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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 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Machine learning models for lung cancer classification using array comparative genomic hybridization.

    PubMed

    Aliferis, C F; Hardin, D; Massion, P P

    2002-01-01

    Array CGH is a recently introduced technology that measures changes in the gene copy number of hundreds of genes in a single experiment. The primary goal of this study was to develop machine learning models that classify non-small Lung Cancers according to histopathology types and to compare several machine learning methods in this learning task. DNA from tumors of 37 patients (21 squamous carcinomas, and 16 adenocarcinomas) were extracted and hybridized onto a 452 BAC clone array. The following algorithms were used: KNN, Decision Tree Induction, Support Vector Machines and Feed-Forward Neural Networks. Performance was measured via leave-one-out classification accuracy. The best multi-gene model found had a leave-one-out accuracy of 89.2%. Decision Trees performed poorer than the other methods in this learning task and dataset. We conclude that gene copy numbers as measured by array CGH are, collectively, an excellent indicator of histological subtype. Several interesting research directions are discussed.

  9. 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.

  10. 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.

  11. 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.

  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. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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

  20. 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.

  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. 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.

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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

  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. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  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. 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

  13. 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.

  14. 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%.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. The Virtual PM

    DTIC Science & Technology

    2013-11-01

    management principles that have brought us to where we are today. Without the likes of Frederick Taylor, W. Edwards Deming, Peter Drucker , Milton...The Virtual PM Robert L. Weinhold Weinhold is a senior acquisition specialist and consultant with Jacobs Technology supporting the Product Manager ...He is a retired U.S. Air Force lieutenant colonel. The era of the Virtual PM (project manager ) is alive and well! In an age of cellphones

  4. 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 .

  5. 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

  6. 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.

  7. 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...

  8. 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…

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Intelligent Vehicle Power Management Using Machine Learning and Fuzzy Logic

    DTIC Science & Technology

    2008-06-01

    machine learning and fuzzy logic. A machine learning algorithm, LOPPS, has been developed to learn about optimal power source combinations with... machine learning algorithm combined with fuzzy logic is a promising technology for vehicle power management. I. INTRODUCTION ROWING...sources, and the complex configuration and operation modes, the control strategy of a hybrid vehicle is more complicated than that of a conventional

  1. 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.

  2. 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.

  3. 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

  4. 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…

  5. 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)

  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. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  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

    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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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....

  5. 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

  6. 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.

  7. 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.

  8. 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…

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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)).

  20. 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).

  1. 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.

  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. 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

  4. [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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  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. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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;…

  15. 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

  16. 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,...

  17. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  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. 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...

  7. 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).

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  14. Agent Based Computing Machine

    DTIC Science & Technology

    2005-12-09

    coordinates as in cellular automata systems. But using biology as a model suggests that the most general systems must provide for partial, but constrained...17. SECURITY CLASSIFICATION OF 118. SECURITY CLASSIFICATION OF 19. SECURITY CLASSIFICATION OF 20. LIMITATION OF ABSTRA REPORT THIS PAGE ABSTRACT...system called an "agent based computing" machine (ABC Machine). The ABC Machine is motivated by cellular biochemistry and it is based upon a concept

  15. 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 ...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  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. 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

  4. 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.

  5. 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.

  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. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  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. 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...

  14. 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.

  15. 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 ...

  16. 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

  17. 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.

  18. 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…

  19. 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)

  20. 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)

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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…

  7. 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,…

  8. 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.

  9. 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

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  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...

  15. 40 CFR 1065.290 - PM gravimetric balance.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 32 2010-07-01 2010-07-01 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 40 CFR 52.2182 - PM10 Committal SIP.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 5 2013-07-01 2013-07-01 false PM10 Committal SIP. 52.2182 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2182 PM10 Committal SIP. On July 12 1988, the State submitted a Committal SIP for the Rapid City Group II PM10 area, as required...

  1. 40 CFR 52.2182 - PM10 Committal SIP.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 4 2011-07-01 2011-07-01 false PM10 Committal SIP. 52.2182 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2182 PM10 Committal SIP. On July 12 1988, the State submitted a Committal SIP for the Rapid City Group II PM10 area, as required...

  2. 40 CFR 52.2182 - PM10 Committal SIP.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 5 2014-07-01 2014-07-01 false PM10 Committal SIP. 52.2182 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2182 PM10 Committal SIP. On July 12 1988, the State submitted a Committal SIP for the Rapid City Group II PM10 area, as required...

  3. 40 CFR 52.2182 - PM10 Committal SIP.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 4 2010-07-01 2010-07-01 false PM10 Committal SIP. 52.2182 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2182 PM10 Committal SIP. On July 12 1988, the State submitted a Committal SIP for the Rapid City Group II PM10 area, as required...

  4. 40 CFR 52.2182 - PM10 Committal SIP.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 5 2012-07-01 2012-07-01 false PM10 Committal SIP. 52.2182 Section 52...) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) South Dakota § 52.2182 PM10 Committal SIP. On July 12 1988, the State submitted a Committal SIP for the Rapid City Group II PM10 area, as required...

  5. 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.

  6. 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.

  7. 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.

  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. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. {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.

  20. [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.

  1. [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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. Sealing intersecting vane machines

    SciTech Connect

    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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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).

  17. 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.

  18. 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

  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. 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.

  1. 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 ±...

  2. 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 ±...

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Quantitative analysis on windblown dust concentrations of PM10 (PM2.5) during dust events in Mongolia

    NASA Astrophysics Data System (ADS)

    Jugder, Dulam; Shinoda, Masato; Kimura, Reiji; Batbold, Altangerel; Amarjargal, Danzansambuu

    2014-09-01

    Dust concentration, wind speed and visibility, measured at four sites in the Gobi Desert and at a site in the steppe zone of Mongolia over a period of 4.5 years (January 2009 to May 2013), have been analyzed for their relationships, their effects on visibility, and for an estimate of the threshold wind necessary for dust emission in the region. Based on quantitative analysis on measurements, we evaluated that dust emission concentrations of 41-61 (20-24) μg m-3 of PM10 (PM2.5) are as the criterion between normal and hazy atmospheric conditions. With the arrival of dust events, wind-borne soil particulate matter (PM10, PM2.5) that originates in the Gobi Desert is changed dramatically. PM10 (PM2.5) concentrations increase by at least double or by several tens of times during severe dust events in comparison with the normal atmospheric condition. Ratio (PM2.5/PM10) between monthly means of PM10 and PM2.5 concentrations showed that anthropogenic particles were dominant in the ambient air of province centers in cool months (November to February). Threshold values of the onset of dust events were determined for PM10 (PM2.5) concentrations. According to the definition of dust storms, dust concentrations of PM10 corresponding to visibility of 1 km or less were determined at sites in the Gobi Desert and the steppe region. The threshold wind speeds during days with dust events were estimated at four sites in the Gobi Desert and compared each other. The threshold wind was higher at Sainshand and its cause might be due to smaller silt and clay fractions of soil.

  11. 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.

  12. 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.

  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. 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.

  15. EPA's proposal to revise the PM standards

    SciTech Connect

    Steve Page

    2006-06-15

    Over the next few months, the US Environmental Protection Agency (EPA) will be finalizing its proposal to revise the National Ambient Air Quality Standards (NAAQS) for fine and coarse particulate matter (PM). Since issuing the proposal in December 2005, the agency has sought comments from all interested parties, and will base its final decision on the record that was established through the comment period, which ended on April 17. In this issue articles present perspectives from some of the many non-EPA stakeholders who have played an important role in this review process. This article summarizes EPA's proposal, as well as the extensive process EPA goes through when setting air quality standards. 1 fig., 2 tabs.

  16. Chemical and morphological properties of particulate matter (PM 10, PM 2.5) in school classrooms and outdoor air

    NASA Astrophysics Data System (ADS)

    Fromme, H.; Diemer, J.; Dietrich, S.; Cyrys, J.; Heinrich, J.; Lang, W.; Kiranoglu, M.; Twardella, D.

    Studies have shown high concentrations of particulate matter (PM) in schools. Further insights into the sources and the composition of these particles are needed. During school hours for a period of 6 weeks, outdoor air and the air in two classrooms were sampled. PM was measured gravimetrically, and PM filters were used for the determination of the elemental and organic carbon, light absorbance, and 10 water-soluble ions. Some filters were further analyzed by scanning electron microscopy (SEM) and energy dispersive microanalysis (EDX). The median PM 10 concentrations were 118.2 μg m -3 indoors and 24.2 μg m -3 outdoors; corresponding results for PM 2.5 were 37.4 μg m -3 indoors and 17.0 μg m -3 outdoors. Using PM 10 and PM 2.5 data, we calculated the following indoor/outdoor ratios: 0.3 and 0.4 (sulfate), 0.1 and 0.2 (nitrate), 0.1 and 0.3 (ammonium), and 1.4 and 1.6 (calcium). Using the measured sulfate content on PM filters as an indicator for ambient PM sources, we estimated that 43% of PM 2.5 and 24% of PM 10, respectively, were of ambient origin. The composition of the classrooms' PM (e.g., high calcium concentrations) and the findings from SEM/EDX suggest that the indoor PM consists mainly of earth crustal materials, detrition of the building materials and chalk. Physical activity of the pupils leads to resuspension of mainly indoor coarse particles and greatly contributes to increased PM 10 in classrooms. The concentration of fine particles caused by combustion processes indoors and outdoors is comparable. We conclude that PM measured in classrooms has major sources other than outdoor particles. Assuming that combustion-related particles and crustal materials vary in toxicity, our results support the hypothesis that indoor-generated PM may be less toxic compared to PM in ambient air.

  17. Non-exhaust PM emissions from electric vehicles

    NASA Astrophysics Data System (ADS)

    Timmers, Victor R. J. H.; Achten, Peter A. J.

    2016-06-01

    Particulate matter (PM) exposure has been linked to adverse health effects by numerous studies. Therefore, governments have been heavily incentivising the market to switch to electric passenger cars in order to reduce air pollution. However, this literature review suggests that electric vehicles may not reduce levels of PM as much as expected, because of their relatively high weight. By analysing the existing literature on non-exhaust emissions of different vehicle categories, this review found that there is a positive relationship between weight and non-exhaust PM emission factors. In addition, electric vehicles (EVs) were found to be 24% heavier than equivalent internal combustion engine vehicles (ICEVs). As a result, total PM10 emissions from EVs were found to be equal to those of modern ICEVs. PM2.5 emissions were only 1-3% lower for EVs compared to modern ICEVs. Therefore, it could be concluded that the increased popularity of electric vehicles will likely not have a great effect on PM levels. Non-exhaust emissions already account for over 90% of PM10 and 85% of PM2.5 emissions from traffic. These proportions will continue to increase as exhaust standards improve and average vehicle weight increases. Future policy should consequently focus on setting standards for non-exhaust emissions and encouraging weight reduction of all vehicles to significantly reduce PM emissions from traffic.

  18. 40 CFR 60.672 - Standard for particulate matter (PM).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Standards of Performance for Nonmetallic Mineral Processing Plants § 60.672 Standard for particulate matter (PM). (a) Affected...

  19. 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.

  20. 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.

  1. The Bateman Flotation Machine

    SciTech Connect

    Bezuidenhout, G.

    1995-12-31

    The newly developed Bateman Flotation Machine has proven its versatility in roughing and cleaning flotation circuits. This mechanical flotation machine has the dual performance capability of suspending solids and dispersing air at relatively low power inputs without compromising these two important fundamentals. This new development has been successfully marketed to a wide cross section of concentrator mineral processes. The mechanical design of the flotation mechanism has been optimized to reduce operational costs and to lower manufacturing costs. Production process environments were utilized for verification of the scale-up of each cell volume size rated mechanism. These thorough investigations produced performance data which could be accurately quoted. This paper is a historical account of the Batement Flotation Machine. Technical details of the development are covered with descriptions of the operational applications.

  2. 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.

  3. 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.

  4. 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

  5. Water soluble organic carbon in aerosols (PM1, PM2.5, PM10) and various precipitation forms (rain, snow, mixed) over the southern Baltic Sea station.

    PubMed

    Witkowska, Agnieszka; Lewandowska, Anita U

    2016-12-15

    In the urbanized coastal zone of the Southern Baltic, complex measurements of water soluble organic carbon (WSOC) were conducted between 2012 and 2015, involving atmospheric precipitation in its various forms (rain, snow, mixed) and PM1, PM2.5 and PM10 aerosols. WSOC constituted about 60% of the organic carbon mass in aerosols of various sizes. The average concentration of WSOC was equal to 2.6μg∙m(-3) in PM1, 3.6μg∙m(-3) in PM2.5 and 4.4μg∙m(-3) in PM10. The lowest concentration of WSOC was noted in summer as a result of effective removal of this compound with rainfall. The highest WSOC concentrations in PM2.5 and PM10 aerosols were measured in spring, which should be associated with developing vegetation on land and in the sea. On the other hand, the highest WSOC concentrations in PM1 occurred in winter at low air temperatures and greatest atmospheric stability, when there were increased carbon emissions from fuel combustion in the communal-utility sector and from transportation. WSOC concentrations in precipitation were determined by its form. Mixed precipitation turned out to be the richest in soluble organic carbon (5.1mg·dm(-3)), while snow contained the least WSOC (1.7mg·dm(-3)). Snow and rain cleaned carbon compounds from the atmosphere more effectively when precipitation lasted longer than 24h, while in the case of mixed precipitation WSOC was removed most effectively within the first 24h.

  6. 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.

  7. 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.

  8. Intersecting vane machines

    SciTech Connect

    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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Influence of PM1 and PM2.5 on lung function parameters in healthy schoolchildren-a panel study.

    PubMed

    Zwozdziak, A; Sówka, I; Willak-Janc, E; Zwozdziak, J; Kwiecińska, K; Balińska-Miśkiewicz, W

    2016-12-01

    To evaluate lung function responses to short-term indoor PM1 and PM2.5 concentrations, we conducted a panel study of healthy schoolchildren aged 13-14 years. The following lung function parameters FVC, FEV1, PEF, and mid expiratory flows MEF25, MEF50, and MEF75 were measured in 141 schoolchildren of the secondary school in Wroclaw, Poland in years 2009-2010. On days when spirometry tests were conducted, simultaneously, PM1 and PM2.5 samples were collected inside the school premises. Information about differentiating factors for children including smoking parents, sex, living close to busy streets, dust, mold, and pollen allergies were collected by means of questionnaires. To account for repeated measurements, the method of generalized estimating equations (GEE) was used. The GEE models for the entire group of children revealed the adverse effects (p < 0.05) of PM1 and PM2.5. Small differences in effects estimates per interquartile range (IQR) of PM1 and PM2.5 on MEF25 (5.1 and 4.8 %), MEF50 (3.7 and 3.9 %), MEF75 (3.5 and 3.6 %) and FEV1 (1.3 and 1.0 %) imply that PM1 was likely the component of PM2.5 that might have a principal health effect on these lung function parameters. However, the reduction of FVC and PEF per IQR for PM2.5 (2.1 and 5.2 %, respectively) was higher than for PM1 (1.0 and 4.4 %, respectively). Adjustment for potential confounders did not change the unadjusted analysis.

  15. Impact of Middle Eastern dust sources on PM10 in Iran: Highlighting the impact of Tigris-Euphrates basin sources and Lake Urmia desiccation

    NASA Astrophysics Data System (ADS)

    Sotoudeheian, Saeed; Salim, Reza; Arhami, Mohammad

    2016-12-01

    Contribution of different Middle Eastern dust origins to PM10 (PM with aerodynamic diameters less than 10 µm) levels in several receptor large cities in Iran was investigated. Initially, the major regional dust episodes were determined through statistical analysis of recorded PM levels at air quality stations and verified using satellite images. The particles dispersion was simulated by Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) to regenerate PM10 during the dust episodes. The accuracy of the modeled results was rather convincing, with an average squared correlation coefficient (R2) of 0.7 (max = 0.95). Consequently, the contributions of different dust sources to the observed concentrations were determined. Basin of Tigris-Euphrates Rivers encompasses active dust sources with significant rate of emission due to fluvial deposits. The sources in this basin with approximately 70-95% contribution, by far, had the most influence on PM10 levels at the receptor cities. In a finer resolution, northern and central parts of Iraq had the most influence on PM10 level during the dust episodes. Effect of probable improvement or deterioration of the current dust origin conditions on PM10 levels was analyzed by performing a sensitivity analysis through varying threshold friction velocities. The results demonstrated that 10% increase or decrease in threshold friction velocities of major dust sources could lead to average of 51% decrease or 77% increase in the receptor cities' PM10, respectively. Finally, effects of Lake Urmia desiccation, as a new hydrological prospect dust origin were analyzed. The predicted dust from the prospective dried lake bed could result in 30-60% increase in PM10 of nearby cities during the studied dust episodes.

  16. Characterization of Fine Particulate Matter (PM) and Secondary PM Precursor Gases in Mexico City

    SciTech Connect

    Dr. Charles E. Kolb Dr. Douglas R. Worsnop Dr. Manjula R. Canagaratna Dr. Scott C. Herndon Dr. John T. Jayne Dr. W. Berk Knighton Dr. Timothy B. Onasch Dr. Ezra C. Wood Dr. Miguel Zavala

    2008-03-31

    This project was one of three collaborating grants designed to understand the atmospheric chemistry and aerosol particle microphysics impacting air quality in the Mexico City Metropolitan Area (MCMA) and its urban plume. The overall effort, titled MCMA- 2006, focused on: 1) the primary emissions of fine particles and precursor gases leading to photochemical production of atmospheric oxidants and secondary aerosol particles and 2) the measurement and analysis of secondary oxidants and secondary fine particular matter (PM) production, with particular emphasis on secondary organic aerosol (SOA). MCAM-2006 pursued it goals through three main activities: 1) performance and publication of detailed analyses of extensive MCMA trace gas and fine PM measurements made by the collaborating groups and others during earlier MCMA field campaigns in 2002 and 2003; 2) deployment and utilization of extensive real-time trace gas and fine PM instrumentation at urban and downwind MCMA sites in support of the MAX-Mex/MILAGRO field measurements in March, 2006; and, 3) analyses of the 2006 MCMA data sets leading to further publications that are based on new data as well as insights from analysis and publication of the 2002/2003 field data. Thirteen archival publications were coauthored with other MCMA-2003 participants. Documented findings included a significantly improved speciated emissions inventory from on-road vehicles, a greatly enhanced understanding of the sources and atmospheric loadings of volatile organic compounds, a unique analysis of the high fraction of ambient formaldehyde from primary emission sources, a much more extensive knowledge of the composition, size distributions and atmospheric mass loadings of both primary and secondary fine PM, including the fact that the rate of MCMA SOA production greatly exceeded that predicted by current atmospheric models, and evaluations of significant errors that can arise from standard air quality monitors for ozone and nitrogen

  17. Global emissions of PM10 and PM2.5 from agricultural tillage and harvesting operations

    NASA Astrophysics Data System (ADS)

    Chen, W.; Tong, D.; Lee, P.

    2014-12-01

    Soil particles emitted during agricultural activities is a major recurring source contributing to atmospheric aerosol loading. Emission inventories of agricultural dust emissions have been compiled in several regions. These inventories, compiled based on historic survey and activity data, may reflect the current emission strengths that introduce large uncertainties when they are used to drive chemical transport models. In addition, there is no global emission inventory of agricultural dust emissions required to support global air quality and climate modeling. In this study, we present our recent efforts to develop a global emission inventory of PM10 and PM2.5 released from field tillage and harvesting operations using an emission factors-based approach. Both major crops (e.g., wheat and corn) and forage production were considered. For each crop or forage, information of crop area, crop calendar, farming activities and emission factors of specified operations were assembled. The key issue of inventory compilation is the choice of suitable emission factors for specified operations over different parts of the world. Through careful review of published emission factors, we modified the traditional emission factor-based model by multiplying correction coefficient factors to reflect the relationship between emission factors, soil texture, and climate conditions. Then, the temporal (i.e., monthly) and spatial (i.e., 0.5º resolution) distribution of agricultural PM10 and PM2.5 emissions from each and all operations were estimated for each crop or forage. Finally, the emissions from individual crops were aggregated to assemble a global inventory from agricultural operations. The inventory was verified by comparing the new data with the existing agricultural fugitive dust inventory in North America and Europe, as well as satellite observations of anthropogenic agricultural dust emissions.

  18. Source contributions to PM2.5 and PM10 at an urban background and a street location

    NASA Astrophysics Data System (ADS)

    Keuken, M. P.; Moerman, M.; Voogt, M.; Blom, M.; Weijers, E. P.; Röckmann, T.; Dusek, U.

    2013-06-01

    The contribution of regional, urban and traffic sources to PM2.5 and PM10 in an urban area was investigated in this study. The chemical composition of PM2.5 and PM10 was measured over a year at a street location and up- and down-wind of the city of Rotterdam, the Netherlands. The 14C content in EC and OC concentrations was also determined, to distinguish the contribution from "modern" carbon (e.g., biogenic emissions, biomass burning and wildfires) and fossil fuel combustion. It was concluded that the urban background of PM2.5 and PM10 is dominated by the regional background, and that primary and secondary PM emission by urban sources contribute less than 15%. The 14C analysis revealed that 70% of OC originates from modern carbon and 30% from fossil fuel combustion. The corresponding percentages for EC are, respectively 17% and 83%. It is concluded that in particular the urban population living in street canyons with intense road traffic has potential health risks. This is due to exposure to elevated concentrations of a factor two for EC from exhaust emissions in PM2.5 and a factor 2-3 for heavy metals from brake and tyre wear, and re-suspended road dust in PM10. It follows that local air quality management may focus on local measures to street canyons with intense road traffic.

  19. Influence of tobacco smoke on carcinogenic PAH composition in indoor PM 10 and PM 2.5

    NASA Astrophysics Data System (ADS)

    Slezakova, K.; Castro, D.; Pereira, M. C.; Morais, S.; Delerue-Matos, C.; Alvim-Ferraz, M. C.

    2009-12-01

    Because of the mutagenic and/or carcinogenic properties, Polycyclic Aromatic Hydrocarbons (PAH), have a direct impact on human population. Consequently, there is a widespread interest in analysing and evaluating the exposure to PAH in different indoor environments, influenced by different emission sources. The information on indoor PAH is still limited, mainly in terms of PAH distribution in indoor particles of different sizes; thus, this study evaluated the influence of tobacco smoke on PM 10 and PM 2.5 characteristics, namely on their PAH compositions, with further aim to understand the negative impact of tobacco smoke on human health. Samples were collected at one site influenced by tobacco smoke and at one reference (non-smoking) site using low-volume samplers; the analyses of 17 PAH were performed by Microwave Assisted Extraction combined with Liquid Chromatography (MAE-LC). At the site influenced by tobacco smoke PM concentrations were higher 650% for PM 10, and 720% for PM 2.5. When influenced by smoking, 4 ring PAH (fluoranthene, pyrene, and chrysene) were the most abundant PAH, with concentrations 4600-21 000% and 5100-20 800% higher than at the reference site for PM 10 and PM 2.5, respectively, accounting for 49% of total PAH (Σ PAH). Higher molecular weight PAH (5-6 rings) reached concentrations 300-1300% and 140-1700% higher for PM 10 and PM 2.5, respectively, at the site influenced by tobacco smoke. Considering 9 carcinogenic PAH this increase was 780% and 760% in PM 10 and PM 2.5, respectively, indicating the strong potential risk for human health. As different composition profiles of PAH in indoor PM were obtained for reference and smoking sites, those 9 carcinogens represented at the reference site 84% and 86% of Σ PAH in PM 10 and PM 2.5, respectively, and at the smoking site 56% and 55% of Σ PAH in PM 10 and PM 2.5, respectively. All PAH (including the carcinogenic ones) were mainly present in fine particles, which corresponds to a strong risk

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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…

  8. 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.

  9. 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…

  10. 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.

  11. 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)

  12. 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…

  13. 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.

  14. 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…

  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. Laser machining of explosives

    DOEpatents

    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.

  17. Comprehensive assessment of PM2.5 physicochemical properties during the Southeast Asia dry season (southwest monsoon)

    NASA Astrophysics Data System (ADS)

    Khan, Md Firoz; Sulong, Nor Azura; Latif, Mohd Talib; Nadzir, Mohd Shahrul Mohd; Amil, Norhaniza; Hussain, Dini Fajrina Mohd; Lee, Vernon; Hosaini, Puteri Nurafidah; Shaharom, Suhana; Yusoff, Nur Amira Yasmin Mohd; Hoque, Hossain Mohammed Syedul; Chung, Jing Xiang; Sahani, Mazrura; Mohd Tahir, Norhayati; Juneng, Liew; Maulud, Khairul Nizam Abdul; Abdullah, Sharifah Mastura Syed; Fujii, Yusuke; Tohno, Susumu; Mizohata, Akira

    2016-12-01

    A comprehensive assessment of fine particulate matter (PM2.5) compositions during the Southeast Asia dry season is presented. Samples of PM2.5 were collected between 24 June and 14 September 2014 using a high-volume sampler. Water-soluble ions, trace species, rare earth elements, and a range of elemental carbon (EC) and organic carbon were analyzed. The characterization and source apportionment of PM2.5 were investigated. The results showed that the 24 h PM2.5 concentration ranged from 6.64 to 68.2 µg m-3. Meteorological driving factors strongly governed the diurnal concentration of aerosol, while the traffic in the morning and evening rush hours coincided with higher levels of CO and NO2. The correlation analysis for non sea-salt K+-EC showed that EC is potentially associated with biomass burning events, while the formation of secondary organic carbon had a moderate association with motor vehicle emissions. Positive matrix factorization (PMF) version 5.0 identified the sources of PM2.5: (i) biomass burning coupled with sea salt [I] (7%), (ii) aged sea salt and mixed industrial emissions (5%), (iii) road dust and fuel oil combustion (7%), (iv) coal-fired combustion (25%), (v) mineral dust (8%), (vi) secondary inorganic aerosol (SIA) coupled with F- (15%), and (vii) motor vehicle emissions coupled with sea salt [II] (24%). Motor vehicle emissions, SIA, and coal-fired power plant are the predominant sources contributing to PM2.5. The response of the potential source contribution function and Hybrid Single-Particle Lagrangian Integrated Trajectory backward trajectory model suggest that the outline of source regions were consistent to the sources by PMF 5.0.

  18. Hybrid fiber resonator employing LRSPP waveguide coupler for gyroscope.

    PubMed

    Qian, Guang; Fu, Xing-Chang; Zhang, Li-Jiang; Tang, Jie; Liu, Yi-Ran; Zhang, Xiao-Yang; Zhang, Tong

    2017-01-24

    Polarization error and temperature noise are two main limits to the performance of resonant fiber optic gyroscope (RFOG). To overcome these limits, we demonstrated a hybrid resonator consisting of a polymer-based long-range surface plasmon polariton (LRSPP) waveguide coupler and a silica fiber. Single-polarization property of LRSPP waveguide and the offsetting of the opposite thermo-optical characteristics between the polymer-based LRSPP waveguide and the silica fiber can effectively inhibit both the polarization error and the temperature noise of RFOG. The measured resonance spectrum of the hybrid resonator shows the absence of polarization noise. The temperature dependence of wavelength shift (TDWS) of resonator dropped to about 2 pm/°C, or even to 0 pm/°C with optimal structure, which dramatically improves the temperature stability of gyroscope system. In addition, the hybrid resonator also shows tremendous application potential in rate-grade and tactical-grade gyroscopes.

  19. Hybrid fiber resonator employing LRSPP waveguide coupler for gyroscope

    NASA Astrophysics Data System (ADS)

    Qian, Guang; Fu, Xing-Chang; Zhang, Li-Jiang; Tang, Jie; Liu, Yi-Ran; Zhang, Xiao-Yang; Zhang, Tong

    2017-01-01

    Polarization error and temperature noise are two main limits to the performance of resonant fiber optic gyroscope (RFOG). To overcome these limits, we demonstrated a hybrid resonator consisting of a polymer-based long-range surface plasmon polariton (LRSPP) waveguide coupler and a silica fiber. Single-polarization property of LRSPP waveguide and the offsetting of the opposite thermo-optical characteristics between the polymer-based LRSPP waveguide and the silica fiber can effectively inhibit both the polarization error and the temperature noise of RFOG. The measured resonance spectrum of the hybrid resonator shows the absence of polarization noise. The temperature dependence of wavelength shift (TDWS) of resonator dropped to about 2 pm/°C, or even to 0 pm/°C with optimal structure, which dramatically improves the temperature stability of gyroscope system. In addition, the hybrid resonator also shows tremendous application potential in rate-grade and tactical-grade gyroscopes.

  20. Hybrid fiber resonator employing LRSPP waveguide coupler for gyroscope

    PubMed Central

    Qian, Guang; Fu, Xing-Chang; Zhang, Li-Jiang; Tang, Jie; Liu, Yi-Ran; Zhang, Xiao-Yang; Zhang, Tong

    2017-01-01

    Polarization error and temperature noise are two main limits to the performance of resonant fiber optic gyroscope (RFOG). To overcome these limits, we demonstrated a hybrid resonator consisting of a polymer-based long-range surface plasmon polariton (LRSPP) waveguide coupler and a silica fiber. Single-polarization property of LRSPP waveguide and the offsetting of the opposite thermo-optical characteristics between the polymer-based LRSPP waveguide and the silica fiber can effectively inhibit both the polarization error and the temperature noise of RFOG. The measured resonance spectrum of the hybrid resonator shows the absence of polarization noise. The temperature dependence of wavelength shift (TDWS) of resonator dropped to about 2 pm/°C, or even to 0 pm/°C with optimal structure, which dramatically improves the temperature stability of gyroscope system. In addition, the hybrid resonator also shows tremendous application potential in rate-grade and tactical-grade gyroscopes. PMID:28117412

  1. 8. VIEW OF THE MACHINE SHOP. BY 1966, THE MACHINE ...

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

    8. VIEW OF THE MACHINE SHOP. BY 1966, THE MACHINE SHOP HANDLED PRIMARILY STAINLESS STEEL COMPONENTS, WHICH WERE SENT TO THE MACHINE SHOP TO BE FORMED INTO THEIR FINAL SHAPES. (7/24/70) - Rocky Flats Plant, General Manufacturing, Support, Records-Central Computing, Southern portion of Plant, Golden, Jefferson County, CO

  2. Saw + LMJ: a hybrid semiconductor dicing solution

    NASA Astrophysics Data System (ADS)

    Richerzhagen, Bernold; Plankensteiner, Martin; Kling, Notker U.; Stay, Keith; Brulé, Arnaud

    2008-02-01

    The concept of combining the Laser MicroJet (R) (LMJ) water jet-guided laser with a standard industrial diamond blade saw was first proposed early in 2006. The idea has now been taken a step forward with a joint project between Synova SA and Disco Hi-Tech Europe GmbH. The hybrid machine being developed integrates an LMJ module in place of the second blade saw on a Disco dual-spindle machine. The resulting machine will be fully capable of sequencing the different processes to carry out dicing of complex and layered semiconductors wafer, in any possible combination. It will be possible to program both processes to run independently in parallel or allow sequential operation during the same cutting pass. This extraordinary flexibility, combined with the speed advantages, quality of material cutting and simplification in processing in a fully automatic mode for up to 300 mm wafers, all now available in a single machine, will greatly benefit the manufacturing community. This paper will provide some insight into the design and operation of the hybrid machine and some examples of the improvements gained from its use.

  3. PM 2.5 and PM 10: The influence of sugarcane burning on potential cancer risk

    NASA Astrophysics Data System (ADS)

    Silva, Flavio S.; Cristale, Joyce; André, Paulo A.; Saldiva, Paulo H. N.; Marchi, Mary R. R.

    2010-12-01

    In Brazil, sugarcane fields are often burned to facilitate manual harvesting, and this burning causes environmental pollution from the large amounts of soot released into the atmosphere. This material contains numerous organic compounds such as PAHs. In this study, the concentrations of PAHs in two particulate-matter fractions (PM 2.5 and PM 10) in the city of Araraquara (SE Brazil, with around 200,000 inhabitants and surrounded by sugarcane plantations) were determined during the sugarcane harvest (HV) and non-harvest (NHV) seasons in 2008 and 2009. The sampling strategy included four campaigns, with 60 samples in the NHV season and 220 samples in the HV season. The PM 2.5 and PM 10 fractions were collected using a dichotomous sampler (10 L min -1, 24 h) with Teflon™ filters. The filter sets were extracted (ultrasonic bath with hexane/acetone (1:1 v/v)) and analyzed by HPLC/Fluorescence. The median concentration for total PAHs (PM 2.5 in 2009) was 0.99 ng m -3 (NHV) and 3.3 ng m -3 (HV). In the HV season, the total concentration of carcinogenic PAHs (benz(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, and benzo(a)pyrene) was 5 times higher than in the NHV season. B(a)P median concentrations were 0.017 ng m -3 and 0.12 ng m -3 for the NHV and HV seasons, respectively. The potential cancer risk associated with exposure through inhalation of these compounds was estimated based on the benzo[a]pyrene toxic equivalence (BaP eq), where the overall toxicity of a PAH mixture is defined by the concentration of each compound multiplied by its relative toxic equivalence factor (TEF). BaP eq median (2008 and 2009 years) ranged between 0.65 and 1.0 ng m -3 and 1.2-1.4 ng m -3 for the NHV and HV seasons, respectively. Considering that the maximum permissible BaP eq in ambient air is 1 ng m -3, related to the increased carcinogenic risk, our data suggest that the level of human exposure to PAHs in cities surrounded by sugarcane crops where the burning process is used

  4. A POPULATION EXPOSURE MODEL FOR PARTICULATE MATTER: SHEDS-PM

    EPA Science Inventory

    The US EPA National Exposure Research Laboratory (NERL) has developed a population exposure and dose model for particulate matter (PM) that will be publicly available in Fall 2002. The Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model uses a probabilistic approach ...

  5. PM2.5 stack sampler performance-laboratory evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In 2006, EPA implemented a more stringent standard for PM2.5, particulate matter whose effective diameter is less than 2.5 microns. PM2.5 is listed as a criteria pollutant in the National Ambient Air Quality Standards (NAAQS). Agricultural operations across the United States are encountering difficu...

  6. NARSTO EPA SS PITTSBURGH GAS PM PROPERTY DATA

    Atmospheric Science Data Center

    2014-04-25

    NARSTO EPA SS PITTSBURGH GAS PM PROPERTY DATA Project Title:  NARSTO Discipline:  Tropospheric Chemistry Field Campaigns Aerosols Level:  L2 ... Data Guide Documents:  Pittsburgh Gas PM Property Guide Pittsburgh Project Plan  (PDF) ...

  7. Low-lying levels in /sup 148/Pm

    SciTech Connect

    Norman, E.B.; Lesko, K.T.; Champagne, A.E.

    1988-02-01

    The /sup 149/Sm(d,/sup 3/He) reaction has been used to populate levels in /sup 148/Pm. Nineteen new excited states have been observed below 1 MeV excitation energy in /sup 148/Pm. The possible astrophysical implications of these results are discussed.

  8. 75 FR 45571 - Determination of Attainment for PM10

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-03

    ... AGENCY 40 CFR Part 81 Determination of Attainment for PM 10 for the Las Vegas Valley Nonattainment Area... determine that the Las Vegas Valley nonattainment area in Nevada attained the National Ambient Air Quality... micrometers (PM 10 ) by the applicable attainment date (December 31, 2006), and that the Las Vegas...

  9. OVERVIEW AND STATUS OF THE PM SUPERSITES PROGRAM

    EPA Science Inventory

    The PM Supersites program was first conceived as a set of special studies extending beyond the national regulatory networks for particulate matter (PM) to elucidate source-receptor relationships and atmospheric processes in support of State implementation plans (SIP's). The pr...

  10. PARTICULATE MATTER (PM) INHIBITS NEUROTROPHIN RELEASE FROM A549 CELLS

    EPA Science Inventory

    Several investigations have linked PM exposure to the exacerbation of allergic lung diseases. Many PM effects are mediated by cells within the lung including the airway epithelium, eosinophils, and lymphocytes. These cells also produce neurotophins such as NGF and/or express neur...

  11. CARDIOVASCULAR TOXICITY OF PM: SOLUBLE COMPONENTS OR SOLID PARTICLES?

    EPA Science Inventory

    Since strong suggestion of cardiac-related deaths has arisen from epidemiological studies of ambient PM, a major effort is required to identify PM components and mechanisms responsible for observed cardiac impairments. Unfortunately, it has been difficult to elucidate causality w...

  12. Characterization and Cytotoxicity of PM<0.2, PM0.2–2.5 and PM2.5–10 around MSWI in Shanghai, China

    PubMed Central

    Cao, Lingling; Zeng, Jianrong; Liu, Ke; Bao, Liangman; Li, Yan

    2015-01-01

    Background: The potential impact of municipal solid waste incineration (MSWI), which is an anthropogenic source of aerosol emissions, is of great public health concern. This study investigated the characterization and cytotoxic effects of ambient ultrafine particles (PM<0.2), fine particles (PM0.2–2.5) and coarse particles (PM2.5–10) collected around a municipal solid waste incineration (MSWI) plant in the Pudong district of Shanghai. Methods: Mass concentrations of trace elements in particulate matter (PM) samples were determined using ICP-MS (Inductively Coupled Plasma Mass Spectrometry). The cytotoxicity of sampled atmospheric PM was evaluated by cell viability and reactive oxygen species (ROS) levels in A549 cells. Result: The mass percentage of PM0.2–2.5 accounted for 72.91% of the total mass of PM. Crustal metals (Mg, Al, and Ti) were abundant in the coarse particles, while the anthropogenic elements (V, Ni, Cu, Zn, Cd, and Pb) were dominant in the fine particles. The enrichment factors of Zn, Cd and Pb in the fine and ultrafine particles were extremely high (>100). The cytotoxicity of the size-resolved particles was in the order of coarse particles < fine particles < ultrafine particles. Conclusions: Fine particles dominated the MSWI ambient particles. Emissions from the MSWI could bring contamination of anthropogenic elements (Zn, Cd and Pb) into ambient environment. The PM around the MSWI plant displayed an additive toxic effect, and the ultrafine and fine particles possessed higher biological toxicity than the coarse particles. PMID:25985309

  13. 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, 2012 CFR

    2012-07-01

    ...% 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 ±0.12...

  14. Hinged Shields for Machine Tools

    NASA Technical Reports Server (NTRS)

    Lallande, J. B.; Poland, W. W.; Tull, S.

    1985-01-01

    Flaps guard against flying chips, but fold away for tool setup. Clear plastic shield in position to intercept flying chips from machine tool and retracted to give operator access to workpiece. Machine shops readily make such shields for own use.

  15. Variability of levels and composition of PM10 and PM2.5 in the Barcelona metro system

    NASA Astrophysics Data System (ADS)

    Querol, X.; Moreno, T.; Karanasiou, A.; Reche, C.; Alastuey, A.; Viana, M.; Font, O.; Gil, J.; de Miguel, E.; Capdevila, M.

    2012-03-01

    From an environmental perspective, the underground metro system is one of the cleanest forms of public transportation in urban agglomerations. Current studies report contradicting results regarding air quality in the metro systems: whereas some reveal poor air quality, others report PM levels which are lower or of the same order of magnitude than those measured in traffic sites above ground level. The present work assesses summer indoor air quality and passenger exposure in the Barcelona metro, focusing on PM levels and their metal contents. In addition, the impact on indoor air quality of platform screen door systems (automated systems consisting of closed rail track and platforms) is evaluated, to determine whether these systems reduce passenger exposure to PM when compared with conventional systems (open tracks and platforms). In the Barcelona metro, PM levels inside the trains in summer are amongst the lowest reported for worldwide metro systems (11-32 μPM2.5 m-3). This is most probably due to the air conditioning system working in all carriages of the Barcelona metro during the whole year. On the platforms, levels were considerably higher, reaching mean levels of 59 and 88 μgPM2.5 m-3 in the new (L9) and old (L3) lines, respectively. PM10 data are also reported in the present study, but comparison with other metro systems is more difficult due to the scarcity of data compared with PM2.5. Results showed clear PM daily cycles, with a drastic increase from 06:00 to 07:00 a.m., a diurnal maximum from 07:00 a.m. to 10:00 p.m., and marked decreases between 10:00 p.m. and 05:00 a.m. The elements with the highest enrichment are those associated with wheel or brake abrasion products (Ba, Fe, Cu, Mn, Cr, Sb, As, Mo, Co, Sr, among others). Laminar hematite (Fe2O3) was the dominant particle type, being mainly originated by mechanical abrasion of the rail track and wheels. Regarding passenger exposure to PM inside the metro system, the contribution of commuting by metro

  16. Understanding intra-neighborhood patterns in PM2.5 and PM10 using mobile monitoring in Braddock, PA

    PubMed Central

    2012-01-01

    Background Braddock, Pennsylvania is home to the Edgar Thomson Steel Works (ETSW), one of the few remaining active steel mills in the Pittsburgh region. An economically distressed area, Braddock exceeds average annual (>15 μg/m3) and daily (>35 μg/m3) National Ambient Air Quality Standards (NAAQS) for particulate matter (PM2.5). Methods A mobile air monitoring study was designed and implemented in morning and afternoon hours in the summer and winter (2010–2011) to explore the within-neighborhood spatial and temporal (within-day and between-day) variability in PM2.5 and PM10. Results Both pollutants displayed spatial variation between stops, and substantial temporal variation within and across study days. For summer morning sampling runs, site-specific mean PM2.5 ranged from 30.0 (SD = 3.3) to 55.1 (SD = 13.0) μg/m3. Mean PM10 ranged from 30.4 (SD = 2.5) to 69.7 (SD = 51.2) μg/m3, respectively. During summer months, afternoon concentrations were significantly lower than morning for both PM2.5 and PM10, potentially owing to morning subsidence inversions. Winter concentrations were lower than summer, on average, and showed lesser diurnal variation. Temperature, wind speed, and wind direction predicted significant variability in PM2.5 and PM10 in multiple linear regression models. Conclusions Data reveals significant morning versus afternoon variability and spatial variability in both PM2.5 and PM10 concentrations within Braddock. Information obtained on peak concentration periods, and the combined effects of industry, traffic, and elevation in this region informed the design of a larger stationary monitoring network. PMID:23051204

  17. Control system for a hybrid powertrain system

    SciTech Connect

    Naqvi, Ali K.; Demirovic, Besim; Gupta, Pinaki; Kaminsky, Lawrence A.

    2014-09-09

    A vehicle includes a powertrain with an engine, first and second torque machines, and a hybrid transmission. A method for operating the vehicle includes operating the engine in an unfueled state, releasing an off-going clutch which when engaged effects operation of the hybrid transmission in a first continuously variable mode, and applying a friction braking torque to a wheel of the vehicle to compensate for an increase in an output torque of the hybrid transmission resulting from releasing the off-going clutch. Subsequent to releasing the off-going clutch, an oncoming clutch which when engaged effects operation of the hybrid transmission in a second continuously variable mode is synchronized. Subsequent to synchronization of the oncoming clutch, the oncoming clutch is engaged.

  18. Hardware Photos: Image Showing JWST Engineering Demonstration Mirror, Mounted Ready for Machining at AXYS and Image Showing HIP Can Containing Light Mirrors 1 and 2 Ready for Mirror Fabrication

    NASA Technical Reports Server (NTRS)

    OKeefe, Sean

    2004-01-01

    The images in this viewgraph presentation have the following captions: 1) EDU mirror after being sawed in half; 2) EDU Delivered to Axsys; 3) Be EDU Blank Received and Machining Started; 4) Loaded HIP can for flight PM segments 1 and 2; 5) Flight Blanks 1 and 2 Loaded into HIP Can at Brush-Wellman; 6) EDU in Machining at Axsys.

  19. GIS Assessment of the PM10, PM2.5 and PM1.0 Concentrations in Urban Area of Tehran in Warm and Cold Seasons

    NASA Astrophysics Data System (ADS)

    Halek, F.; Kavousi-rahim, A.

    2014-10-01

    In recent years, atmospheric models, such as GIS, are used for environmental analysis and the related management for supporting the environmental decision makers in different countries. In this study, concentrations of PM10, PM2.5 and PM1.0 are found in urban areas of Tehran in warm and cold seasons and the data applied in the related modelling, using Arc-GIS. For this purpose, samples were collected from 42 sites in an 18 km2 region located in the west and central parts of Tehran. The mean concentrations of PM1.0, PM2.5 and PM10 are found to be 13.14 μg/m3, 22.67 μg/m3 and 95.72 μg/m3 in the warm season; and 50.12 μg/m3, 70.72 μg/m3 and 193.86 μg/m3 in the cold season respectively. In this paper, with the aid of GIS, concentrations of the suspended particles were measured in 22 major hospitals, the patients in which are in contact with these pollutants. It was found the concentrations of the suspended particles were much higher in the cold season.

  20. Main components and human health risks assessment of PM10, PM2.5, and PM1 in two areas influenced by cement plants

    NASA Astrophysics Data System (ADS)

    Sánchez-Soberón, Francisco; Rovira, Joaquim; Mari, Montse; Sierra, Jordi; Nadal, Martí; Domingo, José L.; Schuhmacher, Marta

    2015-11-01

    Particulate matter (PM) is widely recorded as a source of diseases, being more harmful those particles with smaller size. PM is released to the environment as a consequence of different activities, being one of them cement production. The objective of this pilot study was to characterize PM of different sizes around cement facilities to have a preliminary approach of their origin, and evaluate their potential health risks. For that purpose, three fractions of PM (10, 2.5, and 1) were collected in the nearby area of two cement plants with different backgrounds (urban and rural) in different seasons. Subsequently, main components, outdoor and indoor concentrations, exposure, and human health risks were assessed. Greatest levels of PM1, organic matter, and metals were found in urban location, especially in winter. Consequently, environmental exposure and human health risks registered their highest values in the urban plant during wintertime. Exposure was higher for indoor activities, expressing some metals their peak values in the PM1 fraction. Non-carcinogenic risks were below the safety threshold (HQ < 1). Carcinogenic risks for most of the metals were below the limit of 10-5, except for Cr (VI), which exceeded it in both locations, but being in the range considered as assumable (10-6-10-4).

  1. Bacteriorhodopsin protein hybrids for chemical and biological sensing

    NASA Astrophysics Data System (ADS)

    Winder, Eric Michael

    Bacteriorhodopsin (bR), an optoelectric protein found in Halobacterium salinarum, has the potential for use in protein hybrid sensing systems. Bacteriorhodopsin has no intrinsic sensing properties, however molecular and chemical tools permit production of bR protein hybrids with transducing and sensing properties. As a proof of concept, a maltose binding protein-bacteriorhodopsin ([MBP]-bR) hybrid was developed. It was proposed that the energy associated with target molecule binding, maltose, to the hybrid sensor protein would provide a means to directly modulate the electrical output from the MBP-bR bio-nanosensor platform. The bR protein hybrid is produced by linkage between bR (principal component of purified purple membrane [PM]) and MBP, which was produced by use of a plasmid expression vector system in Escherichia coli and purified utilizing an amylose affinity column. These proteins were chemically linked using 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS), which facilitates formation of an amide bond between a primary carboxylic acid and a primary amine. The presence of novel protein hybrids after chemical linkage was analyzed by SDS-PAGE. Soluble proteins (MBP-only derivatives and unlinked MBP) were separated from insoluble proteins (PM derivatives and unlinked PM) using size exclusion chromatography. The putatively identified MBP-bR protein hybrid, in addition to unlinked bR, was collected. This sample was normalized for bR concentration to native PM and both were deposited onto indium tin oxide (ITO) coated glass slides by electrophoretic sedimentation. The photoresponse of both samples, activated using 100 Watt tungsten lamp at 10 cm distance, were equal at 175 mV. Testing of deposited PM with 1 mM sucrose or 1 mM maltose showed no change in the photoresponse of the material, however addition of 1 mM maltose to the deposited MBP-bR linked hybrid material elicited a 57% decrease in photoresponse

  2. Automatically-Programed Machine Tools

    NASA Technical Reports Server (NTRS)

    Purves, L.; Clerman, N.

    1985-01-01

    Software produces cutter location files for numerically-controlled machine tools. APT, acronym for Automatically Programed Tools, is among most widely used software systems for computerized machine tools. APT developed for explicit purpose of providing effective software system for programing NC machine tools. APT system includes specification of APT programing language and language processor, which executes APT statements and generates NC machine-tool motions specified by APT statements.

  3. Isomap based supporting vector machine

    NASA Astrophysics Data System (ADS)

    Liang, W. N.

    2015-12-01

    This research presents a new isomap based supporting vector machine method. Isomap is a dimension reduction method which is able to analyze nonlinear relationship of data on manifolds. Accordingly, support vector machine is established on the isomap manifold to classify given and predict unknown data. A case study of the isomap based supporting vector machine for environmental planning problems is conducted.

  4. Interferometer systems in machine industry

    NASA Astrophysics Data System (ADS)

    Rzepka, Janusz; Pienkowski, Janusz; Sambor, Slawomir; Budzyn, Grzegorz

    2003-10-01

    In the report the arrangements of laser interferometers for machine history are presented; the laser interferometer LSP30 for investigation of geometry of machine tools, the setup for inspection of ball screw and laser liner for CNC machine. Outstanding feature of the interferometers is the stabilization system of laser frequency using surface stabilized ferroelectric liquid cells (SSFLC).

  5. Machine Shop Fundamentals: Part I.

    ERIC Educational Resources Information Center

    Kelly, Michael G.; And Others

    These instructional materials were developed and designed for secondary and adult limited English proficient students enrolled in machine tool technology courses. Part 1 includes 24 lessons covering introduction, safety and shop rules, basic machine tools, basic machine operations, measurement, basic blueprint reading, layout, and bench tools.…

  6. CHANGES IN OPERATING PROCEDURES FOR AEROSOL CONCENTRATION UNIFORMITY FOR PM2.5 AND PM10 SAMPLER TESTING

    EPA Science Inventory

    This technical note documents changes in the standard operating procedures used at the Environmental Protection Agency's (U.S. EPA) aerosol testing wind tunnel facility for testing of particulate matter monitoring methods of PM2.5 and PM10. These changes are relative to the op...

  7. LINKAGES ACROSS PM POLICY AND RESEARCH: EXAMINING THE POLICY RELEVANT FINDINGS FROM THE PM2.5 SUPERSITES PROGRAM

    EPA Science Inventory

    The PM2.5 Supersites program was designed to complement routinely operating PM2.5 networks by providing enhanced temporal and chemical/physical composition data in addressing three overarching objectives: supporting health effects and exposure research, advanced monitoring meth...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 concentr...

  9. Water-soluble organic compounds (WSOCs) in PM2.5 and PM10 at a subtropical site of India

    NASA Astrophysics Data System (ADS)

    Khare, Puja; Baruah, B. P.; Rao, P. G.

    2011-11-01

    PM2.5 and PM10 samples collected at a suburban site of northeastern part of India have been analysed for particle mass, total carbon (TC), water-soluble total carbon (WSTC), water-soluble organic carbon (WSOC), water-soluble inorganic carbon (WSIC), organic acids (formic, acetic, proponoic and oxalic acids) along with inorganic ions (NO3-, SO42- and NH4-). Most of the PM10 consists of PM2.5 in the present site (ratio 54-74%). WSTC content in PM2.5 and PM10 corresponds to 21% and 16%, respectively, of their total particle masses. Thermo gravimetric analysis showed the presence of humic-like substances (16-22%) in particulate samples. Domestic heating and stagnant atmospheric conditions enhanced the levels of these carbonaceous compounds in PM2.5 and PM10 in winter. Qualitative estimation of various functional groups by Fourier transform infrared (FTIR) analysis indicates the presence of carboxylic, hydroxyl, aliphatic and aromatic hydrocarbons, amines and sulphurous compounds in these aerosols. Absolute principal component analysis applied on the aerosol data resolves four factors. These factors are associated with carbonaceous aerosols released from combustion of coal and wood, secondary inorganic and organic aerosols and water-soluble inorganic fraction.

  10. Variability of levels and composition of PM10 and PM2.5 in the Barcelona metro system

    NASA Astrophysics Data System (ADS)

    Querol, X.; Moreno, T.; Karanasiou, A.; Reche, C.; Alastuey, A.; Viana, M.; Font, O.; Gil, J.; de Miguel, E.; Capdevila, M.

    2012-06-01

    From an environmental perspective, the underground metro system is one of the cleanest forms of public transportation in urban agglomerations. Current studies report contradicting results regarding air quality in the metro systems: whereas some reveal poor air quality, others report PM levels which are lower or of the same order of magnitude than those measured in traffic sites above ground level. The present work assesses summer and winter indoor air quality and passenger exposure in the Barcelona metro, focusing on PM levels and their metal contents. In addition, the impact on indoor air quality of platform screen door systems (automated systems consisting of closed rail track and platforms) is evaluated, to determine whether these systems reduce passenger exposure to PM when compared with conventional systems (open tracks and platforms). In the Barcelona metro PM levels inside the trains in summer are amongst the lowest reported for worldwide metro systems (11-32 μg m-3 PM2.5). This is most likely due to the air conditioning system working in all carriages of the Barcelona metro during the whole year. Levels were considerably higher on the platforms, reaching mean levels of 46 and 125 μg m3 in the new (L9) and old (L3) lines, respectively. PM10 data are also reported in the present study, but comparison with other metro systems is difficult due to the scarcity of data compared with PM2.5. Results showed distinct PM daily cycles, with a drastic increase from 06:00 to 07:00 a.m., a diurnal maximum from 07:00 to 10:00 p.m., and marked decrease between 10:00 p.m. and 05:00 a.m. The elements with the highest enrichment were those associated with wheel or brake abrasion products (Ba, Fe, Cu, Mn, Cr, Sb, As, Mo, Co, Sr, among others). Laminar hematite (Fe2O3) was the dominant particle type, being mainly originated by mechanical abrasion of the rail track and wheels. Regarding passenger exposure to PM, the contribution of commuting by metro was estimated to account

  11. A Boltzmann machine for the organization of intelligent machines

    NASA Technical Reports Server (NTRS)

    Moed, Michael C.; Saridis, George N.

    1989-01-01

    In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved

  12. Weather forecasting based on hybrid neural model

    NASA Astrophysics Data System (ADS)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-02-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  13. Engineering molecular machines

    NASA Astrophysics Data System (ADS)

    Erman, Burak

    2016-04-01

    Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.

  14. Trends in arsenic levels in PM10 and PM 2.5 aerosol fractions in an industrialized area.

    PubMed

    García-Aleix, J R; Delgado-Saborit, J M; Verdú-Martín, G; Amigó-Descarrega, J M; Esteve-Cano, V

    2014-01-01

    Arsenic is a toxic element that affects human health and is widely distributed in the environment. In the area of study, the main Spanish and second largest European industrial ceramic cluster, the main source of arsenic aerosol is related to the impurities in some boracic minerals used in the ceramic process. Epidemiological studies on cancer occurrence in Spain points out the study region as one with the greater risk of cancer. Concentrations of particulate matter and arsenic content in PM10 and PM2.5 were measured and characterized by ICP-MS in the area of study during the years 2005-2010. Concentrations of PM10 and its arsenic content range from 27 to 46 μg/m(3) and from 0.7 to 6 ng/m(3) in the industrial area, respectively, and from 25 to 40 μg/m(3) and from 0.7 to 2.8 ng/m(3) in the urban area, respectively. Concentrations of PM2.5 and its arsenic content range from 12 to 14 μg/m(3) and from 0.5 to 1.4 ng/m(3) in the urban background area, respectively. Most of the arsenic content is present in the fine fraction, with ratios of PM2.5/PM10 in the range of 0.65-0.87. PM10, PM2.5, and its arsenic content show a sharp decrease in recent years associated with the economic downturn, which severely hit the production of ceramic materials in the area under study. The sharp production decrease due to the economic crisis combined with several technological improvements in recent years such as substitution of boron, which contains As impurities as raw material, have reduced the concentrations of PM10, PM2.5, and As in air to an extent that currently meets the existing European regulations.

  15. Machining fiber-reinforced composites

    NASA Astrophysics Data System (ADS)

    Komanduri, Ranga

    1993-04-01

    Compared to high tool wear and high costs of tooling of fiber-reinforced composites (FRCs), noncontact material-removal processes offer attractive alternative. Noncontact machining methods can also minimize dust, noise, and extensive plastic deformation and consequent heat generation associated with conventional machining of FRCs, espacially those with an epoxy matrix. The paper describes the principles involved in and the details of machining of FRCs by laser machining, water jet-cutting and abrasive water jet-cutting, and electrical discharge machining of composites, as well as the limitations of each method.

  16. Safety features in anaesthesia machine.

    PubMed

    Subrahmanyam, M; Mohan, S

    2013-09-01

    Anaesthesia is one of the few sub-specialties of medicine, which has quickly adapted technology to improve patient safety. This application of technology can be seen in patient monitoring, advances in anaesthesia machines, intubating devices, ultrasound for visualisation of nerves and vessels, etc., Anaesthesia machines have come a long way in the last 100 years, the improvements being driven both by patient safety as well as functionality and economy of use. Incorporation of safety features in anaesthesia machines and ensuring that a proper check of the machine is done before use on a patient ensures patient safety. This review will trace all the present safety features in the machine and their evolution.

  17. Hybrid MPI+OpenMP Programming of an Overset CFD Solver and Performance Investigations

    NASA Technical Reports Server (NTRS)

    Djomehri, M. Jahed; Jin, Haoqiang H.; Biegel, Bryan (Technical Monitor)

    2002-01-01

    This report describes a two level parallelization of a Computational Fluid Dynamic (CFD) solver with multi-zone overset structured grids. The approach is based on a hybrid MPI+OpenMP programming model suitable for shared memory and clusters of shared memory machines. The performance investigations of the hybrid application on an SGI Origin2000 (O2K) machine is reported using medium and large scale test problems.

  18. Urban aerosol in Oporto, Portugal: Chemical characterization of PM10 and PM2.5

    NASA Astrophysics Data System (ADS)

    Custódio, Danilo; Ferreira, Catarina; Alves, Célia; Duarte, Mácio; Nunes, Teresa; Cerqueira, Mário; Pio, Casimiro; Frosini, Daniele; Colombi, Cristina; Gianelle, Vorne; Karanasiou, Angeliki; Querol, Xavier

    2014-05-01

    Several urban and industrial areas in Southern Europe are not capable of meeting the implemented EU standards for particulate matter. Efficient air quality management is required in order to ensure that the legal limits are not exceeded and that the consequences of poor air quality are controlled and minimized. Many aspects of the direct and indirect effects of suspended particulate matter on climate and public health are not well understood. The temporal variation of the chemical composition is still demanded, since it enables to adopt off-set strategies and to better estimate the magnitude of anthropogenic forcing on climate. This study aims to provide detailed information on concentrations and chemical composition of aerosol from Oporto city, an urban center in Southern Europe. This city is located near the coast line in the North of Portugal, being the country's second largest urban area. Moreover, Oporto city economic prospects depend heavily on a diversified industrial park, which contribute to air quality degradation. Another strong source of air pollution is traffic. The main objectives of this study are: 1) to characterize the chemical composition of PM10 and PM2.5 by setting up an orchestra of aerosol sampling devices in a strategic place in Oporto; 2) to identify the sources of particles exploring parameters such as organic and inorganic markers (e.g. sugars as tracers for biomass burning; metals and elemental carbon for industrial and vehicular emissions); 3) to evaluate long range transport of pollutants using back trajectory analysis. Here we present data obtained between January 2013 and January 2014 in a heavy traffic roadside sampling site located in the city center. Different PM10 and PM2.5 samplers were operated simultaneously in order to collect enough mass on different filter matrixes and to fulfill the requirements of analytical methodologies. More than 100 aerosol samples were collected and then analysed for their mass concentration and

  19. Quantum Virtual Machine (QVM)

    SciTech Connect

    McCaskey, Alexander J.

    2016-11-18

    There is a lack of state-of-the-art HPC simulation tools for simulating general quantum computing. Furthermore, there are no real software tools that integrate current quantum computers into existing classical HPC workflows. This product, the Quantum Virtual Machine (QVM), solves this problem by providing an extensible framework for pluggable virtual, or physical, quantum processing units (QPUs). It enables the execution of low level quantum assembly codes and returns the results of such executions.

  20. Swinging Atwood's Machine

    NASA Astrophysics Data System (ADS)

    Tufillaro, Nicholas B.; Abbott, Tyler A.; Griffiths, David J.

    1984-10-01

    We examine the motion of an Atwood's Machine in which one of the masses is allowed to swing in a plane. Computer studies reveal a rich variety of trajectories. The orbits are classified (bounded, periodic, singular, and terminating), and formulas for the critical mass ratios are developed. Perturbative techniques yield good approximations to the computer-generated trajectories. The model constitutes a simple example of a nonlinear dynamical system with two degrees of freedom.

  1. Making Atwood's machine ``work''

    NASA Astrophysics Data System (ADS)

    Johnson, Gordon O.

    2001-03-01

    PASCO scientific's Smart Pulley™, a lightweight, low-friction pulley and a photogate, begs to be used as an Atwood's machine to determine the acceleration of gravity, g. Unfortunately ignoring the mass and friction of the pulley results in poor values of g. In this paper a procedure is outlined that includes the effects of the pulley's inertia and friction. As a result, the value of g may be determined to an accuracy of 0.1%.

  2. Risk assessment of heavy metals in road and soil dusts within PM2.5, PM10 and PM100 fractions in Dongying city, Shandong Province, China.

    PubMed

    Kong, Shaofei; Lu, Bing; Ji, Yaqin; Zhao, Xueyan; Bai, Zhipeng; Xu, Yonghai; Liu, Yong; Jiang, Hua

    2012-03-01

    15 road and 14 soil dust samples were collected from an oilfield city, Dongying, from 11/2009-4/2010 and analyzed by inductively coupled plasma-mass spectroscopy (ICP-MS) for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb within PM(2.5), PM(10) and PM(100) fractions synchronously. Metal concentrations, sources and human health risk were studied. Results showed that both soil and road dust exhibited higher values for Mn and Zn and lower values for Co and Cd for the three fractions. Mass concentration ratios of PM(2.5)/PM(10) and PM(10)/PM(100) for metals in road and soil dust indicate that most of the heavy metals tend to concentrate in fine particles. Geoaccumulation index and enrichment factors analysis showed that Cu, Zn and Cd exhibited moderate or heavy contamination and significant enrichment, indicating the influence of anthropogenic sources. Vanadium, Cr, Mn and Co were mostly not enriched and were mainly influenced by crustal sources. For Ni, As and Pb, they ranged from not enriched to moderately enriched and were influenced by both crustal materials and anthropogenic sources. The conclusions were confirmed by multivariate analysis methods. Principle component analysis revealed that the major sources were vehicle emission, industrial activities, coal combustion, agricultural activities and crustal materials. The risk assessment results indicated that metal ingestion appeared to be the main exposure route followed by dermal contact. The most likely cause for cancer and other health risks are both the fine particles of soil and road dusts.

  3. 40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... CO, PM10, and PM2.5 concentrations (hot-spot analysis). 93.123 Section 93.123 Protection of.... or the Federal Transit Laws § 93.123 Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis). (a) CO hot-spot analysis. (1) The demonstrations required by §...

  4. 40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... CO, PM10, and PM2.5 concentrations (hot-spot analysis). 93.123 Section 93.123 Protection of.... or the Federal Transit Laws § 93.123 Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis). (a) CO hot-spot analysis. (1) The demonstrations required by §...

  5. 40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... CO, PM10, and PM2.5 concentrations (hot-spot analysis). 93.123 Section 93.123 Protection of.... or the Federal Transit Laws § 93.123 Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis). (a) CO hot-spot analysis. (1) The demonstrations required by §...

  6. 40 CFR 93.123 - Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis).

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... CO, PM10, and PM2.5 concentrations (hot-spot analysis). 93.123 Section 93.123 Protection of.... or the Federal Transit Laws § 93.123 Procedures for determining localized CO, PM10, and PM2.5 concentrations (hot-spot analysis). (a) CO hot-spot analysis. (1) The demonstrations required by §...

  7. Machine Learning in Medicine.

    PubMed

    Deo, Rahul C

    2015-11-17

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

  8. Universal Memcomputing Machines.

    PubMed

    Traversa, Fabio Lorenzo; Di Ventra, Massimiliano

    2015-11-01

    We introduce the notion of universal memcomputing machines (UMMs): a class of brain-inspired general-purpose computing machines based on systems with memory, whereby processing and storing of information occur on the same physical location. We analytically prove that the memory properties of UMMs endow them with universal computing power (they are Turing-complete), intrinsic parallelism, functional polymorphism, and information overhead, namely, their collective states can support exponential data compression directly in memory. We also demonstrate that a UMM has the same computational power as a nondeterministic Turing machine, namely, it can solve nondeterministic polynomial (NP)-complete problems in polynomial time. However, by virtue of its information overhead, a UMM needs only an amount of memory cells (memprocessors) that grows polynomially with the problem size. As an example, we provide the polynomial-time solution of the subset-sum problem and a simple hardware implementation of the same. Even though these results do not prove the statement NP = P within the Turing paradigm, the practical realization of these UMMs would represent a paradigm shift from the present von Neumann architectures, bringing us closer to brain-like neural computation.

  9. Architectures for intelligent machines

    NASA Technical Reports Server (NTRS)

    Saridis, George N.

    1991-01-01

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

  10. Architecture of the Vibrio cholerae toxin-coregulated pilus machine revealed by electron cryotomography.

    PubMed

    Chang, Yi-Wei; Kjær, Andreas; Ortega, Davi R; Kovacikova, Gabriela; Sutherland, John A; Rettberg, Lee A; Taylor, Ronald K; Jensen, Grant J

    2017-02-06

    Type IV pili (T4P) are filamentous appendages found on many Bacteria and Archaea. They are helical fibres of pilin proteins assembled by a multi-component macromolecular machine we call the basal body. Based on pilin features, T4P are classified into type IVa pili (T4aP) and type IVb pili (T4bP)(1,2). T4aP are more widespread and are involved in cell motility(3), DNA transfer(4), host predation(5) and electron transfer(6). T4bP are less prevalent and are mainly found in enteropathogenic bacteria, where they play key roles in host colonization(7). Following similar work on T4aP machines(8,9), here we use electron cryotomography(10) to reveal the three-dimensional in situ structure of a T4bP machine in its piliated and non-piliated states. The specific machine we analyse is the Vibrio cholerae toxin-coregulated pilus machine (TCPM). Although only about half of the components of the TCPM show sequence homology to components of the previously analysed Myxococcus xanthus T4aP machine (T4aPM), we find that their structures are nevertheless remarkably similar. Based on homologies with components of the M. xanthus T4aPM and additional reconstructions of TCPM mutants in which the non-homologous proteins are individually deleted, we propose locations for all eight TCPM components within the complex. Non-homologous proteins in the T4aPM and TCPM are found to form similar structures, suggesting new hypotheses for their functions and evolutionary histories.

  11. CNC electrical discharge machining centers

    SciTech Connect

    Jaggars, S.R.

    1991-10-01

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

  12. Ambient endotoxin concentrations in PM10 from Southern California.

    PubMed Central

    Mueller-Anneling, Linda; Avol, Ed; Peters, John M; Thorne, Peter S

    2004-01-01

    Concentrations of endotoxin in urban air pollution have not previously been extensively characterized. We measured 24-hr levels of PM10 (particulate matter < 10 microm in aerodynamic diameter) and the associated endotoxin component once every 6 weeks for 1 year in 13 communities in Southern California. All the samples collected had detectable PM10 and endotoxin levels. The geometric mean PM10 was 34.6 microg/m3 [geometric SD (GSD), 2.1; range, 3.0-135]. By volume, the endotoxin geometric mean was 0.44 endotoxin units (EU)/m3 (GSD, 3.1; range, 0.03-5.44). Per unit material collected, the geometric mean of endotoxin collected was 13.6 EU/mg (GSD, 3.2; range, 0.7-96.8). No correlation was found between endotoxin concentrations and other ambient pollutants concurrently measured [ozone, nitrogen dioxide, total acids, or PM2.5 (particulate matter < 2.5 micro m in aerodynamic diameter]. PM10 and endotoxin concentrations were significantly correlated, most strongly in summer. Samples collected in more rural and agricultural areas had lower PM10 and mid-range endotoxin levels. The high desert and mountain communities had lower PM10 levels but endotoxin levels comparable with or higher than the rural agricultural sites. By volume, endotoxin levels were highest at sites downwind of Los Angeles, California, which were also the locations of highest PM10. Endotoxin concentrations measured in this study were all < 5.5 EU/m3, which is lower than recognized thresholds for acute adverse health effects for occupational exposures but in the same range as indoor household concentrations. This study provides the first extensive characterization of endotoxin concentration across a large metropolitan area in relation to PM10 and other pollutant monitoring, and supports the need for studies of the role of endotoxin in childhood asthma in urban settings. PMID:15064165

  13. Addressing Global Mortality from Ambient PM2.5.

    PubMed

    Apte, Joshua S; Marshall, Julian D; Cohen, Aaron J; Brauer, Michael

    2015-07-07

    Ambient fine particulate matter (PM2.5) has a large and well-documented global burden of disease. Our analysis uses high-resolution (10 km, global-coverage) concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease 2010 to assess how regional and global improvements in ambient air quality could reduce attributable mortality from PM2.5. Overall, an aggressive global program of PM2.5 mitigation in line with WHO interim guidelines could avoid 750 000 (23%) of the 3.2 million deaths per year currently (ca. 2010) attributable to ambient PM2.5. Modest improvements in PM2.5 in relatively clean regions (North America, Europe) would result in surprisingly large avoided mortality, owing to demographic factors and the nonlinear concentration-response relationship that describes the risk of particulate matter in relation to several important causes of death. In contrast, major improvements in air quality would be required to substantially reduce mortality from PM2.5 in more polluted regions, such as China and India. Moreover, forecasted demographic and epidemiological transitions in India and China imply that to keep PM2.5-attributable mortality rates (deaths per 100 000 people per year) constant, average PM2.5 levels would need to decline by ∼20-30% over the next 15 years merely to offset increases in PM2.5-attributable mortality from aging populations. An effective program to deliver clean air to the world's most polluted regions could avoid several hundred thousand premature deaths each year.

  14. Hybridization of GA and ANN to Solve Graph Coloring

    NASA Astrophysics Data System (ADS)

    Maitra, Timir; Pal, Anindya J.; Choi, Minkyu; Kim, Taihoon

    A recent and very promising approach for combinatorial optimization is to embed local search into the framework of evolutionary algorithms. In this paper, we present one efficient hybrid algorithms for the graph coloring problem. Here we have considered the hybridization of Boltzmann Machine (BM) of Artificial Neural Network with Genetic Algorithms. Genetic algorithm we have used to generate different coloration of a graph quickly on which we have applied boltzmann machine approach. Unlike traditional approaches of GA and ANN the proposed hybrid algorithm is guranteed to have 100% convergence rate to valid solution with no parameter tuning. Experiments of such a hybrid algorithm are carried out on large DIMACS Challenge benchmark graphs. Results prove very competitive. Analysis of the behavior of the algorithm sheds light on ways to further improvement.

  15. Locomotion training of legged robots using hybrid machine learning techniques

    NASA Technical Reports Server (NTRS)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

    1995-01-01

    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible patent by NASA, Johnson Space Center. An alternative modular approach is also developed which uses separate controllers for each stage of the running stride. A self-organizing fuzzy-neural controller controls the height, distance and angular momentum of the stride. A CMAC-based controller controls the movement of the leg from the time the foot leaves the ground to the time of landing. Because the leg joints are controlled at each time step during flight, movement is smooth and obstacles can be avoided. Initial results indicate that this approach can yield fast, accurate results.

  16. Evaluating Machine Learning Classifiers for Hybrid Network Intrusion Detection Systems

    DTIC Science & Technology

    2015-03-26

    13 2.3.2 Anomaly-Based Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3.3 Stateful Protocol Analysis...1 TCP Transmission Control Protocol ...3 IP Internet Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 VFT Value-Focused Thinking

  17. Proton emission from 125Pm could be observed

    NASA Astrophysics Data System (ADS)

    Maglione, Enrico; Ferreira, Lidia S.

    2016-10-01

    We perform a feasibility study for the search of proton decay from Pm, the last element without an isotope found, that decays by proton emission in the region of charges between 50 and 83. The behaviors of the half-lives for decay from the ground and possible isomeric states of 125Pm are discussed as a function of deformation, spin of the decaying state, and energy of the emitted proton, indicating the most probable regions of energy where proton radioactivity might be detected. We find that within our predictions, proton decay from 125Pm could be measurable.

  18. Number size distribution, mass concentration, and particle composition of PM1, PM2.5, and PM10 in bag filling areas of carbon black production.

    PubMed

    Kuhlbusch, T A J; Neumann, S; Fissan, H

    2004-10-01

    Number size characteristics and PM10 mass concentrations of particles emitted during the packaging of various kinds of carbon blacks were measured continuously in the bag filling areas of three carbon black plants and concurrently at ambient comparison sites. PM10, PM2.5, and PM1 dust fractions were also determined in the bag filling areas. The filter samples were then analyzed for elemental and organic carbon. Comparisons of the measured number size distributions and mass concentrations during bag filling activities with those measured parallel at the ambient site and with those determined during nonworking periods in the work area enabled the characterization of emitted particles. PM10 mass concentrations were consistently elevated (up to a factor of 20 compared to ambient concentrations) during working periods in the bag filling area. Detailed analysis revealed that the carbon black particles released by bag filling activities had a size distribution starting at approximately 400 nm aerodynamic diameter (dae) with modes around 1 microm dae and > 8 microm dae. Ultrafine particles (< 100 nm dae), detected in the bag filling areas, were most likely attributed to noncarbon black sources such as forklift and gas heater emissions.

  19. Manufacturing of aluminium nano hybrid composites: a state of review

    NASA Astrophysics Data System (ADS)

    Madhukar, P.; Selvaraj, N.; Rao, CSP

    2016-09-01

    This paper gives the details of hybrid composites, their fabrication methods and evaluation of mechanical, tribological behaviour and machining characteristics. Investigations on the various aspects of Hybrid composites furnish several conclusions regarding the influence of various parameters on the performance of the composites. Mostly micro structures of the hybrid composites fabricated through casting routes have been found to be stable with the distribution of uniformed reinforce particles. therefore, the hybrid composites can be constructed with various combinations of reinforcements to carry out desirable mechanical properties. The density of Hybrid composites increases with increasing reinforcements such as SiC, TiC, B4C....etc, while incorporation of partial reinforcements like fly ash, mica, rice husk, etc. reduces the density of composites. The study also reports that the hybrid composites can be treated as a replacement for regular composite materials in different advanced applications.

  20. 40 CFR 1065.595 - PM sample post-conditioning and total weighing.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ...., filters). (g) Subtract each buoyancy-corrected tare mass of the sample medium (e.g., filter) from its respective buoyancy-corrected mass. The result is the net PM mass, m PM. Use m PM in emission calculations...

  1. Inhalable Microorganisms in Beijing’s PM2.5 and PM10 Pollutants during a Severe Smog Event

    PubMed Central

    2014-01-01

    Particulate matter (PM) air pollution poses a formidable public health threat to the city of Beijing. Among the various hazards of PM pollutants, microorganisms in PM2.5 and PM10 are thought to be responsible for various allergies and for the spread of respiratory diseases. While the physical and chemical properties of PM pollutants have been extensively studied, much less is known about the inhalable microorganisms. Most existing data on airborne microbial communities using 16S or 18S rRNA gene sequencing to categorize bacteria or fungi into the family or genus levels do not provide information on their allergenic and pathogenic potentials. Here we employed metagenomic methods to analyze the microbial composition of Beijing’s PM pollutants during a severe January smog event. We show that with sufficient sequencing depth, airborne microbes including bacteria, archaea, fungi, and dsDNA viruses can be identified at the species level. Our results suggested that the majority of the inhalable microorganisms were soil-associated and nonpathogenic to human. Nevertheless, the sequences of several respiratory microbial allergens and pathogens were identified and their relative abundance appeared to have increased with increased concentrations of PM pollution. Our findings may serve as an important reference for environmental scientists, health workers, and city planners. PMID:24456276

  2. Inhalable microorganisms in Beijing's PM2.5 and PM10 pollutants during a severe smog event.

    PubMed

    Cao, Chen; Jiang, Wenjun; Wang, Buying; Fang, Jianhuo; Lang, Jidong; Tian, Geng; Jiang, Jingkun; Zhu, Ting F

    2014-01-01

    Particulate matter (PM) air pollution poses a formidable public health threat to the city of Beijing. Among the various hazards of PM pollutants, microorganisms in PM2.5 and PM10 are thought to be responsible for various allergies and for the spread of respiratory diseases. While the physical and chemical properties of PM pollutants have been extensively studied, much less is known about the inhalable microorganisms. Most existing data on airborne microbial communities using 16S or 18S rRNA gene sequencing to categorize bacteria or fungi into the family or genus levels do not provide information on their allergenic and pathogenic potentials. Here we employed metagenomic methods to analyze the microbial composition of Beijing's PM pollutants during a severe January smog event. We show that with sufficient sequencing depth, airborne microbes including bacteria, archaea, fungi, and dsDNA viruses can be identified at the species level. Our results suggested that the majority of the inhalable microorganisms were soil-associated and nonpathogenic to human. Nevertheless, the sequences of several respiratory microbial allergens and pathogens were identified and their relative abundance appeared to have increased with increased concentrations of PM pollution. Our findings may serve as an important reference for environmental scientists, health workers, and city planners.

  3. The direct influence of ship traffic on atmospheric PM2.5, PM10 and PAH in Venice.

    PubMed

    Contini, D; Gambaro, A; Belosi, F; De Pieri, S; Cairns, W R L; Donateo, A; Zanotto, E; Citron, M

    2011-09-01

    The direct influence of ship traffic on atmospheric levels of coarse and fine particulate matter (PM(2.5), PM(10)) and fifteen polycyclic aromatic hydrocarbons (PAHs) has been estimated in the urban area of Venice. Data analysis has been performed on results collected at three sites over the summer, when ship traffic is at a maximum. Results indicate that monitoring of the PM daily concentrations is not sufficiently detailed for the evaluation of this contribution, even though it could be useful for specific markers such as PAHs. Therefore a new methodology, based on high temporal resolution measurements coupled with wind direction information and the database of ship passages of the Harbour Authority of Venice has been developed. The sampling sites were monitored with optical detectors (DustTrack(®) and Mie pDR-1200) operating at a high temporal resolution (20s and 1s respectively) for PM(2.5) and PM(10). PAH in the particulate and gas phases were recovered from quartz fibre filters and polyurethane foam plugs using pressurised solvent extraction, the extracts were then analysed by gas chromatography- high-resolution mass spectrometry. Our results shows that the direct contribution of ships traffic to PAHs in the gas phase is 10% while the contribution to PM(2.5) and to PM(10) is from 1% up to 8%.

  4. Chemical composition and source apportionment of PM10 and PM2.5 in different functional areas of Lanzhou, China.

    PubMed

    Qiu, Xionghui; Duan, Lei; Gao, Jian; Wang, Shulan; Chai, Fahe; Hu, Jun; Zhang, Jingqiao; Yun, Yaru

    2016-02-01

    To elucidate the air pollution characteristics of northern China, airborne PM10 (atmospheric dynamic equivalent diameter ≤ 10 μm) and PM2.5 (atmospheric dynamic equivalent diameter ≤ 2.5 μm) were sampled in three different functional areas (Yuzhong County, Xigu District and Chengguan District) of Lanzhou, and their chemical composition (elements, ions, carbonaceous species) was analyzed. The results demonstrated that the highest seasonal mean concentrations of PM10 (369.48 μg/m(3)) and PM2.5 (295.42 μg/m(3)) were detected in Xigu District in the winter, the lowest concentration of PM2.5 (53.15 μg/m(3)) was observed in Yuzhong District in the fall and PM10 (89.60 μg/m(3)) in Xigu District in the fall. The overall average OC/EC (organic carbon/elemental carbon) value was close to the representative OC/EC ratio for coal consumption, implying that the pollution of Lanzhou could be attributed to the burning of coal. The content of SNA (the sum of sulfate, nitrate, ammonium, SNA) in PM2.5 in Yuzhong County was generally lower than that at other sites in all seasons. The content of SNA in PM2.5 and PM10 in Yuzhong County was generally lower than that at other sites in all seasons (0.24-0.38), indicating that the conversion ratios from precursors to secondary aerosols in the low concentration area was slower than in the area with high and intense pollutants. Six primary particulate matter sources were chosen based on positive matrix factorization (PMF) analysis, and emissions from dust, secondary aerosols, and coal burning were identified to be the primary sources responsible for the particle pollution in Lanzhou.

  5. Hybrid model based on Genetic Algorithms and SVM applied to variable selection within fruit juice classification.

    PubMed

    Fernandez-Lozano, C; Canto, C; Gestal, M; Andrade-Garda, J M; Rabuñal, J R; Dorado, J; Pazos, A

    2013-01-01

    Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.

  6. Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

    PubMed Central

    Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.

    2013-01-01

    Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933

  7. It's a Clean Machine

    NASA Technical Reports Server (NTRS)

    1998-01-01

    Under an SBIR (Small Business Innovative Research) from Lewis Research Center, Precision Combustion, Inc. (PCI) developed the Advanced Technology Catalytic Combustor. The research proved the viability of efficient, cost-effective catalytic reduction of gas turbine nitrogen oxide emissions along with fuel efficiency. PCI has signed agreements with Westinghouse, other gas turbine manufacturers, including Capstone Turbine Corporation to develop a catalytic combustor for their hybrid electric vehicle.

  8. 15. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

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

    15. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to northeast (90mm lens). The arched cutouts in the bottom chords of the roof trusses were necessary to provide clearance for the smokestacks of steam locomotives, and also mark the location of the former inspection pit in the floor (now filled in and covered by a new concrete floor). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

  9. Back to the future: stationary source testing for fine PM

    SciTech Connect

    Ron Myers

    2006-04-15

    Decisions will be necessary concerning the most appropriate stationary source test methodologies for continuing our efforts to clean up the atmosphere. In many regions of the United States, existing methods to measure stationary source pollutant emissions may be acceptable for the foreseeable future. However, other regions will require more comprehensive source measurement methods that expand the measured pollutants to include the full range of the atmospheric burden. Decisions about which path(s) to follow will depend on existing ambient air quality levels an the need to better quantify atmospheric emissions of primary PM from stationary sources, control stationary source primary PM to achieve the ambient air quality standard, and better understand the components of stationary source primary PM emissions. This article focuses on quantifying fine PM emissions from stationary sources, including Method 5B for utility plants. 24 refs., 1 tab.

  10. NARSTO EPA SS ST LOUIS AIR CHEM PM MET DATA

    Atmospheric Science Data Center

    2014-05-07

    NARSTO EPA SS ST LOUIS AIR CHEM PM MET DATA Project Title:  NARSTO ... Aethaelometer Anemometer Rain Gauge Pressure Sensor Radiometers Temperature Sensor Weighing Balance AA (Atomic Absorption Spectrometer) ...

  11. Line drawing of STS-34 middeck experiment Polymer Morphology (PM)

    NASA Technical Reports Server (NTRS)

    1989-01-01

    STS-34 middeck experiment Polymer Morphology (PM) and its apparatus is illustrated in this line drawing. Apparatus for the experiment, developed by 3M, includes a Fournier transform infrared (FTIR) spectrometer, an automatic sample manipulating system and a process control and data acquisition computer known as the Generic Electronics Module (GEM). STS-34 mission specialists will interface with the PM experiment through a small, NASA-supplied laptop computer that is used as an input and output device for the main PM computer. PM experiment is an organic materials processing experiment designed to explore the effects of microgravity on polymeric materials as they are processed in space and is being conducted by 3M's Space Research and Applications Laboratory.

  12. Lab Analyses of Fenceline PM10 Air Filters

    EPA Pesticide Factsheets

    These spreadsheets show the analytical data on PM10 concentration, organic carbon, elemental carbon, and several trace metals at KCBX petroleum coke (also known as pet coke or petcoke) storage terminals in Chicago, Illinois.

  13. ASSESSMENT OF INDOOR, OUTDOOR, AND PERSONAL PM DIFFERENCES

    EPA Science Inventory

    Epidemiological studies have consistently demonstrated that a correlation exists between daily ambient particle concentrations and health effects.' One major area of concern with respect to particulate matter (PM) is the relationship between indoor and outdoor particle concentr...

  14. Phosphoinositide kinase signaling controls ER-PM cross-talk

    PubMed Central

    Omnus, Deike J.; Manford, Andrew G.; Bader, Jakob M.; Emr, Scott D.; Stefan, Christopher J.

    2016-01-01

    Membrane lipid dynamics must be precisely regulated for normal cellular function, and disruptions in lipid homeostasis are linked to the progression of several diseases. However, little is known about the sensory mechanisms for detecting membrane composition and how lipid metabolism is regulated in response to membrane stress. We find that phosphoinositide (PI) kinase signaling controls a conserved PDK-TORC2-Akt signaling cascade as part of a homeostasis network that allows the endoplasmic reticulum (ER) to modulate essential responses, including Ca2+-regulated lipid biogenesis, upon plasma membrane (PM) stress. Furthermore, loss of ER-PM junctions impairs this protective response, leading to PM integrity defects upon heat stress. Thus PI kinase–mediated ER-PM cross-talk comprises a regulatory system that ensures cellular integrity under membrane stress conditions. PMID:26864629

  15. Enhanced PM10 bounded PAHs from shipping emissions

    NASA Astrophysics Data System (ADS)

    Pongpiachan, S.; Hattayanone, M.; Choochuay, C.; Mekmok, R.; Wuttijak, N.; Ketratanakul, A.

    2015-05-01

    Earlier studies have highlighted the importance of maritime transport as a main contributor of air pollutants in port area. The authors intended to investigate the effects of shipping emissions on the enhancement of PM10 bounded polycyclic aromatic hydrocarbons (PAHs) and mutagenic substances in an industrial area of Rayong province, Thailand. Daily PM10 speciation data across two air quality observatory sites in Thailand during 2010-2013 were collected. Diagnostic binary ratios of PAH congeners, analysis of variances (ANOVA), and principal component analysis (PCA) were employed to evaluate the enhanced genotoxicity of PM10 during the docking period. Significant increase of PAHs and mutagenic index (MI) of PM10 were observed during the docking period in both sampling sites. Although stationary sources like coal combustions from power plants and vehicular exhausts from motorway can play a great role in enhancing PAH concentrations, regulating shipping emissions from diesel engine in the port area like Rayong is predominantly crucial.

  16. PM2.5 Gravimetric Lab Training (2016 NAAMC)

    EPA Pesticide Factsheets

    This training focused on understanding/applying the PM2.5 FRM in 40 CFR part 50, Appendix L and the updated QA Guidance Document 2.12. it was geared primarily for monitoring and QA managers and staff.

  17. Machine Learning for Dynamical Mean Field Theory

    NASA Astrophysics Data System (ADS)

    Arsenault, Louis-Francois; Lopez-Bezanilla, Alejandro; von Lilienfeld, O. Anatole; Littlewood, P. B.; Millis, Andy

    2014-03-01

    Machine Learning (ML), an approach that infers new results from accumulated knowledge, is in use for a variety of tasks ranging from face and voice recognition to internet searching and has recently been gaining increasing importance in chemistry and physics. In this talk, we investigate the possibility of using ML to solve the equations of dynamical mean field theory which otherwise requires the (numerically very expensive) solution of a quantum impurity model. Our ML scheme requires the relation between two functions: the hybridization function describing the bare (local) electronic structure of a material and the self-energy describing the many body physics. We discuss the parameterization of the two functions for the exact diagonalization solver and present examples, beginning with the Anderson Impurity model with a fixed bath density of states, demonstrating the advantages and the pitfalls of the method. DOE contract DE-AC02-06CH11357.

  18. Privacy preserving RBF kernel support vector machine.

    PubMed

    Li, Haoran; Xiong, Li; Ohno-Machado, Lucila; Jiang, Xiaoqian

    2014-01-01

    Data sharing is challenging but important for healthcare research. Methods for privacy-preserving data dissemination based on the rigorous differential privacy standard have been developed but they did not consider the characteristics of biomedical data and make full use of the available information. This often results in too much noise in the final outputs. We hypothesized that this situation can be alleviated by leveraging a small portion of open-consented data to improve utility without sacrificing privacy. We developed a hybrid privacy-preserving differentially private support vector machine (SVM) model that uses public data and private data together. Our model leverages the RBF kernel and can handle nonlinearly separable cases. Experiments showed that this approach outperforms two baselines: (1) SVMs that only use public data, and (2) differentially private SVMs that are built from private data. Our method demonstrated very close performance metrics compared to nonprivate SVMs trained on the private data.

  19. Weekly cycle of magnetic characteristics of PM2.5 and PM2.5-10 in Beijing, China

    NASA Astrophysics Data System (ADS)

    SHI, M.; Wu, H.; Zhang, S.; Li, H.; Yang, T.

    2013-12-01

    In urban areas,fine particle matter with aerodynamic diameter between 2.5 um and 10 um (PM2.5-10), and 2.5 um (PM2.5), as an important source of urban particulate matter (PM) pollutants, have significant negative effects on health, atmospheric visibility and climate. PM has increasingly become a significant index of indicating the atmospheric pollution of city. In recent years, Beijing, China has been listed as one of the most serious air pollution city in the world. In order to investigate the sources of air pollutants, a total of 283 pairs of PM2.5 and PM2.5-10 samples were collected daily from July, 2010 to June, 2011 in Beijing. Mineral magnetic properties and Scanning electron microscope (SEM) observations and energy dispersive X-ray spectroscopy (EDS) analyses of PM2.5 and PM2.5-10 were measured to verify the magnetic materials. Magnetic measures for PM indicated that the major magnetic phase was coarse-grained magnetite-like material. The χlf, χarm, SIRM and χarm/SIRM series of the PM2.5 and PM2.5-10 show seasonal dependences: high values in winter and low values in summer. In additional the parameters analyzed by Time-series methods show a strong cycle about 7 days above 95% confidence level. Weekly cycle of magnetic characteristics of PM2.5 and PM2.5-10 show different pattern: the concentration of magnetic particles in PM2.5-10 show high values in mid-week, and particle sizes is steady, while the concentration of magnetic particles in PM2.5 show reverse a weekly cycle pattern, and particle sizes is smaller in the mid-week.Microscopy analyses reveal basically three morphologies of magnetic grains: aggregate, spherules and angular particles. The ultrafine carbonaceous particles which tend to form complex clusters and chain-like structures, most likely come from coal burning and motor vehicle exhaust. Spherical particles in PM2.5 are dominantly composed of Fe, O and C, grain-diameters of particles range from 0.3 to 2 um. Angular particles of Fe

  20. Effect of design variables on starting torque of single phase flux-reversal machine

    NASA Astrophysics Data System (ADS)

    Won, Sung Hong; Kim, Tae Heoung; Jang, Ki-Bong; Choi, Seung-Kil; Oh, Won Seok; Lee, Ju

    2006-04-01

    This article introduces a single phase flux-reversal machine (FRM) and presents the design method to improve its starting torque. The effects of the design parameters on the characteristic and starting torque are analyzed by the finite element method. The design variables considered are tapered airgap, stepped airgap, slotted teeth, and asymmetric PM width. As a result, we can find the best model in producing starting torque of a single phase 2/3 FRM.

  1. All-PM CW fiber optical parametric oscillator.

    PubMed

    Zlobina, Ekaterina A; Kablukov, Sergey I; Babin, Sergey A

    2016-10-31

    We demonstrate for the first time a CW all-polarization maintaining (PM) all-fiber optical parametric oscillator (FOPO) based on a birefringent photonic crystal fiber pumped by a tunable linearly polarized ytterbium-doped fiber laser. The all-PM FOPO features polarization-adjustment-free tunable operation in wavelength range from 920 to 1000 nm for both the slow and the fast fiber axes with output power reaching 1.3 W.

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

    PubMed Central

    Subbulakshmi, C. V.; Deepa, S. N.

    2015-01-01

    Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning paradigm. This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. As a recent off-line learning method, ELM is a single-hidden layer feedforward neural network (FFNN), proved to be an excellent classifier with large number of hidden layer neurons. In this research, PSO is used to determine the optimum set of parameters for the ELM, thus reducing the number of hidden layer neurons, and it further improves the network generalization performance. The proposed method is experimented on five benchmarked datasets of the UCI Machine Learning Repository for handling medical dataset classification. Simulation results show that the proposed approach is able to achieve good generalization performance, compared to the results of other classifiers. PMID:26491713

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

    PubMed

    Subbulakshmi, C V; Deepa, S N

    2015-01-01

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

  4. Will machines ever think

    NASA Technical Reports Server (NTRS)

    Denning, P. J.

    1986-01-01

    Artificial Intelligence research has come under fire for failing to fulfill its promises. A growing number of AI researchers are reexamining the bases of AI research and are challenging the assumption that intelligent behavior can be fully explained as manipulation of symbols by algorithms. Three recent books -- Mind over Machine (H. Dreyfus and S. Dreyfus), Understanding Computers and Cognition (T. Winograd and F. Flores), and Brains, Behavior, and Robots (J. Albus) -- explore alternatives and open the door to new architectures that may be able to learn skills.

  5. Hybrid Gear

    NASA Technical Reports Server (NTRS)

    Handschuh, Robert F. (Inventor); Roberts, Gary D. (Inventor)

    2016-01-01

    A hybrid gear consisting of metallic outer rim with gear teeth and metallic hub in combination with a composite lay up between the shaft interface (hub) and gear tooth rim is described. The composite lay-up lightens the gear member while having similar torque carrying capability and it attenuates the impact loading driven noise/vibration that is typical in gear systems. The gear has the same operational capability with respect to shaft speed, torque, and temperature as an all-metallic gear as used in aerospace gear design.

  6. On the operation of machines powered by quantum non-thermal baths

    NASA Astrophysics Data System (ADS)

    Niedenzu, Wolfgang; Gelbwaser-Klimovsky, David; Kofman, Abraham G.; Kurizki, Gershon

    2016-08-01

    Diverse models of engines energised by quantum-coherent, hence non-thermal, baths allow the engine efficiency to transgress the standard thermodynamic Carnot bound. These transgressions call for an elucidation of the underlying mechanisms. Here we show that non-thermal baths may impart not only heat, but also mechanical work to a machine. The Carnot bound is inapplicable to such a hybrid machine. Intriguingly, it may exhibit dual action, concurrently as engine and refrigerator, with up to 100% efficiency. We conclude that even though a machine powered by a quantum bath may exhibit an unconventional performance, it still abides by the traditional principles of thermodynamics.

  7. Acute Exposure to Particulate Matter (PM) Alters Physiologic ...

    EPA Pesticide Factsheets

    Human exposure to ambient PM from fossil-fuel emissions is linked to cardiovascular disease and death. This association strengthens in people with preexisting cardiopulmonary diseases—especially heart failure (HF). We previously examined the effects of PM on HF by exposing Spontaneously Hypertensive Heart Failure (SHHF) rats to residual oil fly ash (ROFA) after accelerating HF onset via isoproterenol (ISO) infusion. In that study, rats were exposed to PM 2 wks after ISO treatment ceased, which was more than 1 wk after ISO-cessation had induced a 9-d period of hypotension. Epidemiological evidence suggests that effects would be more pronounced if exposure coincided with the HF-like hypotensive period. We hypothesized that PM exposure shortly after cessation of ISO treatment would cause greater cardiopulmonary injury. SHHF rats were infused with ISO (n=24; 1.0 mg/kg/d sc) or saline (n=23) via osmotic pump for 5 wks and then 5 d later exposed by nose-only inhalation for 4 h to either air or 580 µg/m3 of the PM2.5 fraction of a synthetic PM (dried salt solution, MSO4) similar in composition to a well-studied ROFA and consisting of Fe, Ni and V sulfates. In ISO-pretreated rats only, MSO4 decreased pulse pressure (an indirect indicator of cardiac output), decreased systolic and diastolic blood pressures, and increased QA interval (inversely related to myocardial contractility) during inhalation exposure and caused post-inhalation pulmonary inflammation significantl

  8. Implementation and evaluation of PM2.5 source contribution ...

    EPA Pesticide Factsheets

    Source culpability assessments are useful for developing effective emissions control programs. The Integrated Source Apportionment Method (ISAM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to track contributions from source groups and regions to ambient levels and deposited amounts of primary and secondary inorganic PM2.5. Confidence in this approach is established by comparing ISAM source contribution estimates to emissions zero-out simulations recognizing that these approaches are not always expected to provide the same answer. The comparisons are expected to be most similar for more linear processes such as those involving primary emissions of PM2.5 and most different for non-linear systems like ammonium nitrate formation. Primarily emitted PM2.5 (e.g. elemental carbon), sulfur dioxide, ammonia, and nitrogen oxide contribution estimates compare well to zero-out estimates for ambient concentration and deposition. PM2.5 sulfate ion relationships are strong, but nonlinearity is evident and shown to be related to aqueous phase oxidation reactions in the host model. ISAM and zero-out contribution estimates are less strongly related for PM2.5 ammonium nitrate, resulting from instances of non-linear chemistry and negative responses (increases in PM2.5 due to decreases in emissions). ISAM is demonstrated in the context of an annual simulation tracking well characterized emissions source sectors and boundary conditions shows source contri

  9. Anomalous elevated radiocarbon measurements of PM2.5

    NASA Astrophysics Data System (ADS)

    Buchholz, Bruce A.; Fallon, Stewart J.; Zermeño, Paula; Bench, Graham; Schichtel, Bret A.

    2013-01-01

    Two-component models are often used to determine the contributions made by fossil fuel and natural sources of carbon in airborne particulate matter (PM). The models reduce thousands of actual sources to two end members based on isotopic signature. Combustion of fossil fuels produces PM free of carbon-14 (14C). Wood or charcoal smoke, restaurant fryer emissions, and natural emissions from plants produce PM with the contemporary concentration of 14C approximately 1.2 × 10-1214C/C. Such data can be used to estimate the relative contributions of fossil fuels and biogenic aerosols to the total aerosol loading and radiocarbon analysis is becoming a popular source apportionment method. Emissions from incinerators combusting medical or biological wastes containing tracer 14C can skew the 14C/C ratio of PM, however, so critical analysis of sampling sites for possible sources of elevated PM needs to be completed prior to embarking on sampling campaigns. Results are presented for two ambient monitoring sites in different areas of the United States where 14C contamination is apparent. Our experience suggests that such contamination is uncommon but is also not rare (∼10%) for PM sampling sites.

  10. Learning thermodynamics with Boltzmann machines

    NASA Astrophysics Data System (ADS)

    Torlai, Giacomo; Melko, Roger G.

    2016-10-01

    A Boltzmann machine is a stochastic neural network that has been extensively used in the layers of deep architectures for modern machine learning applications. In this paper, we develop a Boltzmann machine that is capable of modeling thermodynamic observables for physical systems in thermal equilibrium. Through unsupervised learning, we train the Boltzmann machine on data sets constructed with spin configurations importance sampled from the partition function of an Ising Hamiltonian at different temperatures using Monte Carlo (MC) methods. The trained Boltzmann machine is then used to generate spin states, for which we compare thermodynamic observables to those computed by direct MC sampling. We demonstrate that the Boltzmann machine can faithfully reproduce the observables of the physical system. Further, we observe that the number of neurons required to obtain accurate results increases as the system is brought close to criticality.

  11. Retrospective prediction of intraurban spatiotemporal distribution of PM2.5 in Taipei

    NASA Astrophysics Data System (ADS)

    Hwa-Lung, Yu; Chih-Hsin, Wang

    2010-08-01

    Numerous studies have shown that fine airborne particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. The assessment of the impacts to human health or ecological effects by long-term PM2.5 exposure is often limited by lack of PM2.5 measurements. In Taipei, PM2.5 was not systematically observed until August, 2005. Taipei is the largest metropolitan area in Taiwan, where a variety of industrial and traffic emissions are continuously generated and distributed across space and time. PM-related data, i.e., PM10 and Total Suspended Particles (TSP) are independently systematically collected by different central and local government institutes. In this study, the retrospective prediction of spatiotemporal distribution of monthly PM2.5 over Taipei will be performed by using Bayesian Maximum Entropy method (BME) to integrate (a) the spatiotemporal dependence among PM measurements (i.e. PM10, TSP, and PM2.5), (b) the site-specific information of PM measurements which can be certain or uncertain information, and (c) empirical evidence about the PM2.5/PM10 and PM10/TSP ratios. The performance assessment of the retrospective prediction for the spatiotemporal distribution of PM2.5 was performed over space and time during 2003-2004 by comparing the posterior pdf of PM2.5 with the observations. Results show that the incorporation of PM10 and TSP observations by BME method can effectively improve the spatiotemporal PM2.5 estimation in the sense of lower mean and standard deviation of estimation errors. Moreover, the spatiotemporal retrospective prediction with PM2.5/PM10 and PM2.5/TSP ratios can provide good estimations of the range of PM2.5 levels over space and time during 2003-2004 in Taipei.

  12. Multiple man-machine interfaces

    NASA Technical Reports Server (NTRS)

    Stanton, L.; Cook, C. W.

    1981-01-01

    The multiple man machine interfaces inherent in military pilot training, their social implications, and the issue of possible negative feedback were explored. Modern technology has produced machines which can see, hear, and touch with greater accuracy and precision than human beings. Consequently, the military pilot is more a systems manager, often doing battle against a target he never sees. It is concluded that unquantifiable human activity requires motivation that is not intrinsic in a machine.

  13. Establishing a link between vehicular PM sources and PM measurements in urban street canyons.

    PubMed

    Eisner, Alfred D; Richmond-Bryant, Jennifer; Wiener, Russell W; Hahn, Intaek; Drake-Richman, Zora E; Ellenson, William D

    2009-12-01

    The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, conducted in Brooklyn, NY, USA, in 2005, was designed with multiple goals in mind, two of which were contaminant source characterization and street canyon transport and dispersion monitoring. In the portion of the study described here, synchronized wind velocity and azimuth as well as particulate matter (PM) concentrations at multiple locations along 33rd Street were used to determine the feasibility of using traffic emissions in a complex urban topography as a sole tracer for studying urban contaminant transport. We demonstrate in this paper that it is possible to link downwind concentrations of contaminants in an urban street canyon to the vehicular traffic cycle using Eigen-frequency analysis. In addition, multivariable circular histograms are used to establish directional frequency maxima for wind velocity and contaminant concentration.

  14. Microvalve and micropump controlled shuttle flow microfluidic device for rapid DNA hybridization.

    PubMed

    Huang, Shuqiang; Li, Chunyu; Lin, Bingcheng; Qin, Jianhua

    2010-11-07

    We present a novel microfluidic device integrated with microvalves and micropumps for rapid DNA hybridization using shuttle flow. The device is composed of 48 hybridization units containing 48 microvalves and 96 micropumps for the automation of shuttle flow. We used four serotypes of Dengue Virus genes (18mer) to demonstrate that the automatic shuttle flow shortened the hybridization time to 90 s, reduced sample consumption to 1 μL and lowered detection limit to 100 pM (100 amol in a 1 μL sample). Moreover, we applied this device to realize single base discrimination and analyze 48 samples containing different DNA targets, simultaneously. For kinetic measurements of nucleotide hybridization, on-line monitoring of the processes was carried out. This rapid hybridization device has the ability for accommodating the entire hybridization process (i.e., injection, hybridization, washing, detection, signal acquisition) in an automated and high-throughput fashion.

  15. Quantification of Global Primary Emissions of PM2.5, PM10, and TSP from Combustion and Industrial Process Sources

    NASA Astrophysics Data System (ADS)

    Huang, Ye; Tao, Shu

    2015-04-01

    Emission quantification of primary particulate matter (PM) is essential for assessment of its related climate and health impacts. To reduce uncertainty associated with global emissions of TSP, PM10 and PM2.5, we compiled data with high spatial (0.1° ×0.1° ) and sectorial (77 primary sources) resolutions for 2007 based on a newly released global fuel data product (PKU-FUEL-2007), and an emission factor database including emission factors measured recently in developing countries. Total emissions for TSP, PM10 and PM2.5 were estimated to be 162 (123-224), 99 (80-130), and 78 (64-101) Tg, respectively. Our estimates for developing countries are higher than those previously reported. Spatial bias associated with large countries could be reduced by using sub-national fuel consumption data. Despite the fact that most industrial and transport sources locate in urban areas, residential fuel consumptions are quite different between rural and urban areas, especially in developing countries. As a result, per person annual primary PM emission in rural areas are much higher than those in urban areas. Further, this difference in developed countries (12 and 2.8 kg PM2.5 for rural and urban areas) is larger than that in developing countries (8.4 and 4.6 kg PM2.5 for rural and urban areas). Additionally, we looked at temporal trends from 1960 to 2009 at country-scale resolution. Although total emissions are still increasing in developing countries, their intensities in terms of gross domestic production or energy consumption have decreased. PM emitted in developed countries is finer owing to a larger contribution from non-industrial sources, and use of abatement technologies. In contrast, countries like China, with strong industry emissions and limited abatement facilities, emit coarser PM. The health impacts of PM are intensified in hotspots and cities owing to covariance of sources and receptors. Although urbanization reduces the per person emission, overall health impacts

  16. Measure Transformer Semantics for Bayesian Machine Learning

    NASA Astrophysics Data System (ADS)

    Borgström, Johannes; Gordon, Andrew D.; Greenberg, Michael; Margetson, James; van Gael, Jurgen

    The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a prior distribution) and a set of observations of variables. There is a trend in machine learning towards expressing Bayesian models as probabilistic programs. As a foundation for this kind of programming, we propose a core functional calculus with primitives for sampling prior distributions and observing variables. We define combinators for measure transformers, based on theorems in measure theory, and use these to give a rigorous semantics to our core calculus. The original features of our semantics include its support for discrete, continuous, and hybrid measures, and, in particular, for observations of zero-probability events. We compile our core language to a small imperative language that has a straightforward semantics via factor graphs, data structures that enable many efficient inference algorithms. We use an existing inference engine for efficient approximate inference of posterior marginal distributions, treating thousands of observations per second for large instances of realistic models.

  17. Using Machine Learning in Adversarial Environments.

    SciTech Connect

    Warren Leon Davis

    2016-02-01

    Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approaches only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.

  18. Stacked Extreme Learning Machines.

    PubMed

    Zhou, Hongming; Huang, Guang-Bin; Lin, Zhiping; Wang, Han; Soh, Yeng Chai

    2015-09-01

    Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast learning speed, good generalization ability, and ease of implementation. It provides a unified solution that can be used directly to solve regression, binary, and multiclass classification problems. In this paper, we propose a stacked ELMs (S-ELMs) that is specially designed for solving large and complex data problems. The S-ELMs divides a single large ELM network into multiple stacked small ELMs which are serially connected. The S-ELMs can approximate a very large ELM network with small memory requirement. To further improve the testing accuracy on big data problems, the ELM autoencoder can be implemented during each iteration of the S-ELMs algorithm. The simulation results show that the S-ELMs even with random hidden nodes can achieve similar testing accuracy to support vector machine (SVM) while having low memory requirements. With the help of ELM autoencoder, the S-ELMs can achieve much better testing accuracy than SVM and slightly better accuracy than deep belief network (DBN) with much faster training speed.

  19. Earth boring machine

    SciTech Connect

    Durham, M. E.

    1985-11-19

    An earth boring machine for boring straight and level elongated holes through rock-laden earth. The machine includes a stationary elongated frame upon which a first slide is carried. A second slide is carried on the first slide. An elongated auger guiding sleeve is carried adjacent one end of the first slide and has a cutting edge on a remote end thereof. A power-driven auger assembly is carried on the second slide and includes an auger which extends within the guiding sleeve. A cutting tool is carried on the end of the auger adjacent a remote end of the guiding sleeve. An hydraulic cylinder is provided for advancing the first sleeve for driving the cutting edge of the guiding sleeve into the earth while the power driven auger removes the earth as the guiding sleeve is advanced. Another set of hydraulic cylinders are provided for advancing the second slide on the first slide causing the cutting tool to extend out beyond the remote end of the guiding sleeve for cutting through obstructions in the earth when the cutting edge of the guiding sleeve is prevented from moving forward.

  20. Smart Test Machines

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Vern Wedeven, president of Wedeven Associates, developed the WAM4, a computer-aided "smart" test machine for simulating stress on equipment, based on his bearing lubrication expertise gained while working for Lewis Research Center. During his NASA years from the 1970s into the early 1980s, Wedeven initiated an "Interdisciplinary Collaboration in Tribology," an effort that involved NASA, six universities, and several university professors. The NASA-sponsored work provided foundation for Wedeven in 1983 to form his own company. Several versions of the smart test machine, the WAM1, WAM2, and WAM3, have proceeded the current version, WAM4. This computer-controlled device can provide detailed glimpses at gear and bearing points of contact. WAM4 can yield a three-dimensional view of machinery as an operator adds "what-if" thermal and lubrication conditions, contact stress, and surface motion. Along with NASA, a number of firms, including Pratt & Whitney, Caterpillar Tractor, Exxon, and Chevron have approached Wedeven for help on resolving lubrication problems.

  1. Hybrid Simulator

    SciTech Connect

    Trujillo, David J.; Sridharan, Srikesh; Weinstock, Irvin

    2005-10-15

    HybSim (short for Hybrid Simulator) is a flexible, easy to use screening tool that allows the user to quanti the technical and economic benefits of installing a village hybrid generating system and simulates systems with any combination of —Diesel generator sets —Photovoltaic arrays -Wind Turbines and -Battery energy storage systems Most village systems (or small population sites such as villages, remote military bases, small communities, independent or isolated buildings or centers) depend on diesel generation systems for their source of energy. HybSim allows the user to determine other "sources" of energy that can greatly reduce the dollar to kilo-watt hour ratio. Supported by the DOE, Energy Storage Program, HybSim was initially developed to help analyze the benefits of energy storage systems in Alaskan villages. Soon after its development, other sources of energy were added providing the user with a greater range of analysis opportunities and providing the village with potentially added savings. In addition to village systems, HybSim has generated interest for use from military institutions in energy provisions and USAID for international village analysis.

  2. Monetary Valuation of PM10-Related Health Risks in Beijing China: The Necessity for PM10 Pollution Indemnity

    PubMed Central

    Yin, Hao; Xu, Linyu; Cai, Yanpeng

    2015-01-01

    Severe health risks caused by PM10 (particulate matter with an aerodynamic diameter ≤10 μm) pollution have induced inevitable economic losses and have rendered pressure on the sustainable development of society as a whole. In China, with the “Polluters Pay Principle”, polluters should pay for the pollution they have caused, but how much they should pay remains an intractable problem for policy makers. This paper integrated an epidemiological exposure-response model with economics methods, including the Amended Human Capital (AHC) approach and the Cost of Illness (COI) method, to value the economic loss of PM10-related health risks in 16 districts and also 4 functional zones in Beijing from 2008 to 2012. The results show that from 2008 to 2012 the estimated annual deaths caused by PM10 in Beijing are around 56,000, 58,000, 63,000, 61,000 and 59,000, respectively, while the economic losses related to health damage increased from around 23 to 31 billion dollars that PM10 polluters should pay for pollution victims between 2008 and 2012. It is illustrated that not only PM10 concentration but also many other social economic factors influence PM10-related health economic losses, which makes health economic losses show a time lag discrepancy compared with the decline of PM10 concentration. In conclusion, health economic loss evaluation is imperative in the pollution indemnity system establishment and should be considered for the urban planning and policy making to control the burgeoning PM10 health economic loss. PMID:26308020

  3. Identification of fine (PM1) and coarse (PM10-1) sources of particulate matter in an urban environment

    NASA Astrophysics Data System (ADS)

    Titos, G.; Lyamani, H.; Pandolfi, M.; Alastuey, A.; Alados-Arboledas, L.

    2014-06-01

    PM10 and PM1 samples were collected at an urban site in southeastern Spain during 2006-2010. The chemical composition of all samples has been determined and analyzed by Positive Matrix Factorization (PMF) technique for fine and coarse source identification. The PMF results have been analyzed for working and non-working days in order to evaluate the change in PM sources contribution and possible future abatement strategies. A decreasing trend in PM10 levels and in its constituents has been observed, being partly associated to a reduction in anthropogenic activities due to the economic crisis. The use of fine and coarse PM in the PMF analysis allowed us for the identification of additional sources that could not be identified using only one size fraction. The mineral dust source was identified in both fractions and comprised 36 and 22% of the total mass in the coarse and fine fractions, respectively. This high contribution of the mineral source to the fine fraction may be ascribed to contamination of the source profile. The regional re-circulation source was traced by secondary sulfate, V and Ni. It was the most important source concerning PM1 mass concentration (41% of the total mass in this fraction). Although V and Ni are commonly associated to fuel oil combustion the seasonality of this source with higher concentrations in summer compared with winter suggest that the most important part of this source can be ascribed to regional pollution episodes. A traffic exhaust source was identified but only in the fine fraction, comprising 29% of the fine mass. The celestite mines source associated with nearby open-pit mines was typified by strontium, sulfate and mineral matter. PM10-1 levels were higher in working days, whereas PM1 levels remained fairly constant throughout the whole week. As a conclusion, traffic seems to be the main source to target in Granada.

  4. Monetary Valuation of PM10-Related Health Risks in Beijing China: The Necessity for PM10 Pollution Indemnity.

    PubMed

    Yin, Hao; Xu, Linyu; Cai, Yanpeng

    2015-08-21

    Severe health risks caused by PM10 (particulate matter with an aerodynamic diameter ≤10 μm) pollution have induced inevitable economic losses and have rendered pressure on the sustainable development of society as a whole. In China, with the "Polluters Pay Principle", polluters should pay for the pollution they have caused, but how much they should pay remains an intractable problem for policy makers. This paper integrated an epidemiological exposure-response model with economics methods, including the Amended Human Capital (AHC) approach and the Cost of Illness (COI) method, to value the economic loss of PM10-related health risks in 16 districts and also 4 functional zones in Beijing from 2008 to 2012. The results show that from 2008 to 2012 the estimated annual deaths caused by PM10 in Beijing are around 56,000, 58,000, 63,000, 61,000 and 59,000, respectively, while the economic losses related to health damage increased from around 23 to 31 billion dollars that PM10 polluters should pay for pollution victims between 2008 and 2012. It is illustrated that not only PM10 concentration but also many other social economic factors influence PM10-related health economic losses, which makes health economic losses show a time lag discrepancy compared with the decline of PM10 concentration. In conclusion, health economic loss evaluation is imperative in the pollution indemnity system establishment and should be considered for the urban planning and policy making to control the burgeoning PM10 health economic loss.

  5. In situ amplification signaling-based autonomous aptameric machine for the sensitive fluorescence detection of cocaine.

    PubMed

    Xie, Su-Jin; Zhou, Hui; Liu, Dengyou; Shen, Guo-Li; Yu, Ruqin; Wu, Zai-Sheng

    2013-06-15

    The development of autonomous DNA machines and their use for specific sensing purpose have recently attracted considerable research attention. In existing autonomous machines, the target recognition process and signal transduction are separated from each other. This results in misunderstanding of the operation behavior, and the assay capability is compromised when serving as a sensing tool. In this communication, the integrated signal transduction-based autonomous aptameric machine, in which the recognition element and signal reporters are integrated into a DNA strand, is developed. This new machine can execute the in situ amplification of target binding-induced signal. The authentic operation behavior of autonomous DNA machine is discovered: the machine's products directly hybridize to the "track" rather than to the signaling probes. Along this line, the machine is employed to detect the cocaine in a more straightforward fashion, and improved assay characteristics (for example, the dynamic response range is widened by more than 500-fold) are achieved. Our efforts not only clarify the concept described in traditional autonomous DNA machines but also have made technological advancements that are expected to be especially valuable in designing nucleic acid-based machines employed in basic research and medical diagnosis.

  6. Cyclone robber system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, EPA finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additi...

  7. First stage mote system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions using stack sampling. In 2006, the Environmental Protection Agency (EPA) finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent n...

  8. Master trash system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, the Environmental Protection Agency (EPA) finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This cr...

  9. Mote cleaner system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, EPA finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additi...

  10. Overflow system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, the Environmental Protection Agency (EPA), finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This c...

  11. Mote trash system PM2.5 emission factors and rate for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, the Environmental Protection Agency (EPA) finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This cr...

  12. Combined mote system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, the Environmental Protection Agency (EPA) finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This cr...

  13. Mote cyclone robber system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, the Environmental Protection Agency (EPA) finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This cr...

  14. Combined lint cleaning system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, EPA finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additi...

  15. Battery condenser system PM2.5 emission factors and rates for cotton gins: Method 201A combination PM10 and PM2.5 sizing cyclones

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This report is part of a project to characterize cotton gin emissions from the standpoint of stack sampling. In 2006, EPA finalized and published a more stringent standard for particulate matter with nominal diameter less than or equal to 2.5 µm (PM2.5). This created an urgent need to collect additi...

  16. Standardized Curriculum for Machine Tool Operation/Machine Shop.

    ERIC Educational Resources Information Center

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

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

  17. Machine Shop Milling Machines. Oklahoma Trade and Industrial Education.

    ERIC Educational Resources Information Center

    Dunn, James

    This curriculum guide provides instructional materials designed to equip students with basic knowledge and skills that will enable them to enter the machine trades at the machine-operator level. The curriculum is designed for use in full-time secondary and postsecondary classes and part-time adult classes. It can also be adapted to open-entry,…

  18. Production Machine Shop Employment Competencies. Part Four: The Milling Machine.

    ERIC Educational Resources Information Center

    Bishart, Gus; Werner, Claire

    Competencies for production machine shop are provided for the fourth of four topic areas: the milling machine. Each competency appears in a one-page format. It is presented as a goal statement followed by one or more "indicator" statements, which are performance objectives describing an ability that, upon attainment, will establish…

  19. Two new anti-apoptotic proteins of white spot syndrome virus that bind to an effector caspase (PmCasp) of the giant tiger shrimp Penaeus (Penaeus) monodon.

    PubMed

    Lertwimol, Tareerat; Sangsuriya, Pakkakul; Phiwsaiya, Kornsunee; Senapin, Saengchan; Phongdara, Amornrat; Boonchird, Chuenchit; Flegel, Timothy W

    2014-05-01

    White spot syndrome virus proteins WSSV134 and WSSV322 have been shown to bind with the p20 domain (residues 55-214) of Penaeus monodon caspase (PmCasp) protein through yeast two-hybrid screening. Binding was confirmed for the p20 domain and the full-length caspase by co-immunoprecipitation. WSSV134 is also known as the WSSV structural protein VP36A, but no function or conserved domains have been ascribed to WSSV322. Discovery of the caspase binding activity of these two proteins led to an investigation of their possible anti-apoptotic roles. Full-length PmCasp was confirmed to be an effector caspase by inducing apoptosis in transfected Sf-9 cells as assessed by DAPI staining. Using the same cell model, comparison of cells co-transfected with PmCasp and either WSSV134 or WSSV322 revealed that both of the binding proteins had anti-apoptotic activity. However, using the same Sf-9 protocol with anti-apoptosis protein-1 (AAP-1; also called WSSV449) previously shown to bind and inactivate a different effector caspase from P. monodon (Pm caspase) did not block apoptosis induced by PmCasp. The results revealed diversity in effector caspases and their viral protein inhibitors in P. monodon.

  20. Chromosomal location and comparative genomics analysis of powdery mildew resistance gene Pm51 in a putative wheat-Thinopyrum ponticum introgression line.

    PubMed

    Zhan, Haixian; Li, Guangrong; Zhang, Xiaojun; Li, Xin; Guo, Huijuan; Gong, Wenping; Jia, Juqing; Qiao, Linyi; Ren, Yongkang; Yang, Zujun; Chang, Zhijian

    2014-01-01

    Powdery mildew (PM) is a very destructive disease of wheat (Triticum aestivum L.). Wheat-Thinopyrum ponticum introgression line CH7086 was shown to possess powdery mildew resistance possibly originating from Th. ponticum. Genomic in situ hybridization and molecular characterization of the alien introgression failed to identify alien chromatin. To study the genetics of resistance, CH7086 was crossed with susceptible genotypes. Segregation in F2 populations and F2:3 lines tested with Chinese Bgt race E09 under controlled conditions indicated that CH7086 carries a single dominant gene for powdery mildew resistance. Fourteen SSR and EST-PCR markers linked with the locus were identified. The genetic distances between the locus and the two flanking markers were 1.5 and 3.2 cM, respectively. Based on the locations of the markers by nullisomic-tetrasomic and deletion lines of 'Chinese Spring', the resistance gene was located in deletion bin 2BL-0.89-1.00. Conserved orthologous marker analysis indicated that the genomic region flanking the resistance gene has a high level of collinearity to that of rice chromosome 4 and Brachypodium chromosome 5. Both resistance specificities and tests of allelism suggested the resistance gene in CH7086 was different from previously reported powdery mildew resistance genes on 2BL, and the gene was provisionally designated PmCH86. Molecular analysis of PmCH86 compared with other genes for resistance to Bgt in the 2BL-0.89-1.00 region suggested that PmCH86 may be a new PM resistance gene, and it was therefore designated as Pm51. The closely linked flanking markers could be useful in exploiting this putative wheat-Thinopyrum translocation line for rapid transfer of Pm51 to wheat breeding programs.

  1. The Potential to Machine Superconductors with Electrochemical Machining

    NASA Astrophysics Data System (ADS)

    Leese, Rebecca J.; Ivanov, Atanas; Babu-Nadendla, Hari

    2016-01-01

    Superconductors (SCs), such as gadolinium barium copper oxide, are brittle ceramics which are very difficult to machine conventionally due to the easy propagation of cracks. The cracks formed during conventional machining destroy the superconductive properties of the material. As a result a new method to machine ceramic SCs is needed. In this paper, polarization experiments were conducted in various nonaqueous salt electrolytes to determine whether electrochemical machining (ECM) is a suitable method for machining gadolinium barium copper oxide with silver inclusions (GdBCO-Ag) for the first time. Sodium chloride in formic acid proved to be the best electrolyte for this application with higher dissolution rates and achieving a better surface finish. It was noted that GdBCO-Ag dissolved at higher rates in NaCl in formic acid than in other salt-solvent systems.

  2. Machine performance assessment and enhancement for a hexapod machine

    SciTech Connect

    Mou, J.I.; King, C.

    1998-03-19

    The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

  3. Predictability Analysis of PM10 Concentrations in Budapest

    NASA Astrophysics Data System (ADS)

    Ferenczi, Zita

    2013-04-01

    Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

  4. Machining of uranium and uranium alloys

    SciTech Connect

    Morris, T.O.

    1981-12-14

    Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures.

  5. EVALUATION OF THE SMPS-APS SYSTEM AS A CONTINUOUS MONITOR FOR MEASURING PM2.5, PM10 AND COARSE (PM2.5-10) CONCENTRATIONS. (R827352C011)

    EPA Science Inventory

    Respirable particulate matter (PM) has been linked to mortality and morbidity by a variety of epidemiological studies. This research has led to the creation of a new PM standard for particles with diameters <2.5 μm (PM2.5). Since the conclusion of these studie...

  6. An experimental investigation on orthogonal cutting of hybrid CFRP/Ti stacks

    NASA Astrophysics Data System (ADS)

    Xu, Jinyang; El Mansori, Mohamed

    2016-10-01

    Hybrid CFRP/Ti stack has been widely used in the modern aerospace industry owing to its superior mechanical/physical properties and excellent structural functions. Several applications require mechanical machining of these hybrid composite stacks in order to achieve dimensional accuracy and assembly performance. However, machining of such composite-to-metal alliance is usually an extremely challenging task in the manufacturing sectors due to the disparate natures of each stacked constituent and their respective poor machinability. Special issues may arise from the high force/heat generation, severe subsurface damage and rapid tool wear. To study the fundamental mechanisms controlling the bi-material machining, this paper presented an experimental study on orthogonal cutting of hybrid CFRP/Ti stack by using superior polycrystalline diamond (PCD) tipped tools. The utilized cutting parameters for hybrid CFRP/Ti machining were rigorously adopted through a compromise selection due to the disparate machinability behaviors of the CFRP laminate and Ti alloy. The key cutting responses in terms of cutting force generation, machined surface quality and tool wear mechanism were precisely addressed. The experimental results highlighted the involved five stages of CFRP/Ti cutting and the predominant crater wear and edge fracture failure governing the PCD cutting process.

  7. Profile machining apparatus

    SciTech Connect

    Fisher, A. J.

    1985-02-26

    The disclosure relates to a profile forming apparatus and in particular a cam grinding machine in which a cam to be ground is mounted for rotation about the axis of the cam shaft in a work-table and a drive motor rotates the cam about its axis at a speed controlled by a predetermined programme. The work-table is mounted for rocking movement about an axis parallel to the cam shaft axis to move towards and away from the rotating grinding wheel which grinds cam surfaces spaced apart along the camshaft. The work-table is driven positively about its axis by a reversible drive motor in accordance with a further programme to rock the camshaft towards and away from the axis of the grinding wheel as the camshaft rotates and thereby determine the shape and dimensions of the profile to which the cam is ground.

  8. Quantum adiabatic machine learning

    NASA Astrophysics Data System (ADS)

    Pudenz, Kristen L.; Lidar, Daniel A.

    2013-05-01

    We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. This approach consists of two quantum phases, with some amount of classical preprocessing to set up the quantum problems. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the training and testing phases are executed via quantum adiabatic evolution. All quantum processing is strictly limited to two-qubit interactions so as to ensure physical feasibility. We apply and illustrate this approach in detail to the problem of software verification and validation, with a specific example of the learning phase applied to a problem of interest in flight control systems. Beyond this example, the algorithm can be used to attack a broad class of anomaly detection problems.

  9. Extremal quantum cloning machines

    SciTech Connect

    Chiribella, G.; D'Ariano, G. M.; Perinotti, P.; Cerf, N.J.

    2005-10-15

    We investigate the problem of cloning a set of states that is invariant under the action of an irreducible group representation. We then characterize the cloners that are extremal in the convex set of group covariant cloning machines, among which one can restrict the search for optimal cloners. For a set of states that is invariant under the discrete Weyl-Heisenberg group, we show that all extremal cloners can be unitarily realized using the so-called double-Bell states, whence providing a general proof of the popular ansatz used in the literature for finding optimal cloners in a variety of settings. Our result can also be generalized to continuous-variable optimal cloning in infinite dimensions, where the covariance group is the customary Weyl-Heisenberg group of displacement000.

  10. MEMS electrostatic influence machines

    NASA Astrophysics Data System (ADS)

    Phu Le, Cuong; Halvorsen, Einar

    2016-11-01

    This paper analyses the possibility of MEMS electrostatic influence machines using electromechanical switches like the historical predecessors did two centuries ago. We find that a generator design relying entirely on standard silicon-on-insulator(SOI) micromachining is conceivable and analyze its performance by simulations. The concept appears preferable over comparable diode circuits due to its higher maximum energy, faster charging and low precharging voltage. A full electromechanical lumped-model including parasitic capacitances of the switches is built to capture the dynamic of the generator. Simulation results show that the output voltage can be exponentially bootstrapped from a very low precharging voltage so that otherwise inadequately small voltage differences or charge imbalances can be made useful.

  11. Control of Two Permanent Magnet Machines Using a Five-Leg Inverter for Automotive Applications

    SciTech Connect

    Su, Gui-Jia; Tang, Lixin; Huang, Xianghui

    2006-01-01

    This paper presents digital control schemes for control of two permanent magnet (PM) machines in an integrated traction and air-conditioning compressor drive system for automotive applications. The integrated drive system employs a five-leg inverter to power a three-phase traction PM motor and a two-phase compressor PM motor by tying the common terminal of the two-phase motor to the neutral point of the three-phase motor. Compared to a three-phase or a standalone two-phase inverter, it eliminates one phase leg and shares the control electronics between the two drives, thus significantly reducing the component count of the compressor drive. To demonstrate that the speed and torque of the two PM motors can be controlled independently, a control strategy was implemented in a digital signal processor, which includes a rotor flux field orientation based control (RFOC) for the three-phase motor, a similar RFOC and a position sensorless control in the brushless dc (BLDC) mode for the two-phase motor. Control implementation issues unique to a two-phase PM motor are also discussed. Test results with the three-phase motor running in the ac synchronous (ACS) mode while the two-phase motor either in the ACS or the BLDC mode are included to verify the independent speed and torque control capability of the integrated drive.

  12. Anaesthesia Machine: Checklist, Hazards, Scavenging

    PubMed Central

    Goneppanavar, Umesh; Prabhu, Manjunath

    2013-01-01

    From a simple pneumatic device of the early 20th century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc.) more than 15 air changes/hour and total intravenous anaesthesia should also be considered. PMID:24249887

  13. Self-Adjusting Teaching Machines.

    ERIC Educational Resources Information Center

    Dovgyallo, A. M.

    A study was made on the synthesis of teaching machine elements to ensure the stabilization of the chi indicator of the teaching process of each student. At first, a procedure was developed for calculating the chi indicator for the case when the teaching machine predicts the magnitude of this indicator based on probabilities derived from an…

  14. Anaesthesia machine: checklist, hazards, scavenging.

    PubMed

    Goneppanavar, Umesh; Prabhu, Manjunath

    2013-09-01

    From a simple pneumatic device of the early 20(th) century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc.) more than 15 air changes/hour and total intravenous anaesthesia should also be considered.

  15. Two color machining of composites

    SciTech Connect

    Maher, W.

    1996-12-31

    Quality cutting and drilling of 9 composite materials is possible using diode-pumped neodymium lasers. Machining at 1.06 {mu}m is improved by optimizing the pulse format of the diode-pumped neodymium lasers of the Precision Laser Machining (PLM) Consortium. Further improvements are obtained with the PLM lasers operating at 0.53 {mu}m.

  16. The Blindstitch Machine. Module 11.

    ERIC Educational Resources Information Center

    South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

    This module on the purpose and use of the blindstitch machine, one in a series on clothing construction for industrial sewing machine operators designed for student self-study, contains three sections. Each section includes the following parts: an introduction, directions, an objective, learning activities, student information, student self-check,…

  17. Robotics: self-reproducing machines.

    PubMed

    Zykov, Victor; Mytilinaios, Efstathios; Adams, Bryant; Lipson, Hod

    2005-05-12

    Self-reproduction is central to biological life for long-term sustainability and evolutionary adaptation. Although these traits would also be desirable in many engineered systems, the principles of self-reproduction have not been exploited in machine design. Here we create simple machines that act as autonomous modular robots and are capable of physical self-reproduction using a set of cubes.

  18. Machine Trades Lab Management Guide.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Instructional Materials Lab.

    This manual was developed to guide machine trades instructors and vocational supervisors in sequencing laboratory instruction and controlling the flow of work for a 2-year machine trades training program. The first part of the guide provides information on program management (program description, safety concerns, academic issues, implementation…

  19. Machine Accounting. An Instructor's Guide.

    ERIC Educational Resources Information Center

    Gould, E. Noah, Ed.

    Designed to prepare students to operate the types of accounting machines used in many medium-sized businesses, this instructor's guide presents a full-year high school course in machine accounting covering 120 hours of instruction. An introduction for the instructor suggests how to adapt the guide to present a 60-hour module which would be…

  20. The Machine Scoring of Writing

    ERIC Educational Resources Information Center

    McCurry, Doug

    2010-01-01

    This article provides an introduction to the kind of computer software that is used to score student writing in some high stakes testing programs, and that is being promoted as a teaching and learning tool to schools. It sketches the state of play with machines for the scoring of writing, and describes how these machines work and what they do.…