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Sample records for hybrid pm machines

  1. Superconducting PM undiffused machines with stationary superconducting coils

    DOEpatents

    Hsu, John S.; Schwenterly, S. William

    2004-03-02

    A superconducting PM machine has a stator, a rotor and a stationary excitation source without the need of a ferromagnetic frame which is cryogenically cooled for operation in the superconducting state. PM material is placed between poles on the rotor to prevent leakage or diffusion of secondary flux before reaching the main air gap, or to divert PM flux where it is desired to weaken flux in the main air gap. The PM material provides hop-along capability for the machine in the event of a fault condition.

  2. PM Motor Parametric Design Analyses for Hybrid Electric Vehicle Traction Drive Application: Interim Report

    SciTech Connect

    Staunton, R.H.

    2004-08-11

    The Department of Energy's (DOE) Office of FreedomCAR (Cooperative Automotive Research) and Vehicle Technologies has a strong interest in making rapid progress in permanent magnet (PM) machine development. The program is directing various technology development projects that will advance the technology and lead to request for proposals (RFP) for manufacturer prototypes. This aggressive approach is possible because the technology is clearly within reach and the approach is deemed essential, based on strong market demand, escalating fuel prices, and competitive considerations. In response, this study began parallel development paths that included a literature search/review, development and utilization of multiple parametric models to determine the effects of design parameters, verification of the modeling methodology, development of an interior PM (IPM) machine baseline design, development of alternative machine baseline designs, and cost analyses for several candidate machines. This interim progress report summarizes the results of these activities as of June 2004. This report provides background and summary information for recent machine parametric studies and testing programs that demonstrate both the potential capabilities and technical limitations of brushless PM machines (axial gap and radial gap), the IPM machine, the surface-mount PM machines (interior or exterior rotor), induction machines, and switched reluctance machines. The FreedomCAR program, while acknowledging the progress made by Oak Ridge National Laboratory, Delphi, Delco-Remy International, and others in these programs, has redirected efforts toward a ''short path'' to a marketable and competitive PM motor for hybrid electric vehicle traction applications. The program has developed a set of performance targets for the type of traction machine desired. The short-path approach entails a comprehensive design effort focusing on the IPM machine and meeting the performance targets. The selection of the

  3. A novel PM motor with hybrid PM excitation and asymmetric rotor structure for high torque performance

    PubMed Central

    Xu, Gaohong; Liu, Guohai; Du, Xinxin; Bian, Fangfang

    2017-01-01

    This paper proposes a novel permanent magnet (PM) motor for high torque performance, in which hybrid PM material and asymmetric rotor design are applied. The hybrid PM material is adopted to reduce the consumption of rare-earth PM because ferrite PM is assisted to enhance the torque production. Meanwhile, the rotor structure is designed to be asymmetric by shifting the surface-insert PM (SPM), which is used to improve the torque performance, including average torque and torque ripple. Moreover, the reasons for improvement of the torque performance are explained by evaluation and analysis of the performances of the proposed motor. Compared with SPM motor and V-type motor, the merit of high utilization ratio of rare-earth PM is also confirmed, showing that the proposed motor can offer higher torque density and lower torque ripple simultaneously with less consumption of rare-earth PM. PMID:28382228

  4. PM Motor Parametric Design Analyses for a Hybrid Electric Vehicle Traction Drive Application

    SciTech Connect

    Staunton, R.H.

    2004-10-11

    The Department of Energy's (DOE) Office of FreedomCAR (Cooperative Automotive Research) and Vehicle Technologies office has a strong interest in making rapid progress in permanent magnet (PM) machine development. The DOE FreedomCAR program is directing various technology development projects that will advance the technology and hopefully lead to a near-term request for proposals (RFP) for a to-be-determined level of initial production. This aggressive approach is possible because the technology is clearly within reach and the approach is deemed essential, based on strong market demand, escalating fuel prices, and competitive considerations. In response, this study began parallel development paths that included a literature search/review, development and utilization of multiple parametric models, verification of the modeling methodology, development of an interior PM (IPM) machine baseline design, development of alternative machine baseline designs, and cost analyses for several candidate machines. This report summarizes the results of these activities as of September 2004. This report provides background and summary information for recent machine parametric studies and testing programs that demonstrate both the potential capabilities and technical limitations of brushless PM machines (axial gap and radial gap), the IPM machine, the surface-mount PM machines (interior or exterior rotor), induction machines, and switched-reluctance machines. The FreedomCAR program, while acknowledging the progress made by Oak Ridge National Laboratory (ORNL), Delphi, Delco-Remy International, and others in these programs, has redirected efforts toward a ''short path'' to a marketable and competitive PM motor for hybrid electric vehicle (HEV) traction applications. The program has developed a set of performance targets for the type of traction machine desired. The short-path approach entails a comprehensive design effort focusing on the IPM machine and meeting the performance targets

  5. A Parallel Vector Machine for the PM Programming Language

    NASA Astrophysics Data System (ADS)

    Bellerby, Tim

    2016-04-01

    PM is a new programming language which aims to make the writing of computational geoscience models on parallel hardware accessible to scientists who are not themselves expert parallel programmers. It is based around the concept of communicating operators: language constructs that enable variables local to a single invocation of a parallelised loop to be viewed as if they were arrays spanning the entire loop domain. This mechanism enables different loop invocations (which may or may not be executing on different processors) to exchange information in a manner that extends the successful Communicating Sequential Processes idiom from single messages to collective communication. Communicating operators avoid the additional synchronisation mechanisms, such as atomic variables, required when programming using the Partitioned Global Address Space (PGAS) paradigm. Using a single loop invocation as the fundamental unit of concurrency enables PM to uniformly represent different levels of parallelism from vector operations through shared memory systems to distributed grids. This paper describes an implementation of PM based on a vectorised virtual machine. On a single processor node, concurrent operations are implemented using masked vector operations. Virtual machine instructions operate on vectors of values and may be unmasked, masked using a Boolean field, or masked using an array of active vector cell locations. Conditional structures (such as if-then-else or while statement implementations) calculate and apply masks to the operations they control. A shift in mask representation from Boolean to location-list occurs when active locations become sufficiently sparse. Parallel loops unfold data structures (or vectors of data structures for nested loops) into vectors of values that may additionally be distributed over multiple computational nodes and then split into micro-threads compatible with the size of the local cache. Inter-node communication is accomplished using

  6. FEM analysis of an single stator dual PM rotors axial synchronous machine

    NASA Astrophysics Data System (ADS)

    Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

    2017-01-01

    The actual e - continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors. The proposed topologies, the magneto-motive force analysis and quasi 3D-FEM analysis are the core of the paper.

  7. Development of Novel Pre-alloyed PM Steels for Optimization of Machinability and Fatigue Resistance of PM Components

    NASA Astrophysics Data System (ADS)

    Mardan, Milad; Blais, Carl

    2016-03-01

    It is well known that a large proportion of ferrous PM components require secondary machining operations for dimensional conformance or for producing geometrical features that cannot be generated during die compaction. Nevertheless, the machining behavior of PM parts is generally characterized as being "difficult" due to the presence of residual porosity that lowers thermal conductivity and induces interrupted cutting. Several admixed additives such as MnS and BN-h can be used to improve the machining behavior of PM steels. Nevertheless, their negative effect on mechanical properties, especially fatigue resistance, makes their utilization uninteresting for the fabrication of high-performance PM steel components. This article summarizes the work carried out to develop a novel PM steel that was especially engineered to form machinability enhancing precipitates. This new material is pre-alloyed with tin (Sn) in order to form Cu-Sn (Cu(α)) precipitates during transient liquid phase sintering. The newly developed material presents machinability improvement of 165% compared to reference material used in the PM industry as well as increases in toughness and fatigue resistance of 100% and 13%, respectively.

  8. Discrete mechanics, "time machines" and hybrid systems

    NASA Astrophysics Data System (ADS)

    Elze, Hans-Thomas

    2013-09-01

    Modifying the discrete mechanics proposed by T.D. Lee, we construct a class of discrete classical Hamiltonian systems, in which time is one of the dynamical variables. This includes a toy model of "time machines" which can travel forward and backward in time and which differ from models based on closed timelike curves (CTCs). In the continuum limit, we explore the interaction between such time reversing machines and quantum mechanical objects, employing a recent description of quantum-classical hybrids.

  9. Multistage axial-flux PM machine for wheel direct drive

    SciTech Connect

    Caricchi, F.; Crescimbini, F.; Mezzetti, F.; Santini, E.

    1996-07-01

    The design of direct-drive wheel motors must comply with diameter restriction due to housing the motor in a wheel rim and allow the achievement of very high torque density and overload capability. Slotless axial-flux permanent magnet machines (AFPMs) prove to be the best candidate for application in electric vehicles as direct-drive wheel motors, as in comparison with conventional machines they allow designs with higher compactness, lightness and efficiency. The paper presents a newly conceived AFPM which has a multistage structure and a water-cooled ironless stator. In the proposed new topology of the machine the space formerly occupied by the toroidal core becomes a water duct, which removes heat directly from the interior surface of the stator winding. The high efficiency of the machine cooling arrangement allows long-term 100% overload operation and great reduction of the machine weight. The multistage structure of the machine is suited to overcome the restriction on the machine diameter and meet the torque required at the wheel shaft. The paper gives guidelines for the design of a multistage AFPM with water-cooled ironless stator, and describes characteristics of a two-stage prototype machine rated 215 N{center_dot}m, 1,100 r/min.

  10. Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies

    PubMed Central

    Lary, D. J.; Lary, T.; Sattler, B.

    2015-01-01

    With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM2.5 from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. We demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM2.5 appears to have an impact on some aspects of mental health. PMID:26005352

  11. A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

    NASA Astrophysics Data System (ADS)

    Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

    2017-05-01

    A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

  12. A novel hybrid strategy for PM2.5 concentration analysis and prediction.

    PubMed

    Jiang, Ping; Dong, Qingli; Li, Peizhi

    2017-03-22

    The analysis and prediction of air pollutants are of great significance in environmental research today since airborne pollution is a substantial threat, especially in urban agglomerations of China. To develop more effective warning systems and management advice, the authorities and city dwellers need more accurate forecasts of the air pollution. Most previous analysis systems were based on costly observation apparatus at fixed sites, forecasting models were usually built on observations within a certain range, and some observations contained biases. In this paper, a novel and effective framework, termed HML-AFNN, was successfully developed to analyse and forecast the concentration of particular matter (PM2.5) for a selected number of forward time steps. In a simulation of the trajectory of air pollutants, the high-dimension association rules (HDAR) approach considered the tempo-spatial relations, as well as the meteorological and geographical factors of the ambient regions, as parameters. In addition, the learning vector quantization (LVQ) network was adopted to select the appropriate inputs to improve the efficiency of the training process. Moreover, an adaptive fuzzy neural network (AFNN), a combination of neural and fuzzy logic, was utilized to analyse and predict the PM2.5 concentration. The experiment results of our study on two major urban agglomerations of China, the Jing-Jin-Ji area and Pearl River Delta, over a period of more than one year demonstrated that the developed hybrid HML-AFNN model outperforms a plain AFNN, an HM-AFNN model without LVQ and the least squares support vector machines (LS-SVM); this superior performance can be determined from the values of several error indexes, including MAE, MAPE and band errors. This hybrid model, which has robust and accurate results, shows the potential to be a political and administrative method to issue effective early warnings and to design suitable abatement strategies.

  13. Electric machine for hybrid motor vehicle

    DOEpatents

    Hsu, John Sheungchun

    2007-09-18

    A power system for a motor vehicle having an internal combustion engine and an electric machine is disclosed. The electric machine has a stator, a permanent magnet rotor, an uncluttered rotor spaced from the permanent magnet rotor, and at least one secondary core assembly. The power system also has a gearing arrangement for coupling the internal combustion engine to wheels on the vehicle thereby providing a means for the electric machine to both power assist and brake in relation to the output of the internal combustion engine.

  14. Hybrid-secondary uncluttered induction machine

    DOEpatents

    Hsu, John S.

    2001-01-01

    An uncluttered secondary induction machine (100) includes an uncluttered rotating transformer (66) which is mounted on the same shaft as the rotor (73) of the induction machine. Current in the rotor (73) is electrically connected to current in the rotor winding (67) of the transformer, which is not electrically connected to, but is magnetically coupled to, a stator secondary winding (40). The stator secondary winding (40) is alternately connected to an effective resistance (41), an AC source inverter (42) or a magnetic switch (43) to provide a cost effective slip-energy-controlled, adjustable speed, induction motor that operates over a wide speed range from below synchronous speed to above synchronous speed based on the AC line frequency fed to the stator.

  15. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

    PubMed

    Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

    2016-01-01

    Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

  16. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology

    PubMed Central

    Ju, Ying

    2016-01-01

    Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics. PMID:27478823

  17. Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

    NASA Astrophysics Data System (ADS)

    Zhan, Yu; Luo, Yuzhou; Deng, Xunfei; Chen, Huajin; Grieneisen, Michael L.; Shen, Xueyou; Zhu, Lizhong; Zhang, Minghua

    2017-04-01

    A high degree of uncertainty associated with the emission inventory for China tends to degrade the performance of chemical transport models in predicting PM2.5 concentrations especially on a daily basis. In this study a novel machine learning algorithm, Geographically-Weighted Gradient Boosting Machine (GW-GBM), was developed by improving GBM through building spatial smoothing kernels to weigh the loss function. This modification addressed the spatial nonstationarity of the relationships between PM2.5 concentrations and predictor variables such as aerosol optical depth (AOD) and meteorological conditions. GW-GBM also overcame the estimation bias of PM2.5 concentrations due to missing AOD retrievals, and thus potentially improved subsequent exposure analyses. GW-GBM showed good performance in predicting daily PM2.5 concentrations (R2 = 0.76, RMSE = 23.0 μg/m3) even with partially missing AOD data, which was better than the original GBM model (R2 = 0.71, RMSE = 25.3 μg/m3). On the basis of the continuous spatiotemporal prediction of PM2.5 concentrations, it was predicted that 95% of the population lived in areas where the estimated annual mean PM2.5 concentration was higher than 35 μg/m3, and 45% of the population was exposed to PM2.5 >75 μg/m3 for over 100 days in 2014. GW-GBM accurately predicted continuous daily PM2.5 concentrations in China for assessing acute human health effects.

  18. Insights Into the Morphology of the East Asia PM2.5 Annual Cycle Provided by Machine Learning

    PubMed Central

    Wu, Daji; Zewdie, Gebreab K; Liu, Xun; Kneen, Melanie Anne; Lary, David John

    2017-01-01

    The abundance of airborne particulate matter with an aerodynamic equivalent diameter of 2.5 µm or less (PM2.5) is a significant environmental and health issue. Many tools have been used to examine the relationship between PM2.5 abundance and meteorological variables, but some of the relationships are nonlinear, non-Gaussian, and even unknown. Machine learning provides a broad range of practical algorithms to help examine this issue. In this study, we use machine learning to classify the morphology of PM2.5 seasonal cycles in East Asia. Machine learning is able to objectively classify the seasonal cycles and, without a priori assumption, is able to clearly distinguish between urban and rural areas. We show an example of this in the Sichuan Basin of China. Furthermore, machine learning is also able to provide physical insights by identifying the key factors associated with each distinct shape of the seasonal cycle, such as highlighting the key role played by the topography and the built environment. PMID:28469447

  19. Rolling forecasting model of PM2.5 concentration based on support vector machine and particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Chang-Jiang; Dai, Li-Jie; Ma, Lei-Ming

    2016-10-01

    The data of current PM2.5 model forecasting greatly deviate from the measured concentration. In order to solve this problem, Support Vector Machine (SVM) and Particle Swarm Optimization (PSO) are combined to build a rolling forecasting model. The important parameters (C and γ) of SVM are optimized by PSO. The data (from February to July in 2015), consisting of measured PM2.5 concentration, PM2.5 model forecasting concentration and five main model forecasting meteorological factors, are provided by Shanghai Meteorological Bureau in Pudong New Area. The rolling model is used to forecast hourly PM2.5 concentration in 12 hours in advance and the nighttime average concentration (mean value from 9 pm to next day 8 am) during the upcoming day. The training data and the optimal parameters of SVM model are different in every forecasting, that is to say, different models (dynamic models) are built in every forecasting. SVM model is compared with Radical Basis Function Neural Network (RBFNN), Multi-variable Linear Regression (MLR) and WRF-CHEM. Experimental results show that the proposed model improves the forecasting accuracy of hourly PM2.5 concentration in 12 hours in advance and nighttime average concentration during the upcoming day. SVM model performs better than MLR, RBFNN and WRF-CHEM. SVM model greatly improves the forecasting accuracy of PM2.5 concentration one hour in advance, according with the result concluded from previous research. The rolling forecasting model can be applied to the field of PM2.5 concentration forecasting, and can offer help to meteorological administration in PM2.5 concentration monitoring and forecasting.

  20. Machine vision system for inspecting characteristics of hybrid rice seed

    NASA Astrophysics Data System (ADS)

    Cheng, Fang; Ying, Yibin

    2004-03-01

    Obtaining clear images advantaged of improving the classification accuracy involves many factors, light source, lens extender and background were discussed in this paper. The analysis of rice seed reflectance curves showed that the wavelength of light source for discrimination of the diseased seeds from normal rice seeds in the monochromic image recognition mode was about 815nm for jinyou402 and shanyou10. To determine optimizing conditions for acquiring digital images of rice seed using a computer vision system, an adjustable color machine vision system was developed. The machine vision system with 20mm to 25mm lens extender produce close-up images which made it easy to object recognition of characteristics in hybrid rice seeds. White background was proved to be better than black background for inspecting rice seeds infected by disease and using the algorithms based on shape. Experimental results indicated good classification for most of the characteristics with the machine vision system. The same algorithm yielded better results in optimizing condition for quality inspection of rice seed. Specifically, the image processing can correct for details such as fine fissure with the machine vision system.

  1. Hybrid-secondary uncluttered permanent magnet machine and method

    DOEpatents

    Hsu, John S.

    2005-12-20

    An electric machine (40) has a stator (43), a permanent magnet rotor (38) with permanent magnets (39) and a magnetic coupling uncluttered rotor (46) for inducing a slip energy current in secondary coils (47). A dc flux can be produced in the uncluttered rotor when the secondary coils are fed with dc currents. The magnetic coupling uncluttered rotor (46) has magnetic brushes (A, B, C, D) which couple flux in through the rotor (46) to the secondary coils (47c, 47d) without inducing a current in the rotor (46) and without coupling a stator rotational energy component to the secondary coils (47c, 47d). The machine can be operated as a motor or a generator in multi-phase or single-phase embodiments and is applicable to the hybrid electric vehicle. A method of providing a slip energy controller is also disclosed.

  2. Manufacturing and Machining Challenges of Hybrid Aluminium Metal Matix Composites

    NASA Astrophysics Data System (ADS)

    Baburaja, Kammuluri; Sainadh Teja, S.; Karthik Sri, D.; Kuldeep, J.; Gowtham, V.

    2017-08-01

    Manufacturing which involves material removal processes or material addition processes or material transformation processes. One or all the processes to obtain the final desired properties for a material with desired shape which meets the required precision and accuracy values for the expected service life of a material in working conditions. Researchers found the utility of aluminium to be the second largest after steel. Aluminium and its metal matrix composite possess wide applications in various applications in aerospace industry, automobile industry, Constructions and even in kitchen utensils. Hybrid Al-MMCconsist of two different materials, and one will be from organic origin along with the base material. In this paper an attempt is made to bring out the importance of utilization of aluminium and the challenges concerned in manufacturing and machining of hybrid aluminium MMC.

  3. Permanent magnet machine and method with reluctance poles and non-identical PM poles for high density operation

    DOEpatents

    Hsu, John S.

    2010-05-18

    A method and apparatus in which a stator (11) and a rotor (12) define a primary air gap (20) for receiving AC flux and at least one source (23, 40), and preferably two sources (23, 24, 40) of DC excitation are positioned for inducing DC flux at opposite ends of the rotor (12). Portions of PM material (17, 17a) are provided as boundaries separating PM rotor pole portions from each other and from reluctance poles. The PM poles (18) and the reluctance poles (19) can be formed with poles of one polarity having enlarged flux paths in relation to flux paths for pole portions of an opposite polarity, the enlarged flux paths communicating with a core of the rotor (12) so as to increase reluctance torque produced by the electric machine. Reluctance torque is increased by providing asymmetrical pole faces. The DC excitation can also use asymmetric poles and asymmetric excitation sources. Several embodiments are disclosed with additional variations.

  4. Performance Prediction of a Hybrid-Excitation Synchronous Machine with Axially Arranged Excitation Poles and Permanent-Magnet Poles

    NASA Astrophysics Data System (ADS)

    Matsuuchi, Kotaro; Fukami, Tadashi; Naoe, Nobuyuki; Hanaoka, Ryoichi; Takata, Shinzo; Miyamoto, Toshio

    This paper presents a method of predicting the steady-state performance of a new hybrid-excitation synchronous machine (HESM) theoretically. The field pole of this HESM is axially divided into two parts; one is an excitation part and the other a permanent-magnet (PM) part. A nonlinear equivalent circuit, which can include the saliency of the rotor and the magnetic saturation due to iron core, is derived. Based on this equivalent circuit, the steady-state performance of the HESM is calculated, and the results are confirmed through experiments.

  5. HYBRID NEURAL NETWORK AND SUPPORT VECTOR MACHINE METHOD FOR OPTIMIZATION

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan (Inventor)

    2005-01-01

    System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

  6. Hybrid Neural Network and Support Vector Machine Method for Optimization

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan (Inventor)

    2007-01-01

    System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

  7. Electrical test prediction using hybrid metrology and machine learning

    NASA Astrophysics Data System (ADS)

    Breton, Mary; Chao, Robin; Muthinti, Gangadhara Raja; de la Peña, Abraham A.; Simon, Jacques; Cepler, Aron J.; Sendelbach, Matthew; Gaudiello, John; Emans, Susan; Shifrin, Michael; Etzioni, Yoav; Urenski, Ronen; Lee, Wei Ti

    2017-03-01

    Electrical test measurement in the back-end of line (BEOL) is crucial for wafer and die sorting as well as comparing intended process splits. Any in-line, nondestructive technique in the process flow to accurately predict these measurements can significantly improve mean-time-to-detect (MTTD) of defects and improve cycle times for yield and process learning. Measuring after BEOL metallization is commonly done for process control and learning, particularly with scatterometry (also called OCD (Optical Critical Dimension)), which can solve for multiple profile parameters such as metal line height or sidewall angle and does so within patterned regions. This gives scatterometry an advantage over inline microscopy-based techniques, which provide top-down information, since such techniques can be insensitive to sidewall variations hidden under the metal fill of the trench. But when faced with correlation to electrical test measurements that are specific to the BEOL processing, both techniques face the additional challenge of sampling. Microscopy-based techniques are sampling-limited by their small probe size, while scatterometry is traditionally limited (for microprocessors) to scribe targets that mimic device ground rules but are not necessarily designed to be electrically testable. A solution to this sampling challenge lies in a fast reference-based machine learning capability that allows for OCD measurement directly of the electrically-testable structures, even when they are not OCD-compatible. By incorporating such direct OCD measurements, correlation to, and therefore prediction of, resistance of BEOL electrical test structures is significantly improved. Improvements in prediction capability for multiple types of in-die electrically-testable device structures is demonstrated. To further improve the quality of the prediction of the electrical resistance measurements, hybrid metrology using the OCD measurements as well as X-ray metrology (XRF) is used. Hybrid metrology

  8. Multi-stage axial-flux PM machine for wheel direct drive

    SciTech Connect

    Caricchi, F.; Crescimbini, F.; Mezzetti, F.; Santini, E.

    1995-12-31

    The design of direct-driven wheel motors must comply with diameter restriction due to housing the motor in a wheel rim and allow the achievement of very high torque density and overload capability. Slotless axial-flux permanent magnet machines (AFPMs) prove to be one best candidate for application in electric vehicles as direct-drive wheel motors, as in comparison with conventional machines they allow designs with higher compactness, lightness and efficiency. The paper presents a newly-conceived AFPM which has multi-stage structure and water-cooled ironless stator. In the proposed new topology of the machine the space formerly occupied by the toroidal core becomes a water duct, which removes heat directly from the interior surface of the stator winding. The high efficiency of the machine cooling arrangement allows long-term 100% overload operation and great reduction of the machine weight. The multistage structure of the machine is suited to overcome the restriction on the machine diameter and meet the torque required at the wheel shaft. The paper gives guidelines for the design of a multi-stage AFPM with water-cooled ironless stator, and describes characteristics of a two-stage prototype machine rated 220 Nm, 1,100 rpm.

  9. Design of high-performing hybrid meta-heuristics for unrelated parallel machine scheduling with machine eligibility and precedence constraints

    NASA Astrophysics Data System (ADS)

    Afzalirad, Mojtaba; Rezaeian, Javad

    2016-04-01

    This study involves an unrelated parallel machine scheduling problem in which sequence-dependent set-up times, different release dates, machine eligibility and precedence constraints are considered to minimize total late works. A new mixed-integer programming model is presented and two efficient hybrid meta-heuristics, genetic algorithm and ant colony optimization, combined with the acceptance strategy of the simulated annealing algorithm (Metropolis acceptance rule), are proposed to solve this problem. Manifestly, the precedence constraints greatly increase the complexity of the scheduling problem to generate feasible solutions, especially in a parallel machine environment. In this research, a new corrective algorithm is proposed to obtain the feasibility in all stages of the algorithms. The performance of the proposed algorithms is evaluated in numerical examples. The results indicate that the suggested hybrid ant colony optimization statistically outperformed the proposed hybrid genetic algorithm in solving large-size test problems.

  10. Soft electroactive actuators and hard ratchet-wheels enable unidirectional locomotion of hybrid machine

    NASA Astrophysics Data System (ADS)

    Sun, Wenjie; Liu, Fan; Ma, Ziqi; Li, Chenghai; Zhou, Jinxiong

    2017-01-01

    Combining synergistically the muscle-like actuation of soft materials and load-carrying and locomotive capability of hard mechanical components results in hybrid soft machines that can exhibit specific functions. Here, we describe the design, fabrication, modeling and experiment of a hybrid soft machine enabled by marrying unidirectionally actuated dielectric elastomer (DE) membrane-spring system and ratchet wheels. Subjected to an applied voltage 8.2 kV at ramping velocity 820 V/s, the hybrid machine prototype exhibits monotonic uniaxial locomotion with an averaged velocity 0.5mm/s. The underlying physics and working mechanisms of the soft machine are verified and elucidated by finite element simulation.

  11. Multi-objective optimization design of a high-speed PM machine supported by magnetic bearings

    NASA Astrophysics Data System (ADS)

    Han, Bangcheng; Xue, Qinghao; Liu, Xu; Wang, Kun

    2017-08-01

    This paper proposes an optimal design method of permanent magnet machine (PMM) with cylindrical permanent magnet supported by magnetic bearings. The objectives of optimization design are minimizing the rotor loss while maximizing the power density of the PMM as well as the 1st order nature frequency of the rotor, and the constraints are size, the strength safety factor and the phase current. A 30 kW, 48,000 r/min PMM designed by the multi-objective optimization method is proposed and the results indicate: the rotor loss is decreased from 393 W to 290 W (is reduced by 26.2%); the power density of the PMM is increased from 1.86 kW/kg to 2.19 kW/kg (is increased by 17.7%); the 1st order nature frequency of the rotor is increased from 1579 Hz to 1812 Hz (is increased by 14.7%). The performances of the PMM are improved after optimization, which are verified by experiment.

  12. Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

    NASA Astrophysics Data System (ADS)

    Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

    2017-03-01

    Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

  13. Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

    2017-09-01

    Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

  14. Hybrid EEG-EOG brain-computer interface system for practical machine control.

    PubMed

    Punsawad, Yunyong; Wongsawat, Yodchanan; Parnichkun, Manukid

    2010-01-01

    Practical issues such as accuracy with various subjects, number of sensors, and time for training are important problems of existing brain-computer interface (BCI) systems. In this paper, we propose a hybrid framework for the BCI system that can make machine control more practical. The electrooculogram (EOG) is employed to control the machine in the left and right directions while the electroencephalogram (EEG) is employed to control the forword, no action, and complete stop motions of the machine. By using only 2-channel biosignals, the average classification accuracy of more than 95% can be achieved.

  15. A hybrid land use regression/AERMOD model for predicting intra-urban variation in PM2.5

    NASA Astrophysics Data System (ADS)

    Michanowicz, Drew R.; Shmool, Jessie L. C.; Tunno, Brett J.; Tripathy, Sheila; Gillooly, Sara; Kinnee, Ellen; Clougherty, Jane E.

    2016-04-01

    Characterizing near-source spatio-temporal variation is a long -standing challenge in air pollution epidemiology, and common intra-urban modeling approaches [e.g., land use regression (LUR)], do not account for short-term meteorological variation. Atmospheric dispersion modeling approaches, such as AERMOD, can account for near-source pollutant behavior by capturing source-meteorological interactions, but requires external validation and resolved background concentrations. In this study, we integrate AERMOD-based predictions for source-specific fine particle (PM2.5) concentrations into LUR models derived from total ambient PM2.5 measured at 36 unique sites selected to represent different source and elevation profiles, during summer and winter, 2012-2013 in Pittsburgh, Pennsylvania (PA). We modeled PM2.5 emissions from 207 local stationary sources in AERMOD, utilizing the monitoring locations as receptors, and hourly meteorological information matching each sampling period. Finally, we compare results of the integrated LUR/AERMOD hybrid model to those of the AERMOD + background and standard LUR models, at the full domain scale and within a 5 km2 sub-domain surrounding a large industrial facility. The hybrid model improved out-of-sample prediction accuracy by 2-10% over LUR alone, though performance differed by season, in part due to within-season temporal variability. We found differences up to 10 μg/m3 in predicted concentrations, and observed the largest differences within the industrial sub-domain. LUR underestimated concentrations from 500 to 2500 m downwind of major sources. The hybrid modeling approach we developed may help to improve intra-urban exposure estimates, particularly in regions of large industrial sources, sharp elevation gradients, or complex meteorology (e.g., frequent inversion events), such as Pittsburgh, PA. More broadly, the approach may inform the development of spatio-temporal modeling frameworks for air pollution exposure assessment for

  16. Marketing image categorization using hybrid human-machine combinations

    NASA Astrophysics Data System (ADS)

    Gnanasambandam, Nathan; Madhu, Himanshu

    2012-03-01

    Marketing instruments with nested, short-form, symbol loaded content need to be studied differently. Image classification in the Web2.0 world can dynamically use a configurable amount of internal and external data as well as varying levels of crowd-sourcing. Our work is one such examination of how to construct a hybrid technique involving learning and crowd-sourcing. Through a parameter called turkmix and a multitude of crowd-sourcing techniques available we show that we can control the trend of metrics such as precision and recall on the hybrid categorizer.

  17. Simplified Hybrid-Secondary Uncluttered Machine And Method

    DOEpatents

    Hsu, John S [Oak Ridge, TN

    2005-05-10

    An electric machine (40, 40') has a stator (43) and a rotor (46) and a primary air gap (48) has secondary coils (47c, 47d) separated from the rotor (46) by a secondary air gap (49) so as to induce a slip current in the secondary coils (47c, 47d). The rotor (46, 76) has magnetic brushes (A, B, C, D) or wires (80) which couple flux in through the rotor (46) to the secondary coils (47c, 47d) without inducing a current in the rotor (46) and without coupling a stator rotational energy component to the secondary coils (47c, 47d). The machine can be operated as a motor or a generator in multi-phase or single-phase embodiments. A method of providing a slip energy controller is also disclosed.

  18. Design of drying chamber and biomass furnace for sun-biomass hybrid rice-drying machine

    NASA Astrophysics Data System (ADS)

    Satria, Dhimas; Haryadi, Austin, Ruben; Kurniawan, Bobby

    2016-03-01

    In most Asian countries, rice drying is carried out manually by exposing rice to sunlight. However, problem occurs when rain season comes. Lack of sunlight deters the drying process. This paper proposes a design of mechanical rice drying machine with hybrid sun-biomass energy source. Pahl & Beitz method, which consists of four steps process: function planning and clarification, design concept, design prototype, and design details; are used as design methodology. Based on design result and calculation, in this paper propose specifications for drying machine and biomass furnace. Drying chamber is a continuous flow system with pneumatic-conveyor as blower. This hybrid utilizes two types of energy sources, sun and biomass. The proposed machine has capacity of 500 kilograms per cycle using 455 Watt of energy, which is more efficient than ordinary heater. Biomass furnace utilizes heat transfer by means of arranging 64 pieces of stainless steel pipes of 0.65 diameters in parallel.

  19. Characteristic analysis of a less-rare-earth hybrid PM-assisted synchronous reluctance motor for EVs application

    NASA Astrophysics Data System (ADS)

    Wu, Wenye; Zhu, Xiaoyong; Quan, Li; Fan, Deyang; Xiang, Zixuan

    2017-05-01

    Low-energy permanent magnet (PM) such as ferrite is usually adopted in a PM-assisted reluctance (PMAREL) motor to enhance the output torque and reduce costs. However, the relatively low magnetic energy product and remanence in such PMs may lead to the risk of demagnetization. By using two types of materials of rare-earth NdFeB and non-rare-earth ferrite PM, a new less-rare-earth hybrid PMAREL motor is proposed in this paper, where the output torque and the power factor can be improved obviously, and meanwhile the risk of irreversible demagnetization in ferrite PMs can be reduced significantly due to the existence of NdFeB PMs. To verify the validity of the proposed motor, the operating principles of the motor and the positive interaction influences between the two involved types of PMs are analyzed. Moreover, by using the finite element method, the torque characteristics and anti-demagnetization capabilities are also investigated in details. Both the theoretical analysis and simulated results confirm the advantages of the proposed motor.

  20. A Hybrid Electromagnetism-Like Algorithm for Single Machine Scheduling Problem

    NASA Astrophysics Data System (ADS)

    Chen, Shih-Hsin; Chang, Pei-Chann; Chan, Chien-Lung; Mani, V.

    Electromagnetism-like algorithm (EM) is a population-based meta-heuristic which has been proposed to solve continuous problems effectively. In this paper, we present a new meta-heuristic that uses the EM methodology to solve the single machine scheduling problem. Single machine scheduling is a combinatorial optimization problem. Schedule representation for our problem is based on random keys. Because there is little research in solving the combinatorial optimization problem (COP) by EM, the paper attempts to employ the random-key concept enabling EM to solve COP in single machine scheduling problem. We present a hybrid algorithm that combines the EM methodology and genetic operators to obtain the best/optimal schedule for this single machine scheduling problem, which attempts to achieve convergence and diversity effect when they iteratively solve the problem. The objective in our problem is minimization of the sum of earliness and tardiness. This hybrid algorithm was tested on a set of standard test problems available in the literature. The computational results show that this hybrid algorithm performs better than the standard genetic algorithm.

  1. A hybrid analytical model for open-circuit field calculation of multilayer interior permanent magnet machines

    NASA Astrophysics Data System (ADS)

    Zhang, Zhen; Xia, Changliang; Yan, Yan; Geng, Qiang; Shi, Tingna

    2017-08-01

    Due to the complicated rotor structure and nonlinear saturation of rotor bridges, it is difficult to build a fast and accurate analytical field calculation model for multilayer interior permanent magnet (IPM) machines. In this paper, a hybrid analytical model suitable for the open-circuit field calculation of multilayer IPM machines is proposed by coupling the magnetic equivalent circuit (MEC) method and the subdomain technique. In the proposed analytical model, the rotor magnetic field is calculated by the MEC method based on the Kirchhoff's law, while the field in the stator slot, slot opening and air-gap is calculated by subdomain technique based on the Maxwell's equation. To solve the whole field distribution of the multilayer IPM machines, the coupled boundary conditions on the rotor surface are deduced for the coupling of the rotor MEC and the analytical field distribution of the stator slot, slot opening and air-gap. The hybrid analytical model can be used to calculate the open-circuit air-gap field distribution, back electromotive force (EMF) and cogging torque of multilayer IPM machines. Compared with finite element analysis (FEA), it has the advantages of faster modeling, less computation source occupying and shorter time consuming, and meanwhile achieves the approximate accuracy. The analytical model is helpful and applicable for the open-circuit field calculation of multilayer IPM machines with any size and pole/slot number combination.

  2. Microstructure of Laser-MAG Hybrid Welds of Sintered P/M Steel

    NASA Astrophysics Data System (ADS)

    Liu, Shuangyu; Zhang, Hong; Hu, Jiandong; Shi, Yan

    2013-01-01

    The microstructure and mechanical properties of iron-based powder metallurgical steels jointed by CO2 laser-metal active gas (MAG) hybrid welding were investigated. The cross-sectional morphology of hybrid weld bead consisted of arc zone and laser zone. The microstructure of arc zone consisted of columnar dendrite and fine acicular dendrite between the columnar dendrites, but that of laser zone was composed of fine equiaxed dendrite. The MAG weld had obvious heat-affected zone (HAZ) zone, while hybrid weld had very narrow HAZ zone because of the rapid cooling rate. The phase constitutions of the joint determined by x-ray diffraction were α-Fe (ferrite) and Cu. The 2θ value of α-Fe (200) peaks of hybrid weld was smaller than that of sintering compact. Compared to MAG weld, hybrid weld had finer grain size, higher micro-hardness, and higher micro-strain, which was caused by the difference of cooling rate and crystallizing.

  3. Drilling of Hybrid Titanium Composite Laminate (HTCL) with Electrical Discharge Machining.

    PubMed

    Ramulu, M; Spaulding, Mathew

    2016-09-01

    An experimental investigation was conducted to determine the application of die sinker electrical discharge machining (EDM) as it applies to a hybrid titanium thermoplastic composite laminate material. Holes were drilled using a die sinker EDM. The effects of peak current, pulse time, and percent on-time on machinability of hybrid titanium composite material were evaluated in terms of material removal rate (MRR), tool wear rate, and cut quality. Experimental models relating each process response to the input parameters were developed and optimum operating conditions with a short cutting time, achieving the highest workpiece MRR, with very little tool wear were determined to occur at a peak current value of 8.60 A, a percent on-time of 36.12%, and a pulse time of 258 microseconds. After observing data acquired from experimentation, it was determined that while use of EDM is possible, for desirable quality it is not fast enough for industrial application.

  4. FINAL REPORT ON CONTROL ALGORITHM TO IMPROVE THE PARTIAL-LOAD EFFICIENCY OFSURFACE PM MACHINES WITH FRACTIONAL-SLOT CONCENTRATED WINDINGS

    SciTech Connect

    Reddy, P.B.; Jahns, T.M.

    2007-04-30

    Surface permanent magnet (SPM) synchronous machines using fractional-slot concentrated windings are being investigated as candidates for high-performance traction machines for automotive electric propulsion systems. It has been shown analytically and experimentally that such designs can achieve very wide constant-power speed ratios (CPSR) [1,2]. This work has shown that machines of this type are capable of achieving very low cogging torque amplitudes as well as significantly increasing the machine power density [3-5] compared to SPM machines using conventional distributed windings. High efficiency can be achieved in this class of SPM machine by making special efforts to suppress the eddy-current losses in the magnets [6-8], accompanied by efforts to minimize the iron losses in the rotor and stator cores. Considerable attention has traditionally been devoted to maximizing the full-load efficiency of traction machines at their rated operating points and along their maximum-power vs. speed envelopes for higher speeds [9,10]. For example, on-line control approaches have been presented for maximizing the full-load efficiency of PM synchronous machines, including the use of negative d-axis stator current to reduce the core losses [11,12]. However, another important performance specification for electric traction applications is the machine's efficiency at partial loads. Partial-load efficiency is particularly important if the target traction application requires long periods of cruising operation at light loads that are significantly lower than the maximum drive capabilities. While the design of the machine itself is clearly important, investigation has shown that this is a case where the choice of the control algorithm plays a critical role in determining the maximum partial-load efficiency that the machine actually achieves in the traction drive system. There is no evidence that this important topic has been addressed for this type of SPM machine by any other authors

  5. Final Report on Control Algorithm to Improve the Partial-Load Efficiency of Surface PM Machines with Fractional-Slot Concentrated Windings

    SciTech Connect

    McKeever, John W; Reddy, Patel; Jahns, Thomas M

    2007-05-01

    Surface permanent magnet (SPM) synchronous machines using fractional-slot concentrated windings are being investigated as candidates for high-performance traction machines for automotive electric propulsion systems. It has been shown analytically and experimentally that such designs can achieve very wide constant-power speed ratios (CPSR) [1,2]. This work has shown that machines of this type are capable of achieving very low cogging torque amplitudes as well as significantly increasing the machine power density [3-5] compared to SPM machines using conventional distributed windings. High efficiency can be achieved in this class of SPM machine by making special efforts to suppress the eddy-current losses in the magnets [6-8], accompanied by efforts to minimize the iron losses in the rotor and stator cores. Considerable attention has traditionally been devoted to maximizing the full-load efficiency of traction machines at their rated operating points and along their maximum-power vs. speed envelopes for higher speeds [9,10]. For example, on-line control approaches have been presented for maximizing the full-load efficiency of PM synchronous machines, including the use of negative d-axis stator current to reduce the core losses [11,12]. However, another important performance specification for electric traction applications is the machine's efficiency at partial loads. Partial-load efficiency is particularly important if the target traction application requires long periods of cruising operation at light loads that are significantly lower than the maximum drive capabilities. While the design of the machine itself is clearly important, investigation has shown that this is a case where the choice of the control algorithm plays a critical role in determining the maximum partial-load efficiency that the machine actually achieves in the traction drive system. There is no evidence that this important topic has been addressed for this type of SPM machine by any other authors

  6. Position error compensation via a variable reluctance sensor applied to a Hybrid Vehicle Electric machine.

    PubMed

    Bucak, Ihsan Ömür

    2010-01-01

    In the automotive industry, electromagnetic variable reluctance (VR) sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV) system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion.

  7. Position Error Compensation via a Variable Reluctance Sensor Applied to a Hybrid Vehicle Electric Machine

    PubMed Central

    Bucak, İhsan Ömür

    2010-01-01

    In the automotive industry, electromagnetic variable reluctance (VR) sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV) system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion. PMID:22294906

  8. A new damage diagnosis approach for NC machine tools based on hybrid Stationary subspace analysis

    NASA Astrophysics Data System (ADS)

    Gao, Chen; Zhou, Yuqing; Ren, Yan

    2017-05-01

    This paper focused on the damage diagnosis for NC machine tools and put forward a damage diagnosis method based on hybrid Stationary subspace analysis (SSA), for improving the accuracy and visibility of damage identification. First, the observed single sensor signal was reconstructed to multi-dimensional signals by the phase space reconstruction technique, as the inputs of SSA. SSA method was introduced to separate the reconstructed data into stationary components and non-stationary components without the need for independency and prior information of the origin signals. Subsequently, the selected non-stationary components were analysed for training LS-SVM (Least Squares Support Vector Machine) classifier model, in which several statistic parameters in the time and frequency domains were exacted as the sample of LS-SVM. An empirical analysis in NC milling machine tools is developed, and the result shows high accuracy of the proposed approach.

  9. 112 Gb/s PM-QPSK transmission up to 6000 km with 200 km amplifier spacing and a hybrid fiber span configuration.

    PubMed

    Downie, John D; Hurley, Jason; Cartledge, John; Bickham, Scott; Mishra, Snigdharaj

    2011-12-12

    We demonstrate transmission of 112 Gb/s PM-QPSK signals over a system with 200 km span lengths. Amplification is provided by hybrid backward-pumped Raman/EDFA amplifiers and reach lengths up to 6000 km for an 8 channel system and 5400 km for a 32 channel system are shown. As a means of maximizing OSNR, a simple hybrid fiber span configuration is used that combines two ultra-low loss fibers, one having very large effective area.

  10. Modified vector control algorithm for increasing partial-load efficiency of fractional-slot concentrated-winding surface PM machines

    SciTech Connect

    El-Refaie, Ayman M; Jahns, Thomas M; Reddy, Patel; McKeever, John W

    2008-01-01

    This paper presents a modified vector control algorithm for a fractional-slot concentrated-winding surface permanent magnet (SPM) machine that has been developed to maximize the machine's partial-load efficiency over a wide range of operating conditions. By increasing the amplitude of the negative d-axis current, the resulting increase in the stator copper losses can be more than offset by the reduction in the iron core losses achieved by lowering the stator d-axis flux amplitude. The effectiveness of this technique has been demonstrated using both analytical models and finite element analysis for a 55-kW (peak) SPM machine design developed for a demanding set of traction drive performance requirements. For this example, the modified control strategy increases the partial-load efficiency at 20% of rated torque by > 6% at 2000 r/min compared to the maximum torque/ampere algorithm, making the machine much more attractive for its intended application.

  11. MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

    PubMed Central

    Ozmutlu, H. Cenk

    2014-01-01

    We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

  12. MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

    PubMed

    Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

    2014-01-01

    We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

  13. Complex hybrid models combining deterministic and machine learning components for numerical climate modeling and weather prediction.

    PubMed

    Krasnopolsky, Vladimir M; Fox-Rabinovitz, Michael S

    2006-03-01

    A new practical application of neural network (NN) techniques to environmental numerical modeling has been developed. Namely, a new type of numerical model, a complex hybrid environmental model based on a synergetic combination of deterministic and machine learning model components, has been introduced. Conceptual and practical possibilities of developing hybrid models are discussed in this paper for applications to climate modeling and weather prediction. The approach presented here uses NN as a statistical or machine learning technique to develop highly accurate and fast emulations for time consuming model physics components (model physics parameterizations). The NN emulations of the most time consuming model physics components, short and long wave radiation parameterizations or full model radiation, presented in this paper are combined with the remaining deterministic components (like model dynamics) of the original complex environmental model--a general circulation model or global climate model (GCM)--to constitute a hybrid GCM (HGCM). The parallel GCM and HGCM simulations produce very similar results but HGCM is significantly faster. The speed-up of model calculations opens the opportunity for model improvement. Examples of developed HGCMs illustrate the feasibility and efficiency of the new approach for modeling complex multidimensional interdisciplinary systems.

  14. A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system

    NASA Astrophysics Data System (ADS)

    Kumar, Vijay M.; Murthy, ANN; Chandrashekara, K.

    2012-05-01

    The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.

  15. A hybrid genetic algorithm-extreme learning machine approach for accurate significant wave height reconstruction

    NASA Astrophysics Data System (ADS)

    Alexandre, E.; Cuadra, L.; Nieto-Borge, J. C.; Candil-García, G.; del Pino, M.; Salcedo-Sanz, S.

    2015-08-01

    Wave parameters computed from time series measured by buoys (significant wave height Hs, mean wave period, etc.) play a key role in coastal engineering and in the design and operation of wave energy converters. Storms or navigation accidents can make measuring buoys break down, leading to missing data gaps. In this paper we tackle the problem of locally reconstructing Hs at out-of-operation buoys by using wave parameters from nearby buoys, based on the spatial correlation among values at neighboring buoy locations. The novelty of our approach for its potential application to problems in coastal engineering is twofold. On one hand, we propose a genetic algorithm hybridized with an extreme learning machine that selects, among the available wave parameters from the nearby buoys, a subset FnSP with nSP parameters that minimizes the Hs reconstruction error. On the other hand, we evaluate to what extent the selected parameters in subset FnSP are good enough in assisting other machine learning (ML) regressors (extreme learning machines, support vector machines and gaussian process regression) to reconstruct Hs. The results show that all the ML method explored achieve a good Hs reconstruction in the two different locations studied (Caribbean Sea and West Atlantic).

  16. Prediction of core cancer genes using a hybrid of feature selection and machine learning methods.

    PubMed

    Liu, Y X; Zhang, N N; He, Y; Lun, L J

    2015-08-03

    Machine learning techniques are of great importance in the analysis of microarray expression data, and provide a systematic and promising way to predict core cancer genes. In this study, a hybrid strategy was introduced based on machine learning techniques to select a small set of informative genes, which will lead to improving classification accuracy. First feature filtering algorithms were applied to select a set of top-ranked genes, and then hierarchical clustering and collapsing dense clusters were used to select core cancer genes. Through empirical study, our approach is capable of selecting relatively few core cancer genes while making high-accuracy predictions. The biological significance of these genes was evaluated using systems biology analysis. Extensive functional pathway and network analyses have confirmed findings in previous studies and can bring new insights into common cancer mechanisms.

  17. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    PubMed

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  18. Accurate modeling of switched reluctance machine based on hybrid trained WNN

    NASA Astrophysics Data System (ADS)

    Song, Shoujun; Ge, Lefei; Ma, Shaojie; Zhang, Man

    2014-04-01

    According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.

  19. River Flow Forecasting: a Hybrid Model of Self Organizing Maps and Least Square Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Ismail, S.; Samsudin, R.; Shabri, A.

    2010-10-01

    Successful river flow time series forecasting is a major goal and an essential procedure that is necessary in water resources planning and management. This study introduced a new hybrid model based on a combination of two familiar non-linear method of mathematical modeling: Self Organizing Map (SOM) and Least Square Support Vector Machine (LSSVM) model referred as SOM-LSSVM model. The hybrid model uses the SOM algorithm to cluster the training data into several disjointed clusters and the individual LSSVM is used to forecast the river flow. The feasibility of this proposed model is evaluated to actual river flow data from Bernam River located in Selangor, Malaysia. Their results have been compared to those obtained using LSSVM and artificial neural networks (ANN) models. The experiment results show that the SOM-LSSVM model outperforms other models for forecasting river flow. It also indicates that the proposed model can forecast more precisely and provides a promising alternative technique in river flow forecasting.

  20. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    NASA Astrophysics Data System (ADS)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  1. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    PubMed Central

    Banik, Shipra; Khodadad Khan, A. F. M.; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange. PMID:24701205

  2. Accurate modeling of switched reluctance machine based on hybrid trained WNN

    SciTech Connect

    Song, Shoujun Ge, Lefei; Ma, Shaojie; Zhang, Man

    2014-04-15

    According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.

  3. Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

    PubMed Central

    Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

    2013-01-01

    Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

  4. A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

    NASA Astrophysics Data System (ADS)

    Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

    2016-06-01

    To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

  5. Performance Characteristics of Hybrid Cycle Combined Absorption Heat Transformer and Absorption Refrigerating Machine

    NASA Astrophysics Data System (ADS)

    Iyoki, Shigeki; Otsuka, Shin-Ichi; Uemura, Tadashi

    In this paper, four kinds of hybrid cycles which combined the single-stage absorption refrigerating machine and four kinds of absorption heat transformers were proposed. It is possible that each of these hybrid cycles gets high temperature and low temperature from one cycle, simultaneously. As basic cycle of absorption heat transformer, the following were chosen: two kinds of single-stage absorption heat transformer and two kinds of two-stage absorption heat transformer. As a working medium-absorbent system, H2O-LiBr system, H2O-LiBr-LiNO3 system, H2O-LiBr-LiNO3-LiCl system, H2O-LiBr-C2H6O2 system and H2O-LiNO3-LiCl system were adopted. Using these five kinds of working medium-absorbent system, the performance characteristics of four kinds of hybrid cycle were simulated. And the performance characteristics of these cycles were compared.

  6. Integrated Inverter For Driving Multiple Electric Machines

    DOEpatents

    Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN

    2006-04-04

    An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.

  7. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    PubMed

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  8. Discrimination of Maize Haploid Seeds from Hybrid Seeds Using Vis Spectroscopy and Support Vector Machine Method.

    PubMed

    Liu, Jin; Guo, Ting-ting; Li, Hao-chuan; Jia, Shi-qiang; Yan, Yan-lu; An, Dong; Zhang, Yao; Chen, Shao-jiang

    2015-11-01

    Doubled haploid (DH) lines are routinely applied in the hybrid maize breeding programs of many institutes and companies for their advantages of complete homozygosity and short breeding cycle length. A key issue in this approach is an efficient screening system to identify haploid kernels from the hybrid kernels crossed with the inducer. At present, haploid kernel selection is carried out manually using the"red-crown" kernel trait (the haploid kernel has a non-pigmented embryo and pigmented endosperm) controlled by the R1-nj gene. Manual selection is time-consuming and unreliable. Furthermore, the color of the kernel embryo is concealed by the pericarp. Here, we establish a novel approach for identifying maize haploid kernels based on visible (Vis) spectroscopy and support vector machine (SVM) pattern recognition technology. The diffuse transmittance spectra of individual kernels (141 haploid kernels and 141 hybrid kernels from 9 genotypes) were collected using a portable UV-Vis spectrometer and integrating sphere. The raw spectral data were preprocessed using smoothing and vector normalization methods. The desired feature wavelengths were selected based on the results of the Kolmogorov-Smirnov test. The wavelengths with p values above 0. 05 were eliminated because the distributions of absorbance data in these wavelengths show no significant difference between haploid and hybrid kernels. Principal component analysis was then performed to reduce the number of variables. The SVM model was evaluated by 9-fold cross-validation. In each round, samples of one genotype were used as the testing set, while those of other genotypes were used as the training set. The mean rate of correct discrimination was 92.06%. This result demonstrates the feasibility of using Vis spectroscopy to identify haploid maize kernels. The method would help develop a rapid and accurate automated screening-system for haploid kernels.

  9. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    SciTech Connect

    Morton, April M; Nagle, Nicholas N; Piburn, Jesse O; Stewart, Robert N; McManamay, Ryan A

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  10. Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

    PubMed Central

    Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

    2014-01-01

    This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

  11. Hybrid independent component analysis and twin support vector machine learning scheme for subtle gesture recognition.

    PubMed

    Naik, Ganesh R; Kumar, Dinesh K; Jayadeva

    2010-10-01

    Myoelectric signal classification is one of the most difficult pattern recognition problems because large variations in surface electromyogram features usually exist. In the literature, attempts have been made to apply various pattern recognition methods to classify surface electromyography into components corresponding to the activities of different muscles, but this has not been very successful, as some muscles are bigger and more active than others. This results in dataset discrepancy during classification. Multicategory classification problems are usually solved by solving many, one-versus-rest binary classification tasks. These subtasks unsurprisingly involve unbalanced datasets. Consequently, we need a learning methodology that can take into account unbalanced datasets in addition to large variations in the distributions of patterns corresponding to different classes. Here, we attempt to address the above issues using hybrid features extracted from independent component analysis and twin support vector machine techniques.

  12. Hybrid metaheuristics for solving a fuzzy single batch-processing machine scheduling problem.

    PubMed

    Molla-Alizadeh-Zavardehi, S; Tavakkoli-Moghaddam, R; Lotfi, F Hosseinzadeh

    2014-01-01

    This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.

  13. Association pattern mining of intron retention events in human based on hybrid learning machine.

    PubMed

    Hu, Hae-Jin; Goh, Sung-Ho; Lee, Yeon-Su

    2010-01-01

    Alternative splicing is a main component of protein diversity, and aberrant splicing is known to be one of the main causes of genetic disorders such as cancer. Many statistical and computational approaches have identified several major factors that determine the splicing event, such as exon/intron length, splice site strength, and density of splicing enhancers or silencers. These factors may be correlated with one another and thus result in a specific type of splicing, but there has not been a systematic approach to extracting comprehensible association patterns. Here, we attempted to understand the decision making process of the learning machine on intron retention event. We adopted a hybrid learning machine approach using a random forest and association rule mining algorithm to determine the governing factors of intron retention events and their combined effect on decision-making processes. By quantifying all candidate features into five category values, we enhanced the understandability of generated rules. The interesting features found by the random forest algorithm are that only the adenine- and thymine-based triplets such as ATA, TTA, and ATT, but not the known intronic splicing enhancer GGG triplet is shown the significant features. The rules generated by the association rule mining algorithm also show that constitutive introns are generally characterized by high adenine- and thymine-based triplet frequency (level 3 and above), 3' and 5' splice site scores, exonic splicing silencer scores, and intron length, whereas retained introns are characterized by low-level counterpart scores.

  14. A hybrid flowshop scheduling model considering dedicated machines and lot-splitting for the solar cell industry

    NASA Astrophysics Data System (ADS)

    Wang, Li-Chih; Chen, Yin-Yann; Chen, Tzu-Li; Cheng, Chen-Yang; Chang, Chin-Wei

    2014-10-01

    This paper studies a solar cell industry scheduling problem, which is similar to traditional hybrid flowshop scheduling (HFS). In a typical HFS problem, the allocation of machine resources for each order should be scheduled in advance. However, the challenge in solar cell manufacturing is the number of machines that can be adjusted dynamically to complete the job. An optimal production scheduling model is developed to explore these issues, considering the practical characteristics, such as hybrid flowshop, parallel machine system, dedicated machines, sequence independent job setup times and sequence dependent job setup times. The objective of this model is to minimise the makespan and to decide the processing sequence of the orders/lots in each stage, lot-splitting decisions for the orders and the number of machines used to satisfy the demands in each stage. From the experimental results, lot-splitting has significant effect on shortening the makespan, and the improvement effect is influenced by the processing time and the setup time of orders. Therefore, the threshold point to improve the makespan can be identified. In addition, the model also indicates that more lot-splitting approaches, that is, the flexibility of allocating orders/lots to machines is larger, will result in a better scheduling performance.

  15. Analysis and forecasting of the particulate matter (PM) concentration levels over four major cities of China using hybrid models

    NASA Astrophysics Data System (ADS)

    Qin, Shanshan; Liu, Feng; Wang, Jianzhou; Sun, Beibei

    2014-12-01

    The analysis and forecasting of PM concentrations play a significant role in regulatory planning on the reduction and control of PM emission and precautionary strategies. However, accurate PM forecasting, which is needed to establish an early warning system, is still a huge challenge and a critical issue. Determining how to address the accurate forecasting problem becomes an even more significant and urgent task. Based on gray correlation analysis (GCA), Ensemble Empirical Mode Decomposition (EEMD), Cuckoo search (CS) and Back-propagation artificial neutral networks (BPANN), this paper proposes the CS-EEMD-BPANN model for forecasting PM concentrations. Prior to establishing this model, gray correlation has been uniquely used to search for possible predictors of PM among other air pollutants (CO, NO2, O3 and SO2) and meteorological environments (wind speed, wind direction, temperature, humidity and pressure). The proposed method was investigated in four major cities of China (Beijing, Shanghai, Guangzhou and Lanzhou) with different characteristics of climatic, terrain and emission sources. The results of the gray correlation analysis indicate that CO, NO2 and SO2 are more related to PM and that the incorporation of these predictors can significantly improve the model performance predictability, suggesting the effectiveness of our developed method.

  16. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

    PubMed Central

    Murat, Miraemiliana; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson’s coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and

  17. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation.

    PubMed

    Clark, Alex M; Bunin, Barry A; Litterman, Nadia K; Schürer, Stephan C; Visser, Ubbo

    2014-01-01

    Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers.

  18. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation

    PubMed Central

    Bunin, Barry A.; Litterman, Nadia K.; Schürer, Stephan C.; Visser, Ubbo

    2014-01-01

    Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers. PMID:25165633

  19. An effective shuffled frog-leaping algorithm for solving the hybrid flow-shop scheduling problem with identical parallel machines

    NASA Astrophysics Data System (ADS)

    Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min

    2013-12-01

    In this article, an effective shuffled frog-leaping algorithm (SFLA) is proposed to solve the hybrid flow-shop scheduling problem with identical parallel machines (HFSP-IPM). First, some novel heuristic decoding rules for both job order decision and machine assignment are proposed. Then, three hybrid decoding schemes are designed to decode job order sequences to schedules. A special bi-level crossover and multiple local search operators are incorporated in the searching framework of the SFLA to enrich the memetic searching behaviour and to balance the exploration and exploitation capabilities. Meanwhile, some theoretical analysis for the local search operators is provided for guiding the local search. The parameter setting of the algorithm is also investigated based on the Taguchi method of design of experiments. Finally, numerical testing based on well-known benchmarks and comparisons with some existing algorithms are carried out to demonstrate the effectiveness of the proposed algorithm.

  20. Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

    PubMed

    Komasi, Mehdi; Sharghi, Soroush

    2016-01-01

    Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.

  1. Hybrid soft-lithography/laser machined microchips for the parallel generation of droplets.

    PubMed

    Muluneh, M; Issadore, D

    2013-12-21

    Microfluidic chips have been developed to generate droplets and microparticles with control over size, shape, and composition not possible using conventional methods. However, it has remained a challenge to scale-up production for practical applications due to the inherently limited throughput of micro-scale devices. To address this problem, we have developed a self-contained microchip that integrates many (N = 512) micro-scale droplet makers. This 3 × 3 cm(2) PDMS microchip consists of a two-dimensional array of 32 × 16 flow-focusing droplet makers, a network of flow channels that connect them, and only two inputs and one output. The key innovation of this technology is the hybrid use of both soft-lithography and direct laser-micromachining. The microscale resolution of soft lithography is used to fabricate flow-focusing droplet makers that can produce small and precisely defined droplets. Deeply engraved (h ≈ 500 μm) laser-machined channels are utilized to supply each of the droplet makers with its oil phase, aqueous phase, and access to an output channel. The engraved channels' low hydrodynamic resistance ensures that each droplet maker is driven with the same flow rates for highly uniform droplet formation. To demonstrate the utility of this approach, water droplets (d ≈ 80 μm) were generated in hexadecane on both 8 × 1 and 32 × 16 geometries.

  2. Fuzzy texture model and support vector machine hybridization for land cover classification of remotely sensed images

    NASA Astrophysics Data System (ADS)

    Jenicka, S.; Suruliandi, A.

    2014-01-01

    Accuracy of land cover classification in remotely sensed images relies on the utilized classifier and extracted features. Texture features are significant in land cover classification. Traditional texture models capture only patterns with discrete boundaries, whereas fuzzy patterns should be classified by assigning due weightage to uncertainty. When a remotely sensed image contains noise, the image may have fuzzy patterns characterizing land covers and fuzzy boundaries separating them. Therefore, a fuzzy texture model is proposed for the effective classification of land covers in remotely sensed images. The model uses a Sugeno fuzzy inference system. A support vector machine (SVM) is used for the precise, fast classification of image pixels. The model is a hybrid of a fuzzy texture model and an SVM for the land cover classification of remotely sensed images. To support this proposal, experiments were conducted in three steps. In the first two steps, the proposed texture model was validated for supervised classifications and segmentation of a standard benchmark database. In the third step, the land cover classification of a remotely sensed image of LISS-IV (an Indian remote sensing satellite) is performed using a multivariate version of the proposed model. The classified image has 95.54% classification accuracy.

  3. Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification

    PubMed Central

    Rajesh Sharma, R.; Marikkannu, P.

    2015-01-01

    A novel hybrid approach for the identification of brain regions using magnetic resonance images accountable for brain tumor is presented in this paper. Classification of medical images is substantial in both clinical and research areas. Magnetic resonance imaging (MRI) modality outperforms towards diagnosing brain abnormalities like brain tumor, multiple sclerosis, hemorrhage, and many more. The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. The design approach was initially preprocessed using 3D Gaussian filter. Based on VOI (volume of interest) of the image, features were extracted using 3D volumetric Square Centroid Lines Gray Level Distribution Method (SCLGM) along with 3D run length and cooccurrence matrix. The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002). The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods. PMID:26509188

  4. Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines

    PubMed Central

    Teodoro, George; Pan, Tony; Kurc, Tahsin; Kong, Jun; Cooper, Lee; Saltz, Joel

    2013-01-01

    We address the problem of efficient execution of a computation pattern, referred to here as the irregular wavefront propagation pattern (IWPP), on hybrid systems with multiple CPUs and GPUs. The IWPP is common in several image processing operations. In the IWPP, data elements in the wavefront propagate waves to their neighboring elements on a grid if a propagation condition is satisfied. Elements receiving the propagated waves become part of the wavefront. This pattern results in irregular data accesses and computations. We develop and evaluate strategies for efficient computation and propagation of wavefronts using a multi-level queue structure. This queue structure improves the utilization of fast memories in a GPU and reduces synchronization overheads. We also develop a tile-based parallelization strategy to support execution on multiple CPUs and GPUs. We evaluate our approaches on a state-of-the-art GPU accelerated machine (equipped with 3 GPUs and 2 multicore CPUs) using the IWPP implementations of two widely used image processing operations: morphological reconstruction and euclidean distance transform. Our results show significant performance improvements on GPUs. The use of multiple CPUs and GPUs cooperatively attains speedups of 50× and 85× with respect to single core CPU executions for morphological reconstruction and euclidean distance transform, respectively. PMID:23908562

  5. Source Identification of PM2.5 in Steubenville, Ohio Using a Hybrid Method for Highly Time-resolved Data

    EPA Science Inventory

    A new source-type identification method, Reduction and Species Clustering Using Episodes (ReSCUE), was developed to exploit the temporal synchronicity between species to form clusters of species that vary together. High time-resolution (30 min) PM2.5 sampling was condu...

  6. Source Identification of PM2.5 in Steubenville, Ohio Using a Hybrid Method for Highly Time-resolved Data

    EPA Science Inventory

    A new source-type identification method, Reduction and Species Clustering Using Episodes (ReSCUE), was developed to exploit the temporal synchronicity between species to form clusters of species that vary together. High time-resolution (30 min) PM2.5 sampling was condu...

  7. Parallel machine scheduling with step-deteriorating jobs and setup times by a hybrid discrete cuckoo search algorithm

    NASA Astrophysics Data System (ADS)

    Guo, Peng; Cheng, Wenming; Wang, Yi

    2015-11-01

    This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical parallel machines. In this problem, the processing time of each job is a step function dependent upon its starting time. An individual extended time is penalized when the starting time of a job is later than a specific deterioration date. The possibility of deterioration of a job makes the parallel machine scheduling problem more challenging than ordinary ones. A mixed integer programming model for the optimal solution is derived. Due to its NP-hard nature, a hybrid discrete cuckoo search algorithm is proposed to solve this problem. In order to generate a good initial swarm, a modified Biskup-Hermann-Gupta (BHG) heuristic called MBHG is incorporated into the population initialization. Several discrete operators are proposed in the random walk of Lévy flights and the crossover search. Moreover, a local search procedure based on variable neighbourhood descent is integrated into the algorithm as a hybrid strategy in order to improve the quality of elite solutions. Computational experiments are executed on two sets of randomly generated test instances. The results show that the proposed hybrid algorithm can yield better solutions in comparison with the commercial solver CPLEX® with a one hour time limit, the discrete cuckoo search algorithm and the existing variable neighbourhood search algorithm.

  8. Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

    NASA Astrophysics Data System (ADS)

    Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

    2016-12-01

    This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

  9. A hybrid fuzzy logic and extreme learning machine for improving efficiency of circulating water systems in power generation plant

    NASA Astrophysics Data System (ADS)

    Aziz, Nur Liyana Afiqah Abdul; Siah Yap, Keem; Afif Bunyamin, Muhammad

    2013-06-01

    This paper presents a new approach of the fault detection for improving efficiency of circulating water system (CWS) in a power generation plant using a hybrid Fuzzy Logic System (FLS) and Extreme Learning Machine (ELM) neural network. The FLS is a mathematical tool for calculating the uncertainties where precision and significance are applied in the real world. It is based on natural language which has the ability of "computing the word". The ELM is an extremely fast learning algorithm for neural network that can completed the training cycle in a very short time. By combining the FLS and ELM, new hybrid model, i.e., FLS-ELM is developed. The applicability of this proposed hybrid model is validated in fault detection in CWS which may help to improve overall efficiency of power generation plant, hence, consuming less natural recourses and producing less pollutions.

  10. A new encoding scheme-based hybrid algorithm for minimising two-machine flow-shop group scheduling problem

    NASA Astrophysics Data System (ADS)

    Liou, Cheng-Dar; Hsieh, Yi-Chih; Chen, Yin-Yann

    2013-01-01

    This article investigates the two-machine flow-shop group scheduling problem (GSP) with sequence-dependent setup and removal times, and job transportation times between machines. The objective is to minimise the total completion time. As known, this problem is an NP-hard problem and generalises the typical two-machine GSPs. In this article, a new encoding scheme based on permutation representation is proposed to transform a random job permutation to a feasible permutation for GSPs. The proposed encoding scheme simultaneously determines both the sequence of jobs in each group and the sequence of groups. By reasonably combining particle swarm optimisation (PSO) and genetic algorithm (GA), we develop a fast and easily implemented hybrid algorithm (HA) for solving the considered problems. The effectiveness and efficiency of the proposed HA are demonstrated and compared with those of standard PSO and GA by numerical results of various tested instances with group numbers up to 20. In addition, three different lower bounds are developed to evaluate the solution quality of the HA. Limited numerical results indicate that the proposed HA is a viable and effective approach for the studied two-machine flow-shop group scheduling problem.

  11. Hybrid polylingual object model: an efficient and seamless integration of Java and native components on the Dalvik virtual machine.

    PubMed

    Huang, Yukun; Chen, Rong; Wei, Jingbo; Pei, Xilong; Cao, Jing; Prakash Jayaraman, Prem; Ranjan, Rajiv

    2014-01-01

    JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO) model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded.

  12. Design comparison of single phase outer and inner-rotor hybrid excitation flux switching motor for hybrid electric vehicles

    NASA Astrophysics Data System (ADS)

    Mazlan, Mohamed Mubin Aizat; Sulaiman, Erwan; Husin, Zhafir Aizat; Othman, Syed Muhammad Naufal Syed; Khan, Faisal

    2015-05-01

    In hybrid excitation machines (HEMs), there are two main flux sources which are permanent magnet (PM) and field excitation coil (FEC). These HEMs have better features when compared with the interior permanent magnet synchronous machines (IPMSM) used in conventional hybrid electric vehicles (HEVs). Since all flux sources including PM, FEC and armature coils are located on the stator core, the rotor becomes a single piece structure similar with switch reluctance machine (SRM). The combined flux generated by PM and FEC established more excitation fluxes that are required to produce much higher torque of the motor. In addition, variable DC FEC can control the flux capabilities of the motor, thus the machine can be applied for high-speed motor drive system. In this paper, the comparisons of single-phase 8S-4P outer and inner rotor hybrid excitation flux switching machine (HEFSM) are presented. Initially, design procedures of the HEFSM including parts drawing, materials and conditions setting, and properties setting are explained. Flux comparisons analysis is performed to investigate the flux capabilities at various current densities. Then the flux linkages of PM with DC FEC of various DC FEC current densities are examined. Finally torque performances are analyzed at various armature and FEC current densities for both designs. As a result, the outer-rotor HEFSM has higher flux linkage of PM with DC FEC and higher average torque of approximately 10% when compared with inner-rotor HEFSM.

  13. An Hybrid Approach Based on Machining and Dynamic Tests Data for the Identification of Material Constitutive Equations

    NASA Astrophysics Data System (ADS)

    Jomaa, Walid; Songmene, Victor; Bocher, Philippe

    2016-03-01

    In recent years, there has been growing interest for the identification of material constitutive equations using machining tests (inverse method). However, the inverse method has shown some drawbacks that could affect the accuracy of the identified material constants. On one hand, this approach requires the use of analytical model to estimate the cutting temperature. Nevertheless, the used temperature models lead to large discrepancies for the calculated temperatures even for the same work material and cutting conditions. On the other hand, some computation issues were observed when all material constants were determined, in the same time, using machining tests data. Therefore, this study attempts to provide a methodology for identifying the coefficients of the Marusich's constitutive equation (MCE) which demonstrated a good capability for the simulation of the material behavior in high speed machining. The proposed approach, which is based on an analytical inverse method together with dynamic tests, was applied to aluminum alloys AA6061-T6 and AA7075-T651, and induction hardened AISI 4340 steel (60 HRC). The response surface methodology was used in this approach. Two sets of material coefficients, for each tested work material, were determined using two different temperature models (Oxley and Loewen-Shaw). The obtained constitutive equations were validated using dynamic tests and finite element simulation of high speed machining. The predictions obtained are also compared to those performed with the corresponding Johnson and Cook constitutive equations (JCE) from the literature. The sensitivity analysis revealed that the selected temperature models used in the analytical inverse method can affect significantly the identified material constants and thereafter predicted dynamic response and machining data. Moreover, the MCE obtained using the hybrid method performed better than the JCE obtained by only dynamic tests.

  14. Insect-machine hybrid system for understanding and evaluating sensory-motor control by sex pheromone in Bombyx mori.

    PubMed

    Kanzaki, Ryohei; Minegishi, Ryo; Namiki, Shigehiro; Ando, Noriyasu

    2013-11-01

    To elucidate the dynamic information processing in a brain underlying adaptive behavior, it is necessary to understand the behavior and corresponding neural activities. This requires animals which have clear relationships between behavior and corresponding neural activities. Insects are precisely such animals and one of the adaptive behaviors of insects is high-accuracy odor source orientation. The most direct way to know the relationships between neural activity and behavior is by recording neural activities in a brain from freely behaving insects. There is also a method to give stimuli mimicking the natural environment to tethered insects allowing insects to walk or fly at the same position. In addition to these methods an 'insect-machine hybrid system' is proposed, which is another experimental system meeting the conditions necessary for approaching the dynamic processing in the brain of insects for generating adaptive behavior. This insect-machine hybrid system is an experimental system which has a mobile robot as its body. The robot is controlled by the insect through its behavior or the neural activities recorded from the brain. As we can arbitrarily control the motor output of the robot, we can intervene at the relationship between the insect and the environmental conditions.

  15. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    PubMed

    Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

    2016-01-01

    Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

  16. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine

    PubMed Central

    Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

    2016-01-01

    Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust. PMID:27551829

  17. Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

    PubMed Central

    2013-01-01

    Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

  18. Hybrid evolutionary multi-objective optimization and analysis of machining operations

    NASA Astrophysics Data System (ADS)

    Deb, Kalyanmoy; Datta, Rituparna

    2012-06-01

    Evolutionary multi-objective optimization (EMO) has received significant attention in recent studies in engineering design and analysis due to its flexibility, wide-spread applicability and ability to find multiple trade-off solutions. Optimal machining parameter determination is an important matter for ensuring an efficient working of a machining process. In this article, the use of an EMO algorithm and a suitable local search procedure to optimize the machining parameters (cutting speed, feed and depth of cut) in turning operations is described. Thereafter, the efficiency of the proposed methodology is demonstrated through two case studies - one having two objectives and the other having three objectives. Then, EMO solutions are modified using a local search procedure to achieve a better convergence property. It has been demonstrated here that a proposed heuristics-based local search procedure in which the problem-specific heuristics are derived from an innovization study performed on the EMO solutions is a computationally faster approach than the original EMO procedure. The methodology adopted in this article can be used in other machining tasks or in other engineering design activities.

  19. Design of a Permanent Magnet Synchronous Machine for a Flywheel Energy Storage System within a Hybrid Electric Vehicle

    NASA Astrophysics Data System (ADS)

    Jiang, Ming

    As an energy storage device, the flywheel has significant advantages over conventional chemical batteries, including higher energy density, higher efficiency, longer life time, and less pollution to the environment. An effective flywheel system can be attributed to its good motor/generator (M/G) design. This thesis describes the research work on the design of a permanent magnet synchronous machine (PMSM) as an M/G suitable for integration in a flywheel energy storage system within a large hybrid electric vehicle (HEV). The operating requirements of the application include wide power and speed ranges combined with high total system efficiency. Along with presenting the design, essential issues related to PMSM design including cogging torque, iron losses and total harmonic distortion (THD) are investigated. An iterative approach combining lumped parameter analysis with 2D Finite Element Analysis (FEA) was used, and the final design is presented showing excellent performance.

  20. Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

    PubMed

    Salehi, Mojtaba; Bahreininejad, Ardeshir

    2011-08-01

    Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

  1. Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

    PubMed Central

    Salehi, Mojtaba

    2010-01-01

    Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously. PMID:21845020

  2. Machine Learning

    DTIC Science & Technology

    1990-04-01

    DTIC i.LE COPY RADC-TR-90-25 Final Technical Report April 1990 MACHINE LEARNING The MITRE Corporation Melissa P. Chase Cs) CTIC ’- CT E 71 IN 2 11990...S. FUNDING NUMBERS MACHINE LEARNING C - F19628-89-C-0001 PE - 62702F PR - MOlE S. AUTHO(S) TA - 79 Melissa P. Chase WUT - 80 S. PERFORMING...341.280.5500 pm I " Aw Sig rill Ia 2110-01 SECTION 1 INTRODUCTION 1.1 BACKGROUND Research in machine learning has taken two directions in the problem of

  3. Classification of urban vegetation patterns from hyperspectral imagery: hybrid algorithm based on genetic algorithm tuned fuzzy support vector machine

    NASA Astrophysics Data System (ADS)

    Zhou, Mandi; Shu, Jiong; Chen, Zhigang; Ji, Minhe

    2012-11-01

    Hyperspectral imagery has been widely used in terrain classification for its high resolution. Urban vegetation, known as an essential part of the urban ecosystem, can be difficult to discern due to high similarity of spectral signatures among some land-cover classes. In this paper, we investigate a hybrid approach of the genetic-algorithm tuned fuzzy support vector machine (GA-FSVM) technique and apply it to urban vegetation classification from aerial hyperspectral urban imagery. The approach adopts the genetic algorithm to optimize parameters of support vector machine, and employs the K-nearest neighbor algorithm to calculate the membership function for each fuzzy parameter, aiming to reduce the effects of the isolated and noisy samples. Test data come from push-broom hyperspectral imager (PHI) hyperspectral remote sensing image which partially covers a corner of the Shanghai World Exposition Park, while PHI is a hyper-spectral sensor developed by Shanghai Institute of Technical Physics. Experimental results show the GA-FSVM model generates overall accuracy of 71.2%, outperforming the maximum likelihood classifier with 49.4% accuracy and the artificial neural network method with 60.8% accuracy. It indicates GA-FSVM is a promising model for vegetation classification from hyperspectral urban data, and has good advantage in the application of classification involving abundant mixed pixels and small samples problem.

  4. A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

    PubMed Central

    Yang, Honghui; Liu, Jingyu; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

    2010-01-01

    We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI) and single nucleotide polymorphism (SNP) data. The method consists of four stages: (1) SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME). (2) Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME). (3) Components of fMRI activation obtained with independent component analysis (ICA) are used to construct a single SVM classifier (ICA-SVMC). (4) The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI). The method was evaluated by a fully validated leave-one-out method using 40 subjects (20 patients and 20 controls). The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder. PMID:21119772

  5. A hybrid model of self organizing maps and least square support vector machine for river flow forecasting

    NASA Astrophysics Data System (ADS)

    Ismail, S.; Shabri, A.; Samsudin, R.

    2012-11-01

    Successful river flow forecasting is a major goal and an essential procedure that is necessary in water resource planning and management. There are many forecasting techniques used for river flow forecasting. This study proposed a hybrid model based on a combination of two methods: Self Organizing Map (SOM) and Least Squares Support Vector Machine (LSSVM) model, referred to as the SOM-LSSVM model for river flow forecasting. The hybrid model uses the SOM algorithm to cluster the entire dataset into several disjointed clusters, where the monthly river flows data with similar input pattern are grouped together from a high dimensional input space onto a low dimensional output layer. By doing this, the data with similar input patterns will be mapped to neighbouring neurons in the SOM's output layer. After the dataset has been decomposed into several disjointed clusters, an individual LSSVM is applied to forecast the river flow. The feasibility of this proposed model is evaluated with respect to the actual river flow data from the Bernam River located in Selangor, Malaysia. The performance of the SOM-LSSVM was compared with other single models such as ARIMA, ANN and LSSVM. The performance of these models was then evaluated using various performance indicators. The experimental results show that the SOM-LSSVM model outperforms the other models and performs better than ANN, LSSVM as well as ARIMA for river flow forecasting. It also indicates that the proposed model can forecast more precisely, and provides a promising alternative technique for river flow forecasting.

  6. A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control.

    PubMed

    Ma, Jiaxin; Zhang, Yu; Cichocki, Andrzej; Matsuno, Fumitoshi

    2015-03-01

    This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects event related potentials (ERPs) like P300. While both eye movements and ERPs have been separately used for implementing assistive interfaces, which help patients with motor disabilities in performing daily tasks, the proposed hybrid interface integrates them together. In this way, both the eye movements and ERPs complement each other. Therefore, it can provide a better efficiency and a wider scope of application. In this study, we design a threshold algorithm that can recognize four kinds of eye movements including blink, wink, gaze, and frown. In addition, an oddball paradigm with stimuli of inverted faces is used to evoke multiple ERP components including P300, N170, and VPP. To verify the effectiveness of the proposed system, two different online experiments are carried out. One is to control a multifunctional humanoid robot, and the other is to control four mobile robots. In both experiments, the subjects can complete tasks effectively by using the proposed interface, whereas the best completion time is relatively short and very close to the one operated by hand.

  7. Hybrid dimensionality reduction method based on support vector machine and independent component analysis.

    PubMed

    Moon, Sangwoo; Qi, Hairong

    2012-05-01

    This paper presents a new hybrid dimensionality reduction method to seek projection through optimization of both structural risk (supervised criterion) and data independence (unsupervised criterion). Classification accuracy is used as a metric to evaluate the performance of the method. By minimizing the structural risk, projection originated from the decision boundaries directly improves the classification performance from a supervised perspective. From an unsupervised perspective, projection can also be obtained based on maximum independence among features (or attributes) in data to indirectly achieve better classification accuracy over more intrinsic representation of the data. Orthogonality interrelates the two sets of projections such that minimum redundancy exists between the projections, leading to more effective dimensionality reduction. Experimental results show that the proposed hybrid dimensionality reduction method that satisfies both criteria simultaneously provides higher classification performance, especially for noisy data sets, in relatively lower dimensional space than various existing methods.

  8. A fast hybrid methodology based on machine learning, quantum methods, and experimental measurements for evaluating material properties

    NASA Astrophysics Data System (ADS)

    Kong, Chang Sun; Haverty, Michael; Simka, Harsono; Shankar, Sadasivan; Rajan, Krishna

    2017-09-01

    We present a hybrid approach based on both machine learning and targeted ab-initio calculations to determine adhesion energies between dissimilar materials. The goals of this approach are to complement experimental and/or all ab-initio computational efforts, to identify promising materials rapidly and identify in a quantitative manner the relative contributions of the different material attributes affecting adhesion. Applications of the methodology to predict bulk modulus, yield strength, adhesion and wetting properties of copper (Cu) with other materials including metals, nitrides and oxides is discussed in this paper. In the machine learning component of this methodology, the parameters that were chosen can be roughly divided into four types: atomic and crystalline parameters (which are related to specific elements such as electronegativities, electron densities in Wigner-Seitz cells); bulk material properties (e.g. melting point), mechanical properties (e.g. modulus) and those representing atomic characteristics in ab-initio formalisms (e.g. pseudopotentials). The atomic parameters are defined over one dataset to determine property correlation with published experimental data. We then develop a semi-empirical model across multiple datasets to predict adhesion in material interfaces outside the original datasets. Since adhesion is between two materials, we appropriately use parameters which indicate differences between the elements that comprise the materials. These semi-empirical predictions agree reasonably with the trend in chemical work of adhesion predicted using ab-initio techniques and are used for fast materials screening. For the screened candidates, the ab-initio modeling component provides fundamental understanding of the chemical interactions at the interface, and explains the wetting thermodynamics of thin Cu layers on various substrates. Comparison against ultra-high vacuum (UHV) experiments for well-characterized Cu/Ta and Cu/α-Al2O3 interfaces is

  9. A hybrid machine learning model to estimate nitrate contamination of production zone groundwater in the Central Valley, California

    NASA Astrophysics Data System (ADS)

    Ransom, K.; Nolan, B. T.; Faunt, C. C.; Bell, A.; Gronberg, J.; Traum, J.; Wheeler, D. C.; Rosecrans, C.; Belitz, K.; Eberts, S.; Harter, T.

    2016-12-01

    A hybrid, non-linear, machine learning statistical model was developed within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface in the Central Valley, California. A database of 213 predictor variables representing well characteristics, historical and current field and county scale nitrogen mass balance, historical and current landuse, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6,000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The machine learning method, gradient boosting machine (GBM) was used to screen predictor variables and rank them in order of importance in relation to the groundwater nitrate measurements. The top five most important predictor variables included oxidation/reduction characteristics, historical field scale nitrogen mass balance, climate, and depth to 60 year old water. Twenty-two variables were selected for the final model and final model errors for log-transformed hold-out data were R squared of 0.45 and root mean square error (RMSE) of 1.124. Modeled mean groundwater age was tested separately for error improvement in the model and when included decreased model RMSE by 0.5% compared to the same model without age and by 0.20% compared to the model with all 213 variables. 1D and 2D partial plots were examined to determine how variables behave individually and interact in the model. Some variables behaved as expected: log nitrate decreased with increasing probability of anoxic conditions and depth to 60 year old water, generally decreased with increasing natural landuse surrounding wells and increasing mean groundwater age, generally increased with increased minimum depth to high water table and with increased base flow index value. Other variables exhibited much more erratic or noisy behavior in

  10. A novel design and driving strategy for a hybrid electric machine with torque performance enhancement both taking reluctance and electromagnetic attraction effects into account

    NASA Astrophysics Data System (ADS)

    Huang, Wen-Nan; Chen, Wan-Pei; Teng, Ching-Cheng; Chen, Mu-Ping

    2006-09-01

    A novel design, the hybrid electric machine, that owns improved competence for the output torque regulation as well as enlarged power density comparing to the conventional brushless machines by making use of the simultaneous performance overlapping concept based on magnetism is proposed in this paper. The developed design concept is focused on electric machine structure and its counterpart drive for applying two main magnetic-power transmitting paths by combination of both features of magnetic tendencies of flux generation that may flow in the path with minimum reluctance and direction owning the electromagnetic motive attraction. The verifications demonstrate that the outputted torque owns effective improvement by the presented concept of the electric machine based on the equivalent 3-hp frame than the conventional brushless motors.

  11. A hybrid prognostic model for multistep ahead prediction of machine condition

    NASA Astrophysics Data System (ADS)

    Roulias, D.; Loutas, T. H.; Kostopoulos, V.

    2012-05-01

    Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

  12. Particulate Matter (PM) Pollution

    MedlinePlus

    ... Environmental Protection Agency Search Search Particulate Matter (PM) Pollution Contact Us Share Most PM particles form in ... and cause serious health effects. Particulate Matter (PM) Pollution PM Basics What is PM, and how does ...

  13. Morphological analysis of dendrites and spines by hybridization of ridge detection with twin support vector machine.

    PubMed

    Wang, Shuihua; Chen, Mengmeng; Li, Yang; Shao, Ying; Zhang, Yudong; Du, Sidan; Wu, Jane

    2016-01-01

    Dendritic spines are described as neuronal protrusions. The morphology of dendritic spines and dendrites has a strong relationship to its function, as well as playing an important role in understanding brain function. Quantitative analysis of dendrites and dendritic spines is essential to an understanding of the formation and function of the nervous system. However, highly efficient tools for the quantitative analysis of dendrites and dendritic spines are currently undeveloped. In this paper we propose a novel three-step cascaded algorithm-RTSVM- which is composed of ridge detection as the curvature structure identifier for backbone extraction, boundary location based on differences in density, the Hu moment as features and Twin Support Vector Machine (TSVM) classifiers for spine classification. Our data demonstrates that this newly developed algorithm has performed better than other available techniques used to detect accuracy and false alarm rates. This algorithm will be used effectively in neuroscience research.

  14. Cervical cancer survival prediction using hybrid of SMOTE, CART and smooth support vector machine

    NASA Astrophysics Data System (ADS)

    Purnami, S. W.; Khasanah, P. M.; Sumartini, S. H.; Chosuvivatwong, V.; Sriplung, H.

    2016-04-01

    According to the WHO, every two minutes there is one patient who died from cervical cancer. The high mortality rate is due to the lack of awareness of women for early detection. There are several factors that supposedly influence the survival of cervical cancer patients, including age, anemia status, stage, type of treatment, complications and secondary disease. This study wants to classify/predict cervical cancer survival based on those factors. Various classifications methods: classification and regression tree (CART), smooth support vector machine (SSVM), three order spline SSVM (TSSVM) were used. Since the data of cervical cancer are imbalanced, synthetic minority oversampling technique (SMOTE) is used for handling imbalanced dataset. Performances of these methods are evaluated using accuracy, sensitivity and specificity. Results of this study show that balancing data using SMOTE as preprocessing can improve performance of classification. The SMOTE-SSVM method provided better result than SMOTE-TSSVM and SMOTE-CART.

  15. Morphological analysis of dendrites and spines by hybridization of ridge detection with twin support vector machine

    PubMed Central

    Wang, Shuihua; Chen, Mengmeng; Li, Yang; Shao, Ying; Zhang, Yudong

    2016-01-01

    Dendritic spines are described as neuronal protrusions. The morphology of dendritic spines and dendrites has a strong relationship to its function, as well as playing an important role in understanding brain function. Quantitative analysis of dendrites and dendritic spines is essential to an understanding of the formation and function of the nervous system. However, highly efficient tools for the quantitative analysis of dendrites and dendritic spines are currently undeveloped. In this paper we propose a novel three-step cascaded algorithm–RTSVM— which is composed of ridge detection as the curvature structure identifier for backbone extraction, boundary location based on differences in density, the Hu moment as features and Twin Support Vector Machine (TSVM) classifiers for spine classification. Our data demonstrates that this newly developed algorithm has performed better than other available techniques used to detect accuracy and false alarm rates. This algorithm will be used effectively in neuroscience research. PMID:27547530

  16. Determination of the contribution of northern Africa dust source areas to PM10 concentrations over the central Iberian Peninsula using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) model

    NASA Astrophysics Data System (ADS)

    Escudero, M.; Stein, A.; Draxler, R. R.; Querol, X.; Alastuey, A.; Castillo, S.; Avila, A.

    2006-03-01

    A source apportionment methodology has been implemented to estimate the contribution from different arid geographical areas to the levels of measured atmospheric particulate matter with diameters less than 10 μm (PM10). Toward that end, the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) has been used to quantify the proportions of mineral dust originated from specific geographical areas in northern Africa. HYSPLIT simulates the transport, dispersion, and deposition of dust plumes as they travel from the source areas to the receptors. This model has been configured to reproduce high daily ambient PM10 levels recorded at three Spanish EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-Range Transmission of Air pollutants in Europe) regional background monitoring stations, located over the central Iberian Peninsula, during a North African dust outbreak from 12 to 15 March 2003. Different model setups have been utilized to determine the best suite of parameters needed to better represent the observed concentrations. Once the simulation has been configured, the model has been run for individual scenarios which include eight specific source areas over northern Africa considered as possible contributors to the PM10 levels measured at the monitoring stations. One additional run has been carried out to account for the rest of the dust sources in northern Africa. Furthermore, the fractional contribution to the PM10 air concentrations at the receptors from each run has been used to estimate the source apportionment. According to these calculations, the contribution from each area to the PM10 recorded over central Iberia for the March 2003 episode can be detailed as follows: 20-30% of the PM10 dust originated in Mauritania and the western Sahara, 15-20% from Mali, Mauritania and the western flanks of the Ahaggar Mountains, and 55-60% from other northwestern African sources within the rest of the desert source area.

  17. Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

    PubMed Central

    Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

    2014-01-01

    The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. PMID:25215324

  18. Satellite fault diagnosis using support vector machines based on a hybrid voting mechanism.

    PubMed

    Yin, Hong; Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

    2014-01-01

    The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved.

  19. Using a brain-machine interface to control a hybrid upper limb exoskeleton during rehabilitation of patients with neurological conditions.

    PubMed

    Hortal, Enrique; Planelles, Daniel; Resquin, Francisco; Climent, José M; Azorín, José M; Pons, José L

    2015-10-17

    As a consequence of the increase of cerebro-vascular accidents, the number of people suffering from motor disabilities is raising. Exoskeletons, Functional Electrical Stimulation (FES) devices and Brain-Machine Interfaces (BMIs) could be combined for rehabilitation purposes in order to improve therapy outcomes. In this work, a system based on a hybrid upper limb exoskeleton is used for neurological rehabilitation. Reaching movements are supported by the passive exoskeleton ArmeoSpring and FES. The movement execution is triggered by an EEG-based BMI. The BMI uses two different methods to interact with the exoskeleton from the user's brain activity. The first method relies on motor imagery tasks classification, whilst the second one is based on movement intention detection. Three healthy users and five patients with neurological conditions participated in the experiments to verify the usability of the system. Using the BMI based on motor imagery, healthy volunteers obtained an average accuracy of 82.9 ± 14.5 %, and patients obtained an accuracy of 65.3 ± 9.0 %, with a low False Positives rate (FP) (19.2 ± 10.4 % and 15.0 ± 8.4 %, respectively). On the other hand, by using the BMI based on detecting the arm movement intention, the average accuracy was 76.7 ± 13.2 % for healthy users and 71.6 ± 15.8 % for patients, with 28.7 ± 19.9 % and 21.2 ± 13.3 % of FP rate (healthy users and patients, respectively). The accuracy of the results shows that the combined use of a hybrid upper limb exoskeleton and a BMI could be used for rehabilitation therapies. The advantage of this system is that the user is an active part of the rehabilitation procedure. The next step will be to verify what are the clinical benefits for the patients using this new rehabilitation procedure.

  20. Hybrid spiral-dynamic bacteria-chemotaxis algorithm with application to control two-wheeled machines.

    PubMed

    Goher, K M; Almeshal, A M; Agouri, S A; Nasir, A N K; Tokhi, M O; Alenezi, M R; Al Zanki, T; Fadlallah, S O

    2017-01-01

    This paper presents the implementation of the hybrid spiral-dynamic bacteria-chemotaxis (HSDBC) approach to control two different configurations of a two-wheeled vehicle. The HSDBC is a combination of bacterial chemotaxis used in bacterial forging algorithm (BFA) and the spiral-dynamic algorithm (SDA). BFA provides a good exploration strategy due to the chemotaxis approach. However, it endures an oscillation problem near the end of the search process when using a large step size. Conversely; for a small step size, it affords better exploitation and accuracy with slower convergence. SDA provides better stability when approaching an optimum point and has faster convergence speed. This may cause the search agents to get trapped into local optima which results in low accurate solution. HSDBC exploits the chemotactic strategy of BFA and fitness accuracy and convergence speed of SDA so as to overcome the problems associated with both the SDA and BFA algorithms alone. The HSDBC thus developed is evaluated in optimizing the performance and energy consumption of two highly nonlinear platforms, namely single and double inverted pendulum-like vehicles with an extended rod. Comparative results with BFA and SDA show that the proposed algorithm is able to result in better performance of the highly nonlinear systems.

  1. Evaluation of performance and magnetic characteristics of a radial-radial flux compound-structure permanent-magnet synchronous machine used for hybrid electric vehicle

    NASA Astrophysics Data System (ADS)

    Zheng, Ping; Liu, Ranran; Shen, Lin; Li, Lina; Fan, Weiguang; Wu, Qian; Zhao, Jing

    2008-04-01

    A breed of compound-structure permanent-magnet synchronous machine (CS-PMSM) is used for power-split hybrid electric vehicles (HEVs). It can help to fulfill both the speed and torque control of the internal combustion engine and, thus, realize the optimum operation of the HEV. In this paper, a radial-radial flux CS-PMSM, which is integrated by two machines radially [one stator machine (SM) and one double-rotor machine (DRM)], is designed and investigated. The machine performance is evaluated with finite-element method (FEM) and satisfactory results are obtained. The back electromotive force curves of the two machines are somewhat similar to sinusoidal ones; the average torques both meet the requirements; and due to the adoption of skewed slots, the cogging torques and torque ripples are quite small. The inductance parameter is calculated with a phasor diagram based two-dimensional FEM and the magnetic saturation and cross-magnetization effect are discussed. It is concluded that the SM is slightly saturated with no or little cross-magnetization phenomenon, whereas the DRM has deep-degree magnetic saturation and the cross-magnetization effect is notable.

  2. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    NASA Astrophysics Data System (ADS)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  3. Analysis and control on changeable wheel tool system of hybrid grinding and polishing machine tool for blade finishing

    NASA Astrophysics Data System (ADS)

    He, Qiuwei; Lv, Xingming; Wang, Xin; Qu, Xingtian; Zhao, Ji

    2017-01-01

    Blade is the key component in the energy power equipment of turbine, aircraft engines and so on. Researches on the process and equipment for blade finishing become one of important and difficult point. To control precisely tool system of developed hybrid grinding and polishing machine tool for blade finishing, the tool system with changeable wheel for belt polishing is analyzed in this paper. Firstly, the belt length and wrap angle of each wheel in different position of tension wheel swing angle in the process of changing wheel is analyzed. The reasonable belt length is calculated by using MATLAB, and relationships between wrap angle of each wheel and cylinder expansion amount of contact wheel are obtained. Then, the control system for changeable wheel tool structure is developed. Lastly, the surface roughness of blade finishing is verified by experiments. Theoretical analysis and experimental results show that reasonable belt length and wheel wrap angle can be obtained by proposed analysis method, the changeable wheel tool system can be controlled precisely, and the surface roughness of blade after grinding meets the design requirements.

  4. Partial least squares regression, support vector machine regression, and transcriptome-based distances for prediction of maize hybrid performance with gene expression data.

    PubMed

    Fu, Junjie; Falke, K Christin; Thiemann, Alexander; Schrag, Tobias A; Melchinger, Albrecht E; Scholten, Stefan; Frisch, Matthias

    2012-03-01

    The performance of hybrids can be predicted with gene expression data from their parental inbred lines. Implementing such prediction approaches in breeding programs promises to increase the efficiency of hybrid breeding. The objectives of our study were to compare the accuracy of prediction models employing multiple linear regression (MLR), partial least squares regression (PLS), support vector machine regression (SVM), and transcriptome-based distances (D(B)). For a factorial of 7 flint and 14 dent maize lines, the grain yield of the hybrids was assessed and the gene expression of the parental lines was profiled with a 56k microarray. The accuracy of the prediction models was measured by the correlation between predicted and observed yield employing two cross-validation schemes. The first modeled the prediction of hybrids when testcross data are available for both parental lines (type 2 hybrids), and the second modeled the prediction of hybrids when no testcross data for the parental lines were available (type 0 hybrids). MLR, SVM, and PLS resulted in a high correlation between predicted and observed yield for type 2 hybrids, whereas for type 0 hybrids D(B) had greater prediction accuracy. The regression methods were robust to the choice of the set of profiled genes and required only a few hundred genes. In contrast, for an accurate hybrid prediction with D(B), 1,000-1,500 genes were required, and the prediction accuracy depended strongly on the set of profiled genes. We conclude that for prediction within one set of genetic material MLR is a promising approach, and for transferring prediction models from one set of genetic material to a related one, the transcriptome-based distance D(B) is most promising.

  5. Daily PM2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm.

    PubMed

    Sun, Wei; Sun, Jingyi

    2017-03-01

    Increased attention has been paid to PM2.5 pollution in China. Due to its detrimental effects on environment and health, it is important to establish a PM2.5 concentration forecasting model with high precision for its monitoring and controlling. This paper presents a novel hybrid model based on principal component analysis (PCA) and least squares support vector machine (LSSVM) optimized by cuckoo search (CS). First PCA is adopted to extract original features and reduce dimension for input selection. Then LSSVM is applied to predict the daily PM2.5 concentration. The parameters in LSSVM are fine-tuned by CS to improve its generalization. An experiment study reveals that the proposed approach outperforms a single LSSVM model with default parameters and a general regression neural network (GRNN) model in PM2.5 concentration prediction. Therefore the established model presents the potential to be applied to air quality forecasting systems.

  6. Prediction of vertical PM2.5 concentrations alongside an elevated expressway by using the neural network hybrid model and generalized additive model

    NASA Astrophysics Data System (ADS)

    Gao, Ya; Wang, Zhanyong; Lu, Qing-Chang; Liu, Chao; Peng, Zhong-Ren; Yu, Yue

    2016-10-01

    A study on vertical variation of PM2.5 concentrations was carried out in this paper. Field measurements were conducted at eight different floor heights outside a building alongside a typical elevated expressway in downtown Shanghai, China. Results show that PM2.5 concentration decreases significantly with the increase of height from the 3rd to 7th floor or the 8th to 15th floor, and increases suddenly from the 7th to 8th floor which is the same height as the elevated expressway. A non-parametric test indicates that the data of PM2.5 concentration is statistically different under the 7th floor and above the 8th floor at the 5% significance level. To investigate the relationships between PM2.5 concentration and influencing factors, the Pearson correlation analysis was performed and the results indicate that both traffic and meteorological factors have crucial impacts on the variation of PM2.5 concentration, but there is a rather large variation in correlation coefficients under the 7th floor and above the 8th floor. Furthermore, the back propagation neural network based on principal component analysis (PCA-BPNN), as well as generalized additive model (GAM), was applied to predict the vertical PM2.5 concentration and examined with the field measurement dataset. Experimental results indicated that both models can obtain accurate predictions, while PCA-BPNN model provides more reliable and accurate predictions as it can reduce the complexity and eliminate data co-linearity. These findings reveal the vertical distribution of PM2.5 concentration and the potential of the proposed model to be applicable to predict the vertical trends of air pollution in similar situations.

  7. Using Phun to Study "Perpetual Motion" Machines

    ERIC Educational Resources Information Center

    Kores, Jaroslav

    2012-01-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th-century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over…

  8. Using Phun to Study "Perpetual Motion" Machines

    ERIC Educational Resources Information Center

    Kores, Jaroslav

    2012-01-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th-century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over…

  9. Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient.

    PubMed

    Resquin, F; Ibañez, J; Gonzalez-Vargas, J; Brunetti, F; Dimbwadyo, I; Alves, S; Carrasco, L; Torres, L; Pons, Jose Luis

    2016-08-01

    Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user's movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.

  10. Research on a novel axial-flux magnetic-field-modulated brushless double-rotor machine with low axial force and high efficiency

    NASA Astrophysics Data System (ADS)

    Tong, Chengde; Song, Zhiyi; Bai, Jingang; Liu, Jiaqi; Zheng, Ping

    2017-05-01

    The axial-flux magnetic-field-modulated brushless double-rotor machine (MFM-BDRM) is a possible alternative as a power-split device for hybrid electric vehicles (HEVs). However, the existence of large axial force may lead to assembly problems and rich inner air-gap harmonics could result in high PM loss and low efficiency. This paper proposes a novel axial-flux MFM-BDRM with improved PM rotor structure. 2-D analytical method to predict the magnetic-field distribution of the proposed MFM-BDRM is developed and the design procedure of the proposed machine is illustrated. The impact of key geometrical parameters on axial force and torque is investigated. To evaluate the advantage of the proposed machine, a comparison is made with a conventional one with respect to electromagnetic performances. Results show that the proposed machine is effective in reducing PM eddy loss and axial force by 60% and 35%, respectively.

  11. Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

    NASA Astrophysics Data System (ADS)

    Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

    2015-05-01

    Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

  12. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

    USGS Publications Warehouse

    Ransom, Katherine M.; Nolan, Bernard T.; Traum, Jonathan A.; Faunt, Claudia; Bell, Andrew M.; Gronberg, Jo Ann M.; Wheeler, David C.; Zamora, Celia; Jurgens, Bryant; Schwarz, Gregory; Belitz, Kenneth; Eberts, Sandra; Kourakos, George; Harter, Thomas

    2017-01-01

    Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative

  13. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA.

    PubMed

    Ransom, Katherine M; Nolan, Bernard T; A Traum, Jonathan; Faunt, Claudia C; Bell, Andrew M; Gronberg, Jo Ann M; Wheeler, David C; Z Rosecrans, Celia; Jurgens, Bryant; Schwarz, Gregory E; Belitz, Kenneth; M Eberts, Sandra; Kourakos, George; Harter, Thomas

    2017-12-01

    Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50ppb and probability of dissolved oxygen concentration to be below 0.5ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971-2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on

  14. A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon, South Korea

    NASA Astrophysics Data System (ADS)

    Vasu, Nikhil N.; Lee, Seung-Rae

    2016-06-01

    An ever-increasing trend of extreme rainfall events in South Korea owing to climate change is causing shallow landslides and debris flows in mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion KRW (South Korean Won) in losses in addition to fatalities every year. The most common type of landslide observed is the shallow landslide, which occurs at 1-3 m depth, and may mobilize into more catastrophic flow-type landslides. Hence, to predict potential landslide areas, susceptibility maps are developed in a geographical information system (GIS) environment utilizing available morphological, hydrological, geotechnical, and geological data. Landslide susceptibility models were developed using 163 landslide points and an equal number of nonlandslide points in Mt. Woomyeon, Seoul, and 23 landslide conditioning factors. However, because not all of the factors contribute to the determination of the spatial probability for landslide initiation, and a simple filter or wrapper-based approach is not efficient in identifying all of the relevant features, a feedback-loop-based hybrid algorithm was implemented in conjunction with a learning scheme called an extreme learning machine, which is based on a single-layer, feed-forward network. Validation of the constructed susceptibility model was conducted using a testing set of landslide inventory data through a prediction rate curve. The model selected 13 relevant conditioning factors out of the initial 23; and the resulting susceptibility map shows a success rate of 85% and a prediction rate of 89.45%, indicating a good performance, in contrast to the low success and prediction rate of 69.19% and 56.19%, respectively, as obtained using a wrapper technique.

  15. Real Time Flux Control in PM Motors

    SciTech Connect

    Otaduy, P.J.

    2005-09-27

    Significant research at the Oak Ridge National Laboratory (ORNL) Power Electronics and Electric Machinery Research Center (PEEMRC) is being conducted to develop ways to increase (1) torque, (2) speed range, and (3) efficiency of traction electric motors for hybrid electric vehicles (HEV) within existing current and voltage bounds. Current is limited by the inverter semiconductor devices' capability and voltage is limited by the stator wire insulation's ability to withstand the maximum back-electromotive force (emf), which occurs at the upper end of the speed range. One research track has been to explore ways to control the path and magnitude of magnetic flux while the motor is operating. The phrase, real time flux control (RTFC), refers to this mode of operation in which system parameters are changed while the motor is operating to improve its performance and speed range. RTFC has potential to meet an increased torque demand by introducing additional flux through the main air gap from an external source. It can augment the speed range by diverting flux away from the main air gap to reduce back-emf at high speeds. Conventional RTFC technology is known as vector control [1]. Vector control decomposes the stator current into two components; one that produces torque and a second that opposes (weakens) the magnetic field generated by the rotor, thereby requiring more overall stator current and reducing the efficiency. Efficiency can be improved by selecting a RTFC method that reduces the back-emf without increasing the average current. This favors methods that use pulse currents or very low currents to achieve field weakening. Foremost in ORNL's effort to develop flux control is the work of J. S. Hsu. Early research [2,3] introduced direct control of air-gap flux in permanent magnet (PM) machines and demonstrated it with a flux-controlled generator. The configuration eliminates the problem of demagnetization because it diverts all the flux from the magnets instead of

  16. Hybrid Optical Inference Machines

    DTIC Science & Technology

    1991-09-27

    Mitsunaga, and K. Kyuma, "GaAs/AlGaAs Optical Synaptic Interconnection Device for Neural Networks,ŗ Opt. Lett. 14, 844-846 (1989). 8. Y. Nitta, J. Ohta, K...tautologies (step .t above) is computationally chne) using both neural network and symbolic substtution the most significant step of the optical resolution...the-theories of connectionistic ( neural net- Derstine and Guha consider PARLOG, a version of PRO- work) computing offer several opportunities for

  17. Hybrid PolyLingual Object Model: An Efficient and Seamless Integration of Java and Native Components on the Dalvik Virtual Machine

    PubMed Central

    Huang, Yukun; Chen, Rong; Wei, Jingbo; Pei, Xilong; Cao, Jing; Prakash Jayaraman, Prem; Ranjan, Rajiv

    2014-01-01

    JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO) model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded. PMID:25110745

  18. The impact analysis of the connecting pipe length and diameter on the operation of a piston hybrid power machine of positive displacement with gas suction capacity

    NASA Astrophysics Data System (ADS)

    Shcherba, V. E.; Grigoriev, A. V.; Averyanov, G. S.; Surikov, V. I.; Vedruchenko, V. P.; Galdin, N. S.; Trukhanova, D. A.

    2017-08-01

    The article analyzes the impact of the connecting liquid pipe length and diameter on consumables and power characteristics of the piston hybrid power machine with gas suction capacity. The following operating characteristics of the machine were constructed and analyzed: the average height of the liquid column in the jacket space; instantaneous velocity and height of the liquid column in the jacket space; the relative height of the liquid column in the jacket space; volumetric efficiency; indicator isothermal efficiency; flowrate in the pump section; relative pressure losses during suction; relative flowrate. The dependence of the instantaneous pressure in the work space and the suction space of the compressor section on the rotation angle of the crankshaft is determined for different values of the length and diameter of the connecting pipeline.

  19. Demonstration of a Semi-Autonomous Hybrid Brain-Machine Interface using Human Intracranial EEG, Eye Tracking, and Computer Vision to Control a Robotic Upper Limb Prosthetic

    PubMed Central

    McMullen, David P.; Hotson, Guy; Katyal, Kapil D.; Wester, Brock A.; Fifer, Matthew S.; McGee, Timothy G.; Harris, Andrew; Johannes, Matthew S.; Vogelstein, R. Jacob; Ravitz, Alan D.; Anderson, William S.; Thakor, Nitish V.; Crone, Nathan E.

    2014-01-01

    To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 seconds for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs. PMID:24760914

  20. Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

    PubMed

    McMullen, David P; Hotson, Guy; Katyal, Kapil D; Wester, Brock A; Fifer, Matthew S; McGee, Timothy G; Harris, Andrew; Johannes, Matthew S; Vogelstein, R Jacob; Ravitz, Alan D; Anderson, William S; Thakor, Nitish V; Crone, Nathan E

    2014-07-01

    To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 s for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

  1. Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states.

    PubMed

    Kloog, Itai; Nordio, Francesco; Coull, Brent A; Schwartz, Joel

    2012-11-06

    Satellite-derived aerosol optical depth (AOD) measurements have the potential to provide spatiotemporally resolved predictions of both long and short-term exposures, but previous studies have generally shown moderate predictive power and lacked detailed high spatio- temporal resolution predictions across large domains. We aimed at extending our previous work by validating our model in another region with different geographical and metrological characteristics, and incorporating fine scale land use regression and nonrandom missingness to better predict PM(2.5) concentrations for days with or without satellite AOD measures. We start by calibrating AOD data for 2000-2008 across the Mid-Atlantic. We used mixed models regressing PM(2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We used inverse probability weighting to account for nonrandom missingness of AOD, nested regions within days to capture spatial variation in the daily calibration, and introduced a penalization method that reduces the dimensionality of the large number of spatial and temporal predictors without selecting different predictors in different locations. We then take advantage of the association between grid-cell specific AOD values and PM(2.5) monitoring data, together with associations between AOD values in neighboring grid cells to develop grid cell predictions when AOD is missing. Finally to get local predictions (at the resolution of 50 m), we regressed the residuals from the predictions for each monitor from these previous steps against the local land use variables specific for each monitor. "Out-of-sample" 10-fold cross-validation was used to quantify the accuracy of our predictions at each step. For all days without AOD values, model performance was excellent (mean "out-of-sample" R(2) = 0.81, year-to-year variation 0.79-0.84). Upon removal of outliers in the PM(2.5) monitoring data, the results of the cross validation procedure was

  2. Using Phun to Study ``Perpetual Motion'' Machines

    NASA Astrophysics Data System (ADS)

    Koreš, Jaroslav

    2012-05-01

    The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th- century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over the centuries numerous proposals for PM have been made, involving ever more elements of modern science in their construction. It is possible to test a variety of PM machines in the classroom using a program called Phun2 or its commercial version Algodoo.3 The programs are designed to simulate physical processes and we can easily simulate mechanical machines using them. They provide an intuitive graphical environment controlled with a mouse; a programming language is not needed. This paper describes simulations of four different (supposed) PM machines.4

  3. A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

    NASA Technical Reports Server (NTRS)

    Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

    2014-01-01

    The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions

  4. A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

    PubMed Central

    Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

    2017-01-01

    Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions

  5. A novel design of DC-AC electrical machine rotary converter for hybrid solar and wind energy applications

    NASA Astrophysics Data System (ADS)

    Mohammed, K. G.; Ramli, A. Q.; Amirulddin, U. A. U.

    2013-06-01

    This paper proposes the design of a new bi-directional DC-AC rotary converter machine to convert a d.c. voltage to three-phase voltage and vice-versa using a two-stage energy conversion machine. The rotary converter consists of two main stages which are combined into single frame. These two stages are constructed from three main electromagnetic components. The first inner electromagnetic component represents the input stage that enables the DC power generated by solar energy from photo-voltaic cells to be transformed by the second and third components electro-magnetically to produce multi-phase voltages at the output stage. At the same time, extra kinetic energy from wind, which is sufficiently available, can be added to existing torque on the second electromagnetic component. Both of these input energies will add up to the final energy generated at the output terminals. Therefore, the machine will be able to convert solar and wind energies to the output terminals simultaneously. If the solar energy is low, the available wind energy will be able to provide energy to the output terminals and at the same time charges the batteries which are connected as backup system. At this moment, the machine behaves as wind turbine. The energy output from the machine benefits from two energy sources which are solar and wind. At night when the solar energy is not available and also the load is low, the wind energy is able to charge the batteries and at the same time provides output electrical power to the remaining the load. Therefore, the proposed system will have high usage of available renewable energy as compared to separated wind or solar systems. MATLAB codes are used to calculate the required dimensions, the magnetic and electrical circuits parameters to design of the new bi-directional rotary converter machine.

  6. Experimental study of cross-phase modulation reduction in hybrid systems with co-propagating 100G PM-QPSK and 10G OOK.

    PubMed

    Searcy, Steven; Tibuleac, Sorin

    2013-12-16

    We experimentally investigate various methods for reducing cross-phase modulation in hybrid networks with mixed 100G and 10G traffic. The experimental results over standard single-mode and non-zero dispersion-shifted fiber types demonstrate the effectiveness of several different XPM reduction techniques as well as the interplay between them. Nonlinear transmission performance is quantified using the Nonlinear Threshold metric as a function of key system features, including DCM type, dispersion map, spectral guard bands, and carrier phase estimation window size. Fiber Bragg grating-based DCMs are shown to offer a distinct advantage over fiber-based DCMs under certain conditions, particularly in dispersion-managed systems with very strong XPM. The average walk-off per span is introduced as a simple yet effective metric to compare different methods of XPM mitigation.

  7. Developing a Hybrid Model to Predict Student First Year Retention in STEM Disciplines Using Machine Learning Techniques

    ERIC Educational Resources Information Center

    Alkhasawneh, Ruba; Hargraves, Rosalyn Hobson

    2014-01-01

    The purpose of this research was to develop a hybrid framework to model first year student retention for underrepresented minority (URM) students comprising African Americans, Hispanic Americans, and Native Americans. Identifying inputs that best contribute to student retention provides significant information for institutions to learn about…

  8. Design Comparison of Inner and Outer Rotor of Permanent Magnet Flux Switching Machine for Electric Bicycle Application

    NASA Astrophysics Data System (ADS)

    Jusoh, L. I.; Sulaiman, E.; Bahrim, F. S.; Kumar, R.

    2017-08-01

    Recent advancements have led to the development of flux switching machines (FSMs) with flux sources within the stators. The advantage of being a single-piece machine with a robust rotor structure makes FSM an excellent choice for speed applications. There are three categories of FSM, namely, the permanent magnet (PM) FSM, the field excitation (FE) FSM, and the hybrid excitation (HE) FSM. The PMFSM and the FEFSM have their respective PM and field excitation coil (FEC) as their key flux sources. Meanwhile, as the name suggests, the HEFSM has a combination of PM and FECs as the flux sources. The PMFSM is a simple and cheap machine, and it has the ability to control variable flux, which would be suitable for an electric bicycle. Thus, this paper will present a design comparison between an inner rotor and an outer rotor for a single-phase permanent magnet flux switching machine with 8S-10P, designed specifically for an electric bicycle. The performance of this machine was validated using the 2D- FEA. As conclusion, the outer-rotor has much higher torque approximately at 54.2% of an innerrotor PMFSM. From the comprehensive analysis of both designs it can be conclude that output performance is lower than the SRM and IPMSM design machine. But, it shows that the possibility to increase the design performance by using “deterministic optimization method”.

  9. Three air quality policy case studies: Evaluating mass balance closure and the federal reference method for PM2.5, impacts of light duty diesel vehicles for GHG emissions control, and fleet hybridization as a cost-effective carbon dioxide reduction approach

    NASA Astrophysics Data System (ADS)

    Rees, Sarah L.

    This dissertation examines several policy issues in air quality regarding fine particulate matter (PM2.5) and greenhouse gas (GHG) emissions. First, mass balance closure for the Federal Reference Method (FRM) for measuring PM2.5 is examined using extensive data available from the Pittsburgh Air Quality Study (PAQS). Evaluating the data from PAQS for different measurement techniques provides insight as to the measurement artifacts associated with the FRM, which is the legal definition of PM2.5. This insight is in turn helpful in evaluating effective control technologies to attain PM 2.5 regulatory standards. The second policy issue evaluated is that of light duty diesel vehicles, and whether they provide the reductions in GHG emissions promised. If so, whether they produce corresponding adverse air quality impacts, and how significant these are. Finally, the current trend of purchasing hybrid vehicles for government fleet use is examined using real time data from the Washington State Department of Ecology (Ecology). Evaluating these data allows for a determination as to whether the fuel savings and GHG emission reductions achieved from the widespread use of hybrids in the fleet are worth the additional capital cost from the purchase of hybrids, and whether there are other strategies that could achieve similar reductions without incurring such capital costs.

  10. A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

    PubMed

    He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

    2015-09-01

    In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications.

  11. Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

    NASA Astrophysics Data System (ADS)

    Mozaffari, Ahmad; Vajedi, Mahyar; Chehresaz, Maryyeh; Azad, Nasser L.

    2016-03-01

    The urgent need to meet increasingly tight environmental regulations and new fuel economy requirements has motivated system science researchers and automotive engineers to take advantage of emerging computational techniques to further advance hybrid electric vehicle and plug-in hybrid electric vehicle (PHEV) designs. In particular, research has focused on vehicle powertrain system design optimization, to reduce the fuel consumption and total energy cost while improving the vehicle's driving performance. In this work, two different natural optimization machines, namely the synchronous self-learning Pareto strategy and the elitism non-dominated sorting genetic algorithm, are implemented for component sizing of a specific power-split PHEV platform with a Toyota plug-in Prius as the baseline vehicle. To do this, a high-fidelity model of the Toyota plug-in Prius is employed for the numerical experiments using the Autonomie simulation software. Based on the simulation results, it is demonstrated that Pareto-based algorithms can successfully optimize the design parameters of the vehicle powertrain.

  12. A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

    PubMed

    Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

    2017-02-15

    The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model combining two-phase decomposition technique and extreme learning machine (ELM) optimized by differential evolution (DE) algorithm is developed for AQI forecasting in this paper. In phase I, the complementary ensemble empirical mode decomposition (CEEMD) is utilized to decompose the AQI series into a set of intrinsic mode functions (IMFs) with different frequencies; in phase II, in order to further handle the high frequency IMFs which will increase the forecast difficulty, variational mode decomposition (VMD) is employed to decompose the high frequency IMFs into a number of variational modes (VMs). Then, the ELM model optimized by DE algorithm is applied to forecast all the IMFs and VMs. Finally, the forecast value of each high frequency IMF is obtained through adding up the forecast results of all corresponding VMs, and the forecast series of AQI is obtained by aggregating the forecast results of all IMFs. To verify and validate the proposed model, two daily AQI series from July 1, 2014 to June 30, 2016 collected from Beijing and Shanghai located in China are taken as the test cases to conduct the empirical study. The experimental results show that the proposed hybrid model based on two-phase decomposition technique is remarkably superior to all other considered models for its higher forecast accuracy.

  13. Estimation of in-situ bioremediation system cost using a hybrid Extreme Learning Machine (ELM)-particle swarm optimization approach

    NASA Astrophysics Data System (ADS)

    Yadav, Basant; Ch, Sudheer; Mathur, Shashi; Adamowski, Jan

    2016-12-01

    In-situ bioremediation is the most common groundwater remediation procedure used for treating organically contaminated sites. A simulation-optimization approach, which incorporates a simulation model for groundwaterflow and transport processes within an optimization program, could help engineers in designing a remediation system that best satisfies management objectives as well as regulatory constraints. In-situ bioremediation is a highly complex, non-linear process and the modelling of such a complex system requires significant computational exertion. Soft computing techniques have a flexible mathematical structure which can generalize complex nonlinear processes. In in-situ bioremediation management, a physically-based model is used for the simulation and the simulated data is utilized by the optimization model to optimize the remediation cost. The recalling of simulator to satisfy the constraints is an extremely tedious and time consuming process and thus there is need for a simulator which can reduce the computational burden. This study presents a simulation-optimization approach to achieve an accurate and cost effective in-situ bioremediation system design for groundwater contaminated with BTEX (Benzene, Toluene, Ethylbenzene, and Xylenes) compounds. In this study, the Extreme Learning Machine (ELM) is used as a proxy simulator to replace BIOPLUME III for the simulation. The selection of ELM is done by a comparative analysis with Artificial Neural Network (ANN) and Support Vector Machine (SVM) as they were successfully used in previous studies of in-situ bioremediation system design. Further, a single-objective optimization problem is solved by a coupled Extreme Learning Machine (ELM)-Particle Swarm Optimization (PSO) technique to achieve the minimum cost for the in-situ bioremediation system design. The results indicate that ELM is a faster and more accurate proxy simulator than ANN and SVM. The total cost obtained by the ELM-PSO approach is held to a minimum

  14. A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

    PubMed Central

    Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338

  15. A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

    PubMed

    Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  16. Machinability of Green Powder Metallurgy Components: Part II. Sintered Properties of Components Machined in Green State

    NASA Astrophysics Data System (ADS)

    Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

    2007-06-01

    The green machining process is virtually a must if the powder metallurgy (PM) industries are to solve the lower machining performances associated with PM components. This process is known for lowering the rate of tool wear. Recent improvements in binder/lubricant technologies have led to high-green-strength systems that enable green machining. Combined with the optimized cutting parameters determined in Part I of the study, the green machining of PM components seems to be a viable process for fabricating high performance parts on large scale and complete other shaping processes. This second part of our study presents a comparison between the machining behaviors and the sintered properties of components machined prior to or after sintering. The results show that the radial crush strength measured on rings machined in their green state is equal to that of parts machined after sintering.

  17. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine.

    PubMed

    Qureshi, Muhammad Naveed Iqbal; Oh, Jooyoung; Cho, Dongrae; Jo, Hang Joon; Lee, Boreom

    2017-01-01

    Multimodal features of structural and functional magnetic resonance imaging (MRI) of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE) and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001) accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function) support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  18. Applying support vector machine on hybrid fNIRS/EEG signal to classify driver's conditions (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Nguyen, Thien; Ahn, Sangtae; Jang, Hyojung; Jun, Sung C.; Kim, Jae G.

    2016-03-01

    Driver's condition plays a critical role in driving safety. The fact that about 20 percent of automobile accidents occurred due to driver fatigue leads to a demand for developing a method to monitor driver's status. In this study, we acquired brain signals such as oxy- and deoxyhemoglobin and neuronal electrical activity by a hybrid fNIRS/EEG system. Experiments were conducted with 11 subjects under two conditions: Normal condition, when subjects had enough sleep, and sleep deprivation condition, when subject did not sleep previous night. During experiment, subject performed a driving task with a car simulation system for 30 minutes. After experiment, oxy-hemoglobin and deoxy-hemoglobin changes were derived from fNIRS data, while beta and alpha band relative power were calculated from EEG data. Decrement of oxy-hemoglobin, beta band power, and increment of alpha band power were found in sleep deprivation condition compare to normal condition. These features were then applied to classify two conditions by Fisher's linear discriminant analysis (FLDA). The ratio of alpha-beta relative power showed classification accuracy with a range between 62% and 99% depending on a subject. However, utilization of both EEG and fNIRS features increased accuracy in the range between 68% and 100%. The highest increase of accuracy is from 63% using EEG to 99% using both EEG and fNIRS features. In conclusion, the enhancement of classification accuracy is shown by adding a feature from fNIRS to the feature from EEG using FLDA which provides the need of developing a hybrid fNIRS/EEG system.

  19. A Novel Hybrid Feature Selection Model for Classification of Neuromuscular Dystrophies Using Bhattacharyya Coefficient, Genetic Algorithm and Radial Basis Function Based Support Vector Machine.

    PubMed

    Anand, Divya; Pandey, Babita; Pandey, Devendra K

    2016-09-17

    An accurate classification of neuromuscular disorders is important in providing proper treatment facilities to the patients. Recently, the microarray technology is employed to monitor the level of activity or expression of large number of genes simultaneously. The gene expression data derived from the microarray experiment usually involve a large number of genes but a very few number of samples. There is a need to reduce the dimension of gene expression data which intends to find a small set of discriminative genes that accurately classifies the samples of various kinds of diseases. So, our goal is to find a small subset of genes which ensures the accurate classification of neuromuscular disorders. In the present paper, we propose a novel hybrid feature selection model for classification of neuromuscular disorders. The process of feature selection is done in two phases by integrating Bhattacharyya coefficient and genetic algorithm (GA). In the first phase, we find Bhattacharyya coefficient to choose a candidate gene subset by removing the most redundant genes. In the second phase, the target gene subset is created by selecting the most discriminative gene subset by applying GA wherein the fitness function is calculated using radial basis function support vector machine (RBF SVM). The proposed hybrid algorithm is applied on two publicly available microarray neuromuscular disorders datasets. The results are compared with two individual techniques of feature selection, namely Bhattacharyya coefficient and GA, and one integrated technique, i.e., Bhattacharyya-GA wherein the fitness function of GA is calculated using four other classifiers, which shows that the proposed integrated method is capable of giving the better classification accuracy.

  20. Cancer Classification in Microarray Data using a Hybrid Selective Independent Component Analysis and υ-Support Vector Machine Algorithm

    PubMed Central

    Saberkari, Hamidreza; Shamsi, Mousa; Joroughi, Mahsa; Golabi, Faegheh; Sedaaghi, Mohammad Hossein

    2014-01-01

    Microarray data have an important role in identification and classification of the cancer tissues. Having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. For this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microarray data. An appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, we use selective independent component analysis (SICA) for decreasing the dimension of microarray data. Using this selective algorithm, we can solve the instability problem occurred in the case of employing conventional independent component analysis (ICA) methods. First, the reconstruction error and selective set are analyzed as independent components of each gene, which have a small part in making error in order to reconstruct new sample. Then, some of the modified support vector machine (υ-SVM) algorithm sub-classifiers are trained, simultaneously. Eventually, the best sub-classifier with the highest recognition rate is selected. The proposed algorithm is applied on three cancer datasets (leukemia, breast cancer and lung cancer datasets), and its results are compared with other existing methods. The results illustrate that the proposed algorithm (SICA + υ-SVM) has higher accuracy and validity in order to increase the classification accuracy. Such that, our proposed algorithm exhibits relative improvements of 3.3% in correctness rate over ICA + SVM and SVM algorithms in lung cancer dataset. PMID:25426433

  1. Cancer Classification in Microarray Data using a Hybrid Selective Independent Component Analysis and υ-Support Vector Machine Algorithm.

    PubMed

    Saberkari, Hamidreza; Shamsi, Mousa; Joroughi, Mahsa; Golabi, Faegheh; Sedaaghi, Mohammad Hossein

    2014-10-01

    Microarray data have an important role in identification and classification of the cancer tissues. Having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. For this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microarray data. An appropriate gene selection method can significantly improve the performance of cancer classification. In this paper, we use selective independent component analysis (SICA) for decreasing the dimension of microarray data. Using this selective algorithm, we can solve the instability problem occurred in the case of employing conventional independent component analysis (ICA) methods. First, the reconstruction error and selective set are analyzed as independent components of each gene, which have a small part in making error in order to reconstruct new sample. Then, some of the modified support vector machine (υ-SVM) algorithm sub-classifiers are trained, simultaneously. Eventually, the best sub-classifier with the highest recognition rate is selected. The proposed algorithm is applied on three cancer datasets (leukemia, breast cancer and lung cancer datasets), and its results are compared with other existing methods. The results illustrate that the proposed algorithm (SICA + υ-SVM) has higher accuracy and validity in order to increase the classification accuracy. Such that, our proposed algorithm exhibits relative improvements of 3.3% in correctness rate over ICA + SVM and SVM algorithms in lung cancer dataset.

  2. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    PubMed

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  3. Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines.

    PubMed

    Zhang, Xiaohua; Wong, Sergio E; Lightstone, Felice C

    2013-04-30

    A mixed parallel scheme that combines message passing interface (MPI) and multithreading was implemented in the AutoDock Vina molecular docking program. The resulting program, named VinaLC, was tested on the petascale high performance computing (HPC) machines at Lawrence Livermore National Laboratory. To exploit the typical cluster-type supercomputers, thousands of docking calculations were dispatched by the master process to run simultaneously on thousands of slave processes, where each docking calculation takes one slave process on one node, and within the node each docking calculation runs via multithreading on multiple CPU cores and shared memory. Input and output of the program and the data handling within the program were carefully designed to deal with large databases and ultimately achieve HPC on a large number of CPU cores. Parallel performance analysis of the VinaLC program shows that the code scales up to more than 15K CPUs with a very low overhead cost of 3.94%. One million flexible compound docking calculations took only 1.4 h to finish on about 15K CPUs. The docking accuracy of VinaLC has been validated against the DUD data set by the re-docking of X-ray ligands and an enrichment study, 64.4% of the top scoring poses have RMSD values under 2.0 Å. The program has been demonstrated to have good enrichment performance on 70% of the targets in the DUD data set. An analysis of the enrichment factors calculated at various percentages of the screening database indicates VinaLC has very good early recovery of actives.

  4. Tribological and microstructural comparison of HIPped PM212 and PM212/Au self-lubricating composites

    NASA Technical Reports Server (NTRS)

    Bogdanski, Michael S.; Sliney, Harold E.; Dellacorte, Christopher

    1992-01-01

    The feasibility of replacing the silver with the volumetric equivalent of gold in the chromium carbide-based self-lubricating composite PM212 (70 wt. percent NiCo-Cr3C2, 15 percent BaF2/CaF2 eutectic) was studied. The new composite, PM212/Au has the following composition: 62 wt. percent NiCo-Cr3C2, 25 percent Au, 13 percent BaF2/CaF2 eutectic. The silver was replaced with gold to minimize the potential reactivity of the composite with possible environmental contaminants such as sulfur. The composites were fabricated by hot isostatic pressing (HIPping) and machined into pin specimens. The pins were slid against nickel-based superalloy disks. Sliding velocities ranged from 0.27 to 10.0 m/s and temperatures from 25 to 900 C. Friction coefficients ranged from 0.25 to 0.40 and wear factors for the pin and disk were typically low 10(exp -5) cu mm/N-m. HIPped PM212 measured fully dense, whereas PM212/Au had 15 percent residual porosity. Examination of the microstructures with optical and scanning electron microscopy revealed the presence of pores in PM212/Au that were not present in PM212. Though the exact reason for the residual porosity in PM212/Au was not determined, it may be due to particle morphology differences between the gold and silver and their effect on powder metallurgy processing.

  5. V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.

    PubMed

    Pian, Cong; Chen, Yuan-Yuan; Zhang, Jin; Chen, Zhi; Zhang, Guang-Le; Li, Qiang; Yang, Tao; Zhang, Liang-Yun

    2017-02-01

    Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this paper, we introduce a series of new features with 80 dimension called short sequence motifs (SSM). A hybrid feature vector with 1444 dimension can be formed by combining 1364 features of [Formula: see text]-mer strings and 80 features of SSM features. We optimize the 1444 dimension features using the feature score criterion (FSC) and list them in descending order according to the scores. The first 462 are selected as the input feature vector in the classifier. Moreover, eight of 80 SSM features appear in the top 20. This indicates that these eight SSM features play an important part in the identification of piRNAs. Since five of the above eight SSM features are associated with nucleotide A and G ('A*G', 'A**G', 'A***G', 'A****G', 'A*****G'). So, we guess there may exist some biological significance. We also use a neural network algorithm called voting-based extreme learning machine (V-ELM) to identify real piRNAs. The Specificity (Sp) and Sensitivity (Sn) of our method are 95.48% and 94.61%, respectively in human species. This result shows that our method is more effective compared with those of the piRPred, piRNApredictor, Asym-Pibomd, Piano and McRUMs. The web service of V-ELMpiRNAPred is available for free at http://mm20132014.wicp.net:38601/velmprepiRNA/Main.jsp .

  6. Insulin glargine and its two active metabolites: A sensitive (16pM) and robust simultaneous hybrid assay coupling immunoaffinity purification with LC-MS/MS to support biosimilar clinical studies.

    PubMed

    Xu, Yang; Sun, Li; Anderson, Melanie; Bélanger, Philippe; Trinh, Vincent; Lavallée, Patricia; Kantesaria, Bhavna; Marcoux, Marie-Josée; Breidinger, Sheila; Bateman, Kevin P; Goykhman, Dina; Woolf, Eric J

    2017-09-15

    MK-1293 is a newly approved follow-on/biosimilar insulin glargine for the treatment of Type 1 and Type 2 diabetics. To support pivotal clinical studies during biosimilar evaluation, a sensitive, specific and robust liquid chromatography and tandem mass spectrometry (LC-MS/MS) assay for the simultaneous quantification of glargine and its two active metabolites, M1 and M2 were developed. Strategies to overcome analytical challenges, so as to optimize assay sensitivity and improve ruggedness, were evolved, resulting in a fully validated LC-MS/MS method with a lower limit of quantification (LLOQ) at 0.1ng/mL (∼16pM, equivalent to ∼2.8μU/mL) for glargine, M1 and M2, respectively, using 0.5mL of human plasma. The assay employed hybrid methodology that combined immunoaffinity purification and reversed-phase chromatography followed by electrospray-MS/MS detection operated under positive ionization mode. Stable-isotope labeled 6[D10]Leu-glargine and 4[D10]Leu-M1 were used as internal standards. With a calibration range from 0.1 to 10ng/mL, the intra-run precision (n=5) and accuracy were <6.21%, and 96.9-102.1%, while the inter-run (n=5/run for 7days) precision and accuracy were <9.55% and 96.5-105.1%, respectively, for all 3 analytes. Matrix effect, recovery, analyte stability, and interferences from control matrix, potential concomitant medications and anti-drug antibody were assessed. The assay was fully automated and has been successfully used in support of biosimilar clinical studies. Greater than 94.3% of incurred sample reanalysis (ISR) results met acceptance criteria, demonstrating the robustness of the assay. The strategic considerations during method development and validation are discussed, and can be applied to quantification of other peptides, especially insulin analogs, in the future. Copyright © 2017. Published by Elsevier B.V.

  7. Tattoo machines, needles and utilities.

    PubMed

    Rosenkilde, Frank

    2015-01-01

    Starting out as a professional tattooist back in 1977 in Copenhagen, Denmark, Frank Rosenkilde has personally experienced the remarkable development of tattoo machines, needles and utilities: all the way from home-made equipment to industrial products of substantially improved quality. Machines can be constructed like the traditional dual-coil and single-coil machines or can be e-coil, rotary and hybrid machines, with the more convenient and precise rotary machines being the recent trend. This development has resulted in disposable needles and utilities. Newer machines are more easily kept clean and protected with foil to prevent crosscontaminations and infections. The machines and the tattooists' knowledge and awareness about prevention of infection have developed hand-in-hand. For decades, Frank Rosenkilde has been collecting tattoo machines. Part of his collection is presented here, supplemented by his personal notes. © 2015 S. Karger AG, Basel.

  8. Business Machines

    ERIC Educational Resources Information Center

    Pactor, Paul

    1970-01-01

    The U.S. Department of Labor has projected a 106 percent increase in the demand for office machine operators over the next 10 years. Machines with a high frequency of use include printing calculators, 10-key adding machines, and key punch machines. The 12th grade is the logical time for teaching business machines. (CH)

  9. A Search for Direct CP Violation in $K^{\\pm} \\to \\pi^{\\pm} \\pi^{\\pm} \\pi^{\\mp}$ Decays

    SciTech Connect

    Choong, Woon Seng

    2000-01-01

    An experimental search for CP violation in $K^{\\pm} \\to \\pi^{\\pm} \\pi^{\\pm} \\pi^{\\mp}$ decays has been performed in Experiment 871 at the Fermi National Accelerator Laboratory. The experiment used an 800 GeV/c primary proton beam impinging on copper targets to produce charged Kaons which were then collimated through a curved channel in a magnetic field. The three pions from the Kaon decays were tracked in the spectrometer with four high-rate multiwire proportional chambers upstream of an analysis magnet and four more downstream. The data was collected between April 1997 and September 1997, resulting in 43.3 billion positive and 18.8 billion negative Kaon triggers. Based on 41.8 million $\\tau^+$ decays and 12.4 million $\\tau^-$ decays of charged Kaon, the linear slope parameter $g$ describing the energy spectrum of the odd pion in the expansion of the squared matrix element was estimated using a Hybrid Monte Carlo method. This is the largest sample of $\\tau$ decays of charged Kaons ever analyzed, over an order of magnitude larger than the previous analysis. The asymmetry in the linear slope $g$ was found to be $\\frac{\\Delta g}{2g_{PDG}}$ = [2.2 $\\pm$ 1.5(stat) $\\pm$ 3.7(syst)] x $10^{-3}$ This result is consistent with no CP violation in $K^{\\pm} \\to \\pi^{\\pm} \\pi^{\\pm} \\pi^{\\mp}$ decays.

  10. A thermomechanical analysis of sticking-sliding zones at the tool-chip interface in dry high-speed machining of aluminium alloy A2024-T351: A hybrid Analytical-Fe model

    NASA Astrophysics Data System (ADS)

    Avevor, Y.; Moufki, A.; Nouari, M.

    2016-10-01

    In high speed dry machining of aluminium alloy (A2024-T351), the tribological conditions at the tool-chip interface strongly affect the thermomechanical process of chip formation, the tool wear and the surface integrity. In order to contribute to the understanding of the effect of friction conditions, a hybrid Analytical-FE model is presented. The transient nonlinear thermal problem in the tool-chip-workpiece system is solved by using a Petrov-Galerkin finite element model. To illustrate the model results, the relationship between the local friction coefficient, in the sliding zone, and the apparent friction coefficient, which takes into account the whole tool-chip contact, is presented.

  11. Machine Shop Grinding Machines.

    ERIC Educational Resources Information Center

    Dunn, James

    This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

  12. Simultaneous monitoring and compositions analysis of PM1 and PM2.5 in Shanghai: Implications for characterization of haze pollution and source apportionment.

    PubMed

    Qiao, Ting; Zhao, Mengfei; Xiu, Guangli; Yu, Jianzhen

    2016-07-01

    A year-long simultaneous observation of PM1 and PM2.5 were conducted at ECUST campus in Shanghai, the compositions were analyzed and compared. Results showed that PM2.5 was dominated by PM1 on clear days while the contribution of PM1-2.5 to PM2.5 increased on haze days, indicating that PM2.5 should be given priority to characterize or predict haze pollution. On haze days, accumulation of organic carbon (OC), elemental carbon (EC) and primary organic carbon (POC) in PM1-2.5 was faster than that in PM1. Humic-like substances carbon (Hulis-C) in both PM2.5 and PM1 formed faster than water soluble organic carbon (WSOC) on haze days, hence Hulis-C/WSOC increased with the intensification of haze pollution. In terms of water soluble ions, NO3(-)/SO4(2-) in PM1 increased with the aggravation of haze pollution, implying that mobile sources dominated on haze days, so is nitrogen oxidation ratio (NOR). Liquid water content (LWC) in both PM1 and PM2.5 had positive correlations with relative humidity (RH) but negative correlations with visibility, implying that hygroscopic growth might be a factor for visibility impairment, especially LWC in PM1. By comparison with multi-linear equations of LWC in PM1 and PM2.5, NO3(-) exerted a higher influence on hygroscopicity of PM1 than PM2.5, while RH, WSOC, SO4(2-) and NH4(+) had higher effects on PM2.5, especially WSOC. Source apportionment of PM2.5 was also investigated to provide reference for policy making. Cluster analysis by HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model showed that PM2.5 originated from marine aerosols, middle-scale transportation and large-scale transportation. Furthermore, PM2.5 on haze days was dominated by middle-scale transportation. In line with source apportionment by positive matrix factorization (PMF) model, PM2.5 was attributed to secondary inorganics, aged sea salt, combustion emissions, hygroscopic growth and secondary organics. Secondary formation was the principle source of

  13. COMPARISON OF PM 2.5 AND PM 10 MONITORS

    EPA Science Inventory

    An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. One goal was to investigate the mass concentration comparability between various monitoring instrumentation located across residential indoor, residential out...

  14. COMPARISON OF PM 2.5 AND PM 10 MONITORS

    EPA Science Inventory

    An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. One goal was to investigate the mass concentration comparability between various monitoring instrumentation located across residential indoor, residential out...

  15. Draft Analyses of PM Data for the PM NAAQS Review

    EPA Pesticide Factsheets

    These files document all analyses conducted in association with the EPA memorandum from Mark Schmidt, David Mintz, Tesh Rao, and Lance McCluney titled Draft Analyses of PM Data for the PM NAAQS Review, January 31, 2005.

  16. Analyses of 1999 PM Data for the PM NAAQS Review

    EPA Pesticide Factsheets

    These files document all analyses conducted in association with the EPA memorandum from Terence Fitz-Simons, Scott Mathias, and Mike Rizzo titled Analyses of 1999 PM Data for the PM NAAQS Review, November 17, 2000.

  17. Data on Support Vector Machines (SVM) model to forecast photovoltaic power.

    PubMed

    Malvoni, M; De Giorgi, M G; Congedo, P M

    2016-12-01

    The data concern the photovoltaic (PV) power, forecasted by a hybrid model that considers weather variations and applies a technique to reduce the input data size, as presented in the paper entitled "Photovoltaic forecast based on hybrid pca-lssvm using dimensionality reducted data" (M. Malvoni, M.G. De Giorgi, P.M. Congedo, 2015) [1]. The quadratic Renyi entropy criteria together with the principal component analysis (PCA) are applied to the Least Squares Support Vector Machines (LS-SVM) to predict the PV power in the day-ahead time frame. The data here shared represent the proposed approach results. Hourly PV power predictions for 1,3,6,12, 24 ahead hours and for different data reduction sizes are provided in Supplementary material.

  18. Database machines

    NASA Technical Reports Server (NTRS)

    Stiefel, M. L.

    1983-01-01

    The functions and performance characteristics of data base machines (DBM), including machines currently being studied in research laboratories and those currently offered on a commerical basis are discussed. The cost/benefit considerations that must be recognized in selecting a DBM are discussed, as well as the future outlook for such machines.

  19. Investigation into the Effect of Atmospheric Particulate Matter (PM2.5 and PM10) Concentrations on GPS Signals

    PubMed Central

    Lau, Lawrence; He, Jun

    2017-01-01

    The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM10. Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM2.5. GPS signals travel through the atmosphere before arriving at receivers on the Earth’s surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM2.5/PM10 particles? There is no standard model of the effect of PM2.5/PM10 particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM2.5/PM10 particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM2.5/PM10 particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements. PMID:28273798

  20. Investigation into the Effect of Atmospheric Particulate Matter (PM2.5 and PM10) Concentrations on GPS Signals.

    PubMed

    Lau, Lawrence; He, Jun

    2017-03-03

    The Global Positioning System (GPS) has been widely used in navigation, surveying, geophysical and geodynamic studies, machine guidance, etc. High-precision GPS applications such as geodetic surveying need millimeter and centimeter level accuracy. Since GPS signals are affected by atmospheric effects, methods of correcting or eliminating ionospheric and tropospheric bias are needed in GPS data processing. Relative positioning can be used to mitigate the atmospheric effect, but its efficiency depends on the baseline lengths. Air pollution is a serious problem globally, especially in developing countries that causes health problems to humans and damage to the ecosystem. Respirable suspended particles are coarse particles with a diameter of 10 micrometers or less, also known as PM10. Moreover, fine particles with a diameter of 2.5 micrometers or less are known as PM2.5. GPS signals travel through the atmosphere before arriving at receivers on the Earth's surface, and the research question posed in this paper is: are GPS signals affected by the increased concentration of the PM2.5/PM10 particles? There is no standard model of the effect of PM2.5/PM10 particles on GPS signals in GPS data processing, although an approximate generic model of non-gaseous atmospheric constituents (<1 mm) can be found in the literature. This paper investigates the effect of the concentration of PM2.5/PM10 particles on GPS signals and validates the aforementioned approximate model with a carrier-to-noise ratio (CNR)-based empirical method. Both the approximate model and the empirical results show that the atmospheric PM2.5/PM10 particles and their concentrations have a negligible effect on GPS signals and the effect is comparable with the noise level of GPS measurements.

  1. The Virtual PM

    DTIC Science & Technology

    2013-11-01

    00-2013 to 00-00-2013 4. TITLE AND SUBTITLE The Virtual PM 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d...PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Defense Acquisition University,Defense AT&L...9820 Belvoir Road,Fort Belvoir,VA,22060-5565 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME( S ) AND ADDRESS(ES) 10

  2. Design study and performance analysis of 12S-14P field excitation flux switching motor for hybrid electric vehicle

    NASA Astrophysics Data System (ADS)

    Husin, Zhafir Aizat; Sulaiman, Erwan; Khan, Faisal; Mazlan, Mohamed Mubin Aizat; Othman, Syed Muhammad Naufal Syed

    2015-05-01

    This paper presents a new structure of 12slot-14pole field excitation flux switching motor (FEFSM) as an alternative candidate of non-Permanent Magnet (PM) machine for HEV drives. Design study, performance analysis and optimization of field excitation flux switching machine with non-rare-earth magnet for hybrid electric vehicle drive applications is done. The stator of projected machine consists of iron core made of electromagnetic steels, armature coils and field excitation coils as the only field mmf source. The rotor is consisted of only stack of iron and hence, it is reliable and appropriate for high speed operation. The design target is a machine with the maximum torque, power and power density, more than 210Nm, 123kW and 3.5kW/kg, respectively, which competes with interior permanent magnet synchronous machine used in existing hybrid electric vehicle. Some design feasibility studies on FEFSM based on 2D-FEA and deterministic optimization method will be applied to design the proposed machine.

  3. Architecture of the type IVa pilus machine.

    PubMed

    Chang, Yi-Wei; Rettberg, Lee A; Treuner-Lange, Anke; Iwasa, Janet; Søgaard-Andersen, Lotte; Jensen, Grant J

    2016-03-11

    Type IVa pili are filamentous cell surface structures observed in many bacteria. They pull cells forward by extending, adhering to surfaces, and then retracting. We used cryo-electron tomography of intact Myxococcus xanthus cells to visualize type IVa pili and the protein machine that assembles and retracts them (the type IVa pilus machine, or T4PM) in situ, in both the piliated and nonpiliated states, at a resolution of 3 to 4 nanometers. We found that T4PM comprises an outer membrane pore, four interconnected ring structures in the periplasm and cytoplasm, a cytoplasmic disc and dome, and a periplasmic stem. By systematically imaging mutants lacking defined T4PM proteins or with individual proteins fused to tags, we mapped the locations of all 10 T4PM core components and the minor pilins, thereby providing insights into pilus assembly, structure, and function. Copyright © 2016, American Association for the Advancement of Science.

  4. Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

    NASA Astrophysics Data System (ADS)

    Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

    2007-06-01

    The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

  5. Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

    NASA Astrophysics Data System (ADS)

    Park, Seohui; Im, Jungho

    2017-04-01

    Atmospheric aerosols are strongly associated with adverse human health effects. In particular, particulate matter less than 10 micrometers and 2.5 micrometers (i.e., PM10 and PM2.5, respectively) can cause cardiovascular and lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Air quality including PM has typically been monitored using station-based in-situ measurements over the world. However, in situ measurements do not provide spatial continuity over large areas. An alternative approach is to use satellite remote sensing as it provides data over vast areas at high temporal resolution. The literature shows that PM concentrations are related with Aerosol Optical Depth (AOD) that is derived from satellite observations, but it is still difficult to identify PM concentrations directly from AOD. Some studies used statistical approaches for estimating PM concentrations from AOD while some others combined numerical models and satellite-derived AOD. In this study, satellite-derived products were used to estimate ground PM concentrations based on machine learning over South Korea. Satellite-derived products include AOD from Geostationary Ocean Color Imager (GOCI), precipitation from Tropical Rainfall Measuring Mission (TRMM), soil moisture from AMSR-2, elevation from Shuttle Radar Topography Mission (SRTM), and land cover, land surface temperature and normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS). PM concentrations data were collected from 318 stations. A statistical ordinary least squares (OLS) approach was also tested and compared with the machine learning approach (i.e., random forest). PM concentration was estimated during spring season (from March to May) in 2015 that typically shows high concentration of PM. The randomly selected 80% of data were used for model calibration and the remaining 20% were used for validation. The developed models were further tested for prediction of PM

  6. PM10, PM2.5 and PM1 distribution in Penang Island, Malaysia

    NASA Astrophysics Data System (ADS)

    Beh, B. C.; Tan, F.; Tan, C. H.; Syahreza, S.; Mat Jafri, M. Z.; Lim, H. S.

    2013-05-01

    Particulate Matter (PM) consist of tiny solid or liquid particles that floating freely in the air. PM10 refers to the particles which have size up to 10 microns (μm). The smaller the particle size (such as PM1), the more severe it will affect our human health if we inhaled too much into our lungs. In this paper, we used the DustTrack{trade mark, serif} Aerosol Monitor with Model 8520 to obtain the PM distribution (PM10, PM2.5 and PM1) in Penang Island. The in-situ measurement was taken on 10 August 2012 at Georgetown, Batu Ferringhi and Permatang Damar Laut open area. The data obtained was analyzed and interpreted. The results show that the dust level at Permatang Damar Laut was low as compare to the other two areas which are located in town area. The highest PM10, PM2.5 and PM1 dust level with an averaging time of 6 hours was observed at Batu Ferringhi with a reading of 200, 194 and 185μg/m3. This study can provide a guideline to detect and monitor the dust level at Penang Island. Further study can be done to monitor the temporal changes of air quality over Penang Island, Malaysia.

  7. New Levels of 157Pm

    NASA Astrophysics Data System (ADS)

    Ranger, J.; Wang, E. H.; Hamilton, J. H.; Ramayya, A. V.; Hwang, J. K.; Navin, A.; Rejmund, M.; Lemasson, A.; Bhattacharyya, S.; Luo, Y. X.; Rasmussen, J. O.; Zhu, S. J.; Ter-Akopian, G. M.; Oganessian, Yu.; Vanderbilt University Team; Ganil Team; Tsinghua University Team; Jinr Team; Lbnl Team

    2014-09-01

    Gamma rays in coincidence with isotopically-identified fission fragments using VAMOS++ and EXOGAM, produced using 238U on a 9Be target, at an energy around the Coulomb barrier have been reported. In the present work, we have combined data from the in-beam mass- and Z-gated spectra with the γ- γ- γ- γ data from 252Cf (SF) to assign transitions and levels in 157Pm. In contrast to Hwang, 2009, the transitions previously assigned to 156Pm are all seen in the M-Z gated spectra of 157Pm and are not seen in the M-Z gated spectra of 156Pm. The new expanded levels of 157Pm are remarkably similar to those of the levels in 155Pm, which have been assigned as a rotational band built on π 5 / 2 [532]. Gamma rays in coincidence with isotopically-identified fission fragments using VAMOS++ and EXOGAM, produced using 238U on a 9Be target, at an energy around the Coulomb barrier have been reported. In the present work, we have combined data from the in-beam mass- and Z-gated spectra with the γ- γ- γ- γ data from 252Cf (SF) to assign transitions and levels in 157Pm. In contrast to Hwang, 2009, the transitions previously assigned to 156Pm are all seen in the M-Z gated spectra of 157Pm and are not seen in the M-Z gated spectra of 156Pm. The new expanded levels of 157Pm are remarkably similar to those of the levels in 155Pm, which have been assigned as a rotational band built on π 5 / 2 [532]. Vanderbilt University Physics and Astronomy REU Program.

  8. Label-free and dual-amplified detection of protein via small molecule-ligand linked DNA and a cooperative DNA machine.

    PubMed

    Li, Pei; Wang, Lei; Zhu, Jing; Wu, Yushu; Jiang, Wei

    2015-10-15

    Sensitive detection of protein is essential for both molecular diagnostics and biomedical research. Here, taking folate receptor as the model analyte, we developed a label-free and dual-amplified strategy via small molecular-ligand linked DNA and a cooperative DNA machine which could perform primary amplification and mediate secondary amplification simultaneously. Firstly, the specific binding of folate receptor to the small-molecule folate which linked to a trigger DNA could protect the trigger DNA from exonuclease I digestion, translating folate receptor detection into trigger DNA detection. Subsequently, trigger DNA initiated the DNA machine through hybridizing with the hairpin of the DNA machine, resulting in hairpin conformational change and stem open. The open stem further hybridized with a primer which initiated circular strand-displacement polymerization reaction; meanwhile the rolling circle amplification templates which were initially blocked in the DNA machine were liberated to mediate rolling circle amplification. In such a working model, the DNA machine achieved cooperatively controlling circular strand-displacement polymerization reaction and rolling circle amplification, realizing dual-amplification. Finally, the rolling circle amplification process synthesized a long repeated G-quadruplex sequence, which strongly interacted with N-methyl mesoporphyrin IX, bringing label-free fluorescence signal. This strategy could detect folate receptor as low as 0.23 pM. A recovery over 90% was obtained when folate receptor was detected in spiked human serum, demonstrating the feasibility of this detection strategy in biological samples.

  9. A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China

    PubMed Central

    Wu, Jinran

    2017-01-01

    Air pollution in China is becoming more serious especially for the particular matter (PM) because of rapid economic growth and fast expansion of urbanization. To solve the growing environment problems, daily PM2.5 and PM10 concentration data form January 1, 2015, to August 23, 2016, in Kunming and Yuxi (two important cities in Yunnan Province, China) are used to present a new hybrid model CI-FPA-SVM to forecast air PM2.5 and PM10 concentration in this paper. The proposed model involves two parts. Firstly, due to its deficiency to assess the possible correlation between different variables, the cointegration theory is introduced to get the input-output relationship and then obtain the nonlinear dynamical system with support vector machine (SVM), in which the parameters c and g are optimized by flower pollination algorithm (FPA). Six benchmark models, including FPA-SVM, CI-SVM, CI-GA-SVM, CI-PSO-SVM, CI-FPA-NN, and multiple linear regression model, are considered to verify the superiority of the proposed hybrid model. The empirical study results demonstrate that the proposed model CI-FPA-SVM is remarkably superior to all considered benchmark models for its high prediction accuracy, and the application of the model for forecasting can give effective monitoring and management of further air quality. PMID:28932237

  10. Research on a new magnetic-field-modulated brushless double-rotor machine with sinusoidal-permeance modulating ring

    NASA Astrophysics Data System (ADS)

    Zheng, Ping; Liu, Jiaqi; Bai, Jingang; Song, Zhiyi; Liu, Yong

    2017-05-01

    The magnetic-field-modulated brushless double-rotor machine (MFM-BDRM), composed of a stator, a modulating ring rotor, and a PM rotor, is a kind of power-split device for hybrid electric vehicles (HEVs). In this paper, a new MFM-BDRM with sinusoidal-permeance modulating ring named Sinusoidal-Permeance-Modulating-Ring Brushless Double-Rotor Machine (SPMR-BDRM) is proposed to solve the problem of poor mechanical strength and large iron loss. The structure and the operating principle of the MFM-BDRM are introduced. The design principle of the sinusoidal-permeance modulating ring is analyzed and derived. The main idea of that is to minimize the harmonic permeance of air gap, thereby the harmonic magnetic fields can be restrained. There are comparisons between a MFM-BDRM with sinusoidal-permeance modulating ring and a same size MFM-BDRM with traditional modulating ring, including magnetic field distributions and electromagnetic performances. Most importantly, the iron losses are compared under six different conditions. The result indicates that the harmonic magnetic fields in the air gap are restrained; the electromagnetic torque and power factor are almost the same with same armature current; the torque ripples of the modulating ring rotor and the PM rotor are reduced; the stator loss is reduced by 13% at least and the PM loss is reduced by 20% at least compared with the same size traditional MFM-BDRM under the same operating conditions.

  11. Electric machine

    DOEpatents

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

    2012-07-17

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

  12. High speed operation of permanent magnet machines

    NASA Astrophysics Data System (ADS)

    El-Refaie, Ayman M.

    This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been

  13. New Levels in 157 Pm

    NASA Astrophysics Data System (ADS)

    Ranger, J.; Wang, E. H.; Hamilton, J. H.; Ramayya, A. V.; Hwang, J. K.; Navin, A.; Rejmund, M.; Lemasson, A.; Bhattacharyya, S.; Luo, Y. X.; Rasmussen, J. O.; Zhu, S. J.; Ter-Akopian, G. M.; Oganessian, Yu.

    2015-04-01

    Gamma rays in coincidence with isotopically-identified fission fragments using VAMOS++ and EXOGAM, produced using 238 U on a 9 Be target, at an energy near the Coulomb barrier have been observed, as reported by Navin et al.. In the present work, we have combined data from the in-beam mass- and Z-gated spectra with the γ- γ- γ- γ data from 252 Cf (SF) to assign transitions and levels in 157 Pm. In contrast to Hwang (2009), the transitions previously assigned to 156 Pm are all seen in the M-Z gated spectra of 157 Pm and are not seen in the M-Z gated spectra of 156 Pm. The new expanded levels of 157 Pm are remarkably similar to those of the levels in 155 Pm, which have been assigned as a well-deformed rotational band built on π 5/2 [2], as in 155 Pm. New level schemes in 147 Ce are also verified and elaborated upon. Part of Vanderbilt University Physics & Astronomy REU Program.

  14. Accelerated hybrid-circuit production

    NASA Technical Reports Server (NTRS)

    Berg, J. E.; Dassele, M. A.

    1979-01-01

    Modified die-bonding machine speeds up hybrid-circuit production. Utilizing two pedestals, one for die tray and another for substrate tray, increased production and decreased error-margin are possible.

  15. The Role of Reluctance in PM Motors

    SciTech Connect

    Otaduy, P.J.

    2005-06-16

    The international research community has lately focused efforts on interior permanent magnet (IPM) motors to produce a traction motor for hybrid electric vehicles (HEV). One of the beneficial features of this technology is the additional torque produced by reluctance. The objective of this report is to analytically describe the role that reluctance plays in permanent magnet (PM) motors, to explore ways to increase reluctance torque without sacrificing the torque produced by the PMs, and to compare three IPM configurations with respect to torque, power, amount of magnet material required (cost), and percentage of reluctance torque. Results of this study will be used to determine future research directions in utilizing reluctance to obtain maximum torque and power while using a minimum amount of magnet material.

  16. Monel Machining

    NASA Technical Reports Server (NTRS)

    1983-01-01

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

  17. Modular PM Motor Drives for Automotive Traction Applications

    SciTech Connect

    Su, G.J.

    2001-10-29

    This paper presents modular permanent magnet (PM) motor drives for automotive traction applications. A partially modularized drive system consisting of a single PM motor and multiple inverters is described. The motor has multiple three-phase stator winding sets and each winding set is driven with a separate three-phase inverter module. A truly modularized inverter and motor configuration based on an axial-gap PM motor is then introduced, in which identical PM motor modules are mounted on a common shaft and each motor module is powered by a separate inverter module. The advantages of the modular approach for both inverter and motor include: (1) power rating scalability--one design meets different power requirements by simply stacking an adequate number of modules, thus avoiding redesigning and reducing the development cost, (2) increased fault tolerance, and (3) easy repairing. A prototype was constructed by using two inverters and an axial-gap PM motor with two sets of three-phase stat or windings, and it is used to assist the diesel engine in a hybrid electric vehicle converted from a Chevrolet Suburban. The effect of different pulse-width-modulation strategies for both motoring and regenerative modes on current control is analyzed. Torque and regenerative control algorithms are implemented with a digital signal processor. Analytical and initial testing results are included in the paper.

  18. Advanced Propulsion Power Distribution System for Next Generation Electric/Hybrid Vehicle. Phase 1; Preliminary System Studies

    NASA Technical Reports Server (NTRS)

    Bose, Bimal K.; Kim, Min-Huei

    1995-01-01

    The report essentially summarizes the work performed in order to satisfy the above project objective. In the beginning, different energy storage devices, such as battery, flywheel and ultra capacitor are reviewed and compared, establishing the superiority of the battery. Then, the possible power sources, such as IC engine, diesel engine, gas turbine and fuel cell are reviewed and compared, and the superiority of IC engine has been established. Different types of machines for drive motor/engine generator, such as induction machine, PM synchronous machine and switched reluctance machine are compared, and the induction machine is established as the superior candidate. Similar discussion was made for power converters and devices. The Insulated Gate Bipolar Transistor (IGBT) appears to be the most superior device although Mercury Cadmium Telluride (MCT) shows future promise. Different types of candidate distribution systems with the possible combinations of power and energy sources have been discussed and the most viable system consisting of battery, IC engine and induction machine has been identified. Then, HFAC system has been compared with the DC system establishing the superiority of the former. The detailed component sizing calculations of HFAC and DC systems reinforce the superiority of the former. A preliminary control strategy has been developed for the candidate HFAC system. Finally, modeling and simulation study have been made to validate the system performance. The study in the report demonstrates the superiority of HFAC distribution system for next generation electric/hybrid vehicle.

  19. Indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations in primary schools in Sari, Iran.

    PubMed

    Mohammadyan, Mahmoud; Shabankhani, Bijan

    2013-09-01

    This study was carried out to determine the distribution of particles in classrooms in primary schools located in the centre of the city of Sari, Iran and identify the relationship between indoor classroom particle levels and outdoor PM2.5 concentrations. Outdoor PM2.5 and indoor PM1, PM2.5, and PM10 were monitored using a real-time Micro Dust Pro monitor and a GRIMM monitor, respectively. Both monitors were calibrated by gravimetric method using filters. The Kolmogorov-Smirnov test showed that all indoor and outdoor data fitted normal distribution. Mean indoor PM1, PM2.5, PM10 and outdoor PM2.5 concentrations for all of the classrooms were 17.6 μg m(-3), 46.6 μg m(-3), 400.9 μg m(-3), and 36.9 μg m(-3), respectively. The highest levels of indoor and outdoor PM2.5 concentrations were measured at the Shahed Boys School (69.1 μg m(-3) and 115.8 μg m(-3), respectively). The Kazemi school had the lowest levels of indoor and outdoor PM2.5 (29.1 μg m(-3) and 15.5 μg m(-3), respectively). In schools located near both main and small roads, the association between indoor fine particle (PM2.5 and PM1) and outdoor PM2.5 levels was stronger than that between indoor PM10 and outdoor PM2.5 levels. Mean indoor PM2.5 and PM10 and outdoor PM2.5 were higher than the standards for PM2.5 and PM10, and there was a good correlation between indoor and outdoor fine particle concentrations.

  20. Workout Machine

    NASA Technical Reports Server (NTRS)

    1995-01-01

    The Orbotron is a tri-axle exercise machine patterned after a NASA training simulator for astronaut orientation in the microgravity of space. It has three orbiting rings corresponding to roll, pitch and yaw. The user is in the middle of the inner ring with the stomach remaining in the center of all axes, eliminating dizziness. Human power starts the rings spinning, unlike the NASA air-powered system. Marketed by Fantasy Factory (formerly Orbotron, Inc.), the machine can improve aerobic capacity, strength and endurance in five to seven minute workouts.

  1. Machine rates for selected forest harvesting machines

    Treesearch

    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...

  2. Wacky Machines

    ERIC Educational Resources Information Center

    Fendrich, Jean

    2002-01-01

    Collectors everywhere know that local antique shops and flea markets are treasure troves just waiting to be plundered. Science teachers might take a hint from these hobbyists, for the next community yard sale might be a repository of old, quirky items that are just the things to get students thinking about simple machines. By introducing some…

  3. Wacky Machines

    ERIC Educational Resources Information Center

    Fendrich, Jean

    2002-01-01

    Collectors everywhere know that local antique shops and flea markets are treasure troves just waiting to be plundered. Science teachers might take a hint from these hobbyists, for the next community yard sale might be a repository of old, quirky items that are just the things to get students thinking about simple machines. By introducing some…

  4. A restriction enzyme-powered autonomous DNA walking machine: its application for a highly sensitive electrochemiluminescence assay of DNA.

    PubMed

    Chen, Ying; Xiang, Yun; Yuan, Ruo; Chai, Yaqin

    2015-01-21

    The construction of a restriction enzyme (Nt.AlwI)-powered DNA walking machine and its application for highly sensitive detection of DNA are described. DNA nanostructure tracks containing four overhang sequences with electrochemiluminescence (ECL) labels and complementary to the walker (target DNA) are self-assembled on the sensing electrode. The walker hybridizes with the complementary sequences on the tracks and forms specific recognition sites for Nt.AlwI, which cleaves the overhang sequences, releases the ECL labels and enables directional movement of the walker along the tracks. The formation of the nanostructure tracks and the Nt.AlwI-assisted cleavage of the overhang sequences in the presence of the walker are verified by using polyacrylamide gel electrophoresis analysis and cyclic voltammetry. The successive movement of the walker on the nanostructure tracks leads to continuous removal of massive ECL labels from the sensing electrode, which results in a significantly amplified suppression of the ECL emission for highly sensitive detection of sequence-specific DNA down to 0.19 pM. Results show that this DNA walking machine can also offer single-base mismatch discrimination capability. The successful application of the DNA walking machine for sequence-specific DNA detection can thus offer new opportunities for molecular machines in biosensing applications.

  5. Drilling Machines: Vocational Machine Shop.

    ERIC Educational Resources Information Center

    Thomas, John C.

    The lessons and supportive information in this field tested instructional block provide a guide for teachers in developing a machine shop course of study in drilling. The document is comprised of operation sheets, information sheets, and transparency masters for 23 lessons. Each lesson plan includes a performance objective, material and tools,…

  6. Machine Learning

    NASA Astrophysics Data System (ADS)

    Hoffmann, Achim; Mahidadia, Ashesh

    The purpose of this chapter is to present fundamental ideas and techniques of machine learning suitable for the field of this book, i.e., for automated scientific discovery. The chapter focuses on those symbolic machine learning methods, which produce results that are suitable to be interpreted and understood by humans. This is particularly important in the context of automated scientific discovery as the scientific theories to be produced by machines are usually meant to be interpreted by humans. This chapter contains some of the most influential ideas and concepts in machine learning research to give the reader a basic insight into the field. After the introduction in Sect. 1, general ideas of how learning problems can be framed are given in Sect. 2. The section provides useful perspectives to better understand what learning algorithms actually do. Section 3 presents the Version space model which is an early learning algorithm as well as a conceptual framework, that provides important insight into the general mechanisms behind most learning algorithms. In section 4, a family of learning algorithms, the AQ family for learning classification rules is presented. The AQ family belongs to the early approaches in machine learning. The next, Sect. 5 presents the basic principles of decision tree learners. Decision tree learners belong to the most influential class of inductive learning algorithms today. Finally, a more recent group of learning systems are presented in Sect. 6, which learn relational concepts within the framework of logic programming. This is a particularly interesting group of learning systems since the framework allows also to incorporate background knowledge which may assist in generalisation. Section 7 discusses Association Rules - a technique that comes from the related field of Data mining. Section 8 presents the basic idea of the Naive Bayesian Classifier. While this is a very popular learning technique, the learning result is not well suited for

  7. Case study of PM pollution in playgrounds in Istanbul

    NASA Astrophysics Data System (ADS)

    Ozdemir, Huseyin; Mertoglu, Bulent; Demir, Goksel; Deniz, Ali; Toros, Hüseyin

    2012-05-01

    In a world where at least 50% of the population is living in urban environments, air pollution and specifically particulate matter (PM) have become one of the most critical issues for human health. Children are more susceptible than adults to air pollution and its adverse effects because they inhale and retain larger amounts of air pollutants per unit of body weight. In this study, PM pollution, particularly PM10 and PM2.5, at selected playgrounds were investigated in Istanbul city. Istanbul is a megacity of over 15 million inhabitants, and on-road traffic is increasing rapidly (over 3 million vehicles on the road). To estimate the effect of traffic emissions on children, the location of the playgrounds were selected according to traffic density. Measurements were carried out at five different playgrounds throughout the city in 2009. Field results show that the values of PM10 and PM2.5 have reached critical limits at the playgrounds close to the main roads, especially at P-1. Thus, we focused on this location and investigated a source other than traffic emissions. One of the episode days has been observed on 5-7 March 2009. Evaluations of meteorological events are very important to determine air pollution sources and their long-range transport. Therefore, the Weather Research and Forecasting model (WRF) was used to simulate and forecast meteorological parameters and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) applied to investigate long-range transport. According to the WRF model outputs, there was a low-pressure system over Geneva gulf on the 500-hPa level, and its core had been located over Britain on 5 March 2009 00UTC. The system had been sweeping dust from the Sahara Desert and carrying the air particles over Istanbul. Similarly, backward HYSPLIT analysis showed that air particles had moved through Istanbul from Northern Africa.

  8. PM levels in urban area of Bejaia

    NASA Astrophysics Data System (ADS)

    Benaissa, Fatima; Maesano, Cara Nichole; Alkama, Rezak; Annesi-Maesano, Isabella

    2017-04-01

    Air pollution is not routinely measured in Bejaia City, Algeria, an urban area of around 200,000 inhabitants. We present first time measurements of particulate matter (PM) mass concentrations for this city (PM10, PM7, PM4, PM2.5 and PM1) over the course of one week, from July 8 to July 14, 2015. This study covered eight urban sampling sites and 169 measurements were obtained to determine mass concentration levels. Air pollution is not routinely measured in Bejaia City, Algeria, an urban area of around 200,000 inhabitants. We present first time measurements of particulate matter (PM) mass concentrations for this city (PM10, PM7, PM4, PM2.5 and PM1) over the course of one week, from July 8 to July 14, 2015. This study covered eight urban sampling sites and 169 measurements were obtained to determine mass concentration levels. The average city-wide PM10 and PM2.5 concentrations measured during this sampling were 87.8 ± 33.9 and 28.7 ± 10.6 µg/m3 respectively. These results show that particulate matter levels are high and exceed Algerian ambient air quality standards (maximum 80 µg/m3, without specifying the particle size). Further, PM10 and PM2.5 averages were well above the prescribed 24-hour average World Health Organization Air Quality Guidelines (WHO AQG) (50 µg/m3 for PM10 and 25 µg/m3 for PM2.5). The PM1, PM2,5, PM4 and PM7 fractions accounted for 15%, 32 %, 56% and 78% respectively of the PM10 measurements. Our analysis reveals that PM concentration variations in the study region were influenced primarily by traffic. In fact, lower PM10 concentrations (21.7 and 33.1 µg/m3) were recorded in residential sites while higher values (53.1, and 45.2 µg/m3) were registered in city centers. Keywords: Particulate matter, Urban area, vehicle fleet, Bejaia.

  9. Implementing the PM Programming Language using MPI and OpenMP - a New Tool for Programming Geophysical Models on Parallel Systems

    NASA Astrophysics Data System (ADS)

    Bellerby, Tim

    2015-04-01

    ) or tasks are divided out among the available processors (number of tasks > number of processors). Nested parallel statements may further subdivide the processor set owned by a given task. Tasks or processors are distributed evenly by default, but uneven distributions are possible under programmer control. It is also possible to explicitly enable child tasks to migrate within the processor set owned by their parent task, reducing load unbalancing at the potential cost of increased inter-processor message traffic. PM incorporates some programming structures from the earlier MIST language presented at a previous EGU General Assembly, while adopting a significantly different underlying parallelisation model and type system. PM code is available at www.pm-lang.org under an unrestrictive MIT license. Reference Ruymán Reyes, Antonio J. Dorta, Francisco Almeida, Francisco de Sande, 2009. Automatic Hybrid MPI+OpenMP Code Generation with llc, Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science Volume 5759, 185-195

  10. Fullerene Machines

    NASA Technical Reports Server (NTRS)

    Globus, Al; Saini, Subhash

    1998-01-01

    Recent computational efforts at NASA Ames Research Center and computation and experiment elsewhere suggest that a nanotechnology of machine phase functionalized fullerenes may be synthetically accessible and of great interest. We have computationally demonstrated that molecular gears fashioned from (14,0) single-walled carbon nanotubes and benzyne teeth should operate well at 50-100 gigahertz. Preliminary results suggest that these gears can be cooled by a helium atmosphere and a laser motor can power fullerene gears if a positive and negative charge have been added to form a dipole. In addition, we have unproven concepts based on experimental and computational evidence for support structures, computer control, a system architecture, a variety of components, and manufacture. Combining fullerene machines with the remarkable mechanical properties of carbon nanotubes, there is some reason to believe that a focused effort to develop fullerene nanotechnology could yield materials with tremendous properties.

  11. Fullerene Machines

    NASA Technical Reports Server (NTRS)

    Globus, Al; Saini, Subhash (Technical Monitor)

    1998-01-01

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

  12. Charging machine

    DOEpatents

    Medlin, John B.

    1976-05-25

    A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine.

  13. Induction machine

    SciTech Connect

    Owen, W.H.

    1980-10-14

    A polyphase rotary induction machine for use as a motor or generator utilizes, a single rotor assembly having two series connected sets of rotor windings, a first stator winding disposed around the first rotor winding and means for controlling the current induced in one set of the rotor windings compared to the current induced in the other set of the rotor windings. The rotor windings may be wound rotor windings or squirrel cage windings.

  14. Induction machine

    DOEpatents

    Owen, Whitney H.

    1980-01-01

    A polyphase rotary induction machine for use as a motor or generator utilizing a single rotor assembly having two series connected sets of rotor windings, a first stator winding disposed around the first rotor winding and means for controlling the current induced in one set of the rotor windings compared to the current induced in the other set of the rotor windings. The rotor windings may be wound rotor windings or squirrel cage windings.

  15. Machine vision

    SciTech Connect

    Horn, D.

    1989-06-01

    To keep up with the speeds of modern production lines, most machine vision applications require very powerful computers (often parallel-processing machines), which process millions of points of data in real time. The human brain performs approximately 100 billion logical floating-point operations each second. That is 400 times the speed of a Cray-1 supercomputer. The right software must be developed for parallel-processing computers. The NSF has awarded Rensselaer Polytechnic Institute (Troy, N.Y.) a $2 million grant for parallel- and image-processing software research. Over the last 15 years, Rensselaer has been conducting image-processing research, including work with high-definition TV (HDTV) and image coding and understanding. A similar NSF grant has been awarded to Michigan State University (East Lansing, Mich.) Neural networks are supposed to emulate human learning patterns. These networks and their hardware implementations (neurocomputers) show a great deal of promise for machine vision systems because they allow the systems to understand the use sensory data input more effectively. Neurocomputers excel at pattern-recognition tasks when input data are fuzzy or the vision algorithm is not optimal and is difficult to ascertain.

  16. Viruses: sophisticated biological machines.

    PubMed

    Rossmann, Michael G; Rao, Venigalla B

    2012-01-01

    Virus infection involves coordination of a series of molecular machines, including entry machines, replication machines, assembly machines, and genome packaging machines, leading to the production of infectious virions. This chapter provides an introduction to various viral molecular machines described in this book.

  17. A Double-Sided Linear Primary Permanent Magnet Vernier Machine

    PubMed Central

    2015-01-01

    The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed. PMID:25874250

  18. A double-sided linear primary permanent magnet vernier machine.

    PubMed

    Du, Yi; Zou, Chunhua; Liu, Xianxing

    2015-01-01

    The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

  19. Ada Compiler Validation Summary Report: Certificate Number: 940325S1. 11352 DDC-I DACS Sun SPARC/Solaries to Pentium PM Bare Ada Cross Compiler System, Version 4.6.4 Sun SPARCclassic => Intel Pentium (Operated as Bare Machine) Based in Xpress Desktop (Intel Product Number: XBASE6E4F-B)

    DTIC Science & Technology

    1994-03-25

    Intel Pentium (operated as Bare Machine) based in Xpres Desktop (Intel product nmber: XAS624F-B) See section 3.1 for any additional information about...operated as Bare Machine) based in Xpress Desktop (Intel product number: XBASE6E4F-B) See section 3.1 for any additional information about the testing...Information Systems Manager, Software Standards Engineering Division (ISED) Validation Group Computer Systems Laboratory (CSL) National Institute of

  20. PM Signals Warfare Contract Opportunities

    DTIC Science & Technology

    2002-05-06

    06MAY2002 - 07MAY2002 Title and Subtitle PM Signals Warfare Contract Opportunities Contract Number Grant Number Program Element Number Author(s...The Future” • Full ISR Wartime Capability • Support OOTW, Counter Narcotic, and Emergency /Natural Disaster Operations • FLIR, IRLS, DIS, MTI/SAR and...ACS Contract Opportunities 3/29/02 Aerial Common Sensor • Objective: Develop, Produce, and Field the Army’s Objective ISR System • Contract Type: CAD

  1. PM Program Prevents Early AM Repairs

    ERIC Educational Resources Information Center

    McRae, David

    1974-01-01

    Discusses how to initiate a preventive maintenance (PM) program: (1) make inventory of equipment that needs a PM program; (2) gather data about each piece of equipment; and (3) set maintenance goals. (Author/PG)

  2. Open burning and open detonation PM10 mass emission factor measurements with optical remote sensing.

    PubMed

    Yuen, Wangki; Johnsen, David L; Koloutsou-Vakakis, Sotiria; Rood, Mark J; Kim, Byung J; Kemme, Michael R

    2014-02-01

    Emission factors (EFs) of particulate matter with aerodynamic diameter <10 microm (PM10) from the open burning/open detonation (OB/OD) of energetic materials were measured using a hybrid-optical remote sensing (hybrid-ORS) method. This method is based on the measurement of range-resolved PM backscattering values with a micropulse light detection and ranging (LIDAR; MPL) device. Field measurements were completed during March 2010 at Tooele Army Depot, Utah, which is an arid continental site. PM10 EFs were quantified for OB of M1 propellant and OD of 2,4,6-trinitrotoluene (TNT). EFs from this study are compared with previous OB/OD measurements reported in the literature that have been determined with point measurements either in enclosed or ambient environments, and with concurrent airborne point measurements. PM10 mass EFs, determined with the hybrid-ORS method, were 7.8 x 10(-3) kg PM10/kg M1 from OB of M1 propellant, and 0.20 kg PM10/kg TNT from OD of TNT. Compared with previous results reported in the literature, the hybrid-ORS method EFs were 13% larger for OB and 174% larger for OD. Compared with the concurrent airborne measurements, EF values from the hybrid-ORS method were 37% larger for OB and 54% larger for OD. For TNT, no statistically significant differences were observed for the EFs measured during the detonation of 22.7 and 45.4 kg of TNT, supporting that the total amount of detonated mass in this mass range does not have an effect on the EFs for OD of TNT.

  3. Anti-scratching behavioral effect of Lactobacillus plantarum PM008 isolated from kimchi in mice.

    PubMed

    Jang, Se-Eun; Hyun, Yang-Jin; Trinh, Hien-Trung; Han, Myung Joo; Kim, Dong-Hyun

    2011-09-01

    To isolate antipruritic lactic acid bacteria (LAB) from kimchi, a traditional Korean food, we investigated the interleukin (IL)-4 production-inhibitory effect in the colon of mice for previously isolated LAB. Orally administered Lactobacillus plantarum PM008 potently inhibited the expression of IgE-switching cytokine, IL-4, and of proinflammatory cytokines, IL-1β and TNF-α, in the colon of mice. Its inhibitory effect was dependent on the dosage and administration period. When PM008 was orally administered to mice, the number of PM008 detected in the intestine and feces by polymerase chain reaction (PCR) and fluorescence in situ hybridization (FISH) methods was dependent on the administration dosage and period. The number of PM008 attached in the intestine was gradually decreased with increasing time after completion of its oral administration. PM008 dose-dependently inhibited the scratching behavior induced by histamine or compound 48/80. PM008 treated at a dose of 1 × 10(10) CFU for 14 days inhibited the histamine- and compound 48/80-induced scratching behaviors by 32.8% and 48.6%, respectively. This inhibitory effect continued, although reduced, at 7 days after stopping the oral administration of PM008 attached in the intestine. Based on these findings, L. plantarum PM008 may improve pruritus by inhibiting IL-4 expression.

  4. An Experimental LISP Machine

    NASA Astrophysics Data System (ADS)

    Lun, Wang

    1987-04-01

    This paper presents a multi-microprocessor LISP machine whose goal is to exploit the inherent parallelism in the LISP programs fully. The base architecture is a MIMD architecture based on a hybrid model for combinating data driven, demand driven and VoN Neumann process schemes. The basic evaluation strategy is data driven. Lazy evaluation mechanism is introduced to avoid unnecessary and unsafe computations. An experimental system with the four processor elements has been built in HIT, China. The system consists of a Z80 microcomputer and three TP8O1s interconnected through three buses. Each processor evaluates a part of programs asynchronously. The shared memory is divided into two parts: list cell area and enviroment area, each of which has the indepen-dent common bus to avoid the bus bottleneck.

  5. TEMPO machine

    SciTech Connect

    Rohwein, G.J.; Lancaster, K.T.; Lawson, R.N.

    1986-06-01

    TEMPO is a transformer powered megavolt pulse generator with an output pulse of 100 ns duration. The machine was designed for burst mode operation at pulse repetition rates up to 10 Hz with minimum pulse-to-pulse voltage variations. To meet the requirement for pulse duration a nd a 20-..omega.. output impedance within reasonable size constraints, the pulse forming transmission line was designed as two parallel water-insulated, strip-type Blumleins. Stray capacitance and electric fields along the edges of the line elements were controlled by lining the tank with plastic sheet.

  6. NodePM: a remote monitoring alert system for energy consumption using probabilistic techniques.

    PubMed

    Filho, Geraldo P R; Ueyama, Jó; Villas, Leandro A; Pinto, Alex R; Gonçalves, Vinícius P; Pessin, Gustavo; Pazzi, Richard W; Braun, Torsten

    2014-01-06

    In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

  7. NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

    PubMed Central

    Filho, Geraldo P. R.; Ueyama, Jó; Villas, Leandro A.; Pinto, Alex R.; Gonçalves, Vinícius P.; Pessin, Gustavo; Pazzi, Richard W.; Braun, Torsten

    2014-01-01

    In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out. PMID:24399157

  8. Vibration-assisted machining of single crystal

    NASA Astrophysics Data System (ADS)

    Zahedi, S. A.; Roy, A.; Silberschmidt, V. V.

    2013-07-01

    Vibration-assisted machining offers a solution to expanding needs for improved machining, especially where accuracy and precision are of importance, such as in micromachining of single crystals of metals and alloys. Crystallographic anisotropy plays a crucial role in determining on overall response to machining. In this study, we intend to address the matter of ultra-precision machining of material at the micron scale using computational modelling. A hybrid modelling approach is implemented that combines two discrete schemes: smoothed particle hydrodynamics and continuum finite elements. The model is implemented in a commercial software ABAQUS/Explicit employing a user-defined subroutine (VUMAT) and used to elucidate the effect of crystallographic anisotropy on a response of face centred cubic (f.c.c.) metals to machining.

  9. Interaction with Machine Improvisation

    NASA Astrophysics Data System (ADS)

    Assayag, Gerard; Bloch, George; Cont, Arshia; Dubnov, Shlomo

    We describe two multi-agent architectures for an improvisation oriented musician-machine interaction systems that learn in real time from human performers. The improvisation kernel is based on sequence modeling and statistical learning. We present two frameworks of interaction with this kernel. In the first, the stylistic interaction is guided by a human operator in front of an interactive computer environment. In the second framework, the stylistic interaction is delegated to machine intelligence and therefore, knowledge propagation and decision are taken care of by the computer alone. The first framework involves a hybrid architecture using two popular composition/performance environments, Max and OpenMusic, that are put to work and communicate together, each one handling the process at a different time/memory scale. The second framework shares the same representational schemes with the first but uses an Active Learning architecture based on collaborative, competitive and memory-based learning to handle stylistic interactions. Both systems are capable of processing real-time audio/video as well as MIDI. After discussing the general cognitive background of improvisation practices, the statistical modelling tools and the concurrent agent architecture are presented. Then, an Active Learning scheme is described and considered in terms of using different improvisation regimes for improvisation planning. Finally, we provide more details about the different system implementations and describe several performances with the system.

  10. Direct control of air gap flux in permanent magnet machines

    DOEpatents

    Hsu, John S.

    2000-01-01

    A method and apparatus for field weakening in PM machines uses field weakening coils (35, 44, 45, 71, 72) to produce flux in one or more stators (34, 49, 63, 64), including a flux which counters flux normally produced in air gaps between the stator(s) (34, 49, 63, 64) and the rotor (20, 21, 41, 61) which carries the PM poles. Several modes of operation are introduced depending on the magnitude and polarity of current in the field weakening coils (35, 44, 45, 71, 72). The invention is particularly useful for, but not limited to, the electric vehicle drives and PM generators.

  11. 75 FR 44142 - Determination of Attainment for PM-10; Fort Hall PM-10 Nonattainment Area, Idaho

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-28

    ... AGENCY 40 CFR Part 81 Determination of Attainment for PM-10; Fort Hall PM-10 Nonattainment Area, Idaho... determination that the Fort Hall PM-10 nonattainment area on the Fort Hall Indian Reservation in Idaho has... less than or equal to 10 microns (PM-10) under the ] Clean Air Act. EPA's final determination that...

  12. PREDICTING POPULATION EXPOSURES TO PM10 AND PM 2.5

    EPA Science Inventory

    An improved model for human exposure to particulate matter (PM), specifically PM10 and PM2.5 is under development by the U.S. EPA/NERL. This model will incorporate data from new PM exposure measurement and exposure factors research. It is intended to be used to predict exposure...

  13. CARDIOVASCULAR MORTALITY IN PHOENIX: PM1 IS A BETTER INDICATOR THAN PM2.5.

    EPA Science Inventory

    EPA has obtained a 3-year database of particulate matter (PM) in Phoenix, AZ from 1995 - 1997 that includes elemental analysis by XRF of daily PM2.5. During this time period PM1 and PM2.5 TEOMs were run simultaneously for about 7 months during two periods of the year. Regressio...

  14. Parallel machines: Parallel machine languages

    SciTech Connect

    Iannucci, R.A. )

    1990-01-01

    This book presents a framework for understanding the tradeoffs between the conventional view and the dataflow view with the objective of discovering the critical hardware structures which must be present in any scalable, general-purpose parallel computer to effectively tolerate latency and synchronization costs. The author presents an approach to scalable general purpose parallel computation. Linguistic Concerns, Compiling Issues, Intermediate Language Issues, and hardware/technological constraints are presented as a combined approach to architectural Develoement. This book presents the notion of a parallel machine language.

  15. Mining machine

    SciTech Connect

    Becker, H.R.

    1984-12-04

    A mining machine is disclosed comprising a mobile base and a cutting head assembly at a forward end of the mobile base having a cutter drum rotatable about an output shaft disposed along the longitudinal axis of the cutter drum. A drive system for the cutting head assembly comprises at least one motor for driving at least one toothed motor pinion and a generally cylindrical combination gear having generally circular end surfaces. A bevel or face gear is formed in at least one of the end surfaces, having teeth adapted to mate with and be driven by the toothed motor pinion. The combination gear has a worm gear formed in the outside cylindrical surface, which is disposed in driving engagement with the teeth of an output gear integrally and coaxially connected to the output shaft of the cutter drum.

  16. A dual-channel flux-switching permanent magnet motor for hybrid electric vehicles

    NASA Astrophysics Data System (ADS)

    Hua, Wei; Wu, Zhongze; Cheng, Ming; Wang, Baoan; Zhang, Jianzhong; Zhou, Shigui

    2012-04-01

    The flux-switching permanent magnet (FSPM) motor is a relatively novel brushless machine having both magnets and concentrated windings in the stator, which exhibits inherently sinusoidal PM flux-linkage, back-EMF waveforms, and high torque capability. However, in the application of hybrid electric vehicles, it is essential to prevent magnets and armature windings moving in radial direction due to the possible vibration during operation, and to ensure fault-tolerant capability. Hence, in this paper based on an original FSPM motor, a dual-channel FSPM (DC-FSPM) motor with modified structure to fix both armature windings and magnets and improved reliability is proposed for a practical 10 kW integral starter/generator (ISG) in hybrid electric vehicles. The influences of different solutions and the end-effect on the static characteristics, are evaluated based on the 2D and 3D finite element analysis, respectively. Finally, both the predicted and experimental results, compared with a prototype DC-FSPM motor and an interior PM motor used in Honda Civic, confirm that the more sinusoidal back-EMF waveform and lower torque ripple can be achieved in the DC-FSPM motor, whereas the torque is smaller under the same coil current.

  17. A MOOC on Approaches to Machine Translation

    ERIC Educational Resources Information Center

    Costa-jussà, Mart R.; Formiga, Lluís; Torrillas, Oriol; Petit, Jordi; Fonollosa, José A. R.

    2015-01-01

    This paper describes the design, development, and analysis of a MOOC entitled "Approaches to Machine Translation: Rule-based, statistical and hybrid", and provides lessons learned and conclusions to be taken into account in the future. The course was developed within the Canvas platform, used by recognized European universities. It…

  18. Diagnostics for hybrid reactors

    SciTech Connect

    Orsitto, Francesco Paolo

    2012-06-19

    The Hybrid Reactor(HR) can be considered an attractive actinide-burner or a fusion assisted transmutation for destruction of transuranic(TRU) nuclear waste. The hybrid reactor has two important subsystems: the tokamak neutron source and the blanket which includes a fuel zone where the TRU are placed and a tritium breeding zone. The diagnostic system for a HR must be as simple and robust as possible to monitor and control the plasma scenario, guarantee the protection of the machine and monitor the transmutation.

  19. Diagnostics for hybrid reactors

    NASA Astrophysics Data System (ADS)

    Orsitto, Francesco Paolo

    2012-06-01

    The Hybrid Reactor(HR) can be considered an attractive actinide-burner or a fusion assisted transmutation for destruction of transuranic(TRU) nuclear waste. The hybrid reactor has two important subsystems: the tokamak neutron source and the blanket which includes a fuel zone where the TRU are placed and a tritium breeding zone. The diagnostic system for a HR must be as simple and robust as possible to monitor and control the plasma scenario, guarantee the protection of the machine and monitor the transmutation.

  20. Ada Compiler Validation Summary Report: Certificate Number: 940325S1. 11353 DDC-I, DACS Sun SPARC/Solaris to Pentium PM Bare Ada Cross Compiler System with Rate Monotonic Scheduling, Version 4.6.4 Sun SPARCclassic => Intel Pentium (operated as Bare Machine) based in Xpress Desktop (Intel product number: XBASE6E4F-B)

    DTIC Science & Technology

    1994-04-11

    Sun SPARC/Solaris to Pentium PM Bare Ada Cross Compiler System with Rate Monotonic Scheduling, Version 4.6.4 6. iAutnors: National Institute of...ýdistribution unlimitedJ 13. (Maghmum 200 Host: Sun SPARClassic (under-Solaris, Release 2.1) Target: Intel Xpress Desktop (product number XBASE6E4F-B, with...Ada implementation was tested and determined to pass ACVC 1.11. Testing was completed on March 25, 1994. Compiler Name and Version: DACS Sun SPARC

  1. A Machine Approach for Field Weakening of Permanent-Magnet Motors

    SciTech Connect

    Hsu, J.S.

    2000-04-02

    The commonly known technology of field weakening for permanent-magnet (PM) motors is achieved by controlling the direct-axis current component through an inverter, without using mechanical variation of the air gap, a new machine approach for field weakening of PM machines by direct control of air-gap fluxes is introduced. The demagnetization situation due to field weakening is not an issue with this new method. In fact, the PMs are strengthened at field weakening. The field-weakening ratio can reach 1O:1 or higher. This technology is particularly useful for the PM generators and electric vehicle drives.

  2. DNA probe attachment on plastic surfaces and microfluidic hybridization array channel devices with sample oscillation.

    PubMed

    Liu, Yingjie; Rauch, Cory B

    2003-06-01

    DNA probe immobilization on plastic surfaces and device assembly are both critical to the fabrication of microfluidic hybridization array channel (MHAC) devices. Three oligonucleotide (oligo) probe immobilization procedures were investigated for attaching oligo probes on four different types of plastic surfaces (polystyrene, polycarbonate, poly(methylmethacrylate), and polypropylene). These procedures are the Surmodics procedure, the cetyltrimethylammonium bromide (CTAB) procedure, and the Reacti-Bind procedure. To determine the optimal plastic substrate and attachment chemistry for array fabrication, we investigated plastic hydrophobicity, intrinsic fluorescence, and oligo attachment efficiency. The Reacti-Bind procedure is least effective for attaching oligo probes in the microarray format. The CTAB procedure performs well enough to use in array fabrication, and the concentration of CTAB has a significant effect on oligo immobilization efficiency. We also found that use of amine-modified oligo probes resulted in better immobilization efficiency than use of unmodified oligos with the CTAB procedure. The oligo probe immobilization on plastic surfaces by the Surmodics procedure is the most effective with regard to probe spot quality and hybridization sensitivity. A DNA hybridization assay on such a device results in a limit of detection of 12pM. Utilizing a CO(2) IR laser machining and adhesive layer approach, we have developed an improved procedure for realizing a DNA microarray inside a microfluidic channel. This device fabrication procedure allows for more feasible spot placement in the channel and reduced sample adsorption by adhesive tapes used in the fabrication procedure. We also demonstrated improved hybridization kinetics and increased detection sensitivity in MHAC devices by implementing sample oscillation inside the channel. A limit of detection of 5pM has been achieved in MHAC devices with sample oscillation.

  3. Label-free colorimetric detection of cancer related gene based on two-step amplification of molecular machine.

    PubMed

    Xu, Huo; Wu, Dong; Li, Chen-Qiao; Lu, Zheng; Liao, Xiao-Yun; Huang, Jie; Wu, Zai-Sheng

    2017-04-15

    Highly sensitive detection of K-ras gene is of great significance in biomedical research and clinical diagnosis. Here, we developed a colorimetric biosensing system for the detection of proto-oncogene K-ras based on enhanced amplification effect of DNA molecular machine, where dual isothermal circular strand-displacement amplification (D-SDA) occurs on two arms in one-to-one correspondence. Specifically, we designed a primer-locked hairpin probe (HP) and a primer-contained linear polymerization template (PPT). In the presence of target gene, HP can hybridize with PPT, forming a DNA molecular machine with dual functional arms (called DFA-machine). Each of the two probes in this machine is able to be extended by polymerase on its counterpart species. Moreover, with the help of nicking endonuclease, the dual isothermal polymerization is converted into dual circular strand-displacement amplification, generating a large amount of anti-hemin aptamer-contained products. After binding to hemins, the aptamer/hemin duplex, horseradish peroxidase (HRP)-mimicking DNAzyme, was formed and catalyzed the oxidation of colorless ABTS by H2O2, producing a visible green color. The proposed colorimetric assay exhibits a wide linear range from 0.01 to 150nM with a low detection limit of 10pM. More interestingly, the mutations existing in target gene are easily observed by the naked eye. It should be noted that this colorimetric system was proved by the analysis of K-ras gene of SW620 cell lines. The simple and powerful DFA-machine is expected to provide promising potential in the sensitive detection of biomarkers for cancer diagnosis, prognosis and therapy. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Machine musicianship

    NASA Astrophysics Data System (ADS)

    Rowe, Robert

    2002-05-01

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

  5. Machine wanting.

    PubMed

    McShea, Daniel W

    2013-12-01

    Wants, preferences, and cares are physical things or events, not ideas or propositions, and therefore no chain of pure logic can conclude with a want, preference, or care. It follows that no pure-logic machine will ever want, prefer, or care. And its behavior will never be driven in the way that deliberate human behavior is driven, in other words, it will not be motivated or goal directed. Therefore, if we want to simulate human-style interactions with the world, we will need to first understand the physical structure of goal-directed systems. I argue that all such systems share a common nested structure, consisting of a smaller entity that moves within and is driven by a larger field that contains it. In such systems, the smaller contained entity is directed by the field, but also moves to some degree independently of it, allowing the entity to deviate and return, to show the plasticity and persistence that is characteristic of goal direction. If all this is right, then human want-driven behavior probably involves a behavior-generating mechanism that is contained within a neural field of some kind. In principle, for goal directedness generally, the containment can be virtual, raising the possibility that want-driven behavior could be simulated in standard computational systems. But there are also reasons to believe that goal-direction works better when containment is also physical, suggesting that a new kind of hardware may be necessary. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Ada Compiler Validation Summary Report: Certificate Number: 940325S1. 11351 DDC-I, DACS Sun SPARC/SunOS to Pentium PM Bare Ada Cross Compiler System with Rate Monotonic Scheduling, Version 4.6.4 Sun SPARCstation IPX => Intel Pentium (operated as Bare Machine) based in Xpress Desktop (Intel product number: XBASE6E4F-B)

    DTIC Science & Technology

    1994-04-11

    Jorhson Chief, Information Systems Manager, Software Standards Engineering Division (ISED) Validation Group Computer Systems Laboratory (CSL) Nation&l...Director, C- er & Software David R. Basel Engineering Division Deputy Director, Institute for Defense Analyses Ada Joint Program Office Alexandria VA 22311...SPARCstation IPX => Intel Pentium (operated as Bare Machine) based in Xpress Desktop (Intel product number: XBASE6E4F-B) Prepared By: Software Standards

  7. Distribution of PM(2.5) and PM(10-2.5) in PM(10) fraction in ambient air due to vehicular pollution in Kolkata megacity.

    PubMed

    Das, Manab; Maiti, Subodh Kumar; Mukhopadhyay, Ujjal

    2006-11-01

    This research paper aims at establishing baseline PM(10) and PM(2.5) concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM(2.5)) and coarser fractions (PM(10-2.5)) to PM(10) fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM(10) concentration was 304 microg/m(3), which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM(10) concentration was due to fine fraction (PM(2.5)) released by vehicular exhaust. The 24h average PM(2.5) concentration was found 179 microg/m(3), which is exceeded USEPA and EU standards of 65 and 50 microg/m(3) respectively for the winter. India does not have any PM(2.5) standards. The 24 h average PM(10-2.5) concentrations were found 126 microg/m(3). The PM(2.5) constituted more than 59% of PM(10) and whereas PM(10)-PM(2.5) fractions constituted 41% of PM(10). The correlation between PM(10) and PM(2.5) was found higher as PM(2.5) comprised major proportion of PM(10) fractions contributed by vehicular emissions.

  8. 40 CFR 93.117 - Criteria and procedures: Compliance with PM10 and PM2.5 control measures.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... with PM10 and PM2.5 control measures. 93.117 Section 93.117 Protection of Environment ENVIRONMENTAL....117 Criteria and procedures: Compliance with PM10 and PM2.5 control measures. The FHWA/FTA project must comply with any PM10 and PM2.5 control measures in the applicable implementation plan....

  9. Seasonal PM 10 dynamics in Kathmandu Valley

    NASA Astrophysics Data System (ADS)

    Aryal, Rupak Kumar; Lee, Byeong-Kyu; Karki, Rahul; Gurung, Anup; Kandasamy, Jaya; Pathak, Bipin Kumar; Sharma, Suman; Giri, Nirita

    Data on ambient PM 10 levels from six locations in the Kathmandu Valley recorded by means of continuous sampling using low volume air samplers from October 2002 to March 2007 were used to investigate PM 10 concentration dynamics in the valley. Monthly average data of the urban areas, which have much higher concentrations than the rural areas, even exceeded the daily standard level of PM 10, in Nepal, 120 μm m -3. Repetitive peaks and troughs each year indicated annual patterns. Monthly average showed seasonal patterns are different between rural area and urban sites. The highest monthly average concentration was observed in February, the end of winter in urban areas where as in rural found in spring, and the lowest concentration was observed in July (monsoon period). The continuous increase in PM 10 concentration from December to February in urban areas showed accumulation of PM 10 in the ambient air during the wintertime. Rainfall in June and September, during the monsoon period, caused a PM 10 concentration decrease, demonstrating that precipitation is effective in removing PM 10 from the valley. Cross correlation analyses among the PM 10 levels measured simultaneously at the sampling stations showed a poor relationship in winter; however, there were good relationships in the monsoon and post-monsoon seasons. Both the PM 10 concentration and the air-mixing environment in the valley were closely associated with the temperature and wind speed.

  10. Flotation machine

    SciTech Connect

    Zlobin, M.N.; Permyakov, G.P.; Nemarov, A.A.; Metsik, V.M.; Medetsky, J.V.; Taraban, N.T.

    1993-08-10

    A flotation machine is described for beneficiating minerals comprising: a vertical cylindrical chamber for circulating a flotation pulp; a downwardly tapered bottom connected to said vertical cylindrical chamber; feed pipe means for feeding the flotation pulp carrying mineral particles of fine fraction, particles of the useful ingredient of the fine fraction being capable of floating up from the volume of said aerated pulp; discharge pipe means connected to the tapered bottom near its lowest point for discharging gangue; an annular trough for collecting froth concentrate at the top of said chamber; a group of frustoconical shells each having bases of different diameters and a tapered surface secured axially in said chamber and spaced equidistantly from one another height wise of said chamber; aerator means for aerating the flotation pulp secured to the walls of said chamber and communicating therewith to provide aerated water into said chamber; means for feeding mineral particles of coarse fraction, particles of the useful ingredient of the coarse fraction being capable of floating in the froth layer of the flotation pulp, in the form of a hydrocyclone having a cylindrical casing positioned axially over said chamber and a downwardly tapering outlet directed downwardly to feed the coarse particles to said chamber; feed pipe means for feeding the flotation pulp carrying mineral particles of coarse fraction positioned tangentially at said cylindrical casing of the hydrocyclone; and evacuation means for evacuating the liquid phase of the flotation pulp positioned tangentially at said casing of the hydrocyclone over said feed pipe means and connected to said feed pipe means for feeding the flotation pulp carrying mineral particles of the fine fraction.

  11. Finely Resolved On-Road PM2.5 and Estimated Premature Mortality in Central North Carolina.

    PubMed

    Chang, Shih Ying; Vizuete, William; Serre, Marc; Vennam, Lakshmi Pradeepa; Omary, Mohammad; Isakov, Vlad; Breen, Michael; Arunachalam, Saravanan

    2017-02-28

    To quantify the on-road PM2.5 -related premature mortality at a national scale, previous approaches to estimate concentrations at a 12-km × 12-km or larger grid cell resolution may not fully characterize concentration hotspots that occur near roadways and thus the areas of highest risk. Spatially resolved concentration estimates from on-road emissions to capture these hotspots may improve characterization of the associated risk, but are rarely used for estimating premature mortality. In this study, we compared the on-road PM2.5 -related premature mortality in central North Carolina with two different concentration estimation approaches-(i) using the Community Multiscale Air Quality (CMAQ) model to model concentration at a coarser resolution of a 36-km × 36-km grid resolution, and (ii) using a hybrid of a Gaussian dispersion model, CMAQ, and a space-time interpolation technique to provide annual average PM2.5 concentrations at a Census-block level (∼105,000 Census blocks). The hybrid modeling approach estimated 24% more on-road PM2.5 -related premature mortality than CMAQ. The major difference is from the primary on-road PM2.5 where the hybrid approach estimated 2.5 times more primary on-road PM2.5 -related premature mortality than CMAQ due to predicted exposure hotspots near roadways that coincide with high population areas. The results show that 72% of primary on-road PM2.5 premature mortality occurs within 1,000 m from roadways where 50% of the total population resides, highlighting the importance to characterize near-road primary PM2.5 and suggesting that previous studies may have underestimated premature mortality due to PM2.5 from traffic-related emissions.

  12. Applied machine vision

    SciTech Connect

    Not Available

    1984-01-01

    This book presents the papers given at a conference on robot vision. Topics considered at the conference included the link between fixed and flexible automation, general applications of machine vision, the development of a specification for a machine vision system, machine vision technology, machine vision non-contact gaging, and vision in electronics manufacturing.

  13. Machine Shop Lathes.

    ERIC Educational Resources Information Center

    Dunn, James

    This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

  14. Time (hole?) machines

    NASA Astrophysics Data System (ADS)

    Manchak, John Byron

    2014-11-01

    Within the context of general relativity, we consider a type of "time machine" and introduce the related "hole machine". We review what is known about each and add results of our own. We conclude that (so far) the hole machine advocate is in a better position than the time machine advocate.

  15. Analyses of 2000-2002 PM Data for the PM NAAQS Review

    EPA Pesticide Factsheets

    These files document all analyses conducted in association with the EPA memorandum from Mark Schmidt, David Mintz, Tesh Rao, and Lance McCluney titled Analyses of 2000-2002 PM Data for the PM NAAQS Review, August 29, 2003.

  16. A single-phase axially-magnetized permanent-magnet oscillating machine for miniature aerospace power sources

    NASA Astrophysics Data System (ADS)

    Sui, Yi; Zheng, Ping; Cheng, Luming; Wang, Weinan; Liu, Jiaqi

    2017-05-01

    A single-phase axially-magnetized permanent-magnet (PM) oscillating machine which can be integrated with a free-piston Stirling engine to generate electric power, is investigated for miniature aerospace power sources. Machine structure, operating principle and detent force characteristic are elaborately studied. With the sinusoidal speed characteristic of the mover considered, the proposed machine is designed by 2D finite-element analysis (FEA), and some main structural parameters such as air gap diameter, dimensions of PMs, pole pitches of both stator and mover, and the pole-pitch combinations, etc., are optimized to improve both the power density and force capability. Compared with the three-phase PM linear machines, the proposed single-phase machine features less PM use, simple control and low controller cost. The power density of the proposed machine is higher than that of the three-phase radially-magnetized PM linear machine, but lower than the three-phase axially-magnetized PM linear machine.

  17. A PROBABILISTIC POPULATION EXPOSURE MODEL FOR PM10 AND PM 2.5

    EPA Science Inventory

    A first generation probabilistic population exposure model for Particulate Matter (PM), specifically for predicting PM10, and PM2.5, exposures of an urban, population has been developed. This model is intended to be used to predict exposure (magnitude, frequency, and duration) ...

  18. Automated mineralogical analysis of PM10: new parameters for assessing PM toxicity.

    PubMed

    Williamson, Ben J; Rollinson, Gavyn; Pirrie, Duncan

    2013-06-04

    This work provides the first automated mineralogical/phase assessment of urban airborne PM10 and a new method for determining particle surface mineralogy (PSM), which is a major control on PM toxicity in the lung. PM10 was analyzed on a TEOM filter (Aug.-Sept. 2006 collection) from the London Air Quality Network Bexley, East London, U.K. A cross-section of the filter was analyzed using a QEMSCAN automated mineralogical analysis system which provided 381,981 points of analysis for 14,525 particles over a period of 9 h 54 min. The method had a detection limit for individual mineral components of 0.05 ppm (by area). Particle shape and mineralogical characteristics were determined for particles in the size ranges PM(10-4), PM(4-2.5), and PM(2.5-0.8). The PM(2.5-0.8) fraction contained 2 orders of magnitude more mineral particles than the PM(10-4) and PM(4-2.5) fractions, however the PM(10-4) fraction forms 94% and 79% of the mineral mass and surface area, respectively. PSM of the PM10 was dominated by gypsum (36%), plagioclase (16%), Na sulphates (8%), and Fe-S-O phases (8%) in the PM(10-2.5), which may be important in explaining the toxicity of the coarse fraction. The wider implications of the study are discussed.

  19. Method and apparatus for PM filter regeneration

    DOEpatents

    Opris, Cornelius N.; Verkiel, Maarten

    2006-01-03

    A method and apparatus for initiating regeneration of a particulate matter (PM) filter in an exhaust system in an internal combustion engine. The method and apparatus includes determining a change in pressure of exhaust gases passing through the PM filter, and responsively varying an opening of an intake valve in fluid communication with a combustion chamber.

  20. Performance comparison between rotor flux-switching and stator flux-switching machines considering local demagnetization

    NASA Astrophysics Data System (ADS)

    Su, Peng; Hua, Wei

    2017-05-01

    This paper investigates the local permanent magnet (PM) demagnetization characteristics of stator-PM flux-switching (SPM-FS) machine and rotor-PM flux-switching (RPM-FS) machine. The partial demagnetization mechanisms of two machines are analyzed based on a simple magnetic circuit method, and verified by finite-element analysis (FEA). In addition, the performance degradation due to demagnetization effect is evaluated, and a comprehensive comparison of a pair of three-phase prototyped machines is conducted, where the two machines have the same stator outer diameter, stack length and rated current density. The predicted results indicate the demagnetization is generated in the corner parts of PMs near to air-gap for SPM-FS machines, and then the torque performances are degraded, while PMs in RPM-FS machine are hardly influenced by demagnetization effect. Hence, the anti-demagnetization capability of the RPM-FS machine is significantly stronger than that of the SPM-FS machine.

  1. The PM-200 lubrication system

    NASA Technical Reports Server (NTRS)

    Sliney, Harold E.

    1991-01-01

    Plasma sprayed composite coating of metal-bonded chromium carbide with additions of silver and thermochemically stable fluorides were previously reported to be lubricative in pin on desk bench tests from room temperature to 900 C. An early coating formulation of this type, designated as PS-200, was successfully tested as a cylinder coating in a Stirling engine at a TRRT of 760 C in a hydrogen atmosphere, and as a backup lubricant for gas bearings to 650 C. A subsequent optimization program has shown that tribological properties are further improved by increasing the solid lubricant content. The improved coating is designated as PS-212. The same powder formulation was used to make free-standing powder metallurgy (PM-212) parts by sintering or hot isostatic pressing. The process is very attractive for making parts that cannot be readily plasma sprayed such as bushings and cylinders that have small bore diameters and/or high length to diameter ratios. The properties of coatings and free-standing parts fabricated from these powders are reviewed.

  2. Influences of wind and precipitation on different-sized particulate matter concentrations (PM2.5, PM10, PM2.5-10)

    NASA Astrophysics Data System (ADS)

    Zhang, Boen; Jiao, Limin; Xu, Gang; Zhao, Suli; Tang, Xin; Zhou, Yue; Gong, Chen

    2017-04-01

    Though it is recognized that meteorology has a great impact on the diffusion, accumulation and transport of air pollutants, few studies have investigated the impacts on different-sized particulate matter concentrations. We conducted a systematic comparative analysis and used the framework of generalized additive models (GAMs) to explore the influences of critical meteorological parameters, wind and precipitation, on PM2.5, PM10 and PM2.5-10 concentrations in Wuhan during 2013-2016. Overall, results showed that the impacts of wind and precipitation on different-sized PM concentrations are significantly different. The fine PM concentrations decreased gradually with the increase of wind speed, while coarse PM concentrations would increase due to dust resuspension under strong wind. Wind direction exerts limited influence on coarse PM concentrations. Wind speed was linearly correlated with log-transformed PM2.5 concentrations, but nonlinearly correlated with log-transformed PM10 and PM2.5-10 concentrations. We also found the PM2.5 and PM2.5-10 concentrations decreased by nearly 60 and 15% when the wind speed was up to 6 m/s, respectively, indicating a stronger negative impact of wind-speed on fine PM than coarse PM. The scavenging efficiency of precipitation on PM2.5-10 was over twice as high as on PM2.5. Our findings may help to understand the impacts of meteorology on different PM concentrations as well as discriminate and forecast variation in particulate matter concentrations.

  3. Implications of tighter PM10 air quality standards

    USDA-ARS?s Scientific Manuscript database

    The EPA is proposing to adopt a new PM10 Air Quality Standard. The proposed PM10 Standard requires the daily PM10 concentration to be no greater than 65 or 85 µg m-3, which is lower than the current Standard (daily PM10 concentration no greater than 150 µg m-3). The proposed PM10 Standard does allow...

  4. 40 CFR 52.378 - Control strategy: PM10

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS Connecticut § 52.378 Control strategy: PM10 (a) Approval... in the event the PM10 design value in the maintenance area exceeds 98 µgm/m3 for the 24-hour PM10... on maintaining levels of ambient PM10 below a PM10 design value criteria of 98 µgm/m3 for the...

  5. Shrimp Serine Proteinase Homologues PmMasSPH-1 and -2 Play a Role in the Activation of the Prophenoloxidase System

    PubMed Central

    Jearaphunt, Miti; Amparyup, Piti; Sangsuriya, Pakkakul; Charoensapsri, Walaiporn; Senapin, Saengchan; Tassanakajon, Anchalee

    2015-01-01

    Melanization mediated by the prophenoloxidase (proPO) activating system is a rapid immune response used by invertebrates against intruding pathogens. Several masquerade-like and serine proteinase homologues (SPHs) have been demonstrated to play an essential role in proPO activation in insects and crustaceans. In a previous study, we characterized the masquerade-like SPH, PmMasSPH1, in the black tiger shrimp Penaeus monodon as a multifunctional immune protein based on its recognition and antimicrobial activity against the Gram-negative bacteria Vibrio harveyi. In the present study, we identify a novel SPH, known as PmMasSPH2, composed of an N-terminal clip domain and a C-terminal SP-like domain that share high similarity to those of other insect and crustacean SPHs. We demonstrate that gene silencing of PmMasSPH1 and PmMasSPH2 significantly reduces PO activity, resulting in a high number of V. harveyi in the hemolymph. Interestingly, knockdown of PmMasSPH1 suppressed not only its gene transcript but also other immune-related genes in the proPO system (e.g., PmPPAE2) and antimicrobial peptides (e.g., PenmonPEN3, PenmonPEN5, crustinPm1 and Crus-likePm). The PmMasSPH1 and PmMasSPH2 also show binding activity to peptidoglycan (PGN) of Gram-positive bacteria. Using a yeast two-hybrid analysis and co-immunoprecipitation, we demonstrate that PmMasSPH1 specifically interacted with the final proteinase of the proPO cascade, PmPPAE2. Furthermore, the presence of both PmMasSPH1 and PmPPAE2 enhances PGN-induced PO activity in vitro. Taken together, these results suggest the importance of PmMasSPHs in the activation of the shrimp proPO system. PMID:25803442

  6. Influence of Southeast Asian Haze episodes on high PM10 concentrations across Brunei Darussalam.

    PubMed

    Dotse, Sam-Quarcoo; Dagar, Lalit; Petra, Mohammad Iskandar; De Silva, Liyanage C

    2016-12-01

    Particulate matter (PM10) is the key indicator of air quality index in Brunei Darussalam and the principal pollutant for haze related episodes in Southeast Asia. This study examined the temporal and spatial distribution of PM10 base on a long-term monitoring data (2009-2014) in order to identify the emission sources and favorable meteorological conditions for high PM10 concentrations across the country. PM10 concentrations measured at the various locations differ significantly but the general temporal characteristics show clear patterns of seasonal variations across the country with the highest concentrations recorded during the southwest monsoon. The high PM10 values defined in the study were not evenly distributed over the years but occurred mostly within the southwest monsoon months of June to September. Further investigations with bivariate polar concentrations plots and k-means clustering demonstrated the significant influence of Southeast Asian regional biomass fires on the high PM10 concentrations recorded across the country. The results of the polar plots and cluster analyses were further confirmed by the evaluations with Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward air masses trajectories analysis and the Moderate Resolution Imaging Spectroradiometer (MODIS) fire records. Among the meteorological variables considered, temperature, rainfall and relative humidity were the most important meteorological variables that influence the concentration throughout the year. High PM10 values are associated with high temperatures and low amounts of rainfall and relative humidity. In addition, wind speed and direction also play significant role in the recorded high PM10 concentrations and were mainly responsible for its seasonality during the study period.

  7. Application of positive matrix factorization in characterization of PM(10) and PM(2.5) emission sources at urban roadside.

    PubMed

    Srimuruganandam, B; Shiva Nagendra, S M

    2012-06-01

    The 24-h average coarse (PM(10)) and fine (PM(2.5)) fraction of airborne particulate matter (PM) samples were collected for winter, summer and monsoon seasons during November 2008-April 2009 at an busy roadside in Chennai city, India. Results showed that the 24-h average ambient PM(10) and PM(2.5) concentrations were significantly higher in winter and monsoon seasons than in summer season. The 24-h average PM(10) concentration of weekdays was significantly higher (12-30%) than weekends of winter and monsoon seasons. On weekends, the PM(2.5) concentration was found to slightly higher (4-15%) in monsoon and summer seasons. The chemical composition of PM(10) and PM(2.5) masses showed a high concentration in winter followed by monsoon and summer seasons. The U.S.EPA-PMF (positive matrix factorization) version 3 was applied to identify the source contribution of ambient PM(10) and PM(2.5) concentrations at the study area. Results indicated that marine aerosol (40.4% in PM(10) and 21.5% in PM(2.5)) and secondary PM (22.9% in PM(10) and 42.1% in PM(2.5)) were found to be the major source contributors at the study site followed by the motor vehicles (16% in PM(10) and 6% in PM(2.5)), biomass burning (0.7% in PM(10) and 14% in PM(2.5)), tire and brake wear (4.1% in PM(10) and 5.4% in PM(2.5)), soil (3.4% in PM(10) and 4.3% in PM(2.5)) and other sources (12.7% in PM(10) and 6.8% in PM(2.5)).

  8. Tube Alinement for Machining

    NASA Technical Reports Server (NTRS)

    Garcia, J.

    1984-01-01

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

  9. Women, Men, and Machines.

    ERIC Educational Resources Information Center

    Form, William; McMillen, David Byron

    1983-01-01

    Data from the first national study of technological change show that proportionately more women than men operate machines, are more exposed to machines that have alienating effects, and suffer more from the negative effects of technological change. (Author/SSH)

  10. Stirling machine operating experience

    NASA Technical Reports Server (NTRS)

    Ross, Brad; Dudenhoefer, James E.

    1991-01-01

    Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that Stirling machines are capable of reliable and lengthy lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and were not expected to operate for any lengthy period of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered.

  11. Satellite-based PM concentrations and their application to COPD in Cleveland, OH

    PubMed Central

    Kumar, Naresh; Liang, Dong; Comellas, Alejandro; Chu, Allen D.; Abrams, Thad

    2014-01-01

    A hybrid approach is proposed to estimate exposure to fine particulate matter (PM2.5) at a given location and time. This approach builds on satellite-based aerosol optical depth (AOD), air pollution data from sparsely distributed Environmental Protection Agency (EPA) sites and local time–space Kriging, an optimal interpolation technique. Given the daily global coverage of AOD data, we can develop daily estimate of air quality at any given location and time. This can assure unprecedented spatial coverage, needed for air quality surveillance and management and epidemiological studies. In this paper, we developed an empirical relationship between the 2 km AOD and PM2.5 data from EPA sites. Extrapolating this relationship to the study domain resulted in 2.3 million predictions of PM2.5 between 2000 and 2009 in Cleveland Metropolitan Statistical Area (MSA). We have developed local time–space Kriging to compute exposure at a given location and time using the predicted PM2.5. Daily estimates of PM2.5 were developed for Cleveland MSA between 2000 and 2009 at 2.5 km spatial resolution; 1.7 million (~79.8%) of 2.13 million predictions required for multiyear and geographic domain were robust. In the epidemiological application of the hybrid approach, admissions for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was examined with respect to time–space lagged PM2.5 exposure. Our analysis suggests that the risk of AECOPD increases 2.3% with a unit increase in PM2.5 exposure within 9 days and 0.05° (~5 km) distance lags. In the aggregated analysis, the exposed groups (who experienced exposure to PM2.5 >15.4 μg/m3) were 54% more likely to be admitted for AECOPD than the reference group. The hybrid approach offers greater spatiotemporal coverage and reliable characterization of ambient concentration than conventional in situ monitoring-based approaches. Thus, this approach can potentially reduce exposure misclassification errors in the conventional

  12. Composition and distribution of particulate matter (PM10) in a mechanically ventilated University building

    NASA Astrophysics Data System (ADS)

    Ali, Mohamed Yasreen Mohamed; Hanafiah, Marlia Mohd; Latif, Mohd Talib

    2016-11-01

    This study analyses the composition and distribution of particulate matter (PM10) in the Biology department building, in UKM. PM10 were collected using SENSIDYNE Gillian GilAir-5 Personal Air Sampling System, a low-volume sampler, whereas the concentration of heavy metals was determined using Inductively coupled plasma-mass spectrometry (ICP-MS). The concentration of PM10 recorded in the mechanically ventilated building ranges from 89 µgm-3 to 910 µgm-3. The composition of the selected heavy metals in PM10 were dominated by zinc, followed by copper, lead and cadmium. It was found that the present of indoor-related particulate matter were originated from the poorly maintained ventilation system, the activity of occupants and typical office equipments such as printers and photocopy machines. The haze event occured during sampling periods was also affected the PM10 concentration in the building. This results can serve as a starting point to assess the potential human health damage using the life cycle impact assessment, expressed in term of disability adjusted life year (DALY).

  13. The Iowa wave machines

    NASA Astrophysics Data System (ADS)

    Daffron, John D.; Greenslade, Thomas B.; Stille, Dale

    2010-03-01

    Wave machines are a staple of demonstration lectures, and a good pair of wave machines can make the idea of transverse and longitudinal waves clearly evident to students. The demonstration apparatus collection of the University of Iowa contains examples of transverse and longitudinal wave machines that will be of interest to readers of The Physics Teacher. These machines probably date from about 1925 and may have been locally produced. You too can build them.

  14. Applying or Implementing Particulate Matter (PM) Standards

    EPA Pesticide Factsheets

    Along with developing the PM standards themselves (part of the National Ambient Air Quality Standards, or NAAQS), EPA also develops requirements for how to go about attaining and maintaining those standards.

  15. PM State Implementation Plan (SIP) Checklist Guide

    EPA Pesticide Factsheets

    Guidance documents and examples to assist air quality agencies of non-attainment areas in developing plans to implement national ambient air quality standards (NAAQS), including the PM air emissions standard.

  16. Your Sewing Machine.

    ERIC Educational Resources Information Center

    Peacock, Marion E.

    The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

  17. Automatic Inspection During Machining

    NASA Technical Reports Server (NTRS)

    Ransom, Clyde L.

    1988-01-01

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

  18. Apprentice Machine Theory Outline.

    ERIC Educational Resources Information Center

    Connecticut State Dept. of Education, Hartford. Div. of Vocational-Technical Schools.

    This volume contains outlines for 16 courses in machine theory that are designed for machine tool apprentices. Addressed in the individual course outlines are the following topics: basic concepts; lathes; milling machines; drills, saws, and shapers; heat treatment and metallurgy; grinders; quality control; hydraulics and pneumatics;…

  19. Machining lead wafers

    SciTech Connect

    Schamaun, R.T.

    1987-09-01

    Recently, MEC-6 machined some 4-inch-diameter lead wafers to precision tolerances. The tolerance on the wafer thickness was +-0.000080 inch. A diamond tool was used to machine the wafers on a Moore No. 3 lathe. This report discusses the methods used to machine the wafers, the fixtures used to hold the wafers, and the inspection methods and results.

  20. Cable-Twisting Machine

    NASA Technical Reports Server (NTRS)

    Kurnett, S.

    1982-01-01

    New cable-twisting machine is smaller and faster than many production units. Is useful mainly in production of short-run special cables. Already-twisted cable can be fed along axis of machine. Faster operation than typical industrial cable-twisting machines possible by using smaller spools of wire.

  1. The distribution of PM10 and PM2.5 carbonaceous aerosol in Baotou, China

    NASA Astrophysics Data System (ADS)

    Zhou, Haijun; He, Jiang; Zhao, Boyi; Zhang, Lijun; Fan, Qingyun; Lü, Changwei; Dudagula; Liu, Tao; Yuan, Yinghui

    2016-09-01

    Particulate matter (PM), including PM10 and PM2.5, is one of the major impacts on air quality, visibility, climate change, earth radiation balance, and public health. Organic carbon (OC) and elemental carbon (EC) are the major components of PM. 804 samples (PM10 and PM2.5) were simultaneously collected from six urban sites covering 3 districts in Baotou, in January, April, September, and November 2014. As to a long-term study on the effects of carbonaceous aerosol, data were collected annually at Environmental Protection Agency of Baotou (EPB). The concentrations of PM10 and PM2.5, the spatial distribution and content of OC and EC, the relationship between OC and EC, and the formation of secondary organic carbon (SOC) have been investigated. The findings indicated that the concentrations of these particle matter are higher than that in US or European standards. The average concentrations of OC in PM10 and PM2.5 follow the order: January > November > April > September; and for EC in PM10 and PM2.5 follow the order: January > November > September > April. Affected by metrological factors, it was indicated that high wind speed and low relative humidity were beneficial for removal of OC and EC in January and November. Pearson correlations and cluster analysis on OC and EC concentrations in PM10 and PM2.5 with gaseous pollutants (SO2, NO2, and CO) suggested that OC shared the same emission sources with SO2 and CO from combustion, while EC's sources mainly came from vehicles exhaust and combustion which contributed to NO2 as well. The OC concentration is mainly primary in warm months, while it appears secondary in cold months in Baotou. There is a common characteristic among the cities with higher SOC in winter, wherever the coal combustion can lead to the severe pollution. This work is important for the construction of the database of OC and EC concentrations in PM10 and PM2.5 at spatial and time intervals, and it can provide scientific suggestion for similar PM

  2. Efficiency of Big Spring Number Eight (BSNE) and Modified Wilson and Cook (MWAC) samplers to collect PM10, PM2.5 and PM1

    NASA Astrophysics Data System (ADS)

    Mendez, Mariano J.; Funk, Roger; Buschiazzo, Daniel E.

    2016-06-01

    The internal efficiency of Big Spring Number Eight (BSNE) and Modified Wilson and Cook (MWAC) samplers for trapping PM10, PM2.5 and PM1 were tested in a wind tunnel, at two wind speeds (3.0 and 6.8 m s-1) in the saltation zone (SAZ) and the suspension zone (SAZ). PM concentrations measured in the inlet and the outlet of both samplers were correlated and the slopes of fitting equations were used for calculating sampling efficiencies. Results showed that BSNE efficiencies ranged from 12% to 32% for PM10, from 0% to 19% for PM2.5 and from 0% to 12% for PM1. The BSNE's efficiency decreased with decreasing particle sizes in SAZ and SUZ at both wind speeds as a consequence of the very low deposition velocity of the finest size particles. The BSNE's efficiency increased with increasing wind speed in SAZ for PM10 and PM2.5 and in SUZ for PM2.5. The MWAC's efficiency ranged from 1% to 20% for PM10, from 0% to 15% for PM2.5 and from 0% to 16% for PM1. The MWAC efficiency was 0% for PM10, PM2.5 and PM1 in the SUZ at 3 m s-1 and for PM2.5 and PM1 in the SUZ at 6.8 m s-1. These results provide evidence that the efficiency of BSNE and MWAC for trapping PM10 change with wind speed and position of the sampler. Results also show that BSNEs and MWACs can potentially be used for PM10 emission studies but more research is needed in order to understand and improve their efficiency.

  3. Improved EMCCD gamma camera performance by SiPM pre-localization.

    PubMed

    Salvador, S; Korevaar, M A N; Heemskerk, J W T; Kreuger, R; Huizenga, J; Seifert, S; Schaart, D R; Beekman, F J

    2012-11-21

    High spatial resolution γ-imaging can be achieved with scintillator readout by low-noise, fast, electron-multiplying charge-coupled devices (EMCCDs). Previously we have shown that false-positive events due to EMCCD noise can be rejected by using the sum signal from silicon photomultipliers (SiPMs) mounted on the sides of the scintillator. Here we launch a next generation hybrid CCD-SiPM camera that utilizes the individual SiPM signals and maximum likelihood estimation (MLE) pre-localization of events to discriminate between true and false events in CCD frames. In addition, SiPM signals are utilized for improved energy discrimination. The performance of this hybrid detector was tested for a continuous CsI:Tl crystal at 140 keV. With a pre-localization accuracy of 1.06 mm (full-width-at-half-maximum) attained with MLE the signal-to-background ratio (SBR) was improved by a factor of 5.9, 4.0 or 2.2 compared to the EMCCD-only readout, at the cost of rejecting, respectively, 47%, 9% or 4% of the events. Combining the pre-localization and SiPM energy estimation improved the energy resolution from 50% to (19 ± 3)% while maintaining the spatial resolution at 180 µm.

  4. Intelligent, Energy Saving Power Supply and Control System of Hoisting Mine Machine with Compact and Hybrid Drive System / Inteligentne, Energooszczędne Układy Zasilania I Sterowania Górniczych Maszyn Wyciągowych Z Napędem Zintegrowanym Lub Hybrydowym

    NASA Astrophysics Data System (ADS)

    Szymański, Zygmunt

    2015-03-01

    In the paper present's an analysis of suitableness an application of compact and hybrid drive system in hoisting machine. In the paper presented the review of constructional solutions of hoisting machines drive system, driving with AC and DC motor. In the paper presented conception of modern, energy sparing hoisting machine supply system, composed with compact motor, an supplied with transistor or thyristor converter supply system, and intelligent control system composed with multilevel microprocessor controller. In the paper present's also analysis of suitableness application an selected method of artificial intelligent in hoisting machine control system, automation system, and modern diagnostic system. In the paper one limited to analysis of: fuzzy logic method, genetic algorithms method, and modern neural net II and III generation. That method enables realization of complex control algorithms of hosting machine with insurance of energy sparing exploitation conditions, monitoring of exploitation parameters, and prediction diagnostic of hoisting machine technical state, minimization a number of failure states. In the paper present's a conception of control and diagnostic system of the hoisting machine based on fuzzy logic neural set control. In the chapter presented also a selected control algorithms and results of computer simulations realized for particular mathematical models of hoisting machine. Results of theoretical investigation were partly verified in laboratory and industrial experiments. Przedstawiono analizę celowości wprowadzania, napędów zintegrowanych oraz napędów hybrydowych, do układów napędowych maszyn wyciągowych. Zamieszczono przegląd rozwiązań konstrukcyjnych wybranych hybrydowych oraz zintegrowanych napędów maszyn wyciągowych z silnikami DC i AC. Opisano koncepcję nowoczesnego, energooszczędnego układu zasilania górniczych maszyny wyciągowej, złożonego z silnika zintegrowanego, (tranzystorowego

  5. [Concentrations of PM10 and PM2.5 particulate material in the atmosphere of Rome].

    PubMed

    Marconi, A; Menichini, E; Ziemacki, G; Cattani, G; Stacchini, G

    2000-01-01

    Starting from 1993, various monitoring campaigns were carried out in Rome to determine PM10 and PM2.5. Their results are presented here cumulatively, with the aim of obtaining preliminary information on relationships among these size fractions, in various seasonal periods and in two sites with different characteristics (a road site and an urban background site in a public park). Particles were collected on filter and gravimetrically determined. Both PM10 and PM2.5 concentrations show temporal fluctuations with higher values during winter months. Background concentrations are lower than those contemporaneously measured at the road site only to a limited extent (10-17%). The contribution of PM2.5 to PM10 during the winter semester is higher than during the summer one (67 vs. 52%), with no substantial intersite differences.

  6. 16,000-rpm Interior Permanent Magnet Reluctance Machine with Brushless Field Excitation

    SciTech Connect

    Hsu, J.S.; Burress, T.A.; Lee, S.T.; Wiles, R.H.; Coomer, C.L.; McKeever, J.W.; Adams, D.J.

    2007-10-31

    The reluctance interior permanent magnet (RIPM) motor is currently used by many leading auto manufacturers for hybrid vehicles. The power density for this type of motor is high compared with that of induction motors and switched reluctance motors. The primary drawback of the RIPM motor is the permanent magnet (PM) because during high-speed operation, the fixed PM produces a huge back electromotive force (emf) that must be reduced before the current will pass through the stator windings. This reduction in back-emf is accomplished with a significant direct-axis (d-axis) demagnetization current, which opposes the PM's flux to reduce the flux seen by the stator wires. This may lower the power factor and efficiency of the motor and raise the requirement on the alternate current (ac) power supply; consequently, bigger inverter switching components, thicker motor winding conductors, and heavier cables are required. The direct current (dc) link capacitor is also affected when it must accommodate heavier harmonic currents. It is commonly agreed that, for synchronous machines, the power factor can be optimized by varying the field excitation to minimize the current. The field produced by the PM is fixed and cannot be adjusted. What can be adjusted is reactive current to the d-axis of the stator winding, which consumes reactive power but does not always help to improve the power factor. The objective of this project is to avoid the primary drawbacks of the RIPM motor by introducing brushless field excitation (BFE). This offers both high torque per ampere (A) per core length at low speed by using flux, which is enhanced by increasing current to a fixed excitation coil, and flux, which is weakened at high speed by reducing current to the excitation coil. If field weakening is used, the dc/dc boost converter used in a conventional RIPM motor may be eliminated to reduce system costs. However, BFE supports a drive system with a dc/dc boost converter, because it can further extend

  7. PM2.5 and PM10 concentrations in four dairies on the Southern High Plains

    USDA-ARS?s Scientific Manuscript database

    Air quality was determined in 4 dairies at the boundary, commodity barn, and compost field. Two laser DustTrak PM10 aerosol monitors and four RAAS -300 gravimetric monitors, 2 PM2.5 and 2 PM10 were employed. The DustTrak flow rate was set at 1.7 L/min and the RAAS were set at 16.6 L/min. Monitors we...

  8. Chemical composition of PM2.5 and PM10 in Mexico City during winter 1997.

    PubMed

    Chow, Judith C; Watson, John G; Edgerton, Sylvia A; Vega, Elizabeth

    2002-03-27

    PM2.5 and PM10 were measured over 24-h intervals at six core sites and at 25 satellite sites in and around Mexico City from 23 February to 22 March 1997. In addition, four 6-h samples were taken each day at three of the core sites. Sampling locations were selected to represent regional, central city, commercial, residential, and industrial portions of the city. Mass and light transmission concentrations were determined on all of the samples, while elements, ions and carbon were measured on approximately two-thirds of the samples. PM10 concentrations were highly variable, with almost three-fold differences between the highest and lowest concentrations. Fugitive dust was the major cause of PM10 differences, although carbon concentrations were also highly variable among the sampling sites. Approximately 50% of PM10 was in the PM2.5 fraction. The majority of PM mass was comprised of carbon, sulfate, nitrate, ammonium and crustal components, but in different proportions on different days and at different sites. The largest fine-particle components were carbonaceous aerosols, constituting approximately 50% of PM2.5 mass, followed by approximately 30% secondary inorganic aerosols and approximately 15% geological material. Geological material is the largest component of PM10, constituting approximately 50% of PM10 mass, followed by approximately 32% carbonaceous aerosols and approximately 17% secondary inorganic aerosols. Sulfate concentrations were twice as high as nitrate concentrations. Sulfate and nitrate were present as ammonium sulfate and ammonium nitrate. Approximately two-thirds of the ammonium sulfate measured in urban areas appears to have been transported from regions outside of the study domain, rather than formed from emissions in the urban area. Diurnal variations are apparent, with two-fold increases in concentration from night-time to daytime. Morning samples had the highest PM2.5 and PM10 mass, secondary inorganic aerosols and carbon concentrations

  9. Quantum machine learning

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  10. Quantum machine learning.

    PubMed

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

    2017-09-13

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

  11. Clamping in Boltzmann machines.

    PubMed

    Livesey, M

    1991-01-01

    A certain assumption that appears in the proof of correctness of the standard Boltzmann machine learning procedure is investigated. The assumption, called the clamping assumption, concerns the behavior of a Boltzmann machine when some of its units are clamped to a fixed state. It is argued that the clamping assumption is essentially an assertion of the time reversibility of a certain Markov chain underlying the behavior of the Boltzmann machine. As such, the clamping assumption is generally false, though it is certainly true of the Boltzmann machines themselves. The author also considers how the concept of the Boltzmann machine may be generalized while retaining the validity of the clamping assumption.

  12. Validation of PM6 & PM7 semiempirical methods on polarizability calculations

    SciTech Connect

    Praveen, P. A.; Babu, R. Ramesh; Ramamurthi, K.

    2015-06-24

    Modern semiempirical methods such as PM6 and PM7 are often used to explore the electronic structure dependent properties of molecules. In this work we report the evaluation of PM6 and PM7 methods towards linear and nonlinear optical polarizability calculations for different molecules and solid nanoclusters. The results are compared with reported experimental results as well as theoretical results from other high level theories for the same systems. It is found that both methods produce accurate results for small molecules and the accuracy increases with the increase in asymmetry of the medium sized organic molecules and accuracy reduces for solid nanoclusters.

  13. Effect of the Machining Processes on Low Cycle Fatigue Behavior of a Powder Metallurgy Disk

    NASA Technical Reports Server (NTRS)

    Telesman, J.; Kantzos, P.; Gabb, T. P.; Ghosn, L. J.

    2010-01-01

    A study has been performed to investigate the effect of various machining processes on fatigue life of configured low cycle fatigue specimens machined out of a NASA developed LSHR P/M nickel based disk alloy. Two types of configured specimen geometries were employed in the study. To evaluate a broach machining processes a double notch geometry was used with both notches machined using broach tooling. EDM machined notched specimens of the same configuration were tested for comparison purposes. Honing finishing process was evaluated by using a center hole specimen geometry. Comparison testing was again done using EDM machined specimens of the same geometry. The effect of these machining processes on the resulting surface roughness, residual stress distribution and microstructural damage were characterized and used in attempt to explain the low cycle fatigue results.

  14. Two-machine flow shop scheduling integrated with preventive maintenance planning

    NASA Astrophysics Data System (ADS)

    Wang, Shijin; Liu, Ming

    2016-02-01

    This paper investigates an integrated optimisation problem of production scheduling and preventive maintenance (PM) in a two-machine flow shop with time to failure of each machine subject to a Weibull probability distribution. The objective is to find the optimal job sequence and the optimal PM decisions before each job such that the expected makespan is minimised. To investigate the value of integrated scheduling solution, computational experiments on small-scale problems with different configurations are conducted with total enumeration method, and the results are compared with those of scheduling without maintenance but with machine degradation, and individual job scheduling combined with independent PM planning. Then, for large-scale problems, four genetic algorithm (GA) based heuristics are proposed. The numerical results with several large problem sizes and different configurations indicate the potential benefits of integrated scheduling solution and the results also show that proposed GA-based heuristics are efficient for the integrated problem.

  15. Chemical characterization and mass closure of PM10 and PM2.5 at an urban site in Karachi - Pakistan

    NASA Astrophysics Data System (ADS)

    Shahid, Imran; Kistler, Magdalena; Mukhtar, Azam; Ghauri, Badar M.; Ramirez-Santa Cruz, Carlos; Bauer, Heidi; Puxbaum, Hans

    2016-03-01

    A mass balance method is applied to assess main source contributions to PM2.5 and PM10 levels in Karachi. Carbonaceous species (elemental carbon, organic carbon, carbonate carbon), soluble ions (Ca++, Mg++, Na+, K+, NH4+, Cl-, NO3-, SO4-), saccharides (levoglucosan, galactosan, mannosan, sucrose, fructose, glucose, arabitol and mannitol) were determined in atmospheric fine (PM2.5) and coarse (PM10) aerosol samples collected under pre-monsoon conditions (March-April 2009) at an urban site in Karachi (Pakistan). The concentrations of PM2.5 and PM10 were found to be 75 μg/m3 and 437 μg/m3 respectively. The large difference between PM10 and PM2.5 originated predominantly from mineral dust. "Calcareous dust" and "siliceous dust" were the over all dominating material in PM, with 46% contribution to PM2.5 and 78% to PM10-2.5. Combustion particles and secondary organics (EC + OM) comprised 23% of PM2.5 and 6% of PM10-2.5. EC, as well as OC ambient levels were higher (59% and 56%) in PM10-2.5 than in PM2.5. Biomass burning contributed about 3% to PM2.5, and had a share of about 13% of "EC + OM" in PM2.5. The impact of bioaerosol (fungal spores) was minor and had a share of 1 and 2% of the OC in the PM2.5 and PM10-2.5 size fractions. In case of secondary inorganic aerosols, ammonium sulphate (NH4)2SO4 contributes 4.4% to PM2.5 and no detectable quantity were found in fraction PM10-2.5. The sea salt contribution is about 2% both to PM2.5 and PM10-2.5.

  16. Influences of Secondary Chemical Gas Processes on PM1, PM2.5 and PM10 Concentrations Over the Korean Coast

    NASA Astrophysics Data System (ADS)

    Choi, Hyo; Speer, Milton S.

    An aerosol sampler was installed at Kangnung city in the east coast of Korea to measure mass concentrations of PM10, PM2.5, and PM1 covering particle diameter sizes ranging from 300 ηm to 20 μm from February 14 to 16, 2005. The concentrations of PM10, PM2.5, and PM1 showed a high morning (09:00 LST) and afternoon (17:00 LST) concentration and a low concentration around midday (12:00 LST). First maximum concentrations of PM10, PM2.5, and PM1 occurred at 20:00 LST. Secondary maximum concentrations were detected at 01:00 LST, February 15. The distribution of CO and NOx concentrations showed a similar diurnal distribution to those of PM10, PM2.5, and PM1, except for the morning of February 14. The first and secondary maximum concentrations of NOx occurred at the same times as those of PM10, PM2.5, and PM1. This implies that the increase in NOx and CO emissions from road vehicles and combustion gases from boilers in residential areas can contribute substantially to the increase in PM concentration. As a result of a typical daytime westerly wind regime over Korea, the rotor action of a lee-side easterly breeze transports PM from Kangnung toward the mountains, which is then recycled toward Kangnung in the westerly airflow at night. Some PM from Wonju city upwind on the western side can also contribute significantly to the secondary maximum at Kangnang city on the eastern or lee side.

  17. Perspex machine: VII. The universal perspex machine

    NASA Astrophysics Data System (ADS)

    Anderson, James A. D. W.

    2006-01-01

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

  18. High-Resolution Satellite-Derived PM2.5 from Optimal Estimation and Geographically Weighted Regression over North America.

    PubMed

    van Donkelaar, Aaron; Martin, Randall V; Spurr, Robert J D; Burnett, Richard T

    2015-09-01

    We used a geographically weighted regression (GWR) statistical model to represent bias of fine particulate matter concentrations (PM2.5) derived from a 1 km optimal estimate (OE) aerosol optical depth (AOD) satellite retrieval that used AOD-to-PM2.5 relationships from a chemical transport model (CTM) for 2004-2008 over North America. This hybrid approach combined the geophysical understanding and global applicability intrinsic to the CTM relationships with the knowledge provided by observational constraints. Adjusting the OE PM2.5 estimates according to the GWR-predicted bias yielded significant improvement compared with unadjusted long-term mean values (R(2) = 0.82 versus R(2) = 0.62), even when a large fraction (70%) of sites were withheld for cross-validation (R(2) = 0.78) and developed seasonal skill (R(2) = 0.62-0.89). The effect of individual GWR predictors on OE PM2.5 estimates additionally provided insight into the sources of uncertainty for global satellite-derived PM2.5 estimates. These predictor-driven effects imply that local variability in surface elevation and urban emissions are important sources of uncertainty in geophysical calculations of the AOD-to-PM2.5 relationship used in satellite-derived PM2.5 estimates over North America, and potentially worldwide.

  19. Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings

    NASA Astrophysics Data System (ADS)

    Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Yahaya, Ahmad Shukri Bin; Al Madhoun, Wesam; Ul-Saufie, Ahmed Zia

    2014-09-01

    In this study the concentrations of PM10, PM2.5, CO and CO2 concentrations and meteorological variables (wind speed, air temperature, and relative humidity) were employed to predict the annual and seasonal indoor concentration of PM10 and PM2.5 using multivariate statistical methods. The data have been collected in twelve naturally ventilated schools in Gaza Strip (Palestine) from October 2011 to May 2012 (academic year). The bivariate correlation analysis showed that the indoor PM10 and PM2.5 were highly positive correlated with outdoor concentration of PM10 and PM2.5. Further, Multiple linear regression (MLR) was used for modelling and R2 values for indoor PM10 were determined as 0.62 and 0.84 for PM10 and PM2.5 respectively. The Performance indicators of MLR models indicated that the prediction for PM10 and PM2.5 annual models were better than seasonal models. In order to reduce the number of input variables, principal component analysis (PCA) and principal component regression (PCR) were applied by using annual data. The predicted R2 were 0.40 and 0.73 for PM10 and PM2.5, respectively. PM10 models (MLR and PCR) show the tendency to underestimate indoor PM10 concentrations as it does not take into account the occupant's activities which highly affect the indoor concentrations during the class hours.

  20. Aptamer/Protein Proximity Binding-Triggered Molecular Machine for Amplified Electrochemical Sensing of Thrombin.

    PubMed

    Yang, Jianmei; Dou, Baoting; Yuan, Ruo; Xiang, Yun

    2017-04-13

    The development of convenient and sensitive methods without involving any enzymes or complex nanomaterials for the monitoring of proteins is of great significance in disease diagnostics. In this work, we describe the validation of a new aptamer/protein proximity binding-triggered molecular machinery amplification strategy for sensitive electrochemical assay of thrombin in complex serum samples. The sensing interface is prepared by self-assembly of three-stranded DNA complexes on the gold electrode. The association of two distinct functional aptamers with different sites of thrombin triggers proximity binding-induced displacement of one of the short single-stranded DNAs (ssDNAs) from the surface-immobilized three-stranded DNA complexes, exposing a prelocked toehold domain to hybridize with a methylene blue (MB)-tagged fuel ssDNA strand (MB-DNA). Subsequent toehold-mediated strand displacement by the MB-DNA leads to the release and recycling of the aptamer/protein complexes and the function of the molecular machine. Eventually, a large number of MB-DNA strands are captured by the sensor surface, generating drastically amplified electrochemical responses from the MB tags for sensitive detection of thrombin. Our signal amplified sensor is completely enzyme-free and shows a dynamic range from 5 pM to 1 nM with a detection limit of 1.7 pM. Such sensor also has a high specificity for thrombin assay in serum samples. By changing the affinity probe pairs, the developed sensor can be readily expanded as a more general platform for sensitive detection of different types of proteins.

  1. PM2.5 and PM10 Emission from agricultural soils by wind erosion

    USDA-ARS?s Scientific Manuscript database

    Soil tillage and wind erosion are a major source of particulate matter less than 2.5 and 10 µm (PM2.5 and PM10) emission from cultivated soil. Fifteen cultivated soils collected from 5 states were tested as crushed (<2.0 mm) and uncrushed (natural aggregation) at 8, 10, and 13 m s-1 wind velocity in...

  2. PM2.5 and PM10 emission from agricultural soils by wind erosion

    USDA-ARS?s Scientific Manuscript database

    Soil tillage and wind erosion are a major source of particulate matter less than 2.5 and 10 µm (PM2.5 and PM10) emission from cultivated soil. Fifteen cultivated soils collected from 5 states were tested as crushed (<2.0 mm) and uncrushed (natural aggregation) at 8, 10, and 13 m s-1 wind velocity in...

  3. 75 FR 14259 - Transportation Conformity Rule PM2.5

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-24

    ... Protection Agency 40 CFR Part 93 Transportation Conformity Rule PM2.5 and PM10 Amendments; Final Rule #0;#0...; ] ENVIRONMENTAL PROTECTION AGENCY 40 CFR Part 93 RIN 2060-AP29 Transportation Conformity Rule PM 2.5 and PM 10... amending the transportation conformity rule to finalize provisions that were proposed on May 15,...

  4. Functional specification of the Performance Measurement (PM) module

    NASA Technical Reports Server (NTRS)

    Berliner, J. E.

    1980-01-01

    The design of the Performance Measurement Module is described with emphasis on what the PM Module would do, and what it would look like to the user. The PM Module as described could take several man-years to develop. An evolutionary approach to the implementation of the PM Module is presented which would provide an operational baseline PM Module within a few months.

  5. Fault Tolerant State Machines

    NASA Technical Reports Server (NTRS)

    Burke, Gary R.; Taft, Stephanie

    2004-01-01

    State machines are commonly used to control sequential logic in FPGAs and ASKS. An errant state machine can cause considerable damage to the device it is controlling. For example in space applications, the FPGA might be controlling Pyros, which when fired at the wrong time will cause a mission failure. Even a well designed state machine can be subject to random errors us a result of SEUs from the radiation environment in space. There are various ways to encode the states of a state machine, and the type of encoding makes a large difference in the susceptibility of the state machine to radiation. In this paper we compare 4 methods of state machine encoding and find which method gives the best fault tolerance, as well as determining the resources needed for each method.

  6. Machine tool locator

    DOEpatents

    Hanlon, John A.; Gill, Timothy J.

    2001-01-01

    Machine tools can be accurately measured and positioned on manufacturing machines within very small tolerances by use of an autocollimator on a 3-axis mount on a manufacturing machine and positioned so as to focus on a reference tooling ball or a machine tool, a digital camera connected to the viewing end of the autocollimator, and a marker and measure generator for receiving digital images from the camera, then displaying or measuring distances between the projection reticle and the reference reticle on the monitoring screen, and relating the distances to the actual position of the autocollimator relative to the reference tooling ball. The images and measurements are used to set the position of the machine tool and to measure the size and shape of the machine tool tip, and examine cutting edge wear. patent

  7. PM2.5 of ambient origin: estimates and exposure errors relevant to PM epidemiology.

    PubMed

    Meng, Qing Yu; Turpin, Barbara J; Polidori, Andrea; Lee, Jong Hoon; Weisel, Clifford; Morandi, Maria; Colome, Steven; Stock, Thomas; Winer, Arthur; Zhang, Jenfeng

    2005-07-15

    Epidemiological studies routinely use central-site particulate matter (PM) as a surrogate for exposure to PM of ambient (outdoor) origin. Below we quantify exposure errors that arise from variations in particle infiltration to aid evaluation of the use of this surrogate, rather than actual exposure, in PM epidemiology. Measurements from 114 homes in three cities from the Relationship of Indoor, Outdoor and Personal Air (RIOPA) study were used. Indoor PM2.5 of outdoor origin was calculated as follows: (1) assuming a constant infiltration factor, as would be the case if central-site PM were a "perfect surrogate" for exposure to outdoor particles; (2) including variations in measured air exchange rates across homes; (3) also incorporating home-to-home variations in particle composition, and (4) calculating sample-specific infiltration factors. The final estimates of PM2.5 of outdoor origin take into account variations in building construction, ventilation practices, and particle properties that result in home-to-home and day-to-day variations in particle infiltration. As assumptions became more realistic (from the first, most constrained model to the fourth, least constrained model), the mean concentration of PM2.5 of outdoor origin increased. Perhaps more importantly, the bandwidth of the distribution increased. These results quantify several ways in which the use of central site PM results in underestimates of the ambient PM2.5 exposure distribution bandwidth. The result is larger uncertainties in relative risk factors for PM2.5 than would occur if epidemiological studies used more accurate exposure measures. In certain situations this can lead to bias.

  8. PM2.5 of ambient origin: Estimates and exposure errors relevant to PM epidemiology

    PubMed Central

    Meng, Qing Yu; Turpin, Barbara J.; Polidori, Andrea; Lee, Jong Hoon; Weisel, Clifford; Morandi, Maria; Colome, Steven; Stock, Thomas; Winer, Arthur; Zhang, Jim

    2008-01-01

    Epidemiological studies routinely use central-site particulate matter (PM) as a surrogate for exposure to PM of ambient (outdoor) origin. Below we quantify exposure errors that arise from variations in particle infiltration to aid evaluation of the use of this surrogate, rather than actual exposure, in PM epidemiology. Measurements from 114 homes in 3 cities from the Relationship of Indoor, Outdoor and Personal Air (RIOPA) study were used. Indoor PM2.5 of outdoor origin was calculated: 1) assuming a constant infiltration factor, as would be the case if central-site PM were a “perfect surrogate” for exposure to outdoor particles; 2) including variations in measured air exchange rates across homes; 3) also incorporating home-to-home variations in particle composition, and 4) calculating sample-specific infiltration factors. The final estimates of PM2.5 of outdoor origin take into account variations in building construction, ventilation practices, and particle properties that result in home-to-home and day-to-day variations in particle infiltration. As assumptions became more realistic (from the first, most constrained model to the fourth, least constrained model), the mean concentration of PM2.5 of outdoor origin increased. Perhaps more importantly, the bandwidth of the distribution increased. These results quantify several ways in which the use of central site PM results in underestimates of the ambient PM2.5 exposure distribution bandwidth. The result is larger uncertainties in relative risk factors for PM2.5 than would occur if epidemiological studies used more accurate exposure measures. In certain situations this can lead to bias. PMID:16082937

  9. Breeding highbush blueberry cultivars adapted to machine harvest for the fresh market

    USDA-ARS?s Scientific Manuscript database

    In recent years, world blueberry production has been split evenly between processing and fresh fruit markets. Machine harvest of highbush blueberry [northern highbush (NHB, Vaccinium corymbosum L.), southern highbush (SHB, Vaccinium corymbosum interspecific hybrids), and rabbiteye (RE, Vaccinium vi...

  10. Chaotic Boltzmann machines

    PubMed Central

    Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

    2013-01-01

    The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

  11. Perspex machine II: visualization

    NASA Astrophysics Data System (ADS)

    Anderson, James A. D. W.

    2004-12-01

    We review the perspex machine and improve it by reducing its halting conditions to one condition. We also introduce a data structure, called the "access column," that can accelerate a wide class of perspex programs. We show how the perspex can be visualised as a tetrahedron, artificial neuron, computer program, and as a geometrical transformation. We discuss the temporal properties of the perspex machine, dissolve the famous time travel paradox, and present a hypothetical time machine. Finally, we discuss some mental properties and show how the perspex machine solves the mind-body problem and, specifically, how it provides one physical explanation for the occurrence of paradigm shifts.

  12. Perspex machine II: visualization

    NASA Astrophysics Data System (ADS)

    Anderson, James A. D. W.

    2005-01-01

    We review the perspex machine and improve it by reducing its halting conditions to one condition. We also introduce a data structure, called the "access column," that can accelerate a wide class of perspex programs. We show how the perspex can be visualised as a tetrahedron, artificial neuron, computer program, and as a geometrical transformation. We discuss the temporal properties of the perspex machine, dissolve the famous time travel paradox, and present a hypothetical time machine. Finally, we discuss some mental properties and show how the perspex machine solves the mind-body problem and, specifically, how it provides one physical explanation for the occurrence of paradigm shifts.

  13. Machine listening intelligence

    NASA Astrophysics Data System (ADS)

    Cella, C. E.

    2017-05-01

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

  14. Progress in machine consciousness.

    PubMed

    Gamez, David

    2008-09-01

    This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper.

  15. Chaotic Boltzmann machines

    NASA Astrophysics Data System (ADS)

    Suzuki, Hideyuki; Imura, Jun-Ichi; Horio, Yoshihiko; Aihara, Kazuyuki

    2013-04-01

    The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented.

  16. Chaotic Boltzmann machines.

    PubMed

    Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

    2013-01-01

    The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented.

  17. Modernization of machines laboratory

    SciTech Connect

    Mako, T.J.; Kasten, D.; Kent, J.C.; Turner, S.C. )

    1992-01-01

    The Ohio State University has maintained an undergraduate machinery laboratory using 10 to 15 hp AC and DC machines. a recent gift from the American Electric Power Service Corporation is being used to modernize the laboratory. This modernization includes the electrical and mechanical refurbishment of the 10 to 15 hp machines, the development of a computerized data acquisition system, and the specification and purchase of a three-machine (1 to 2 hp) table-top unit with variable speed drives. This paper will present information about the computerized data acquisition system and how it is being used by the students to investigate machine characteristics.

  18. EVALUATION OF PM 10, PM 2.5 AND PM 10-2.5 MEASUREMENTS USING A PASSIVE PARTICULATE SAMPLER

    EPA Science Inventory

    This is an extended abstract of a presentation made at the Air and Waste Management Association's Symposium on Air Quality Measurement Methods and Technology, Durham, NC, May 9-11, 2006. The abstract describes field evaluations of a passive aerosol sampler for PM2.5, P...

  19. Energy harvesting using AC machines with high effective pole count

    NASA Astrophysics Data System (ADS)

    Geiger, Richard Theodore

    In this thesis, ways to improve the power conversion of rotating generators at low rotor speeds in energy harvesting applications were investigated. One method is to increase the pole count, which increases the generator back-emf without also increasing the I2R losses, thereby increasing both torque density and conversion efficiency. One machine topology that has a high effective pole count is a hybrid "stepper" machine. However, the large self inductance of these machines decreases their power factor and hence the maximum power that can be delivered to a load. This effect can be cancelled by the addition of capacitors in series with the stepper windings. A circuit was designed and implemented to automatically vary the series capacitance over the entire speed range investigated. The addition of the series capacitors improved the power output of the stepper machine by up to 700%. At low rotor speeds, with the addition of series capacitance, the power output of the hybrid "stepper" was more than 200% that of a similarly sized PMDC brushed motor. Finally, in this thesis a hybrid lumped parameter / finite element model was used to investigate the impact of number, shape and size of the rotor and stator teeth on machine performance. A typical off-the-shelf hybrid stepper machine has significant cogging torque by design. This cogging torque is a major problem in most small energy harvesting applications. In this thesis it was shown that the cogging and ripple torque can be dramatically reduced. These findings confirm that high-pole-count topologies, and specifically the hybrid stepper configuration, are an attractive choice for energy harvesting applications.

  20. Predicting submicron air pollution indicators: a machine learning approach.

    PubMed

    Pandey, Gaurav; Zhang, Bin; Jian, Le

    2013-05-01

    The regulation of air pollutant levels is rapidly becoming one of the most important tasks for the governments of developing countries, especially China. Submicron particles, such as ultrafine particles (UFP, aerodynamic diameter ≤ 100 nm) and particulate matter ≤ 1.0 micrometers (PM1.0), are an unregulated emerging health threat to humans, but the relationships between the concentration of these particles and meteorological and traffic factors are poorly understood. To shed some light on these connections, we employed a range of machine learning techniques to predict UFP and PM1.0 levels based on a dataset consisting of observations of weather and traffic variables recorded at a busy roadside in Hangzhou, China. Based upon the thorough examination of over twenty five classifiers used for this task, we find that it is possible to predict PM1.0 and UFP levels reasonably accurately and that tree-based classification models (Alternating Decision Tree and Random Forests) perform the best for both these particles. In addition, weather variables show a stronger relationship with PM1.0 and UFP levels, and thus cannot be ignored for predicting submicron particle levels. Overall, this study has demonstrated the potential application value of systematically collecting and analysing datasets using machine learning techniques for the prediction of submicron sized ambient air pollutants.

  1. Motor vehicle contributions to ambient PM10 and PM2.5 at selected urban areas in the USA.

    PubMed

    Abu-Allaban, Mahmoud; Gillies, John A; Gertler, Alan W; Clayton, Russ; Proffitt, David

    2007-09-01

    A source apportionment study was carried out to estimate the contribution of motor vehicles to ambient particulate matter (PM) in selected urban areas in the USA. Measurements were performed at seven locations during the period September 7, 2000 through March 9, 2001. Measurements included integrated PM(2.5) and PM(10) concentrations and polycyclic aromatic hydrocarbons (PAHs). Ambient PM(2.5) and PM(10) were apportioned to their local sources using the chemical mass balance (CMB) receptor model and compared with results obtained using scanning electron microscopy (SEM). Results indicate that PM(2.5) components were mainly from combustion sources, including motor vehicles, and secondary species (nitrates and sulfates). PM(10) consisted mainly of geological material, in addition to emissions from combustion sources. The fractional contributions of motor vehicles to ambient PM were estimated to be in the range from 20 to 76% and from 35 to 92% for PM(2.5) and PM(10), respectively.

  2. Drum cutter mining machine

    SciTech Connect

    Oberste-beulmann, K.; Schupphaus, H.

    1980-02-19

    A drum cutter mining machine includes a machine frame with a winch having a drive wheel to engage a rack or chain which extends along the path of travel by the mining machine to propel the machine along a mine face. The mining machine is made up of discrete units which include a machine body and machine housings joined to opposite sides of the machine body. The winch is either coupled through a drive train with a feed drive motor or coupled to the drive motor for cutter drums. The machine housings each support a pivot shaft coupled by an arm to a drum cutter. One of these housings includes a removable end cover and a recess adapted to receive a support housing for a spur gear system used to transmit torque from a feed drive motor to a reduction gear system which is, in turn, coupled to the drive wheel of the winch. In one embodiment, a removable end cover on the machine housing provides access to the feed drive motor. The feed drive motor is arranged so that the rotational axis of its drive output shaft extends transversely to the stow side of the machine frame. In another embodiment, the reduction gear system is arranged at one side of the pivot shaft for the cutter drum while the drive motor therefor is arranged at the other side of the pivot shaft and coupled thereto through the spur gear system. In a further embodiment, the reduction gear system is disposed between the feed motor and the pivot shaft.

  3. Discrete phase model representation of particulate matter (PM) for simulating PM separation by hydrodynamic unit operations.

    PubMed

    Dickenson, Joshua A; Sansalone, John J

    2009-11-01

    Modeling the separation of dilute particulate matter (PM) has been a topic of interest since the introduction of unit operations for clarification of rainfall-runoff. One consistent yet controversial issue is the representation of PM and PM separation mechanisms for treatment. While Newton's Law and surface overflow rate were utilized, many historical models represented PM as a lumped gravimetric index largely out of economy and lack of particle analysis methods. As a result such models did not provide information about particle fate in or through a unit operation. In this study, PM discrete phase modeling (DPM) and computational fluid dynamics (CFD) are applied to model PM fate as a function of particle size and flow rate in two common types of hydrodynamic separator (HS) units. The study examines the discretization requirements (as a discretization number, DN) and errors for particle size distributions (PSDs) that range from the common heterodisperse to a monodisperse PSD. PSDs are categorized based on granulometric indices. Results focus on ensuring modeling accuracy while examining the role of size dispersivity and overall PM fineness on DN requirements. The fate of common heterodisperse PSDs is accurately predicted for a DN of 16, whereas a single particle size index, commonly the d(50m), is limited to monodisperse PSDs in order to achieve similar accuracy.

  4. Diamond machine tool face lapping machine

    DOEpatents

    Yetter, H.H.

    1985-05-06

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

  5. Particulate matter in California: part 2--Spatial, temporal, and compositional patterns of PM2.5, PM10-2.5, and PM10.

    PubMed

    Motallebi, Nehzat; Taylor, Clinton A; Croes, Bart E

    2003-12-01

    Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM2.5 and PM10 concentrations range from 3 to 10 microg/m3 and from 5 to 18 microg/m3, respectively. In the urban areas of California, annual-averages for PM2.5 range from 7 to 30 microg/m3, with observed 24-hr peaks reaching levels as high as 160 microg/m3. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM2.5 concentrations that are more prolonged and regional in nature. PM2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO4(2-)) and nitrate (NO3-) components of PM2.5 and PM10) and correlate with reductions in ambient levels of oxides of sulfur (SOx) and oxides of nitrogen (NOx). Annual averages for PM10-2.5 and PM10 exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.

  6. PM2.5 emission elemental composition.

    PubMed

    Mugica, Violetta; Mugica, Francisco; Torres, M; Figueroa, J

    2008-03-17

    A field study was carried out from 2003 to 2004 with the aim to develop the PM2.5 emission source profiles from light duty gasoline and heavy-duty diesel vehicles, as well as emission source profiles from waste incineration, wood burning and meatbroiling. Over 25 chemical species were quantified from the fine particles emitted by the different combustion sources investigated, including organic and elemental carbon, ions and elements. The OC/TC ratio found in the different PM2.5 profiles was dissimilar as well as the sulfate, nitrate, ammonium, soil species and trace element content. Consequently these combustion emission profiles could be used in source reconciliation studies for fine particles.A field study was carried out from 2003 to 2004 with the aim to develop the PM2.5 emission source profiles from light-duty gasoline and heavy-duty diesel vehicles, as well as emission source profiles from waste incineration, wood burning, LP gas combustion, and meat broiling. Over 25 chemical species were quantified from the fine particles emitted by the different combustion sources investigated, including organic and elemental carbon, ions, and elements. The OC/TC ratio found in the different PM2.5 profiles was dissimilar as well as the sulfate, nitrate, ammonium, soil species, and trace element content. Consequently, these combustion emission profiles could be used in source reconciliation studies for fine particles.

  7. P/M Materials for Wear Applications

    SciTech Connect

    Hawk, Jeffrey A.

    2000-10-01

    Wear resistant materials usually consist of either very hard homogeneous single phase materials (e.g., ceramics like Al2O3, SiC, etc.) or heterogenous materials (e.g., white cast irons, composites or cermets, or composite-type materials), typically with a hard reinforcing phase dispersed in a softer matrix. In both instances, the result is the same, less penetration of the abrasive into the surface of the material being worn. Composite type materials can be produced using either a melting/solidification scheme or through powder metallurgy (P/M) techniques. In either case the result is the same, a microstructure that consists of a high volume fraction of hard, usually brittle, second phase particles in a softer matrix. However, P/M can be used to create a wider range of these materials than can melting/solidification, because in P/M processing, the desired phase does not have to be precipitated during solidification. Thus, more materials can be produced with higher volume fractions of reinforcing phases. Obviously, other factors like reinforcement size, matrix-particle interfacial strength, plastic accommodation of the matrix, etc. become important in the wear behavior of these materials. Various categories of P/M wear resistant materials will be discussed, and their wear behavior will be compared against traditional wear resistant cast materials like white cast iron and tool steels.

  8. Impacts of PM concentrations on visibility impairment

    NASA Astrophysics Data System (ADS)

    Jie, Guo; Wang, Mei-mei; Han, Ye-Xing; Yu, Zhi-Wei; Tang, Huai-Wu

    2016-11-01

    In the paper, an accurate and sensitive cavity attenuated phase shift spectroscopy (CAPS) sensor was used to monitor the atmospheric visibility. The CAPS system mainly includes a LED light source, a band-pass filter, an optical resonant cavity (composed of two high mirror, reflectivity is greater than 99.99%), a photoelectric detector and a lock-in amplifier. The 2L/min flow rate, the optical sensor rise and fall response time is about 15 s, so as to realize the fast measurement of visibility. An Allan variance analysis was carried out evaluating the optical system stability (and hence the maximum averaging time for the minimum detection limit) of the CAPS system. The minima ( 0.1 Mm-1) in the Allan plots show the optimum average time ( 100s) for optimum detection performance of the CAPS system. During this period, the extinction coefficient was correlated with PM2.5 mass (0.88), the extinction coefficient was correlated with PM10 mass (0.85). The atmospheric visibility was correlated with PM2.5 mass (0.74). The atmospheric visibility was correlated with PM10 mass (0.66).

  9. INTERPOLATING VANCOUVER'S DAILY AMBIENT PM 10 FIELD

    EPA Science Inventory

    In this article we develop a spatial predictive distribution for the ambient space- time response field of daily ambient PM10 in Vancouver, Canada. Observed responses have a consistent temporal pattern from one monitoring site to the next. We exploit this feature of the field b...

  10. INTERPOLATING VANCOUVER'S DAILY AMBIENT PM 10 FIELD

    EPA Science Inventory

    In this article we develop a spatial predictive distribution for the ambient space- time response field of daily ambient PM10 in Vancouver, Canada. Observed responses have a consistent temporal pattern from one monitoring site to the next. We exploit this feature of the field b...

  11. Spatial and seasonal variation of particulate matter (PM10 and PM2.5) in Middle Eastern classrooms

    NASA Astrophysics Data System (ADS)

    Elbayoumi, Maher; Ramli, Nor Azam; Md Yusof, Noor Faizah Fitri; Al Madhoun, Wesam

    2013-12-01

    Monitoring of PM10 and PM2.5 particularly in school microenvironments is extremely important due to their impact on the global burden of disease. PM10 and PM2.5 levels were monitored inside and outside the classrooms of twelve naturally ventilated schools located in Gaza strip, Palestine. The measurements were carried out using hand held particulate matter instrument during fall, winter and spring seasons from October 2011 to May 2012. The average concentration of indoor PM10 was 349.49 (±196.57) μg m-3 and for PM2.5 was 103.96 (±84.96) μg m-3. The indoor/outdoor ratios for PM10 and PM2.5 were found to be much greater than 1.00 for all case study schools due to resuspension of deposited particles from the floors. Furthermore, strong correlations were found between indoor-outdoor PM10 and PM2.5. The variations of PM10 and PM2.5 concentrations were significant for the three seasons. During winter, the mean indoor PM10 was 1.30 and 2.50 times higher than fall and spring concentrations respectively. Meanwhile, PM2.5 concentration in winter was 3.00 times higher than fall and spring concentrations. In relation to spatial variation, the concentration of PM10 in the lower storey level was significantly higher than the classrooms located in the higher storey level.

  12. BRITISH MOLDING MACHINE, PBQ AUTOMATIC COPE AND DRAG MOLDING MACHINE ...

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

    BRITISH MOLDING MACHINE, PBQ AUTOMATIC COPE AND DRAG MOLDING MACHINE MAKES BOTH MOLD HALVES INDIVIDUALLY WHICH ARE LATER ROTATED, ASSEMBLED, AND LOWERED TO POURING CONVEYORS BY ASSISTING MACHINES. - Southern Ductile Casting Company, Casting, 2217 Carolina Avenue, Bessemer, Jefferson County, AL

  13. BRITISH MOLDING MACHINE, PBQ AUTOMATIC COPE AND DRAG MOLDING MACHINE ...

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

    BRITISH MOLDING MACHINE, PBQ AUTOMATIC COPE AND DRAG MOLDING MACHINE MAKES BOTH MOLD HALVES INDIVIDUALLY WHICH ARE LATER ROTATED, ASSEMBLED, AND LOWERED TO POURING CONVEYORS BY ASSISTING MACHINES. - Southern Ductile Casting Company, Casting, 2217 Carolina Avenue, Bessemer, Jefferson County, AL

  14. 14. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

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

    14. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to north (90mm lens). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

  15. A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

    DTIC Science & Technology

    2008-11-01

    retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach

  16. Modeling Reluctance-Assisted PM Motors

    SciTech Connect

    Otaduy, P.J.

    2006-01-13

    This report contains a derivation of the fundamental equations used to calculate the base speed, torque delivery, and power output of a reluctance-assisted PM motor which has a saliency ratio greater than 1 as a function of its terminal voltage, current, voltage-phase angle, and current-phase angle. The equations are applied to model Motor X using symbolically-oriented methods with the computer tool Mathematica to determine: (1) the values of current-phase angle and voltage-phase angle that are uniquely determined once a base speed has been selected; (2) the attainable current in the voltage-limited region above base speed as a function of terminal voltage, speed, and current-phase angle; (3) the attainable current in the voltage-limited region above base speed as a function of terminal voltage, speed, and voltage-phase angle; (4) the maximum-power output in the voltage-limited region above base speed as a function of speed; (5) the optimal voltage-phase angle in the voltage-limited region above base speed required to obtain maximum-power output; (6) the maximum-power speed curve which was linear from rest to base speed in the current limited region below base speed; (7) the current angle as a function of saliency ratio in the current-limited region below base speed; and (8) the torque as a function of saliency ratio which is almost linear in the current-limited region below base speed. The equations were applied to model Motor X using numerically-oriented methods with the computer tool LabVIEW. The equations were solved iteratively to find optimal current and voltage angles that yield maximum power and maximum efficiency from rest through the current-limited region to base speed and then through the voltage-limited region to high-rotational speeds. Currents, voltages, and reluctance factors were all calculated and external loops were employed to perform additional optimization with respect to PM pitch angle (magnet fraction) and with respect to magnet strength

  17. THE TEACHING MACHINE.

    ERIC Educational Resources Information Center

    KLEIN, CHARLES; WAYNE, ELLIS

    THE ROLE OF THE TEACHING MACHINE IS COMPARED WITH THE ROLE OF THE PROGRAMED TEXTBOOK. THE TEACHING MACHINE IS USED FOR INDIVIDUAL INSTRUCTION, CONTAINS AND PRESENTS PROGRAM CONTENT IN STEPS, PROVIDES A MEANS WHEREBY THE STUDENT MAY RESPOND TO THE PROGRAM, PROVIDES THE STUDENT WITH IMMEDIATE INFORMATION OF SOME KIND CONCERNING HIS RESPONSE THAT CAN…

  18. Simple Machines Made Simple.

    ERIC Educational Resources Information Center

    St. Andre, Ralph E.

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

  19. Machining heavy plastic sections

    NASA Technical Reports Server (NTRS)

    Stalkup, O. M.

    1967-01-01

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

  20. Technique for Machining Glass

    NASA Technical Reports Server (NTRS)

    Rice, S. H.

    1982-01-01

    Process for machining glass with conventional carbide tools requires a small quantity of a lubricant for aluminum applied to area of glass to be machined. A carbide tool is then placed against workpiece with light pressure. Tool is raised periodically to clear work of glass dust and particles. Additional lubricant is applied as it is displaced.

  1. Simple Machine Junk Cars

    ERIC Educational Resources Information Center

    Herald, Christine

    2010-01-01

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

  2. Human Machine Learning Symbiosis

    ERIC Educational Resources Information Center

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

    2017-01-01

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

  3. Simple Machines Made Simple.

    ERIC Educational Resources Information Center

    St. Andre, Ralph E.

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

  4. Machine Translation Project

    NASA Technical Reports Server (NTRS)

    Bajis, Katie

    1993-01-01

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

  5. Compound taper milling machine

    NASA Technical Reports Server (NTRS)

    Campbell, N. R.

    1969-01-01

    Simple, inexpensive milling machine tapers panels from a common apex to a uniform height at panel edge regardless of the panel perimeter configuration. The machine consists of an adjustable angled beam upon which the milling tool moves back and forth above a rotatable table upon which the workpiece is held.

  6. The Hooey Machine.

    ERIC Educational Resources Information Center

    Scarnati, James T.; Tice, Craig J.

    1992-01-01

    Describes how students can make and use Hooey Machines to learn how mechanical energy can be transferred from one object to another within a system. The Hooey Machine is made using a pencil, eight thumbtacks, one pushpin, tape, scissors, graph paper, and a plastic lid. (PR)

  7. Semantics via Machine Translation

    ERIC Educational Resources Information Center

    Culhane, P. T.

    1977-01-01

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

  8. Stirling machine operating experience

    SciTech Connect

    Ross, B.; Dudenhoefer, J.E.

    1994-09-01

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

  9. An asymptotical machine

    NASA Astrophysics Data System (ADS)

    Cristallini, Achille

    2016-07-01

    A new and intriguing machine may be obtained replacing the moving pulley of a gun tackle with a fixed point in the rope. Its most important feature is the asymptotic efficiency. Here we obtain a satisfactory description of this machine by means of vector calculus and elementary trigonometry. The mathematical model has been compared with experimental data and briefly discussed.

  10. Biological Molecular Machines

    NASA Astrophysics Data System (ADS)

    Kurzyński, Michał

    2007-11-01

    Like small molecules taking part in usual chemical reactions, biological molecular machines perform their functions owing to thermal fluctuations and the only difference consists in more complex and specially organized internal dynamics. It is this dynamics that determines processes of free energy transduction in molecular machines. The case of the actomyosin motor is considered in some detail.

  11. Machine Translation Project

    NASA Technical Reports Server (NTRS)

    Bajis, Katie

    1993-01-01

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

  12. Technique for Machining Glass

    NASA Technical Reports Server (NTRS)

    Rice, S. H.

    1982-01-01

    Process for machining glass with conventional carbide tools requires a small quantity of a lubricant for aluminum applied to area of glass to be machined. A carbide tool is then placed against workpiece with light pressure. Tool is raised periodically to clear work of glass dust and particles. Additional lubricant is applied as it is displaced.

  13. Simple Machine Junk Cars

    ERIC Educational Resources Information Center

    Herald, Christine

    2010-01-01

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

  14. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

    NASA Astrophysics Data System (ADS)

    Ausati, Shadi; Amanollahi, Jamil

    2016-10-01

    Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.

  15. Micro-machining.

    PubMed

    Brinksmeier, Ekkard; Preuss, Werner

    2012-08-28

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

  16. Introduction to machine learning.

    PubMed

    Baştanlar, Yalin; Ozuysal, Mustafa

    2014-01-01

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

  17. The powdery mildew resistance gene Pm8 derived from rye is suppressed by its wheat ortholog Pm3.

    PubMed

    Hurni, Severine; Brunner, Susanne; Stirnweis, Daniel; Herren, Gerhard; Peditto, David; McIntosh, Robert A; Keller, Beat

    2014-09-01

    The powdery mildew resistance gene Pm8 derived from rye is located on a 1BL.1RS chromosome translocation in wheat. However, some wheat lines with this translocation do not show resistance to isolates of the wheat powdery mildew pathogen avirulent to Pm8 due to an unknown genetically dominant suppression mechanism. Here we show that lines with suppressed Pm8 activity contain an intact and expressed Pm8 gene. Therefore, the absence of Pm8 function in certain 1BL.1RS-containing wheat lines is not the result of gene loss or mutation but is based on suppression. The wheat gene Pm3, an ortholog of rye Pm8, suppressed Pm8-mediated powdery mildew resistance in lines containing Pm8 in a transient single-cell expression assay. This result was further confirmed in transgenic lines with combined Pm8 and Pm3 transgenes. Expression analysis revealed that suppression is not the result of gene silencing, either in wheat 1BL.1RS translocation lines carrying Pm8 or in transgenic genotypes with both Pm8 and Pm3 alleles. In addition, a similar abundance of the PM8 and PM3 proteins in single or double homozygous transgenic lines suggested that a post-translational mechanism is involved in suppression of Pm8. Co-expression of Pm8 and Pm3 genes in Nicotiana benthamiana leaves followed by co-immunoprecipitation analysis showed that the two proteins interact. Therefore, the formation of a heteromeric protein complex might result in inefficient or absent signal transmission for the defense reaction. These data provide a molecular explanation for the suppression of resistance genes in certain genetic backgrounds and suggest ways to circumvent it in future plant breeding.

  18. Machine tool evaluation and machining operation development

    SciTech Connect

    Morris, T.O.; Kegg, R.

    1997-03-15

    The purpose of this CRADA was to support Cincinnati Milacron`s needs in fabricating precision components, from difficult to machine materials, while maintaining and enhancing the precision manufacturing skills of the Oak Ridge Complex. Oak Ridge and Cincinnati Milacron personnel worked in a team relationship wherein each contributed equally to the success of the program. Process characterization, control technologies, machine tool capabilities, and environmental issues were the primary focus areas. In general, Oak Ridge contributed a wider range of expertise in machine tool testing and monitoring, and environmental testing on machining fluids to the defined tasks while Cincinnati Milacron personnel provided equipment, operations-specific knowledge and shop-floor services to each task. Cincinnati Milacron was very pleased with the results of all of the CRADA tasks. However, some of the environmental tasks were not carried through to a desired completion due to an expanding realization of need as the work progressed. This expansion of the desired goals then exceeded the time length of the CRADA. Discussions are underway on continuing these tasks under either a Work for Others agreement or some alternate funding.

  19. INDOOR-OUTDOOR PM2.5 AND PM10 IN NEW YORK CITY

    EPA Science Inventory

    PM health effects have been reported to be highest in sensitive subpopulations such as COPD patients. Since such individuals are spend higher proportions of their day indoors, the relationship between indoor and outdoor concentrations is therefore particularly important. The ...

  20. INDOOR-OUTDOOR PM2.5 AND PM10 IN NEW YORK CITY

    EPA Science Inventory

    PM health effects have been reported to be highest in sensitive subpopulations such as COPD patients. Since such individuals are spend higher proportions of their day indoors, the relationship between indoor and outdoor concentrations is therefore particularly important. The ...

  1. Basic statistics of PM2.5 and PM10 in the atmosphere of Mexico City.

    PubMed

    Vega, E; Reyes, E; Sánchez, G; Ortiz, E; Ruiz, M; Chow, J; Watson, J; Edgerton, S

    2002-03-27

    The high levels of fine particulate matter in Mexico City are of concern since they may induce severe public health effects as well as the attenuation of visible light. Sequential filter samplers were used at six different sites from 23 February to 22 March 1997. The sampling campaign was carried out as part of the project 'Investigación sobre Materia Particulada y Deterioro Atmosferico-Aerosol and Visibility Evaluation Research'. This research was a cooperative project sponsored by PEMEX and by the US Department of Energy. Sampling sites represent the different land uses along the city, the northwest station, Tlalnepantla, is located in a mixed medium income residential and industrial area. The northeast station, Xalostoc, is located in a highly industrialized area, Netzahualcoyotl is located in a mixed land use area, mainly commercial and residential. Station La Merced is located in the commercial and administrative district downtown. The southwest station is located in the Pedregal de San Angel, in a high-income neighborhood, and the southeast station located in Cerro de la Estrella is a mixed medium income residential and commercial area. Samples were collected four times a day in Cerro de la Estrella (CES), La Merced (MER) and Xalostoc (XAL) with sampling periods of 6 h. In Pedregal (PED), Tlalnepantla (TLA) and Netzahualcoyot1 (NEZ) sampling periods were every 24 h. In this paper the basic statistics of PM2.5 and PM10 mass concentrations are presented. The average results showed that 49, 61, 46, 57, 51 and 44% of the PM10 consisted of PM2.5 for CES, MER, XAL, PED, TLA and NEZ, respectively. The 24-h average highest concentrations of PM25 and PM10 were registered at NEZ (184 and 267 microg/m3) and the lowest at PED (22 and 39 microg/m3). The highest PM10 correlations were between XAL-CES (0.79), PED-TLA (0.80). In contrast, the highest PM2.5 correlations were between CES-PED (0.74), MER-CES (0.73) and TLA-PED (0.72), showing a lower correlation than the PM10

  2. Source Apportionment and Elemental Composition of PM2.5 and PM10 in Jeddah City, Saudi Arabia

    PubMed Central

    Khodeir, Mamdouh; Shamy, Magdy; Alghamdi, Mansour; Zhong, Mianhua; Sun, Hong; Costa, Max; Chen, Lung-Chi; Maciejczyk, Polina

    2014-01-01

    This paper presents the first comprehensive investigation of PM2.5 and PM10 composition and sources in Saudi Arabia. We conducted a multi-week multiple sites sampling campaign in Jeddah between June and September, 2011, and analyzed samples by XRF. The overall mean mass concentration was 28.4 ± 25.4 μg/m3 for PM2.5 and 87.3 ± 47.3 μg/m3 for PM10, with significant temporal and spatial variability. The average ratio of PM2.5/PM10 was 0.33. Chemical composition data were modeled using factor analysis with varimax orthogonal rotation to determine five and four particle source categories contributing significant amount of for PM2.5 and PM10 mass, respectively. In both PM2.5 and PM10 sources were (1) heavy oil combustion characterized by high Ni and V; (2) resuspended soil characterized by high concentrations of Ca, Fe, Al, and Si; and (3) marine aerosol. The two other sources in PM2.5 were (4) Cu/Zn source; (5) traffic source identified by presence of Pb, Br, and Se; while in PM10 it was a mixed industrial source. To estimate the mass contributions of each individual source category, the CAPs mass concentration was regressed against the factor scores. Cumulatively, resuspended soil and oil combustion contributed 77 and 82% mass of PM2.5 and PM10, respectively. PMID:24634602

  3. TSP, PM10, and PM2.5 emissions from a beef cattle feedlot using the flux-gradient technique

    NASA Astrophysics Data System (ADS)

    Bonifacio, Henry F.; Maghirang, Ronaldo G.; Trabue, Steven L.; McConnell, Laura L.; Prueger, John H.; Bonifacio, Edna R.

    2015-01-01

    Emissions data on air pollutants from large open-lot beef cattle feedlots are limited. This research was conducted to determine emissions of total suspended particulates (TSP) and particulate matter (PM10 and PM2.5) from a commercial beef cattle feedlot in Kansas (USA). Vertical particulate concentration profiles at the feedlot were measured using gravimetric samplers, and micrometeorological parameters were monitored with eddy covariance instrumentation during the nine 4- to 5-day intensive sampling campaigns from May 2010 through September 2011. Emission fluxes were determined from the measured concentration gradients and meteorological parameters using the flux-gradient technique. PM ratios based on calculated emission fluxes were 0.28 for PM2.5/PM10, 0.12 for PM2.5/TSP, and 0.24 for PM10/TSP, indicating that a large fraction of the PM emitted at the studied feedlot was in the coarse range of aerodynamic diameter, >10 μm. Median daily emission factors were 57, 21, and 11 kg 1000-head (hd)-1 d-1 for TSP (n = 20 days), PM10 (n = 19 days), and PM2.5 (n = 11 days), respectively. Cattle pen surface moisture contents of at least 20-30% significantly reduced both TSP and PM10 emissions, but moisture's effect on PM2.5 emissions was not established due to difficulty in measuring PM2.5 concentrations under low-PM conditions.

  4. Development of novel alternative biodiesel fuels for reducing PM emissions and PM-related genotoxicity.

    PubMed

    Yang, Po-Ming; Wang, Chia-Chi; Lin, Ying-Chi; Jhang, Syu-Ruei; Lin, Li-Jung; Lin, Yuan-Chung

    2017-07-01

    This paper intend to investigate the effects of biodiesel fuel blends comprising of waste-cooking oil and butanol-diesel (B10W10-B10W40) under steady-state conditions. Both particulate organic carbon (OC) and PM including PM2.5 and PM10 significantly decreased with the increasing percentage of biodiesel fuel blends. The fuel blend of B10W40 also demonstrated the most effective function in reducing the emissions of PM10 and PM2.5 in the volume by 59.4% and 57.7%, respectively. Moreover, the emissions of nitrogen oxides decreased with the blending of B10W10-B10W40 (13.9-28.5%), while the brake specific fuel consumption was substantially increased (5.69-13.4%). The overall biological toxicity of PM10 generated from the fuel tested in this study was determined according to Single Cell Gel Electrophoresis assay in human alveolar basal epithelial A549 cells and micronucleus assay in CHO-K1 cells. In addition, the volume of more than 20% waste-cooking oil (B10W20 and B10W40) significantly reduced diesel-induced genotoxicity in lung cells and micronucleus formation in CHO-K1 cells. Collectively, these results indicated that biodiesel fuel blends with the butanol could be a potential alternative fuels for diesel engines because of its substantial property with a significant reduction of the PM-related genotoxicity and the emissions of PM, particulate OC, and NOX. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Hybrid Vehicles

    DTIC Science & Technology

    2008-12-08

    hybrid electric vehicles typically contain potentially hazardous levels of electrical voltage or current. It is important to protect the operators...60740. ITOP 2-2-607(1)41 is used for tracked vehicles. 13 TOP 2-1-003 08 December 2008 Hybrid electric vehicles often employ much more

  6. Variability of aerosols and chemical composition of PM10, PM2.5 and PM1 on a platform of the Prague underground metro

    NASA Astrophysics Data System (ADS)

    Cusack, M.; Talbot, N.; Ondráček, J.; Minguillón, M. C.; Martins, V.; Klouda, K.; Schwarz, J.; Ždímal, V.

    2015-10-01

    Measurements of PM10, PM2.5 and PM1 and particle number concentration and size distribution were measured for 24 h on a platform of the Prague underground metro in October 2013. The three PM fractions were analysed for major and minor elements, secondary inorganic aerosols (SIA) and total carbon (TC). Measurements were performed both when the metro was inoperative and closed to the public (referred to as background), and when the metro was in operation and open to passengers. PM concentrations were elevated during both periods, but were substantially increased in the coarse fraction during hours when the metro was in operation. Average PM concentrations were 214.8, 93.9 and 44.8 μg m-3 for PM10, PM2.5 and PM1, respectively (determined gravimetrically). Average particle number concentrations were 8.5 × 103 cm-3 for background hours and 11.5 × 103 cm-3 during operational hours. Particle number concentrations were found to not vary as significantly as PM concentrations throughout the day. Variations in PM were strongly governed by passing trains, with highest concentrations recorded during rush hour. When trains were less frequent, PM concentrations were shown to fluctuate in unison with the entrance and exit of trains (as shown by wind velocity measured on the platform). PM was found to be highly enriched with iron, especially in the coarse fraction, comprising 46% of PM10 (98.9 μg m-3). This reduces to 6.7 μg m-3 during background hours, proving that the trains themselves were the main source of iron, most probably from wheel-rail mechanical abrasion. Other enriched elements relative to background hours included Ba, Cu, Mn, Cr, Mo, Ni and Co, among others. Many of these elements exhibited a similar size distribution, further indicating their sources were common and were attributed to train operations.

  7. Characterization of PAHs and metals in indoor/outdoor PM10/PM2.5/PM1 in a retirement home and a school dormitory.

    PubMed

    Hassanvand, Mohammad Sadegh; Naddafi, Kazem; Faridi, Sasan; Nabizadeh, Ramin; Sowlat, Mohammad Hossein; Momeniha, Fatemeh; Gholampour, Akbar; Arhami, Mohammad; Kashani, Homa; Zare, Ahad; Niazi, Sadegh; Rastkari, Noushin; Nazmara, Shahrokh; Ghani, Maryam; Yunesian, Masud

    2015-09-15

    In the present work, we investigated the characteristics of polycyclic aromatic hydrocarbons (PAHs) and metal(loid)s in indoor/outdoor PM10, PM2.5, and PM1 in a retirement home and a school dormitory in Tehran from May 2012 to May 2013. The results indicated that the annual levels of indoor and outdoor PM10 and PM2.5 were much higher than the guidelines issued by the World Health Organization (WHO). The most abundant detected metal(loid)s in PM were Si, Fe, Zn, Al, and Pb. We found higher percentages of metal(loid)s in smaller size fractions of PM. Additionally, the results showed that the total PAHs (ƩPAHs) bound to PM were predominantly (83-88%) found in PM2.5, which can penetrate deep into the alveolar regions of the lungs. In general, carcinogenic PAHs accounted for 40-47% of the total PAHs concentrations; furthermore, the smaller the particle size, the higher the percentage of carcinogenic PAHs. The percentages of trace metal(loid)s and carcinogenic PAHs in PM2.5 mass were almost twice as high as those in PM10. This can most likely be responsible for the fact that PM2.5 can cause more adverse health effects than PM10 can. The average BaP-equivalent carcinogenic (BaP-TEQ) levels both indoors and outdoors considerably exceeded the maximum permissible risk level of 1 ng/m(3) of BaP. The enrichment factors and diagnostic ratios indicated that combustion-related anthropogenic sources, such as gasoline- and diesel-fueled vehicles as well as natural gas combustion, were the major sources of PAHs and trace metal(loid)s bound to PM.

  8. Machine Learning and Radiology

    PubMed Central

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

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

  9. The Basic Anaesthesia Machine

    PubMed Central

    Gurudatt, CL

    2013-01-01

    After WTG Morton's first public demonstration in 1846 of use of ether as an anaesthetic agent, for many years anaesthesiologists did not require a machine to deliver anaesthesia to the patients. After the introduction of oxygen and nitrous oxide in the form of compressed gases in cylinders, there was a necessity for mounting these cylinders on a metal frame. This stimulated many people to attempt to construct the anaesthesia machine. HEG Boyle in the year 1917 modified the Gwathmey's machine and this became popular as Boyle anaesthesia machine. Though a lot of changes have been made for the original Boyle machine still the basic structure remains the same. All the subsequent changes which have been brought are mainly to improve the safety of the patients. Knowing the details of the basic machine will make the trainee to understand the additional improvements. It is also important for every practicing anaesthesiologist to have a thorough knowledge of the basic anaesthesia machine for safe conduct of anaesthesia. PMID:24249876

  10. The basic anaesthesia machine.

    PubMed

    Gurudatt, Cl

    2013-09-01

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

  11. Lung response to coarse PM: Bioassay in mice

    SciTech Connect

    Wegesser, Teresa C.; Last, Jerold A.

    2008-07-15

    Particulate matter (PM) elicits inflammatory and toxic responses in the lung specific to its constituents, which can vary by region, time, and particle size. To identify the mechanism of toxicity in PM collected in a rural area in the San Joaquin Valley of Central California, we studied coarse particles of 2.5-10 {mu}m diameter (PM{sub 2.5}-PM{sub 10}). Potential pro-inflammatory and toxic effects of PM{sub 2.5}-PM{sub 10} in the lung were investigated using intratracheally instilled mice. We determined total and differential cell profiles and inflammatory chemokines in lung lavage fluid, and biomarkers of toxicity resulting from coarse PM exposure. Responses of the mice were readily observed with total doses of 25-50 {mu}g of PM per mouse. Changes in pro-inflammatory cellular profiles and chemokines showed both dose and time responses; peak responses were observed 24 h after PM instillation, with recovery as early as 48 h. Furthermore, macrophage inflammatory protein (MIP-2) profiles following PM exposures were correlated to levels of measured macrophages and neutrophils recovered from lung lavage fluid of PM-treated animals. Our data suggest that pro-inflammatory effects observed from coarse PM collected during the summer months from California's hot and dry Central Valley are driven largely by the insoluble components of the PM mixture, and are not caused by endotoxin.

  12. DNA-based machines.

    PubMed

    Wang, Fuan; Willner, Bilha; Willner, Itamar

    2014-01-01

    The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

  13. Novel Transverse Flux Machine for Vehicle Traction Applications: Preprint

    SciTech Connect

    Wan, Z.; Ahmed, A.; Husain, I.; Muljadi, E.

    2015-04-02

    A novel transverse flux machine topology for electric vehicle traction applications using ferrite magnets is presented in this paper. The proposed transverse flux topology utilizes novel magnet arrangements in the rotor that are similar to the Halbach array to boost flux linkage; on the stator side, cores are alternately arranged around a pair of ring windings in each phase to make use of the entire rotor flux that eliminates end windings. Analytical design considerations and finite-element methods are used for an optimized design of a scooter in-wheel motor. Simulation results from finite element analysis (FEA) show that the motor achieved comparable torque density to conventional rare-earth permanent magnet (PM) machines. This machine is a viable candidate for direct-drive applications with low cost and high torque density.

  14. Process capability improvement through DMAIC for aluminum alloy wheel machining

    NASA Astrophysics Data System (ADS)

    Sharma, G. V. S. S.; Rao, P. Srinivasa; Babu, B. Surendra

    2017-07-01

    This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improve-control (DMAIC) approach. By following the DMAIC approach, the C p, C pk and C pm showed signs of improvement from an initial value of 0.66, -0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.

  15. Inferring Mealy Machines

    NASA Astrophysics Data System (ADS)

    Shahbaz, Muzammil; Groz, Roland

    Automata learning techniques are getting significant importance for their applications in a wide variety of software engineering problems, especially in the analysis and testing of complex systems. In recent studies, a previous learning approach [1] has been extended to synthesize Mealy machine models which are specifically tailored for I/O based systems. In this paper, we discuss the inference of Mealy machines and propose improvements that reduces the worst-time learning complexity of the existing algorithm. The gain over the complexity of the proposed algorithm has also been confirmed by experimentation on a large set of finite state machines.

  16. Machine Tool Software

    NASA Technical Reports Server (NTRS)

    1988-01-01

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

  17. Quantum Boltzmann Machine

    NASA Astrophysics Data System (ADS)

    Kulchytskyy, Bohdan; Andriyash, Evgeny; Amin, Mohammed; Melko, Roger

    The field of machine learning has been revolutionized by the recent improvements in the training of deep networks. Their architecture is based on a set of stacked layers of simpler modules. One of the most successful building blocks, known as a restricted Boltzmann machine, is an energetic model based on the classical Ising Hamiltonian. In our work, we investigate the benefits of quantum effects on the learning capacity of Boltzmann machines by extending its underlying Hamiltonian with a transverse field. For this purpose, we employ exact and stochastic training procedures on data sets with physical origins.

  18. High spin states in {sup 139}Pm

    SciTech Connect

    Dhal, A.; Sinha, R. K.; Chaturvedi, L.; Agarwal, P.; Kumar, S.; Jain, A. K.; Kumar, R.; Govil, I. M.; Mukhopadhyay, S.; Chakraborty, A.; Krishichayan; Ray, S.; Ghugre, S. S.; Sinha, A. K.; Kumar, R.; Singh, R. P.; Muralithar, S.; Bhowmik, R. K.; Pancholi, S. C.; Gupta, J. B.

    2009-07-15

    The odd mass nucleus {sup 139}Pm has been studied to high spins through the {sup 116}Cd({sup 27}Al,4n){sup 139}Pm reaction at an incident beam energy of 120 MeV. The de-exciting {gamma}-rays were detected using an array of 12 Compton suppressed Ge detectors. A total of 46 new levels have been proposed in the present work as a result of the observation of 60 new {gamma}-rays. Four new bands including a {delta}J=1 sequence have been identified and all the earlier reported bands, other than the yrast band, have been extended to higher spins and excitation energy. The spin assignments for most of the newly reported levels have been made using the observed coincidence angular anisotropy. Tilted axis cranking calculations support the interpretation of two of the observed magnetic dipole sequences as examples of magnetic rotational bands.

  19. Portland cement industry PM{sub 2.5} and PM{sub 10} emission testing

    SciTech Connect

    Richards, J.; Holder, T.E.

    1999-07-01

    The Portland Cement Association and its member companies have undertaken a study of PM{sub 2.5} and PM{sub 10} particulate emissions from cement plants to compile accurate emission factor data and chemical characterization data. The scope of the testing for the cement manufacturing sources includes cement kilns, alkali bypass streams, clinker coolers, finish mills, raw mills, coal mills, silos, bagging operations, and loadout operations. To ensure consistency of the data, a recently developed PCA emission test protocol is being used at the plants participating in the program. This protocol was developed for PCA by Air Control Techniques, P.C. based on draft EPA PM{sub 2.5} test procedures released in 1989. The testing procedure specified in the PCA Protocol was developed because the US EPA has not yet promulgated a PM{sub 2.5} emission test reference method for stationary sources. The PM{sub 2.5} and PM{sub 10} data are being obtained simultaneously using a dual cyclone sampling train operated in a manner consistent with US EPA Method 201A. The sampling times are selected to ensure that there are adequate particulate catch weights in each particulate size category to allow for chemical analyses. The particulate samples are being analyzed for sulfates, nitrates, and ammonium compounds. The measured emissions of filterable PM{sub 2.5} were very low. The preliminary results of tests conducted at five cement plants indicate that the emissions of filterable PM{sub 10} are approximately sixteen percent (16%) of the value of the limited PM{sub 10} emission factor data published in the Fifth Edition of AP-42, Section 11.6. The air emission test data compiled from 1997 to 1999 for the PCA test program represent the most accurate and complete analyses of Portland cement industry particulate emissions that are presently available. These data will be helpful in the development of PM{sub 2.5} implementation programs.

  20. Probable Health Risks Due to Exposure to Outdoor PM2.5 in India

    NASA Astrophysics Data System (ADS)

    Dey, S.; Chowdhury, S.

    2014-12-01

    Particulate matter of size <2.5 μm (commonly referred to as PM2.5) is considered to be the best indicator of health risks due to exposure to particulate pollution. Unlike the decreasing trends in the developed countries, aerosol loading continues to increase over the Indian subcontinent in the recent past, exposing ~1.6 billion population at risk. Lack of direct measurements prompted us to utilize satellite data in establishing a robust long-term database of surface PM2.5 at high spatial resolution. The hybrid approach utilizes a chemical transport model to constrain the relation between columnar aerosol optical depth (AOD) and surface PM2.5 and establish mean monthly conversion factor. Satellite-derived daily AODs for the period 2000-2012 are then converted to PM2.5 using the conversion factors. The dataset (after validation against coincident in-situ measurements and bias-correction) was used to carry out the exposure assessment. 51% of the population is exposed to PM2.5 concentration exceeding WHO air quality interim target-3 threshold (35 μg m-3). The health impacts are categorized in terms of four diseases - cardio ortho-pulmonary disease (COPD), stroke, ischemic heart disease (IHD) and lung cancer (LC). In absence of any region-specific cohort study, published studies are consulted to estimate risk. The risks relative to the background concentration of 10 μg m-3 are estimated by logarithmic fitting of the individual cohort studies against the corresponding PM2.5 concentration. This approach considers multiple (>100) cohort studies across a wide variety of adult population from various socio-economic backgrounds. Therefore, the calculated risks are considered to be better estimates in relative to any one particular type of risk function model (e.g. linear 50 or linear 70 or exponential). The risk values are used to calculate the additional mortality due to exposure to PM2.5 in each of the administrative districts in India to identify the vulnerable regions

  1. Monitoing PM2.5 from Space

    NASA Astrophysics Data System (ADS)

    Chu, D.; Remer, L.; Szykman, J.; Kaumfan, Y.; Neil, D.; Pierce, B.

    2003-12-01

    MODIS sensors onboard the EOS Terra and Aqua satellites launched in 1999 and 2002 provide the revolutionized perspectives to study the Earth systems. MODIS ability to derive the first aerosol product over land has advanced our understanding of aerosols into the source regions. The analysis of MODIS-derived columnar aerosol loading has shown good correlation (correlation coefficient ~0.8-0.9) with EPA PM2.5 (particulate matter with particle size less than 2.5 mm) at surface in metropolitan areas (e.g., New York City, Chicago, Houston, etc.) and also over broad regions including 11 states and Washington DC. At present, the EPA, along with Regional Planning Organizations, and state and local governments use a multitude of decision support tools to assess, control, and report the nature of air pollution related to PM. However, the current existing air quality decision processes solely rely on urban scale model and ground-based network. Using MODIS aerosol data can aid significantly in tracking the movement of pollutants, which can be used as a proxy of PM2.5 for regions without ground measurements. NASA (GSFC and LaRC) is collaborating with EPA and NOAA in providing MODIS aerosol data to benchmark PM2.5 forecast in the East US in the summer 2003. This activity is to prototype similar activities in the following years using MODIS direct broadcasting to study transport (national, international, or intercontinental) issues and assess performance effectiveness of existing air quality regulations. Improvements of MODIS aerosol algorithm are planned to achieve better spatial resolution for urban pollution and health-related studies.

  2. Related Rules and Programs that Help States Attain PM Standards

    EPA Pesticide Factsheets

    EPA’s national and regional rules to reduce emissions of pollutants that form particle pollution will help state and local governments meet the PM NAAQS. A number of voluntary programs also are helping areas reduce fine PM pollution.

  3. Emissions Removal Efficiency from Diesel Gensets Using Aftermarket PM Controls

    EPA Science Inventory

    Diesel particulate matter (PM) has been associated with adverse health effects in humans and is classified as a human carcinogen. Additionally, diesel PM, particularly the strongly light absorbing fraction, black carbon (BC), is an important climate forcer. The adverse impacts ...

  4. Evaluation of Field-deployed Low Cost PM Sensors

    EPA Science Inventory

    Background Particulate matter (PM) is a pollutant of high public interest regulated by national ambient air quality standards (NAAQS) using federal reference method (FRM) and federal equivalent method (FEM) instrumentation identified for environmental monitoring. PM is present i...

  5. Evaluation of Field-deployed Low Cost PM Sensors

    EPA Science Inventory

    Background Particulate matter (PM) is a pollutant of high public interest regulated by national ambient air quality standards (NAAQS) using federal reference method (FRM) and federal equivalent method (FEM) instrumentation identified for environmental monitoring. PM is present i...

  6. Emissions Removal Efficiency from Diesel Gensets Using Aftermarket PM Controls

    EPA Science Inventory

    Diesel particulate matter (PM) has been associated with adverse health effects in humans and is classified as a human carcinogen. Additionally, diesel PM, particularly the strongly light absorbing fraction, black carbon (BC), is an important climate forcer. The adverse impacts ...

  7. PmVRP15, a novel viral responsive protein from the black tiger shrimp, Penaeus monodon, promoted white spot syndrome virus replication.

    PubMed

    Vatanavicharn, Tipachai; Prapavorarat, Adisak; Jaree, Phattarunda; Somboonwiwat, Kunlaya; Tassanakajon, Anchalee

    2014-01-01

    Suppression subtractive hybridization of Penaeus monodon hemocytes challenged with white spot syndrome virus (WSSV) has identified the viral responsive gene, PmVRP15, as the highest up-regulated gene ever reported in shrimps. Expression analysis by quantitative real time RT-PCR revealed 9410-fold up-regulated level at 48 h post WSSV injection. Tissue distribution analysis showed that PmVRP15 transcript was mainly expressed in the hemocytes of shrimp. The full-length cDNA of PmVRP15 transcript was obtained and showed no significant similarity to any known gene in the GenBank database. The predicted open reading frame of PmVRP15 encodes for a deduced 137 amino acid protein containing a putative transmembrane helix. Immunofluorescent localization of the PmVRP15 protein revealed it accumulated around the nuclear membrane in all three types of shrimp hemocytes and that the protein was highly up-regulated in WSSV-infected shrimps. Double-stranded RNA interference-mediated gene silencing of PmVRP15 in P. monodon significantly decreased WSSV propagation compared to the control shrimps (injected with GFP dsRNA). The significant decrease in cumulative mortality rate of WSSV-infected shrimp following PmVRP15 knockdown was observed. These results suggest that PmVRP15 is likely to be a nuclear membrane protein and that it acts as a part of WSSV propagation pathway.

  8. PmVRP15, a Novel Viral Responsive Protein from the Black Tiger Shrimp, Penaeus monodon, Promoted White Spot Syndrome Virus Replication

    PubMed Central

    Vatanavicharn, Tipachai; Prapavorarat, Adisak; Jaree, Phattarunda; Somboonwiwat, Kunlaya; Tassanakajon, Anchalee

    2014-01-01

    Suppression subtractive hybridization of Penaeus monodon hemocytes challenged with white spot syndrome virus (WSSV) has identified the viral responsive gene, PmVRP15, as the highest up-regulated gene ever reported in shrimps. Expression analysis by quantitative real time RT-PCR revealed 9410–fold up-regulated level at 48 h post WSSV injection. Tissue distribution analysis showed that PmVRP15 transcript was mainly expressed in the hemocytes of shrimp. The full-length cDNA of PmVRP15 transcript was obtained and showed no significant similarity to any known gene in the GenBank database. The predicted open reading frame of PmVRP15 encodes for a deduced 137 amino acid protein containing a putative transmembrane helix. Immunofluorescent localization of the PmVRP15 protein revealed it accumulated around the nuclear membrane in all three types of shrimp hemocytes and that the protein was highly up-regulated in WSSV-infected shrimps. Double-stranded RNA interference-mediated gene silencing of PmVRP15 in P. monodon significantly decreased WSSV propagation compared to the control shrimps (injected with GFP dsRNA). The significant decrease in cumulative mortality rate of WSSV-infected shrimp following PmVRP15 knockdown was observed. These results suggest that PmVRP15 is likely to be a nuclear membrane protein and that it acts as a part of WSSV propagation pathway. PMID:24637711

  9. CMOS SiPM with integrated amplifier

    NASA Astrophysics Data System (ADS)

    Schwinger, Alexander; Brockherde, Werner; Hosticka, Bedrich J.; Vogt, Holger

    2017-02-01

    The integration of silicon photomultiplier (SiPM) and frontend electronics in a suitable optoelectronic CMOS process is a promising approach to increase the versatility of single-photon avalanche diode (SPAD)-based singlephoton detectors. By integrating readout amplifiers, the device output capacitance can be reduced to minimize the waveform tail, which is especially important for large area detectors (>10 × 10mm2). Possible architectures include a single readout amplifier for the whole detector, which reduces the output capacitance to 1:1 pF at minimal reduction in detector active area. On the other hand, including a readout amplifier in every SiPM cell would greatly improve the total output capacitance by minimizing the influence of metal routing parasitic capacitance, but requiring a prohibitive amount of detector area. As tradeoff, the proposed detector features one readout amplifier for each column of the detector matrix to allow for a moderate reduction in output capacitance while allowing the electronics to be placed in the periphery of the active detector area. The presented detector with a total size of 1.7 ♢ 1.0mm2 features 400 cells with a 50 μm pitch, where the signal of each column of 20 SiPM cells is summed in a readout channel. The 20 readout channels are subsequently summed into one output channel, to allow the device to be used as a drop-in replacement for commonly used analog SiPMs.

  10. 16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

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

    16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to south (90mm lens). Note the large segmental-arched doorway to move locomotives in and out of Machine Shop. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

  11. Tunnel boring machine

    SciTech Connect

    Snyder, L. L.

    1985-07-09

    A tunnel boring machine for controlled boring of a curvilinear tunnel including a rotating cutter wheel mounted on the forward end of a thrust cylinder assembly having a central longitudinal axis aligned with the cutter wheel axis of rotation; the thrust cylinder assembly comprising a cylinder barrel and an extendable and retractable thrust arm received therein. An anchoring assembly is pivotally attached to the rear end of the cylinder barrel for anchoring the machine during a cutting stroke and providing a rear end pivot axis during curved cutting strokes. A pair of laterally extending, extendable and retractable arms are fixedly mounted at a forward portion of the cylinder barrel for providing lateral displacement in a laterally curved cutting mode and for anchoring the machine between cutting strokes and during straight line boring. Forward and rear transverse displacement and support assemblies are provided to facilitate cutting in a transversely curved cutting mode and to facilitate machine movement between cutting strokes.

  12. Molecular Machines: Nanoscale gadgets

    NASA Astrophysics Data System (ADS)

    Garcia-Garibay, Miguel A.

    2008-06-01

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

  13. Source apportionment of ambient PM10 and PM2.5 in Haikou, China

    NASA Astrophysics Data System (ADS)

    Fang, Xiaozhen; Bi, Xiaohui; Xu, Hong; Wu, Jianhui; Zhang, Yufen; Feng, Yinchang

    2017-07-01

    In order to identify the sources of PM10 and PM2.5 in Haikou, 60 ambient air samples were collected in winter and spring, respectively. Fifteen elements (Na, Mg, Al, Si, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb), water-soluble ions (SO42 - and NO3-), and organic carbon (OC) and elemental carbon (EC) were analyzed. It was clear that the concentration of particulate matter was higher in winter than in spring. The value of PM2.5/PM10 was > 0.6. Moreover, the proportions of TC, ions, Na, Al, Si and Ca were more high in PM10 and PM2.5. The SOC concentration was estimated by the minimum OC/EC ratio method, and deducted from particulate matter compositions when running CMB model. According to the results of CMB model, the resuspended dust (17.5-35.0%), vehicle exhaust (14.9-23.6%) and secondary particulates (20.4-28.8%) were the major source categories of ambient particulate matter. Additionally, sea salt also had partial contribution (3-8%). And back trajectory analysis results showed that particulate matter was greatly affected by regional sources in winter, while less affected in spring. So particulate matter was not only affected by local sources, but also affected by sea salt and regional sources in coastal cities. Further research could focuses on establishing the actual secondary particles profiles and identifying the local and regional sources of PM at once by one model or analysis method.

  14. Comparative PM10-PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain.

    PubMed

    Rodríguez, Sergio; Querol, Xavier; Alastuey, Andrés; Viana, María-Mar; Alarcón, Marta; Mantilla, Enrique; Ruiz, C R

    2004-07-26

    In this study a set of 340 PM10 and PM2.5 samples collected throughout 16 months at rural, an urban kerbside and an industrial background site (affected by the emissions from the ceramic manufacture and other activities) were interpreted. On the regional scale, the main PM10 sources were mineral dust (mainly Al2O3, Fe, Ti, Sr, CaCO3, Mg, Mn and K), emissions derived from power generation (SO4=, V, Zn and Ni), vehicle exhausts (organic and elemental carbon, NO3- and trace elements) and marine aerosol (Na, Cl and Mg). The latter was not identified in PM2.5. At the industrial site, additional PM10 sources were identified (tile covering in the ceramic production, petrochemical emissions and bio-mass burning from a large orange tree cultivation area). The contribution of each PM source to PM10 and PM2.5 levels experiences significant variations depending on the type of PM episode (Local-urban mainly in autumn-winter, regional mainly in summer, African or Atlantic episode), which are discussed in this study. The results show that it would be very difficult to meet the EU limit values for PM10 established for 2010. The annual mean PM levels are 22.0 microg PM10/m3 at the rural and 49.5 microg PM10/m3 and 33.9 microg PM2.5/m3 at the urban site. The natural contribution in this region, estimated at 6 microg/m3 of natural mineral dust (resulting from the African events and natural resuspension) and 2 microg/m3 of marine aerosol, accounts for 40% of the 2010 EU annual limit value (20 microg PM10/m3). Mineral dust concentrations at the urban and industrial sites are higher than those at the rural site because of the urban road dust and the ceramic-production contributions, respectively. At the urban site, the vehicle exhaust contribution (17 microg/m3) alone is very close to the 2010 EU PM10 limit value. At the rural site, the African dust is the main contributor to PM10 levels during the highest daily mean PM10 events (100th-97th percentile range). At the urban site, the

  15. Approaches to Machine Learning.

    DTIC Science & Technology

    1984-02-16

    The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)

  16. Sealing intersecting vane machines

    DOEpatents

    Martin, Jedd N.; Chomyszak, Stephen M.

    2005-06-07

    The invention provides a toroidal intersecting vane machine incorporating intersecting rotors to form primary and secondary chambers whose porting configurations minimize friction and maximize efficiency. Specifically, it is an object of the invention to provide a toroidal intersecting vane machine that greatly reduces the frictional losses through intersecting surfaces without the need for external gearing by modifying the width of one or both tracks at the point of intermeshing. The inventions described herein relate to these improvements.

  17. Sealing intersecting vane machines

    DOEpatents

    Martin, Jedd N.; Chomyszak, Stephen M.

    2007-06-05

    The invention provides a toroidal intersecting vane machine incorporating intersecting rotors to form primary and secondary chambers whose porting configurations minimize friction and maximize efficiency. Specifically, it is an object of the invention to provide a toroidal intersecting vane machine that greatly reduces the frictional losses through intersecting surfaces without the need for external gearing by modifying the width of one or both tracks at the point of intermeshing. The inventions described herein relate to these improvements.

  18. Maraging Steel Machining Improvements

    DTIC Science & Technology

    2007-04-23

    APR 2007 2. REPORT TYPE Technical, Success Story 3. DATES COVERED 01-12-2006 to 23-04-2007 4. TITLE AND SUBTITLE Maraging Steel Machining...consumers of cobalt-strengthened maraging steel . An increase in production requires them to reduce the machining time of certain operations producing... maraging steel ; Success Stories 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 1 18. NUMBER OF PAGES 1 19a. NAME OF RESPONSIBLE

  19. Flexible machining systems described

    NASA Astrophysics Data System (ADS)

    Butters, H. J.

    1985-03-01

    The rationalization and gradual automation of short rotationally symmetric parts in the Saalfeld VEB Machine Tool Factory was carried out in three stages: (1) part-specific manufacturing; (2) automated production line for manufacturing toothed gears; and (3) automated manufacturing section for short rotationally symmetric parts. The development of numerically controlled machine tools and of industrial robot technology made possible automated manufacturing. The design of current facilities is explored, manufacturing control is examined, experience is reported.

  20. Doubly fed induction machine

    DOEpatents

    Skeist, S. Merrill; Baker, Richard H.

    2005-10-11

    An electro-mechanical energy conversion system coupled between an energy source and an energy load including an energy converter device having a doubly fed induction machine coupled between the energy source and the energy load to convert the energy from the energy source and to transfer the converted energy to the energy load and an energy transfer multiplexer coupled to the energy converter device to control the flow of power or energy through the doubly fed induction machine.

  1. Human-machine interactions

    DOEpatents

    Forsythe, J. Chris; Xavier, Patrick G.; Abbott, Robert G.; Brannon, Nathan G.; Bernard, Michael L.; Speed, Ann E.

    2009-04-28

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

  2. Metalworking and machining fluids

    DOEpatents

    Erdemir, Ali; Sykora, Frank; Dorbeck, Mark

    2010-10-12

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

  3. 40 CFR 1065.290 - PM gravimetric balance.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 33 2014-07-01 2014-07-01 false PM gravimetric balance. 1065.290 Section 1065.290 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Pm Measurements § 1065.290 PM...

  4. 40 CFR 1065.290 - PM gravimetric balance.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 34 2012-07-01 2012-07-01 false PM gravimetric balance. 1065.290 Section 1065.290 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Pm Measurements § 1065.290 PM...

  5. 40 CFR 1065.290 - PM gravimetric balance.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 33 2011-07-01 2011-07-01 false PM gravimetric balance. 1065.290 Section 1065.290 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Pm Measurements § 1065.290 PM...

  6. 40 CFR 1065.290 - PM gravimetric balance.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 34 2013-07-01 2013-07-01 false PM gravimetric balance. 1065.290 Section 1065.290 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Pm Measurements § 1065.290 PM...

  7. 40 CFR 52.378 - Control strategy: PM10.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... redesignate the City of New Haven PM10 nonattainment area to attainment for PM10. The redesignation request... Maintenance Plan (LMP) for the City of New Haven PM10 attainment area for the area's initial ten-year... all applicable requirements of section 175A of the Clean Air Act. Approval of the LMP is conditioned...

  8. 40 CFR 52.378 - Control strategy: PM10.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... redesignate the City of New Haven PM10 nonattainment area to attainment for PM10. The redesignation request... Maintenance Plan (LMP) for the City of New Haven PM10 attainment area for the area's initial ten-year... all applicable requirements of section 175A of the Clean Air Act. Approval of the LMP is conditioned...

  9. 40 CFR 52.378 - Control strategy: PM10.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... redesignate the City of New Haven PM10 nonattainment area to attainment for PM10. The redesignation request... Maintenance Plan (LMP) for the City of New Haven PM10 attainment area for the area's initial ten-year... all applicable requirements of section 175A of the Clean Air Act. Approval of the LMP is conditioned...

  10. Performance characteristics of a low-volume PM10 sampler

    USDA-ARS?s Scientific Manuscript database

    Four identical PM10 pre-separators, along with four identical low-volume (1m3 hr-1) total suspended particulate (TSP) samplers were tested side-by-side in a controlled laboratory particulate matter (PM) chamber. The four PM10 and four TSP samplers were also tested in an oil pipe-cleaning field to ev...

  11. 40 CFR 1065.395 - Inertial PM balance verifications.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Inertial PM balance verifications... Inertial PM balance verifications. This section describes how to verify the performance of an inertial PM balance. (a) Independent verification. Have the balance manufacturer (or a representative approved by the...

  12. 40 CFR 1065.395 - Inertial PM balance verifications.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 33 2011-07-01 2011-07-01 false Inertial PM balance verifications... Inertial PM balance verifications. This section describes how to verify the performance of an inertial PM balance. (a) Independent verification. Have the balance manufacturer (or a representative approved by the...

  13. 40 CFR 1065.395 - Inertial PM balance verifications.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Inertial PM balance verifications... Inertial PM balance verifications. This section describes how to verify the performance of an inertial PM balance. (a) Independent verification. Have the balance manufacturer (or a representative approved by the...

  14. 40 CFR 1065.395 - Inertial PM balance verifications.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Inertial PM balance verifications... Inertial PM balance verifications. This section describes how to verify the performance of an inertial PM balance. (a) Independent verification. Have the balance manufacturer (or a representative approved by the...

  15. 40 CFR 1065.395 - Inertial PM balance verifications.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Inertial PM balance verifications... Inertial PM balance verifications. This section describes how to verify the performance of an inertial PM balance. (a) Independent verification. Have the balance manufacturer (or a representative approved by the...

  16. Could a machine think

    SciTech Connect

    Churchland, P.M.; Churchland, P.S. )

    1990-01-01

    There are many reasons for saying yes. One of the earliest and deepest reason lay in two important results in computational theory. The first was Church's thesis, which states that every effectively computable function is recursively computable. The second important result was Alan M. Turing's demonstration that any recursively computable function can be computed in finite time by a maximally simple sort of symbol-manipulating machine that has come to be called a universal Turing machine. This machine is guided by a set of recursively applicable rules that are sensitive to the identity, order and arrangement of the elementary symbols it encounters as input. The authors reject the Turing test as a sufficient condition for conscious intelligence. They base their position of the specific behavioral failures of the classical SM machines and on the specific virtues of machines with a more brain-like architecture. These contrasts show that certain computational strategies have vast and decisive advantages over others where typical cognitive tasks are concerned, advantages that are empirically inescapable. Clearly, the brain is making systematic use of these computational advantage. But it need not be the only physical system capable of doing so. Artificial intelligence, in a nonbiological but massively parallel machine, remain a compelling and discernible prospect.

  17. The Knife Machine. Module 15.

    ERIC Educational Resources Information Center

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

  18. The Buttonhole Machine. Module 13.

    ERIC Educational Resources Information Center

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

  19. The Knife Machine. Module 15.

    ERIC Educational Resources Information Center

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

  20. Stellarator hybrids

    SciTech Connect

    Furth, H.P.; Ludescher, C.

    1984-08-01

    The present paper briefly reviews the subject of tokamak-stellarator and pinch-stellarator hybrids, and points to two interesting new possibilities: compact-torus-stellarators and mirror-stellarators.

  1. Distribution of a lanthanide (147 Pm) in vascular smooth muscle.

    PubMed

    Weiss, G B; Goodman, F R

    1976-08-01

    In order to ascertain whether trivalent rare earth ions such as lanthanum (La+++) penetrate the cell membrane under physiological conditions, the extracellular and cellular distribution of promethium (147 Pm), a carrier-free rare earth radioisotope, was examined in rabbit aortic smooth muscle. As the duration of incubation was lengthened, uptake of 147Pm continued to increase; it was inhibited by La+++ and other rare earth ions (Nd+++, Lu+++) only when the 147 Pm/rare earth concentration ratio exceeded 1:10(6). However, equally high concentrations of Ca++ had no effect on 147Pm uptake. Efflux of 147Pm was only transiently increased by 1.5 mM La+++, and exposure to 0.05 mM EDTA elicited an increased 147Pm efflux with both transient and maintained components. The magnitude of the EDTA-induced increase in 147 Pm efflux was similar over a 30-fold range of EDTA concentration (0.05-1.5 mM); the limiting factor for 147Pm efflux is the rate of 147Pm desorption from the tissue rather than the extracellular concentration of EDTA. Loss of 147Pm in the presence of 0.05 mM EDTA could be described in terms of two specific washout components (the more rapid of which included 147Pm within the extracellular space and the slower of which had half-times of washout of approximately 7-10 minutes). Uptake of 147Pm was inhibited by lowering the incubation solution temperature to 0 degrees C or by procaine. However, concentrations of metabolic inhibitors (iodoacetate and dinitrophenol) which diminish loss of Ca++ from the cell did not decrease either the uptake or efflux of 147Pm. Thus, significant quantities of 147Pm do not appear to be accumulated within the cell or transported out of the cell; distribution of 147Pm can be most simply described in terms of a binding at and desorption from surface acessible fiber sites.

  2. Non-traditional machining techniques

    SciTech Connect

    Day, Robert D; Fierro, Frank; Garcia, Felix P; Hatch, Douglass J; Randolph, Randall B; Reardon, Patrick T; Rivera, Gerald

    2008-01-01

    During the course of machining targets for various experiments it sometimes becomes necessary to adapt fixtures or machines, which are designed for one function, to another function. When adapting a machine or fixture is not adequate, it may be necessary to acquire a machine specifically designed to produce the component required. In addition to the above scenarios, the features of a component may dictate that multi-step machining processes are necessary to produce the component. This paper discusses the machining of four components where adaptation, specialized machine design, or multi-step processes were necessary to produce the components.

  3. Relevance analysis and short-term prediction of PM2.5 concentrations in Beijing based on multi-source data

    NASA Astrophysics Data System (ADS)

    Ni, X. Y.; Huang, H.; Du, W. P.

    2017-02-01

    The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.

  4. Evidence for reflection asymmetric shape in the nucleus sup 151 sub 61 Pm sub 90

    SciTech Connect

    Sood, P.C.; Sheline, R.K. )

    1989-09-01

    The occurrence of multiple parity doublets, enhanced {ital E}1 transitions between parity-doublet levels, characteristic decoupling parameters for {ital K}=1/2 parity-doublet bands, and hybridization of the nuclear magnetic moments are sought as evidence for reflection asymmetric shape in odd-{ital Z} odd-mass rare-earth nuclei. Specific results consistent with such an assumption are presented for the nucleus {sup 151}{sub 61}Pm{sub 90}. Suggestions are offered for further experiments following a review of available information on other nuclei of the region.

  5. Emission reduction of NOx, PM, PM-carbon, and PAHs from a generator fuelled by biodieselhols.

    PubMed

    Tsai, Jen-Hsiung; Chen, Shui-Jen; Huang, Kuo-Lin; Lin, Wen-Yinn; Lee, Wen-Jhy; Chao, How-Ran; Lin, Chih-Chung; Hsieh, Lien-Te

    2014-06-15

    This investigation examines the particulate matter (PM), particulate carbon, polycyclic aromatic hydrocarbons (PAHs), and nitrogen oxides (NOx) emitted from a generator fueled by petroleum diesel blended with waste-edible-oil-biodiesel and water-containing acetone. Experimental results show that using biodieselhols with water-containing (or pure) acetone as the fuel of generator, in comparison to using petroleum diesel, significantly reduces PM emission; roughly, this reduction increased as percentage of water-containing acetone increased. When the percentages of waste-edible-oil-biodiesel were ≤ 5 vol%, adding pure or water-containing acetone (1-3 vol%) to biodieselhols generated emission reductions of NOx, PM, particle-bound organic carbon (OC), total-PAHs, and total-BaPeq. Consequently, using water-containing acetone biodieselhols as an alternative generator fuel is feasible and helps recycle and reuse waste solvents containing water-containing acetone. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Confirmation of PM typing protocols for consistent and reliable results.

    PubMed

    Crouse, C A; Nippes, D C; Ritzline, E L

    1996-05-01

    A recent report in the Perkin Elmer "Forensic Forum" bulletin described a modification to the previously published PM typing protocol indicating that in order to obtain consistent and reliable PM and DQA1 typing results, disodium EDTA should be added to the post-amplification mixture before denaturation of the DNA fragments. The analysis and validation of this suggestion is described in the accompanying paper. We report the evaluation of this additional step when typing for PM alleles and conclude that the standard operating procedures currently enforced at the Palm Beach County Sheriff's Office and Indian River crime laboratories do not necessitate the need for the addition of disodium EDTA to the PM amplified products prior to the heat denaturation step. Further, depending on an individual laboratory's PM protocol, the recommendation by Perkin Elmer to add disodium EDTA to PM amplified products before typing has merit and should be carefully considered when determining laboratory PM typing protocols.

  7. High Metal Removal Rate Process for Machining Difficult Materials

    SciTech Connect

    Bates, Robert; McConnell, Elizabeth

    2016-06-29

    Machining methods across many industries generally require multiple operations to machine and process advanced materials, features with micron precision, and complex shapes. The resulting multiple machining platforms can significantly affect manufacturing cycle time and the precision of the final parts, with a resultant increase in cost and energy consumption. Ultrafast lasers represent a transformative and disruptive technology that removes material with micron precision and in a single step manufacturing process. Such precision results from athermal ablation without modification or damage to the remaining material which is the key differentiator between ultrafast laser technologies and traditional laser technologies or mechanical processes. Athermal ablation without modification or damage to the material eliminates post-processing or multiple manufacturing steps. Combined with the appropriate technology to control the motion of the work piece, ultrafast lasers are excellent candidates to provide breakthrough machining capability for difficult-to-machine materials. At the project onset in early 2012, the project team recognized that substantial effort was necessary to improve the application of ultrafast laser and precise motion control technologies (for micromachining difficult-to-machine materials) to further the aggregate throughput and yield improvements over conventional machining methods. The project described in this report advanced these leading-edge technologies thru the development and verification of two platforms: a hybrid enhanced laser chassis and a multi-application testbed.

  8. Effects of Wire EDM on the Microstructure of P/M Titanium Samples

    PubMed Central

    Viskić, Joško; Schauperl, Zdravko; Ćatić, Amir; Balog, Martin; Krizik, Peter; Gržeta, Biserka; Popović, Jasminka; Ortolan, Slađana Milardović

    2014-01-01

    Purpose Commercially pure titanium (CP Ti) has been recognized in dentistry for its biocompatibility, good mechanical properties and corrosion resistance. Conventional manufacturing processes can affect surface quality and result in poor bonding of dental ceramics to CP Ti. This is why powder metallurgy (P/M) and wire electro-discharge machining (WEDM) are being introduced in the manufacturing process. The aim of this study was to evaluate the effect of WEDM on the surface composition and microstructure of P/M CP Ti samples produced for bond strength testing according to ISO 9693. Materials and methods Eight samples of P/M CP Ti, dimensions according to ISO 9693, were made using WEDM and divided in two groups (untreated and grinded). Microanalyses of chemical composition and microstructure of both groups were made using SEM, EDS and XDR. Results SEM and EDS analysis of untreated samples showed a thin layer on surfaces with fractures in it. Grinded samples showed homogenous structure with no layer and no fractures. XDR analysis showed high level of oxides on the surface of untreated samples, while after grinding only pure α-phase was found. Conclusion WEDM is a suitable method of sample production for ISO 9693 if accompanied by grinding with silicon carbide papers P320-P4000. PMID:27688377

  9. Analysis of PM2.5 and PM10 in the atmosphere of Mexico City during 2000-2002.

    PubMed

    Vega, Elizabeth; Reyes, Elizabeth; Ruiz, Hugo; García, José; Sánchez, Gabriela; Martínez-Villa, Gerardo; González, Uriel; Chow, Judith C; Watson, John G

    2004-07-01

    During the last 10 years, high atmospheric concentrations of airborne particles recorded in the Mexico City metropolitan area have caused concern because of their potential harmful effects on human health. Four monitoring campaigns have been carried out in the Mexico City metropolitan area during 2000-2002 at three sites: (1) Xalostoc, located in an industrial region; (2) La Merced, located in a commercial area; and (3) Pedregal, located in a residential area. Results of gravimetric and chemical analyses of 330 samples of particulate matter (PM) with an aerodynamic diameter less than 2.5 microm (PM2.5) and PM with an aerodynamic diameter less than 10 microm (PM10) indicate that (1) PM2.5/PM10 average ratios were 0.42, 0.46, and 0.52 for Xalostoc, La Merced, and Pedregal, respectively; (2) the highest PM2.5 and PM10 concentrations were found at the industrial site; (3) PM2.5 and PM10 concentrations were lower at nighttime; (4) PM2.5 and PM10 spatial averages concentrations were 35 and 76 microg/m3, respectively; and (5) when the PM2.5 standard was exceeded, nitrate, sulfate, ammonium, organic carbon, and elemental carbon concentrations were high. Twenty-four hour averaged PM2.5 concentrations in Mexico City and Sao Paulo were similar to those recorded in the 1980s in Los Angeles. PM10 concentrations were comparable in Sao Paulo and Mexico City but 3-fold lower than those found in Santiago.

  10. Reduction of PM emissions from specific sources reflected on key components concentrations of ambient PM10

    NASA Astrophysics Data System (ADS)

    Minguillon, M. C.; Querol, X.; Monfort, E.; Alastuey, A.; Escrig, A.; Celades, I.; Miro, J. V.

    2009-04-01

    The relationship between specific particulate emission control and ambient levels of some PM10 components (Zn, As, Pb, Cs, Tl) was evaluated. To this end, the industrial area of Castellón (Eastern Spain) was selected, where around 40% of the EU glazed ceramic tiles and a high proportion of EU ceramic frits (middle product for the manufacture of ceramic glaze) are produced. The PM10 emissions from the ceramic processes were calculated over the period 2000 to 2007 taking into account the degree of implementation of corrective measures throughout the study period. Abatement systems (mainly bag filters) were implemented in the majority of the fusion kilns for frit manufacture in the area as a result of the application of the Directive 1996/61/CE, leading to a marked decrease in PM10 emissions. On the other hand, ambient PM10 sampling was carried out from April 2002 to July 2008 at three urban sites and one suburban site of the area and a complete chemical analysis was made for about 35 % of the collected samples, by means of different techniques (ICP-AES, ICP-MS, Ion Chromatography, selective electrode and elemental analyser). The series of chemical composition of PM10 allowed us to apply a source contribution model (Principal Component Analysis), followed by a multilinear regression analysis, so that PM10 sources were identified and their contribution to bulk ambient PM10 was quantified on a daily basis, as well as the contribution to bulk ambient concentrations of the identified key components (Zn, As, Pb, Cs, Tl). The contribution of the sources identified as the manufacture and use of ceramic glaze components, including the manufacture of ceramic frits, accounted for more than 65, 75, 58, 53, and 53% of ambient Zn, As, Pb, Cs and Tl levels, respectively (with the exception of Tl contribution at one of the sites). The important emission reductions of these sources during the study period had an impact on ambient key components levels, such that there was a high

  11. Extreme ultraviolet lithography machine

    DOEpatents

    Tichenor, Daniel A.; Kubiak, Glenn D.; Haney, Steven J.; Sweeney, Donald W.

    2000-01-01

    An extreme ultraviolet lithography (EUVL) machine or system for producing integrated circuit (IC) components, such as transistors, formed on a substrate. The EUVL machine utilizes a laser plasma point source directed via an optical arrangement onto a mask or reticle which is reflected by a multiple mirror system onto the substrate or target. The EUVL machine operates in the 10-14 nm wavelength soft x-ray photon. Basically the EUV machine includes an evacuated source chamber, an evacuated main or project chamber interconnected by a transport tube arrangement, wherein a laser beam is directed into a plasma generator which produces an illumination beam which is directed by optics from the source chamber through the connecting tube, into the projection chamber, and onto the reticle or mask, from which a patterned beam is reflected by optics in a projection optics (PO) box mounted in the main or projection chamber onto the substrate. In one embodiment of a EUVL machine, nine optical components are utilized, with four of the optical components located in the PO box. The main or projection chamber includes vibration isolators for the PO box and a vibration isolator mounting for the substrate, with the main or projection chamber being mounted on a support structure and being isolated.

  12. Organisms ≠ Machines.

    PubMed

    Nicholson, Daniel J

    2013-12-01

    The machine conception of the organism (MCO) is one of the most pervasive notions in modern biology. However, it has not yet received much attention by philosophers of biology. The MCO has its origins in Cartesian natural philosophy, and it is based on the metaphorical redescription of the organism as a machine. In this paper I argue that although organisms and machines resemble each other in some basic respects, they are actually very different kinds of systems. I submit that the most significant difference between organisms and machines is that the former are intrinsically purposive whereas the latter are extrinsically purposive. Using this distinction as a starting point, I discuss a wide range of dissimilarities between organisms and machines that collectively lay bare the inadequacy of the MCO as a general theory of living systems. To account for the MCO's prevalence in biology, I distinguish between its theoretical, heuristic, and rhetorical functions. I explain why the MCO is valuable when it is employed heuristically but not theoretically, and finally I illustrate the serious problems that arise from the rhetorical appeal to the MCO. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. The Bearingless Electrical Machine

    NASA Technical Reports Server (NTRS)

    Bichsel, J.

    1992-01-01

    Electromagnetic bearings allow the suspension of solids. For rotary applications, the most important physical effect is the force of a magnetic circuit to a high permeable armature, called the MAXWELL force. Contrary to the commonly used MAXWELL bearings, the bearingless electrical machine will take advantage of the reaction force of a conductor carrying a current in a magnetic field. This kind of force, called Lorentz force, generates the torque in direct current, asynchronous and synchronous machines. The magnetic field, which already exists in electrical machines and helps to build up the torque, can also be used for the suspension of the rotor. Besides the normal winding of the stator, a special winding was added, which generates forces for levitation. So a radial bearing, which is integrated directly in the active part of the machine, and the motor use the laminated core simultaneously. The winding was constructed for the levitating forces in a special way so that commercially available standard ac inverters for drives can be used. Besides wholly magnetic suspended machines, there is a wide range of applications for normal drives with ball bearings. Resonances of the rotor, especially critical speeds, can be damped actively.

  14. PM composition and source reconciliation in Mexico City

    NASA Astrophysics Data System (ADS)

    Mugica, V.; Ortiz, E.; Molina, L.; De Vizcaya-Ruiz, A.; Nebot, A.; Quintana, R.; Aguilar, J.; Alcántara, E.

    PM 2.5 and PM 10 were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM 2.5 concentrations ranged from 32 to 70 μg m -3 while that of PM10 did so from 51 to 132 μg m -3. The most abundant chemical species for both PM fractions were: OC, EC, SO 42-, NO 3-, NH 4+, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM 2.5 than for PM 10, and did not display significant differences during the sampling period. The PM 2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O 3S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.

  15. Design of a surface attachable hybrid fiber sensor packaged in a polyimide film for engineering applications

    NASA Astrophysics Data System (ADS)

    Ramakrishnan, Manjusha; Rajan, Ginu; Semenova, Yuliya; Farrell, Gerald

    2010-09-01

    The design of a polyimide film packaged hybrid fiber sensor for simultaneous strain and temperature measurement is presented. This hybrid sensor operates in the intensity domain by converting the polarization and wavelength information from a polarization maintaining photonic crystal fiber (PM-PCF) sensor and fiber Bragg grating sensor (FBG) respectively into intensity variations. The strain sensitivity of a polarimetric sensor for various lengths of the PM-PCF is studied. The effective strain sensitivity of the FBG sensing system is adjusted to match that of the polarimetric sensor by varying the slope of the edge filter. The packaging aspects of the hybrid fiber sensor are also presented in this paper.

  16. Concentrations and emission factors for PM2.5 and PM10 from road traffic in Sweden

    NASA Astrophysics Data System (ADS)

    Ferm, Martin; Sjöberg, Karin

    2015-10-01

    PM10 concentrations exceed the guidelines in some Swedish cities and the limit values will likely be further reduced in the future. In order to gain more knowledge of emission factors for road traffic and concentrations of PM10 and PM2.5, existing monitoring stations in two cities, Gothenburg and Umeå, with international E-road thoroughfares, were complemented with some PM2.5 measurements. Emission factors for PM10 and PM2.5 were estimated using NOX as a tracer. Monitoring data from kerbside and urban background sites in Gothenburg during 2006-2010 and in Umeå during 2006-2012 were used. NOX emissions were estimated from the traffic flow and emission factors calculated from the HBEFA3.1 model. PM2.5 constitutes the finer part of PM10. Emissions of the coarser part of PM10 (PM10-PM2.5) are suppressed when roads are wet and show a maximum during spring when the roads dry up and studded tyres are still used. Less than 1% of the road wear caused by studded tyres give rise to airborne PM2.5-10 particles. The NOX emission factors decrease with time in the used model, due to the renewal of the vehicle fleet. However, the NOX concentrations resulting from the roads show no clear trend. The air dispersion is an important factor controlling the PM concentration near the road. The dispersion has a minimum in winter and during midnight. The average street level concentrations of PM10 and PM2.5 in Gothenburg were 21 ± 20 and 8 ± 6 μg m-3 respectively, which is 36% and 22% higher than the urban background concentrations. Despite the four times lower traffic flow in Umeå compared to Gothenburg, the average particle concentrations were very similar; 21 ± 31 and 7 ± 5 μg m-3 for PM10 and PM2.5 respectively. These concentrations were, however, 108% and 55% higher than the urban background concentrations in Umeå. The emission factors for PM10 decreased with time, and the average factor was 0.06 g km-1 vehichle-1. The emission factors for PM2.5 are very uncertain due to the

  17. {beta}{sup +} decay and cosmic-ray half-lives of {sup 143}Pm and {sup 144}Pm

    SciTech Connect

    Hindi, M.M.; da Cruz, M.T.F.; Larimer, R.M.; Lesko, K.T.; Norman, E.B.; Sur, B. |; Champagne, A.E.

    1993-04-12

    The positron decay partial half-lives of {sup 143}Pm and {sup 144}Pm are needed to assess the viability of elemental Pm as a cosmic-ray clock. We have conducted experiments to measure the {beta}{sup +} branches of these isotopes; we find {beta}{sup +} branches of these isotopes; we find {beta}{sup +} branches of <5.7 {times}10{sup {minus}8} for {sup 143}Pm and <8{times}10{sup {minus} 7} for {sup 144}Pm. Through these branches are a factor of 20 lower than the previous experimental limits, the resulting partial half-lives are still too uncertain to permit any firm conclusions.

  18. [beta][sup +] decay and cosmic-ray half-lives of [sup 143]Pm and [sup 144]Pm

    SciTech Connect

    Hindi, M.M. . Dept. of Physics); da Cruz, M.T.F.; Larimer, R.M.; Lesko, K.T.; Norman, E.B. ); Sur, B. Queen's Univ., Kingston, ON . Dept. of Physics); Champagne, A.E. . Dept. of Physics and A

    1993-04-12

    The positron decay partial half-lives of [sup 143]Pm and [sup 144]Pm are needed to assess the viability of elemental Pm as a cosmic-ray clock. We have conducted experiments to measure the [beta][sup +] branches of these isotopes; we find [beta][sup +] branches of these isotopes; we find [beta][sup +] branches of <5.7 [times]10[sup [minus]8] for [sup 143]Pm and <8[times]10[sup [minus] 7] for [sup 144]Pm. Through these branches are a factor of 20 lower than the previous experimental limits, the resulting partial half-lives are still too uncertain to permit any firm conclusions.

  19. [beta][sup +] decay and cosmic-ray half-lives of [sup 143]Pm and [sup 144]Pm

    SciTech Connect

    Hindi, M.M.; Champagne, A.E.; da Cruz, M.T.F.; Larimer, R.; Lesko, K.T.; Norman, E.B.; Sur, B. Department of Physics, Princeton University, Princeton, New Jersey 08544 Nuclear Science Division, Lawrence Berkeley Laboratory, Berkeley, California 94720 )

    1994-08-01

    The positron decay partial half-lives of [sup 143]Pm and [sup 144]Pm are needed to assess the viability of elemental Pm as a cosmic-ray clock. We have conducted experiments to measure the [beta][sup +] branches of these isotopes; we find [beta][sup +] branches of [lt]5.7[times]10[sup [minus]6]% for [sup 143]Pm and [lt]8[times]10[sup [minus]5]% for [sup 144]Pm. Although these branches are a factor of 20 lower than the previous experimental limits, the resulting partial half-lives are still too uncertain to permit any firm conclusions.

  20. Source identification of PM 2.5 particles measured in Gwangju, Korea

    NASA Astrophysics Data System (ADS)

    Lee, Hanlim; Park, Seung S.; Kim, Kyung W.; Kim, Young J.

    The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM 2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM 2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM 2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM 2.5 mass (21.5 μg m - 3 ), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM 2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM 2.5 sources. Additionally, the impact of air mass pathways on the PM 2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM 2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of

  1. The effect of outdoor air and indoor human activity on mass concentrations of PM(10), PM(2.5), and PM(1) in a classroom.

    PubMed

    Branis, Martin; Rezácová, Pavla; Domasová, Markéta

    2005-10-01

    The 12-h mass concentration of PM(10), PM(2.5), and PM(1) was measured in a lecturing room by means of three co-located Harvard impactors. The filters were changed at 8 AM and at 8 PM to cover the periods of presence and absence of students. Concentrations were assessed by gravimetry. Ambient PM(10) data were available for corresponding 12-h intervals from the nearest state air-quality-monitoring network station. The data were pooled into four periods according to the presence and absence of students-Monday-Thursday day (workday daytime), Monday-Thursday night (workday night), Friday-Sunday day (weekend daytime), and Friday-Sunday night (weekend night). Average indoor workday daytime concentrations were 42.3, 21.9 and 13.7 microgm(-3), workday night were 20.9, 19.1 and 15.2 microgm(-3), weekend daytime were 21.9, 18.1 and 11.4 microgm(-3), and weekend night were 24.5, 21.3, and 15.6 microgm(-3) for PM(10), PM(2.5), and PM(1), respectively. The highest 12-h mean, median, and maximum (42.3, 43.0, and 76.2 microgm(-3), respectively) indoor concentrations were recorded on workdays during the daytime for PM(10). The statistically significant (r=0.68,P<0.0009) correlation between the number of students per hour per day and the indoor coarse fraction calculated as PM(10--2.5) during daytime on workdays indicates that the presence of people is an important source of coarse particles indoor. On workdays, the daytime PM(10) indoor/outdoor ratio was positively associated (r=0.93) with an increasing indoor coarse fraction (PM(10--2.5)), also indicating that an important portion of indoor PM(10) had its source inside the classroom. With the exception of the calculated coarse fraction (PM(10--2.5)), all of the measured indoor particulate matter fractions were significantly highly correlated with outdoor PM(10) and negatively correlated with wind velocity, showing that outdoor levels of particles influence their indoor concentrations.

  2. Characterizing metal(loid) solubility in airborne PM10, PM2.5 and PM1 in Frankfurt, Germany using simulated lung fluids

    NASA Astrophysics Data System (ADS)

    Wiseman, Clare L. S.; Zereini, Fathi

    2014-06-01

    The purpose of this study is to assess the solubility of traffic-related metal(loid)s associated with airborne PM of human health concern, employing a physiologically-based extraction test with simulated lung fluids (artificial lysosomal fluid (ALF) and Gamble's solution). Airborne PM (PM10, PM2.5 and PM1) samples were collected in Frankfurt am Main, Germany, using a high volume sampler. Following extraction of the soluble metal(loid) fractions, sample filters were digested with a high pressure asher. Metal(loid) concentrations (As, Ce, Co, Cr, Cu, Mn, Ni, Pb, Sb, Ti and V) were determined in extracts and digests per ICP-Q-MS. All metal(loid)s occurred at detectable concentrations in the three airborne PM fractions. Copper was the most abundant element in mass terms, with mean concentrations of 105 and 53 ng/m3 in PM10 and PM2.5, respectively. Many of the metal(loid)s were observed to be soluble in simulated lung fluids, with Cu, As, V and Sb demonstrating the highest overall mobility in airborne PM. For instance, all four elements associated with PM10 had a solubility of >80% in ALF (24 h). Clearly, solubility is strongly pH dependent, as reflected by the higher relative mobility of samples extracted with the acidic ALF. Given their demonstrated solubility, this study provides indirect evidence that a number of toxic metal(loid)s are likely to possess an enhanced pulmonary toxic potential upon their inhalation. The co-presence of many toxic elements of concern in airborne PM suggests an assessment of health risk must consider the possible interactive impacts of multi-element exposures.

  3. Study of the Productivity and Surface Quality of Hybrid EDM

    NASA Astrophysics Data System (ADS)

    Wankhade, Sandeepkumar Haribhau; Sharma, Sunil Bansilal

    2016-01-01

    The development of new, advanced engineering materials and the need for precise prototypes and low-volume production have made the electric discharge machining (EDM), an important manufacturing process to meet such demands. It is capable of machining geometrically complex and hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides etc. Conversely the low MRR limits its productivity. Abrasive water jet machine (AJM) tools are quick to setup and offer quick turn-around on the machine and could make parts out of virtually any material. They do not heat the material hence no heat affected zone and can make any intricate shape easily. The main advantages are flexibility, low heat production and ability to machine hard and brittle materials. Main disadvantages comprise the process produces a tapered cut and health hazards due to dry abrasives. To overcome the limitations and exploit the best of each of above processes; an attempt has been made to hybridize the processes of AJM and EDM. The appropriate abrasives routed with compressed air through the hollow electrode to construct the hybrid process i.e., abrasive jet electric discharge machining (AJEDM), the high speed abrasives could impinge on the machined surface to remove the recast layer caused by EDM process. The main process parameters were varied to explore their effects and experimental results show that AJEDM enhances the machining efficiency with better surface finish hence can fit the requirements of modern manufacturing applications.

  4. Dust Monitoring on the Hanford Site: An Investigation into the Relationship Between TSP, PM-10, and PM-2.5

    SciTech Connect

    Schwartz, T.; Fitz, B.G.

    2004-01-01

    High levels of particulate matter (PM) are linked to some health problems and environmental issues. Air quality standards have been developed in hopes to reduce particulate matter problems. The most common fractions of particulate matter measured include PM2.5, PM10, and total suspended particles (TSP). The focus of this study was to evaluate relationships between PM2.5, PM10, and TSP concentrations specific to the Hanford Site, near Richland, Washington. Measurements of PM2.5 and PM10 concentrations continued while additional measurements of TSP were made over several summer months. Four sampling locations on the Hanford Site were used to compare spatial differences in the data. Comparison of the data revealed a strong linear correlation between PM10 and TSP for the time period evaluated. The correlation between PM2.5 and TSP was not as strong, and indicated that local sources rarely were above background measurements. This was supported by the correlation of ground level PM2.5 with PM2.5 concentrations measured on a near by mountain.

  5. Spatial distribution of particulate matter (PM10 and PM2.5) in Seoul Metropolitan Subway stations.

    PubMed

    Kim, Ki Youn; Kim, Yoon Shin; Roh, Young Man; Lee, Cheol Min; Kim, Chi Nyon

    2008-06-15

    The aims of this study are to examine the concentrations of PM10 and PM2.5 in areas within the Seoul Metropolitan Subway network and to provide fundamental data in order to protect respiratory health of subway workers and passengers from air pollutants. A total of 22 subway stations located on lines 1-4 were selected based on subway official's guidance. At these stations both subway worker areas (station offices, rest areas, ticket offices and driver compartments) and passengers areas (station precincts, subway carriages and platforms) were the sites used for measuring the levels of PM. The mean concentrations of PM10 and PM2.5 were relatively higher on platforms, inside subway carriages and in driver compartments than in the other areas monitored. The levels of PM10 and PM2.5 for station precincts and platforms exceeded the 24-h acceptable threshold limits of 150 microg/m3 for PM10 and 35 microg/m3 for PM2.5, which are regulated by the U.S. Environmental Protection Agency (EPA). However, levels measured in station and ticket offices fell below the respective threshold. The mean PM10 and PM2.5 concentrations on platforms located underground were significantly higher than those at ground level (p<0.05).

  6. In Vitro Exposures in Diesel Exhaust Atmospheres: Resuspension of PM from Filters Verses Direct Deposition of PM from Air

    PubMed Central

    Lichtveld, Kim M.; Ebersviller, Seth M.; Sexton, Kenneth G.; Vizuete, William; Jaspers, Ilona; Jeffries, Harvey E.

    2012-01-01

    One of the most widely used in vitro particulate matter (PM) exposures methods is the collection of PM on filters, followed by resuspension in a liquid medium, with subsequent addition onto a cell culture. To avoid disruption of equilibria between gases and PM, we have developed a direct in vitro sampling and exposure method (DSEM) capable of PM-only exposures. We hypothesize that the separation of phases and post-treatment of filter-collected PM significantly modifies the toxicity of the PM compared to direct deposition, resulting in a distorted view of the potential PM health effects. Controlled test environments were created in a chamber that combined diesel exhaust with an urban-like mixture. The complex mixture was analyzed using both the DSEM and concurrently-collected filter samples. The DSEM showed that PM from test atmospheres produced significant inflammatory response, while the resuspension exposures at the same exposure concentration did not. Increasing the concentration of resuspended PM sixteen times was required to yield measurable IL-8 expression. Chemical analysis of the resuspended PM indicated a total absence of carbonyl compounds compared to the test atmosphere during the direct-exposures. Therefore, collection and resuspension of PM into liquid modifies its toxicity and likely leads to underestimating toxicity. PMID:22834915

  7. Brown coal preparation machines

    SciTech Connect

    Bleckmann, H.; Sitte, W.; Kellerwessel, H.

    1981-05-01

    Lignite usually requires comminuting and screening before being used as a fuel in power plants. Reduction machines normally used for coarse crushing bituminous coal, such as jaw crushers, roll crushers, and impact crushers, are not generally suitable for lignite as they require a brittle feed and large grain size. In contrast to these requirements, lignite can be easily compressed and has a small grain size. Therefore, special crusher types have been developed for the coarse reduction of lignite. These machines resemble roll crushers but subject the feed to shearing and tearing forces rather than to compressive stress. It is often necessary to screen the lignite to remove the undersize or to limit the maximum particle size before the next comminution process. Screening the lignite is a particularly difficult operation due to the high water content and the presence of clay minerals which tend to clog the screening machines. These problems can be overcome with multi-roll sizers.

  8. Micro-machined resonator

    DOEpatents

    Godshall, N.A.; Koehler, D.R.; Liang, A.Y.; Smith, B.K.

    1993-03-30

    A micro-machined resonator, typically quartz, with upper and lower micro-machinable support members, or covers, having etched wells which may be lined with conductive electrode material, between the support members is a quartz resonator having an energy trapping quartz mesa capacitively coupled to the electrode through a diaphragm; the quartz resonator is supported by either micro-machined cantilever springs or by thin layers extending over the surfaces of the support. If the diaphragm is rigid, clock applications are available, and if the diaphragm is resilient, then transducer applications can be achieved. Either the thin support layers or the conductive electrode material can be integral with the diaphragm. In any event, the covers are bonded to form a hermetic seal and the interior volume may be filled with a gas or may be evacuated. In addition, one or both of the covers may include oscillator and interface circuitry for the resonator.

  9. Micro-machined resonator

    DOEpatents

    Godshall, Ned A.; Koehler, Dale R.; Liang, Alan Y.; Smith, Bradley K.

    1993-01-01

    A micro-machined resonator, typically quartz, with upper and lower micro-machinable support members, or covers, having etched wells which may be lined with conductive electrode material, between the support members is a quartz resonator having an energy trapping quartz mesa capacitively coupled to the electrode through a diaphragm; the quartz resonator is supported by either micro-machined cantilever springs or by thin layers extending over the surfaces of the support. If the diaphragm is rigid, clock applications are available, and if the diaphragm is resilient, then transducer applications can be achieved. Either the thin support layers or the conductive electrode material can be integral with the diaphragm. In any event, the covers are bonded to form a hermetic seal and the interior volume may be filled with a gas or may be evacuated. In addition, one or both of the covers may include oscillator and interface circuitry for the resonator.

  10. Collocated comparisons of continuous and filter-based PM2.5 measurements at Fort McMurray, Alberta, Canada

    PubMed Central

    Hsu, Yu-Mei; Wang, Xiaoliang; Chow, Judith C.; Watson, John G.; Percy, Kevin E.

    2016-01-01

    ABSTRACT Collocated comparisons for three PM2.5 monitors were conducted from June 2011 to May 2013 at an air monitoring station in the residential area of Fort McMurray, Alberta, Canada, a city located in the Athabasca Oil Sands Region. Extremely cold winters (down to approximately −40°C) coupled with low PM2.5 concentrations present a challenge for continuous measurements. Both the tapered element oscillating microbalance (TEOM), operated at 40°C (i.e., TEOM40), and Synchronized Hybrid Ambient Real-time Particulate (SHARP, a Federal Equivalent Method [FEM]), were compared with a Partisol PM2.5 U.S. Federal Reference Method (FRM) sampler. While hourly TEOM40 PM2.5 were consistently ~20–50% lower than that of SHARP, no statistically significant differences were found between the 24-hr averages for FRM and SHARP. Orthogonal regression (OR) equations derived from FRM and TEOM40 were used to adjust the TEOM40 (i.e., TEOMadj) and improve its agreement with FRM, particularly for the cold season. The 12-year-long hourly TEOMadj measurements from 1999 to 2011 based on the OR equations between SHARP and TEOM40 were derived from the 2-year (2011–2013) collocated measurements. The trend analysis combining both TEOMadj and SHARP measurements showed a statistically significant decrease in PM2.5 concentrations with a seasonal slope of −0.15 μg m−3 yr−1 from 1999 to 2014.Implications: Consistency in PM2.5 measurements are needed for trend analysis. Collocated comparison among the three PM2.5 monitors demonstrated the difference between FRM and TEOM, as well as between SHARP and TEOM. The orthogonal regressions equations can be applied to correct historical TEOM data to examine long-term trends within the network. PMID:26727574

  11. PM10 forecasting using clusterwise regression

    NASA Astrophysics Data System (ADS)

    Poggi, Jean-Michel; Portier, Bruno

    2011-12-01

    In this paper, we are interested in the statistical forecasting of the daily mean PM10 concentration. Hourly concentrations of PM10 have been measured in the city of Rouen, in Haute-Normandie, France. Located at northwest of Paris, near the south side of Manche sea and heavily industrialised. We consider three monitoring stations reflecting the diversity of situations: an urban background station, a traffic station and an industrial station near the cereal harbour of Rouen. We have focused our attention on data for the months that register higher values, from December to March, on years 2004-2009. The models are obtained from the winter days of the four seasons 2004/2005 to 2007/2008 (training data) and then the forecasting performance is evaluated on the winter days of the season 2008/2009 (test data). We show that it is possible to accurately forecast the daily mean concentration by fitting a function of meteorological predictors and the average concentration measured on the previous day. The values of observed meteorological variables are used for fitting the models and are also considered for the test data. We have compared the forecasts produced by three different methods: persistence, generalized additive nonlinear models and clusterwise linear regression models. This last method gives very impressive results and the end of the paper tries to analyze the reasons of such a good behavior.

  12. Scalable hybrid computation with spikes.

    PubMed

    Sarpeshkar, Rahul; O'Halloran, Micah

    2002-09-01

    We outline a hybrid analog-digital scheme for computing with three important features that enable it to scale to systems of large complexity: First, like digital computation, which uses several one-bit precise logical units to collectively compute a precise answer to a computation, the hybrid scheme uses several moderate-precision analog units to collectively compute a precise answer to a computation. Second, frequent discrete signal restoration of the analog information prevents analog noise and offset from degrading the computation. And, third, a state machine enables complex computations to be created using a sequence of elementary computations. A natural choice for implementing this hybrid scheme is one based on spikes because spike-count codes are digital, while spike-time codes are analog. We illustrate how spikes afford easy ways to implement all three components of scalable hybrid computation. First, as an important example of distributed analog computation, we show how spikes can create a distributed modular representation of an analog number by implementing digital carry interactions between spiking analog neurons. Second, we show how signal restoration may be performed by recursive spike-count quantization of spike-time codes. And, third, we use spikes from an analog dynamical system to trigger state transitions in a digital dynamical system, which reconfigures the analog dynamical system using a binary control vector; such feedback interactions between analog and digital dynamical systems create a hybrid state machine (HSM). The HSM extends and expands the concept of a digital finite-state-machine to the hybrid domain. We present experimental data from a two-neuron HSM on a chip that implements error-correcting analog-to-digital conversion with the concurrent use of spike-time and spike-count codes. We also present experimental data from silicon circuits that implement HSM-based pattern recognition using spike-time synchrony. We outline how HSMs may be

  13. Interior Permanent Magnet Reluctance Machine with Brushless Field Excitation

    SciTech Connect

    Wiles, R.H.

    2005-10-07

    In a conventional permanent magnet (PM) machine, the air-gap flux produced by the PM is fixed. It is difficult to enhance the air-gap flux density due to limitations of the PM in a series-magnetic circuit. However, the air-gap flux density can be weakened by using power electronic field weakening to the limit of demagnetization of the PMs. This paper presents the test results of controlling the PM air-gap flux density through the use of a stationary brushless excitation coil in a reluctance interior permanent magnet with brushless field excitation (RIPM-BFE) motor. Through the use of this technology the air-gap flux density can be either enhanced or weakened. There is no concern with demagnetizing the PMs during field weakening. The leakage flux of the excitation coil through the PMs is blocked. The prototype motor built on this principle confirms the concept of flux enhancement and weakening through the use of excitation coils.

  14. Paradigms for machine learning

    NASA Technical Reports Server (NTRS)

    Schlimmer, Jeffrey C.; Langley, Pat

    1991-01-01

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

  15. Autonomous quantum thermodynamic machines

    NASA Astrophysics Data System (ADS)

    Tonner, Friedemann; Mahler, Günter

    2005-12-01

    We investigate the dynamics of a quantum system consisting of a single spin coupled to an oscillator and sandwiched between two thermal baths at different temperatures. By means of an adequately designed Lindblad equation, it is shown that this device can function as a thermodynamic machine exhibiting Carnot-type cycles. For the present model, this means that when run as a heat engine, coherent motion of the oscillator is amplified. Contrary to the quantum computer, such a machine has a quantum as well as a classical limit. Away from the classical limit, it asymptotically approaches a stationary transport scenario.

  16. Refrigerating machine oil

    SciTech Connect

    Nozawa, K.

    1981-03-17

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

  17. Intersecting vane machines

    DOEpatents

    Bailey, H. Sterling; Chomyszak, Stephen M.

    2007-01-16

    The invention provides a toroidal intersecting vane machine incorporating intersecting rotors to form primary and secondary chambers whose porting configurations minimize friction and maximize efficiency. Specifically, it is an object of the invention to provide a toroidal intersecting vane machine that greatly reduces the frictional losses through meshing surfaces without the need for external gearing by modifying the function of one or the other of the rotors from that of "fluid moving" to that of "valving" thereby reducing the pressure loads and associated inefficiencies at the interface of the meshing surfaces. The inventions described herein relate to these improvements.

  18. Precision Robotic Assembly Machine

    ScienceCinema

    None

    2016-07-12

    The world's largest laser system is the National Ignition Facility (NIF), located at Lawrence Livermore National Laboratory. NIF's 192 laser beams are amplified to extremely high energy, and then focused onto a tiny target about the size of a BB, containing frozen hydrogen gas. The target must be perfectly machined to incredibly demanding specifications. The Laboratory's scientists and engineers have developed a device called the "Precision Robotic Assembly Machine" for this purpose. Its unique design won a prestigious R&D-100 award from R&D Magazine.

  19. Precision Robotic Assembly Machine

    SciTech Connect

    2009-08-14

    The world's largest laser system is the National Ignition Facility (NIF), located at Lawrence Livermore National Laboratory. NIF's 192 laser beams are amplified to extremely high energy, and then focused onto a tiny target about the size of a BB, containing frozen hydrogen gas. The target must be perfectly machined to incredibly demanding specifications. The Laboratory's scientists and engineers have developed a device called the "Precision Robotic Assembly Machine" for this purpose. Its unique design won a prestigious R&D-100 award from R&D Magazine.

  20. New photolithography stepping machine

    SciTech Connect

    Hale, L.; Klingmann, J.; Markle, D.

    1995-03-08

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

  1. Machining in Microgravity

    NASA Astrophysics Data System (ADS)

    Vincent, Graylan

    2003-01-01

    A CNC mill was flown aboard NASA's KC-135 ``Weightless Wonder'' microgravity research aircraft to investigate the effect of gravity on the machining process and to demonstrate the feasibility and functionality of a CNC mill in a weightless environment, such as aboard the International Space Station. The experiment hypothesis was that the surface roughness of milling cuts made in microgravity would be of higher quality than cuts made in a gravitational environment due to increased chip removal. The technical problems associated with microgravity machining (such as the chip removal and collection process), and the engineering solutions to these problems were also evaluated in this experiment.

  2. Automated fiber pigtailing machine

    DOEpatents

    Strand, Oliver T.; Lowry, Mark E.

    1999-01-01

    The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectonic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems.

  3. Automated fiber pigtailing machine

    DOEpatents

    Strand, O.T.; Lowry, M.E.

    1999-01-05

    The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectronic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems. 26 figs.

  4. Size distribution of PM at Cape Verde - Santiago Island

    NASA Astrophysics Data System (ADS)

    Pio, C.; Nunes, T.; Cardoso, J.; Caseiro, A.; Cerqueira, M.; Custodio, D.; Freitas, M. C.; Almeida, S. M.

    2012-04-01

    The archipelago of Cape Verde is located on the eastern North Atlantic, about 500 km west of the African coast. Its geographical location, inside the main area of dust transport over tropical Atlantic and near the coast of Africa, is strongly affected by mineral dust from the Sahara and the Sahel regions. In the scope of the CVDust project a surface field station was implemented in the surroundings of Praia City, Santiago Island (14° 55' N e 23° 29' W, 98 m at sea level), where aerosol sampling throughout different samplers was performed during one year. To study the size distribution of aerosol, an optical dust monitor (Grimm 180), from 0.250 to 32 μm in 31 size channels, was running almost continuously from January 2011 to December 2011. The performance of Grimm 180 to quantify PM mass concentration in an area affected by the transport of Saharan dust particles was evaluated throughout the sampling period by comparison with PM10 mass concentrations obtained with the gravimetric reference method (PM10 TSI High-Volume, PM10 Partisol and PM10 TCR-Tecora). PM10 mass concentration estimated with the Grimm 180 dust monitor, an optical counter, showed a good correlation with the reference gravimetric method, with R2= 0.94 and a linear regression equation of PM10Grimm = 0.81PM10TCR- 5.34. The number and mass size distribution of PM at ground level together with meteorological and back trajectories were analyzed and compared for different conditions aiming at identifying different signatures related to sources and dust transport. January and February, the months when most Saharan dust events occurred, showed the highest concentrations, with PM10 daily average of 66.6±60.2 μg m-3 and 91.6±97.4 μg m-3, respectively. During these months PM1 and PM2.5 accounted for less than 11% and 47% of PM10 respectively, and the contribution of fine fractions (PM1 and PM2.5) to PM mass concentrations tended to increase for the other months. During Saharan dust events, the PM2

  5. A multivariate study for characterizing particulate matter (PM(10), PM(2.5), and PM(1)) in Seoul metropolitan subway stations, Korea.

    PubMed

    Kwon, Soon-Bark; Jeong, Wootae; Park, Duckshin; Kim, Ki-Tae; Cho, Kyung Hwa

    2015-10-30

    Given that around eight million commuters use the Seoul Metropolitan Subway (SMS) each day, the indoor air quality (IAQ) of its stations has attracted much public attention. We have monitored the concentration of particulate matters (PMx) (i.e., PM10, PM2.5, and PM1) in six major transfer stations per minute for three weeks during the summer, autumn, and winter in 2014 and 2015. The data were analyzed to investigate the relationship between PMx concentration and multivariate environmental factors using statistical methods. The average PM concentration observed was approximately two or three times higher than outdoor PM10 concentration, showing similar temporal patterns at concourses and platforms. This implies that outdoor PM10 is the most significant factor in controlling indoor PM concentration. In addition, the station depth and number of trains passing through stations were found to be additional influences on PMx. Principal component analysis (PCA) and self-organizing map (SOM) were employed, through which we found that the number of trains influences PM concentration in the vicinity of platforms only, and PMx hotspots were determined. This study identifies the external and internal factors affecting PMx characteristics in six SMS stations, which can assist in the development of effective IAQ management plans to improve public health.

  6. 40 CFR Table C-4 to Subpart C of... - Test Specifications for PM10, PM2.5 and PM10-2.5 Candidate Equivalent Methods

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ...% 10% 2 10% 2 10% 2 10% 2 Precision of PM2.5 or PM10-2.5 candidate method, CP, each site 10% 2 15% 2 15% 2 15% 2 Slope of regression relationship 1 ± 0.10 1 ± 0.05 1 ± 0.10 1 ± 0.10 1 ± 0.10 1 ±...

  7. 40 CFR Table C-4 to Subpart C of... - Test Specifications for PM10, PM2.5 and PM10-2.5 Candidate Equivalent Methods

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...% 10% 2 10% 2 10% 2 10% 2 Precision of PM2.5 or PM10-2.5 candidate method, CP, each site 10% 2 15% 2 15% 2 15% 2 Slope of regression relationship 1 ± 0.10 1 ± 0.05 1 ± 0.10 1 ± 0.10 1 ± 0.10 1 ±...

  8. DEVELOPMENT AND EVALUATION OF A CONTINUOUS COARSE (PM10-PM2.5) PARTICLE MONITOR

    EPA Science Inventory

    In this paper, we describe the development and laboratory and field evaluation of a continuous coarse (2.5-10 um) particle mass (PM) monitor that can provide reliable measurements of the coarse mass (CM) concentrations in time intervals as short as 5-10 min. The operating princ...

  9. DEVELOPMENT AND EVALUATION OF A CONTINUOUS COARSE (PM10-PM2.5) PARTICLE MONITOR

    EPA Science Inventory

    In this paper, we describe the development and laboratory and field evaluation of a continuous coarse (2.5-10 um) particle mass (PM) monitor that can provide reliable measurements of the coarse mass (CM) concentrations in time intervals as short as 5-10 min. The operating princ...

  10. Gravimetric and chemical features of airborne PM 10 AND PM 2.5 in mainland Portugal.

    PubMed

    Freitas, M C; Farinha, M M; Ventura, M G; Almeida, S M; Reis, M A; Pacheco, A M G

    2005-10-01

    This paper describes concentration amounts of arsenic (As), particulate mercury (Hg), nickel (Ni) and lead (Pb) in PM(10) and PM(2.5), collected since 1993 by the Technological and Nuclear Institute (ITN) at different locations in mainland Portugal, featuring urban, industrial and rural environments, and a control as well. Most results were obtained in the vicinity of coal- and oil-fired power plants. Airborne mass concentrations were determined by gravimetry. As and Hg concentrations were obtained through instrumental neutron activation analysis (INAA), and Ni and Pb concentrations through proton-induced X-ray emission (PIXE). Comparison with the EU (European Union) and the US EPA (United States Environmental Protection Agency) directives for Ambient Air has been carried out, even though the sampling protocols herein--set within the framework of ITN's R&D projects and/or monitoring contracts--were not consistent with the former regulations. Taking this into account, 1) the EU daily limit for PM(10) was exceeded a few times in all sites except the control, even if the number of times was still inferior to the allowed one; 2) the EU annual mean for PM(10) was exceeded at one site; 3) the EPA daily limit for PM(2.5) was exceeded one time at three sites; 4) the EPA annual mean for PM(2.5) was exceeded at most sites; 5) the inner-Lisbon site approached or exceeded the legislated PMs; 6) Pb levels stayed far below the EU limit value; and 7) concentrations of As, Ni and Hg were also far less than the reference values adopted by EU. In every location, Ni appeared more concentrated in PM(2.5) than in coarser particles, and its levels were not that different from site to site, excluding the control. The highest As and Hg concentrations were found in the neighbourhood of the coal-fired, utility power plants. The results may be viewed as a "worst-case scenario" of atmospheric pollution, since they have been obtained in busy urban-industrial areas and/or near major power

  11. Analysis of PM10, PM2.5, and PM2 5-10 concentrations in Santiago, Chile, from 1989 to 2001.

    PubMed

    Koutrakis, Petros; Sax, Sonja N; Sarnat, Jeremy A; Coull, Brent; Demokritou, Phil; Oyola, Pedro; Garcia, Javier; Gramsch, Ernesto

    2005-03-01

    Daily particle samples were collected in Santiago, Chile, at four urban locations from January 1, 1989, through December 31, 2001. Both fine PM with da < 2.5 microm (PM2.5) and coarse PM with 2.5 < da < 10 microm (PM2.5-10) were collected using dichotomous samplers. The inhalable particle fraction, PM10, was determined as the sum of fine and coarse concentrations. Wind speed, temperature and relative humidity (RH) were also measured continuously. Average concentrations of PM2.5 for the 1989-2001 period ranged from 38.5 microg/m3 to 53 microg/m3. For PM2.5-10 levels ranged from 35.8-48.2 microg/m3 and for PM10 results were 74.4-101.2 microg/m3 across the four sites. Both annual and daily PM2.5 and PM10 concentration levels exceeded the U.S. National Ambient Air Quality Standards and the European Union concentration limits. Mean PM2.5 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March); whereas coarse particle levels were similar in both seasons. PM concentration trends were investigated using regression models, controlling for site, weekday, month, wind speed, temperature, and RH. Results showed that PM2.5 concentrations decreased substantially, 52% over the 12-year period (1989-2000), whereas PM2.5-10 concentrations increased by approximately 50% in the first 5 years and then decreased by a similar percentage over the following 7 years. These decreases were evident even after controlling for significant climatic effects. These results suggest that the pollution reduction programs developed and implemented by the Comisión Nacional del Medio Ambiente (CONAMA) have been effective in reducing particle levels in the Santiago Metropolitan region. However, particle levels remain high and it is thus imperative that efforts to improve air quality continue.

  12. In vitro investigations of platinum, palladium, and rhodium mobility in urban airborne particulate matter (PM10, PM2.5, and PM1) using simulated lung fluids.

    PubMed

    Zereini, Fathi; Wiseman, Clare L S; Püttmann, Wilhelm

    2012-09-18

    Environmental concentrations of platinum group elements (PGE) have been increasing since the introduction of automotive catalytic converters to control harmful emissions. Assessments of the human health risks of exposures to these elements, especially through the inhalation of PGE-associated airborne particulate matter (PM), have been hampered by a lack of data on their bioaccessibility. The purpose of this study is to apply in vitro methods using simulated human lung fluids [artificial lysosomal fluid (ALF) and Gamble's solution] to assess the mobility of the PGE, platinum (Pt), palladium (Pd), and rhodium (Rh) in airborne PM of human health concern. Airborne PM samples (PM(10), PM(2.5), and PM(1)) were collected in Frankfurt am Main, Germany. For comparison, the same extraction experiments were conducted using the standard reference material, Used Auto Catalyst (monolith) (NIST 2557). Pt and Pd concentrations were measured using isotope dilution ICP-Q-MS, while Rh was measured directly with ICP-Q-MS (in collision mode with He), following established matrix separation and enrichment procedures, for both solid (filtered residues) and extracted sample phases. The mobilized fractions measured for PGE in PM(10), PM(2.5), and PM(1) were highly variable, which can be attributed to the heterogenic nature of airborne PM and its composition. Overall, the mobility of PGE in airborne PM samples was notable, with a mean of 51% Rh, 22% Pt, and 29% Pd present in PM(1) being mobilized by ALF after 24 h. For PM(1) exposed to Gamble's solution, a mean of 44% Rh, 18% Pt, and 17% Pd was measured in solution after 24 h. The mobility of PGE associated with airborne PM was also determined to be much higher compared to that measured for the auto catalyst standard reference material. The results suggest that PGE emitted from automotive catalytic converters are likely to undergo chemical transformations during and/or after being emitted in the environment. This study highlights the need

  13. ENSO-related PM10 variability on the Korean Peninsula

    NASA Astrophysics Data System (ADS)

    Wie, Jieun; Moon, Byung-Kwon

    2017-10-01

    Particulate matter, defined as particles of less than 10 μm in diameter (PM10), was analyzed over the Korean Peninsula from 2001 to 2015 to examine the influence of the El Niño-Southern Oscillation (ENSO) on subseasonal PM10 variability. The PM10 data were obtained from 151 air quality monitoring stations provided by the Korea Environment Corporation (KECO). Lead-lag correlation analysis, which was performed to investigate the connection between NDJF (November-February) NINO3 index and seasonal mean PM10 data, did not yield any statistically significant correlations. However, using five-pentad moving-averaged PM10 data, statistically significant correlations between NDJF NINO3 index and PM10 variability were found in four subseasonal periods, with alternating positive and negative correlations. In the periods during which PM10 levels on the Korean Peninsula were positively (negatively) correlated with the ENSO index, the positive PM10 anomalies are associated with El Niño (La Niña) years, which implies that the occurrence of high-PM10 events could be modulated by the ENSO phase. In addition, this ENSO-related PM10 variation is negatively correlated with ENSO-related precipitation in the Korean Peninsula, indicating that more (less) wet deposition leads to lower (higher) PM10 level. Therefore, we conclude that the ENSO-induced precipitation anomalies over the Korean Peninsula are mainly responsible for ENSO-related PM10 variations. This study will be helpful for further identifying detailed chemistry-climate processes that control PM10 concentrations.

  14. Design and analysis of linear fault-tolerant permanent-magnet vernier machines.

    PubMed

    Xu, Liang; Ji, Jinghua; Liu, Guohai; Du, Yi; Liu, Hu

    2014-01-01

    This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis.

  15. Design and Analysis of Linear Fault-Tolerant Permanent-Magnet Vernier Machines

    PubMed Central

    Xu, Liang; Liu, Guohai; Du, Yi; Liu, Hu

    2014-01-01

    This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis. PMID:24982959

  16. 14. Machine in north 1922 section of Building 59. Machine ...

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

    14. Machine in north 1922 section of Building 59. Machine is 24' Jointer made by Oliver Machinery Co. Camera pointed E. - Puget Sound Naval Shipyard, Pattern Shop, Farragut Avenue, Bremerton, Kitsap County, WA

  17. BRASS FOUNDRY MACHINE ROOM USED TO MACHINE CAST BRONZE PIECES ...

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

    BRASS FOUNDRY MACHINE ROOM USED TO MACHINE CAST BRONZE PIECES FOR VALVES AND PREPARE BRONZE VALVE BODIES FOR ASSEMBLY. - Stockham Pipe & Fittings Company, Brass Foundry, 4000 Tenth Avenue North, Birmingham, Jefferson County, AL

  18. 12. Photocopied August 1978. CHANNELING MACHINES, NOVEMBER 1898. THESE MACHINES ...

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

    12. Photocopied August 1978. CHANNELING MACHINES, NOVEMBER 1898. THESE MACHINES BLOCKED OUT SECTIONS IN THE ROCK CUT IN PREPARATION FOR DRILLING AND BLASTING. (17) - Michigan Lake Superior Power Company, Portage Street, Sault Ste. Marie, Chippewa County, MI

  19. 42. MACHINE SHOP Machine shop area with small parts bins ...

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

    42. MACHINE SHOP Machine shop area with small parts bins on the right and pipe storage racks on the left. Remains of the power drive system are suspended from the ceiling. - Hovden Cannery, 886 Cannery Row, Monterey, Monterey County, CA

  20. Machine learning techniques and drug design.

    PubMed

    Gertrudes, J C; Maltarollo, V G; Silva, R A; Oliveira, P R; Honório, K M; da Silva, A B F

    2012-01-01

    The interest in the application of machine learning techniques (MLT) as drug design tools is growing in the last decades. The reason for this is related to the fact that the drug design is very complex and requires the use of hybrid techniques. A brief review of some MLT such as self-organizing maps, multilayer perceptron, bayesian neural networks, counter-propagation neural network and support vector machines is described in this paper. A comparison between the performance of the described methods and some classical statistical methods (such as partial least squares and multiple linear regression) shows that MLT have significant advantages. Nowadays, the number of studies in medicinal chemistry that employ these techniques has considerably increased, in particular the use of support vector machines. The state of the art and the future trends of MLT applications encompass the use of these techniques to construct more reliable QSAR models. The models obtained from MLT can be used in virtual screening studies as well as filters to develop/discovery new chemicals. An important challenge in the drug design field is the prediction of pharmacokinetic and toxicity properties, which can avoid failures in the clinical phases. Therefore, this review provides a critical point of view on the main MLT and shows their potential ability as a valuable tool in drug design.

  1. Machine speech and speaking about machines

    SciTech Connect

    Nye, A.

    1996-12-31

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

  2. Fatigue life and performance testing of hybrid ceramic ball bearings

    SciTech Connect

    Chiu, Y.P.; Prason, P.K.; Dezzani, M.

    1996-03-01

    Hybrid ceramic ball bearings are finding increased applications in machine tool spindles and aerospace vehicles. Results of three types of testing hybrid ceramic ball bearing are presented and discussed. The first is the classical endurance testing of highly loaded hybrid bearings with good lubrication. The second is the endurance test of hybrid nitrided bearings after running in a contaminated lubricant which caused dented raceways. The third is the high-speed performance testing of spindle bearings lubricated with grease or an oil-air mixture. Recent material development, bearing temperature at high-speed and reliability considerations are discussed. 14 refs., 9 fig., 4 tab.

  3. Contamination characteristics and possible sources of PM10 and PM2.5 in different functional areas of Shanghai, China

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Hu, Zimei; Chen, Yuanyuan; Chen, Zhenlou; Xu, Shiyuan

    2013-04-01

    From July 2009 through September 2010, PM10 and PM2.5 were collected at two different functional areas in Shanghai (Baoshan district, an industrial area, and Putuo district, a mixed-use area of residential, commercial, and educational compounds). In our analysis, 15 elements were determined using a 710-ES Inductively Coupled Plasma-Emission Spectrometer (ICP-AES). The contents of PM2.5, PM10, and metal elements at the two different sites were comparatively analyzed. The results show that the mean annual concentrations of PM10 and PM2.5 (149.22 μg m-3 and 103.07 μg m-3, respectively) in Baoshan district were significantly higher than those in Putuo district (97.44 μg m-3 and 62.25 μg m-3 respectively). The concentrations of PM10 and PM2.5 were both greatest in winter and lowest in summer, with the two different sites exhibiting the same seasonal variation. It was found that the proportions of 15 metal elements in PM10 and PM2.5 in Baoshan district were 20.49% and 20.56%, respectively, while the proportions in Putuo district were higher (25.98% and 25.93%, respectively). In addition, the proportions of eight heavy metals in PM10 and PM2.5 were 5.50% and 3.07%, respectively, for Baoshan district, while these proportions in Putuo district were 3.18% and 2.77%, respectively, indicating that heavy metal pollution is more pronounced in Baoshan district. Compared with cities in developed countries, the total levels of PM10, PM2.5 and heavy metals in Shanghai were slightly higher. Scanning electron microscopy (SEM) and principal component analysis (PCA) suggested that the possible sources of PM10 in Baoshan district were ground level fugitive dust, traffic sources, and industrial activities, whereas PM2.5 mainly originated from industrial activities, coal combustion, and traffic sources. The sources are same for PM10 and PM2.5 in Putuo region, which originate from traffic sources and ground level fugitive dust.

  4. Characteristics of vertical profiles and sources of PM 2.5, PM 10 and carbonaceous species in Beijing

    NASA Astrophysics Data System (ADS)

    Chan, C. Y.; Xu, X. D.; Li, Y. S.; Wong, K. H.; Ding, G. A.; Chan, L. Y.; Cheng, X. H.

    In August 2003 during the anticipated month of the 2008 Beijing Summer Olympic Games, we simultaneously collected PM 10 and PM 2.5 samples at 8, 100, 200 and 325 m heights up a meteorological tower and in an urban and a suburban site in Beijing. The samples were analysed for organic carbon (OC) and elemental carbon (EC) contents. Particulate matter (PM) and carbonaceous species pollution in the Beijing region were serious and widespread with 86% of PM 2.5 samples exceeding the daily National Ambient Air Quality Standard of the USA (65 μg m -3) and the overall daily average PM 10 concentrations of the three surface sites exceeding the Class II National Air Quality Standard of China (150 μg m -3). The maximum daily PM 2.5 and PM 10 concentrations reached 178.7 and 368.1 μg m -3, respectively, while those of OC and EC reached 22.2 and 9.1 μg m -3 in PM 2.5 and 30.0 and 13.0 μg m -3 in PM 10, respectively. PM, especially PM 2.5, OC and EC showed complex vertical distributions and distinct layered structures up the meteorological tower with elevated levels extending to the 100, 200 and 300 m heights. Meteorological evidence suggested that there exist fine atmospheric layers over urban Beijing. These layers were featured by strong temperature inversions close to the surface (<50 m) and more stable conditions aloft. They enhanced the accumulation of pollutants and probably caused the complex vertical distributions of PM and carbonaceous species over urban Beijing. The built-up of PM was accompanied by transport of industrial emissions from the southwest direction of the city. Emissions from road traffic and construction activities as well as secondary organic carbon (SOC) are important sources of PM. High OC/EC ratios (range of 1.8-5.1 for PM 2.5 and 2.0-4.3 for PM 10) were found, especially in the higher levels of the meteorological tower suggesting there were substantial productions of SOC in summer Beijing. SOC is estimated to account for at least 33.8% and 28

  5. Support vector machines

    NASA Technical Reports Server (NTRS)

    Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

    2004-01-01

    Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

  6. The Answer Machine.

    ERIC Educational Resources Information Center

    Feldman, Susan

    2000-01-01

    Discusses information retrieval systems and the need to have them adapt to user needs, integrate information in any format, reveal patterns and trends in information, and answer questions. Topics include statistics and probability; natural language processing; intelligent agents; concept mapping; machine-aided indexing; text mining; filtering;…

  7. Machine Parts as Metaphor.

    ERIC Educational Resources Information Center

    Porter, Gerald

    The connection between Language for Specific Purposes (LSP) and literature is discussed with examples of technical vocabulary drawn from a variety of writers, with particular attention to a sketch by the British dramatist Harold Pinter, "Trouble in the Works," which makes extensive use of the terminology of machine parts. It is noted…

  8. Laser machining of explosives

    SciTech Connect

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

    2000-01-01

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

  9. History of wood machining

    Treesearch

    Peter Koch

    1967-01-01

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

  10. Copy Machine Art.

    ERIC Educational Resources Information Center

    Sommer, Jean

    1984-01-01

    Images created with copy machines make children feel successful, as their work acquires the authority of being printed. Students can learn advanced processes like electrostatic image-making and can get involved in projects like making collages. They acquire an appreciation of design and of two-dimensional composition. (CS)

  11. Biomimetic machine vision system.

    PubMed

    Harman, William M; Barrett, Steven F; Wright, Cameron H G; Wilcox, Michael

    2005-01-01

    Real-time application of digital imaging for use in machine vision systems has proven to be prohibitive when used within control systems that employ low-power single processors without compromising the scope of vision or resolution of captured images. Development of a real-time machine analog vision system is the focus of research taking place at the University of Wyoming. This new vision system is based upon the biological vision system of the common house fly. Development of a single sensor is accomplished, representing a single facet of the fly's eye. This new sensor is then incorporated into an array of sensors capable of detecting objects and tracking motion in 2-D space. This system "preprocesses" incoming image data resulting in minimal data processing to determine the location of a target object. Due to the nature of the sensors in the array, hyperacuity is achieved thereby eliminating resolutions issues found in digital vision systems. In this paper, we will discuss the biological traits of the fly eye and the specific traits that led to the development of this machine vision system. We will also discuss the process of developing an analog based sensor that mimics the characteristics of interest in the biological vision system. This paper will conclude with a discussion of how an array of these sensors can be applied toward solving real-world machine vision issues.

  12. Cybernetic anthropomorphic machine systems

    NASA Technical Reports Server (NTRS)

    Gray, W. E.

    1974-01-01

    Functional descriptions are provided for a number of cybernetic man machine systems that augment the capacity of normal human beings in the areas of strength, reach or physical size, and environmental interaction, and that are also applicable to aiding the neurologically handicapped. Teleoperators, computer control, exoskeletal devices, quadruped vehicles, space maintenance systems, and communications equipment are considered.

  13. Working with Simple Machines

    ERIC Educational Resources Information Center

    Norbury, John W.

    2006-01-01

    A set of examples is provided that illustrate the use of work as applied to simple machines. The ramp, pulley, lever and hydraulic press are common experiences in the life of a student, and their theoretical analysis therefore makes the abstract concept of work more real. The mechanical advantage of each of these systems is also discussed so that…

  14. Protein thin film machines.

    PubMed

    Federici, Stefania; Oliviero, Giulio; Hamad-Schifferli, Kimberly; Bergese, Paolo

    2010-12-01

    We report the first example of microcantilever beams that are reversibly driven by protein thin film machines fueled by cycling the salt concentration of the surrounding solution. We also show that upon the same salinity stimulus the drive can be completely reversed in its direction by introducing a surface coating ligand. Experimental results are throughout discussed within a general yet simple thermodynamic model.

  15. Support vector machines

    NASA Technical Reports Server (NTRS)

    Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

    2004-01-01

    Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

  16. Machine Aids to Translation.

    ERIC Educational Resources Information Center

    Brinkmann, Karl-Heinz

    1981-01-01

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

  17. The Art Machine.

    ERIC Educational Resources Information Center

    Vertelney, Harry; Grossberger, Lucia

    1983-01-01

    Introduces educators to possibilities of computer graphics using an inexpensive computer system which takes advantage of existing equipment (35mm camera, super 8 movie camera, VHS video cassette recorder). The concept of the "art machine" is explained, highlighting input and output devices (X-Y plotter, graphic tablets, video…

  18. Working with Simple Machines

    ERIC Educational Resources Information Center

    Norbury, John W.

    2006-01-01

    A set of examples is provided that illustrate the use of work as applied to simple machines. The ramp, pulley, lever and hydraulic press are common experiences in the life of a student, and their theoretical analysis therefore makes the abstract concept of work more real. The mechanical advantage of each of these systems is also discussed so that…

  19. Machine Aids to Translation.

    ERIC Educational Resources Information Center

    Brinkmann, Karl-Heinz

    1981-01-01

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

  20. Introduction to Exploring Machines

    ERIC Educational Resources Information Center

    Early Childhood Today, 2006

    2006-01-01

    Young children are fascinated by how things "work." They are at a stage of development where they want to experiment with the many ways to use an object or take things apart and put them back together. In the process of exploring tools and machines, children use the scientific method and problem-solving skills. They observe how things work, wonder…