody delineation; and safety. Selected papers have been abstracted separately for the IEA Coal Research databases available on CD-ROM and the worldwide web.

Collapse moment estimation by support vector machines for wall-thinned pipe bends and elbows

International Nuclear Information System (INIS)

Na, Man Gyun; Kim, Jin Weon; Hwang, In Joon

2007-01-01

The collapse moment due to wall-thinned defects is estimated through support vector machines with parameters optimized by a genetic algorithm. The support vector regression models are developed and applied to numerical data obtained from the finite element analysis for wall-thinned defects in piping systems. The support vector regression models are optimized by using both the data sets (training data and optimization data) prepared for training and optimization, and its performance verification is performed by using another data set (test data) different from the training data and the optimization data. In this work, three support vector regression models are developed, respectively, for three data sets divided into the three classes of extrados, intrados, and crown defects, which is because they have different characteristics. The relative root mean square (RMS) errors of the estimated collapse moment are 0.2333% for the training data, 0.5229% for the optimization data and 0.5011% for the test data. It is known from this result that the support vector regression models are sufficiently accurate to be used in the integrity evaluation of wall-thinned pipe bends and elbows

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

Science.gov (United States)

2010-07-01

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

Technological highwall mining

Energy Technology Data Exchange (ETDEWEB)

Davison, I. [Highwall Systems (United States)

2006-09-15

The paper explores the issues facing highwall mining. Based in Chilhowie, Virginia, American Highwall Systems has developed a highwall mining system that will allow the mining of coal seams from 26 in to 10 ft in thickness. The first production model, AH51, began mining in August 2006. Technologies incorporated into the company's mining machines to improve the performance, enhance the efficiency, and improve the reliability of the highwall mining equipment incorporate technologies from many disciplines. Technology as applied to design engineering, manufacturing and fabrication engineering, control and monitoring computer hardware and software has played an important role in the evolution of the American Highwall Systems design concept. 5 photos.

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

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...

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.

Pneumatic automation systems in coal mines

Energy Technology Data Exchange (ETDEWEB)

Shmatkov, N.A.; Kiklevich, Yu.N.

1981-04-01

Giprougleavtomatizatsiya, Avtomatgormash, Dongiprouglemash, VNIIGD and other plants develop 30 new pneumatic systems for mine machines and equipment control each year. The plants produce about 200 types of pneumatic systems. Major pneumatic systems for face systems, machines and equipment are reviewed: Sirena system for remote control of ANShch and AShchM face systems for steep coal seams, UPS control systems for pump stations, PAUZA control system for stowing machines, remote control system of B100-200 drilling machines, PUSK control system for coal cutter loaders with pneumatic drive (A-70, Temp), PUVSh control system for ventilation barriers activated from moving electric locomotives, PAZ control system for skip hoist loading. Specifications of the systems are given. Economic benefit produced by the pneumatic control systems are evaluated (from 1,500 to 40,000 rubles/year). Using the systems increases productivity of face machines and other machines used in black coal mines by 5 to 30%.

Case studies of slope stability radar used in coal mines

Energy Technology Data Exchange (ETDEWEB)

Noon, D. [GroundProbe Pty Ltd., South Brisbane, Qld. (Australia)

2005-07-01

This paper presents case studies about how the Slope Stability Radar (SSR) system provided adequate warning to safeguard people and equipment prior to highwall and low wall failure at two Australian coal mines. At Drayton mine, the SSR was able to provide the mine with sufficient warning to move the shovel and trucks away from the highwall, while personnel safely watched 50,000 tonnes of bulk material coming down from the wall. At Mt Owen mine, the SSR alarm allowed the mine to evacuate equipment and personnel four hours prior to a 30,000,000 tonne low wall failure. These two case studies demonstrate how the SSR system was able to continuously monitor the stability of these critical slopes, enabling greater mine productivity whilst maintaining the highest quality of safety. 2 refs., 7 figs., 1 tab.

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

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.

Engineer exchanging project on coal mine technology field in fiscal 1999. International information exchanging project (advance survey on North America); 1999 nendo gijutsusha koryu jigyo (tanko gijutsu bun'ya) kokusai koryu jigyo. Jizen chosa (Hokubei)

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-03-01

This project has been performed with an intention of making visiting surveys and information collection at coal related organizations in overseas coal producing countries on production technology levels and trends. The project is intended to serve for improvement in the contents of and smooth execution of the engineer exchange project in the 'coal mine technology field. It was carried out by the site surveys. The surveys revealed that the situation of the American coal industry is expected of stable increase in the demand and supply in the future, but the coal price is on the falling trend, and therefore, the industry is compelled to further increase the intensity and enhance the productivity. The industry is strongly influenced by the amended air pollution prevention act and nature destruction problems, hence further coal mine curtailment is estimated. Under such a background, it was found that the long-wall mining process progressing toward larger scale and higher productivity, and the high-wall mining process that provides higher productivity at lower cost and has less impact on the environmental problems can continue development in mountainous areas, particularly in the Appalachian area. The high-wall mining process mines coal at exposed facings on the side of a mountain by using a continuous miner, and transports the coal using machines. (NEDO)

Quantum Machine Learning

OpenAIRE

Romero García, Cristian

2017-01-01

[EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged to face problems in data mining, pattern recognition, automatic prediction, among others. Quantum Machine Learning is an interdisciplinary research area combining quantum mechanics with methods of ML, in which quantum properties allow fo...

Increased productivity in construction of civil and mining tunnels through the use of high-capacity tunnel-boring machines and continuous belt conveyor muck haulage

Energy Technology Data Exchange (ETDEWEB)

Beatty, J.G.; Ganey, R.J.; Killingsworth, J.E. [Perini Corp., Chicago, IL (United States). US Heavy Division

1994-12-31

The use of a large diameter high production tunnel boring machine interfaced with a high capacity continuous belt conveyor system provides a highly productive and cost effective construction system for both civil and mining tunnels. Continuous advance of the tunnel boring machine for a distance of 1,000 feet (305 m) allows for very efficient operation of the system. The available cost reductions will likely prove that this approach to waste handling will make marginally viable projects economically feasible. 9 refs., 10 figs., 1 tab.

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

Science.gov (United States)

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

2017-09-01

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

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...

A Review of Extra-Terrestrial Mining Concepts

Science.gov (United States)

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

2012-01-01

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

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).

Absorbed and effective dose from periapical radiography by portable intraoral x-ray machine

International Nuclear Information System (INIS)

Cho, Jeong Yeon; Han, Won Jeong; Kim, Eun Kyung

2007-01-01

The purpose of this study was to measure the absorbed dose and to calculate the effective dose for periapical radiography done by portable intraoral x-ray machines. 14 full mouth, upper posterior and lower posterior periapical radiographs were taken by wall-type 1 and portable type 3 intraoral x-ray machines. Thermoluminescent dosemeters were placed at 23 sites at the layers of the tissue-equivalent ART woman phantom for dosimetry. Average tissue absorbed dose and radiation weighted dose were calculated for each major anatomical site. Effective dose was calculated using 2005 ICRP tissue weighted factors. On 14 full mouth periapical radiographs, the effective dose for wall-type x-ray machine was 30 Sv; for portable x-ray machines were 30 Sv, 22 Sv, 36 Sv. On upper posterior radiograph, the effective dose for wall-type x-ray machine was 4 Sv; for portable x-ray machines doses were 4 Sv, 3 Sv, 5 Sv. On lower posterior radiograph, the effective dose for wall type x-ray machine was 5 Sv; for portable x-ray machines doses were 4 Sv, 4 Sv, 5 Sv. Effective doses for periapical radiographs performed by portable intraoral x-ray machines were similar to doses for periapical radiographs taken by wall type intraoral x-ray machines

A Comparison of the Effects of K-Anonymity on Machine Learning Algorithms

OpenAIRE

Hayden Wimmer; Loreen Powell

2014-01-01

While research has been conducted in machine learning algorithms and in privacy preserving in data mining (PPDM), a gap in the literature exists which combines the aforementioned areas to determine how PPDM affects common machine learning algorithms. The aim of this research is to narrow this literature gap by investigating how a common PPDM algorithm, K-Anonymity, affects common machine learning and data mining algorithms, namely neural networks, logistic regression, decision trees, and Baye...

Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method

Science.gov (United States)

Khandelwal, Manoj; Monjezi, M.

2013-03-01

Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.

Feasibility of introducing continuous systems in surface mines of India

Energy Technology Data Exchange (ETDEWEB)

Bordia, S K

1987-06-01

The paper presents a brief outline of the mineral types, production trends and techno-economic feasiblity associated with the possible introduction of continuous mining systems to India. Production trends are outlined for coal, limestone, bauxite, phosphate, and iron ore. Continuous mining systems described are heavy-duty bucket wheel excavators, road milling type machines and shearing type machines. 8 refs.

30 CFR 77.401 - Stationary grinding machines; protective devices.

Science.gov (United States)

2010-07-01

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

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.

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

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval of machines constructed of components... APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.95 Approval of machines constructed of components approved...

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

Science.gov (United States)

Wang, Hua

2018-02-01

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

Post-mining in France

International Nuclear Information System (INIS)

2007-01-01

This plentifully illustrated book aims at showing how new equilibria are building up during the transition between mining activity and post-mining, and at stressing on the necessity to keep up the cultural elements, the competencies and knowledge of mining works. The first chapter - mine and men - shows the importance of mineral substances in the objects of the everyday life, illustrates the importance of the mining tradition in France and describes the technical and administrative organisation of the end of the mining activity (works, rehabilitation, regulation, monitoring..). Chapter two - exploitation methods - presents the surface and underground facilities and their impact on the environment (extraction machines, workshops, ore processing plants, decantation ponds..). The third chapter deals with the rehabilitation and monitoring aspects: impact of mining activity stoppage on underground and surface waters, land stability, soils cleansing.. The last chapter summarizes the history of French mining region by region: Nord-Pas-de-Calais, Lorraine-Alsace, Massif central, Bretagne-Normandie, Provence-Alpes-Cote d'Azur and Pyrenees

Modelling open pit shovel-truck systems using the Machine Repair Model

Energy Technology Data Exchange (ETDEWEB)

Krause, A.; Musingwini, C. [CBH Resources Ltd., Sydney, NSW (Australia). Endeaver Mine

2007-08-15

Shovel-truck systems for loading and hauling material in open pit mines are now routinely analysed using simulation models or off-the-shelf simulation software packages, which can be very expensive for once-off or occasional use. The simulation models invariably produce different estimations of fleet sizes due to their differing estimations of cycle time. No single model or package can accurately estimate the required fleet size because the fleet operating parameters are characteristically random and dynamic. In order to improve confidence in sizing the fleet for a mining project, at least two estimation models should be used. This paper demonstrates that the Machine Repair Model can be modified and used as a model for estimating truck fleet size in an open pit shovel-truck system. The modified Machine Repair Model is first applied to a virtual open pit mine case study. The results compare favourably to output from other estimation models using the same input parameters for the virtual mine. The modified Machine Repair Model is further applied to an existing open pit coal operation, the Kwagga Section of Optimum Colliery as a case study. Again the results confirm those obtained from the virtual mine case study. It is concluded that the Machine Repair Model can be an affordable model compared to off-the-shelf generic software because it is easily modelled in Microsoft Excel, a software platform that most mines already use.

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...

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.

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

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval of machines assembled with certified... ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Machines Assembled With Certified or Explosion-Proof Components, Field...

A Review of Extra-Terrestrial Mining Robot Concepts

Science.gov (United States)

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

2011-01-01

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

GPK heading machine

Energy Technology Data Exchange (ETDEWEB)

Krmasek, J.; Novosad, K.

1981-01-01

This article evaluates performance tests of the Soviet made GPK heading machine carried out in 4 coal mines in Czechoslovakia (Ostrava-Karvina region and Kladno mines). GPK works in coal seams and rocks with compression strength of 40 to 50 MPa. Dimensions of the tunnel are height 1.8 to 3.8 m and width 2.6 to 4.7 m, tunnel gradient plus to minus 10 degrees. GPK weighs 16 t, its conical shaped cutting head equipped with RKS-1 cutting tools is driven by an electric motor with 55 kW capacity. Undercarriage of the GPK, gathering-arm loader, hydraulic system, electric system and dust supression system (water spraying or pneumatic section) are characterized. Specifications of GPK heading machines are compared with PK-3r and F8 heading machines. Reliability, number of failures, dust level, noise, productivity depending on compression strength of rocks, heading rate in coal and in rocks, energy consumption, performance in inclined tunnels, and cutting tool wear are evaluated. Tests show that GPK can be used to drive tunnels in coal with rock constituting up to 50% of the tunnel crosscut, as long as rock compression strength does not exceed 50 MPa. In rocks characterized by higher compression strength cutting tool wear sharply increases. GPK is characterized by higher productivity than that of the PK-3r heading machine. Among the weak points of the GPK are: unsatisfactory reliability and excessive wear of its elements. (4 refs.) (In Czech)

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

Science.gov (United States)

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

2016-11-01

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

INTEGRATED ROBOT-HUMAN CONTROL IN MINING OPERATIONS

Energy Technology Data Exchange (ETDEWEB)

George Danko

2005-04-01

This report contains a detailed description of the work conducted in the first year of the project on Integrated Robot-Human Control in Mining Operations at University of Nevada, Reno. This project combines human operator control with robotic control concepts to create a hybrid control architecture, in which the strengths of each control method are combined to increase machine efficiency and reduce operator fatigue. The kinematics reconfiguration type differential control of the excavator implemented with a variety of ''software machine kinematics'' is the key feature of the project. This software re-configured excavator is more desirable to execute a given digging task. The human operator retains the master control of the main motion parameters, while the computer coordinates the repetitive movement patterns of the machine links. These repetitive movements may be selected from a pre-defined family of trajectories with different transformations. The operator can make adjustments to this pattern in real time, as needed, to accommodate rapidly-changing environmental conditions. A Bobcat{reg_sign} 435 excavator was retrofitted with electro-hydraulic control valve elements. The modular electronic control was tested and the basic valve characteristics were measured for each valve at the Robotics Laboratory at UNR. Position sensors were added to the individual joint control actuators, and the sensors were calibrated. An electronic central control system consisting of a portable computer, converters and electronic driver components was interfaced to the electro-hydraulic valves and position sensors. The machine is operational with or without the computer control system depending on whether the computer interface is on or off. In preparation for emulated mining tasks tests, typical, repetitive tool trajectories during surface mining operations were recorded at the Newmont Mining Corporation's ''Lone Tree'' mine in Nevada.

Data Mining Aplications in Livestock

Directory of Open Access Journals (Sweden)

Feyza ALEV ÇETİN

2016-03-01

Full Text Available Data mining provides discovering the required and applicable knowledge from very large amounts of information collected in one centre. Data mining has been used in the information industry and society. Although many methods of data mining has been used, these techniques has been remarkable in animal husbandry in recent years. For the solution of complex problems in animal husbandry many methods were discussed and developed. Brief information on data mining techniques such as k-means approach, k-nearest neighbor approach, multivariate adaptive regression function (MARS, naive Bayesian classifiers (NBC, artificial neural networks (ANN, support vector machines (SVM, decision trees are given in the study. Some data mining methods are presented and examples of the application of data mining in the field of animal husbandry in the world are provided with this study.

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

Science.gov (United States)

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

2016-01-01

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

Robotics for mining control

Energy Technology Data Exchange (ETDEWEB)

1986-11-01

In 1982 surveys of the mining industry revealed no applications of robotics existed and none were planned. This report provides a general overview of automation in the mining industry since this point in time. Roof control electronics, gas monitoring, jumbo drill automation, remote and sensor- controlled continuous miners, automated trolley trucks, roof bolting and screening machines are examples of technology available today. The report concludes with recommendations as to six potential research areas. 25 refs.

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

Science.gov (United States)

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

2018-04-14

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

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

Ergonomics of mining machinery and transport in the South African mining industry.

CSIR Research Space (South Africa)

Schutte, PC

2003-03-01

Full Text Available this background, a study was conducted to assess the ergonomics of a number of mining machines and transport systems to identify the ergonomics-related hazards that could impact on the operators’ ability to work safely and efficiently....

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.

Mechanical design of walking machines.

Science.gov (United States)

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

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

Tunnelling support methods and their possible application to machine rock face excavation in coal mining

Energy Technology Data Exchange (ETDEWEB)

Maidl, B.; Edeling, H.

1981-06-11

Mechanized pushing through the rocks is possible even in teary rock if protective measures are taken directly behind the drill bit. Present arch-type supports are best reinforced with sprayed concrete as it will take up rock deformations. In this case, however, the question soon arises whether arch-type steel supports should be used at all. So far, mature solutions have not been found but they will be possible if the mining industry is really interested. Sprayed concrete with admixtures of reinforcing steel fibers plays a major role here as it will protect miner's heads already at an early stage and is suitable as support even at a later stage. Equally interesting would be reinforced concrete pumped behind advancing formwork. A combination of both techniques may turn out to be the most suitable method to replace arch-type supports. A problem of particular importance is machine bracing in the fresh concrete lining. If the concrete is filled in directly behind the drill bit, it is only 4 to 6 h old when it reaches the bracing device, i.e., its pressure resistance is lower than the contact pressure of present mining machinery. It may be difficult to find a solution here but it is considered to be possible. With shell concrete, the formwork should be constructed so as to withstand the contact pressure.

MINE WASTE TECHNOLOGY PROGRAM - SULFATE REDUCING BACTERIA REACTIVE WALL DEMO

Science.gov (United States)

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

Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

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

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

Review of fill mining technology in Canada

Energy Technology Data Exchange (ETDEWEB)

Singh, K. H.; Hedley, D. G.F.

1980-05-15

The Canadian mining industry has a long history of being in the fore-front in developing new technology in underground hardrock mines. Examples include the development of hydraulic and cemented fills, undercut-and-fill, mechanized cut-and-fill, post pillar, vertical retreat and blasthole mining methods. The evolution of this technology is briefly described in an historical review. Backfill serves many functions, although it is generally considered in terms of its support capabilities. These functions, mainly related to the mining method used, are evaluated in regard to regional support, pillar support, fill roof, working floor, dilution control and waste disposal. With the advent of blasthole and vertical retreat methods for pillar recovery operations, the freestanding height of backfill walls has assumed greater importance. Consequently, more attention is being given to what fill properties are required to achieve fill wall exposures up to 25 m wide by 90 m high. With the large increases in energy costs, alternatives to partially replace Portland cement in fill are being examined. The validation of mining concepts and the interaction of backfill is perhaps best evaluated by in-situ measurements. Examples are given of stress, deformation and fill pressure measurements in longitudinal cut-and-fill, post pillar mining and blasthole stoping with delayed fill which were taken in several mines in Canada. Finally, the overall design procedure used in deciding mining method, stope and pillar dimensions, sequence of extraction, fill properties and support systems at a new mine is described.

Preliminary report on LLNL mine seismicity deployment at the Twentymile Coal Mine

International Nuclear Information System (INIS)

Walter, W.R.; Hunter, S.L.; Glenn, L.A.

1996-01-01

This report summarizes the preliminary results of a just completed experiment at the Twentymile Coal Mine, operated by the Cyprus Amax Coal Company near Oak Creek, CO. The purpose of the experiment was to obtain local and regional seismic data from roof caves associated with long-wall mining activities and to use this data to help determine the effectiveness with which these events can be discriminated from underground nuclear explosions under a future Comprehensive Test Ban Treaty

Mining robotics sensors

CSIR Research Space (South Africa)

Green, JJ

2011-07-01

Full Text Available International Conference of CAD/CAM, Robotics & Factories of the Future (CARs&FOF 2011) 26-28 July 2-11, Kuala Lumpur, Malaysia Mining Robotics Sensors Perception Sensors on a Mine Safety Platform Green JJ1, Hlophe K2, Dickens J3, Teleka R4, Mathew Price5...-28 July 2-11, Kuala Lumpur, Malaysia visualization in confined, lightless environments, and thermography for assessing the safety and stability of hanging walls. Over the last decade approximately 200 miners have lost their lives per year in South...

Use of natural gamma radiation in the coal mining industry

International Nuclear Information System (INIS)

Wykes, J.S.; Adsley, I.; Cooper, L.R.

1982-01-01

The technique of delineating coal seams by the use of natural gamma borehole logging sondes has been known for many years. The principle of the technique is that the gamma fluxes in shales are higher than in coals as the abundance of naturally occurring radionuclides is some twenty times greater in the former. This paper discusses other applications where the differeing natural gamma properties of coals and shales can be used. These are: (a) To distinguish between stone (shale) and run-of-mine coal on conveyor belts. A common situation underground is one in which stone from development headings and normal run-of-mine coal have to be batched along the same conveyor system. A natural gamma device capable of distinguishing between such batches of material, and thus allowing suitable mechanical separation, will be described. (b) To provide an accurate measurement of roof coal thickness by measuring the natural gamma flux penetrating the roof coal. To illustrate this examples will be given where this technique is used to provide automatic controlled steering of Long Wall Shearers and to provide manually assisted steering of In-seam Heading Machines

CSIR Centre for Mining Innovation and the mine safety platform robot

CSIR Research Space (South Africa)

Green, JJ

2012-11-01

Full Text Available The Council for Scientific and Industrial Research (CSIR) in South Africa is currently developing a robot for the inspection of the ceiling (hanging wall) in an underground gold mine. The robot autonomously navigates the 30 meter long by 3 meter...

Highly-productive mechanization systems for coal mining in the Polish coal industry

Energy Technology Data Exchange (ETDEWEB)

Sikora, W

1985-01-01

Effects of mechanization on underground coal mining in Poland from 1960 to 1980 and mining equipment used in Poland is reviewed. In 1983 black coal output increased to 191.1 Mt. There were 765 working faces, 442 of which with powered supports. Six hundred thirty-four shearer loaders were in use. About 82.7% of coal output fell on faces mined by sets of mining equipment (shearer loaders, powered supports and chain conveyors). The average coal output per working face amounted to 889 t/d. About 50% of mine roadways was driven by heading machines (346 heading machines were in use). The average coal output per face mined by a set of mining equipment amounted to 1248 t/d. About 86% of shearer loaders fell on double drum shearer loaders. Types of mining equipment used in underground mining are reviewed: powered supports (Pioma, Fazos, Glinik and the SOW), shearer loaders (drum shearer loaders and double-drum shearer loaders with chain haulage and chainless haulage systems for unidirectional and bi-directional mining), chain conveyors (Samson, Rybnik). Statistical data on working faces with various sets of equipment are given. 3 references.

A systematic mapping study of process mining

Science.gov (United States)

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

2018-05-01

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

Development trends in mining technologies. [Poland

Energy Technology Data Exchange (ETDEWEB)

Sikora, W

1983-01-01

Research programs on underground black coal mining in Poland are discussed. It is assumed that no major technology changes will take place by the year 2000. Second generation of mining technologies will be used after the year 2000. The following technologies of the second generation are discussed: in-situ gasification, chemical coal disintegration, manless hydraulic mining with hydraulic transport. Research programs on technologies of the second generation should guarantee their commercial and economic use by the year 2000. The following targets for research programs aimed at increasing productivity, reducing mining cost, reducing labor and increasing safety in mining, covering the next 2 decades are comparatively evaluated: increasing advance rate of longwall faces, increasing machine time of integrated face systems by at least 20%, improving design of powered supports for eliminating rock falls, development of heavy-duty face systems for longwall mining with hydraulic stowing, development of face systems for mining thick coal seams on their whole thickness, slice mining thick coal seams with artificial roofs, bidirectional longwall mining by shearer loaders, use of more elastic and reliable mining systems.

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

Science.gov (United States)

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

2014-01-01

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

Mining in 2015

Energy Technology Data Exchange (ETDEWEB)

Hood, M.; Hatherly, P.; Gurgenci, H. [Centre for Mining Technology and Equipment (Australia)

1999-10-01

New technology in open-pit and underground hard rock mining in 2015 is anticipated in this article, based on a paper presented to the 1998 invitation symposium - 'Technology - Australia's future: new technology for traditional industry', held in Freemantle, WA, 24-25 November 1998. It is expected that essential mining operations of rock breakage and transport and ore processing will still exist but the use of drills, shovels/LHDs and trucks is likely to be replaced by continuous, intelligent, automated mining systems. Rock blasting models need to be fed data on rock properties at each blasthole for high accuracy. The authors believe that in 2015 measurements of rock properties will be a routine part of the drilling process. Blasthole drills will be fitted with a range of mechanical and geophysical sensors. New, non-explosive methods of rock breaking such as oscillating disc cutting, may be available. Mining automation will improve safety and productivity, perhaps with the automation of dragline swing LHDs and trucks may be able to drive themselves, with operators monitoring and intervening when necessary. Performance and machine condition data may be applied to improve equipment design. Australian mining stands to gain by these advances in mining technology. 1 fig., 3 photos.

Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

Science.gov (United States)

Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

2017-12-01

In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to

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.

Analysis and Optimization of Entry Stability in Underground Longwall Mining

Directory of Open Access Journals (Sweden)

Yubing Gao

2017-11-01

Full Text Available For sustainable utilization of limited coal resources, it is important to increase the coal recovery rate and reduce mine accidents, especially those occurring in the entry (gateroad. Entry stabilities are vital for ventilation, transportation and other essential services in underground coal mining. In the present study, a finite difference model was built to investigate stress evolutions around the entry, and true triaxial tests were carried out at the laboratory to explore entry wall stabilities under different mining conditions. The modeling and experimental results indicated that a wide coal pillar was favorable for entry stabilities, but oversize pillars caused a serious waste of coal resources. As the width of the entry wall decreased, the integrated vertical stress, induced by two adjacent mining panels, coupled with each other and experienced an increase on the entry wall, which inevitably weakened the stability of the entry. Therefore, mining with coal pillars always involves a tradeoff between economy and safety. To address this problem, an innovative non-pillar mining technique by optimizing the entry surrounding structures was proposed. Numerical simulation showed that the deformation of the entry roof decreased by approximately 66% after adopting the new approach, compared with that using the conventional mining method. Field monitoring indicated that the stress condition of the entry was significantly improved and the average roof pressure decreased by appropriately 60.33% after adopting the new technique. This work provides an economical and effective approach to achieve sustainable exploitation of underground coal resources.

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

Effects on Buildings of Surface Curvature Caused by Underground Coal Mining

Directory of Open Access Journals (Sweden)

Haifeng Hu

2016-08-01

Full Text Available Ground curvature caused by underground mining is one of the most obvious deformation quantities in buildings. To study the influence of surface curvature on buildings and predict the movement and deformation of buildings caused by ground curvature, a prediction model of the influence function on mining subsidence was used to establish the relationship between surface curvature and wall deformation. The prediction model of wall deformation was then established and the surface curvature was obtained from mining subsidence prediction software. Five prediction lines were set up in the wall from bottom to top and the predicted deformation of each line was used to calculate the crack positions in the wall. Thus, the crack prediction model was obtained. The model was verified by a case study from a coalmine in Shanxi, China. The results show that when the ground curvature is positive, the crack in the wall is shaped like a “V”; when the ground curvature is negative, the crack is shaped like a “∧”. The conclusion provides the basis for a damage evaluation method for buildings in coalmine areas.

Aachen international mining symposia: 5. International symposium on roofbolting in mining. Proceedings

International Nuclear Information System (INIS)

2004-01-01

The authors of the symposium report on the following topics: roofbolting in German, Australian, British, Indian, Chinese coal mines, historical aspects, research programs, concrete lining, cable bolts, bolting machines, rectangular roadways,shear behavior of bolts, rock mechanics, resin grouted bolts, effects of earthquakes, support design guidelines, strata movements, numerical modelling, safety aspects. (uke)

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.

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

Science.gov (United States)

Trubetskoy, Kliment; Rylnikova, Marina; Esina, Ekaterina

2017-11-01

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

Practical difficulties in determining 222Rn flux density in underground uranium mines

International Nuclear Information System (INIS)

Bigu, J.

1991-01-01

Radon-222 flux density, J, has been determined in a number of locations in an underground U mine. Measurements were conducted using the Two-Point Measurement (2PM) method, consisting of measuring the 222Rn concentration at two different points a distance apart within a given section of the mine. Several mine models were used for determining J by the above method. The 2PM method is sensitive to sources and sinks of 222Rn other than mine walls, as well as mining operations and mining activities of a diverse nature, and to local variations in airflow conditions. Because of this, J obtained by the 2PM method represents an 'apparent' flux density. Significant differences were found in the flux density calculated according to different mine models. In addition, J measurements using the flux 'can' method were also carried out in mine walls and compared with the values obtained by the 2PM method. Wide discrepancies between the two methods were found. The practical and theoretical difficulties in determining J are discussed

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...

Information mining in remote sensing imagery

Science.gov (United States)

Li, Jiang

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

Mine games

Energy Technology Data Exchange (ETDEWEB)

Patchett, A. [Hitachi Construction Equipment (United Kingdom)

2006-09-15

The article describes various excavators used in the UK by Hall Construction for coal mining and reclamation projects. They include machines from Hitachi Construction Machinery that have been modified with a coal shovel at the front end. The ZX350LC-3, for example incorporates a coal shovel, manufactured by Kocurek, to allow it to work at the rock face and lift coal into road wagons or dump trucks. 5 figs.

Proposal to negotiate a collaboration agreement for the design and prototyping of a machine for laser treatment of metallic vacuum chamber walls for electron cloud mitigation at the High Luminosity LHC

CERN Document Server

2016-01-01

Proposal to negotiate a collaboration agreement for the design and prototyping of a machine for laser treatment of metallic vacuum chamber walls for electron cloud mitigation at the High Luminosity LHC

Lunar construction/mining equipment

Science.gov (United States)

Ozdemir, Levent

1990-01-01

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

Experimental High Speed Milling of the Selected Thin-Walled Component

Directory of Open Access Journals (Sweden)

Jozef Zajac

2017-11-01

Full Text Available In a technical practice, it is possible to meet thin-walled parts more and more often. These parts are most commonly used in the automotive industry or aircraft industry to reduce the weight of different design part of cars or aircraft. Presented article is focused on experimental high speed milling of selected thin-walled component. The introduction of this article presents description of high speed machining and specification of thin – walled parts. The experiments were carried out using a CNC machine Pinnacle VMC 650S and C45 material - plain carbon steel for automotive components and mechanical engineering. In the last part of the article, described are the arrangements to reduction of deformation of thin-walled component during the experimental high speed milling.

Mine for sale

International Nuclear Information System (INIS)

Beer, G.

2006-01-01

The newest Slovak brown coal mine - Bana Zahorie is in crisis. Despite the fact that experts believe that along with Bana Novaky, it has the most potential. The owners have started its liquidation. One of the walls has collapsed and another part flooded. Nobody was hurt, but some equipment is still underground. The mine had already lost equipment in the past. During an accident in 2000, equipment worth several tens of millions was destroyed. 'After the accident, mining had to be stopped and from a technical point of view that was the end of the joint stock company, Bana Zahorie Cary. The company could not raise the funds necessary to recover from the accident,' stated the Director of the mine, Jan Palkovic. But he stressed that only the joint stock company is in liquidation, the mine is still being ventilated and the water is being pumped out. But the company management still does not want to specify who will become the new owner of the lignite deposits in Zahorie. The Director promised to publish more details within several weeks. All competencies and mining rights of the former Bana Zahorie are being transferred to a new company - joint stock company Bana Cary. (author)

Underground coal mining technology - the future

Energy Technology Data Exchange (ETDEWEB)

Lama, R P [Kembla Coal and Coke Pty Limited, Wollongong, NSW (Australia)

1989-01-01

Discusses development of underground coal mining in Australia in the last four decades. The following aspects are reviewed: technology for underground mining (longwall mining, unidirectional cutting, bidirectional cutting, operation of more than one shearer on a working face, optimum dimensions of longwall blocks), longwall productivity (productivity increase will depend on increasing the availability factor of equipment, reducing failures due to human errors, organizational models, improving on-site decision making, improving monitoring, maintenance, planning and scheduling, concept of 'Transparent Mine'), roadway development systems (types of heading machines, standard systems for mine drivage and roof bolting and their productivity), size of coal mines, man and material transport systems (20,000-30,000 t/d from a single longwall face, mine shafts with a diameter 9-10 m), mine layout design (layout of longwall blocks, main intakes and returns situated in rock layers), mine environmental systems (ventilation systems, gas control), management, training and interpersonal relationships. Future coal mines will be developed with an integral capacity of 8-10 Mt/a from a single longwall operation with main development arteries placed in rocks. Development of gate roadways will require novel solutions with continuous cutting, loading and bolting. Information technology, with the concept of 'transparent mine', will form the backbone of decision making.

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…

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.

Radon exhalations of rock samples from the Muellenbach uranium test mine

International Nuclear Information System (INIS)

Keller, G.; Dudler, R.

1985-01-01

Radiation exposure of workers in underground mines with high U/Ra concentration is mostly due to inhalation of the short-lived radioactive decay products of the noble gas radon. Knowledge of the Rn-222 exhalation rates of walls and rocks as well as the contributing influencing parameters is therefore of interest for radiation protection purposes. Measurements showed that in the hours following shortfiring operations, the fresh dirt and the new walls had several times the exhalation rates of older dirt and walls. Measurements of exhalation rates on drill cores can help to assess exhalation for an adequate layout of the mine ventilation system. (orig./PW) [de

A Data Mining Approach for Cardiovascular Diagnosis

Directory of Open Access Journals (Sweden)

Pereira Joana

2017-12-01

Full Text Available The large amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analysed by traditional methods. Data mining can improve decision-making by discovering patterns and trends in large amounts of complex data. In the healthcare industry specifically, data mining can be used to decrease costs by increasing efficiency, improve patient quality of life, and perhaps most importantly, save the lives of more patients. The main goal of this project is to apply data mining techniques in order to make possible the prediction of the degree of disability that patients will present when they leave hospitalization. The clinical data that will compose the data set was obtained from one single hospital and contains information about patients who were hospitalized in Cardio Vascular Disease’s (CVD unit in 2016 for having suffered a cardiovascular accident. To develop this project, it will be used the Waikato Environment for Knowledge Analysis (WEKA machine learning Workbench since this one allows users to quickly try out and compare different machine learning methods on new data sets

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

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.

Mudstone depressurization behaviour in an open pit coal mine, Indonesia

Energy Technology Data Exchange (ETDEWEB)

Marchand, G.; Waterhouse, J. [Golder Associates, West Perth, WA (Australia); Crisostomo, J. [PT Adaro Indonesia, Jakarta (Indonesia)

2010-07-01

Mining activities in the Tutupan mine in Indonesia began in the mid-1990s. The open pit mine's coal seams are interbedded with fine-grained sandstones, mudstones, and carbonaceous mudstones. Slope stability analyses at the pit have integrated hydrogeology with geotechnical engineering analyses to optimize slope designs and reduce the risk of slope failure. This paper discussed the impact of mining and dewatering on mudstone depressurization. Sensors were placed at key points in the mine to obtain data related to the mudstone units. Reductions in pore pressure occurred as a result of groundwater flow away from the observed zones, increases in porosity, and increases in total porosity caused by an expansion of the rock mass as a result of drainage and hydrostatic unloading. Mudstone pore pressure trends with time were interpreted by determining the thickness of the mudstone unit, the presence or absence of known thin sandstone beds, unloading from overhead mining activities, and the position of the mudstone within the sedimentary sequence. The study showed that unloading activities have a significant impact on pore pressure in thick mudstone units, regardless of the depth, thickness, or properties of the unit. Pore pressure within high wall mudstone units typically decreased to values equivalent to the elevation of the unit where it was exposed to dips in a high wall. The dewatering of sandstone units in low walls caused a decline in pore pressure within the thick mudstone units located beneath the sandstones. Differences in primary permeabilities were attributed to greater fracturing in deeper and stronger rock units. 3 refs., 4 figs.

Data Mining Solutions for the Business Environment

OpenAIRE

Ruxandra-Stefania PETRE

2013-01-01

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 p...

An overview of data mining algorithms in drug induced toxicity prediction.

Science.gov (United States)

Omer, Ankur; Singh, Poonam; Yadav, N K; Singh, R K

2014-04-01

The growth in chemical diversity has increased the need to adjudicate the toxicity of different chemical compounds raising the burden on the demand of animal testing. The toxicity evaluation requires time consuming and expensive undertaking, leading to the deprivation of the methods employed for screening chemicals pointing towards the need to develop more efficient toxicity assessment systems. Computational approaches have reduced the time as well as the cost for evaluating the toxicity and kinetic behavior of any chemical. The accessibility of a large amount of data and the intense need of turning this data into useful information have attracted the attention towards data mining. Machine Learning, one of the powerful data mining techniques has evolved as the most effective and potent tool for exploring new insights on combinatorial relationships among various experimental data generated. The article accounts on some sophisticated machine learning algorithms like Artificial Neural Networks (ANN), Support Vector Machine (SVM), k-mean clustering and Self Organizing Maps (SOM) with some of the available tools used for classification, sorting and toxicological evaluation of data, clarifying, how data mining and machine learning interact cooperatively to facilitate knowledge discovery. Addressing the association of some commonly used expert systems, we briefly outline some real world applications to consider the crucial role of data set partitioning.

Radioactivity measurements in Egyptian phosphate mines and their significance in the occupational exposure of mine workers

International Nuclear Information System (INIS)

Bigu, J.; Hussein, Mohamed I.; Hussein, A.Z.

2000-01-01

Radioactivity measurements have been conducted in nine underground phosphate mines in the Egyptian Eastern Desert in order to estimate the occupational radiation exposure of mine workers in those mining sites. Measurements were carried out of airborne radon ( 222 Rn) and its short-lived decay products (progeny) and thoron ( 220 Rn) progeny, as well as γ-radiation from mine walls, ceilings and floors. Comparison of experimental data and theoretical predictions showed partial agreement between these two sets of data. This result is partly attributed to the complex layout of these mines which causes undesirable ventilation conditions, such as recirculation airflow patterns which could not be adequately identified or quantified. The radiation data obtained were used to estimate the Maximum Annual Dose (MAD), and other important occupational radiation exposure variables. These calculations indicate that in eight out of the nine mines surveyed, the MAD exceeded (by a factor of up to 7) the maximum recommended level by ICRP-60. A number of suggestions are made in order to reduce the MAD in the affected mines

Bigger hybrid loader on the drawing board : Mining Technologies International hybrid gets rave reviews for power and comfort

Energy Technology Data Exchange (ETDEWEB)

Tollinsky, N.

2010-12-01

This article presented a hybrid loader that reduces diesel emissions in underground mining. Sudbury-based Mining Technologies International (MTI) plans to build a 4 cubic yard loader in 2011, following the successful trial of a smaller 1.5 cubic yard machine at the CANMET experimental mine in Val d'Or, Quebec. The prototype hybrid loader was equipped with a metal hydride battery pack and a 2-cylinder, 35 hp Deutz engine. Performance testing revealed that the machine is capable of providing much more torque than originally expected and that it has more power compared to a mechanical drive machine. Operators at the CANMET mine also gave the hybrid loader high marks for comfort. The MTI loaders are equipped with a load sensing hydraulics system to eliminate jarring movement. The prototype experienced some premature failures in the flex coupling, which was subsequently replaced at the MTI shop in Sudbury. The primary reason for building the hybrid loader was to reduce diesel emissions underground in anticipation of stricter emission standards planned by the Mine Safety and Health Administration, the United States Environmental Protection Agency and CANMET for 2014. Compared to a conventional machine, there is virtually no exhaust from the hybrid loader. It is an ideal machine for a mine with very limited ventilation. Since the loader runs off the battery, MTI is currently looking at battery technologies other than metal hydrides to obtain a much higher energy density. Diesel is used to recharge the loader, and eliminates the need to plug in the unit between shifts. 1 ref., 2 figs.

Health in mines

Energy Technology Data Exchange (ETDEWEB)

Breuer, H

1978-01-01

This report summarizes the information gained from research carried out under the five-year programme (1971-1976) relating to health in mines. This programme concentrates on technical means of dust control, and the various aspects of this topic are reviewed. The purpose of the epidemiology of pneumoconiosis is to determine the origin and development of this endemic disease with a view to formulating a policy of worker protection. The constituents of dust and their possible influences are studied. Measuring and determining the characteristics of dusts are the subject of the second group of research projects. Prevention techniques have been proposed, tried out and developed, thus providing the mining industry with a set of dust control methods. water infusion, dedusting on coal-getting and heading machines, control of dust produced by caving, etc. A chapter devoted to iron ore mines discusses means of protection against noxious emissions from Diesel engines and explosives. (Editions available in English, in German, in French, in Italian, and in Dutch)

Overview of the INEX 2008 XML Mining Track

Science.gov (United States)

Denoyer, Ludovic; Gallinari, Patrick

We describe here the XML Mining Track at INEX 2008. This track was launched for exploring two main ideas: first identifying key problems for mining semi-structured documents and new challenges of this emerging field and second studying and assessing the potential of machine learning techniques for dealing with generic Machine Learning (ML) tasks in the structured domain i.e. classification and clustering of semi structured documents. This year, the track focuses on the supervised classification and the unsupervised clustering of XML documents using link information. We consider a corpus of about 100,000 Wikipedia pages with the associated hyperlinks. The participants have developed models using the content information, the internal structure information of the XML documents and also the link information between documents.

Machine learning and medicine: book review and commentary.

Science.gov (United States)

Koprowski, Robert; Foster, Kenneth R

2018-02-01

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

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.

Integrated Robot-Human Control in Mining Operations

Energy Technology Data Exchange (ETDEWEB)

George Danko

2007-09-30

This report contains a detailed description of the work conducted for the project on Integrated Robot-Human Control in Mining Operations at University of Nevada, Reno. This project combines human operator control with robotic control concepts to create a hybrid control architecture, in which the strengths of each control method are combined to increase machine efficiency and reduce operator fatigue. The kinematics reconfiguration type differential control of the excavator implemented with a variety of 'software machine kinematics' is the key feature of the project. This software re-configured excavator is more desirable to execute a given digging task. The human operator retains the master control of the main motion parameters, while the computer coordinates the repetitive movement patterns of the machine links. These repetitive movements may be selected from a pre-defined family of trajectories with different transformations. The operator can make adjustments to this pattern in real time, as needed, to accommodate rapidly-changing environmental conditions. A working prototype has been developed using a Bobcat 435 excavator. The machine is operational with or without the computer control system depending on whether the computer interface is on or off. In preparation for emulated mining tasks tests, typical, repetitive tool trajectories during surface mining operations were recorded at the Newmont Mining Corporation's 'Lone Tree' mine in Nevada. Analysis of these working trajectories has been completed. The motion patterns, when transformed into a family of curves, may serve as the basis for software-controlled machine kinematics transformation in the new human-robot control system. A Cartesian control example has been developed and tested both in simulation and on the experimental excavator. Open-loop control is robustly stable and free of short-term dynamic problems, but it allows for drifting away from the desired motion kinematics of the

Drivage of development workings in Kuzbass mines. Opyt provedeniya podgotovitel'nykh vyrabotok na shakhtakh Kuzbassa

Energy Technology Data Exchange (ETDEWEB)

Abramov, V M; Gusakov, F K; Goloshchapov, R E

1983-01-01

Mine drivage is evaluated in underground coal mines in the Kuzbass and factors which influence drivage advance rate and cost. Mine drivage in the Kuzbass in 1982 is described: 1,706.3 km of workings were driven by explosive fracturing and heading machines, 853.8 km of workings were driven with mechanized rock handling systems, 205.8 km with rock handling by loaders, 532.1 km were driven by heading machines. The average cross-section of workings driven in the Kuzbass ranged from 4 to 12 m/SUP/2; from 8 to 12% of workings had a cross-section exceeding 12 m/SUP/2. Strata control systems used in mine drivage are evaluated: 22.8% of workings was supported by steel arched supports, 20.3% by roof bolts, 0.07% by concrete supports or tubbings, 47.5% by timber props and 9.2% by other support systems. Statistical data on mine drivage of mine roadways, development workings, ventilation tunnels, inclined workings and coal chutes in the Kuzbass are given in 7 tables. Mine drivage in selected coal mines of the basin is evaluated: drivage systems, materials handling, mine haulage, strata control, transport of materials, safety.

Empirical approach for designing of support system in mechanized coal pillar mining

Energy Technology Data Exchange (ETDEWEB)

Kushwaha, A.; Singh, S.K.; Tewari, S.; Sinha, A. [Central Institute of Mining & Fuel Research, Dhanbad (India)

2010-10-15

Mechanized room-and-pillar system of coal pillar mining using side dump loading machine or load haul dumper machine, or by continuous miner, is the presently most dominant under ground method of extraction in India. Under this method of extraction, strata control is a major problem affecting safety and productivity of the mine. As per existing Director General of Mine Safety guidelines, systematic support rules must be followed at the depillaring faces irrespective of immediate roof rock type and competency. Therefore, there is a high chance that sometimes these systematic support rules give unnecessarily high support, or sometimes inadequate support, which may lead to roof failure at the face. As a result, there is a big loss of life and material including coal in terms of left-outribs/stooks and other associated mining equipment deployed at the faces. Therefore, in the present paper, authors attempted to develop generalized empirical equations for estimating the required support load density at different places of the face based on geotechnical parameters of the mine and physico-mechanical properties of the immediate roof rocks for designing of support system during mechanized coal pillar mining.

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.

Dust-control for thick-seam wall mines.

CSIR Research Space (South Africa)

Belle, BK

2002-02-01

Full Text Available configuration and the belt curtains on the shearer. 3. Install, and evaluate the efficiency of, the physical shield curtains (conveyor belt or other flexible material) hanging from the shield structure inside the shield leg area at every 4th shield to reduce... and 1997, coal production hovered around the 50 million tonnes-a-year level (UK DTI, 2001). Currently, there are 16 producing underground mines in the UK, which includes 15 longwall faces, face lengths range from 250 m to 300 m (Creedy, 2001). Most...

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

Science.gov (United States)

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

2012-04-01

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

Intelligent Mining Engineering Systems in the Structure of Industry 4.0

OpenAIRE

Rylnikova Marina; Radchenko Dmitriy; Klebanov Dmitriy

2017-01-01

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, machine...

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.

Continuous Rating for Diggability Assessment in Surface Mines

Science.gov (United States)

IPHAR, Melih

2016-10-01

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

Using the method of mathematical-logical modeling in compiling an engineering plan for development of a mine

Energy Technology Data Exchange (ETDEWEB)

Fajkos, A.; Klimek, M.

1980-01-01

A possibility of using a mathematical-logical modeling to improve the quality of mine shaft operation planning in Czechloslovakia based on the example of the Sverma mine in Ostrova with complex mining-geological conditions is studied. For the basic criteria we assumed: extraction plant, number of shifts in the long walls, time period for beginning and ending long wall operation, processing of reserves with consideration of existing conditions, output and dip angle of a formation, quality of extracted coal, and also: time intervals for processing separate formations, limitation of extraction load in a long wall in connection with gas emission, timbering, the necessity of insuring normal operating conditions, concentration of extraction, time relationship of preparatory and extraction operations.

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...

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.

Underground mining robot: a CSIR project

CSIR Research Space (South Africa)

Green, JJ

2012-11-01

Full Text Available The Council for Scientific and Industrial Research (CSIR) in South Africa is currently developing a robot for the inspection of the ceiling (hanging-wall) in an underground gold mine. The robot autonomously navigates the 30 meter long by 3 meter...

A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING

OpenAIRE

Arumugam.S

2016-01-01

The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is mainly used to make predictions about future events which are unknown. Predictive analytics which uses various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for analyzing the current data and to make predictions about futu...

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

A security-awareness virtual machine management scheme based on Chinese wall policy in cloud computing.

Science.gov (United States)

Yu, Si; Gui, Xiaolin; Lin, Jiancai; Tian, Feng; Zhao, Jianqiang; Dai, Min

2014-01-01

Cloud computing gets increasing attention for its capacity to leverage developers from infrastructure management tasks. However, recent works reveal that side channel attacks can lead to privacy leakage in the cloud. Enhancing isolation between users is an effective solution to eliminate the attack. In this paper, to eliminate side channel attacks, we investigate the isolation enhancement scheme from the aspect of virtual machine (VM) management. The security-awareness VMs management scheme (SVMS), a VMs isolation enhancement scheme to defend against side channel attacks, is proposed. First, we use the aggressive conflict of interest relation (ACIR) and aggressive in ally with relation (AIAR) to describe user constraint relations. Second, based on the Chinese wall policy, we put forward four isolation rules. Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. Finally, based on the normal distribution, we conduct a series of experiments to evaluate SVMS. The experimental results show that SVMS is efficient in guaranteeing isolation between VMs owned by conflict users, while the resource utilization rate decreases but not by much.

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.

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 ...

Energy Consumption in the Process of Excavator-Automobile Complexes Distribution at Kuzbass Open Pit Mines

Directory of Open Access Journals (Sweden)

Panachev Ivan

2017-01-01

Full Text Available Every year worldwide coal mining companies seek to maintain the tendency of the mining machine fleet renewal. Various activities to maintain the service life of already operated mining equipment are implemented. In this regard, the urgent issue is the problem of efficient distribution of available machines in different geological conditions. The problem of “excavator-automobile” complex effective distribution occurs when heavy dump trucks are used in mining. For this reason, excavation and transportation of blasted rock mass are the most labor intensive and costly processes, considering the volume of transported overburden and coal, as well as diesel fuel, electricity, fuel and lubricants costs, consumables for repair works and downtime, etc. Currently, it is recommended to take the number of loading buckets in the range of 3 to 5, according to which the dump trucks are distributed to faces.

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

Development and application of new composite grouting material for sealing groundwater inflow and reinforcing wall rock in deep mine.

Science.gov (United States)

Jinpeng, Zhang; Limin, Liu; Futao, Zhang; Junzhi, Cao

2018-04-04

With cement, bentonite, water glass, J85 accelerator, retarder and water as raw materials, a new composite grouting material used to seal groundwater inflow and reinforce wall rock in deep fractured rock mass was developed in this paper. Based on the reaction mechanism of raw material, the pumpable time, stone rate, initial setting time, plastic strength and unconfined compressive strength of multi-group proportion grouts were tested by orthogonal experiment. Then, the optimum proportion of composite grouting material was selected and applied to the grouting engineering for sealing groundwater inflow and reinforcing wall rock in mine shaft lining. The results show the mixing proportion of the maximum pumpable time, maximum stone rate and minimum initial setting time of grout are A K4 B K1 C K4 D K2 , A K3 B K1 C K1 D K4 and A K3 B K3 C K4 D K1 , respectively. The mixing proportion of the maximum plastic strength and unconfined compressive strength of grouts concretion bodies are A K1 B K1 C K1 D K3 and A K1 B K1 C K1 D K1 , respectively. Balanced the above 5 indicators overall and determined the optimum proportion of grouts: bentonite-cement ratio of 1.0, water-solid ratio of 3.5, accelerator content of 2.9% and retarder content of 1.45%. This new composite grouting material had good effect on the grouting engineering for sealing groundwater inflow and reinforcing wall rock in deep fractured rock mass.

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

Developments in the application of underground battery vehicles in the UK coal mining industry

Energy Technology Data Exchange (ETDEWEB)

Fortune, J A.B.; Crawshaw, S A.M. [Long-Airdox International Ltd. (United Kingdom)

1996-10-01

Trackless battery powered haulage vehicles have been in operation in British coal mines principally for longwall face transfer and personnel transportation. Changes within the industry have resulted in the introduction of room and pillar coal mining methods and the introduction of increasingly heavier longwall roof supports. This has resulted in the introduction of: battery powered coal haulage machines, which, without the need for trailing cables, increase productivity within room and pillar mining; and battery powered longwall shield haulers which are capable of carrying the heaviest shield supports currently being utilised within the British coal mining industry. The conventional machines have been adapted from an American design to meet the requirements of European legislation. This has seen the emphasis being placed upon the supplier with the European Machinery Directive being introduced, necessitating the assigning of a `CE` mark to each vehicle. Battery vehicle technology has advanced to meet the demands of the ever changing market and will no doubt be further adapted to meet the requirement of the British coal mining industry. 1 ref., 12 figs., 3 tabs.

Current status of thin seam longwall mining in the US

Energy Technology Data Exchange (ETDEWEB)

Peng, S.S. [West Virginia Univ., Morgantown, WV (United States); Orndorff, A.

1996-12-31

Thin seams in this paper refers to those seams the economic mining height of which is below 50-55 in. that are traditionally considered to be the proprietary of plowing and present a whole net set of problems for longwall mining. In thin seams it is difficult to design and manufacture an efficient high capacity cutting machine for maintenance and production operations. Thin seam mining by longwall plowing began in the late fifties in southern West Virginia, and continues to the present time. In the seventies when longwall mining began to take off a large percentage of U.S. longwalls were operating in the thin seams. Tables 1 and 2 show the historical trends of cutting machines used for seams less than 55 in and 50 in, respectively. In addition to the plow system, the single-ended fixed drum and single-ended ranging drum shearers were introduced in the mid and late seventies and operated continuously until 2-4 years ago. The double-ended ranging drum shearers have also been employed for thin seam longwall mining during this period including several in-web (or off-pan) shearers between late seventies and early eighties. In this paper three thin-seam longwalls in three states employing the latest thin-seam longwall technology will be reviewed. However only two of them are still in operation while the third one ceased operation recently.

Mining of sedimentary-type ore deposits

International Nuclear Information System (INIS)

Bruha, J.; Slovacek, T.; Berka, J.; Sadilek, P.

1992-01-01

A procedure is proposed for mining sedimentary-type ore deposits, particularly uranium deposits, using the stope-pillar technique. The stope having been mined out, the free room is filled with hydro-setting gob from the surface. A precondition for the application of this technique is horizontal ore mineralization in sediments where the total thickness of the mineralized ore layer is at least 3 to 5 m. Mining losses do not exceed 5%. For thicknesses greater than 5 m, the roof is reinforced and the walls are secured with netting. The assets of the technique include higher labor productivity of the driving, lower material demands in reinforcing and filling, lower power consumption, and reduced use of explosives. (Z.S.). 3 figs

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

Science.gov (United States)

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

2017-10-01

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

47 CFR 15.509 - Technical requirements for ground penetrating radars and wall imaging systems.

Science.gov (United States)

2010-10-01

..., fire fighting, emergency rescue, scientific research, commercial mining, or construction. (1) Parties... radars and wall imaging systems. 15.509 Section 15.509 Telecommunication FEDERAL COMMUNICATIONS... ground penetrating radars and wall imaging systems. (a) The UWB bandwidth of an imaging system operating...

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

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.

Process and device for hacking and arranging the mining face in mines. Verfahren und Einrichtung zum Auffahren eines Aufhauens und Einrichten des Gewinnungsstrebs in Bergbaubetrieben

Energy Technology Data Exchange (ETDEWEB)

Beckmann, K

1982-04-01

A process for driving a heading machine and a device for arranging the mining face is described. A movable heading and conveyor device is used for this purpose and to secure the roof in the area of the conveyor device, a moving hydraulic prop is used as the support. After preparing the heading, the frames remain as movable roadway supports to secure the entry to the mining face.

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

Data Mining Process Optimization in Computational Multi-agent Systems

OpenAIRE

Kazík, O.; Neruda, R. (Roman)

2015-01-01

In this paper, we present an agent-based solution of metalearning problem which focuses on optimization of data mining processes. We exploit the framework of computational multi-agent systems in which various meta-learning problems have been already studied, e.g. parameter-space search or simple method recommendation. In this paper, we examine the effect of data preprocessing for machine learning problems. We perform the set of experiments in the search-space of data mining processes which is...

First Wall and Operational Diagnostics

International Nuclear Information System (INIS)

Lasnier, C; Allen, S; Boedo, J; Groth, M; Brooks, N; McLean, A; LaBombard, B; Sharpe, J; Skinner, C; Whyte, D; Rudakov, D; West, W; Wong, C

2006-01-01

In this chapter we review numerous diagnostics capable of measurements at or near the first wall, many of which contribute information useful for safe operation of a tokamak. There are sections discussing infrared cameras, visible and VUV cameras, pressure gauges and RGAs, Langmuir probes, thermocouples, and erosion and deposition measurements by insertable probes and quartz microbalance. Also discussed are dust measurements by electrostatic detectors, laser scattering, visible and IR cameras, and manual collection of samples after machine opening. In each case the diagnostic is discussed with a view toward application to a burning plasma machine such as ITER

Report. First international symposium on innovating mining systems

Energy Technology Data Exchange (ETDEWEB)

Blackwood, R L

1985-01-01

The author presents a summary of proceedings of the First International Symposium on Innovative Mining Systems held at Massachusetts Institute of Technology, USA 4-5 November 1985, together with some comments on the conclusions and discussion throughout. The Symposium agenda included the following (i) Symposium intentions and expectations; (ii) International; (iii) Developments in safety; (iv) Overview of current major research and trends; (v) Panel discussion: Mechanisms for industrial and international collaboration; (vi) Closing remarks; (vii) Review of innovations: university programs; (viii) Review of selected mine operator programs and needs; Review of equipment innovations; capabilities and trends in areas of mining equipment and robotics; Concurrent sessions: operations and manufacturing. A series of workshops was also held, the titles of which were as follows: (i) Establishment of research network; (ii) Entry development-machine excavation; (iii) Sensing, monitoring, diagnostics, artificial intelligence; (iv) Remote control, automation, mining systems; (v) Computer aided design, simulation, system development; (vi) Surface mining; (vii) Rock breakage.

THE DEVELOPMENT OF A NOVEL MODEL FOR MINING METHOD SELECTION IN A FUZZY ENVIRONMENT; CASE STUDY: TAZAREH COAL MINE, SEMNAN PROVINCE, IRAN

Directory of Open Access Journals (Sweden)

Fatemeh Asadi Ooriad

2018-01-01

Full Text Available Mining method selection (MMS for mineral resources is one of the most significant steps in mining production management. Due to high costs involved and environmental problems, it is usually not possible to change the coal mining method after planning and starting the operation. In most cases, MMS can be considered as an irreversible process. Selecting a method for mining mainly depends on geological, geometrical properties of the resource, environmental impacts of exploration, impacts of hazardous activities and land use management. This paper seeks to develop a novel model for mining method selection in order to achieve a stable production rate and to reduce environmental problems. This novel model is illustrated by implementing for Tazareh coal mine. Given the disadvantages of the previous models for selecting coal mining method, the purpose of this research is modifying the previous models and offering a comprehensive model. In this respect, TOPSIS method is used as a powerful multi attribute decision-making procedure in Fuzzy environment. After implementation of the presented model in Tazareh coal mine, long wall mining method has been selected as the most appropriate mining method.

Multipass mining sequence room closures: In situ data report

International Nuclear Information System (INIS)

Munson, D.E.; Jones, R.L.; Northrop-Salazar, C.L.; Woerner, S.J.

1992-12-01

During the construction of the Thermal/Structural In Situ Test Rooms at the Waste Isolation Pilot Plant (WIPP) facility, measurements of the salt displacements were obtained at very early times, essentially concurrent with the mining activity. This was accomplished by emplacing manually read closure gage stations directly at the mining face, actually between the face and the mining machine, immediately upon mining of the intended gage location. Typically, these mining sequence closure measurements were taken within one hour of mining of the location and within one meter of the mining face. Readings were taken at these gage stations as the multipass mining continued, with the gage station reestablished as each successive mining pass destroyed the earlier gage points. Data reduction yields the displacement history during the mining operation. These early mining sequence closure data, when combined with the later data of the permanently emplaced closure gages, gives the total time-dependent closure displacements of the test rooms. This complete closure history is an essential part of assuring that the in situ test databases will provide an adequate basis for validation of the predictive technology of salt creep behavior, as required by the WIPP technology development program for disposal of radioactive waste in bedded salt

Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

Directory of Open Access Journals (Sweden)

Kuchin Yan

2017-12-01

Full Text Available The paper explores geophysical methods of wells survey, as well as their role in the development of Kazakhstan’s uranium deposit mining efforts. An analysis of the existing methods for solving the problem of interpreting geophysical data using machine learning in petroleum geophysics is made. The requirements and possible applications of machine learning methods in regard to uranium deposits of Kazakhstan are formulated in the paper.

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.

A tm Plug-In for Distributed Text Mining in R

Directory of Open Access Journals (Sweden)

Stefan Theussl

2012-11-01

Full Text Available R has gained explicit text mining support with the tm package enabling statisticians to answer many interesting research questions via statistical analysis or modeling of (text corpora. However, we typically face two challenges when analyzing large corpora: (1 the amount of data to be processed in a single machine is usually limited by the available main memory (i.e., RAM, and (2 the more data to be analyzed the higher the need for efficient procedures for calculating valuable results. Fortunately, adequate programming models like MapReduce facilitate parallelization of text mining tasks and allow for processing data sets beyond what would fit into memory by using a distributed file system possibly spanning over several machines, e.g., in a cluster of workstations. In this paper we present a plug-in package to tm called tm.plugin.dc implementing a distributed corpus class which can take advantage of the Hadoop MapReduce library for large scale text mining tasks. We show on the basis of an application in culturomics that we can efficiently handle data sets of significant size.

Discussion on the safety production risk managmeent of uranium mines

International Nuclear Information System (INIS)

Liu Bin; Luo Yun; Hu Penghua; Zhu Disi

2009-01-01

Based on the modern safety risk management theories and according to the actual situation, risk management for work safety in uranium mines is discussed from three aspects: risk identification,risk analysis and evaluation, and risk control. Referring to the '4M(Men,Machine,Medium,Management) factors' and 'Three types of hazards' theory, the classification of uranium mine accidents and risk factors are analyzed. In addition, the types and evaluation indexes of major risks of uranium mines as well as the 'spot, line, area' model of risk identification and analysis and the 'hierarchical' risk control mechanism are also studied. (authors)

Traction sheave elevator, hoisting unit and machine space

Science.gov (United States)

Hakala, Harri; Mustalahti, Jorma; Aulanko, Esko

2000-01-01

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

A complex of optimization problems in planning for the development of mining operations in coal mines

Energy Technology Data Exchange (ETDEWEB)

Todorov, A K; Arnaudov, B K; Brankova, B A; Gyuleva, B I; Zakhariyev, G K

1977-01-01

The system for planning for the development of coal mines is a complex of interrelated plan optimization, plan calculation and supporting (accounting-analytical and standards) tasks. An important point in this complex is held by the plan optimization tasks. The questions about the synthesis and the structural peculiarities of the system, the essence and machine realization of the tasks are examined.

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...

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

Science.gov (United States)

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

2017-04-01

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

Supporting Solar Physics Research via Data Mining

Science.gov (United States)

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

2012-05-01

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

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.

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. .

Computer-based expert system aids underground mine planning

Energy Technology Data Exchange (ETDEWEB)

Britton, S.G.

1987-04-01

Artificial intelligence (AI) systems have been rapidly expanded over the last few years to aid in the decision making processes in a whole range of industries, including the use of machines for operating in high risk/dangerous areas such as at the working faces in longwall mining. Using Prolog software a program for mine management is being developed called CHOOZ. This system can help managers identify staffing problems and change manpower shifts to cope with unexpected labor problems such as absenteeism and sickness. All the programs have been developed for the IBM PC microcomputer.

Flux measurements with a sniffer probe near the wall in ASDEX

International Nuclear Information System (INIS)

Poschenrieder, W.; Venus, G.; Wang, Y.G.; Mueller, E.R.; Bartiromo, R.; Becker, G.; Bosch, H.S.; Brocken, H.; Eberhagen, A.; Fussmann, G.; Gehre, O.; Gernhardt, J.; Gierke, G. v.; Glock, E.; Gruber, O.; Haas, G.; Janeschitz, G.; Karger, F.; Kotze, P.B.; Keilhacker, M.; Klueber, O.; Kornherr, M.; Lackner, K.; Lenoci, M.; Lisitano, G.; Mayer, H.M.; McCormick, K.; Meisel, D.; Mertens, V.; Murmann, H.; Niedermeyer, H.; Rapp, H.; Roehr, H.; Ryter, F.; Schneider, F.; Siller, G.; Smeulders, P.; Soeldner, F.; Speth, E.; Steuer, K.H.; Vollmer, O.; Wagner, F.

1985-01-01

For a detailed assessment of particle recycling in a tokamak it is necessary to know quality and quantity of the particle fluxes directed to the elements of the wall. In a divertor machine like ASDEX we have to differentiate between at least four distinct elements: main chamber wall, protective limiters, collector plates, and divertor walls. Relevant data about the divertor region are obtained from pressure and flux measurements. (orig./GG)

Experimental force modeling for deformation machining stretching ...

Indian Academy of Sciences (India)

ARSHPREET SINGH

requires different machining techniques such as use of long ... thin structure to a desired shape incrementally using com- .... 4.1c Influence of wall angle (a): The average resultant ..... [3] Agrawal A, Smith S, Woody B and Cao J 2012 Study of.

Tectonic fault monitoring at open pit mine at Zarnitsa Kimberlite Pipe

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

2016-01-01

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

DECISION SUPPORT SYSTEM TO SUPPORT DECISION PROCESSES WITH DATA MINING

OpenAIRE

Rupnik, Rok; Kukar, Matjaž

2007-01-01

Traditional techniques of data analysis do not enable the solution of all kind of problems and for that reason they have become insufficient. This caused a newinterdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning techniques to support the data analysis and knowledge discovery from data. Data mining methods are powerful in dealing with large quantities of data, but on the other hand they are difficult to master by business users t...

METODE DATA MINING UNTUK SELEKSI CALON MAHASISWA PADA PENERIMAAN MAHASISWA BARU DI UNIVERSITAS PAMULANG

Directory of Open Access Journals (Sweden)

Aries Saifudin

2018-01-01

Full Text Available Universitas Pamulang berusaha memberikan pendidikan tinggi dengan biaya yang terjangkau oleh kalangan bawah. Tetapi mahasiswanya banyak yang keluar di tiap semester, sehingga menyebabkan rasio jumlah mahasiswa baru dengan jumlah yang lulus tidak seimbang. Selain itu banyak mahasiswa yang tidak lulus tepat waktu, hal ini mengakibatkan rasio dosen dan mahasiswa tidak seimbang. Kedua hal ini akan mengurangi penilaian pada saat akreditasi. Penyebab keluarnya mahasiswa tanpa menyelesaikan pendidikannya, atau tidak dapat menyelesaikan pendidikannya tepat waktu belum dapat dideteksi dengan sistem seleksi saat ini. Pada penelitian ini diusulkan penggunaan teknik data mining untuk memprediksi ketepatan waktu lulus calon mahasiswa. Teknik data mining dan machine learning dapat digunakan untuk memprediksi berdasarkan data-data masa lalu. Metode data mining yang digunakan untuk memprediksi adalah klasifikasi, yaitu Naïve Bayes (NB, k-Nearest Neighbor (k-NN, Random Forest (RF, Decision Stump (DS, Decision Tree (DT, Rule Induction (RI, Linear Regression (LR, Linear Discriminant Analysis (LDA, Neural Network (NN, dan Support Vector Machine (SVM. Berdasarkan hasil implementasi dan pengukuran algoritma/model yang diusulkan diperoleh algoritma/model terbaik, yaitu Support Vector Machine (SVM dengan akurasi 65.00%. Tetapi akurasi ini masih jauh dari nilai excellent (sangat baik.

The effect of time-dependent ventilation and radon (thoron) gas emanation rates in underground uranium mines

International Nuclear Information System (INIS)

Bigu, J.

1987-01-01

A theoretical radiation mine model, suitable for underground uranium mines, has been investigated. In this model, the rate of ventilation and/or the radon (thoron) gas emanation from mine walls are time-dependent. Several cases of practical interest have been investigated including sinusoidal, linear, exponential, stepwise, or a combination of two or more of the above. Analytical solutions were obtained for the time-dependent radon (thoron) gas emanation rate. However, because of the extreme analytical complexity of the solutions corresponding to the time-dependent ventilation rate case, numerical solutions were found using a special Runge-Kutta procedure and the Hamming's modified predictor-corrector method for the solution of linear initial-value problems. The mine model makes provisions for losses of radioactivity, other than by ventilation and radioactive decay, by, say, plate-out on mine walls, and by other mechanisms. Radioactivity data, i.e., radon, thoron, and their progeny, obtained with the above mine model for a number of ventilation and emanation conditions, are presented. Experimental data obtained in an inactive stope of an underground uranium mine for a time-dependent air flow case are shown. Air flow conditions (ventilation rate) were determined by tracer gas techniques using SF 6

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

Science.gov (United States)

Vallmuur, Kirsten

2015-06-01

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

Machine Learning Methods for Knowledge Discovery in Medical Data on Atherosclerosis

Czech Academy of Sciences Publication Activity Database

Serrano, J.I.; Tomečková, Marie; Zvárová, Jana

2006-01-01

Roč. 1, - (2006), s. 6-33 ISSN 1801-5603 Institutional research plan: CEZ:AV0Z10300504 Keywords : knowledge discovery * supervised machine learning * biomedical data mining * risk factors of atherosclerosis Subject RIV: BB - Applied Statistics, Operational Research

Methods for protecting mine roadways used by two faces

Energy Technology Data Exchange (ETDEWEB)

Katkov, G A; Dimanshtein, A S

1983-09-01

Use of a mine roadway by two longwall faces reduces mine drivage by half and positively influences ventilation and mine haulage. Economic effects of repeated use of mine roadways depend on strata control cost and repair of support systems damaged or deformed by rock strata stress. Use of strips of pneumatic stowing along mine roadways is uneconomical due to low support strength and significant subsidence of the waste rock strip under rock strata stress. Use of timber cribbings as well as blocks of reinforced concrete for strata control is uneconomical due to their high damage rate and low support capacity. Investigations carried out by the IGD Im. A.A. Skochinski Institute and other research institutes show that use of hardening stowing is superior to other methods for strata control in mine roadways used by two longwall faces. Hardening stowing (on a cement basis) is prepared by the SB-67 or the PBM-2Eh machines and by other systems used for guniting in coal mines. The optimum dimensions of a strip of hardening stowing depend on coal seam thickness and mechanical properties of the surrounding rock strata. Use of hardening stowing successfully controls roof subsidence in mine roadways and reduces support deformation. Examples of hardening stowing use in some Donbass coal mines are discussed.

Mining Method

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Shik; Lee, Kyung Woon; Kim, Oak Hwan; Kim, Dae Kyung [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)

1996-12-01

The reducing coal market has been enforcing the coal industry to make exceptional rationalization and restructuring efforts since the end of the eighties. To the competition from crude oil and natural gas has been added the growing pressure from rising wages and rising production cost as the workings get deeper. To improve the competitive position of the coal mines against oil and gas through cost reduction, studies to improve mining system have been carried out. To find fields requiring improvements most, the technologies using in Tae Bak Colliery which was selected one of long running mines were investigated and analyzed. The mining method appeared the field needing improvements most to reduce the production cost. The present method, so-called inseam roadway caving method presently is using to extract the steep and thick seam. However, this method has several drawbacks. To solve the problems, two mining methods are suggested for a long term and short term method respectively. Inseam roadway caving method with long-hole blasting method is a variety of the present inseam roadway caving method modified by replacing timber sets with steel arch sets and the shovel loaders with chain conveyors. And long hole blasting is introduced to promote caving. And pillar caving method with chock supports method uses chock supports setting in the cross-cut from the hanging wall to the footwall. Two single chain conveyors are needed. One is installed in front of chock supports to clear coal from the cutting face. The other is installed behind the supports to transport caved coal from behind. This method is superior to the previous one in terms of safety from water-inrushes, production rate and productivity. The only drawback is that it needs more investment. (author). 14 tabs., 34 figs.

Classification Identification of Acoustic Emission Signals from Underground Metal Mine Rock by ICIMF Classifier

Directory of Open Access Journals (Sweden)

Hongyan Zuo

2014-01-01

Full Text Available To overcome the drawback that fuzzy classifier was sensitive to noises and outliers, Mamdani fuzzy classifier based on improved chaos immune algorithm was developed, in which bilateral Gaussian membership function parameters were set as constraint conditions and the indexes of fuzzy classification effectiveness and number of correct samples of fuzzy classification as the subgoal of fitness function. Moreover, Iris database was used for simulation experiment, classification, and recognition of acoustic emission signals and interference signals from stope wall rock of underground metal mines. The results showed that Mamdani fuzzy classifier based on improved chaos immune algorithm could effectively improve the prediction accuracy of classification of data sets with noises and outliers and the classification accuracy of acoustic emission signal and interference signal from stope wall rock of underground metal mines was 90.00%. It was obvious that the improved chaos immune Mamdani fuzzy (ICIMF classifier was useful for accurate diagnosis of acoustic emission signal and interference signal from stope wall rock of underground metal mines.

Application of rock mechanics to cut-and-fill mining. Volume 1

Energy Technology Data Exchange (ETDEWEB)

1980-05-15

The conference on application of rock mechanics to cut-and-fill mining was held June 1-3, 1980, at the University of Luleaa, Sweden. The conference began with reviews of the application of rock mechanics to mining and back filling in Australia, Canada and the USA. More particular papers involved mines in Sweden, Italy, Australia (pre reinforcement of walls with steel cables cemented in) and at the Con Mine in Canada. Two papers involved backfill material and specifications. Eight papers involved the use of the mathematical models for calculating the stresses developed in the rock mass by computer calculations and therefore, the probable stability. Such calculations are particularly necessary in deep mines. Papers of general interest were entered individually into EDB. (LTN)

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

Science.gov (United States)

Ball, N. M.

2013-10-01

To-date, computing systems have allowed either sophisticated analysis of small datasets, as exemplified by most astronomy software, or simple analysis of large datasets, such as database queries. At the Canadian Astronomy Data Centre, we have combined our cloud computing system, the Canadian Advanced Network for Astronomical Research (CANFAR), with the world's most advanced machine learning software, Skytree, to create the world's first cloud computing system for data mining in astronomy. CANFAR provides a generic environment for the storage and processing of large datasets, removing the requirement for an individual or project to set up and maintain a computing system when implementing an extensive undertaking such as a survey pipeline. 500 processor cores and several hundred terabytes of persistent storage are currently available to users, and both the storage and processing infrastructure are expandable. The storage is implemented via the International Virtual Observatory Alliance's VOSpace protocol, and is available as a mounted filesystem accessible both interactively, and to all processing jobs. The user interacts with CANFAR by utilizing virtual machines, which appear to them as equivalent to a desktop. Each machine is replicated as desired to perform large-scale parallel processing. Such an arrangement enables the user to immediately install and run the same astronomy code that they already utilize, in the same way as on a desktop. In addition, unlike many cloud systems, batch job scheduling is handled for the user on multiple virtual machines by the Condor job queueing system. Skytree is installed and run just as any other software on the system, and thus acts as a library of command line data mining functions that can be integrated into one's wider analysis. Thus we have created a generic environment for large-scale analysis by data mining, in the same way that CANFAR itself has done for storage and processing. Because Skytree scales to large data in

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.

Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data

OpenAIRE

Veale, M; Binns, RDP

2017-01-01

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining (DADM) and fairness, accountability and transparency machine learning (FATML), their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data o...

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

Directory of Open Access Journals (Sweden)

Santana Isabel

2011-08-01

Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

An IPSO-SVM algorithm for security state prediction of mine production logistics system

Science.gov (United States)

Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

2017-06-01

A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

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

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Permit to use experimental electric face... ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Machines Assembled With Certified or Explosion-Proof Components, Field...

Application of the chain saw machine for underground quarry

Energy Technology Data Exchange (ETDEWEB)

Lim, Han-Uk; Baek, Hwan-Jo [Kangwon National University, Chuncheon(Korea); Kim, Chi-Hwan [Woosuk University, Wonju(Korea); Kim, Tae-Soo [Sungshin Mining Co., Jungseun(Korea)

2001-10-31

Many regulatory activities for preservation of the environment make it recently difficult for the stone industry in our country. To reduce environmental hazards and to conserve original surface and woods, some effective underground methods must be adopted. Some new techniques such as chain saw machine, diamond wire saw and water jet cutting can be considered. But application of chain saw machine for underground quarry is proposed in this study. Some technical adoptions with chain saw were carried out at Jungseun marble mine. It is proved that this machine can be effectively adopted to cut dimension stone. With chain saw and diamond wire saw, it can be expected to achieve more effectively cutting the dimension stone. (author). 6 refs., 3 tabs., 6 figs.

The Application of Machine Learning Algorithms for Text Mining based on Sentiment Analysis Approach

Directory of Open Access Journals (Sweden)

Reza Samizade

2018-06-01

Full Text Available Classification of the cyber texts and comments into two categories of positive and negative sentiment among social media users is of high importance in the research are related to text mining. In this research, we applied supervised classification methods to classify Persian texts based on sentiment in cyber space. The result of this research is in a form of a system that can decide whether a comment which is published in cyber space such as social networks is considered positive or negative. The comments that are published in Persian movie and movie review websites from 1392 to 1395 are considered as the data set for this research. A part of these data are considered as training and others are considered as testing data. Prior to implementing the algorithms, pre-processing activities such as tokenizing, removing stop words, and n-germs process were applied on the texts. Naïve Bayes, Neural Networks and support vector machine were used for text classification in this study. Out of sample tests showed that there is no evidence indicating that the accuracy of SVM approach is statistically higher than Naïve Bayes or that the accuracy of Naïve Bayes is not statistically higher than NN approach. However, the researchers can conclude that the accuracy of the classification using SVM approach is statistically higher than the accuracy of NN approach in 5% confidence level.

Simulations and Experiments on Vibration Control of Aerospace Thin-Walled Parts via Preload

Directory of Open Access Journals (Sweden)

Qiong Wu

2017-01-01

Full Text Available Thin-walled parts primarily comprise the entire piece of rough machining, and the material removal rate can surpass 95%. Numerous components with thin-walled structures are preferred in the aerospace industry for their light weight, high strength, and other advantages. In aerospace thin-walled workpiece machining processes and practical applications, they are excited by the vibration. The preload changing the modal stiffness of the part is found and this change causes continuous changes in the natural frequency. Researching on the influence of pretightening force on dynamic characteristics of thin-walled components is highly significant for controlling vibration. In this study, the typical aviation thin-walled part is the research object. Finite element numerical simulation and experimental verification are employed to analyze the dynamic characteristics of 7075 aluminum alloy thin-walled plates under different preloads for exploring the relationship between natural frequency and preload. The relationship is validated by comparative results. Both the simulation and experimental results show that the natural frequencies of plates increase following the augmentation of the preload. Thus, this research introduces the method where vibration of aerospace thin-walled parts is reduced by preload. For practical engineering application, a program showing the relationship between natural frequency and preload is written using Visual Basic language.

Diagnostic integration solutions in the ITER first wall

International Nuclear Information System (INIS)

Martínez, Gonzalo; Martin, Alex; Watts, Christopher; Veshchev, Evgeny; Reichle, Roger; Shigin, Pavel; Sabourin, Flavien; Gicquel, Stefan; Mitteau, Raphael; González, Jorge

2015-01-01

Highlights: • This paper describes the current status of the integration efforts to implement diagnostics in the ITER first wall (FW). • Some diagnostics require a plasma facing element attached to the FW, commonly known as a FW diagnostic. Their design must comply not only with their functional requirements but also with the design of the blankets. • An integrated design concept has been developed. It provides a design that respects the requirements of each system. Thermo-mechanical analyses are on-going to confirm that this configuration respects the heat loads limits on the blanket FW. - Abstract: ITER will have about 50 diagnostic systems for machine protection, plasma control and optimization, and understanding the physics of burning plasma. The implementation in the ITER machine is challenging, particularly for the in-vessel diagnostics, region defined between the vacuum vessel and first wall (FW) contours, where space is constrained by the high number of systems. This paper describes the current status of design integration efforts to implement diagnostics in the ITER first wall. These approaches are the basis for detailed optimization and improvement of conceptual interfaces designs between systems.

Diagnostic integration solutions in the ITER first wall

Energy Technology Data Exchange (ETDEWEB)

Martínez, Gonzalo, E-mail: gonzalo.martinez@iter.org [Technical University of Catalonia (UPC), Barcelona-Tech, Barcelona (Spain); Martin, Alex; Watts, Christopher; Veshchev, Evgeny; Reichle, Roger [ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 St Paul Lez Durance Cedex (France); Shigin, Pavel [ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 St Paul Lez Durance Cedex (France); National Research Nuclear University (MEPhI), Kashirskoe shosse, 115409 Moscow (Russian Federation); Sabourin, Flavien [ABMI-Groupe, Parc du Relais BatD 201 Route de SEDS, 13127 Vitrolles (France); Gicquel, Stefan; Mitteau, Raphael [ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 St Paul Lez Durance Cedex (France); González, Jorge [RÜECKER LYPSA, Carretera del Prat, 65, Cornellá de Llobregat (Spain)

2015-10-15

Highlights: • This paper describes the current status of the integration efforts to implement diagnostics in the ITER first wall (FW). • Some diagnostics require a plasma facing element attached to the FW, commonly known as a FW diagnostic. Their design must comply not only with their functional requirements but also with the design of the blankets. • An integrated design concept has been developed. It provides a design that respects the requirements of each system. Thermo-mechanical analyses are on-going to confirm that this configuration respects the heat loads limits on the blanket FW. - Abstract: ITER will have about 50 diagnostic systems for machine protection, plasma control and optimization, and understanding the physics of burning plasma. The implementation in the ITER machine is challenging, particularly for the in-vessel diagnostics, region defined between the vacuum vessel and first wall (FW) contours, where space is constrained by the high number of systems. This paper describes the current status of design integration efforts to implement diagnostics in the ITER first wall. These approaches are the basis for detailed optimization and improvement of conceptual interfaces designs between systems.

The geomicrobiology of used and disused mines in Britain

International Nuclear Information System (INIS)

Christofi, N.; Philp, J.C.; West, J.M.; Robbins, J.E.

1984-03-01

Several used and disused mines in Britain have been analysed for microbial presence, content and activity. The sites sampled are located in Cornwall, Derbyshire and Cumbria. The mines in Cornwall can be called 'working' and were being operated at the time of sampling. The mine in Derbyshire was disused until recently re-opened by cavers while the mines in Cumbria had remained closed up to the time of sampling. Waters and solid materials have been sampled where detailed microbiology has been undertaken. In Cumbria a detailed description of structures of biological interest was carried out. Both heterotrophic and autotrophic microorganisms have been found in some waters and on mine walls. The actual content of each mine is different according to local conditions and chemistries. The results of the microbiological analyses are given. The origin of these microorganisms cannot be determined although it is likely that they have been introduced by water running down mine shafts from surface strata and/or from excavation processes. Activity measurements have shown that waters in some mines are organic carbon limited. There are indications from the working mines that such carbon would be available from autotrophic populations present within the ecosystem or from backfill material. (author)

TSC mobile mining and extraction technology

Energy Technology Data Exchange (ETDEWEB)

Lavender, W.J. [TSC Company Ltd., Calgary, AB (Canada)

2001-11-01

This Power-Point presentation described an innovative mining and extraction technology developed by Calgary-based TSC Company Ltd. that has provided a major breakthrough in bitumen production from mineable oil sands. The presentation described the process and key mechanical components as demonstrated on oil sands leases. It also described the step change in cost structure and profitability. Oil sands mining provide a hugh resource base with no exploration costs and no decline in production. Despite these advantages, oil sands mining faces the challenge of high capital and operating costs and materials handling. Other challenges include the variability of the ore and environmental impacts. This paper described the fundamentals of the new technology called the Tar Sand Combine (TSC), a continuous mining machine, crusher, cyclone, tailings filter and stacker all in one mobile module. Several viewgraphs were included with the presentation to depict the recovery process as successfully demonstrated at a pilot project. Patent is pending on the process and components. The advantages of the TSC are reduced materials handling, and no tailings ponds are generated since tailings remain where they are mined. The final product is clean bitumen. The specifications of a commercial TSC are: 2000 ton/stream hour mining produce 25,000 bpsd bitumen at 12 per cent ore grade; mined ore bitumen recovery is greater than 95 per cent and the availability factor is 85 per cent. It was concluded that the TSC can maximize oil sands reserves, while providing significant cost savings and environmental benefits. 2 tabs., 24 figs.

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.

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.

Mechanization of operations in underground workings in coal mines and research project trends. [Poland

Energy Technology Data Exchange (ETDEWEB)

Reich, K; Skoczynski, W; Sikora, W

1985-01-01

Structure of black coal reserves of Poland, imported and Polish made equipment for underground mining, prospects for mechanization of selected operations in underground mines and research programs of the KOMAG Center for Mechanization of Mining are evaluated. Prospects for longwall mining with caving or stowing in thick coal seams (slice mining), thin (0.8 to 1.2 m), level or inclined coal seams and steep seams are analyzed. The following equipment for mechanization of underground mining is evaluated: integrated face systems, shearer loaders, chain conveyors, belt conveyors, coal plows, equipment for mine drivage, hoists, drive systems for mining equipment. The following research programs of the KOMAG Center are reviewed: modernization of face systems for coal seams with uncomplicated mining conditions, development of equipment for thin seam mining, development of types of mining equipment for coal seams from 1.5 to 3.0 m thick with dip angles to 25 degrees, modernization of equipment for thick seam mining, increasing efficiency of mine drivage (new types of heading machines, materials handling equipment for mine drivage), mechanization of auxiliary operations in underground coal mines, improving quality of mining equipment, development of equipment for coal preparation, increasing occupational safety in underground mining.

Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining

Directory of Open Access Journals (Sweden)

P. Kalaivani

2015-01-01

Full Text Available With the rapid growth of websites and web form the number of product reviews is available on the sites. An opinion mining system is needed to help the people to evaluate emotions, opinions, attitude, and behavior of others, which is used to make decisions based on the user preference. In this paper, we proposed an optimized feature reduction that incorporates an ensemble method of machine learning approaches that uses information gain and genetic algorithm as feature reduction techniques. We conducted comparative study experiments on multidomain review dataset and movie review dataset in opinion mining. The effectiveness of single classifiers Naïve Bayes, logistic regression, support vector machine, and ensemble technique for opinion mining are compared on five datasets. The proposed hybrid method is evaluated and experimental results using information gain and genetic algorithm with ensemble technique perform better in terms of various measures for multidomain review and movie reviews. Classification algorithms are evaluated using McNemar’s test to compare the level of significance of the classifiers.

Materials for heat flux components of the first wall in fusion reactors

International Nuclear Information System (INIS)

Hoven, H.; Koizlik, K.; Linke, J.; Nickel, H.; Wallura, E.

1985-08-01

Materials of the First Wall in near-fusion plasma machines are subjected to a complex load system resulting from the plasma-wall interaction. The materials for their part also influence the plasma. Suitable materials must be available in order to ensure that the wall components achieve a sufficiently long dwell time and that their effects on the plasma remain small and controllable. The present report discusses relations between the plasma-wall interaction, the reactions of the materials and testing and examination methods for specific problems in developing and selecting suitable materials for highly stressed components on the First Wall of fusion reactors. (orig.)

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

Science.gov (United States)

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

2016-12-01

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

Homopolar machine for reversible energy storage and transfer systems

International Nuclear Information System (INIS)

Stillwagon, R.E.

1978-01-01

A homopolar machine designed to operate as a generator and motor in reversibly storing and transferring energy between the machine and a magnetic load coil for a thermonuclear reactor is described. The machine rotor comprises hollow thin-walled cylinders or sleeves which form the basis of the system by utilizing substantially all of the rotor mass as a conductor thus making it possible to transfer substantially all the rotor kinetic energy electrically to the load coil in a highly economical and efficient manner. The rotor is divided into multiple separate cylinders or sleeves of modular design, connected in series and arranged to rotate in opposite directions but maintain the supply of current in a single direction to the machine terminals

Smart material screening machines using smart materials and controls

Science.gov (United States)

Allaei, Daryoush; Corradi, Gary; Waigand, Al

2002-07-01

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

Qualification Test for Korean Mockups of ITER Blanket First Wall

International Nuclear Information System (INIS)

Kim, S. K.; Lee, D. W.; Bae, Y. D.; Hong, B. G.; Jung, H. K.; Jung, Y. I.; Park, J. Y.; Jeong, Y. H.; Choi, B. K.; Kim, B. Y.

2009-01-01

ITER First Wall (FW) includes the beryllium armor tiles joined to CuCrZr heat sink with stainless steel cooling tubes. This first wall panels are one of the critical components in the ITER machine with the surface heat flux of 0.5 MW/m 2 or above. So qualification program needs to be performed with the goal to qualify the joining technologies required for the ITER First Wall. Based on the results of tests, the acceptance of the developed joining technologies will be established. The results of this qualification test will affect the final selection of the manufacturers for the ITER First Wall

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...

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....

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

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

Science.gov (United States)

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

2012-09-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Development of remote control decontamination machines for BWR nuclear power plants

International Nuclear Information System (INIS)

Miyakawa, Minoru; Nozawa, Katsuro; Yamada, Masuji; Mizutani, Takeshi; Onozuka, Kazuaki

1981-01-01

The dose rate of radiation on the surfaces of equipments and in rooms tends to increase as radioactive substances accumulate with the continuous operation of nuclear power stations. The decontamination works to remove radioactive substances are carried out to prevent the exposure of workers in the case of inspection and repair. In order to reduce the exposure of decontamination workers, to save labor and to shorten decontamination time, Chubu Electric Power Co., Inc., has developed the decontamination machines for the walls of reactor wells, the walls and bottoms of equipment pits, the internal surfaces of suppression chambers, and the internal surfaces of tanks. The decontamination machines have several remote-handling functions: (a) brushing up with sprinkling against complicate surface such as a wall with step, (b) vertical transfer of brushing position with sucking force, (c) sucking out slurries under the water of storage pool or inside the pressure-supression pool, (d) horizontal transfer of suction position with electric motors. (J.P.N.)

INTEGRATED ROBOT-HUMAN CONTROL IN MINING OPERATIONS

Energy Technology Data Exchange (ETDEWEB)

George Danko

2006-04-01

This report describes the results of the 2nd year of a research project on the implementation of a novel human-robot control system for hydraulic machinery. Sensor and valve re-calibration experiments were conducted to improve open loop machine control. A Cartesian control example was tested both in simulation and on the machine; the results are discussed in detail. The machine tests included open-loop as well as closed-loop motion control. Both methods worked reasonably well, due to the high-quality electro-hydraulic valves used on the experimental machine. Experiments on 3-D analysis of the bucket trajectory using marker tracking software are also presented with the results obtained. Open-loop control is robustly stable and free of short-term dynamic problems, but it allows for drifting away from the desired motion kinematics of the machine. A novel, closed-loop control adjustment provides a remedy, while retaining much of the advantages of the open-loop control based on kinematics transformation. Additional analysis of previously recorded, three-dimensional working trajectories of the bucket of large mine shovels was completed. The motion patterns, when transformed into a family of curves, serve as the basis for software-controlled machine kinematics transformation in the new human-robot control system.

Dependence of the mean time to failure of a hydraulic balancing machine unit on different factors for sectional pumps of the Alrosa JSC

Science.gov (United States)

Ovchinnikov, N. P.; Portnyagina, V. V.; Sobakina, M. P.

2017-12-01

This paper presents factors that have a greater impact on the mean time to failure of a hydraulic balancing machine unit working in underground kimberlite mines of the Alrosa JSC, the hydraulic balancing machine unit being the least reliable structural elements in terms of error-free operation. In addition, a multifactor linear dependence of mean time to failure of a hydraulic balancing machine unit is shown regarding it being parts of stage sectional pumps in the underground kimberlite mines of the Alrosa JSC. In prospect, this diagram can allow us to predict the durability of the least reliable structural element of a sectional pump.

Multiaxial loading of large-diameter, thin-walled tube rock specimens

International Nuclear Information System (INIS)

Hecker, S.S.; Petrovic, J.J.

1981-01-01

A large-scale mechanical testing facility permits previously impossible thin-walled tube multiaxial loading experiments on rock materials. Constraints are removed regarding tube wall thickness in relation to rock microstructural features and tube diameter as well as test machine load capacity. Thin-walled tube studies clarify the influence of intermediate principal stress sigma 2 on rock fracture and help define a realistic rock fracture criterion for all multiaxial stressing situations. By comparing results of thin-walled and thick-walled tube fracture investigations, effects of stress gradients can be established. Finally, influence of stress path on rock fracture, an area largely ignored in current rock failure criteria, can be examined in detail using controlled loading changes as well as specimen prestrains

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

Science.gov (United States)

Mohd Khairudin, Nazli; Mustapha, Aida

2014-01-01

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

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.

Measurements of very large deformations in potash salt in conjunction with an ongoing mining operation

International Nuclear Information System (INIS)

Sattler, A.R.; Christensen, C.L.

1980-01-01

Room and pillar deformation were measured in conjunction with a relatively new type of mining operation in a southeastern New Mexico potash mine. The extraction ration was approximately 90 percent in a first mining operation. Due to severe deformations encountered, instrumentation had to be developed/modified for these measurements. This paper concentrates on experiment design, design of special instrumentation, field installation of equipment, and presentation of the data. Measurements made include extensometers in the pillar, in the floor and ceiling in the room between pillars, absolute level measurements, floor ceiling closure, and stress (strain) measurements. Associated laboratory rock mechanics measurements of samples from the mine are being done separately. Two separate room pillar complexes were instrumented. In the first complex, floor-ceiling deformations of approximately 1 inch/day and pillar deformations around 1/2 inch/day were measured. In the second complex, instrumentation was installed while the pillar was a part of a long wall and the subsequent sequential mining (long wall-pillar with only one adjoining room on one side - pillar in the middle of room pillar complex) was observed. Data return from this operation was good

Calculation of parameters of technological equipment for deep-sea mining

Science.gov (United States)

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

2018-03-01

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

Temperature-gradient instability induced by conducting end walls

International Nuclear Information System (INIS)

Berk, H.L.; Ryutov, D.D.; Tsidulko, Yu.A.

1990-04-01

A new rapidly growing electron temperature gradient instability is found for a plasma in contact with a conducting wall. The linear instability analysis is presented and speculations are given for its nonlinear consequences. This instability illustrates that conducting walls can produce effects that are detrimental to plasma confinement. This mode should be of importance in open-ended systems including astrophysical plasmas, mirror machines and at the edge of tokamaks where field lines are open and are connected to limiters or divertors. 16 refs., 2 figs

Underground coal mining - methods, equipment developments and trends

Energy Technology Data Exchange (ETDEWEB)

Singhal, R

1988-12-01

Underground mines are truly beginning to accept the so-called 'high tech' technology evident in other industries. Automation, remote control and robotics have taken an added significance. Wireless communication, mine-wide equipment health and performance monitoring, and transmission of data from deeper levels to surface is moving towards becoming the norm. There is emphasis on developing and applying continuous mining systems, as well as on modifying cyclical discontinuous methods to continuous systems. Multi-purpose equipment is also being developed. Technology transfer is playing its role - equipment and systems from surface coal mining are being applied to underground mining and vice-versa. At the American Mining Congress Exhibition held in Chicago in April 1988, a variety of equipment for underground mining was displayed including coal face equipment such as shearer loaders, conveyors and powered supports, and equipment for room-and-pillar coal mining. The trend continues to be towards high power machines equipped with a variety of electronics and sensors, safety devices, and alarm systems. Ancillary equipment on display covered a variety of cutting drums, cutting tools, conveying equipment and so on. In room-and-pillar mining, the overall emphasis was on moving away from the cyclical nature of the work. Transportation by shuttle cars must be replaced by continuous transport systems such as conveyors. Experience from Australia has shown that the application of continuous haulage and breaker line supports has permitted a doubling of production from room-and-pillar systems. Production levels of 3,000tpd have already been achieved, and 4,000tpd is considered achievable.

The BUK-GPK suspended drilling equipment for the GPK heading machine

Energy Technology Data Exchange (ETDEWEB)

1982-11-01

The BUK-GPK system developed by PechorNIIproekt is used for borehole drilling in rocks with compression strength to 12 degrees on the Protod'yakonov scale. The BUK-GPK is used for drilling boreholes for roof bolts in development workings driven by heading machines under difficult conditions. The GPK heading machine with the BUK-GPK drill is 10 m long, 2.1 m high and 2.1 m wide. A borehole is up to 50 mm in diameter, rotating speed ranges from 170 to 315 rpm. Drillings are removed from a boreholes by flushing using water. The system is equipped with remote control. The BUK-GPK system was tested at the Pechora basin during mine drivage in a coal seam from 1.4 to 1.5 m thick. The BUK-GPK was reliable. It permitted labor productivity and occupational safety during during mine drivage to be increased. Commercial production of the BUK-GPK drill is recommended. (In Russian)

Efficiency of measures aimed at improving health by normalization of temperature conditions in the Kochegarka mine

Energy Technology Data Exchange (ETDEWEB)

Litvinov, G.I.; Nifonov, V.P.; Kobets, A.N.

1981-06-01

This paper evaluates effects of air conditioning in the Kochegarka black coal mine on miners' health. Up to 1975 air temperature in the lowest mine horizon located at a depth of 970 m ranged from 26 to 32 C, in summer from 34 to 36 C. Air humidity ranged from 94 to 98%. Since 1975 KhTMF-248-4000 freon air cooling machines have been used in the mine; their capacity amounts to 3.8 x 10/SUP/6 kcal/h. Use of air cooling systems reduces air temperature to permissible limits. Air temperature measured at a distance of 1 km from mine shaft ranges from 24 to 26 C, and air humidity from 90 to 95%. At a distance of 1.5 km from the mine shaft air temperature in conveyor roadways is 26.4 C, in dead-end development workings 27 C, and at working faces 26 C (with air humidity ranging from 96 to 98%). ARVP systems for local air cooling are used at places distant from the mine shaft. The ARVP reduces air temperature from 2 to 4.5 C at a distance ranging from 4 to 8 m from the machine. Reducing air temperature, combined with other measures aimed at improving miners' health, has caused a decrease in miner absenteeism due to illness by 25.4%.

Forming the management model in industrial partnerships of the machine-building complex of Ukraine

OpenAIRE

Reshetilova, T.; Kuvaieva, T.

2016-01-01

Stages of development the processes of forming the industrial networks, technological and logistic chains, partnership and their varieties are analyzed. Factors that determine the rate and scale of the process of forming the partnerships in the machine-building complex of Ukraine are established. A group of the factors that lead to forming the vertical partnership based on Partner Relationship Management (PRM) in mining machinery and mining industry are determined and analyzed. It is possible...

The Analisis Sentimen Sosial Media Twitter Dengan Algoritma Machine Learning Menggunakan Software R

Directory of Open Access Journals (Sweden)

Jaka Aulia Pratama

2017-10-01

Full Text Available Media sosial adalah wadah untuk mengungkapkan opini terhadap suatu topik tertentu. Ketersediaan informasi dan opini dari para pengguna media sosial merupakan kumpulan dokumen data berupa teks yang amat sangat besar dan berguna untuk kepentingan penelitian maupun membuat suatu keputusan bagi pihak – pihak tertentu. Text Mining bisa didefinisikan sebagai proses penggalian informasi di mana pengguna berinteraksi dengan kumpulan dokumen dari waktu ke waktu dengan menggunakan suatu alat analisis. Analisis sentimen atau Opinion Mining adalah salah satu studi di bidang komputasi yang berhubungan dengan kasus publik mengenai opini, penilaian, sikap, dan emosi. Penelitian ini akan menggunakan metode Machine Learning pada analisis sentimen pengguna layanan jejaring sosial Twitter terhadap Donald Trump dan Barack Obama dalam 20000 tweets. Nilai akurasi metode Machine Learning yang diperoleh cukup tinggi yaitu 87.52% untuk Data Training dan 87.4% untuk Data Testing.

Underground roadway drivage with heading machines in Indian coal industry

Energy Technology Data Exchange (ETDEWEB)

Mukherjee, T.K.

1983-03-01

Heading machines have assumed a very important place in underground roadway drivage. They are not only a compromise between ''drill-and-blast'' technique and full-face machines, but are also an economic and versatile form of mechanised roadway drivage. Since the advantages gained by heading machines are considerable, the use of these machines is becoming popular in underground roadway drivage. Experience with continuous miner and heading machines in Indian coal mines is very limited compared to that of Western countries. In 1964-65, for the first time, two units of Lee Norse Miner were used at Kunostoria Colliery of Bengal Coal Company. In 1966, two units of Joy Continuous Miner were introduced at Chalkari Colliery of National Coal Development Corporation, but had to be adandoned because of heavy make of water at the installation site. A Russian PK-3 heading machine was used limitedly during the development of Banki Colliery, Madhya Pradesh. A Demag Unicorn VS-1 machine operated for the development of roadways at Jitpur and Chasnala Collieries of IISCO between 1967-70. With this machine, progress of 7 m per day was attained in level roadways and of about 2 m per day in steep raises.

Technology Transfer at Edgar Mine: Phase 1; October 2016

Energy Technology Data Exchange (ETDEWEB)

Augustine, Chad R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bauer, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nakagawa, Masami [Colorado School of Mines, Golden, CO (United States); Zhou, Wendy [Colorado School of Mines, Golden, CO (United States)

2017-09-14

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

Survey of Machine Learning Methods for Database Security

Science.gov (United States)

Kamra, Ashish; Ber, Elisa

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

Stress measurements in the Naesliden Mine

Energy Technology Data Exchange (ETDEWEB)

Leijon, B. [Univ. of Luleaa, Sweden; Carlsson, H.; Myrvang, A.

1980-05-15

Determinations of virgin stresses were performed at an early stage of the Naesliden Project in order to obtain input data for the finite element models of the mine. The Leeman three-dimensional overcoring technique was used at five locations on levels ranging from 210 m to 460 m below surface. Stress data were obtained at four of these locations. The results show an excess of horizontal stresses whilst the vertical stress is in accordance with the gravitational load from the overburden. The major and intermediate principal stresses are sub-horizontal and directed respectively perpendicular and parallel to the schisotsity of the wall rock and the strike of the tabular ore body. The minor principal stress is directed almost vertically. Stresses were also measured close to a stope on 300 m level in the mine. Biaxial and triaxial overcoring measurements were made at eighteen points between 0.25 m and 7.2 m above the roof of the stope. The stresses were found to have magnitudes of about 70 MPa close to the roof and to decrease rapidly with the distance from the roof. Stress measurements were made in connection with slot blastings in the foot wall, the latter measure being made in an attempt to de-stress the roof of stope 3. Two methods were used for stress monitorings, both showing that expected stress changes did not take place. Long-term stress guages have been installed in the ore body in order to monitor expected re-distributions of stresses due to mining. So far, the recorded stress changes are below 5 MPa.

Initial Ferritic Wall Mode studies on HBT-EP

Science.gov (United States)

Hughes, Paul; Bialek, J.; Boozer, A.; Mauel, M. E.; Levesque, J. P.; Navratil, G. A.

2013-10-01

Low-activation ferritic steels are leading material candidates for use in next-generation fusion development experiments such as a prospective US component test facility and DEMO. Understanding the interaction of plasmas with a ferromagnetic wall will provide crucial physics for these experiments. Although the ferritic wall mode (FWM) was seen in a linear machine, the FWM was not observed in JFT-2M, probably due to eddy current stabilization. Using its high-resolution magnetic diagnostics and positionable walls, HBT-EP has begun exploring the dynamics and stability of plasma interacting with high-permeability ferritic materials tiled to reduce eddy currents. We summarize a simple model for plasma-wall interaction in the presence of ferromagnetic material, describe the design of a recently-installed set of ferritic shell segments, and report initial results. Supported by U.S. DOE Grant DE-FG02-86ER53222.

Participation of Ostrava Mining College in training of personnel for nuclear technology

International Nuclear Information System (INIS)

Kuchar, L.

1983-01-01

The mining and geology faculty of the Mining College educates specialists for surveying, extraction and treatment of uranium raw materials. In 1980 the faculty introduced an interdisciplinary study course for the technology of drilling, geological surveying and mine surveying. A contract has been signed between the College and the Czechoslovak Uranium Industry on specialized and scientific cooperation, expertise, postgraduate courses, etc. The metallurgy faculty of the College introduced the nuclear metallurgy specialization in 1964. Students attending the course will acquire knowledge not only on the metallurgy of nuclear fuels, cladding, shielding and structural materials, their production and processing but also on the science of metals, heat treatment, metal testing, etc. A study course is now being prepared relating to materials problems of nuclear power which is oriented to modern methods of material assessment for nuclear power facilities, light water reactors and their components. In 1976 the Mining College also introduced the nuclear power specialization at its mechanical engineering and electrical engineering faculties. In the years 1976-1982 more than fifty students graduated from the faculty whose theses were oriented to the problems of welding, surfacing, machining and upgrading of WWER-440 and WWER-1000 components. In the years 1979-82 the College ran a postgraduate study course on ''Machines and equipment of nuclear power plants''. (E.S.)

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.  

Mining and global environmental challenges

Energy Technology Data Exchange (ETDEWEB)

Greeff, J C; Bailey-McEwan, M [Chamber of Mines of South Africa, Johannesburg (South Africa)

1992-04-01

At least half of South Africa's gold production is presently dependent on CFC11 an CFC12 as refrigerants in water chilling machines used in cooling the underground workings. The South African Government will ratify the revised Montreal Protocol on substances that deplete the ozone layer which will mean CFCs will have to be phased out probably by 1997. HFC134 or HFC22 are possible replacements for CFC but present costs of converting machines are high. The article goes on to discuss the contribution of CFCs and CO{sub 2} to global warming and model simulations and predictions of climate change. Likely effects of growing concern about global warming on the coal mining industry are the possible limitations on the use of coal and the increased need for clean coal technology. 12 refs., 5 figs., 3 tabs.

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.

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

Science.gov (United States)

Kadela, Marta; Chomacki, Leszek

2017-10-01

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

Bucket wheel excavator performances at Neyveli lignite mine

Energy Technology Data Exchange (ETDEWEB)

Kumaraswamy, S; Mozumdar, B K

1987-03-01

Bucket-wheel excavators have been in use at the Neyveli Lignite Mine in the State of Tamil Nadu, India, since the early nineteen-sixties. The mining environment has been particularly harsh for BWE application. The adverse influencing factors are the hardness of the over-burden formation, high abrasivity of rock and artesian ground water conditions. In this paper, the performances of the BWEs at Neyveli have been statistically analysed to determine the effects of physico-mechanical properties of overburden, blasting and rainfall on machine productivity, availability, wear-and-tear of bucket teeth, power consumption, production efficiency and cost of mining. An empirical relationship between the production efficiency, defined as the ratio of actual production rate to the theoretical one, and the bench height and width, height of slices, specific cutting resistance of the overburden material and its clay content, consumption of explosives, and conveyor length has been established.

Data Mining Learning Models and Algorithms on a Scada System Data Repository

Directory of Open Access Journals (Sweden)

Mircea Rîşteiu

2010-06-01

Full Text Available This paper presents three data mining techniques applied
on a SCADA system data repository: Naijve Bayes, k-Nearest Neighbor and Decision Trees. A conclusion that k-Nearest Neighbor is a suitable method to classify the large amount of data considered is made finally according to the mining result and its reasonable explanation. The experiments are built on the training data set and evaluated using the new test set with machine learning tool WEKA.

The new technology of dividing wall in stope

International Nuclear Information System (INIS)

Li Zhiguo

1999-01-01

The author analyzes advantages and disadvantages of the ordinary separating methods between stopes at deep mine, points out the main problems of the original projects constructing dividing wall, presents an idea of new technology which can overcome the main problems, predicts effect adopting the new technology, and analyzes that feasibility applying the new technology to construct mortar pad in stope and dyke-dam

Methodes de compensation des erreurs d'usinage utilisant la mesure sur machines-outils

Science.gov (United States)

Guiassa, Rachid

proposed compensation model. The coordinate measurement machine is used to verify the on machine measurement of a ring gauge. For a simple straight thin wall, an error of 78 microm is reduced to less than +/- 3 microm. For a circular wall with variable stiffness using a multi-cut process, the error is reduced from -60 microm to +/-6 microm. For a free form thin wall similar to airfoil profile represented with the B-Spline, the improvement is from +140 microm to +/-20 microm.

Characteristics of a large reversed field pinch machine, TPE-RX

International Nuclear Information System (INIS)

Yagi, Y.; Shimada, T.; Hirano, Y.; Sekine, S.; Sakakita, H.; Koguchi, H.; Kiyama, S.; Maejima, Y.; Hirota, I.; Hayase, K.; Sato, Y.; Sugisaki, K.; Oyabu, I.; Hasegawa, M.; Yamane, M.; Sato, F.; Kuno, K.; Minato, T.; Kiryu, A.; Takagi, S.; Sako, K.; Kudough, F.; Urata, K.; Orita, J.; Kaguchi, H.; Sago, H.; Ue, K.

1998-01-01

Construction of a new, large reversed field pinch (RFP) machine called TPE-RX was complete at the end of 1997 as a successor of the previous TPE-1RM20 machine at the Electrotechnical Laboratory (ETL). RFP configuration has been successfully obtained in March 1998. The optimization of the operating condition and discharge cleaning of the wall are presently undergoing with the first physics experiments. This paper is the first report of TPE-RX especially on the goals, overall machine characteristics and the present status. Other papers accompanying with this one will present specific topics on the magnetic coil system and the vacuum vessel system. (author)

Characteristics of a large reversed field pinch machine, TPE-RX

Energy Technology Data Exchange (ETDEWEB)

Yagi, Y.; Shimada, T.; Hirano, Y.; Sekine, S.; Sakakita, H.; Koguchi, H.; Kiyama, S.; Maejima, Y.; Hirota, I.; Hayase, K.; Sato, Y.; Sugisaki, K. [Electrotechnical Lab., Tsukuba-shi, Ibaraki (Japan); Oyabu, I.; Hasegawa, M.; Yamane, M.; Sato, F.; Kuno, K.; Minato, T.; Kiryu, A.; Takagi, S.; Sako, K. [Mitsubishi Electric Corp. (Japan); Kudough, F.; Urata, K.; Orita, J.; Kaguchi, H.; Sago, H.; Ue, K. [Mitsubishi Heavy Industries Ltd. (Japan)

1998-07-01

Construction of a new, large reversed field pinch (RFP) machine called TPE-RX was complete at the end of 1997 as a successor of the previous TPE-1RM20 machine at the Electrotechnical Laboratory (ETL). RFP configuration has been successfully obtained in March 1998. The optimization of the operating condition and discharge cleaning of the wall are presently undergoing with the first physics experiments. This paper is the first report of TPE-RX especially on the goals, overall machine characteristics and the present status. Other papers accompanying with this one will present specific topics on the magnetic coil system and the vacuum vessel system. (author)

Numerical analysis of special-shaped surface in abrasive flow machining

Science.gov (United States)

Li, Junye; Zhou, Zengwei; Wu, Guiling; Lu, Hui; Sun, Zhihuai

2018-03-01

Solid-liquid two-phase abrasive flow machining is a method to effectively polish the surface of Special-shaped surface parts. Based on the processing characteristics of the abrasive flow machining. The standard model and the pressure-coupled SIMPLEC algorithm are used. The shear force and velocity of the near-wall surface of the runner of the solid-liquid two-phase abrasive machining with different inlet pressure are analyzed. The numerical simulation results show that the inlet pressure has little effect on the velocity, and the shear force has a linear relationship with the inlet pressure. To obtain a better polishing effect, the outlet pressure can be appropriately increased.

Explaining and predicting workplace accidents using data-mining techniques

International Nuclear Information System (INIS)

Rivas, T.; Paz, M.; Martin, J.E.; Matias, J.M.; Garcia, J.F.; Taboada, J.

2011-01-01

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Zhijie Wen

2014-01-01

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

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...

Analysis of gas migration patterns in fractured coal rocks under actual mining conditions

Directory of Open Access Journals (Sweden)

Gao Mingzhong

2017-01-01

Full Text Available Fracture fields in coal rocks are the main channels for gas seepage, migration, and extraction. The development, evolution, and spatial distribution of fractures in coal rocks directly affect the permeability of the coal rock as well as gas migration and flow. In this work, the Ji-15-14120 mining face at the No. 8 Coal Mine of Pingdingshan Tian’an Coal Mining Co. Ltd., Pingdingshan, China, was selected as the test site to develop a full-parameter fracture observation instrument and a dynamic fracture observation technique. The acquired video information of fractures in the walls of the boreholes was vectorized and converted to planarly expanded images on a computer-aided design platform. Based on the relative spatial distances between the openings of the boreholes, simultaneous planar images of isolated fractures in the walls of the boreholes along the mining direction were obtained from the boreholes located at various distances from the mining face. Using this information, a 3-D fracture network under mining conditions was established. The gas migration pattern was calculated using a COMSOL computation platform. The results showed that between 10 hours and 1 day the fracture network controlled the gas-flow, rather than the coal seam itself. After one day, the migration of gas was completely controlled by the fractures. The presence of fractures in the overlying rock enables the gas in coal seam to migrate more easily to the surrounding rocks or extraction tunnels situated relatively far away from the coal rock. These conclusions provide an important theoretical basis for gas extraction.

Universal machine ''Shtrek'' and the tractor-lifter with pneumatic-equipment control. [Auxiliary multipurpose materials handling equipment

Energy Technology Data Exchange (ETDEWEB)

Bal' bert, B M; Borumenskiy, V A; Lishenko, A P; Mitchenko, G A

1982-01-01

The machine ''Shtrek'' is described. It makes it possible to mechanize over 20 auxiliary operations: loading-unloading operations: extraction of old and deformed timbering; dissmantling of obstructions; erection of different types of timbering; making and restoring of drainage channels; laying and straightening of a drift and its leveling; assembly and disassembly of pipelines and mine equipment, etc. Depending on the type of operation, the machine has the corresponding suspended equipment. The elementary variant has a limited area of application at mines of the central region of the Dunbass. Currently a pneumatic variant of the machine ''Shtrek'' has been developed. The electric motor and the starter of the pumping equipment of the machine have been replaced by a pneumatic motor and pneumatically controlled valve KTM-50. In this case there was significant reduction in the weight of the pumping equipment and in its overall dimensions; the electric drive of the hydraulic distributors for controlling the mechanisms were replaced by simpler pneumatic ones; the logical circuit of the control system was constructed on the USEPPA elements. A specialized tractor-lifter designed for moving suspended loads is described for auxiliary operations in the near-face zone of the preparatory drifts. The machine also lifts and lowers the boom, rotates the boom by 270/sup 0/ and additionally lifts and lowers the weight-lifting hook.

On deformation of thin-walled parts while turning on the lathes

Directory of Open Access Journals (Sweden)

E. V. Arbuzov

2014-01-01

Full Text Available In a number of industries such as aviation engineering, instrumentation engineering, etc. the nonrigid thin-walled parts are a widespread sort of products. For their turning on the lathes the specially designed arrangements are necessary to prevent parts from deformation caused by the action of cutting force and retaining pressure. To create and use the arrangements extra costs are needed, and it, as a consequence, leads to the growth of production price. Potentially, there is another approach. It is to machine using the standard arrangements under special "soft" cutting operation conditions, which are characterized by reduced forces to act on the part, thus decreasing process deformations to the appropriate level. It may be a priori expected that such approach is economically more preferable. Unfortunately, it is difficult to conduct a comparative assessment of these two alternatives to choose a preferable version because of limited data on studies and implementation of the second alternative. Thereupon, to learn the thin-walled deformations versus their treatment conditions is of interest.The aim of the paper is to have general information on topology and elastic deformation value of thin-walled parts, machined on the lathes. The objective is to assess a perspective for further potentially possible activities to develop a concept of machining the thin-walled parts with controlled deformation due to selecting the "soft" cutting operation conditions.The paper studies the thin-walled steel parts of class "Tube" and "Disk" in the role of force action with their dimensions within the range of 5-200 mm for the length, 60-250 mm for diameter, and 4-25 mm for the wall thickness. It considers a chucked work-holding scheme and two machining types, namely external turning cut (for parts of class "Tube" and cross butt turning (for parts of class "Disk". Three stages of machining have been simulated for each type of machining, namely rough (Ra 12.5; IT10

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.

Obstacle detection system for underground mining vehicles

Energy Technology Data Exchange (ETDEWEB)

Cohen, P.; Polotski, V.; Piotte, M.; Melamed, F. [Ecole Polytechnique de Montreal, Montreal, PQ (Canada)

1998-01-01

A device for detecting obstacles by autonomous vehicles navigating in mine drifts is described. The device is based upon structured lighting and the extraction of relevant features from images of obstacles. The system uses image profile changes, ground and wall irregularities, disturbances of the vehicle`s trajectory, and impaired visibility to detect obstacles, rather than explicit three-dimensional scene reconstruction. 7 refs., 5 figs.

Machine Learning Methods to Predict Diabetes Complications.

Science.gov (United States)

Dagliati, Arianna; Marini, Simone; Sacchi, Lucia; Cogni, Giulia; Teliti, Marsida; Tibollo, Valentina; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

2018-03-01

One of the areas where Artificial Intelligence is having more impact is machine learning, which develops algorithms able to learn patterns and decision rules from data. Machine learning algorithms have been embedded into data mining pipelines, which can combine them with classical statistical strategies, to extract knowledge from data. Within the EU-funded MOSAIC project, a data mining pipeline has been used to derive a set of predictive models of type 2 diabetes mellitus (T2DM) complications based on electronic health record data of nearly one thousand patients. Such pipeline comprises clinical center profiling, predictive model targeting, predictive model construction and model validation. After having dealt with missing data by means of random forest (RF) and having applied suitable strategies to handle class imbalance, we have used Logistic Regression with stepwise feature selection to predict the onset of retinopathy, neuropathy, or nephropathy, at different time scenarios, at 3, 5, and 7 years from the first visit at the Hospital Center for Diabetes (not from the diagnosis). Considered variables are gender, age, time from diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), hypertension, and smoking habit. Final models, tailored in accordance with the complications, provided an accuracy up to 0.838. Different variables were selected for each complication and time scenario, leading to specialized models easy to translate to the clinical practice.

X-ray radiometric method of ore quality monitoring during mining

International Nuclear Information System (INIS)

Ivanyukovich, G.A.

1979-01-01

The method is basically applied for sampling ore deposits, mainly of nonferrous and rare metals. It can be used for determining one, two or three elements in the deposit. In the USSR, the method has so far been used in Far East tin deposits and in the North Caucasus tungsten-molybdenum deposit. It is used for the analysis of boreholes, shaft walls, mined ore and ore material intended for enriching. The instruments used include single-channel gamma spectrometers using scintillation or proportional counters as detectors. Logging instruments include dual-channel spectrometers featuring automatic gain control and data processing devices. The instruments are designed for separating elements with atomic numbers 19 to 88 from mine wall materials and with atomic numbers 26 to 88 in boreholes at concentrations exceeding 0.1% and 0.01% for tin and silver, respectively. The economic benefit is shown of the introduction of the method using the Sadon lead-zinc plant and Khrustalnensk ore treatment plant as examples. (H.S.)

DEM study of granular flow around blocks attached to inclined walls

Science.gov (United States)

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

2017-06-01

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

DEM study of granular flow around blocks attached to inclined walls

Directory of Open Access Journals (Sweden)

Samsu Joel

2017-01-01

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

Development of the testing procedure for units and elements of mining equipment

Directory of Open Access Journals (Sweden)

P. B. Gerike

2017-09-01

Full Text Available The author considers in detail the stages of creating a testing procedure for mining equipment based on the complex implementation of principles of nondestructive testing and technical diagnostics. The author substantiates effectiveness of application of a complex diagnostic approach for assessing the state of metal structures and energy-mechanical equipment of mining machines. The opportunity for timely detection of defects, regardless of their type and degree of danger, presents itself only with a wide application of the modern methods of vibration diagnostics and nondestructive testing. The author substantiates the effectiveness of specific combination of methods of nondestructive testing, most optimally suited for solving given tasks. The article contains the developed complex of more than 120 diagnostic rules, suitable for performing automated analysis of vibroacoustic signal and revealing the main damages of energy-mechanical equipment based on selective groups of informative frequencies. The author formulates the main criteria that one can use as a basic platform for improving the methodology for normalizing the parameters of mechanical oscillations. The developed diagnostic criteria became a basis for the development of individual spectral masks suitable for performing the analysis of parameters of vibroacoustic waves generated during operation of mining equipment. The author proves necessity of transition of repair and maintenance divisions of industrial enterprises to the system of maintenance of machinery according to its actual technical state, and the developed complex of diagnostic rules for detecting defects can serve as a platform for the implementation of basic elements of this system. The author substantiates the principal validity of the developed methodology for testing mining machines equipment and its individual elements, such as the predictive modeling of degradation of technical state of mining equipment and the

Fiscal 1998 engineer interexchange project (coal mine technology field). Preliminary survey on the international interexchange project in America; 1998 nendo gijutsusha koryu jigyo (tanko gijutsu bun'ya) kokusai koryu jigyo. Jizen chosa (Beikoku)

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-03-01

As a part of the fiscal 1998 international interexchange project in a coal mine technology field, the survey was made in America. Geological engineering problem has large effect on the protection and productivity of underground coal mines. Promotion of long wall mining has contributed to reduction of disasters, however, recently deaths due to roof collapse and wall collapse are on the increase. A roof evaluation technique was developed for adequate selection of mining methods and support design, and its standardization and diffusion are in promotion. Integration and improvement advanced in facility technology because of worldwide integration by acquisition of coal mine facility manufacturers. Introduction of high-power high-capacity facilities is increasing with introduction of large long wall working faces, and development of rear transport system technology and labor saving by remote control are also in promotion according to such trend. As automation and labor saving technology of mining facilities, the automated direction detection and control system by laser and gyroscope is under development. (NEDO)

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

Science.gov (United States)

Jimeno Yepes, Antonio; Berlanga, Rafael

2015-02-01

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

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

Identification of Work-Related Musculoskeletal Disorders in Mining

Science.gov (United States)

Weston, Eric; Pollard, Jonisha P.

2016-01-01

Work-related musculoskeletal disorder (WMSD) prevention measures have been studied in great depth throughout various industries. While the nature and causes of these disorders have been characterized in many industries, WMSDs occurring in the U.S. mining sector have not been characterized for several years. In this report, MSHA accident/injury/illness data from 2009 to 2013 were characterized to determine the most frequently reported WMSDs in the U.S. mining sector. WMSDs were most frequently reported in workers with less than 5 years or more than 20 years of mining experience. The number of days lost from work was the highest for shoulder and knee injuries and was found to increase with worker age. Underground and surface coal, surface stone and stone processing plants experienced the greatest number of WMSDs over the period studied. WMSDs were most commonly caused by an employee suffering from an overexertion, falls or being struck by an object while performing materials handling, maintenance and repair tasks, getting on or off equipment or machines, and walking or running. The injury trends presented should be used to help determine the focus of future WMSD prevention research in mining. PMID:27294012

Automation of strata bolting in iron mines

Energy Technology Data Exchange (ETDEWEB)

Belin, M; Lethuaire, M

1978-01-01

The Moyeure iron mine (Lorraine), with an output of 16,000 t/day, works 2 seams separated by a dirt band 6.50 m thick. The tyre-mounted Diesel Secoma jumbo for bolting operations can insert resin-embedded bolts 1.70 m in length. The jumbo is fitted with a standard universal boom with two settings - one for drilling and one for bolting. As the operator has to work in the unbolted zone in order to offer up the bolt on the boom and insert the resin cartridge, the mine in conjunction with the manufacturers, Secoma, have improved the safety and performance of the machine by adding three special attachments to the standard boom: a reamer, a resin-injection system and a bolt supply-magazine. Gives details of the results achieved. (In French)

THE VERIFICATION BRAKE MECHANISM OF WINDING MACHINES WITH SINGLE CABLE DRIVING WHEELS ON

Directory of Open Access Journals (Sweden)

Răzvan Bogdan ITU

2017-12-01

Full Text Available The development in safe conditions of the extracting process continuously imposes the need of optimal functioning of the extracting installations as important links in the transport flow. Diagnosis of winding engine brake mechanism in mines is important to provide normal extraction vessel movement in the shaft, or stopping machines in a certain position of the vessels in disturbances or failures. The paper presents the calculus of safety coefficients in the use of safety and maneuver brakes. Mine winding engines brake mechanisms is important to provide normal extraction vessel movement along the shaft, or stopping the engine in a certain position of the vessel in disturbances or failures. To assess the real safety coefficient, results obtained by tensiometric measurements were used. After diagnosis, necessary information is obtained to improve present maintenance system and repair this category of machines in view of increasing safety in use of winding installations, with possibility of monitoring brake mechanism...

Twenty third scientific conference on research-scientific problems of constructing mine buildings and metallurgical plants

Energy Technology Data Exchange (ETDEWEB)

Swiadrowski, W

1978-01-01

Annual conference was held in Krynica from 16-23 September 1977. One hundred and nineteen papers were delivered, of these 24 papers were on mine buildings. It was noted that damage caused by underground coal mining is prevalent and characterized by a tendency to increase. In the middle of the 1970s damages paid by mines (mainly by coal mines) reached 5 billion zlotys yearly. Damages which were not compensated, and social cost of mining damages are not included in the calculation. The following problems were discussed: interaction between foundations of buildings with ground in areas affected by deformations; influnce of underground coal mining on properties of soil; improving construction of large industrial plants located on grounds characterized by surface deformations; influence of underground coal mining on deformations of walls of sedimentation tanks; complex utilization of mined deposits in the Upper Silesian basin, Rybnik basin and in the Lublin black coal basin (coal and other minerals). (In Polish)

Assessment of the Manufacturing Possibility of Thin-Walled Robotic Portals for Conveyor Worklace

Directory of Open Access Journals (Sweden)

Peter Michalik

2018-03-01

Full Text Available The paper discusses evaluation of machining solutions for oversized thin-walled robotic portal component for conveyance workplaces. The following portal CNC machining centers have been selected. Firstly, a FSGC 300 “portal type” portal was proposed, with a 50000 mm “X” axis and Heidenhain control system, the second portal was a DMU 340 portal with the maximum axis “X” of 6000 mm and Siemens Sinumerik control system and the last portal was the VF-10 / 40 one, with the maximum axis “X” of 3048 mm and Fanuc control system. Further, the method of fixing a thin-walled robotic portal is designed and individual options are evaluated for their economy. The CAM software application used for programming the production was SolidWorks.

Heat transfer phenomena in the first wall of the RFX fusion experiment

International Nuclear Information System (INIS)

Oliveira Pauletti, R.M. de

1988-12-01

The thermal analysis of the first wall (FW) of the RFX machine is presented. RFX is a large fusion experiment under construction at Padua, Italy. The RFX FW is briefly described, together with the critical thermal conditions. The numerical analyses performed to predict the FW thermal behaviour are presented. 1-D and 2-D finite element models give accurate predictions of the FW temperatures and of the thermal exchanges in the machine environment. (author) [pt

Investigation for closedown activities in the uranium mine Zirovski vrh

International Nuclear Information System (INIS)

Cadez, F.; Likar, B.; Logar, Z.

1995-01-01

The uranium mine Zirovski vrh was temporarily shut down by order of Government of the Republic of Slovenia in the second half of the year 1990. After the Slovenian parliament passed the law on definite closing down of the uranium mine exploitation and on rehabilitation the effect of mining on the environment in July 1992 was starting to make the Programme of the Permanent Closing down of the Uranium ore Exploitation and Permanent Protection of the Environment in Uranium Mine that is in final phase. In the meantime the studies that would define necessary parameters for elaborating the projects of closure have been done. Two essential studies for the realization of closure of mine are working out: 1. Previous dewatering of the deposit by boreholes for diminishing of pollution of mine water by uranium; 2. Filling of partially collapsed stops by hydromettallurgical waste to assure permanent stability above the mine spaces. The aim of the first study is to reduce percolation of mine water through the mineralized parts of the deposit by drilling boreholes in the footwall and in the hanging wall. Pollution of mine water which outflows from the lowest tunnel in the local creek Brebovscica should be diminished. Tests of stability and lixiviation on the cubes that are made of hydrometallurgical waste are the topic of the second study. Cement and different additives are added in the cubes and testings have been made in situ. (author). 3 refs, 3 figs, 2 tabs

Knowledge Exchange between Poland and Vietnam in Mining and Geology - the Status Quo and Future Development

Science.gov (United States)

Nguyen, Nga; Pham, Nguyet

2018-03-01

From the beginning of the 21st century, knowledge exchange between Poland and Vietnam in mining and geology has been focusing in technology, education and training. Since years, Polish academic and commercial partners have been developing a close collaboration with Vietnam National Coal - Mineral Industries Holding Corporation Limited. Major outcomes of the collaboration are installations and operation of mining equipments and machines in Vietnamese mining companies, and excellent training programs for graduate and post graduate students and mining staff for both countries, etc. From aspects of knowledge management in globalization, the article highlights the outstanding outcomes of knowledge exchanges between the two countries, outlines cultural and economic challenges for the exchange and proposes some improvement in the future.

Mining Trust Relationships from Online Social Networks

Institute of Scientific and Technical Information of China (English)

Yu Zhang; Tong Yu

2012-01-01

With the growing popularity of online social network,trust plays a more and more important role in connecting people to each other.We rely on our personal trust to accept recommendations,to make purchase decisions and to select transaction partners in the online community.Therefore,how to obtain trust relationships through mining online social networks becomes an important research topic.There are several shortcomings of existing trust mining methods.First,trust is category-dependent.However,most of the methods overlook the category attribute of trust relationships,which leads to low accuracy in trust calculation.Second,since the data in online social networks cannot be understood and processed by machines directly,traditional mining methods require much human effort and are not easily applied to other applications.To solve the above problems,we propose a semantic-based trust reasoning mechanism to mine trust relationships from online social networks automatically.We emphasize the category attribute of pairwise relationships and utilize Semantic Web technologies to build a domain ontology for data communication and knowledge sharing.We exploit role-based and behavior-based reasoning functions to infer implicit trust relationships and category-specific trust relationships.We make use of path expressions to extend reasoning rules so that the mining process can be done directly without much human effort.We perform experiments on real-life data extracted from Epinions.The experimental results verify the effectiveness and wide application use of our proposed method.

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

Science.gov (United States)

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

2008-10-01

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

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…

Design of instrumentation and software for precise laser machining

Science.gov (United States)

Wyszyński, D.; Grabowski, Marcin; Lipiec, Piotr

2017-10-01

The paper concerns the design of instrumentation and software for precise laser machining. Application of advanced laser beam manipulation instrumentation enables noticeable improvement of cut quality and material loss. This factors have significant impact on process efficiency and cutting edge quality by means of machined part size and shape accuracy, wall taper, material loss reduction (e.g. diamond) and time effectiveness. The goal can be reached by integration of laser drive, observation and optical measurement system, beam manipulation system and five axis mechanical instrumentation with use of advanced tailored software enabling full laser cutting process control and monitoring.

Mining user-generated geographic content : an interactive, crowdsourced approach to validation and supervision

NARCIS (Netherlands)

Ostermann, F.O.; Garcia Chapeton, Gustavo Adolfo; Zurita-Milla, R.; Kraak, M.J.; Bergt, A.; Sarjakoski, T.; van Lammeren, R.; Rip, F.

2017-01-01

This paper describes a pilot study that implements a novel approach to validate data mining tasks by using the crowd to train a classifier. This hybrid approach to processing successfully addresses challenges faced during human curation or machine processing of user-generated geographic content

The participation of the Experimental Design Factory of the Uranium Industry of Czechoslovakia in the design of a tunneling machine with disk bits

Energy Technology Data Exchange (ETDEWEB)

Kastner, P

1983-01-01

A tunneling machine, two prototypes of which were designed and built jointly on the basis of scientific and technical cooperation between the Experimental Design Factory of the Uranium Industry of Czechoslovakia and the VEB-Schachtbau enterprise (East Germany), is described. The experimental design operations were conducted under the methodological leadership of the Mine Construction in the Uranium Industry (Czechoslovakia) enterprise. The experimental design factory developed a general design system for the machine and its individual subassemblies. The detailed technical documentation for the machine units was developed by both enterprises. Each enterprise made two complexes of specific units and spare parts. The prototypes were assembled in both countries with the technical assistance of the producer enterprise of the appropriate subassembly. Industrial tests were conducted by each enterprise independently with technical assistance and delivery of spare parts on the part of the producer enterprise. A machine under the title of VM 24-27 was used to drill more than 2,300 meters of water supply tunnel in East Germany in 1982 and a machine called the RS 24-27 (29) was used in Prague in the same year to drill approximately 1,400 meters of cable collectors. The machine is designed for the passage of rounded mine drifts with a diameter of 2.4 to 2.7 (2.9) meters) to the full cross section in stable rocks. Its overall length is 32.5 meters, while the total weight is 85 tons. The shift productivity was 9.55 meters. Since 1979 the Mining Construction in the Uranium Industry and the Experimental Design Plant of the Uranium Industry Enterprises of Czechoslovakia have supplied disk bits for the TVM Demag tunnel drilling machines (West Germany) and RS 24-27 and the HG 210 Wirth (West Germany) cross cut drills.

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

Science.gov (United States)

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

2012-10-01

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

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

Improving mining technology and organization of labor in the light of medical-biological aspects of physical health of miners

Energy Technology Data Exchange (ETDEWEB)

Egorov, P.V.; Nirenburg, K.G.; Davydova, N.N.; Dyatlova, L.A. (Kuzbasskii Politekhnicheskii Institut (USSR))

1991-12-01

Transfer to a contract-bonus system in mines of the Severokuzbassugol' and Leninskugol' associations (USSR) increased coal mining productivity by 42.2-54.4%, but, at the same time, problems concerning miners' health were noted. Presents data on the productivity and labor conditions of contract teams working at coal mining and in development faces. The influence of noise and vibration induced stresses on organisms of underground workers is analyzed. Investigations showed that 3 stages of exhaustion are likely to develop and that the most vulnerable are the cardiovascular system and the respiratory tract. The 3 stages of exhaustion and ability to recover were studied on mining machine operators and drivers of heading machines. Data showed that during the 1985-89 period, 972 miners received disability certificates; the rate of disability was 2.6 miners per 1 Mt of coal; 40.5% of miners over 40 years working on labor-intensive jobs had three or more chronic diseases which could cause permanent disability. In the structure of disability, cardio-vascular system cases accounted for 25%, osseous-muscular system cases for 20% and pulmonary diseases for 13%. Stresses the need for every mine to maintain its own medical center equipped with inhalation therapy, psychological relief, acupuncture and physiotherapy facilities.

Wall-rock alteration and uranium mineralization in parts of Thomas Range Mining District, San Juan County, Utah, and its significance in mineral exploration

International Nuclear Information System (INIS)

Mohammad, H.

1985-01-01

Several important uranium deposits associated with fluorspar and beryllium are located in parts of Thomas Range area. the mineralization is found in dolomites and dolomitic limestones of Paleozoic age and sandstones, tuffs, and rhyolites belonging to the Tertiary Spor Mountain and Topaz Mountain Formations. The pipes, veins, and nodules of fluorspar are replaced by uranium. Veins and disseminations of radioactive fluorspar and opal and overgrowths of secondary minerals are found in rhyolites, tuffs, carbonate rocks, and breccias. The radioactivity in sandstones and conglomerates emanates from weeksite, beta-uranophane, zircon, gummite, and zircon. It also occurs as highly oxidized rare aphanitic grains disseminated in a few ore deposits. The results of the present investigations may influence the initiation of future exploration programs in the Thomas Range mining district. Hydrothermal fluids of deep-seated magmatic origin rich in U, V, Th, Be, and F reacted with the country rocks. The nature and sequence of wall-rock alteration and its paragenetic relationship with the ores have been determined. The mineralization is confined to the altered zones. The ore bodies in the sedimentary rocks and the breccias are located in the fault zones. More than 1000 faults are present in the area, greatly complicating mineral prospecting. The wall-rock alteration is very conspicuous and can be used as a valuable tool in mineral exploration

Neutron shielding and its impact on the ITER machine design

International Nuclear Information System (INIS)

Daenner, W.; El Guebaly, L.; Sawan, M.; Gohar, Y.; Maki, K.; Rado, V.; Schchipakin, O.; Zimin, S.

1991-01-01

This paper describes the efforts made in the frame of the ITER project to analyze the shielding of the superconducting magnets. First, the radiation limits to be achieved are specified as well as the neutron source in terms of wall loading on the first wall of the machine. Then the general shield concept is explained, including the most essential details of the various shield components. A brief section is devoted to the calculational tools, the data base, and the safety factors to be applied to the results obtained. The neutronics models of four different configurations are summarized as they were used to study the most critical parts of the machine. This section is followed by a presentation of the most important results from one-, two- and three-dimensional calculations. They are given for both the reference design and an improved one in which the critical regions are reinforced with respect to their shielding capability. It is concluded that the ITER shield layout just marginally meets the stated limits provided that some tungsten is included in the critical regions. A slight revision of the overall machine dimensions with the aim to achieve a less complex shield and a higher margin with respect to the limits is, however, seen the better solution. (orig.)

Repair of walls of coke ovens with a volume of 41. 6 m/sup 3/

Energy Technology Data Exchange (ETDEWEB)

Pyatnitsa, V.A.; Bulyga, N.I.

1988-11-01

Discusses repair of coke oven walls and the heating system of a battery with coke ovens 7.0 m high in the Avdeevka plant. The following problems are evaluated: types of wall deformation and wear, distribution of wear zones, zones with maximum wear, coke oven repair without cooling and with cooling, repair of cracks in oven walls, effects of wall temperature (in schemes without cooling) on repair, behavior of walls in zones of temperature differences, sequence of repair operations, repair of heating channels, specific problems of wall repair at the machine side and at the pusher side of a coke oven battery, methods for reducing repair time, materials used for coke oven repair.

Data Mining and Data Fusion for Enhanced Decision Support

Energy Technology Data Exchange (ETDEWEB)

Khan, Shiraj [ORNL; Ganguly, Auroop R [ORNL; Gupta, Amar [University of Arizona

2008-01-01

The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

Unified communication and standardized data exchange for underground mines; Einheitliche, standardisierte Kommunikation zur Effizienzsteigerung von Bergwerken

Energy Technology Data Exchange (ETDEWEB)

Mueller, C. [Embigence GmbH, Ladbergen (Germany)

2006-11-07

Communication in many forms during the past ten years has changed our daily life: Cellphone technology as well as the Internet are just two examples. In the same way, modern network based communication now starts to change the way how underground mines are run: The lack of proper communication traditionally caused downtime and production loss. In the future, mine communication will be crucial for efficiency and profitability of underground operations. This enables intelligent machines to be used like e.g. a machine server equipped drill rig at LKAB or highly advanced, networked monorail systems at DSK. Standardized communication and information exchange is a basis for using three dimensional visualization tools to support decision finding. The paper explains these visions and goals for the future and explains the feasibility by two running example applications. (orig.)

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.

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

Science.gov (United States)

Ray, Sutapa; Dey, Kaushik

2018-01-01

The Kyoto Protocol, 1998, was signed by member countries to reduce greenhouse gas (GHG) emissions to a minimum acceptable level. India agreed to Kyoto Protocol since 2002 and started its research on GHG mitigation. Few researchers have carried out research work on CO2 sequestration in different rock formations. However, CO2 sequestration in abandoned mines has yet not drawn its attention largely. In the past few years or decades, a significant amount of research and development has been done on Carbon Capture and Storage (CCS) technologies, since it is a possible solution for assuring less emission of CO2 to the atmosphere from power plants and some other major industrial plants. CCS mainly involves three steps: (a) capture and compression of CO2 from source (power plants and industrial areas), (b) transportation of captured CO2 to the storage mine and (c) injecting CO2 into underground mine. CO2 is stored at an underground mine mainly in three forms: (1) adsorbed in the coals left as pillars of the mine, (2) absorbed in water through a chemical process and (3) filled in void with compressed CO2. Adsorption isotherm is a graph developed between the amounts of adsorbate adsorbed on the surface of adsorbent and the pressure at constant temperature. Various types of adsorption isotherms are available, namely, Freundlich, Langmuir and BET theory. Indian coal is different in origin from most of the international coal deposits and thus demands isotherm experiments of the same to arrive at the right adsorption isotherm. To carry out these experiments, adsorption isotherm set up is fabricated in the laboratory with a capacity to measure the adsorbed volume up to a pressure level of 100 bar. The coal samples are collected from the pillars and walls of the underground coal seam using a portable drill machine. The adsorption isotherm experiments have been carried out for the samples taken from a mine. From the adsorption isotherm experiments, Langmuir Equation is found to be

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

Science.gov (United States)

Ray, Sutapa; Dey, Kaushik

2018-04-01

The Kyoto Protocol, 1998, was signed by member countries to reduce greenhouse gas (GHG) emissions to a minimum acceptable level. India agreed to Kyoto Protocol since 2002 and started its research on GHG mitigation. Few researchers have carried out research work on CO2 sequestration in different rock formations. However, CO2 sequestration in abandoned mines has yet not drawn its attention largely. In the past few years or decades, a significant amount of research and development has been done on Carbon Capture and Storage (CCS) technologies, since it is a possible solution for assuring less emission of CO2 to the atmosphere from power plants and some other major industrial plants. CCS mainly involves three steps: (a) capture and compression of CO2 from source (power plants and industrial areas), (b) transportation of captured CO2 to the storage mine and (c) injecting CO2 into underground mine. CO2 is stored at an underground mine mainly in three forms: (1) adsorbed in the coals left as pillars of the mine, (2) absorbed in water through a chemical process and (3) filled in void with compressed CO2. Adsorption isotherm is a graph developed between the amounts of adsorbate adsorbed on the surface of adsorbent and the pressure at constant temperature. Various types of adsorption isotherms are available, namely, Freundlich, Langmuir and BET theory. Indian coal is different in origin from most of the international coal deposits and thus demands isotherm experiments of the same to arrive at the right adsorption isotherm. To carry out these experiments, adsorption isotherm set up is fabricated in the laboratory with a capacity to measure the adsorbed volume up to a pressure level of 100 bar. The coal samples are collected from the pillars and walls of the underground coal seam using a portable drill machine. The adsorption isotherm experiments have been carried out for the samples taken from a mine. From the adsorption isotherm experiments, Langmuir Equation is found to be

Differential Privacy and Machine Learning: a Survey and Review

OpenAIRE

Ji, Zhanglong; Lipton, Zachary C.; Elkan, Charles

2014-01-01

The objective of machine learning is to extract useful information from data, while privacy is preserved by concealing information. Thus it seems hard to reconcile these competing interests. However, they frequently must be balanced when mining sensitive data. For example, medical research represents an important application where it is necessary both to extract useful information and protect patient privacy. One way to resolve the conflict is to extract general characteristics of whole popul...

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.

Dune Mining and the Nhlabane Estuary, South Africa: the Effect of a Dredger Crossing on the Zoobenthic Community

International Nuclear Information System (INIS)

Vivier, L.; Cyrus, D.P.

1999-01-01

The Nhlabane Estuary, located on the north-east coast of South Africa, is situated in a titanium dune mining lease area. During 1993, a mining dredger and concentrator crossed the middle reaches of the estuary. For this purpose, two berm walls were constructed across the estuary. Two impacts stemmed from the crossing. A series of fine sediment intrusions into the estuary from the berm wall area occurred during late 1993 and early 1994 and caused a rapid decline in benthic densities and number of taxa. Recovery of the affected area was slow and characterized by initial proliferation of opportunistic colonizers. The berm walls, which divided the estuary in half, were kept in place for nearly three years and caused changes in water quality and the benthic community of the upper and lower halves of the estuary. Artificial breaching of the estuary in August 1995 and removal of the berm walls in May 1996 initiated recovery of the estuary. The success of a second dredger crossing, scheduled for January 1999, depends on addressing the mistakes made during the first crossing and on the speed with which the carefully planned crossing operation, berm wall removal and estuary rehabilitation proceed

Data Mining Methods for Recommender Systems

Science.gov (United States)

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

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

A comparison of machine learning techniques for predicting downstream acid mine drainage

CSIR Research Space (South Africa)

van Zyl, TL

2014-07-01

Full Text Available windowing approach over historical values to generate a prediction for the current value. We evaluate a number of Machine Learning techniques as regressors including Support Vector Regression, Random Forests, Stochastic Gradient Decent Regression, Linear...

Dust control in Belgian coal mines. Position at the beginning of 1975

Energy Technology Data Exchange (ETDEWEB)

Preat, B; Vanstraelen, M

1975-01-01

A general view is given of dust control in Belgian coal mines at the beginning of 1975. The statistical data received from the mines are presented in tabular form. The length and the output of coal faces treated by the classical methods of pre-spraying of the wall, wet cutting, water infusion and wet pneumatic picks are given separately; in some cases two or more of these techniques are used together on the same coalface. The number of rock headings in which different methods of dust control are used is also given.

Evidence for land plant cell wall biosynthetic mechanisms in charophyte green algae

DEFF Research Database (Denmark)

Mikkelsen, Maria Dalgaard; Harholt, Jesper; Ulvskov, Peter

2014-01-01

in CGA is currently unknown, as no genomes are available, so this study sought to give insight into the evolution of the biosynthetic machinery of CGA through an analysis of available transcriptomes. METHODS: Available CGA transcriptomes were mined for cell wall biosynthesis GTs and compared with GTs...... to colonize land. These cell walls provide support and protection, are a source of signalling molecules, and provide developmental cues for cell differentiation and elongation. The cell wall of land plants is a highly complex fibre composite, characterized by cellulose cross-linked by non......-cellulosic polysaccharides, such as xyloglucan, embedded in a matrix of pectic polysaccharides. How the land plant cell wall evolved is currently unknown: early-divergent chlorophyte and prasinophyte algae genomes contain a low number of glycosyl transferases (GTs), while land plants contain hundreds. The number of GTs...

Shaft Boring Machine: A method of mechanized vertical shaft excavation

International Nuclear Information System (INIS)

Goodell, T.M.

1991-01-01

The Shaft Boring Machine (SBM) is a vertical application of proven rock boring technology. The machine applies a rotating cutter wheel with disk cutters for shaft excavation. The wheel is thrust against the rock by hydraulic cylinders and slews about the shaft bottom as it rotates. Cuttings are removed by a clam shell device similar to conventional shaft mucking and the muck is hoisted by buckets. The entire machine moves down (and up) the shaft through the use of a system of grippers thrust against the shaft wall. These grippers and their associated cylinders also provide the means to maintain verticality and stability of the machine. The machine applies the same principles as tunnel boring machines but in a vertical mode. Other shaft construction activities such as rock bolting, utility installation and shaft concrete lining can be accomplished concurrent with shaft boring. The method is comparable in cost to conventional sinking to a depth of about 460 meters (1500 feet) beyond which the SBM has a clear host advantage. The SBM has a greater advantage in productivity in that it can excavate significantly faster than drill and blast methods

Design and installation of a ferromagnetic wall in tokamak geometry

International Nuclear Information System (INIS)

Hughes, P. E.; Levesque, J. P.; Rivera, N.; Mauel, M. E.; Navratil, G. A.

2015-01-01

Low-activation ferritic steels are leading material candidates for use in next-generation fusion development experiments such as a prospective component test facility and DEMO power reactor. Understanding the interaction of plasmas with a ferromagnetic wall will provide crucial physics for these facilities. In order to study ferromagnetic effects in toroidal geometry, a ferritic wall upgrade was designed and installed in the High Beta Tokamak–Extended Pulse (HBT-EP). Several material options were investigated based on conductivity, magnetic permeability, vacuum compatibility, and other criteria, and the material of choice (high-cobalt steel) is characterized. Installation was accomplished quickly, with minimal impact on existing diagnostics and overall machine performance, and initial results demonstrate the effects of the ferritic wall on plasma stability

Design and installation of a ferromagnetic wall in tokamak geometry

Energy Technology Data Exchange (ETDEWEB)

Hughes, P. E., E-mail: peh2109@columbia.edu; Levesque, J. P.; Rivera, N.; Mauel, M. E.; Navratil, G. A. [Columbia University Plasma Physics Laboratory, Columbia University, 102 S.W. Mudd, 500 W. 120th St., New York, New York 10027 (United States)

2015-10-15

Low-activation ferritic steels are leading material candidates for use in next-generation fusion development experiments such as a prospective component test facility and DEMO power reactor. Understanding the interaction of plasmas with a ferromagnetic wall will provide crucial physics for these facilities. In order to study ferromagnetic effects in toroidal geometry, a ferritic wall upgrade was designed and installed in the High Beta Tokamak–Extended Pulse (HBT-EP). Several material options were investigated based on conductivity, magnetic permeability, vacuum compatibility, and other criteria, and the material of choice (high-cobalt steel) is characterized. Installation was accomplished quickly, with minimal impact on existing diagnostics and overall machine performance, and initial results demonstrate the effects of the ferritic wall on plasma stability.

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

Science.gov (United States)

Dhar, Vasant

1998-01-01

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

Machine Learning in Nutritional Follow-up Research

Directory of Open Access Journals (Sweden)

Reis Rita

2017-12-01

Full Text Available Healthcare is one of the world’s fastest growing industries, having large volumes of data collected on a daily basis. It is generally perceived as being ‘information rich’ yet ‘knowledge poor’. Hidden relationships and valuable knowledge can be discovered in the collected data from the application of data mining techniques. These techniques are being increasingly implemented in healthcare organizations in order to respond to the needs of doctors in their daily decision-making activities. To help the decision-makers to take the best decision it is fundamental to develop a solution able to predict events before their occurrence. The aim of this project was to predict if a patient would need to be followed by a nutrition specialist, by combining a nutritional dataset with data mining classification techniques, using WEKA machine learning tools. The achieved results showed to be very promising, presenting accuracy around 91%, specificity around 97% and precision about 95%.

Mechatronics in the mining industry. Modelling of underground machines; Mechatronik im Bergbau. Modellbildung von Untertage-Maschinen

Energy Technology Data Exchange (ETDEWEB)

Bruckmann, Tobias; Brandt, Thorsten [mercatronics GmbH, Duisburg (Germany)

2009-12-17

The development of new functions for machines operating underground often requires a prolonged and cost-intensive test phase. Precisely the development of complex functions as occur in operating assistance systems, for example, is highly iterative. If a corresponding prototype is required for each iteration step of the development, the development costs will, of course, increase rapidly. Virtual prototypes and simulators based on mathematical models of the machine offer an alternative in this case. The article describes the same principles for modelling the kinematics of underground machines. (orig.)

Experimental investigation of the tip based micro/nano machining

Science.gov (United States)

Guo, Z.; Tian, Y.; Liu, X.; Wang, F.; Zhou, C.; Zhang, D.

2017-12-01

Based on the self-developed three dimensional micro/nano machining system, the effects of machining parameters and sample material on micro/nano machining are investigated. The micro/nano machining system is mainly composed of the probe system and micro/nano positioning stage. The former is applied to control the normal load and the latter is utilized to realize high precision motion in the xy plane. A sample examination method is firstly introduced to estimate whether the sample is placed horizontally. The machining parameters include scratching direction, speed, cycles, normal load and feed. According to the experimental results, the scratching depth is significantly affected by the normal load in all four defined scratching directions but is rarely influenced by the scratching speed. The increase of scratching cycle number can increase the scratching depth as well as smooth the groove wall. In addition, the scratching tests of silicon and copper attest that the harder material is easier to be removed. In the scratching with different feed amount, the machining results indicate that the machined depth increases as the feed reduces. Further, a cubic polynomial is used to fit the experimental results to predict the scratching depth. With the selected machining parameters of scratching direction d3/d4, scratching speed 5 μm/s and feed 0.06 μm, some more micro structures including stair, sinusoidal groove, Chinese character '田', 'TJU' and Chinese panda have been fabricated on the silicon substrate.

Mining and mining authorities in Saarland 2016. Mining economy, mining technology, occupational safety, environmental protection, statistics, mining authority activities. Annual report

International Nuclear Information System (INIS)

2016-01-01

The annual report of the Saarland Upper Mining Authority provides an insight into the activities of mining authorities. Especially, the development of the black coal mining, safety and technology of mining as well as the correlation between mining and environment are stressed.

Mathematical modeling of methane migration into the mine workings during the face downtime

Science.gov (United States)

Govorukhin, Yu M.; Domrachev, A. N.; Krivopalov, V. G.; Paleev, D. Yu

2017-09-01

For the estimation of safe distances during explosions of mixtures of coal dust, methane, and air in the process of emergency rescue operations in coal mines, it is necessary to determine the gas volumes in the mine workings. Errors in determining such volumes often lead to tragic consequences. The calculation schemes are suggested that allow the methane generation rate into the mine air to be determined on the basis of physical regularities (mine and gas pressures, gas permeability dynamics, depth of the gas drainage zone, etc.), underlying the processes of gas migration from coal and rocks into the mine workings. The following methane emission sources are considered at the site: the surface of the stopped face; walls of development opening; the gob (potential volume of the gas reservoir in the caving area). Test calculations of methane generation have been performed based on the mining, geological and technological data of one of the mines in Baydaevsky geological and economic region. In general, the results obtained are consistent with the data of long-term empirical observations. The directions of further research aimed at improving the synthesized methodology are presented.

Data preparation for municipal virtual assistant using machine learning

OpenAIRE

Jovan, Leon Noe

2016-01-01

The main goal of this master’s thesis was to develop a procedure that will automate the construction of the knowledge base for a virtual assistant that answers questions about municipalities in Slovenia. The aim of the procedure is to replace or facilitate manual preparation of the virtual assistant's knowledge base. Theoretical backgrounds of different machine learning fields, such as multilabel classification, text mining and learning from weakly labeled data were examined to gain a better ...

Clad vent set cup open end (closure weld zone) wall-thickness study

Energy Technology Data Exchange (ETDEWEB)

Ulrich, G.B.; Sherrill, M.W.

1994-09-01

The wall thickness at the open end of Clad Vent Set (CVS) cups is a very important parameter for maintaining control of the fueled CVS closure weld process. Ideally, the wall thickness in the closure weld zone should be constant. The DOP-26 iridium alloy is very difficult to machine; therefore, key dimensional features are established during the two-draw warm-forming operation. Unfortunately, anisotropy in the forming blanks produces four ears at the open end of each cup. Formation of these ears produces axial and circumferential variations in wall thickness. The cup certification requirement is that the wall thickness in the closure weld zone, defined as the 2.5-mm band at the open end of a cup, measure from 0.63 to 0.73 mm. The wall thickness certification data for the open end of the CVS cups have been statistically evaluated. These data show that the cups recently produced for the Cassini mission have well-controlled open-end wall thicknesses.

Research on Health State Perception Algorithm of Mining Equipment Based on Frequency Closeness

Directory of Open Access Journals (Sweden)

Gang Wang

2014-06-01

Full Text Available The health state perception of mining equipment is intended to have an online real- time knowledge and analysis of the running conditions of large mining equipments. Due to its unknown failure mode, a challenge was raised to the traditional fault diagnosis of mining equipments. A health state perception algorithm of mining equipment was introduced in this paper, and through continuous sampling of the machine vibration data, the time-series data set was set up; subsequently, the mode set based on the frequency closeness was constructed by the d neighborhood method combined with the TSDM algorithm, thus the forecast method on the basis of the dual mode set was eventually formed. In the calculation of the frequency closeness, the Goertzel algorithm was introduced to effectively decrease the computation amount. It was indicated through the simulation test on the vibration data of the drum shaft base that the health state of the device could be effectively distinguished. The algorithm has been successfully applied to equipment monitoring in the Huoer Xinhe Coal Mine of Shanxi Coal Imp&Exp. Group Co., Ltd.

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

Science.gov (United States)

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

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

On the classification techniques in data mining for microarray data classification

Science.gov (United States)

Aydadenta, Husna; Adiwijaya

2018-03-01

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

A study of the flow boiling heat transfer in a minichannel for a heated wall with surface texture produced by vibration-assisted laser machining

International Nuclear Information System (INIS)

Piasecka, Magdalena; Strąk, Kinga; Grabas, Bogusław; Maciejewska, Beata

2016-01-01

The paper presents results concerning flow boiling heat transfer in a vertical minichannel with a depth of 1.7 mm and a width of 16 mm. The element responsible for heating FC-72, which flowed laminarly in the minichannel, was a plate with an enhanced surface. Two types of surface textures were considered. Both were produced by vibration-assisted laser machining. Infrared thermography was used to record changes in the temperature on the outer smooth side of the plate. Two-phase flow patterns were observed through a glass pane. The main aim of the study was to analyze how the two types of surface textures affect the heat transfer coefficient. A two-dimensional heat transfer approach was proposed to determine the local values of the heat transfer coefficient. The inverse problem for the heated wall was solved using a semi-analytical method based on the Trefftz functions. The results are presented as relationships between the heat transfer coefficient and the distance along the minichannel length and as boiling curves. The experimental data obtained for the two types of enhanced heated surfaces was compared with the results recorded for the smooth heated surface. The highest local values of the heat transfer coefficient were reported in the saturated boiling region for the plate with the type 1 texture produced by vibration-assisted laser machining. (paper)

Testing of a new mining system performance at narrow coal bed; Ensayo de un sistema de arranque con cepillo mediante accionamiento hidraulico para capas estrechas de carbon

Energy Technology Data Exchange (ETDEWEB)

1999-09-01

This researching project had the aim of: Testing a new mining system performance at narrow coal bed, which uses plough equipment with hydraulic driving devices. Minimising driving power group size to avoid problems regarding with the wall mining-heading transition, decreasing the needed room to house it and thus, simplifying wall mining edge support. The expected goals were: Take advantage of hydraulic driving devices to obtain a good efficiency with a variable and discontinuous load, but without loosing the electric driving devices advantages, consisting on increase driving torque, being the engine blocked Lengthen the mechanical equipment life (chains, driving sprockets, etc) Reach an economic production rate Researching project was developed in El Bierzo basin (leon, Spain), in Grupo Ampliacion, a mining group belonged to Viloria Hnos, S. A. (Author)

Throughput centered prioritization of machines in transfer lines

International Nuclear Information System (INIS)

Pascual, R.; Godoy, D.; Louit, D.M.

2011-01-01

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.

Evaluating operational efficiency of drainage holes in the Belchatow coal mine

Energy Technology Data Exchange (ETDEWEB)

Marek, A.; Paluch, W.

1979-03-01

This paper characterizes drainage holes used for lowering water level in the Belchatow brown coal surface mine in central Poland. Machines and installations used for drilling holes, and filter construction are described. Two types of filters are evaluated, one based an a steel construction, the other an a concrete- asbestos construction. The problem of evaluating operational efficiency of drainage holes is discussed. Yield of the well is presented as the factor characterizing operational efficiency of the hole. Factors influencing yield of the well are described. The proposed analysis of drainage hole efficiency makes it possible to compare efficiency of work of the filters with steel construction and asbestos-concrete construction. Under conditions of the Belchatow mine the asbestos-concrete filters are more efficient than steel filters. All drainage holes at the mine are characterized by declining efficiency. This can be caused prematurely by silting up. (2 refs.) (In Polish)

Design, fabrication and evaluation of fish meal pelletizing machine ...

African Journals Online (AJOL)

A 113.1kg/h fish meal pellet processing machine which produced 4mm diameter pellet, with an average length of 6mm was designed and fabricated. Design values of 210 was used for the maximum angle that the hopper wall formed with the vertical in the discharge zone, a critical stress of 1.3kPa of the ground particulate ...

Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

CERN Document Server

Pal, Sankar K

2004-01-01

Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

Integration of MOOCs in Advanced Mining Training Programmes

Science.gov (United States)

Saveleva, Irina; Greenwald, Oksana; Kolomiets, Svetlana; Medvedeva, Elena

2017-11-01

The paper covers the concept of innovative approaches in education based on incorporating MOOCs options into traditional classroom. It takes a look at the ways higher education instructors working with the mining engineers enrolled in advanced training programmes can brighten, upgrade and facilitate the learning process. The shift of higher education from in-class to online format has changed the learning environment and the methods of teaching including professional retraining courses. In addition, the need of mining companies for managers of a new kind obligates high school retraining centres rapidly move towards the 21st century skill framework. One of widely recognized innovations in the sphere of e-learning is MOOCs (Massive Open Online Courses) that can be used as an effective teaching tool for organizing professional training of managing staff of mining companies within the walls of a university. The authors share their instructional experience and show the benefits of introducing MOOCs options at the courses designed for retraining mining engineers and senior managers of coal enterprises. Though in recent researches the pedagogical value of MOOCs is highly questioned and even negated this invention of the 21st century can become an essential and truly helpful instrument in the hands of educators.

Some Considerations about Modern Database Machines

Directory of Open Access Journals (Sweden)

Manole VELICANU

2010-01-01

Full Text Available Optimizing the two computing resources of any computing system - time and space - has al-ways been one of the priority objectives of any database. A current and effective solution in this respect is the computer database. Optimizing computer applications by means of database machines has been a steady preoccupation of researchers since the late seventies. Several information technologies have revolutionized the present information framework. Out of these, those which have brought a major contribution to the optimization of the databases are: efficient handling of large volumes of data (Data Warehouse, Data Mining, OLAP – On Line Analytical Processing, the improvement of DBMS – Database Management Systems facilities through the integration of the new technologies, the dramatic increase in computing power and the efficient use of it (computer networks, massive parallel computing, Grid Computing and so on. All these information technologies, and others, have favored the resumption of the research on database machines and the obtaining in the last few years of some very good practical results, as far as the optimization of the computing resources is concerned.

Study of Environmental Data Complexity using Extreme Learning Machine

Science.gov (United States)

Leuenberger, Michael; Kanevski, Mikhail

2017-04-01

The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

Design problems of social-administrative complexes on the example of the Morcinek mine

Energy Technology Data Exchange (ETDEWEB)

Bielski, M.; Trojanowski, S.

1987-01-01

Buildings at the Morcinek mine head are designed as four complexes: the lamp room of 28,850 m/sup 3/ for 6,440 lamps; the washing room block of 92,491 m/sup 3/ for 7,623 miners (including mine operation offices, control room, mine rescue station, laundry and canteen); administration and social services block of 47,645 m/sup 3/ (mine management, telephone exchange, dispatcher room, health services, rooms for training and social organizations, snack bar); shaft landing and waiting room block of 12,080 m/sup 3/ (transportation, bus depot, parking). The buildings are built as frame type structures. Reinforced concrete is used for frames up to 6 m and steel for the larger ones. Prefabricated reinforced concrete floors and skirt type walls of glass panels, bricks or prefabricated materials are incorporated. The multi-storey buildings are built on 'Franki' type piles.

Reliability analysis of mining equipment: A case study of a crushing plant at Jajarm Bauxite Mine in Iran

International Nuclear Information System (INIS)

Barabady, Javad; Kumar, Uday

2008-01-01

The performance of mining machines depends on the reliability of the equipment used, the operating environment, the maintenance efficiency, the operation process, the technical expertise of the miners, etc. As the size and complexity of mining equipments continue to increase, the implications of equipment failure become ever more critical. Therefore, reliability analysis is required to identify the bottlenecks in the system and to find the components or subsystems with low reliability for a given designed performance. It is important to select a suitable method for data collection as well as for reliability analysis. This paper presents a case study describing reliability and availability analysis of the crushing plant number 3 at Jajarm Bauxite Mine in Iran. In this study, the crushing plant number 3 is divided into six subsystems. The parameters of some probability distributions, such as Weibull, Exponential, and Lognormal distributions have been estimated by using ReliaSoft's Weibull++6 software. The results of the analysis show that the conveyer subsystem and secondary screen subsystem are critical from a reliability point of view, and the secondary crusher subsystem and conveyer subsystem are critical from an availability point of view. The study also shows that the reliability analysis is very useful for deciding maintenance intervals

Mine Water Treatment in Hongai Coal Mines

Science.gov (United States)

Dang, Phuong Thao; Dang, Vu Chi

2018-03-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

Homopolar machine for reversible energy storage and transfer systems

Science.gov (United States)

Stillwagon, Roy E.

1978-01-01

A homopolar machine designed to operate as a generator and motor in reversibly storing and transferring energy between the machine and a magnetic load coil for a thermo-nuclear reactor. The machine rotor comprises hollow thin-walled cylinders or sleeves which form the basis of the system by utilizing substantially all of the rotor mass as a conductor thus making it possible to transfer substantially all the rotor kinetic energy electrically to the load coil in a highly economical and efficient manner. The rotor is divided into multiple separate cylinders or sleeves of modular design, connected in series and arranged to rotate in opposite directions but maintain the supply of current in a single direction to the machine terminals. A stator concentrically disposed around the sleeves consists of a hollow cylinder having a number of excitation coils each located radially outward from the ends of adjacent sleeves. Current collected at an end of each sleeve by sleeve slip rings and brushes is transferred through terminals to the magnetic load coil. Thereafter, electrical energy returned from the coil then flows through the machine which causes the sleeves to motor up to the desired speed in preparation for repetition of the cycle. To eliminate drag on the rotor between current pulses, the brush rigging is designed to lift brushes from all slip rings in the machine.

Homopolar machine for reversible energy storage and transfer systems

International Nuclear Information System (INIS)

Stillwagon, R.E.

1981-01-01

A homopolar machine designed to operate as a generator and motor in reversibly storing and transferring energy between the machine and a magnetic load coil for a thermo-nuclear reactor. The machine rotor comprises hollow thin-walled cylinders or sleeves which form the basis of the system by utilizing substantially all of the rotor mass as a conductor thus making it possible to transfer substantially all the rotor kinetic energy electrically to the load coil in a highly economical and efficient manner. The rotor is divided into multiple separate cylinders or sleeves of modular design, connected in series and arranged to rotate in opposite directions but maintain the supply of current in a single direction to the machine terminals. A stator concentrically disposed around the sleeves consists of a hollow cylinder having a number of excitation coils each located radially outward from the ends of adjacent sleeves. Current collected at an end of each sleeve by sleeve slip rings and brushes is transferred through terminals to the magnetic load coil. Thereafter, electrical energy returned from the coil then flows through the machine which causes the sleeves to motor up to the desired speed in preparation for repetition of the cycle. To eliminate drag on the rotor between current pulses, the brush rigging is designed to lift brushes from all slip rings in the machine

Mine Water Treatment in Hongai Coal Mines

OpenAIRE

Dang Phuong Thao; Dang Vu Chi

2018-01-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine ...

Lead, cadmium, and zinc concentrations in plaster and mortar from structures in Jasper and Newton Counties, Missouri (Tri-State Mining District)

Energy Technology Data Exchange (ETDEWEB)

Perry, Phyllis M [Chemistry Department, Southwest Missouri State University, 901 S. National Avenue, Springfield, MO 65804 (United States); Pavlik, Jeffrey W [Chemistry Department, Southwest Missouri State University, 901 S. National Avenue, Springfield, MO 65804 (United States); Sheets, Ralph W [Chemistry Department, Southwest Missouri State University, 901 S. National Avenue, Springfield, MO 65804 (United States); Biagioni, Richard N [Chemistry Department, Southwest Missouri State University, 901 S. National Avenue, Springfield, MO 65804 (United States)

2005-01-05

The primary goal of this study was to evaluate anecdotal evidence that within Jasper and Newton Counties, Missouri, two counties within the Tri-State Mining District, granular mine tailings were commonly used in place of river sands in wall plasters and mortar. Interior wall plaster and mortar samples from structures in this mining district were analyzed for lead, cadmium, and zinc, and compared to samples from Springfield, MO (comparison site). The Jasper and Newton County samples showed elevated concentrations of the three elements, consistent with the inclusion of mine tailings, with a number of samples containing lead and cadmium at concentrations greater than EPA remediation targets for yard soil. X-ray diffraction studies showed the presence of the zinc ore minerals, sphalerite and hemimorphite, in high level samples. Thin section optical studies identified the major component of the aggregate as chert, a mineral abundant within the tailing piles. Because dust from crumbling plaster and mortar could represent an avenue for significant heavy metal exposure to building occupants, we suggest that there may be associated health consequences that should be further evaluated.

Lead, cadmium, and zinc concentrations in plaster and mortar from structures in Jasper and Newton Counties, Missouri (Tri-State Mining District)

International Nuclear Information System (INIS)

Perry, Phyllis M.; Pavlik, Jeffrey W.; Sheets, Ralph W.; Biagioni, Richard N.

2005-01-01

The primary goal of this study was to evaluate anecdotal evidence that within Jasper and Newton Counties, Missouri, two counties within the Tri-State Mining District, granular mine tailings were commonly used in place of river sands in wall plasters and mortar. Interior wall plaster and mortar samples from structures in this mining district were analyzed for lead, cadmium, and zinc, and compared to samples from Springfield, MO (comparison site). The Jasper and Newton County samples showed elevated concentrations of the three elements, consistent with the inclusion of mine tailings, with a number of samples containing lead and cadmium at concentrations greater than EPA remediation targets for yard soil. X-ray diffraction studies showed the presence of the zinc ore minerals, sphalerite and hemimorphite, in high level samples. Thin section optical studies identified the major component of the aggregate as chert, a mineral abundant within the tailing piles. Because dust from crumbling plaster and mortar could represent an avenue for significant heavy metal exposure to building occupants, we suggest that there may be associated health consequences that should be further evaluated

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

Science.gov (United States)

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

2017-01-01

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

Mine Water Treatment in Hongai Coal Mines

Directory of Open Access Journals (Sweden)

Dang Phuong Thao

2018-01-01

Full Text Available Acid mine drainage (AMD is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

The role of waste sorting in the South African gold-mining industry

International Nuclear Information System (INIS)

Freer, J.S.; Boehme, R.C.

1985-01-01

The absolute potential for sorting waste from run-of-mine Witwatersrand gold ores normally lies between 60 and 90 per cent by mass. At present, the practical potential lies between 40 and 50 per cent. Yet few mines achieve a waste rejection of even 30 per cent. The average waste rejection for industry, including underground sorting, fell from 19,6 per cent in 1959 to 10,1 per cent in 1983, as industry moved from labour-intensive, multistage comminution, incorporating washing, screening, and sorting, to single-stage run-of-mine milling. Most of the sorting is still being done by hand; yet photometric and radiometric sorting machines of high capacity are available. More recently, a sorter based on neutron activation and the subsequent isomeric radioactive decay of gold itself was designed. This paper examines the case for an increased role for sorting in the South African gold-mining industry brought about by the increasing cost of power for milling and the possibility of extracting gold from low-grade reject fractions by heap leaching

The automation of the "making safe" process in South African hard-rock underground mine

CSIR Research Space (South Africa)

Teleka, SR

2011-07-01

Full Text Available In South African hard-rock mines, best practice dictates that the hanging-walls be inspected after blasting. This process is known as ‘making safe’ and although intended to save lives, it is laborious and subjective. Pressure is placed on the barrer...

Feasibility of a continuous surface mining machine using impact breakers. First quarterly report, October 1-December 31, 1979

Energy Technology Data Exchange (ETDEWEB)

Fisk, A. T.

1980-01-01

This is the first quarterly report on the efforts to evaluate the feasibility of excavating coal and overburden from surface mines using impact breakers. The initial stages of the project are devoted to a literature search, equipment selection, test site selection, and conceptual test system design. Hence, this report details the progress made in these areas; the next quarter will see the finalization of Phase I. Included as appendices to this report are FMA internal reports on the individual mines visited. These reports are the basis of the test site selection, and have been censored here to remove data the mine operators deemed as confidential.

Impact of wall materials and seeding gases on the pedestal and on core plasma performance

Directory of Open Access Journals (Sweden)

E. Wolfrum

2017-08-01

Full Text Available Plasmas in machines with all metal plasma facing components have a lower Zeff, less radiation cooling in the scrape-off layer and divertor regions and are prone to impurity accumulation in the core. Higher gas puff and the seeding of low-Z impurities are applied to prevent impurity accumulation, to increase the frequency of edge localised modes and to cool the divertor. A lower power threshold for the transition from low-confinement mode to high confinement mode has been found in all metal wall machines when compared to carbon wall machines. The application of lithium before or during discharges can lead to ELM free H-modes. The seeding of high-Z impurities increases core radiation, reduces the power flux across the separatrix and, if applied in the right amount, does not lead to deterioration of the confinement. All these effects have in common that they can often be explained by the shape or position of the density profile. Not only the peakedness of the density profile in the core but also the position of the edge pressure gradient influences global confinement. It is shown how (i ionisation in the pedestal region due to higher reflection of deuterium from high-Z walls, (ii reduced recycling in consequence of lithium wall conditioning, (iii the fostering of edge modes with lithium dropping, (iv increased gas puff and (v the cooling of the scrape-off layer by medium-Z impurities such as nitrogen affect the edge density profile. The consequence is a shift in the pressure profile relative to the separatrix, leading to improved pedestal stability of H-mode plasmas when the direction is inwards.

Application of data mining techniques for nuclear data and instrumentation

International Nuclear Information System (INIS)

Toshniwal, Durga

2013-01-01

Data mining is defined as the discovery of previously unknown, valid, novel, potentially useful, and understandable patterns in large databases. It encompasses many different techniques and algorithms which differ in the kinds of data that can be analyzed and the form of knowledge representation used to convey the discovered knowledge. Patterns in the data can be represented in many different forms, including classification rules, association rules, clusters, etc. Data mining thus deals with the discovery of hidden trends and patterns from large quantities of data. The field of data mining is emerging as a new, fundamental research area with important applications to science, engineering, medicine, business, and education. It is an interdisciplinary research area and draws upon several roots, including database systems, machine learning, information systems, statistics and expert systems. Data mining, when performed on time series data, is known as time series data mining (TSDM). A time series is a sequence of real numbers, each number representing a value at a point of time. During the past few years, there has been an explosion of research in the area of time series data mining. This includes attempts to model time series data, to design languages to query such data, and to develop access structures to efficiently process queries on such data. Time series data arises naturally in many real-world applications. Efficient discovery of knowledge through time series data mining can be helpful in several domains such as: Stock market analysis, Weather forecasting etc. An important application area of data mining techniques is in nuclear power plant and related data. Nuclear power plant data can be represented in form of time sequences. Often it may be of prime importance to analyze such data to find trends and anomalies. The general goals of data mining include feature extraction, similarity search, clustering and classification, association rule mining and anomaly

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

KAUST Repository

Yucel, Abdulkadir C.

2018-02-05

A fast and memory efficient 3D full wave simulator for analyzing electromagnetic (EM) wave propagation in electrically large and realistic mine tunnels/galleries loaded with conductors is proposed. The simulator relies on Muller and combined field surface integral equations (SIEs) to account for scattering from mine walls and conductors, respectively. During the iterative solution of the system of SIEs, the simulator uses a fast multipole method - fast Fourier transform (FMM-FFT) scheme to reduce CPU and memory requirements. The memory requirement is further reduced by compressing large data structures via singular value and Tucker decompositions. The efficiency, accuracy, and real-world applicability of the simulator are demonstrated through characterization of EM wave propagation in electrically large mine tunnels/galleries loaded with conducting cables and mine carts.

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.

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

Science.gov (United States)

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

2017-03-01

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

Prediction of tunnel boring machine performance using machine and rock mass data

International Nuclear Information System (INIS)

Dastgir, G.

2012-01-01

Performance of the tunnel boring machine and its prediction by different methods has been a hot issue since the first TBM came into being. For the sake of safe and sound transport, improvement of hydro-power, mining, civil and many other tunneling projects that cannot be driven efficiently and economically by conventional drill and blast, TBMs are quite frequently used. TBM parameters and rock mass properties, which heavily influence machine performance, should be estimated or known before choice of TBM-type and start of excavation. By applying linear regression analysis (SPSS19), fuzzy logic tools and a special Math-Lab code on actual field data collected from seven TBM driven tunnels (Hieflau expansion, Queen water tunnel, Vereina, Hemerwald, Maen, Pieve and Varzo tunnel), an attempt was made to provide prediction of rock mass class (RMC), rock fracture class (RFC), penetration rate (PR) and advance rate (AR). For detailed analysis of TBM performance, machine parameters (thrust, machine rpm, torque, power etc.), machine types and specification and rock mass properties (UCS, discontinuity in rock mass, RMC, RFC, RMR, etc.) were analyzed by 3-D surface plotting using statistical software R. Correlations between machine parameters and rock mass properties which effectively influence prediction models, are presented as well. In Hieflau expansion tunnel AR linearly decreases with increase of thrust due to high dependence of machine advance rate upon rock strength. For Hieflau expansion tunnel three types of data (TBM, rock mass and seismic data e.g. amplitude, pseudo velocity etc.) were coupled and simultaneously analyzed by plotting 3-D surfaces. No appreciable correlation between seismic data (Amplitude and Pseudo velocity) and rock mass properties and machine parameters could be found. Tool wear as a function of TBM operational parameters was analyzed which revealed that tool wear is minimum if applied thrust is moderate and that tool wear is high when thrust is

Seismic velocity distribution in the vicinity of a mine tunnel at Thabazimbi, South Africa

CSIR Research Space (South Africa)

Wright, C

2000-07-01

Full Text Available Analysis of the refracted arrivals on a seismic reflection profile recorded along the wall of a tunnel at an iron mine near Thabazimbi, South Africa, shows variations in P-wave velocity in dolomite away from the de-stressed zone that vary between 4...

Special method of coal winning in Hambach open-cast mine in 1987 using large machines in tandem operation

Energy Technology Data Exchange (ETDEWEB)

Krug, M; Muellensiefen, K

1988-05-01

In 1987 an additional 1,75 Mt coal, which were only overlain by slight layers of overburden, were won from the marginal batter system at Hambach open-cast mine by using a bucket wheel dredger with a daily output of 240 000 m/sup 3/ (solid) and at the same time bringing up the inside dump. During this working method the dredger and the spreader operated with a common belt conveyor in so-called tandem operation. Thanks to the efficient co-operation of the head planning department, field mining department, opencast mine surveying department and rock and soil mechanics department of the head office of the Rheinische Braunkohlenwerke AG, this special coal winning operation could be completed successfully.

EAST machine assembly and its measurement system

International Nuclear Information System (INIS)

Wu, S.T.

2005-01-01

The EAST (HT-7U) superconducting tokamak consists of a superconducting poloidal field magnet system, a toroidal field magnet system, a vacuum vessel and in-vessel components, thermal shields and a cryostat vessel. The main parts of the machine have been delivered to ASIPP (Institute of Plasma Physics, Chinese Academy of Sciences) successionally from 2003. For its complicated constitution and precise requirement, a reasonable assembly procedure and measurement technique should be defined carefully. Before the assembly procedure, a reference frame has been set up with reference fiducial targets on the wall of the test hall by an industrial measurement system. After the torus of TF coils is formed, a new reference frame will be set up from the position of the TF torus. The vacuum vessel with all inner parts will be installed with reference of the new reference frame. The big size and mass of components, special configuration of the superconducting machine with tight installation tolerances of the HT-7U (EAST) machine result in complicated assembly procedure. The procedure had begun with the installation of the support frame and the base of cryostat vessel last year. In this paper, the requirements of the assembly precise for some key components of the machine are described. The reference frame for the assembly and maintenance is explained. The assembly procedure is introduced

An examination of methods whereby noise levels in current and new mining equipment may be reduced

CSIR Research Space (South Africa)

Maneylaws, A

1997-12-01

Full Text Available An extensive literature review of international work of mining equipment noise control has been carried out. The sources of noise on percussion rock drills, continuous miners, dust scrubbers and fans, long wall machinery and trackless vehicles...

International mining forum 2004, new technologies in underground mining, safety in mines proceedings

Energy Technology Data Exchange (ETDEWEB)

Jerzy Kicki; Eugeniusz Sobczyk (eds.)

2004-01-15

The book comprises technical papers that were presented at the International Mining Forum 2004. This event aims to bring together scientists and engineers in mining, rock mechanics, and computer engineering, with a view to explore and discuss international developments in the field. Topics discussed in this book are: trends in the mining industry; new solutions and tendencies in underground mines; rock engineering problems in underground mines; utilization and exploitation of methane; prevention measures for the control of rock bursts in Polish mines; and current problems in Ukrainian coal mines.

Development of opencast mining technology during the last decade. El desarrollo de la tecnologia de la mineria de superficie de la ultima decada

Energy Technology Data Exchange (ETDEWEB)

Van Leyen, H. (Rheinbraun Engineering und Wasser GmbH, Koeln (Germany). Departamento de Ingernieria Mecancia)

1992-03-01

This review only covers the development of equipment and technology and is limited to those projects involving bucket wheel excavators, including compact conveyors for use with bucket wheel excavators, main and intermediate conveyors, overburden stripping systems for continuous mining operations, cutting and trenching equipment, crushing and conveying systems for hard rock mining, aspects of excavator and dumper systems, surface winning machines, draglines and special developments in the field of materials handling and storage, blasting and other deep-mining operations. 24 refs., 19 figs., 1 tab.

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 The project has produced information and methodologies for use by designers, mine managers and engineers to improve the health and safety associated with the use of trackless vehicles in mines. The project deliverables focus on assisting; designers...

Angular mining conveyor

Energy Technology Data Exchange (ETDEWEB)

Sender, A; Mura, A; Liduchowski, L; Zok, P; Skolik, W; Szyngiel, S; Rojek, H; Gajda, B; Major, M; Stanislawski, P; Sliwiok, H; Sikora, J

1988-10-19

Angular mining conveyor provided with a drag chain extending along the axis of its path of movement, and a corner member, inside which the drag chain is led in a forced way, characterized in that the drag chain, where its path curves around the corner member, is located by supporting of the vertical links of the chain along the required curved section of the conveyor path around said corner member, and the supporting line of the links is so chosen, that, within the said curved section of the conveyor path, a space is maintained between the vertical end surface of the scrapers and the outer curved surface of the radially inner side wall of a corner trough associated with the corner member, through which corner trough the scrapers pass. 10 figs.

Releveling and behavior of strap-retrofitted damaged test foundations exposed to mine subsidence

International Nuclear Information System (INIS)

Marino, G.G.

1997-01-01

Test foundation walls were constructed in an area of planned subsidence. These crawl space-sized block bearing walls were located in the tension zone of a longwall panel. The test walls were 1.2 m (40 ft) long and were vertically loaded on top with soil binds to simulate the weight of a house. As the longwall proceeded past these test foundations, subsidence movements damaged the test structures. These damaged foundations were then structurally and aesthetically repaired by using a steel strap retrofit and applying a cementitious surface coating. The repaired test foundations underwent significant subsequent subsidence as an adjacent longwall was mined beneath. The response of the repaired foundation is summarized in this paper. The steel straps were also used to relevel another set of the test foundations after they were tilted and damaged by subsidence. First, the straps were applied to the block bearing walls, and then wall jacks were used to lift the upper portion of the walls to a level position. This releveling procedure is outlined with the results

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

Science.gov (United States)

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

2017-08-01

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

Quality of research results in agro-economy by data mining

Directory of Open Access Journals (Sweden)

Vukelić Gordana

2015-01-01

Full Text Available Data Mining (DM through data in agroeconomy is a scientific method that enables researchers not to go through set research scenarioes that are predetermined assumptions and hypotheses on the basis of insignificant atributes. On the contrary, by data mining detection of these atributes is made possible, in general, those hiden facts that enable setting a hypothesis. The DM method does this by an iterative way, including key atributes and factors and their influence on the quality of agro-resources. The research was conducted on a random sample, by analyzing the quality of eggs. The research subject is the posibility of classifying and predicting significant variablesatributes that determine the level of egg quality. The research starts from the use of Data Mining, as an area of machine studies, which significantly helps researchers in optimizing research. The applied methodology during research includes analyticalsintetic procedures and methods of Data Mining, with a special focus on using Supervised linear discrimination analysis and the Decision Tree. The results indicate significant posibilities of using DM as an additional analytical procedure in performing agroresearch and it can be concluded that it contributes to an improvement in effectiveness and validity of process in performing these researches.

Production and repair of metal supports as an indispensable activity of the Georgi Dimitrov mining and power combine

Energy Technology Data Exchange (ETDEWEB)

Mladenov, O

1979-07-01

Georgi Dimitrov underground mines have favoured metal supports over concrete slabs and timber since 1972 because of their well known advantages and because metal supports lend themselves to easy handling by 4-PU combines and 1PNB-2 loading machines. To eliminate bottlenecks and high costs of procurement from a central base individual mines were charged with production of their own metal supports. This resulted in some new developments, for example, in the production of supports with a 3.16 times greater capacity in the Marshall Tolbukhin and Al. Milenov mines in 1978. Hydraulic presses are generally used to produce conventional arch and ring type supports, and the Polish make PHPG-100 press is used for repairs. Decentralization also caused problems: different length timber and metal supports often necessitate additional cutting operations, a multitude of machines cause increased manual handling, and equipment is too often adapted to special requirements of individual shifts. However, costs of metal supports have dropped about 15%. Further improvement would require that the production of metal supports be centralized for the entire combine, supports be used according to their strength, and screw joinings be replaced with cotter type fastenings.

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

Science.gov (United States)

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

2017-09-01

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

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...

Ion-surface interaction: simulation of plasma-wall interaction (ITER)

International Nuclear Information System (INIS)

Salou, Pierre

2013-01-01

The wall materials of magnetic confinement in fusion machines are exposed to an aggressive environment; the reactor blanket is bombarded with a high flux of particles extracted from the plasma, leading to the sputtering of surface material. This sputtering causes wall erosion as well as plasma contamination problems. In order to control fusion reactions in complex reactors, it is thus imperative to well understand the plasma-wall interactions. This work proposes the study of the sputtering of fusion relevant materials. We propose to simulate the charged particles influx by few keV single-charged ion beams. This study is based on the catcher method; to avoid any problem of pollution (especially in the case of carbon) we designed a new setup allowing an in situ Auger electron spectroscopy analysis. The results provide the evolution of the angular distribution of the sputtering yield as a function of the ion mass (from helium to xenon) and its energy (from 3 keV to 9 keV). (author) [fr

Sustainable Mining Environment: Technical Review of Post-mining Plans

Directory of Open Access Journals (Sweden)

Restu Juniah

2017-12-01

Full Text Available The mining industry exists because humans need mining commodities to meet their daily needs such as motor vehicles, mobile phones, electronic equipment and others. Mining commodities as mentioned in Government Regulation No. 23 of 2010 on Implementation of Mineral and Coal Mining Business Activities are radioactive minerals, metal minerals, nonmetallic minerals, rocks and coal. Mineral and coal mining is conducted to obtain the mining commodities through production operations. Mining and coal mining companies have an obligation to ensure that the mining environment in particular after the post production operation or post mining continues. The survey research aims to examine technically the post-mining plan in coal mining of PT Samantaka Batubara in Indragiri Hulu Regency of Riau Province towards the sustainability of the mining environment. The results indicate that the post-mining plan of PT Samantaka Batubara has met the technical aspects required in post mining planning for a sustainable mining environment. Postponement of post-mining land of PT Samantaka Batubara for garden and forest zone. The results of this study are expected to be useful and can be used by stakeholders, academics, researchers, practitioners and associations of mining, and the environment.

Dynamic aspects of design and maintenance of the rotating machinery applied in the mining industry

Directory of Open Access Journals (Sweden)

Szolc Tomasz

2017-01-01

Full Text Available In the paper a dynamic behaviour of the selected typical group of rotating machines applied in the mining industry is investigated. These are the beater mills and crushers as well as blowers and compressors, all driven by the asynchronous motors. In particular, there is considered an influence of various types of machine working tool loadings on the system lateral steady-state dynamic responses as well as a mutual torsional electromechanical interaction between the driving motor and the driven machine in transient operational conditions. The theoretical calculations have been performed by means of the advanced structural mechanical models. The conclusions drawn from computational results can be very useful during design phase of these devices as well as helpful for their users during regular maintenance.

Contract Mining versus Owner Mining

African Journals Online (AJOL)

Owner

mining companies can concentrate on their core businesses while using specialists for ... 2 Definition of Contract and Owner. Mining ... equipment maintenance, scheduling and budgeting ..... No. Region. Amount Spent on. Contract Mining. ($ billion). Percent of. Total. 1 ... cost and productivity data based on a large range.

Optimization of mining design of Hongwei uranium mine

International Nuclear Information System (INIS)

Wu Sanmao; Yuan Baixiang

2012-01-01

Combined with the mining conditions of Hongwei uranium mine, optimization schemes for hoisting cage, mine drainge,ore transport, mine wastewater treatment, power-supply system,etc are put forward in the mining design of the mine. Optimized effects are analyzed from the aspects of technique, economy, and energy saving and reducing emissions. (authors)

Electromechanical dynamic analysis for the drum driving system of the long-wall shearer

Directory of Open Access Journals (Sweden)

Changzhao Liu

2015-10-01

Full Text Available The drum driving system is one of the weakest parts of the long-wall shearer, and some methods are also needed to monitor and control the long-wall shearer to adapt to the important trend of unmanned operation in future mining systems. Therefore, it is essential to conduct an electromechanical dynamic analysis for the drum driving system of the long-wall shearer. First, a torsional dynamic model of planetary gears is proposed which is convenient to be connected to the electric motor model for electromechanical dynamic analysis. Next, an electromechanical dynamic model for the drum driving system is constructed including the electric motor, the gear transmission system, and the drum. Then, the electromechanical dynamic characteristics are simulated when the shock loads are acted on the drum driving system. Finally, some advices are proposed for improving the reliability, monitoring the operating state, and choosing the control signals of the long-wall shearer based on the simulation.

Mining for Strategic Competitive Intelligence Foundations and Applications

CERN Document Server

Ziegler, Cai-Nicolas

2012-01-01

The textbook at hand aims to provide an introduction to the use of automated methods for gathering strategic competitive intelligence. Hereby, the text does not describe a singleton research discipline in its own right, such as machine learning or Web mining. It rather contemplates an application scenario, namely the gathering of knowledge that appears of paramount importance to organizations, e.g., companies and corporations. To this end, the book first summarizes the range of research disciplines that contribute to addressing the issue, extracting from each those grains that are of utmost relevance to the depicted application scope. Moreover, the book presents systems that put these techniques to practical use (e.g., reputation monitoring platforms) and takes an inductive approach to define the gestalt of mining for competitive strategic intelligence by selecting major use cases that are laid out and explained in detail. These pieces form the first part of the book. Each of those use cases is backed by a nu...

The influence of the mining operation on the mine seismicity of Vorkuta coal deposit

Science.gov (United States)

Zmushko, T.; Turuntaev, S. B.; Kulikov, V. I.

2012-04-01

The mine seismicity of Vorkuta coal deposit was analyzed. Seismic network consisting of 24 seismic sensors (accelerometers) cover the area of "Komsomolskaya" and "North" mines of Vorkuta deposit. Also there is seismic station of IDG RAS with three-component seismometer near this mines for better defining energy of the seismic events. The catalogs of seismic events contain 9000 and 7000 events with maximum magnitude M=2.3 for "Komsomolskaya" and "North" mines respectively and include the period from 01.09.2008 to 01.09.2011. The b-value of the magnitude-frequency relation was -1.0 and -1.15 respectively for the mines, meanwhile b-value for the nature seismicity was -0,9. It was found, that the number of seismic events per hour during mine combine operation is higher in 2.5 times than the number of seismic events during the break in the operation. Also, the total energy of the events per hour during the operation is higher in 3-5 times than during the break. The study showed, that the number and the energy of the seismic events relate with the hours of mine combine operation. The spatial distribution of the seismic events showed, that 80% of all events and 85% of strong events (M>1.6) were located in and near the longwall under development during the mine combine operations as well asduring the breaks. The isoclines of seismic event numbers proved that the direction of motion of the boundary of seismic events extension coincides with the direction of development, the maximum number of events for any period lies within the wall under operation. The rockburst with M=2.3 occurring at the North mine at July 16, 2011 was considered. The dependences of the energy and of the number of events with different magnitudes on the time showed that the number of events with M=1 and especially M=0.5 before the rockburst decreased, which corresponds to the prognostic seismic quietness, described in the research works. The spatial distribution of the events for the 6 month before the

One method for life time estimation of a bucket wheel machine for coal moving

Science.gov (United States)

Vîlceanu, Fl; Iancu, C.

2016-08-01

Rehabilitation of outdated equipment with lifetime expired, or in the ultimate life period, together with high cost investments for their replacement, makes rational the efforts made to extend their life. Rehabilitation involves checking operational safety based on relevant expertise of metal structures supporting effective resistance and assessing the residual lifetime. The bucket wheel machine for coal constitute basic machine within deposits of coal of power plants. The estimate of remaining life can be done by checking the loading on the most stressed subassembly by Finite Element Analysis on a welding detail. The paper presents step-by-step the method of calculus applied in order to establishing the residual lifetime of a bucket wheel machine for coal moving using non-destructive methods of study (fatigue cracking analysis + FEA). In order to establish the actual state of machine and areas subject to study, was done FEA of this mining equipment, performed on the geometric model of mechanical analyzed structures, with powerful CAD/FEA programs. By applying the method it can be calculated residual lifetime, by extending the results from the most stressed area of the equipment to the entire machine, and thus saving time and money from expensive replacements.

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...

Behavior of crushed salt under heat source in boreholes in a salt mine (Amelie Mine, Alsace Potash Mines, France)

International Nuclear Information System (INIS)

Ghoreychi, M.

1991-01-01

The study of thermomechanical interaction between rock salt and crushed salt, used as a backfilling material at the final stage of radioactive waste disposal in salt formations, led to perform an in situ test at the Amelie Mine(The Alsace Potash Mines in France). The field tests site is located at a depth of 520m and the tests were performed in six parallel boreholes. Five boreholes were backfilled using three types of crushed salt, changing by their grain size (fine = 0.4 mm; natural = 1 mm; coarse = 2 mm). The sixth borehole was not backfilled in order to witness for rock salt behavior without backfilling confinement. Except the first borehole used as a pilot test, the four backfilled boreholes were heated during four months with two levels of heat output (1.6 kW, then 2.2 kW). Cooling was also followed during four months after heating interruption. The maximum of temperature obtained on the wall of the backfilled boreholes was about 100 0 C during the first field test and 130 0 C during the second. The thermal diffusivity of rock mass and the coefficient of heat exchange by convection are studied. In spite of the case that the crushed salt thermal conductivity is initially ten times less than of rock salt, no excessive temperature concentration was obtained on the heat sources

Study on friction behaviour of brake shoe materials for mining hoist

Science.gov (United States)

Ungureanu, M.; Ungureanu, N. S.; Crăciun, I.

2017-02-01

The friction coefficient in the brake linkages has an important influence on the braking efficiency and safety of machines. The paper presents a method for the study of the friction coefficient of the friction couple brake shoe-drum for mining hoist. In this context, it is interesting to define the friction coefficient, not just according to the materials in contact, but according to the entire ensemble of tribological factors of the friction couple.

Application for trackless mining technique in Benxi uranium mine

International Nuclear Information System (INIS)

Chen Bingguo

1998-01-01

The author narrates the circumstances achieving constructional target in Benxi Uranium Mine under relying on advance of science and technology and adopting small trackless mining equipment, presents the application of trackless mining equipment at mining small mine and complex mineral deposit and discusses the unique superiority of trackless mining technique in development work, mining preparation work and backstoping

Mining engineer requirements in a German coal mine

Energy Technology Data Exchange (ETDEWEB)

Rauhut, F J

1985-10-01

Basic developments in German coal mines, new definitions of working areas of mining engineers, and groups of requirements in education are discussed. These groups include: requirements of hard-coal mining at great depth and in extended collieries; application of process technology and information systems in semi-automated mines; thinking in processes and systems; organizational changes; future requirements of mining engineers; responsibility of the mining engineer for employees and society.

Mining Social Media and DBpedia Data Using Gephi and R

Directory of Open Access Journals (Sweden)

Sadiq HUSSAIN

2018-04-01

Full Text Available The big data is playing a big role in the field of machine learning and data mining. To extract meaningful and interesting information from big data mining is a challenge. The size of the data at social media and Wikipedia are increasing exponentially. To visualize such huge data is another aspect of big data. The roles of graphs are becoming important in case of visualization and modelling of such data. Gephi and R are two important visualization and exploration tools in this field. Using graph, one may find and calculate modularity, eccentricity, Indegree, Outdegree, betweenness centrality etc. In this paper, we had used Dbpedia, facebook and twitter datasets. We had used Gephi and R to look inside the structure of such data and comparing different statistics based on the graph by exploring the graphs.

The JET ITER-like wall experiment: First results and lessons for ITER

Energy Technology Data Exchange (ETDEWEB)

Horton, Lorne, E-mail: Lorne.Horton@jet.efda.org [EFDA-CSU Culham, Culham Science Centre, Abingdon, OX14 3DB (United Kingdom); European Commission, B-1049 Brussels (Belgium)

2013-10-15

Highlights: ► JET has recently completed the installation of an ITER-like wall. ► Important operational aspects have changed with the new wall. ► Initial experiments have confirmed the expected low fuel retention. ► Disruption dynamics have change dramatically. ► Development of wall-compatible, ITER-relevant regimes of operation has begun. -- Abstract: The JET programme is strongly focused on preparations for ITER construction and exploitation. To this end, a major programme of machine enhancements has recently been completed, including a new ITER-like wall, in which the plasma-facing armour in the main vacuum chamber is beryllium while that in the divertor is tungsten—the same combination of plasma-facing materials foreseen for ITER. The goal of the initial experimental campaigns is to fully characterise operation with the new wall, concentrating in particular on plasma-material interactions, and to make direct comparisons of plasma performance with the previous, carbon wall. This is being done in a progressive manner, with the input power and plasma performance being increased in combination with the commissioning of a comprehensive new real-time protection system. Progress achieved during the first set of experimental campaigns with the new wall, which took place from September 2011 to July 2012, is reported.

Geminivirus data warehouse: a database enriched with machine learning approaches.

Science.gov (United States)

Silva, Jose Cleydson F; Carvalho, Thales F M; Basso, Marcos F; Deguchi, Michihito; Pereira, Welison A; Sobrinho, Roberto R; Vidigal, Pedro M P; Brustolini, Otávio J B; Silva, Fabyano F; Dal-Bianco, Maximiller; Fontes, Renildes L F; Santos, Anésia A; Zerbini, Francisco Murilo; Cerqueira, Fabio R; Fontes, Elizabeth P B

2017-05-05

The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.

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

Science.gov (United States)

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

2018-01-01

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

Radioactivity measurements in Egyptian Phosphate Mines and Their Significance As a Source of Hazardous Radioactive Waste

International Nuclear Information System (INIS)

Hussein, A.Z.; Hussein, M.I.; Abdel Hady, M.L.

1999-01-01

Phosphate mines that may contain radioactive traces in the composition of their ores represent source of hazardous radioactive waste in the environment. Radioactivity measurements have been conducted in nine underground phosphate mines in the Egyptian Eastern Desert in order to estimate the occupational radiation exposure of mine workers in those mining sites. Measurements were carried out of airborne radon and its short- lived decay products (progeny) and thoron progeny, as well as radiation from mines walls, ceilings and floors. Conventional, well established techniques, methods and instrumentation were used to make these measurements. Comparison of experimental data and theoretical predictions showed partial agreement between these two sets of data. This result is partly attributed to the complex layout of these mines, which causes undesirable ventilation conditions, such as recirculation airflow patterns, which could not be adequately identified or quantified. The radiation data obtained were used to estimate the maximum Annual Dose (MAD), and other important occupational radiation exposure variables. These calculations indicate that in eight out of the nine mines surveyed, the MAD exceeded (by a factor of up to 7) the maximum recommended level by ICRP 60. Numbers of suggestions are made in order to reduce the MAD in the affected mines. This study could help in the estimation of the environmental impact of these mine operations on the environment

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...

Design upgrading on Ignitor Machine

International Nuclear Information System (INIS)

Cucchiaro, A.; Coletti, A.; Bianchi, A.

2006-01-01

Ignitor is a high field compact machine conceived to achieve ignition in D-T plasma. The upgraded design of the Plasma Chamber (PC) and of the First Wall (FW) system consider the updated scenarios for IGNITOR vertical plasma disruption (VDE). The electromagnetic (EM) loads arising from halo currents and net horizontal force with the proper toroidal distribution have been envisaged. The dynamic elastic-plastic structural analysis of the PC has brought to a tayloring of the wall thickness such to reduce the displacements within the clearance with toroidal coil. A detailed 3D finite elements model has been developed in order to evaluate the electromagnetic loads on FW. The thermal loads arisen from plasma heat loads (peak value 1.8 MW/m 2 ) have been also considered. In any case the maximum calculated stresses are within the allowable limits. The relevant 3D virtual mockup software simulates the inside of the PC including the entire boom with end-effector. This allowed for the analysis of the boom kinematics to cover all positions with the various end-effectors to assess the Remote Handling task operations. The structural analysis of the IGNITOR machine Load Assembly has been performed taking into account the friction coefficients between the significant components. The non linear analysis takes into account for both the in-plane and the out-of-plane loads. The vertical plasma disruption conditions (VDE) result in bigger out-of-plane loads than the normal operating conditions. Keys of proper dimensions between the 30 o extension C-Clamps modules was adopted to assure structural stability. As far as the interlaminar shear stresses on toroidal field coils are concerned, the related safety factors are decreased respect to the normal operating conditions, but remaining around 2. (author)

Fuel handling machine and auxiliary systems for a fuel handling cell

International Nuclear Information System (INIS)

Suikki, M.

2013-10-01

This working report is an update for as well as a supplement to an earlier fuel handling machine design (Kukkola and Roennqvist 2006). A focus in the earlier design proposal was primarily on the selection of a mechanical structure and operating principle for the fuel handling machine. This report introduces not only a fuel handling machine design but also auxiliary fuel handling cell equipment and its operation. An objective of the design work was to verify the operating principles of and space allocations for fuel handling cell equipment. The fuel handling machine is a remote controlled apparatus capable of handling intensely radiating fuel assemblies in the fuel handling cell of an encapsulation plant. The fuel handling cell is air tight space radiation-shielded with massive concrete walls. The fuel handling machine is based on a bridge crane capable of traveling in the handling cell along wall tracks. The bridge crane has its carriage provided with a carousel type turntable having mounted thereon both fixed and telescopic masts. The fixed mast has a gripper movable on linear guides for the transfer of fuel assemblies. The telescopic mast has a manipulator arm capable of maneuvering equipment present in the fuel handling cell, as well as conducting necessary maintenance and cleaning operations or rectifying possible fault conditions. The auxiliary fuel handling cell systems consist of several subsystems. The subsystems include a service manipulator, a tool carrier for manipulators, a material hatch, assisting winches, a vacuum cleaner, as well as a hose reel. With the exception of the vacuum cleaner, the devices included in the fuel handling cell's auxiliary system are only used when the actual encapsulation process is not ongoing. The malfunctions of mechanisms or actuators responsible for the motion actions of a fuel handling machine preclude in a worst case scenario the bringing of the fuel handling cell and related systems to a condition appropriate for

Fuel handling machine and auxiliary systems for a fuel handling cell

Energy Technology Data Exchange (ETDEWEB)

Suikki, M. [Optimik Oy, Turku (Finland)

2013-10-15

This working report is an update for as well as a supplement to an earlier fuel handling machine design (Kukkola and Roennqvist 2006). A focus in the earlier design proposal was primarily on the selection of a mechanical structure and operating principle for the fuel handling machine. This report introduces not only a fuel handling machine design but also auxiliary fuel handling cell equipment and its operation. An objective of the design work was to verify the operating principles of and space allocations for fuel handling cell equipment. The fuel handling machine is a remote controlled apparatus capable of handling intensely radiating fuel assemblies in the fuel handling cell of an encapsulation plant. The fuel handling cell is air tight space radiation-shielded with massive concrete walls. The fuel handling machine is based on a bridge crane capable of traveling in the handling cell along wall tracks. The bridge crane has its carriage provided with a carousel type turntable having mounted thereon both fixed and telescopic masts. The fixed mast has a gripper movable on linear guides for the transfer of fuel assemblies. The telescopic mast has a manipulator arm capable of maneuvering equipment present in the fuel handling cell, as well as conducting necessary maintenance and cleaning operations or rectifying possible fault conditions. The auxiliary fuel handling cell systems consist of several subsystems. The subsystems include a service manipulator, a tool carrier for manipulators, a material hatch, assisting winches, a vacuum cleaner, as well as a hose reel. With the exception of the vacuum cleaner, the devices included in the fuel handling cell's auxiliary system are only used when the actual encapsulation process is not ongoing. The malfunctions of mechanisms or actuators responsible for the motion actions of a fuel handling machine preclude in a worst case scenario the bringing of the fuel handling cell and related systems to a condition appropriate for

Influences of overload on low cycle fatigue behaviors of elbow pipe with local wall thinning

International Nuclear Information System (INIS)

Sato, Kyohei; Ogino, Kanako; Takahashi, Koji; Ando, Kotoji; Urabe, Yoshio

2011-01-01

Low cycle fatigue tests were conducted using 100A elbow pipe specimens with or without local wall thinning. Local wall thinning was machined on the inside of the extrados of test elbows to simulate metal loss due to flow-accelerated corrosion or liquid droplet impingement erosion. Low cycle fatigue tests were carried out under displacement control with an inner pressure of 9 MPa. To simulate seismic events, low cycle fatigue tests were carried out on elbow pipe subjected to cyclic overloads. Regardless of local wall thinning, fatigue life of overload pipe was not so different from that of the non-overload pipe in appearance. Miner's rule can be applied to evaluate fatigue life of the elbow pipes with and without wall thinning, even if overload is applied. (author)

Respirable quartz hazard associated with coal mine roof bolter dust

International Nuclear Information System (INIS)

Joy, G.J.; Beck, T.W.; Listak, J.M.

2010-01-01

Pneumoconiosis has been reported to be increasing among underground coal miners in the Southern Appalachian Region. The National Institute for Occupational Safety and Health conducted a study to examine the particle size distribution and quartz content of dust generated by the installation of roof bolts in mines. Forty-six bulk samples of roof bolting machine pre-cleaner cyclone dump dust and collector box dust were collected from 26 underground coal mines. Real-time and integrated airborne respirable dust concentrations were measured on 3 mining sections in 2 mines. The real-time airborne dust concentrations profiles were examined to identify any concentration changes that might be associated with pre-cleaner cyclone dust discharge events. The study showed that bolter dust is a potential inhalation hazard due to the fraction of dust less than 10 μm in size, and the quartz content of the dust. The pre-cleaner cyclone dust was significantly larger than the collector box dust, indicating that the pre-cleaner functioned properly in removing the larger dust size fraction from the airstream. However, the pre-cleaner dust still contained a substantial amount of respirable dust. It was concluded that in order to maintain the effectiveness of a roof bolter dust collector, periodic removal of dust is required. Appropriate work procedures and equipment are necessary to minimize exposure during this cleaning task. 13 refs., 3 tabs., 2 figs.

The JET real-time plasma-wall load monitoring system

International Nuclear Information System (INIS)

Valcárcel, D.F.; Alves, D.; Card, P.; Carvalho, B.B.; Devaux, S.; Felton, R.; Goodyear, A.; Lomas, P.J.; Maviglia, F.; McCullen, P.; Reux, C.; Rimini, F.; Stephen, A.; Zabeo, L.

2014-01-01

Highlights: • The paper describes the JET real-time system monitoring the first-wall plasma loads. • It presents the motivation, physics basis, design and implementation of the system. • It also presents the integration in the JET CODAS. • Operational results are presented. - Abstract: In the past, the Joint European Torus (JET) has operated with a first-wall composed of Carbon Fibre Composite (CFC) tiles. The thermal properties of the wall were monitored in real-time during plasma operations by the WALLS system. This software routinely performed model-based thermal calculations of the divertor and Inner Wall Guard Limiter (IWGL) tiles calculating bulk temperatures and strike-point positions as well as raising alarms when these were beyond operational limits. Operation with the new ITER-like wall presents a whole new set of challenges regarding machine protection. One example relates to the new beryllium limiter tiles with a melting point of 1278 °C, which can be achieved during a plasma discharge well before the bulk temperature rises to this value. This requires new and accurate power deposition and thermal diffusion models. New systems were deployed for safe operation with the new wall: the Real-time Protection Sequencer (RTPS) and the Vessel Thermal Map (VTM). The former allows for a coordinated stop of the pulse and the latter uses the surface temperature map, measured by infra-red (IR) cameras, to raise alarms in case of hot-spots. Integration of WALLS with these systems is required as RTPS responds to raised alarms and VTM, the primary protection system for the ITER-like wall, can use WALLS as a vessel temperature provider. This paper presents the engineering design, implementation and results of WALLS towards D-T operation, where it will act as a primary protection system when the IR cameras are blinded by the fusion reaction neutrons. The first operational results, with emphasis on its performance, are also presented

The JET real-time plasma-wall load monitoring system

Energy Technology Data Exchange (ETDEWEB)

Valcárcel, D.F., E-mail: daniel.valcarcel@ipfn.ist.utl.pt [Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade Técnica de Lisboa, P-1049-001 Lisboa (Portugal); Alves, D. [Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade Técnica de Lisboa, P-1049-001 Lisboa (Portugal); Card, P. [Euratom/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Carvalho, B.B. [Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade Técnica de Lisboa, P-1049-001 Lisboa (Portugal); Devaux, S. [Max-Planck-Institut für Plasmaphysik, EURATOM-Assoziation, D-85748 Garching (Germany); Felton, R.; Goodyear, A.; Lomas, P.J. [Euratom/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Maviglia, F. [Associazione EURATOM-ENEA-CREATE, Univ. di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy); McCullen, P. [Euratom/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Reux, C. [Ecole Polytechnique, LPP, CNRS UMR 7648, 91128 Palaiseau (France); Rimini, F.; Stephen, A. [Euratom/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Zabeo, L. [ITER Organization, Route de Vinon sur Verdon, 13115 St., Paul Lez Durance (France); and others

2014-03-15

Highlights: • The paper describes the JET real-time system monitoring the first-wall plasma loads. • It presents the motivation, physics basis, design and implementation of the system. • It also presents the integration in the JET CODAS. • Operational results are presented. - Abstract: In the past, the Joint European Torus (JET) has operated with a first-wall composed of Carbon Fibre Composite (CFC) tiles. The thermal properties of the wall were monitored in real-time during plasma operations by the WALLS system. This software routinely performed model-based thermal calculations of the divertor and Inner Wall Guard Limiter (IWGL) tiles calculating bulk temperatures and strike-point positions as well as raising alarms when these were beyond operational limits. Operation with the new ITER-like wall presents a whole new set of challenges regarding machine protection. One example relates to the new beryllium limiter tiles with a melting point of 1278 °C, which can be achieved during a plasma discharge well before the bulk temperature rises to this value. This requires new and accurate power deposition and thermal diffusion models. New systems were deployed for safe operation with the new wall: the Real-time Protection Sequencer (RTPS) and the Vessel Thermal Map (VTM). The former allows for a coordinated stop of the pulse and the latter uses the surface temperature map, measured by infra-red (IR) cameras, to raise alarms in case of hot-spots. Integration of WALLS with these systems is required as RTPS responds to raised alarms and VTM, the primary protection system for the ITER-like wall, can use WALLS as a vessel temperature provider. This paper presents the engineering design, implementation and results of WALLS towards D-T operation, where it will act as a primary protection system when the IR cameras are blinded by the fusion reaction neutrons. The first operational results, with emphasis on its performance, are also presented.

Technical and economic assessment of losses caused by rock swelling in mines of the Western Donbass

Energy Technology Data Exchange (ETDEWEB)

Pirskii, A A; Stovpnik, S N; Shmigol' , A V

1988-07-01

Describes mining geologic conditions in mines of the Pavlovgradugol' association where production increased by 1.7 times during the last 10 years. Floor swelling of 1.1 m/a occurs at depths over 300 m and with rock strength in side walls below 20 MPa. Annually 22 km of workings must undergo repair and 10.4% of crews does the repair work. Technical and economic consequences of floor swelling are analyzed. Annual outlays on maintenance of 1 m of roadways increased to 160-200 rubles. Annual losses on maintenance of workings per coal mining association lie within 300,000-500,000 rubles. At the im. Geroev Kosmosa and im. Leninskogo Komsomola Ukrainy mines these losses amount to 520,000-730,000 and 840,000-845,000 rubles respectively. A comprehensive analysis of production losses and delays in development workings caused by floor swelling is presented. Formulae for loss calculation are given.

Machine rates for selected forest harvesting machines

Science.gov (United States)

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

Data mining for the identification of metabolic syndrome status.

Science.gov (United States)

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS.

Data mining for the identification of metabolic syndrome status

Science.gov (United States)

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS. PMID:29383020

Engineering design and performances of the IGNITOR first wall

International Nuclear Information System (INIS)

Bonizzoni, G.

1989-01-01

Extensive work was carried out to define the working conditions and the reference design of the first wall for the IGNITOR machine: graphite covered modular elements attached to the vacuum vessel by a locking key for remote handling are proposed. The work includes a transient thermostructural analysis of the graphite tiles to evaluate temperatures and thermal stresses in normal and fault conditions. A full scale prototype of the element was manufactured. (author). 7 figs.; 1 tab

Mill tailings based composites as paste backfill in mines of U-bearing dolomitic limestone ore

Directory of Open Access Journals (Sweden)

Sandeep Panchal

2018-04-01

Full Text Available This paper elaborates on the development of paste backfill using mill tailings generated during the processing of a uranium ore deposit hosted in dolomitic limestone. The tailings have been characterized in terms of the physical, chemical and mineralogical properties. Time-dependent rheological behaviors and geotechnical properties of cemented paste backfill (CPB are also determined. The studies show that the mill tailing has the potential to form paste and the CPB has adequate strength to provide support to mine pillars, roofs, and walls. Keywords: Mining engineering, Uranium ore deposit, Tailings, Cemented paste backfill (CPB, Rheology, Compressive strength

Ensemble Data Mining Methods

Science.gov (United States)

Oza, Nikunj C.

2004-01-01

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 better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

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

Science.gov (United States)

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

2017-12-01

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

data mining in distributed database

International Nuclear Information System (INIS)

Ghunaim, A.A.A.

2007-01-01

as we march into the age of digital information, the collection and the storage of large quantities of data is increased, and the problem of data overload looms ominously ahead. it is estimated today that the volume of data stored by a company doubles every year but the amount of meaningful information is decreases rapidly. the ability to analyze and understand massive datasets lags far behind the ability to gather and store the data. the unbridled growth of data will inevitably lead to a situation in which it is increasingly difficult to access the desired information; it will always be like looking for a needle in a haystack, and where only the amount of hay will be growing all the time . so, a new generation of computational techniques and tools is required to analyze and understand the rapidly growing volumes of data . and, because the information technology (it) has become a strategic weapon in the modern life, it is needed to use a new decision support tools to be an international powerful competitor.data mining is one of these tools and its methods make it possible to extract decisive knowledge needed by an enterprise and it means that it concerned with inferring models from data , including statistical pattern recognition, applied statistics, machine learning , and neural networks. data mining is a tool for increasing productivity of people trying to build predictive models. data mining techniques have been applied successfully to several real world problem domains; but the application in the nuclear reactors field has only little attention . one of the main reasons, is the difficulty in obtaining the data sets

Productivity Improvement in Underground Coal Mines - A Case Study

Directory of Open Access Journals (Sweden)

Devi Prasad Mishra

2013-01-01

Full Text Available Improvement of productivity has become an important goal for today's coal industry in the race to increase price competitiveness. The challenge now lying ahead for the coal industry is to identify areas of waste, meet the market price and maintain a healthy profit. The only way to achieve this is to reduce production costs by improving productivity, efficiency and the effectiveness of the equipment. This paper aims to identify the various factors and problems affecting the productivity of underground coal mines adopting the bord and pillar method of mining and to propose suitable measures for improving them. The various key factors affecting productivity, namely the cycle of operations, manpower deployment, machine efficiency, material handling and management of manpower are discussed. In addition, the problem of side discharge loader (SDL cable handling resulting in the wastage of precious manpower resources and SDL breakdown have also been identified and resolved in this paper.

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