Comparison and Analysis on Mechanical Property and Machinability about Polyetheretherketone and Carbon-Fibers Reinforced Polyetheretherketone

PubMed Central

Ji, Shijun; Sun, Changrui; Zhao, Ji; Liang, Fusheng

2015-01-01

The aim of this paper is to compare the mechanical property and machinability of Polyetheretherketone (PEEK) and 30 wt% carbon-fibers reinforced Polyetheretherketone (PEEK CF 30). The method of nano-indentation is used to investigate the microscopic mechanical property. The evolution of load with displacement, Young’s modulus curves and hardness curves are analyzed. The results illustrate that the load-displacement curves of PEEK present better uniformity, and the variation of Young’s modulus and hardness of PEEK both change smaller at the experimental depth. The machinability between PEEK and PEEK CF 30 are also compared by the method of single-point diamond turning (SPDT), and the peak-to-valley value (PV) and surface roughness (Ra) are obtained to evaluate machinability of the materials after machining. The machining results show that PEEK has smaller PV and Ra, which means PEEK has superior machinability. PMID:28793428

Comparison and Analysis on Mechanical Property and Machinability about Polyetheretherketone and Carbon-Fibers Reinforced Polyetheretherketone.

PubMed

Ji, Shijun; Sun, Changrui; Zhao, Ji; Liang, Fusheng

2015-07-07

The aim of this paper is to compare the mechanical property and machinability of Polyetheretherketone (PEEK) and 30 wt% carbon-fibers reinforced Polyetheretherketone (PEEK CF 30). The method of nano-indentation is used to investigate the microscopic mechanical property. The evolution of load with displacement, Young's modulus curves and hardness curves are analyzed. The results illustrate that the load-displacement curves of PEEK present better uniformity, and the variation of Young's modulus and hardness of PEEK both change smaller at the experimental depth. The machinability between PEEK and PEEK CF 30 are also compared by the method of single-point diamond turning (SPDT), and the peak-to-valley value (PV) and surface roughness (Ra) are obtained to evaluate machinability of the materials after machining. The machining results show that PEEK has smaller PV and Ra, which means PEEK has superior machinability.

Perspex machine: V. Compilation of C programs

NASA Astrophysics Data System (ADS)

Spanner, Matthew P.; Anderson, James A. D. W.

2006-01-01

The perspex machine arose from the unification of the Turing machine with projective geometry. The original, constructive proof used four special, perspective transformations to implement the Turing machine in projective geometry. These four transformations are now generalised and applied in a compiler, implemented in Pop11, that converts a subset of the C programming language into perspexes. This is interesting both from a geometrical and a computational point of view. Geometrically, it is interesting that program source can be converted automatically to a sequence of perspective transformations and conditional jumps, though we find that the product of homogeneous transformations with normalisation can be non-associative. Computationally, it is interesting that program source can be compiled for a Reduced Instruction Set Computer (RISC), the perspex machine, that is a Single Instruction, Zero Exception (SIZE) computer.

Diamond turning of glass

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

Blackley, W.S.; Scattergood, R.O.

A new research initiative will be undertaken to investigate the critical cutting depth concepts for single point diamond turning of brittle, amorphous materials. Inorganic glasses and a brittle, thermoset polymer (organic glass) are the principal candidate materials. Interrupted cutting tests similar to those done in earlier research are Ge and Si crystals will be made to obtain critical depth values as a function of machining parameters. The results will provide systematic data with which to assess machining performance on glasses and amorphous materials

Diamond turning of thermoplastic polymers

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

Smith, E.; Scattergood, R.O.

Single point diamond turning studies were made using a series of thermoplastic polymers with different glass transition temperatures. Variations in surface morphology and surface roughness were observed as a function of cutting speed. Lower glass transition temperatures facilitate smoother surface cuts and better surface finish. This can be attributed to the frictional heating that occurs during machining. Because of the very low glass transition temperatures in polymeric compared to inorganic glasses, the precision machining response can be very speed sensitive.

Single-point diamond crushing of Zerodur with in-situ polishing and metrology on a diamond turning machine

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

Bryan, J.B.; Carter, D.L.

1985-04-01

Large, complicated, aspherical optical elements of glass are presently used in many astronomical devices, both on land and in space. Grazing-incident mirrors are envisioned for use in such missions as the proposed Advanced X-Ray Astrophysical Facility (AXAF), the Far Ultraviolet Spectroscopic Explorer (FUSE), and others. These elements are very expensive to fabricate because a great deal of time and labor are required to shape a glass blank. The fabrication of these mirrors can best be achieved by applying precision machining techniques and precision machines for figuring and finishing low-expansion glasses such as Zerodur.

Wearable-Sensor-Based Classification Models of Faller Status in Older Adults.

PubMed

Howcroft, Jennifer; Lemaire, Edward D; Kofman, Jonathan

2016-01-01

Wearable sensors have potential for quantitative, gait-based, point-of-care fall risk assessment that can be easily and quickly implemented in clinical-care and older-adult living environments. This investigation generated models for wearable-sensor based fall-risk classification in older adults and identified the optimal sensor type, location, combination, and modelling method; for walking with and without a cognitive load task. A convenience sample of 100 older individuals (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m under single-task and dual-task conditions while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, and left and right shanks. Participants also completed the Activities-specific Balance Confidence scale, Community Health Activities Model Program for Seniors questionnaire, six minute walk test, and ranked their fear of falling. Fall risk classification models were assessed for all sensor combinations and three model types: multi-layer perceptron neural network, naïve Bayesian, and support vector machine. The best performing model was a multi-layer perceptron neural network with input parameters from pressure-sensing insoles and head, pelvis, and left shank accelerometers (accuracy = 84%, F1 score = 0.600, MCC score = 0.521). Head sensor-based models had the best performance of the single-sensor models for single-task gait assessment. Single-task gait assessment models outperformed models based on dual-task walking or clinical assessment data. Support vector machines and neural networks were the best modelling technique for fall risk classification. Fall risk classification models developed for point-of-care environments should be developed using support vector machines and neural networks, with a multi-sensor single-task gait assessment.

Noncontact on-machine measurement system based on capacitive displacement sensors for single-point diamond turning

NASA Astrophysics Data System (ADS)

Li, Xingchang; Zhang, Zhiyu; Hu, Haifei; Li, Yingjie; Xiong, Ling; Zhang, Xuejun; Yan, Jiwang

2018-04-01

On-machine measurements can improve the form accuracy of optical surfaces in single-point diamond turning applications; however, commercially available linear variable differential transformer sensors are inaccurate and can potentially scratch the surface. We present an on-machine measurement system based on capacitive displacement sensors for high-precision optical surfaces. In the proposed system, a position-trigger method of measurement was developed to ensure strict correspondence between the measurement points and the measurement data with no intervening time-delay. In addition, a double-sensor measurement was proposed to reduce the electric signal noise during spindle rotation. Using the proposed system, the repeatability of 80-nm peak-to-valley (PV) and 8-nm root-mean-square (RMS) was achieved through analyzing four successive measurement results. The accuracy of 109-nm PV and 14-nm RMS was obtained by comparing with the interferometer measurement result. An aluminum spherical mirror with a diameter of 300 mm was fabricated, and the resulting measured form error after one compensation cut was decreased to 254 nm in PV and 52 nm in RMS. These results confirm that the measurements of the surface form errors were successfully used to modify the cutting tool path during the compensation cut, thereby ensuring that the diamond turning process was more deterministic. In addition, the results show that the noise level was significantly reduced with the reference sensor even under a high rotational speed.

Aspects of ultra-high-precision diamond machining of RSA 443 optical aluminium

NASA Astrophysics Data System (ADS)

Mkoko, Z.; Abou-El-Hossein, K.

2015-08-01

Optical aluminium alloys such as 6061-T6 are traditionally used in ultra-high precision manufacturing for making optical mirrors for aerospace and other applications. However, the optics industry has recently witnessed the development of more advanced optical aluminium grades that are capable of addressing some of the issues encountered when turning with single-point natural monocrystalline diamond cutters. The advent of rapidly solidified aluminium (RSA) grades has generally opened up new possibilities for ultra-high precision manufacturing of optical components. In this study, experiments were conducted with single-point diamond cutters on rapidly solidified aluminium RSA 443 material. The objective of this study is to observe the effects of depth of cut and feed rate at a fixed rotational speed on the tool wear rate and resulting surface roughness of diamond turned specimens. This is done to gain further understanding of the rate of wear on the diamond cutters versus the surface texture generated on the RSA 443 material. The diamond machining experiments yielded machined surfaces which are less reflective but with consistent surface roughness values. Cutting tools were observed for wear through scanning microscopy; relatively low wear pattern was evident on the diamond tool edge. The highest tool wear were obtained at higher depth of cut and increased feed rate.

Micro-optical fabrication by ultraprecision diamond machining and precision molding

NASA Astrophysics Data System (ADS)

Li, Hui; Li, Likai; Naples, Neil J.; Roblee, Jeffrey W.; Yi, Allen Y.

2017-06-01

Ultraprecision diamond machining and high volume molding for affordable high precision high performance optical elements are becoming a viable process in optical industry for low cost high quality microoptical component manufacturing. In this process, first high precision microoptical molds are fabricated using ultraprecision single point diamond machining followed by high volume production methods such as compression or injection molding. In the last two decades, there have been steady improvements in ultraprecision machine design and performance, particularly with the introduction of both slow tool and fast tool servo. Today optical molds, including freeform surfaces and microlens arrays, are routinely diamond machined to final finish without post machining polishing. For consumers, compression molding or injection molding provide efficient and high quality optics at extremely low cost. In this paper, first ultraprecision machine design and machining processes such as slow tool and fast too servo are described then both compression molding and injection molding of polymer optics are discussed. To implement precision optical manufacturing by molding, numerical modeling can be included in the future as a critical part of the manufacturing process to ensure high product quality.

Energy landscapes for a machine learning application to series data

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

Ballard, Andrew J.; Stevenson, Jacob D.; Das, Ritankar

2016-03-28

Methods developed to explore and characterise potential energy landscapes are applied to the corresponding landscapes obtained from optimisation of a cost function in machine learning. We consider neural network predictions for the outcome of local geometry optimisation in a triatomic cluster, where four distinct local minima exist. The accuracy of the predictions is compared for fits using data from single and multiple points in the series of atomic configurations resulting from local geometry optimisation and for alternative neural networks. The machine learning solution landscapes are visualised using disconnectivity graphs, and signatures in the effective heat capacity are analysed in termsmore » of distributions of local minima and their properties.« less

Testing single point incremental forming molds for thermoforming operations

NASA Astrophysics Data System (ADS)

Afonso, Daniel; de Sousa, Ricardo Alves; Torcato, Ricardo

2016-10-01

Low pressure polymer processing processes as thermoforming or rotational molding use much simpler molds then high pressure processes like injection. However, despite the low forces involved with the process, molds manufacturing for this operations is still a very material, energy and time consuming operation. The goal of the research is to develop and validate a method for manufacturing plastically formed sheets metal molds by single point incremental forming (SPIF) operation for thermoforming operation. Stewart platform based SPIF machines allow the forming of thick metal sheets, granting the required structural stiffness for the mold surface, and keeping the short lead time manufacture and low thermal inertia.

Assessment of New Load Schedules for the Machine Calibration of a Force Balance

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Gisler, R.; Kew, R.

2015-01-01

New load schedules for the machine calibration of a six-component force balance are currently being developed and evaluated at the NASA Ames Balance Calibration Laboratory. One of the proposed load schedules is discussed in the paper. It has a total of 2082 points that are distributed across 16 load series. Several criteria were applied to define the load schedule. It was decided, for example, to specify the calibration load set in force balance format as this approach greatly simplifies the definition of the lower and upper bounds of the load schedule. In addition, all loads are assumed to be applied in a calibration machine by using the one-factor-at-a-time approach. At first, all single-component loads are applied in six load series. Then, three two-component load series are applied. They consist of the load pairs (N1, N2), (S1, S2), and (RM, AF). Afterwards, four three-component load series are applied. They consist of the combinations (N1, N2, AF), (S1, S2, AF), (N1, N2, RM), and (S1, S2, RM). In the next step, one four-component load series is applied. It is the load combination (N1, N2, S1, S2). Finally, two five-component load series are applied. They are the load combination (N1, N2, S1, S2, AF) and (N1, N2, S1, S2, RM). The maximum difference between loads of two subsequent data points of the load schedule is limited to 33 % of capacity. This constraint helps avoid unwanted load "jumps" in the load schedule that can have a negative impact on the performance of a calibration machine. Only loadings of the single- and two-component load series are loaded to 100 % of capacity. This approach was selected because it keeps the total number of calibration points to a reasonable limit while still allowing for the application of some of the more complex load combinations. Data from two of NASA's force balances is used to illustrate important characteristics of the proposed 2082-point calibration load schedule.

Preconditioned implicit solvers for the Navier-Stokes equations on distributed-memory machines

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Liou, Meng-Sing; Dyson, Rodger W.

1994-01-01

The GMRES method is parallelized, and combined with local preconditioning to construct an implicit parallel solver to obtain steady-state solutions for the Navier-Stokes equations of fluid flow on distributed-memory machines. The new implicit parallel solver is designed to preserve the convergence rate of the equivalent 'serial' solver. A static domain-decomposition is used to partition the computational domain amongst the available processing nodes of the parallel machine. The SPMD (Single-Program Multiple-Data) programming model is combined with message-passing tools to develop the parallel code on a 32-node Intel Hypercube and a 512-node Intel Delta machine. The implicit parallel solver is validated for internal and external flow problems, and is found to compare identically with flow solutions obtained on a Cray Y-MP/8. A peak computational speed of 2300 MFlops/sec has been achieved on 512 nodes of the Intel Delta machine,k for a problem size of 1024 K equations (256 K grid points).

Finite element computation on nearest neighbor connected machines

NASA Technical Reports Server (NTRS)

Mcaulay, A. D.

1984-01-01

Research aimed at faster, more cost effective parallel machines and algorithms for improving designer productivity with finite element computations is discussed. A set of 8 boards, containing 4 nearest neighbor connected arrays of commercially available floating point chips and substantial memory, are inserted into a commercially available machine. One-tenth Mflop (64 bit operation) processors provide an 89% efficiency when solving the equations arising in a finite element problem for a single variable regular grid of size 40 by 40 by 40. This is approximately 15 to 20 times faster than a much more expensive machine such as a VAX 11/780 used in double precision. The efficiency falls off as faster or more processors are envisaged because communication times become dominant. A novel successive overrelaxation algorithm which uses cyclic reduction in order to permit data transfer and computation to overlap in time is proposed.

Position uncertainty distribution for articulated arm coordinate measuring machine based on simplified definite integration

NASA Astrophysics Data System (ADS)

You, Xu; Zhi-jian, Zong; Qun, Gao

2018-07-01

This paper describes a methodology for the position uncertainty distribution of an articulated arm coordinate measuring machine (AACMM). First, a model of the structural parameter uncertainties was established by statistical method. Second, the position uncertainty space volume of the AACMM in a certain configuration was expressed using a simplified definite integration method based on the structural parameter uncertainties; it was then used to evaluate the position accuracy of the AACMM in a certain configuration. Third, the configurations of a certain working point were calculated by an inverse solution, and the position uncertainty distribution of a certain working point was determined; working point uncertainty can be evaluated by the weighting method. Lastly, the position uncertainty distribution in the workspace of the ACCMM was described by a map. A single-point contrast test of a 6-joint AACMM was carried out to verify the effectiveness of the proposed method, and it was shown that the method can describe the position uncertainty of the AACMM and it was used to guide the calibration of the AACMM and the choice of AACMM’s accuracy area.

Examining Effects of Virtual Machine Settings on Voice over Internet Protocol in a Private Cloud Environment

ERIC Educational Resources Information Center

Liao, Yuan

2011-01-01

The virtualization of computing resources, as represented by the sustained growth of cloud computing, continues to thrive. Information Technology departments are building their private clouds due to the perception of significant cost savings by managing all physical computing resources from a single point and assigning them to applications or…

Rapid fabrication of miniature lens arrays by four-axis single point diamond machining

PubMed Central

McCall, Brian; Tkaczyk, Tomasz S.

2013-01-01

A novel method for fabricating lens arrays and other non-rotationally symmetric free-form optics is presented. This is a diamond machining technique using 4 controlled axes of motion – X, Y, Z, and C. As in 3-axis diamond micro-milling, a diamond ball endmill is mounted to the work spindle of a 4-axis ultra-precision computer numerical control (CNC) machine. Unlike 3-axis micro-milling, the C-axis is used to hold the cutting edge of the tool in contact with the lens surface for the entire cut. This allows the feed rates to be doubled compared to the current state of the art of micro-milling while producing an optically smooth surface with very low surface form error and exceptionally low radius error. PMID:23481813

AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

PubMed

Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

2016-10-01

We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.

Diamond Turning Of Infra-Red Components

NASA Astrophysics Data System (ADS)

Hodgson, B.; Lettington, A. H.; Stillwell, P. F. T. C.

1986-05-01

Single point diamond machining of infra-red optical components such as aluminium mirrors, germanium lenses and zinc sulphide domes is potentially the most cost effective method for their manufacture since components may be machined from the blanks to a high surface finish, requiring no subsequent polishing, in a few minutes. Machines for the production of flat surfaces are well established. Diamond turning lathes for curved surfaces however require a high capital investment which can be justified only for research purposes or high volume production. The present paper describes the development of a low cost production machine based on a Bryant Symons diamond turning lathe which is able to machine spherical components to the required form and finish. It employs two horizontal spindles one for the workpiece the other for the tool. The machined radius of curvature is set by the alignment of the axes and the radius of the tool motion, as in conventional generation. The diamond tool is always normal to the workpiece and does not need to be accurately profiled. There are two variants of this basic machine. For machining hemispherical domes the axes are at right angles while for lenses with positive or negative curvature these axes are adjustable. An aspherical machine is under development, based on the all mechanical spherical machine, but in which a ± 2 mm aspherecity may be imposed on the best fit sphere by moving the work spindle under numerical control.

Interconnect Performance Evaluation of SGI Altix 3700 BX2, Cray X1, Cray Opteron Cluster, and Dell PowerEdge

NASA Technical Reports Server (NTRS)

Fatoohi, Rod; Saini, Subbash; Ciotti, Robert

2006-01-01

We study the performance of inter-process communication on four high-speed multiprocessor systems using a set of communication benchmarks. The goal is to identify certain limiting factors and bottlenecks with the interconnect of these systems as well as to compare these interconnects. We measured network bandwidth using different number of communicating processors and communication patterns, such as point-to-point communication, collective communication, and dense communication patterns. The four platforms are: a 512-processor SGI Altix 3700 BX2 shared-memory machine with 3.2 GB/s links; a 64-processor (single-streaming) Cray XI shared-memory machine with 32 1.6 GB/s links; a 128-processor Cray Opteron cluster using a Myrinet network; and a 1280-node Dell PowerEdge cluster with an InfiniBand network. Our, results show the impact of the network bandwidth and topology on the overall performance of each interconnect.

Design of a Modular E-Core Flux Concentrating Axial Flux Machine: Preprint

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

Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal

2015-08-24

In this paper a novel E-Core axial flux machine is proposed. The machine has a double-stator, single-rotor configuration with flux-concentrating ferrite magnets and pole windings across each leg of an E-Core stator. E-Core stators with the proposed flux-concentrating rotor arrangement result in better magnet utilization and higher torque density. The machine also has a modular structure facilitating simpler construction. This paper presents a single-phase and a three-phase version of the E-Core machine. Case studies for a 1.1-kW, 400-rpm machine for both the single-phase and three-phase axial flux machines are presented. The results are verified through 3D finite element analysis. facilitatingmore » simpler construction. This paper presents a single-phase and a three-phase version of the E-Core machine. Case studies for a 1.1-kW, 400-rpm machine for both the single-phase and three-phase axial flux machines are presented. The results are verified through 3D finite element analysis.« less

Single event effects in high-energy accelerators

NASA Astrophysics Data System (ADS)

García Alía, Rubén; Brugger, Markus; Danzeca, Salvatore; Cerutti, Francesco; de Carvalho Saraiva, Joao Pedro; Denz, Reiner; Ferrari, Alfredo; Foro, Lionel L.; Peronnard, Paul; Røed, Ketil; Secondo, Raffaello; Steckert, Jens; Thurel, Yves; Toccafondo, Iacocpo; Uznanski, Slawosz

2017-03-01

The radiation environment encountered at high-energy hadron accelerators strongly differs from the environment relevant for space applications. The mixed-field expected at modern accelerators is composed of charged and neutral hadrons (protons, pions, kaons and neutrons), photons, electrons, positrons and muons, ranging from very low (thermal) energies up to the TeV range. This complex field, which is extensively simulated by Monte Carlo codes (e.g. FLUKA) is due to beam losses in the experimental areas, distributed along the machine (e.g. collimation points) and deriving from the interaction with the residual gas inside the beam pipe. The resulting intensity, energy distribution and proportion of the different particles largely depends on the distance and angle with respect to the interaction point as well as the amount of installed shielding material. Electronics operating in the vicinity of the accelerator will therefore be subject to both cumulative damage from radiation (total ionizing dose, displacement damage) as well as single event effects which can seriously compromise the operation of the machine. This, combined with the extensive use of commercial-off-the-shelf components due to budget, performance and availability reasons, results in the need to carefully characterize the response of the devices and systems to representative radiation conditions.

Predictive optimized adaptive PSS in a single machine infinite bus.

PubMed

Milla, Freddy; Duarte-Mermoud, Manuel A

2016-07-01

Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Development of plasma chemical vaporization machining

NASA Astrophysics Data System (ADS)

Mori, Yuzo; Yamauchi, Kazuto; Yamamura, Kazuya; Sano, Yasuhisa

2000-12-01

Conventional machining processes, such as turning, grinding, or lapping are still applied for many materials including functional ones. But those processes are accompanied with the formation of a deformed layer, so that machined surfaces cannot perform their original functions. In order to avoid such points, plasma chemical vaporization machining (CVM) has been developed. Plasma CVM is a chemical machining method using neutral radicals, which are generated by the atmospheric pressure plasma. By using a rotary electrode for generation of plasma, a high density of neutral radicals was formed, and we succeeded in obtaining high removal rate of several microns to several hundred microns per minute for various functional materials such as fused silica, single crystal silicon, molybdenum, tungsten, silicon carbide, and diamond. Especially, a high removal rate equal to lapping in the mechanical machining of fused silica and silicon was realized. 1.4 nm (p-v) was obtained as a surface roughness in the case of machining a silicon wafer. The defect density of a silicon wafer surface polished by various machining method was evaluated by the surface photo voltage spectroscopy. As a result, the defect density of the surface machined by plasma CVM was under 1/100 in comparison with the surface machined by mechanical polishing and argon ion sputtering, and very low defect density which was equivalent to the chemical etched surface was realized. A numerically controlled CVM machine for x-ray mirror fabrication is detailed in the accompanying article in this issue.

Computational Model for Impact-Resisting Critical Thickness of High-Speed Machine Outer Protective Plate

NASA Astrophysics Data System (ADS)

Wu, Huaying; Wang, Li Zhong; Wang, Yantao; Yuan, Xiaolei

2018-05-01

The blade or surface grinding blade of the hypervelocity grinding wheel may be damaged due to too high rotation rate of the spindle of the machine and then fly out. Its speed as a projectile may severely endanger the field persons. Critical thickness model of the protective plate of the high-speed machine is studied in this paper. For easy analysis, the shapes of the possible impact objects flying from the high-speed machine are simplified as sharp-nose model, ball-nose model and flat-nose model. Whose front ending shape to represent point, line and surface contacting. Impact analysis based on J-C model is performed for the low-carbon steel plate with different thicknesses in this paper. One critical thickness computational model for the protective plate of high-speed machine is established according to the damage characteristics of the thin plate to get relation among plate thickness and mass, shape and size and impact speed of impact object. The air cannon is used for impact test. The model accuracy is validated. This model can guide identification of the thickness of single-layer outer protective plate of a high-speed machine.

Design and Construction Multi Output Power Transmition with Single Prime Mover on Agricultural Products Machine

NASA Astrophysics Data System (ADS)

Koten, V. K.; Tanamal, C. E.

2017-03-01

Manufacturing agricultural products by the farmers, people or person who involve in medium industry, small industry, and households industry still be done in separately. Although the power on primemover is enough, in operations, primemover was only to move one of several agricultural products machine. This study attempts to design and construct power transmition multi output with single primemover; a single construction that allows primemover move some agricultur products machine in the same or not. This study begins with the determination of production capacity and the power to destroy products, the determination of resources and rotation, normalization of resources and rotation, the determination of the type material used, the size determination of each machine elements, construction machine elements, and assemble machine elements into a construction multi output power transmition with single primemover on agricultural products machine. The results show that with a input normalization 4 PK (2984 Watt), rotation 2000 rpm, the strength of material 60 kg/mm2, and several operating consideration, thus obtained size of machine elements through calculation. Based on the size, the machine elements is made through the use of some machine tools and assembled to form a multi output power transmition with single primemover.

A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

NASA Astrophysics Data System (ADS)

Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

2018-05-01

A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the efficiency of the method.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

NASA Astrophysics Data System (ADS)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

Experimental and numerical study on optimization of the single point incremental forming of AINSI 304L stainless steel sheet

NASA Astrophysics Data System (ADS)

Saidi, B.; Giraud-Moreau, L.; Cherouat, A.; Nasri, R.

2017-09-01

AINSI 304L stainless steel sheets are commonly formed into a variety of shapes for applications in the industrial, architectural, transportation and automobile fields, it’s also used for manufacturing of denture base. In the field of dentistry, there is a need for personalized devises that are custom made for the patient. The single point incremental forming process is highly promising in this area for manufacturing of denture base. The single point incremental forming process (ISF) is an emerging process based on the use of a spherical tool, which is moved along CNC controlled tool path. One of the major advantages of this process is the ability to program several punch trajectories on the same machine in order to obtain different shapes. Several applications of this process exist in the medical field for the manufacturing of personalized titanium prosthesis (cranial plate, knee prosthesis...) due to the need of product customization to each patient. The objective of this paper is to study the incremental forming of AISI 304L stainless steel sheets for future applications in the dentistry field. During the incremental forming process, considerable forces can occur. The control of the forming force is particularly important to ensure the safe use of the CNC milling machine and preserve the tooling and machinery. In this paper, the effect of four different process parameters on the maximum force is studied. The proposed approach consists in using an experimental design based on experimental results. An analysis of variance was conducted with ANOVA to find the input parameters allowing to minimize the maximum forming force. A numerical simulation of the incremental forming process is performed with the optimal input process parameters. Numerical results are compared with the experimental ones.

Single molecule detection, thermal fluctuation and life

PubMed Central

YANAGIDA, Toshio; ISHII, Yoshiharu

2017-01-01

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines. PMID:28190869

Automated apparatus and method of generating native code for a stitching machine

NASA Technical Reports Server (NTRS)

Miller, Jeffrey L. (Inventor)

2000-01-01

A computer system automatically generates CNC code for a stitching machine. The computer determines the locations of a present stitching point and a next stitching point. If a constraint is not found between the present stitching point and the next stitching point, the computer generates code for making a stitch at the next stitching point. If a constraint is found, the computer generates code for changing a condition (e.g., direction) of the stitching machine's stitching head.

Acceleration of saddle-point searches with machine learning.

PubMed

Peterson, Andrew A

2016-08-21

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

Acceleration of saddle-point searches with machine learning

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

Peterson, Andrew A., E-mail: andrew-peterson@brown.edu

In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the numbermore » of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.« less

New Single Piece Blast Hardware design

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

Ulrich, Andri; Steinzig, Michael Louis; Aragon, Daniel Adrian

W, Q and PF engineers and machinists designed and fabricated, on the new Mazak i300, the first Single Piece Blast Hardware (unclassified design shown) reducing fabrication and inspection time by over 50%. The first DU Single Piece is completed and will be used for Hydro Test 3680. Past hydro tests used a twopiece assembly due to a lack of equipment capable of machining the complex saddle shape in a single piece. The i300 provides turning and milling 5-axis machining on one machine. The milling head on the i300 can machine past 90 relative to the spindle axis. This makes itmore » possible to machine the complex saddle surface on a single piece. Going to a single piece eliminates tolerance problems, such as tilting and eccentricity, that typically occurred when assembling the two pieces together« less

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

NASA Astrophysics Data System (ADS)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

FEATURE B. MACHINE GUN POSITION WITH LEWIS MOUNT, VIEW FACING ...

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

FEATURE B. MACHINE GUN POSITION WITH LEWIS MOUNT, VIEW FACING NORTHWEST. - Naval Air Station Barbers Point, Battery-Machine Gun Positions, South of Point Cruz Road & west of Coral Sea Road, Ewa, Honolulu County, HI

QCDOC: A 10-teraflops scale computer for lattice QCD

NASA Astrophysics Data System (ADS)

Chen, D.; Christ, N. H.; Cristian, C.; Dong, Z.; Gara, A.; Garg, K.; Joo, B.; Kim, C.; Levkova, L.; Liao, X.; Mawhinney, R. D.; Ohta, S.; Wettig, T.

2001-03-01

The architecture of a new class of computers, optimized for lattice QCD calculations, is described. An individual node is based on a single integrated circuit containing a PowerPC 32-bit integer processor with a 1 Gflops 64-bit IEEE floating point unit, 4 Mbyte of memory, 8 Gbit/sec nearest-neighbor communications and additional control and diagnostic circuitry. The machine's name, QCDOC, derives from "QCD On a Chip".

The Improvement of the Closed Bounded Volume (CBV) Evaluation Methods to Compute a Feasible Rough Machining Area Based on Faceted Models

NASA Astrophysics Data System (ADS)

Hadi Sutrisno, Himawan; Kiswanto, Gandjar; Istiyanto, Jos

2017-06-01

The rough machining is aimed at shaping a workpiece towards to its final form. This process takes up a big proportion of the machining time due to the removal of the bulk material which may affect the total machining time. In certain models, the rough machining has limitations especially on certain surfaces such as turbine blade and impeller. CBV evaluation is one of the concepts which is used to detect of areas admissible in the process of machining. While in the previous research, CBV area detection used a pair of normal vectors, in this research, the writer simplified the process to detect CBV area with a slicing line for each point cloud formed. The simulation resulted in three steps used for this method and they are: 1. Triangulation from CAD design models, 2. Development of CC point from the point cloud, 3. The slicing line method which is used to evaluate each point cloud position (under CBV and outer CBV). The result of this evaluation method can be used as a tool for orientation set-up on each CC point position of feasible areas in rough machining.

FEATURE C. MACHINE GUN POSITION WITH REMNANT OF MOUNT, VIEW ...

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

FEATURE C. MACHINE GUN POSITION WITH REMNANT OF MOUNT, VIEW FACING SOUTH-SOUTHEAST. - Naval Air Station Barbers Point, Battery-Machine Gun Positions, South of Point Cruz Road & west of Coral Sea Road, Ewa, Honolulu County, HI

FEATURE B. MACHINE GUN POSITION WITH LEWIS MOUNT, VIEW FACING ...

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

FEATURE B. MACHINE GUN POSITION WITH LEWIS MOUNT, VIEW FACING NORTHWEST (with scale stick). - Naval Air Station Barbers Point, Battery-Machine Gun Positions, South of Point Cruz Road & west of Coral Sea Road, Ewa, Honolulu County, HI

Free-form machining for micro-imaging systems

NASA Astrophysics Data System (ADS)

Barkman, Michael L.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

2008-02-01

While mechanical ruling and single point diamond turning has been a mainstay of optical fabrication for many years, many types of micro-optical devices and structures are not conducive to simple diamond turning or ruling, such as, for example, microlens arrays, and optical surfaces with non-radial symmetry. More recent developments in machining technology have enabled significant expansion of fabrication capabilities. Modern machine tools can generate complex three-dimensional structures with optical quality surface finish, and fabricate structures across a dynamic range of dimensions not achievable with lithographic techniques. In particular, five-axis free-form micromachining offers a great deal of promise for realization of essentially arbitrary surface structures, including surfaces not realizable through binary or analog lithographic techniques. Furthermore, these machines can generate geometric features with optical finish on scales ranging from centimeters to micrometers with accuracies of 10s of nanometers. In this paper, we discuss techniques and applications of free-form surface machining of micro-optical elements. Aspects of diamond machine tool design to realize desired surface geometries in specific materials are discussed. Examples are presented, including fabrication of aspheric lens arrays in germanium for compact infrared imaging systems. Using special custom kinematic mounting equipment and the additional axes of the machine, the lenses were turned with surface finish better than 2 nm RMS and center to center positioning accuracy of +/-0.5 μm.

Design of a Modular E-Core Flux Concentrating Axial Flux Machine

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

Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal

2015-09-02

In this paper a novel E-Core axial flux machine is proposed. The machine has a double stator-single rotor configuration with flux concentrating ferrite magnets, and pole windings across each leg of an E-Core stator. E-Core stators with the proposed flux-concentrating rotor arrangement result in better magnet utilization and higher torque density. The machine also has a modular structure facilitating simpler construction. This paper presents a single phase and a three-phase version of the E-Core machine. Case study for a 1.1 kW, 400 rpm machine for both the single phase and three-phase axial flux machine is presented. The results are verifiedmore » through 3D finite element analysis.« less

Performance evaluation of various classifiers for color prediction of rice paddy plant leaf

NASA Astrophysics Data System (ADS)

Singh, Amandeep; Singh, Maninder Lal

2016-11-01

The food industry is one of the industries that uses machine vision for a nondestructive quality evaluation of the produce. These quality measuring systems and softwares are precalculated on the basis of various image-processing algorithms which generally use a particular type of classifier. These classifiers play a vital role in making the algorithms so intelligent that it can contribute its best while performing the said quality evaluations by translating the human perception into machine vision and hence machine learning. The crop of interest is rice, and the color of this crop indicates the health status of the plant. An enormous number of classifiers are available to solve the purpose of color prediction, but choosing the best among them is the focus of this paper. Performance of a total of 60 classifiers has been analyzed from the application point of view, and the results have been discussed. The motivation comes from the idea of providing a set of classifiers with excellent performance and implementing them on a single algorithm for the improvement of machine vision learning and, hence, associated applications.

The study on the nanomachining property and cutting model of single-crystal sapphire by atomic force microscopy.

PubMed

Huang, Jen-Ching; Weng, Yung-Jin

2014-01-01

This study focused on the nanomachining property and cutting model of single-crystal sapphire during nanomachining. The coated diamond probe is used to as a tool, and the atomic force microscopy (AFM) is as an experimental platform for nanomachining. To understand the effect of normal force on single-crystal sapphire machining, this study tested nano-line machining and nano-rectangular pattern machining at different normal force. In nano-line machining test, the experimental results showed that the normal force increased, the groove depth from nano-line machining also increased. And the trend is logarithmic type. In nano-rectangular pattern machining test, it is found when the normal force increases, the groove depth also increased, but rather the accumulation of small chips. This paper combined the blew by air blower, the cleaning by ultrasonic cleaning machine and using contact mode probe to scan the surface topology after nanomaching, and proposed the "criterion of nanomachining cutting model," in order to determine the cutting model of single-crystal sapphire in the nanomachining is ductile regime cutting model or brittle regime cutting model. After analysis, the single-crystal sapphire substrate is processed in small normal force during nano-linear machining; its cutting modes are ductile regime cutting model. In the nano-rectangular pattern machining, due to the impact of machined zones overlap, the cutting mode is converted into a brittle regime cutting model. © 2014 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls

PubMed Central

Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

PubMed

Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.

Laser Induced Damage of Potassium Dihydrogen Phosphate (KDP) Optical Crystal Machined by Water Dissolution Ultra-Precision Polishing Method

PubMed Central

Gao, Hang; Wang, Xu; Guo, Dongming; Liu, Ziyuan

2018-01-01

Laser induced damage threshold (LIDT) is an important optical indicator for nonlinear Potassium Dihydrogen Phosphate (KDP) crystal used in high power laser systems. In this study, KDP optical crystals are initially machined with single point diamond turning (SPDT), followed by water dissolution ultra-precision polishing (WDUP) and then tested with 355 nm nanosecond pulsed-lasers. Power spectral density (PSD) analysis shows that WDUP process eliminates the laser-detrimental spatial frequencies band of micro-waviness on SPDT machined surface and consequently decreases its modulation effect on the laser beams. The laser test results show that LIDT of WDUP machined crystal improves and its stability has a significant increase by 72.1% compared with that of SPDT. Moreover, a subsequent ultrasonic assisted solvent cleaning process is suggested to have a positive effect on the laser performance of machined KDP crystal. Damage crater investigation indicates that the damage morphologies exhibit highly thermal explosion features of melted cores and brittle fractures of periphery material, which can be described with the classic thermal explosion model. The comparison result demonstrates that damage mechanisms for SPDT and WDUP machined crystal are the same and WDUP process reveals the real bulk laser resistance of KDP optical crystal by removing the micro-waviness and subsurface damage on SPDT machined surface. This improvement of WDUP method makes the LIDT more accurate and will be beneficial to the laser performance of KDP crystal. PMID:29534032

Testing single point incremental forming moulds for rotomoulding operations

NASA Astrophysics Data System (ADS)

Afonso, Daniel; de Sousa, Ricardo Alves; Torcato, Ricardo

2017-10-01

Low pressure polymer processes as thermoforming or rotational moulding use much simpler moulds than high pressure processes like injection. However, despite the low forces involved in the process, moulds manufacturing for these applications is still a very material, energy and time consuming operation. Particularly in rotational moulding there is no standard for the mould manufacture and very different techniques are applicable. The goal of this research is to develop and validate a method for manufacturing plastically formed sheet metal moulds by single point incremental forming (SPIF) for rotomoulding and rotocasting operations. A Stewart platform based SPIF machine allow the forming of thick metal sheets, granting the required structural stiffness for the mould surface, and keeping a short manufacture lead time and low thermal inertia. The experimental work involves the proposal of a hollow part, design and fabrication of a sheet metal mould using dieless incremental forming techniques and testing its operation in the production of prototype parts.

Identification of bearing faults using time domain zero-crossings

NASA Astrophysics Data System (ADS)

William, P. E.; Hoffman, M. W.

2011-11-01

In this paper, zero-crossing characteristic features are employed for early detection and identification of single point bearing defects in rotating machinery. As a result of bearing defects, characteristic defect frequencies appear in the machine vibration signal, normally requiring spectral analysis or envelope analysis to identify the defect type. Zero-crossing features are extracted directly from the time domain vibration signal using only the duration between successive zero-crossing intervals and do not require estimation of the rotational frequency. The features are a time domain representation of the composite vibration signature in the spectral domain. Features are normalized by the length of the observation window and classification is performed using a multilayer feedforward neural network. The model was evaluated on vibration data recorded using an accelerometer mounted on an induction motor housing subjected to a number of single point defects with different severity levels.

Program Converts VAX Floating-Point Data To UNIX

NASA Technical Reports Server (NTRS)

Alves, Marcos; Chapman, Bruce; Chu, Eugene

1996-01-01

VAX Floating Point to Host Floating Point Conversion (VAXFC) software converts non-ASCII files to unformatted floating-point representation of UNIX machine. This is done by reading bytes bit by bit, converting them to floating-point numbers, then writing results to another file. Useful when data files created by VAX computer must be used on other machines. Written in C language.

40 CFR 433.10 - Applicability; description of the metal finishing point source category.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Descaling, Solvent Degreasing, Paint Stripping, Painting, Electrostatic Painting, Electropainting, Vacuum..., Electrochemical Machining, Electron Beam Machining, Laser Beam Machining, Plasma Arc Machining, Ultrasonic...

40 CFR 433.10 - Applicability; description of the metal finishing point source category.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Descaling, Solvent Degreasing, Paint Stripping, Painting, Electrostatic Painting, Electropainting, Vacuum..., Electrochemical Machining, Electron Beam Machining, Laser Beam Machining, Plasma Arc Machining, Ultrasonic...

40 CFR 433.10 - Applicability; description of the metal finishing point source category.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Descaling, Solvent Degreasing, Paint Stripping, Painting, Electrostatic Painting, Electropainting, Vacuum..., Electrochemical Machining, Electron Beam Machining, Laser Beam Machining, Plasma Arc Machining, Ultrasonic...

40 CFR 433.10 - Applicability; description of the metal finishing point source category.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Descaling, Solvent Degreasing, Paint Stripping, Painting, Electrostatic Painting, Electropainting, Vacuum..., Electrochemical Machining, Electron Beam Machining, Laser Beam Machining, Plasma Arc Machining, Ultrasonic...

40 CFR 433.10 - Applicability; description of the metal finishing point source category.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Descaling, Solvent Degreasing, Paint Stripping, Painting, Electrostatic Painting, Electropainting, Vacuum..., Electrochemical Machining, Electron Beam Machining, Laser Beam Machining, Plasma Arc Machining, Ultrasonic...

Parallel Processing of Big Point Clouds Using Z-Order Partitioning

NASA Astrophysics Data System (ADS)

Alis, C.; Boehm, J.; Liu, K.

2016-06-01

As laser scanning technology improves and costs are coming down, the amount of point cloud data being generated can be prohibitively difficult and expensive to process on a single machine. This data explosion is not only limited to point cloud data. Voluminous amounts of high-dimensionality and quickly accumulating data, collectively known as Big Data, such as those generated by social media, Internet of Things devices and commercial transactions, are becoming more prevalent as well. New computing paradigms and frameworks are being developed to efficiently handle the processing of Big Data, many of which utilize a compute cluster composed of several commodity grade machines to process chunks of data in parallel. A central concept in many of these frameworks is data locality. By its nature, Big Data is large enough that the entire dataset would not fit on the memory and hard drives of a single node hence replicating the entire dataset to each worker node is impractical. The data must then be partitioned across worker nodes in a manner that minimises data transfer across the network. This is a challenge for point cloud data because there exist different ways to partition data and they may require data transfer. We propose a partitioning based on Z-order which is a form of locality-sensitive hashing. The Z-order or Morton code is computed by dividing each dimension to form a grid then interleaving the binary representation of each dimension. For example, the Z-order code for the grid square with coordinates (x = 1 = 012, y = 3 = 112) is 10112 = 11. The number of points in each partition is controlled by the number of bits per dimension: the more bits, the fewer the points. The number of bits per dimension also controls the level of detail with more bits yielding finer partitioning. We present this partitioning method by implementing it on Apache Spark and investigating how different parameters affect the accuracy and running time of the k nearest neighbour algorithm for a hemispherical and a triangular wave point cloud.

Vowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram

PubMed Central

Kim, Jongin; Park, Hyeong-jun

2016-01-01

The purpose of this study is to classify EEG data on imagined speech in a single trial. We recorded EEG data while five subjects imagined different vowels, /a/, /e/, /i/, /o/, and /u/. We divided each single trial dataset into thirty segments and extracted features (mean, variance, standard deviation, and skewness) from all segments. To reduce the dimension of the feature vector, we applied a feature selection algorithm based on the sparse regression model. These features were classified using a support vector machine with a radial basis function kernel, an extreme learning machine, and two variants of an extreme learning machine with different kernels. Because each single trial consisted of thirty segments, our algorithm decided the label of the single trial by selecting the most frequent output among the outputs of the thirty segments. As a result, we observed that the extreme learning machine and its variants achieved better classification rates than the support vector machine with a radial basis function kernel and linear discrimination analysis. Thus, our results suggested that EEG responses to imagined speech could be successfully classified in a single trial using an extreme learning machine with a radial basis function and linear kernel. This study with classification of imagined speech might contribute to the development of silent speech BCI systems. PMID:28097128

Data-Driven Learning of Total and Local Energies in Elemental Boron

NASA Astrophysics Data System (ADS)

Deringer, Volker L.; Pickard, Chris J.; Csányi, Gábor

2018-04-01

The allotropes of boron continue to challenge structural elucidation and solid-state theory. Here we use machine learning combined with random structure searching (RSS) algorithms to systematically construct an interatomic potential for boron. Starting from ensembles of randomized atomic configurations, we use alternating single-point quantum-mechanical energy and force computations, Gaussian approximation potential (GAP) fitting, and GAP-driven RSS to iteratively generate a representation of the element's potential-energy surface. Beyond the total energies of the very different boron allotropes, our model readily provides atom-resolved, local energies and thus deepened insight into the frustrated β -rhombohedral boron structure. Our results open the door for the efficient and automated generation of GAPs, and other machine-learning-based interatomic potentials, and suggest their usefulness as a tool for materials discovery.

Data-Driven Learning of Total and Local Energies in Elemental Boron.

PubMed

Deringer, Volker L; Pickard, Chris J; Csányi, Gábor

2018-04-13

The allotropes of boron continue to challenge structural elucidation and solid-state theory. Here we use machine learning combined with random structure searching (RSS) algorithms to systematically construct an interatomic potential for boron. Starting from ensembles of randomized atomic configurations, we use alternating single-point quantum-mechanical energy and force computations, Gaussian approximation potential (GAP) fitting, and GAP-driven RSS to iteratively generate a representation of the element's potential-energy surface. Beyond the total energies of the very different boron allotropes, our model readily provides atom-resolved, local energies and thus deepened insight into the frustrated β-rhombohedral boron structure. Our results open the door for the efficient and automated generation of GAPs, and other machine-learning-based interatomic potentials, and suggest their usefulness as a tool for materials discovery.

Support vector machine-based facial-expression recognition method combining shape and appearance

NASA Astrophysics Data System (ADS)

Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

2010-11-01

Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

A 34-meter VAWT (Vertical Axis Wind Turbine) point design

NASA Astrophysics Data System (ADS)

Ashwill, T. D.; Berg, D. E.; Dodd, H. M.; Rumsey, M. A.; Sutherland, H. J.; Veers, P. S.

The Wind Energy Division at Sandia National Laboratories recently completed a point design based on the 34-m Vertical Axis Wind Turbine (VAWT) Test Bed. The 34-m Test Bed research machine incorporates several innovations that improve Darrieus technology, including increased energy production, over previous machines. The point design differs minimally from the Test Bed; but by removing research-related items, its estimated cost is substantially reduced. The point design is a first step towards a Test-Bed-based commercial machine that would be competitive with conventional sources of power in the mid-1990s.

The Python Spectral Analysis Tool (PySAT) for Powerful, Flexible, and Easy Preprocessing and Machine Learning with Point Spectral Data

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T.; Morris, R. V.; Laura, J.

2018-04-01

The PySAT point spectra tool provides a flexible graphical interface, enabling scientists to apply a wide variety of preprocessing and machine learning methods to point spectral data, with an emphasis on multivariate regression.

Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces

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

Brown, W Michael; Wang, Peng; Plimpton, Steven J

The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - 1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory,more » 2) minimizing the amount of code that must be ported for efficient acceleration, 3) utilizing the available processing power from both many-core CPUs and accelerators, and 4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.« less

THRESHOLD LOGIC SYNTHESIS OF SEQUENTIAL MACHINES.

DTIC Science & Technology

The application of threshold logic to the design of sequential machines is the subject of this research. A single layer of threshold logic units in...advantages of fewer components because of the use of threshold logic, along with very high-speed operation resulting from the use of only a single layer of...logic. In some instances, namely for asynchronous machines, the only delay need be the natural delay of the single layer of threshold elements. It is

Nano Mechanical Machining Using AFM Probe

NASA Astrophysics Data System (ADS)

Mostofa, Md. Golam

Complex miniaturized components with high form accuracy will play key roles in the future development of many products, as they provide portability, disposability, lower material consumption in production, low power consumption during operation, lower sample requirements for testing, and higher heat transfer due to their very high surface-to-volume ratio. Given the high market demand for such micro and nano featured components, different manufacturing methods have been developed for their fabrication. Some of the common technologies in micro/nano fabrication are photolithography, electron beam lithography, X-ray lithography and other semiconductor processing techniques. Although these methods are capable of fabricating micro/nano structures with a resolution of less than a few nanometers, some of the shortcomings associated with these methods, such as high production costs for customized products, limited material choices, necessitate the development of other fabricating techniques. Micro/nano mechanical machining, such an atomic force microscope (AFM) probe based nano fabrication, has, therefore, been used to overcome some the major restrictions of the traditional processes. This technique removes material from the workpiece by engaging micro/nano size cutting tool (i.e. AFM probe) and is applicable on a wider range of materials compared to the photolithographic process. In spite of the unique benefits of nano mechanical machining, there are also some challenges with this technique, since the scale is reduced, such as size effects, burr formations, chip adhesions, fragility of tools and tool wear. Moreover, AFM based machining does not have any rotational movement, which makes fabrication of 3D features more difficult. Thus, vibration-assisted machining is introduced into AFM probe based nano mechanical machining to overcome the limitations associated with the conventional AFM probe based scratching method. Vibration-assisted machining reduced the cutting forces and burr formations through intermittent cutting. Combining the AFM probe based machining with vibration-assisted machining enhanced nano mechanical machining processes by improving the accuracy, productivity and surface finishes. In this study, several scratching tests are performed with a single crystal diamond AFM probe to investigate the cutting characteristics and model the ploughing cutting forces. Calibration of the probe for lateral force measurements, which is essential, is also extended through the force balance method. Furthermore, vibration-assisted machining system is developed and applied to fabricate different materials to overcome some of the limitations of the AFM probe based single point nano mechanical machining. The novelty of this study includes the application of vibration-assisted AFM probe based nano scale machining to fabricate micro/nano scale features, calibration of an AFM by considering different factors, and the investigation of the nano scale material removal process from a different perspective.

Application of modified profile analysis to function testing of the motion/no-motion issue in an aircraft ground-handling simulation. [statistical analysis procedure for man machine systems flight simulation

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Steinmetz, G. G.

1979-01-01

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

Container Prevents Oxidation Of Metal Powder

NASA Technical Reports Server (NTRS)

Woodford, William H.; Power, Christopher A.; Mckechnie, Timothy N.; Burns, David H.

1992-01-01

Sealed high-vacuum container holds metal powder required free of contamination by oxygen from point of manufacture to point of use at vacuum-plasma-spraying machine. Container protects powder from air during filling, storage, and loading of spraying machine. Eliminates unnecessary handling and transfer of powder from one container to another. Stainless-steel container sits on powder feeder of vacuum-plasma-spraying machine.

Fiber laser drilling of Ni46Mn27Ga27 ferromagnetic shape memory alloy

NASA Astrophysics Data System (ADS)

Biffi, C. A.; Tuissi, A.

2014-11-01

The interest in ferromagnetic shape memory alloys (SMAs), such as NiMnGa, is increasing, thanks to the functional properties of these smart and functional materials. One of the most evident properties of these systems is their brittleness, which makes attractive the study of unconventional manufacturing processes, such as laser machining. In this work the interaction of laser beam, once focalized on the surface of Ni46Mn27Ga27 [at%] alloy, has been studied. The experiments were performed with a single laser pulse, using a 1 kW continuous wave fiber laser. The morphology of the laser machined surfaces was evaluated using scanning electron microscopy, coupled with energetic dispersion spectroscopy for the measurement of the chemical composition. The results showed that the high quality of the laser beam, coupled with great irradiances available, allow for blind or through holes to be machined on 1.8 mm plates with a single pulse in the order of a few ms. Holes were produced with size in the range of 200-300 μm; despite the long pulse duration, low amount of melted material is produced around the hole periphery. No significant variation of the chemical composition has been detected on the entrance surfaces while the exit ones have been characterized by the loss of Ga content, due to its melting point being significantly lower with respect to the other alloying elements.

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

PubMed Central

Huang, Xiwei; Jiang, Yu; Liu, Xu; Xu, Hang; Han, Zhi; Rong, Hailong; Yang, Haiping; Yan, Mei; Yu, Hao

2016-01-01

A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR) processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR) and Convolutional Neural Network based SR (CNNSR). Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications. PMID:27827837

Motion Estimation System Utilizing Point Cloud Registration

NASA Technical Reports Server (NTRS)

Chen, Qi (Inventor)

2016-01-01

A system and method of estimation motion of a machine is disclosed. The method may include determining a first point cloud and a second point cloud corresponding to an environment in a vicinity of the machine. The method may further include generating a first extended gaussian image (EGI) for the first point cloud and a second EGI for the second point cloud. The method may further include determining a first EGI segment based on the first EGI and a second EGI segment based on the second EGI. The method may further include determining a first two dimensional distribution for points in the first EGI segment and a second two dimensional distribution for points in the second EGI segment. The method may further include estimating motion of the machine based on the first and second two dimensional distributions.

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

Pre-Finishing of SiC for Optical Applications

NASA Technical Reports Server (NTRS)

Rozzi, Jay; Clavier, Odile; Gagne, John

2011-01-01

13 Manufacturing & Prototyping A method is based on two unique processing steps that are both based on deterministic machining processes using a single-point diamond turning (SPDT) machine. In the first step, a high-MRR (material removal rate) process is used to machine the part within several microns of the final geometry. In the second step, a low-MRR process is used to machine the part to near optical quality using a novel ductile regime machining (DRM) process. DRM is a deterministic machining process associated with conditions under high hydrostatic pressures and very small depths of cut. Under such conditions, using high negative-rake angle cutting tools, the high-pressure region near the tool corresponds to a plastic zone, where even a brittle material will behave in a ductile manner. In the high-MRR processing step, the objective is to remove material with a sufficiently high rate such that the process is economical, without inducing large-scale subsurface damage. A laser-assisted machining approach was evaluated whereby a CO2 laser was focused in advance of the cutting tool. While CVD (chemical vapor deposition) SiC was successfully machined with this approach, the cutting forces were substantially higher than cuts at room temperature under the same machining conditions. During the experiments, the expansion of the part and the tool due to the heating was carefully accounted for. The higher cutting forces are most likely due to a small reduction in the shear strength of the material compared with a larger increase in friction forces due to the thermal softening effect. The key advantage is that the hybrid machine approach has the potential to achieve optical quality without the need for a separate optical finishing step. Also, this method is scalable, so one can easily progress from machining 50-mm-diameter samples to the 250-mm-diameter mirror that NASA desires.

Design and FPGA Implementation of a Universal Chaotic Signal Generator Based on the Verilog HDL Fixed-Point Algorithm and State Machine Control

NASA Astrophysics Data System (ADS)

Qiu, Mo; Yu, Simin; Wen, Yuqiong; Lü, Jinhu; He, Jianbin; Lin, Zhuosheng

In this paper, a novel design methodology and its FPGA hardware implementation for a universal chaotic signal generator is proposed via the Verilog HDL fixed-point algorithm and state machine control. According to continuous-time or discrete-time chaotic equations, a Verilog HDL fixed-point algorithm and its corresponding digital system are first designed. In the FPGA hardware platform, each operation step of Verilog HDL fixed-point algorithm is then controlled by a state machine. The generality of this method is that, for any given chaotic equation, it can be decomposed into four basic operation procedures, i.e. nonlinear function calculation, iterative sequence operation, iterative values right shifting and ceiling, and chaotic iterative sequences output, each of which corresponds to only a state via state machine control. Compared with the Verilog HDL floating-point algorithm, the Verilog HDL fixed-point algorithm can save the FPGA hardware resources and improve the operation efficiency. FPGA-based hardware experimental results validate the feasibility and reliability of the proposed approach.

Boltzmann sampling from the Ising model using quantum heating of coupled nonlinear oscillators.

PubMed

Goto, Hayato; Lin, Zhirong; Nakamura, Yasunobu

2018-05-08

A network of Kerr-nonlinear parametric oscillators without dissipation has recently been proposed for solving combinatorial optimization problems via quantum adiabatic evolution through its bifurcation point. Here we investigate the behavior of the quantum bifurcation machine (QbM) in the presence of dissipation. Our numerical study suggests that the output probability distribution of the dissipative QbM is Boltzmann-like, where the energy in the Boltzmann distribution corresponds to the cost function of the optimization problem. We explain the Boltzmann distribution by generalizing the concept of quantum heating in a single nonlinear oscillator to the case of multiple coupled nonlinear oscillators. The present result also suggests that such driven dissipative nonlinear oscillator networks can be applied to Boltzmann sampling, which is used, e.g., for Boltzmann machine learning in the field of artificial intelligence.

Fractal Properties of Some Machined Surfaces

NASA Astrophysics Data System (ADS)

Thomas, T. R.; Rosén, B.-G.

Many surface profiles are self-affine fractals defined by fractal dimension D and topothesy Λ. Traditionally these parameters are derived laboriously from the slope and intercept of the profile's structure function. Recently a quicker and more convenient derivation from standard roughness parameters has been suggested. Based on this derivation, it is shown that D and Λ depend on two dimensionless numbers: the ratio of the mean peak spacing to the rms roughness, and the ratio of the mean local peak spacing to the sampling interval. Using this approach, values of D and Λ are calculated for 125 profiles produced by polishing, plateau honing and various single-point machining processes. Different processes are shown to occupy different regions in D-Λ space, and polished surfaces show a relationship between D and Λ which is independent of the surface material.

A scheme for solving the plane-plane challenge in force measurements at the nanoscale.

PubMed

Siria, Alessandro; Huant, Serge; Auvert, Geoffroy; Comin, Fabio; Chevrier, Joel

2010-05-19

Non-contact interaction between two parallel flat surfaces is a central paradigm in sciences. This situation is the starting point for a wealth of different models: the capacitor description in electrostatics, hydrodynamic flow, thermal exchange, the Casimir force, direct contact study, third body confinement such as liquids or films of soft condensed matter. The control of parallelism is so demanding that no versatile single force machine in this geometry has been proposed so far. Using a combination of nanopositioning based on inertial motors, of microcrystal shaping with a focused-ion beam (FIB) and of accurate in situ and real-time control of surface parallelism with X-ray diffraction, we propose here a "gedanken" surface-force machine that should enable one to measure interactions between movable surfaces separated by gaps in the micrometer and nanometer ranges.

Development of the self-learning machine for creating models of microprocessor of single-phase earth fault protection devices in networks with isolated neutral voltage above 1000 V

NASA Astrophysics Data System (ADS)

Utegulov, B. B.; Utegulov, A. B.; Meiramova, S.

2018-02-01

The paper proposes the development of a self-learning machine for creating models of microprocessor-based single-phase ground fault protection devices in networks with an isolated neutral voltage higher than 1000 V. Development of a self-learning machine for creating models of microprocessor-based single-phase earth fault protection devices in networks with an isolated neutral voltage higher than 1000 V. allows to effectively implement mathematical models of automatic change of protection settings. Single-phase earth fault protection devices.

Precision tool holder with flexure-adjustable, three degrees of freedom for a four-axis lathe

DOEpatents

Bono, Matthew J [Pleasanton, CA; Hibbard, Robin L [Livermore, CA

2008-03-04

A precision tool holder for precisely positioning a single point cutting tool on 4-axis lathe, such that the center of the radius of the tool nose is aligned with the B-axis of the machine tool, so as to facilitate the machining of precision meso-scale components with complex three-dimensional shapes with sub-.mu.m accuracy on a four-axis lathe. The device is designed to fit on a commercial diamond turning machine and can adjust the cutting tool position in three orthogonal directions with sub-micrometer resolution. In particular, the tool holder adjusts the tool position using three flexure-based mechanisms, with two flexure mechanisms adjusting the lateral position of the tool to align the tool with the B-axis, and a third flexure mechanism adjusting the height of the tool. Preferably, the flexures are driven by manual micrometer adjusters. In this manner, this tool holder simplifies the process of setting a tool with sub-.mu.m accuracy, to substantially reduce the time required to set the tool.

Triangular Quantum Loop Topography for Machine Learning

NASA Astrophysics Data System (ADS)

Zhang, Yi; Kim, Eun-Ah

Despite rapidly growing interest in harnessing machine learning in the study of quantum many-body systems there has been little success in training neural networks to identify topological phases. The key challenge is in efficiently extracting essential information from the many-body Hamiltonian or wave function and turning the information into an image that can be fed into a neural network. When targeting topological phases, this task becomes particularly challenging as topological phases are defined in terms of non-local properties. Here we introduce triangular quantum loop (TQL) topography: a procedure of constructing a multi-dimensional image from the ''sample'' Hamiltonian or wave function using two-point functions that form triangles. Feeding the TQL topography to a fully-connected neural network with a single hidden layer, we demonstrate that the architecture can be effectively trained to distinguish Chern insulator and fractional Chern insulator from trivial insulators with high fidelity. Given the versatility of the TQL topography procedure that can handle different lattice geometries, disorder, interaction and even degeneracy our work paves the route towards powerful applications of machine learning in the study of topological quantum matters.

A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

NASA Astrophysics Data System (ADS)

Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid

2016-09-01

Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

Some single-piston closed-cycle machines and Peter Tailer's thermal lag engine

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

West, C.D.

1993-01-01

Peter Tailer has devised, built, and operated a beautifully simple engine with a closed working gas cycle, external heating, and only a single piston. The aim of this paper is to cast some light on the possible modes of operation for his machine. The methods develops to analyze certain aspects of Stirling cycle engines, and especially the thermodynamic losses incurred in systems that are neither perfectly isothermal nor perfectly adiabatic, can be applied to Tailer's system. The results identify two idealized cycles fr such machines; relate those cycles to a single piston, ported cylinder machine proposed earlier; and offer amore » possible explanation for the success of the thermal lag engine.« less

5 CFR 532.279 - Special wage schedules for printing positions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Opaquer 4 Offset Press Helper 5 Bindery Machine Operator (Helper) 5 Film Assembler-Stripper (Single Flat-Single Color) 5 Platemaker (Single Color) 5 Film Assembler-Stripper (Partial and Composite Flats) 7... Cutter) 8 Bindery Machine Operator (Power Folder) 8 Film Assembler-Stripper (Multiple Flat-Multiple Color...

5 CFR 532.279 - Special wage schedules for printing positions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Opaquer 4 Offset Press Helper 5 Bindery Machine Operator (Helper) 5 Film Assembler-Stripper (Single Flat-Single Color) 5 Platemaker (Single Color) 5 Film Assembler-Stripper (Partial and Composite Flats) 7... Cutter) 8 Bindery Machine Operator (Power Folder) 8 Film Assembler-Stripper (Multiple Flat-Multiple Color...

Man-machine communication - A transparent switchboard for computers

NASA Technical Reports Server (NTRS)

Rasmussen, H.

1971-01-01

Device uses pattern of transparent contact touch points that are put on cathode ray tube screen. Touch point system compels more precise and unambiguous communication between man and machine than is possible with any other means, and speeds up operation responses.

Large-scale structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1983-01-01

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Findings from the National Machine Guarding Program–A Small Business Intervention: Machine Safety

PubMed Central

Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 – 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of OSHA citations and may result in serious traumatic injury. Methods Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits and a twelve-month follow-up evaluation. Results The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10-percentage point increase in business-level machine scores (p< 0.0001) and a 33-percentage point increase in LOTO program scores (p <0.0001). Conclusions Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:26716850

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

PubMed

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P < 0.0001) and a 33% point increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

Hysteresis compensation for piezoelectric actuators in single-point diamond turning

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Hu, Dejin; Wan, Daping; Liu, Hongbin

2006-02-01

In recent years, interests have been growing for fast tool servo (FTS) systems to increase the capability of existing single-point diamond turning machines. Although piezoelectric actuator is the most universal base of FTS system due to its high stiffness, accuracy and bandwidth, nonlinearity in piezoceramics limits both the static and dynamic performance of piezoelectric-actuated control systems evidently. To compensate the nonlinear hysteresis behavior of piezoelectric actuators, a hybrid model coupled with Preisach model and feedforward neural network (FNN) has been described. Since the training of FNN does not require a special calibration sequence, it is possible for on-line identification and real-time implementation with general operating data of a specific piezoelectric actuator. To describe the rate dependent behavior of piezoelectric actuators, a hybrid dynamic model was developed to predict the response of piezoelectric actuators in a wider range of input frequency. Experimental results show that a maximal error of less than 3% was accomplished by this dynamic model.

OptiCentric lathe centering machine

NASA Astrophysics Data System (ADS)

Buß, C.; Heinisch, J.

2013-09-01

High precision optics depend on precisely aligned lenses. The shift and tilt of individual lenses as well as the air gap between elements require accuracies in the single micron regime. These accuracies are hard to meet with traditional assembly methods. Instead, lathe centering can be used to machine the mount with respect to the optical axis. Using a diamond turning process, all relevant errors of single mounted lenses can be corrected in one post-machining step. Building on the OptiCentric® and OptiSurf® measurement systems, Trioptics has developed their first lathe centering machines. The machine and specific design elements of the setup will be shown. For example, the machine can be used to turn optics for i-line steppers with highest precision.

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,…

Radiation tolerant combinational logic cell

NASA Technical Reports Server (NTRS)

Maki, Gary R. (Inventor); Whitaker, Sterling (Inventor); Gambles, Jody W. (Inventor)

2009-01-01

A system has a reduced sensitivity to Single Event Upset and/or Single Event Transient(s) compared to traditional logic devices. In a particular embodiment, the system includes an input, a logic block, a bias stage, a state machine, and an output. The logic block is coupled to the input. The logic block is for implementing a logic function, receiving a data set via the input, and generating a result f by applying the data set to the logic function. The bias stage is coupled to the logic block. The bias stage is for receiving the result from the logic block and presenting it to the state machine. The state machine is coupled to the bias stage. The state machine is for receiving, via the bias stage, the result generated by the logic block. The state machine is configured to retain a state value for the system. The state value is typically based on the result generated by the logic block. The output is coupled to the state machine. The output is for providing the value stored by the state machine. Some embodiments of the invention produce dual rail outputs Q and Q'. The logic block typically contains combinational logic and is similar, in size and transistor configuration, to a conventional CMOS combinational logic design. However, only a very small portion of the circuits of these embodiments, is sensitive to Single Event Upset and/or Single Event Transients.

Improved tool grinding machine

DOEpatents

Dial, C.E. Sr.

The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thicknesses may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

Tool grinding machine

DOEpatents

Dial, Sr., Charles E.

1980-01-01

The present invention relates to an improved tool grinding mechanism for grinding single point diamond cutting tools to precise roundness and radius specifications. The present invention utilizes a tool holder which is longitudinally displaced with respect to the remainder of the grinding system due to contact of the tool with the grinding surface with this displacement being monitored so that any variation in the grinding of the cutting surface such as caused by crystal orientation or tool thickness may be compensated for during the grinding operation to assure the attainment of the desired cutting tool face specifications.

Fast Nonparametric Machine Learning Algorithms for High-Dimensional Massive Data and Applications

DTIC Science & Technology

2006-03-01

know the probability of that from Lemma 2. Using the union bound, we know that for any query q, the probability that i-am-feeling-lucky search algorithm...and each point in a d-dimensional space, a naive k-NN search needs to do a linear scan of T for every single query q, and thus the computational time...algorithm based on partition trees with priority search , and give an expected query time O((1/)d log n). But the constant in the O((1/)d log n

Some single-piston closed-cycle machines and Peter Tailer`s thermal lag engine

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

West, C.D.

1993-06-01

Peter Tailer has devised, built, and operated a beautifully simple engine with a closed working gas cycle, external heating, and only a single piston. The aim of this paper is to cast some light on the possible modes of operation for his machine. The methods develops to analyze certain aspects of Stirling cycle engines, and especially the thermodynamic losses incurred in systems that are neither perfectly isothermal nor perfectly adiabatic, can be applied to Tailer`s system. The results identify two idealized cycles fr such machines; relate those cycles to a single piston, ported cylinder machine proposed earlier; and offer amore » possible explanation for the success of the thermal lag engine.« less

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data

PubMed Central

Navarro, Pedro J.; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-01-01

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%). PMID:28025565

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

PubMed

Navarro, Pedro J; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-12-23

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).

On the analysis of the double Hopf bifurcation in machining processes via centre manifold reduction

NASA Astrophysics Data System (ADS)

Molnar, T. G.; Dombovari, Z.; Insperger, T.; Stepan, G.

2017-11-01

The single-degree-of-freedom model of orthogonal cutting is investigated to study machine tool vibrations in the vicinity of a double Hopf bifurcation point. Centre manifold reduction and normal form calculations are performed to investigate the long-term dynamics of the cutting process. The normal form of the four-dimensional centre subsystem is derived analytically, and the possible topologies in the infinite-dimensional phase space of the system are revealed. It is shown that bistable parameter regions exist where unstable periodic and, in certain cases, unstable quasi-periodic motions coexist with the equilibrium. Taking into account the non-smoothness caused by loss of contact between the tool and the workpiece, the boundary of the bistable region is also derived analytically. The results are verified by numerical continuation. The possibility of (transient) chaotic motions in the global non-smooth dynamics is shown.

Multi-point laser coherent detection system and its application on vibration measurement

NASA Astrophysics Data System (ADS)

Fu, Y.; Yang, C.; Xu, Y. J.; Liu, H.; Yan, K.; Guo, M.

2015-05-01

Laser Doppler vibrometry (LDV) is a well-known interferometric technique to measure the motions, vibrations and mode shapes of machine components and structures. The drawback of commercial LDV is that it can only offer a pointwise measurement. In order to build up a vibrometric image, a scanning device is normally adopted to scan the laser point in two spatial axes. These scanning laser Doppler vibrometers (SLDV) assume that the measurement conditions remain invariant while multiple and identical, sequential measurements are performed. This assumption makes SLDVs impractical to do measurement on transient events. In this paper, we introduce a new multiple-point laser coherent detection system based on spatial-encoding technology and fiber configuration. A simultaneous vibration measurement on multiple points is realized using a single photodetector. A prototype16-point laser coherent detection system is built and it is applied to measure the vibration of various objects, such as body of a car or a motorcycle when engine is on and under shock tests. The results show the prospect of multi-point laser coherent detection system in the area of nondestructive test and precise dynamic measurement.

Relative Performance of Hardwood Sawing Machines

Treesearch

Philip H. Steele; Michael W. Wade; Steven H. Bullard; Philip A. Araman

1991-01-01

Only limited information has been available to hardwood sawmillers on the performance of their sawing machines. This study analyzes a large database of individual machine studies to provide detailed information on 6 machine types. These machine types were band headrig, circular headrig, band linebar resaw, vertical band splitter resaw, single arbor gang resaw and...

29 CFR 1926.300 - General requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... apply to concrete vibrators, concrete breakers, powered tampers, jack hammers, rock drills, and similar... guarding. One or more methods of machine guarding shall be provided to protect the operator and other employees in the machine area from hazards such as those created by point of operation, ingoing nip points...

29 CFR 1926.300 - General requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... apply to concrete vibrators, concrete breakers, powered tampers, jack hammers, rock drills, and similar... guarding. One or more methods of machine guarding shall be provided to protect the operator and other employees in the machine area from hazards such as those created by point of operation, ingoing nip points...

29 CFR 1926.300 - General requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... apply to concrete vibrators, concrete breakers, powered tampers, jack hammers, rock drills, and similar... guarding. One or more methods of machine guarding shall be provided to protect the operator and other employees in the machine area from hazards such as those created by point of operation, ingoing nip points...

Distributed Computation of the knn Graph for Large High-Dimensional Point Sets

PubMed Central

Plaku, Erion; Kavraki, Lydia E.

2009-01-01

High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) graphs. The knn graph of a data set is obtained by connecting each point to its k closest points. As the research in the above-mentioned fields progressively addresses problems of unprecedented complexity, the demand for computing knn graphs based on arbitrary distance metrics and large high-dimensional data sets increases, exceeding resources available to a single machine. In this work we efficiently distribute the computation of knn graphs for clusters of processors with message passing. Extensions to our distributed framework include the computation of graphs based on other proximity queries, such as approximate knn or range queries. Our experiments show nearly linear speedup with over one hundred processors and indicate that similar speedup can be obtained with several hundred processors. PMID:19847318

A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

PubMed

Frohlich, Holger; Claes, Kasper; De Wolf, Catherine; Van Damme, Xavier; Michel, Anne

2018-05-01

Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Noldus Catwalk system, in which footprints are automatically captured and stored. We present a - to our knowledge - first machine learning based approach for the Catwalk system, which comprises a step decomposition, definition and extraction of meaningful features, multivariate step sequence alignment, feature selection, and training of different classifiers (gradient boosting machine, random forest, and elastic net). Using animal-wise leave-one-out cross validation we demonstrate that with our method we can reliable separate movement patterns of a putative Parkinson's disease animal model and several control groups. Furthermore, we show that we can predict the time point after and the type of different brain lesions and can even forecast the brain region, where the intervention was applied. We provide an in-depth analysis of the features involved into our classifiers via statistical techniques for model interpretation. A machine learning method for automated analysis of data from the Noldus Catwalk system was established. Our works shows the ability of machine learning to discriminate pharmacologically relevant animal groups based on their walking behavior in a multivariate manner. Further interesting aspects of the approach include the ability to learn from past experiments, improve with more data arriving and to make predictions for single animals in future studies.

Array microscopy technology and its application to digital detection of Mycobacterium tuberculosis

NASA Astrophysics Data System (ADS)

McCall, Brian P.

Tuberculosis causes more deaths worldwide than any other curable infectious disease. This is the case despite tuberculosis appearing to be on the verge of eradication midway through the last century. Efforts at reversing the spread of tuberculosis have intensified since the early 1990s. Since then, microscopy has been the primary frontline diagnostic. In this dissertation, advances in clinical microscopy towards array microscopy for digital detection of Mycobacterium tuberculosis are presented. Digital array microscopy separates the tasks of microscope operation and pathogen detection and will reduce the specialization needed in order to operate the microscope. Distributing the work and reducing specialization will allow this technology to be deployed at the point of care, taking the front-line diagnostic for tuberculosis from the microscopy center to the community health center. By improving access to microscopy centers, hundreds of thousands of lives can be saved. For this dissertation, a lens was designed that can be manufactured as 4x6 array of microscopes. This lens design is diffraction limited, having less than 0.071 waves of aberration (root mean square) over the entire field of view. A total area imaged onto a full-frame digital image sensor is expected to be 3.94 mm2, which according to tuberculosis microscopy guidelines is more than sufficient for a sensitive diagnosis. The design is tolerant to single point diamond turning manufacturing errors, as found by tolerance analysis and by fabricating a prototype. Diamond micro-milling, a fabrication technique for lens array molds, was applied to plastic plano-concave and plano-convex lens arrays, and found to produce high quality optical surfaces. The micro-milling technique did not prove robust enough to produce bi-convex and meniscus lens arrays in a variety of lens shapes, however, and it required lengthy fabrication times. In order to rapidly prototype new lenses, a new diamond machining technique was developed called 4-axis single point diamond machining. This technique is 2-10x faster than micro-milling, depending on how advanced the micro-milling equipment is. With array microscope fabrication still in development, a single prototype of the lens designed for an array microscope was fabricated using single point diamond turning. The prototype microscope objective was validated in a pre-clinical trial. The prototype was compared with a standard clinical microscope objective in diagnostic tests. High concordance, a Fleiss's kappa of 0.88, was found between diagnoses made using the prototype and standard microscope objectives and a reference test. With the lens designed and validated and an advanced fabrication process developed, array microscopy technology is advanced to the point where it is feasible to rapidly prototype an array microscope for detection of tuberculosis and translate array microscope from an innovative concept to a device that can save lives.

MPIRUN: A Portable Loader for Multidisciplinary and Multi-Zonal Applications

NASA Technical Reports Server (NTRS)

Fineberg, Samuel A.; Woodrow, Thomas S. (Technical Monitor)

1994-01-01

Multidisciplinary and multi-zonal applications are an important class of applications in the area of Computational Aerosciences. In these codes, two or more distinct parallel programs or copies of a single program are utilized to model a single problem. To support such applications, it is common to use a programming model where a program is divided into several single program multiple data stream (SPMD) applications, each of which solves the equations for a single physical discipline or grid zone. These SPMD applications are then bound together to form a single multidisciplinary or multi-zonal program in which the constituent parts communicate via point-to-point message passing routines. One method for implementing the message passing portion of these codes is with the new Message Passing Interface (MPI) standard. Unfortunately, this standard only specifies the message passing portion of an application, but does not specify any portable mechanisms for loading an application. MPIRUN was developed to provide a portable means for loading MPI programs, and was specifically targeted at multidisciplinary and multi-zonal applications. Programs using MPIRUN for loading and MPI for message passing are then portable between all machines supported by MPIRUN. MPIRUN is currently implemented for the Intel iPSC/860, TMC CM5, IBM SP-1 and SP-2, Intel Paragon, and workstation clusters. Further, MPIRUN is designed to be simple enough to port easily to any system supporting MPI.

Low-order models of a single-screw expander for organic Rankine cycle applications

NASA Astrophysics Data System (ADS)

Ziviani, D.; Desideri, A.; Lemort, V.; De Paepe, M.; van den Broek, M.

2015-08-01

Screw-type volumetric expanders have been demonstrated to be a suitable technology for organic Rankine cycle (ORC) systems because of higher overall effectiveness and good part-load behaviour over other positive displacement machines. An 11 kWe single-screw expander (SSE) adapted from an air compressor has been tested in an ORC test-rig operating with R245fa as working fluid. A total of 60 steady-steady points have been obtained at four different rotational speeds of the expander in the range between 2000 rpm and 3300 rpm. The maximum electrical power output and overall isentropic effectiveness measured were 7.3 kW and 51.9%, respectively. In this paper, a comparison between two low-order models is proposed in terms of accuracy of the predictions, the robustness of the model and the computational time. The first model is the Pacejka equation-based model and the second is a semi-empirical model derived from a well-known scroll expander model and modified to include the geometric aspects of a single screw expander. The models have been calibrated with the available steady-state measurement points by identifying the proper parameters.

Human Movement Recognition Based on the Stochastic Characterisation of Acceleration Data

PubMed Central

Munoz-Organero, Mario; Lotfi, Ahmad

2016-01-01

Human activity recognition algorithms based on information obtained from wearable sensors are successfully applied in detecting many basic activities. Identified activities with time-stationary features are characterised inside a predefined temporal window by using different machine learning algorithms on extracted features from the measured data. Better accuracy, precision and recall levels could be achieved by combining the information from different sensors. However, detecting short and sporadic human movements, gestures and actions is still a challenging task. In this paper, a novel algorithm to detect human basic movements from wearable measured data is proposed and evaluated. The proposed algorithm is designed to minimise computational requirements while achieving acceptable accuracy levels based on characterising some particular points in the temporal series obtained from a single sensor. The underlying idea is that this algorithm would be implemented in the sensor device in order to pre-process the sensed data stream before sending the information to a central point combining the information from different sensors to improve accuracy levels. Intra- and inter-person validation is used for two particular cases: single step detection and fall detection and classification using a single tri-axial accelerometer. Relevant results for the above cases and pertinent conclusions are also presented. PMID:27618063

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.

A novel single-phase flux-switching permanent magnet linear generator used for free-piston Stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Ping; Sui, Yi; Tong, Chengde; Bai, Jingang; Yu, Bin; Lin, Fei

2014-05-01

This paper investigates a novel single-phase flux-switching permanent-magnet (PM) linear machine used for free-piston Stirling engines. The machine topology and operating principle are studied. A flux-switching PM linear machine is designed based on the quasi-sinusoidal speed characteristic of the resonant piston. Considering the performance of back electromotive force and thrust capability, some leading structural parameters, including the air gap length, the PM thickness, the ratio of the outer radius of mover to that of stator, the mover tooth width, the stator tooth width, etc., are optimized by finite element analysis. Compared with conventional three-phase moving-magnet linear machine, the proposed single-phase flux-switching topology shows advantages in less PM use, lighter mover, and higher volume power density.

Findings From the National Machine Guarding Program–A Small Business Intervention

PubMed Central

Parker, David L.; Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives: The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Methods: Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. Results: The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P < 0.0001) and a 33% point increase in LOTO program scores (P < 0.0001). Conclusions: Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:27466709

Development of a low energy micro sheet forming machine

NASA Astrophysics Data System (ADS)

Razali, A. R.; Ann, C. T.; Shariff, H. M.; Kasim, N. I.; Musa, M. A.; Ahmad, A. F.

2017-10-01

It is expected that with the miniaturization of materials being processed, energy consumption is also being `miniaturized' proportionally. The focus of this study was to design a low energy micro-sheet-forming machine for thin sheet metal application and fabricate a low direct current powered micro-sheet-forming machine. A prototype of low energy system for a micro-sheet-forming machine which includes mechanical and electronic elements was developed. The machine was tested for its performance in terms of natural frequency, punching forces, punching speed and capability, energy consumption (single punch and frequency-time based). Based on the experiments, the machine can do 600 stroke per minute and the process is unaffected by the machine's natural frequency. It was also found that sub-Joule of power was required for a single stroke of punching/blanking process. Up to 100micron thick carbon steel shim was successfully tested and punched. It concludes that low power forming machine is feasible to be developed and be used to replace high powered machineries to form micro-products/parts.

Wavefront correction using machine learning methods for single molecule localization microscopy

NASA Astrophysics Data System (ADS)

Tehrani, Kayvan F.; Xu, Jianquan; Kner, Peter

2015-03-01

Optical Aberrations are a major challenge in imaging biological samples. In particular, in single molecule localization (SML) microscopy techniques (STORM, PALM, etc.) a high Strehl ratio point spread function (PSF) is necessary to achieve sub-diffraction resolution. Distortions in the PSF shape directly reduce the resolution of SML microscopy. The system aberrations caused by the imperfections in the optics and instruments can be compensated using Adaptive Optics (AO) techniques prior to imaging. However, aberrations caused by the biological sample, both static and dynamic, have to be dealt with in real time. A challenge for wavefront correction in SML microscopy is a robust optimization approach in the presence of noise because of the naturally high fluctuations in photon emission from single molecules. Here we demonstrate particle swarm optimization for real time correction of the wavefront using an intensity independent metric. We show that the particle swarm algorithm converges faster than the genetic algorithm for bright fluorophores.

Control of anisotropic shape deviation in single point incremental forming of paperboard

NASA Astrophysics Data System (ADS)

Stein, Philipp; Franke, Wilken; Hoppe, Florian; Hesse, Daniel; Mill, Katharina; Groche, Peter

2017-10-01

The increasing social demand for sustainable material use leads to new process strategies as well as to the use of new materials in nearly all industries. In light of this demand, paperboard shows potential to substitute polymer-based components while also exhibiting improved ecological properties. However, in contrast to polymer-based products, the forming limits of paperboard are relatively low. Therefore, three dimensional forming of paperboard is subject of current research. One area of research focuses on the control of the fiber orientation dependent anisotropic material behavior of industrial paperboard in forming processes. For an examined industrial paperboard, an average elongation at break of 1.2% in the so called machine direction (fiber preferential direction, MD) has been determined at standard climate conditions. In contrast, in cross-direction (orthogonal to the machine direction, CD) a value of 2.6% was observed. With increased moisture content of the specimens the difference between the mechanical properties in MD and CD even increases. As a result of the various fiber-orientation dependent mechanical properties, forming with symmetric tools leads to asymmetrically shaped final parts. Within this article, an approach to reduce the asymmetric shape of three-dimensional formed paperboard by using single point incremental forming technology is presented. For a free spatial processing strategy the 3D Servo Press Technology, which enables circular as well as free processing strategies, is used. Based on reference tests with a circular processing strategy, it is shown that by using an adapted, elliptical tool path, an almost symmetric shaped part can be formed.

Tool setting device

DOEpatents

Brown, Raymond J.

1977-01-01

The present invention relates to a tool setting device for use with numerically controlled machine tools, such as lathes and milling machines. A reference position of the machine tool relative to the workpiece along both the X and Y axes is utilized by the control circuit for driving the tool through its program. This reference position is determined for both axes by displacing a single linear variable displacement transducer (LVDT) with the machine tool through a T-shaped pivotal bar. The use of the T-shaped bar allows the cutting tool to be moved sequentially in the X or Y direction for indicating the actual position of the machine tool relative to the predetermined desired position in the numerical control circuit by using a single LVDT.

Detecting Abnormal Word Utterances in Children With Autism Spectrum Disorders: Machine-Learning-Based Voice Analysis Versus Speech Therapists.

PubMed

Nakai, Yasushi; Takiguchi, Tetsuya; Matsui, Gakuyo; Yamaoka, Noriko; Takada, Satoshi

2017-10-01

Abnormal prosody is often evident in the voice intonations of individuals with autism spectrum disorders. We compared a machine-learning-based voice analysis with human hearing judgments made by 10 speech therapists for classifying children with autism spectrum disorders ( n = 30) and typical development ( n = 51). Using stimuli limited to single-word utterances, machine-learning-based voice analysis was superior to speech therapist judgments. There was a significantly higher true-positive than false-negative rate for machine-learning-based voice analysis but not for speech therapists. Results are discussed in terms of some artificiality of clinician judgments based on single-word utterances, and the objectivity machine-learning-based voice analysis adds to judging abnormal prosody.

A Novel Application of Machine Learning Methods to Model Microcontroller Upset Due to Intentional Electromagnetic Interference

NASA Astrophysics Data System (ADS)

Bilalic, Rusmir

A novel application of support vector machines (SVMs), artificial neural networks (ANNs), and Gaussian processes (GPs) for machine learning (GPML) to model microcontroller unit (MCU) upset due to intentional electromagnetic interference (IEMI) is presented. In this approach, an MCU performs a counting operation (0-7) while electromagnetic interference in the form of a radio frequency (RF) pulse is direct-injected into the MCU clock line. Injection times with respect to the clock signal are the clock low, clock rising edge, clock high, and the clock falling edge periods in the clock window during which the MCU is performing initialization and executing the counting procedure. The intent is to cause disruption in the counting operation and model the probability of effect (PoE) using machine learning tools. Five experiments were executed as part of this research, each of which contained a set of 38,300 training points and 38,300 test points, for a total of 383,000 total points with the following experiment variables: injection times with respect to the clock signal, injected RF power, injected RF pulse width, and injected RF frequency. For the 191,500 training points, the average training error was 12.47%, while for the 191,500 test points the average test error was 14.85%, meaning that on average, the machine was able to predict MCU upset with an 85.15% accuracy. Leaving out the results for the worst-performing model (SVM with a linear kernel), the test prediction accuracy for the remaining machines is almost 89%. All three machine learning methods (ANNs, SVMs, and GPML) showed excellent and consistent results in their ability to model and predict the PoE on an MCU due to IEMI. The GP approach performed best during training with a 7.43% average training error, while the ANN technique was most accurate during the test with a 10.80% error.

Estimation of Alpine Skier Posture Using Machine Learning Techniques

PubMed Central

Nemec, Bojan; Petrič, Tadej; Babič, Jan; Supej, Matej

2014-01-01

High precision Global Navigation Satellite System (GNSS) measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier's neck. A key issue is how to estimate other more relevant parameters of the skier's body, like the center of mass (COM) and ski trajectories. Previously, these parameters were estimated by modeling the skier's body with an inverted-pendulum model that oversimplified the skier's body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier's body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing. PMID:25313492

Bayesian structural inference for hidden processes.

PubMed

Strelioff, Christopher C; Crutchfield, James P

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ε-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ε-machines, irrespective of estimated transition probabilities. Properties of ε-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Bayesian structural inference for hidden processes

NASA Astrophysics Data System (ADS)

Strelioff, Christopher C.; Crutchfield, James P.

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Experimental Investigation on Cutting Characteristics in Nanometric Plunge-Cutting of BK7 and Fused Silica Glasses

PubMed Central

An, Qinglong; Ming, Weiwei; Chen, Ming

2015-01-01

Ductile cutting are most widely used in fabricating high-quality optical glass components to achieve crack-free surfaces. For ultra-precision machining of brittle glass materials, critical undeformed chip thickness (CUCT) commonly plays a pivotal role in determining the transition point from ductile cutting to brittle cutting. In this research, cutting characteristics in nanometric cutting of BK7 and fused silica glasses, including machined surface morphology, surface roughness, cutting force and specific cutting energy, were investigated with nanometric plunge-cutting experiments. The same cutting speed of 300 mm/min was used in the experiments with single-crystal diamond tool. CUCT was determined according to the mentioned cutting characteristics. The results revealed that 320 nm was found as the CUCT in BK7 cutting and 50 nm was determined as the size effect of undeformed chip thickness. A high-quality machined surface could be obtained with the undeformed chip thickness between 50 and 320 nm at ductile cutting stage. Moreover, no CUCT was identified in fused silica cutting with the current cutting conditions, and brittle-fracture mechanism was confirmed as the predominant chip-separation mode throughout the nanometric cutting operation. PMID:28788010

Experimental Investigation on Cutting Characteristics in Nanometric Plunge-Cutting of BK7 and Fused Silica Glasses.

PubMed

An, Qinglong; Ming, Weiwei; Chen, Ming

2015-03-27

Ductile cutting are most widely used in fabricating high-quality optical glass components to achieve crack-free surfaces. For ultra-precision machining of brittle glass materials, critical undeformed chip thickness (CUCT) commonly plays a pivotal role in determining the transition point from ductile cutting to brittle cutting. In this research, cutting characteristics in nanometric cutting of BK7 and fused silica glasses, including machined surface morphology, surface roughness, cutting force and specific cutting energy, were investigated with nanometric plunge-cutting experiments. The same cutting speed of 300 mm/min was used in the experiments with single-crystal diamond tool. CUCT was determined according to the mentioned cutting characteristics. The results revealed that 320 nm was found as the CUCT in BK7 cutting and 50 nm was determined as the size effect of undeformed chip thickness. A high-quality machined surface could be obtained with the undeformed chip thickness between 50 and 320 nm at ductile cutting stage. Moreover, no CUCT was identified in fused silica cutting with the current cutting conditions, and brittle-fracture mechanism was confirmed as the predominant chip-separation mode throughout the nanometric cutting operation.

Characteristics and Machining Performance of TiN and TiAlN Coatings on a Milling Cutter

NASA Astrophysics Data System (ADS)

Sarwar, Mohammed; Haider, Julfikar

2011-01-01

Titanium Nitride (TiN) coating deposited by Physical Vapour Deposition (PVD) or Chemical Vapour Deposition (CVD) techniques on cutting tools (single point or multipoint) has contributed towards the improvement of tool life, productivity and product quality [1]. Addition of Al in TiN coating (e.g., TiAlN or AlTiN) has further improved the coating properties required for machining applications [2, 3]. This work presents a comparative investigation on TiN and TiAlN coatings deposited on to a Powder Metallurgy High Speed Steel (PM HSS) milling cutter used for machining bimetal (M42+D6A) steel strips. PVD (Arc evaporation) technique was used to deposit the coatings after carefully preparing the cutting edges of the milling cutter. Microstructure, chemical composition, hardness and adhesion of the coatings have been characterised using different techniques. The incorporation of Al into TiN coating results in an improvement in hardness, wear resistance and cutting performance. Examination of the worn flank in the coated cutting edges revealed that abrasive and adhesive wear are the predominant failure mechanisms. Tool designers, coating suppliers and manufacturing engineers could benefit from the information provided.

Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

PubMed

Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

2016-07-01

Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

AE Monitoring of Diamond Turned Rapidly Soldified Aluminium 443

NASA Astrophysics Data System (ADS)

Onwuka, G.; Abou-El-Hossein, K.; Mkoko, Z.

2017-05-01

The fast replacement of conventional aluminium with rapidly solidified aluminium alloys has become a noticeable trend in the current manufacturing industries involved in the production of optics and optical molding inserts. This is as a result of the improved performance and durability of rapidly solidified aluminium alloys when compared to conventional aluminium. Melt spinning process is vital for manufacturing rapidly solidified aluminium alloys like RSA 905, RSA 6061 and RSA 443 which are common in the industries today. RSA 443 is a newly developed alloy with few research findings and huge research potential. There is no available literature focused on monitoring the machining of RSA 443 alloys. In this research, Acoustic Emission sensing technique was applied to monitor the single point diamond turning of RSA 443 on an ultrahigh precision lathe machine. The machining process was carried out after careful selection of feed, speed and depths of cut. The monitoring process was achieved with a high sampling data acquisition system using different tools while concurrent measurement of the surface roughness and tool wear were initiated after covering a total feed distance of 13km. An increasing trend of raw AE spikes and peak to peak signal were observed with an increase in the surface roughness and tool wear values. Hence, acoustic emission sensing technique proves to be an effective monitoring method for the machining of RSA 443 alloy.

Breast Cancer Detection

NASA Technical Reports Server (NTRS)

1976-01-01

NASA's Jet Propulsion Laboratory has come up with a technique to decrease exposure to harmful x-rays in mammographies or breast radiography. Usually, physicians make more than one exposure to arrive at an x-ray film of acceptable density. Now the same solar cells used to convert sunlight into electricity on space satellites can make a single exposure sufficient. When solar cell sensor is positioned directly beneath x-ray film, it can determine exactly when film has received sufficient radiation and has been exposed to optimum density. At that point associated electronic equipment sends signal to cut off x-ray source. Reduction of mammography to single exposures not only reduced x-ray hazard significantly, but doubled the number of patient examinations handled by one machine. The NASA laboratory used this control system at the Huntington Memorial Hospital with overwhelming success.

Detection of longitudinal visual field progression in glaucoma using machine learning.

PubMed

Yousefi, Siamak; Kiwaki, Taichi; Zheng, Yuhui; Suigara, Hiroki; Asaoka, Ryo; Murata, Hiroshi; Lemij, Hans; Yamanishi, Kenji

2018-06-16

Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine-learning-based index for glaucoma progression detection that outperforms global, region-wise, and point-wise indices. Development and comparison of a prognostic index. Visual fields from 2085 eyes of 1214 subjects were used to identify glaucoma progression patterns using machine learning. Visual fields from 133 eyes of 71 glaucoma patients were collected 10 times over 10 weeks to provide a no-change, test-retest dataset. The parameters of all methods were identified using visual field sequences in the test-retest dataset to meet fixed 95% specificity. An independent dataset of 270 eyes of 136 glaucoma patients and survival analysis were utilized to compare methods. The time to detect progression in 25% of the eyes in the longitudinal dataset using global mean deviation (MD) was 5.2 years (95% confidence interval, 4.1 - 6.5 years); 4.5 years (4.0 - 5.5) using region-wise, 3.9 years (3.5 - 4.6) using point-wise, and 3.5 years (3.1 - 4.0) using machine learning analysis. The time until 25% of eyes showed subsequently confirmed progression after two additional visits were included were 6.6 years (5.6 - 7.4 years), 5.7 years (4.8 - 6.7), 5.6 years (4.7 - 6.5), and 5.1 years (4.5 - 6.0) for global, region-wise, point-wise, and machine learning analyses, respectively. Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods. Copyright © 2018 Elsevier Inc. All rights reserved.

A single-chip 32-channel analog beamformer with 4-ns delay resolution and 768-ns maximum delay range for ultrasound medical imaging with a linear array transducer.

PubMed

Um, Ji-Yong; Kim, Yoon-Jee; Cho, Seong-Eun; Chae, Min-Kyun; Kim, Byungsub; Sim, Jae-Yoon; Park, Hong-June

2015-02-01

A single-chip 32-channel analog beamformer is proposed. It achieves a delay resolution of 4 ns and a maximum delay range of 768 ns. It has a focal-point based architecture, which consists of 7 sub-analog beamformers (sub-ABF). Each sub-ABF performs a RX focusing operation for a single focal point. Seven sub-ABFs perform a time-interleaving operation to achieve the maximum delay range of 768 ns. Phase interpolators are used in sub-ABFs to generate sampling clocks with the delay resolution of 4 ns from a low frequency system clock of 5 MHz. Each sub-ABF samples 32 echo signals at different times into sampling capacitors, which work as analog memory cells. The sampled 32 echo signals of each sub-ABF are originated from one target focal point at one instance. They are summed at one instance in a sub-ABF to perform the RX focusing for the target focal point. The proposed ABF chip has been fabricated in a 0.13- μ m CMOS process with an active area of 16 mm (2). The total power consumption is 287 mW. In measurement, the digital echo signals from a commercial ultrasound medical imaging machine were applied to the fabricated chip through commercial DAC chips. Due to the speed limitation of the DAC chips, the delay resolution was relaxed to 10 ns for the real-time measurement. A linear array transducer with no steering operation is used in this work.

48 CFR 252.211-7003 - Item unique identification and valuation.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reader or interrogator, used to retrieve data encoded on machine-readable media. Concatenated unique item... identifier. Item means a single hardware article or a single unit formed by a grouping of subassemblies... manufactured under identical conditions. Machine-readable means an automatic identification technology media...

Numerical analysis method for linear induction machines.

NASA Technical Reports Server (NTRS)

Elliott, D. G.

1972-01-01

A numerical analysis method has been developed for linear induction machines such as liquid metal MHD pumps and generators and linear motors. Arbitrary phase currents or voltages can be specified and the moving conductor can have arbitrary velocity and conductivity variations from point to point. The moving conductor is divided into a mesh and coefficients are calculated for the voltage induced at each mesh point by unit current at every other mesh point. Combining the coefficients with the mesh resistances yields a set of simultaneous equations which are solved for the unknown currents.

More About The Farley Three-Dimensional Braider

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1993-01-01

Farley three-dimensional braider, undergoing development, is machine for automatic fabrication of three-dimensional braided structures. Incorporates yarns into structure at arbitrary braid angles to produce complicated shape. Braiding surface includes movable braiding segments containing pivot points, along which yarn carriers travel during braiding process. Yarn carrier travels along sequence of pivot points as braiding segments move. Combined motions position yarns for braiding onto preform. Intended for use in making fiber preforms for fiber/matrix composite parts, such as multiblade propellers. Machine also described in "Farley Three-Dimensional Braiding Machine" (LAR-13911).

Comparisons between designs for single-sided linear electric motors: Homopolar synchronous and induction

NASA Astrophysics Data System (ADS)

Nondahl, T. A.; Richter, E.

1980-09-01

A design study of two types of single sided (with a passive rail) linear electric machine designs, namely homopolar linear synchronous machines (LSM's) and linear induction machines (LIM's), is described. It is assumed the machines provide tractive effort for several types of light rail vehicles and locomotives. These vehicles are wheel supported and require tractive powers ranging from 200 kW to 3735 kW and top speeds ranging from 112 km/hr to 400 km/hr. All designs are made according to specified magnetic and thermal criteria. The LSM advantages are a higher power factor, much greater restoring forces for track misalignments, and less track heating. The LIM advantages are no need to synchronize the excitation frequency precisely to vehicle speed, simpler machine construction, and a more easily anchored track structure. The relative weights of the two machine types vary with excitation frequency and speed; low frequencies and low speeds favor the LSM.

Simulation model of a single-stage lithium bromide-water absorption cooling unit

NASA Technical Reports Server (NTRS)

Miao, D.

1978-01-01

A computer model of a LiBr-H2O single-stage absorption machine was developed. The model, utilizing a given set of design data such as water-flow rates and inlet or outlet temperatures of these flow rates but without knowing the interior characteristics of the machine (heat transfer rates and surface areas), can be used to predict or simulate off-design performance. Results from 130 off-design cases for a given commercial machine agree with the published data within 2 percent.

Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

ERIC Educational Resources Information Center

Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

2009-01-01

In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

Machined electrostatic sector for mass spectrometer

NASA Technical Reports Server (NTRS)

Sinha, Mahadeva P. (Inventor)

2001-01-01

An electrostatic sector device for a mass spectrometer is formed from a single piece of machinable ceramic. The machined ceramic is coated with a nickel coating, and a notch is etched in the nickel coating to form two separated portions. The sector can be covered by a cover formed from a separate piece of machined ceramic.

The Single Needle Lockstitch Machine. [Constructing Darts.] Module 3.

ERIC Educational Resources Information Center

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

This module on constructing darts, one in a series on the single needle lockstitch sewing machine for student self-study, contains two sections. Each section includes the following parts: an introduction, directions, an objective, learning activities, student information, student self-check, check-out activities, and an instructor's final…

The Single Needle Lockstitch Machine. [Setting Zippers.] Module 8.

ERIC Educational Resources Information Center

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

This module on setting zippers, one in a series on the single needle lockstitch sewing machine for student self-study, contains five sections. Each section includes the following parts: an introduction, directions, an objective, learning activities, student information, student self-check, check-out activities, and an instructor's final checklist.…

An observational study investigating the association of ultrasonographically assessed machine milking-induced changes in teat condition and teat-end shape in dairy cows.

PubMed

Wieland, M; Virkler, P D; Borkowski, A H; Älveby, N; Wood, P; Nydam, D V

2018-06-21

Mechanical forces during machine milking induce changes in teat condition which can be differentiated into short-term and long-term changes. Machine milking-induced short-term changes in teat condition (STC) are defined as tissue responses to a single milking and have been associated with the risk of new intramammary infection. Albeit, their association with teat characteristics, such as teat-end shape, has not been investigated by rigorous methods. The primary objective was to determine the association of STC, as measured by ultrasonography, with teat-end shape. The second objective was to describe possible differences in the recovery time of teat tissue after machine milking among teats with different teat-end shapes. Holstein cows (n=128) were enrolled in an observational study, housed in free-stall pens with sand bedding and milked three times a day. Ultrasonography of the left front and right hind teat was performed after teat preparation before milking (t-1), immediately after milking (t 0) and 1, 3, 5 and 7 h after milking (t 1, t 3, t 5, t 7). The teat tissue parameters measured from ultrasound scans were teat canal length, teat-end diameter, teat-end diameter at the midpoint between the distal and proximal end of the teat canal, teat wall thickness, and teat cistern width. Teat-end shape was assessed visually and classified into three categories: pointed, flat and round. Multivariable linear regression analyses showed differences in the relative change of teat tissue parameters (compared with t-1) at t 0 among teats with different teat-end shapes, with most parameters showing the largest change for round teats. The premilking values were reached (recovery time) after 7 h in teats with a pointed teat-end shape, whereas recovery time was greater than 7 h in teats with flat and round teat-end shapes. Under the same liner and milking machine conditions, teats with a round teat-end shape had the most severe short-term changes. The results of this observational study indicated that teat-end shape may be one of the factors that contribute to the severity of STC.

The use of point-of-sale machines in school cafeterias as a method of parental influence over child lunch food choices

USDA-ARS?s Scientific Manuscript database

Computerized point-of-sale (POS) machine software that allows parents to place restrictions on their child’s school meal accounts is available. Parents could restrict specific foods (eg, chips), identify specific days the child can purchase extra foods, or set monetary limits. This descriptive study...

A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

PubMed

S K, Somasundaram; P, Alli

2017-11-09

The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to determine the presence of an abnormality in Fundus images (FI) but, the classification process is poorly performed. Recently, few research works have been designed for analyzing texture discrimination capacity in FI to distinguish the healthy images. However, the feature extraction (FE) process was not performed well, due to the high dimensionality. Therefore, to identify retinal features for DR disease diagnosis and early detection using Machine Learning and Ensemble Classification method, called, Machine Learning Bagging Ensemble Classifier (ML-BEC) is designed. The ML-BEC method comprises of two stages. The first stage in ML-BEC method comprises extraction of the candidate objects from Retinal Images (RI). The candidate objects or the features for DR disease diagnosis include blood vessels, optic nerve, neural tissue, neuroretinal rim, optic disc size, thickness and variance. These features are initially extracted by applying Machine Learning technique called, t-distributed Stochastic Neighbor Embedding (t-SNE). Besides, t-SNE generates a probability distribution across high-dimensional images where the images are separated into similar and dissimilar pairs. Then, t-SNE describes a similar probability distribution across the points in the low-dimensional map. This lessens the Kullback-Leibler divergence among two distributions regarding the locations of the points on the map. The second stage comprises of application of ensemble classifiers to the extracted features for providing accurate analysis of digital FI using machine learning. In this stage, an automatic detection of DR screening system using Bagging Ensemble Classifier (BEC) is investigated. With the help of voting the process in ML-BEC, bagging minimizes the error due to variance of the base classifier. With the publicly available retinal image databases, our classifier is trained with 25% of RI. Results show that the ensemble classifier can achieve better classification accuracy (CA) than single classification models. Empirical experiments suggest that the machine learning-based ensemble classifier is efficient for further reducing DR classification time (CT).

Near-Miss Effects on Response Latencies and Win Estimations of Slot Machine Players

ERIC Educational Resources Information Center

Dixon, Mark R.; Schreiber, James E.

2004-01-01

The present study examined the degree to which slot machine near-miss trials, or trials that displayed 2 of 3 winning symbols on the payoff line, affected response times and win estimations of 12 recreational slot machine players. Participants played a commercial slot machine in a casino-like laboratory for course extra-credit points. Videotaped…

A study on using pre-forming blank in single point incremental forming process by finite element analysis

NASA Astrophysics Data System (ADS)

Abass, K. I.

2016-11-01

Single Point Incremental Forming process (SPIF) is a forming technique of sheet material based on layered manufacturing principles. The edges of sheet material are clamped while the forming tool is moved along the tool path. The CNC milling machine is used to manufacturing the product. SPIF involves extensive plastic deformation and the description of the process is more complicated by highly nonlinear boundary conditions, namely contact and frictional effects have been accomplished. However, due to the complex nature of these models, numerical approaches dominated by Finite Element Analysis (FEA) are now in widespread use. The paper presents the data and main results of a study on effect of using preforming blank in SPIF through FEA. The considered SPIF has been studied under certain process conditions referring to the test work piece, tool, etc., applying ANSYS 11. The results show that the simulation model can predict an ideal profile of processing track, the behaviour of contact tool-workpiece, the product accuracy by evaluation its thickness, surface strain and the stress distribution along the deformed blank section during the deformation stages.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Alchemical and structural distribution based representation for universal quantum machine learning

NASA Astrophysics Data System (ADS)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Synthetic hardware performance analysis in virtualized cloud environment for healthcare organization.

PubMed

Tan, Chee-Heng; Teh, Ying-Wah

2013-08-01

The main obstacles in mass adoption of cloud computing for database operations in healthcare organization are the data security and privacy issues. In this paper, it is shown that IT services particularly in hardware performance evaluation in virtual machine can be accomplished effectively without IT personnel gaining access to actual data for diagnostic and remediation purposes. The proposed mechanisms utilized the hypothetical data from TPC-H benchmark, to achieve 2 objectives. First, the underlying hardware performance and consistency is monitored via a control system, which is constructed using TPC-H queries. Second, the mechanism to construct stress-testing scenario is envisaged in the host, using a single or combination of TPC-H queries, so that the resource threshold point can be verified, if the virtual machine is still capable of serving critical transactions at this constraining juncture. This threshold point uses server run queue size as input parameter, and it serves 2 purposes: It provides the boundary threshold to the control system, so that periodic learning of the synthetic data sets for performance evaluation does not reach the host's constraint level. Secondly, when the host undergoes hardware change, stress-testing scenarios are simulated in the host by loading up to this resource threshold level, for subsequent response time verification from real and critical transactions.

Engineering specification and system design for CAD/CAM of custom shoes. Phase 5: UMC involvement (January 1, 1989 - June 30, 1989)

NASA Technical Reports Server (NTRS)

Bao, Han P.

1989-01-01

The CAD/CAM of custom shoes is discussed. The solid object for machining is represented by a wireframe model with its nodes or vertices specified systematically in a grid pattern covering its entire length (point-to-point configuration). Two sets of data from CENCIT and CYBERWARE were used for machining purposes. It was found that the indexing technique (turning the stock by a small angle then moving the tool on a longitudinal path along the foot) yields the best result in terms of ease of programming, savings in wear and tear of the machine and cutting tools, and resolution of fine surface details. The work done using the LASTMOD last design system results in a shoe last specified by a number of congruent surface patches of different sizes. This data format was converted into a form amenable to the machine tool. It involves a series of sorting algorithms and interpolation algorithms to provide the grid pattern that the machine tool needs as was the case in the point to point configuration discussed above. This report also contains an in-depth treatment of the design and production technique of an integrated sole to complement the task of design and manufacture of the shoe last. Clinical data and essential production parameters are discussed. Examples of soles made through this process are given.

Electric field prediction for a human body-electric machine system.

PubMed

Ioannides, Maria G; Papadopoulos, Peter J; Dimitropoulou, Eugenia

2004-01-01

A system consisting of an electric machine and a human body is studied and the resulting electric field is predicted. A 3-phase induction machine operating at full load is modeled considering its geometry, windings, and materials. A human model is also constructed approximating its geometry and the electric properties of tissues. Using the finite element technique the electric field distribution in the human body is determined for a distance of 1 and 5 m from the machine and its effects are studied. Particularly, electric field potential variations are determined at specific points inside the human body and for these points the electric field intensity is computed and compared to the limit values for exposure according to international standards.

SU-C-BRA-04: Automated Segmentation of Head-And-Neck CT Images for Radiotherapy Treatment Planning Via Multi-Atlas Machine Learning (MAML)

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

Ren, X; Gao, H; Sharp, G

Purpose: Accurate image segmentation is a crucial step during image guided radiation therapy. This work proposes multi-atlas machine learning (MAML) algorithm for automated segmentation of head-and-neck CT images. Methods: As the first step, the algorithm utilizes normalized mutual information as similarity metric, affine registration combined with multiresolution B-Spline registration, and then fuses together using the label fusion strategy via Plastimatch. As the second step, the following feature selection strategy is proposed to extract five feature components from reference or atlas images: intensity (I), distance map (D), box (B), center of gravity (C) and stable point (S). The box feature Bmore » is novel. It describes a relative position from each point to minimum inscribed rectangle of ROI. The center-of-gravity feature C is the 3D Euclidean distance from a sample point to the ROI center of gravity, and then S is the distance of the sample point to the landmarks. Then, we adopt random forest (RF) in Scikit-learn, a Python module integrating a wide range of state-of-the-art machine learning algorithms as classifier. Different feature and atlas strategies are used for different ROIs for improved performance, such as multi-atlas strategy with reference box for brainstem, and single-atlas strategy with reference landmark for optic chiasm. Results: The algorithm was validated on a set of 33 CT images with manual contours using a leave-one-out cross-validation strategy. Dice similarity coefficients between manual contours and automated contours were calculated: the proposed MAML method had an improvement from 0.79 to 0.83 for brainstem and 0.11 to 0.52 for optic chiasm with respect to multi-atlas segmentation method (MA). Conclusion: A MAML method has been proposed for automated segmentation of head-and-neck CT images with improved performance. It provides the comparable result in brainstem and the improved result in optic chiasm compared with MA. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less

Robust Fault Diagnosis in Electric Drives Using Machine Learning

DTIC Science & Technology

2004-09-08

detection of fault conditions of the inverter. A machine learning framework is developed to systematically select torque-speed domain operation points...were used to generate various fault condition data for machine learning . The technique is viable for accurate, reliable and fast fault detection in electric drives.

77 FR 38777 - 36(b)(1) Arms Sales Notification

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-29

... Systems (SINCGARS), 200 M2 Chrysler Mount Machine Guns, 400 7.62MM M240 Machine Guns, 12,049,842... Exportable Single Channel Ground and Airborne Radio Systems (SINCGARS), 200 M2 Chrysler Mount Machine Guns, and 400 7.62MM M240 Machine Guns. The possible sale also includes 12,049,842 Ammunition Rounds...

Machined versus roughened immediately loaded and finally restored single implants inserted flapless: Preliminary 6-month data from a split- mouth randomised controlled trial.

PubMed

Cannizzaro, Gioacchino; Felice, Pietro; Loi, Ignazio; Viola, Paolo; Ferri, Vittorio; Leone, Michele; Lazzarini, Matteo; Trullenque-Eriksson, Anna; Esposito, Marco

To compare the outcome of immediately loaded single implants with a machined or a roughened surface. Fifty patients had two implant sites randomly allocated to receive flaplessplaced single Syra implants (Sweden & Martina), one with a machined and one with a roughened surface (sand-blasted with zirconia powder and acid etched), according to a split-mouth design. To be loaded immediately, implants had to be inserted with a torque superior to 50 Ncm. Implants were restored with definitive crowns in direct occlusal contact within 48 h. Patients were followed for 6 months after loading. Outcome measures were prosthetic and implant failures and complications. Two machined implants and four roughened implants were not loaded immediately. Six months after loading no dropout occurred. One implant loaded late, which had a rough implant surface, failed 20 days after loading (P (McNemar test) = 0.625; difference in proportions = -0.04; 95% CI: -0.15 to 0.07). Three crowns had to be remade on machined implants and four on roughened implants (P (McNemar test) = 1.000; difference in proportions = -0.02; 95% CI: -0.12 to 0.08). Three machined and five roughened implants experienced complications (P (McNemar test) = 0.625; difference in proportions = -0.04; 95% CI: -0.15 to 0.07). There were no statistically significant differences between groups for crown and implant losses as well as complications. Up to 6 months after loading both machined and roughened flapless-placed and immediately loaded single implants provided good and similar results, however, longer follow-ups are needed to evaluate the long-term prognosis of implants with different surfaces.

41 CFR 50-204.5 - Machine guarding.

Code of Federal Regulations, 2011 CFR

2011-07-01

... usually require point of operation guarding: Guillotine cutters. Shears. Alligator shears. Power presses. Milling machines. Power saws. Jointers. Portable power tools. Forming rolls and calenders. (d) Revolving...

Multi-Point Thomson Scattering Diagnostic for the Helicity Injected Torus

NASA Astrophysics Data System (ADS)

Liptac, J. E.; Smith, R. J.; Hoffman, C. S.; Jarboe, T. R.; Nelson, B. A.; Leblanc, B. P.; Phillips, P.

1999-11-01

The multi-point Thomson scattering system on the Helicity Injected Torus--II can determine electron temperature and density at 11 radial positions at a single time during the plasma discharge. The system includes components on loan from both PPPL and from the University of Texas. The collection optics and Littrow spectrometer from Princeton, and the 1 GW laser and multi-anode microchannel plate detector from Texas have been integrated into a compact structure, creating a mobile and reliable diagnostic. The mobility of the system allows alignment to occur in a room adjacent to the experiment, greatly reducing the disturbance to normal machine operation. The four main parts of the Thomson scattering system, namely, the laser, the beam line, the collection optics, and the mobile structure are presented and discussed.

A group communication approach for mobile computing mobile channel: An ISIS tool for mobile services

NASA Astrophysics Data System (ADS)

Cho, Kenjiro; Birman, Kenneth P.

1994-05-01

This paper examines group communication as an infrastructure to support mobility of users, and presents a simple scheme to support user mobility by means of switching a control point between replicated servers. We describe the design and implementation of a set of tools, called Mobile Channel, for use with the ISIS system. Mobile Channel is based on a combination of the two replication schemes: the primary-backup approach and the state machine approach. Mobile Channel implements a reliable one-to-many FIFO channel, in which a mobile client sees a single reliable server; servers, acting as a state machine, see multicast messages from clients. Migrations of mobile clients are handled as an intentional primary switch, and hand-offs or server failures are completely masked to mobile clients. To achieve high performance, servers are replicated at a sliding-window level. Our scheme provides a simple abstraction of migration, eliminates complicated hand-off protocols, provides fault-tolerance and is implemented within the existing group communication mechanism.

Autonomous proximity operations using machine vision for trajectory control and pose estimation

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Sternberg, Stanley R.

1991-01-01

A machine vision algorithm was developed which permits guidance control to be maintained during autonomous proximity operations. At present this algorithm exists as a simulation, running upon an 80386 based personal computer, using a ModelMATE CAD package to render the target vehicle. However, the algorithm is sufficiently simple, so that following off-line training on a known target vehicle, it should run in real time with existing vision hardware. The basis of the algorithm is a sequence of single camera images of the target vehicle, upon which radial transforms were performed. Selected points of the resulting radial signatures are fed through a decision tree, to determine whether the signature matches that of the known reference signatures for a particular view of the target. Based upon recognized scenes, the position of the maneuvering vehicle with respect to the target vehicles can be calculated, and adjustments made in the former's trajectory. In addition, the pose and spin rates of the target satellite can be estimated using this method.

Computational complexity of symbolic dynamics at the onset of chaos

NASA Astrophysics Data System (ADS)

Lakdawala, Porus

1996-05-01

In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

Usage of CT data in biomechanical research

NASA Astrophysics Data System (ADS)

Safonov, Roman A.; Golyadkina, Anastasiya A.; Kirillova, Irina V.; Kossovich, Leonid Y.

2017-02-01

Object of study: The investigation is focused on development of personalized medicine. The determination of mechanical properties of bone tissues based on in vivo data was considered. Methods: CT, MRI, natural experiments on versatile test machine Instron 5944, numerical experiments using Python programs. Results: The medical diagnostics methods, which allows determination of mechanical properties of bone tissues based on in vivo data. The series of experiments to define the values of mechanical parameters of bone tissues. For one and the same sample, computed tomography (CT), magnetic resonance imaging (MRI), ultrasonic investigations and mechanical experiments on single-column test machine Instron 5944 were carried out. The computer program for comparison of CT and MRI images was created. The grayscale values in the same points of the samples were determined on both CT and MRI images. The Haunsfield grayscale values were used to determine rigidity (Young module) and tensile strength of the samples. The obtained data was compared to natural experiments results for verification.

Biomechanical and magnetic resonance imaging evaluation of a single- and double-row rotator cuff repair in an in vivo sheep model.

PubMed

Baums, Mike H; Spahn, Gunter; Buchhorn, Gottfried H; Schultz, Wolfgang; Hofmann, Lars; Klinger, Hans-Michael

2012-06-01

To investigate the biomechanical and magnetic resonance imaging (MRI)-derived morphologic changes between single- and double-row rotator cuff repair at different time points after fixation. Eighteen mature female sheep were randomly assigned to either a single-row treatment group using arthroscopic Mason-Allen stitches or a double-row treatment group using a combination of arthroscopic Mason-Allen and mattress stitches. Each group was analyzed at 1 of 3 survival points (6 weeks, 12 weeks, and 26 weeks). We evaluated the integrity of the cuff repair using MRI and biomechanical properties using a mechanical testing machine. The mean load to failure was significantly higher in the double-row group compared with the single-row group at 6 and 12 weeks (P = .018 and P = .002, respectively). At 26 weeks, the differences were not statistically significant (P = .080). However, the double-row group achieved a mean load to failure similar to that of a healthy infraspinatus tendon, whereas the single-row group reached only 70% of the load of a healthy infraspinatus tendon. No significant morphologic differences were observed based on the MRI results. This study confirms that in an acute repair model, double-row repair may enhance the speed of mechanical recovery of the tendon-bone complex when compared with single-row repair in the early postoperative period. Double-row rotator cuff repair enables higher mechanical strength that is especially sustained during the early recovery period and may therefore improve clinical outcome. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

Visualization of Unsteady Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Haimes, Robert

1997-01-01

The current compute environment that most researchers are using for the calculation of 3D unsteady Computational Fluid Dynamic (CFD) results is a super-computer class machine. The Massively Parallel Processors (MPP's) such as the 160 node IBM SP2 at NAS and clusters of workstations acting as a single MPP (like NAS's SGI Power-Challenge array and the J90 cluster) provide the required computation bandwidth for CFD calculations of transient problems. If we follow the traditional computational analysis steps for CFD (and we wish to construct an interactive visualizer) we need to be aware of the following: (1) Disk space requirements. A single snap-shot must contain at least the values (primitive variables) stored at the appropriate locations within the mesh. For most simple 3D Euler solvers that means 5 floating point words. Navier-Stokes solutions with turbulence models may contain 7 state-variables. (2) Disk speed vs. Computational speeds. The time required to read the complete solution of a saved time frame from disk is now longer than the compute time for a set number of iterations from an explicit solver. Depending, on the hardware and solver an iteration of an implicit code may also take less time than reading the solution from disk. If one examines the performance improvements in the last decade or two, it is easy to see that depending on disk performance (vs. CPU improvement) may not be the best method for enhancing interactivity. (3) Cluster and Parallel Machine I/O problems. Disk access time is much worse within current parallel machines and cluster of workstations that are acting in concert to solve a single problem. In this case we are not trying to read the volume of data, but are running the solver and the solver outputs the solution. These traditional network interfaces must be used for the file system. (4) Numerics of particle traces. Most visualization tools can work upon a single snap shot of the data but some visualization tools for transient problems require dealing with time.

[A new machinability test machine and the machinability of composite resins for core built-up].

PubMed

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Single product lot-sizing on unrelated parallel machines with non-decreasing processing times

NASA Astrophysics Data System (ADS)

Eremeev, A.; Kovalyov, M.; Kuznetsov, P.

2018-01-01

We consider a problem in which at least a given quantity of a single product has to be partitioned into lots, and lots have to be assigned to unrelated parallel machines for processing. In one version of the problem, the maximum machine completion time should be minimized, in another version of the problem, the sum of machine completion times is to be minimized. Machine-dependent lower and upper bounds on the lot size are given. The product is either assumed to be continuously divisible or discrete. The processing time of each machine is defined by an increasing function of the lot volume, given as an oracle. Setup times and costs are assumed to be negligibly small, and therefore, they are not considered. We derive optimal polynomial time algorithms for several special cases of the problem. An NP-hard case is shown to admit a fully polynomial time approximation scheme. An application of the problem in energy efficient processors scheduling is considered.

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

Ramli, Nor Azuana; Ismail, Mohd Tahir; Wooi, Hooy Chee

2014-07-01

There are many methods that had been experimented in the analysis of currency crisis. However, not all methods could provide accurate indications. This paper introduces an ensemble of classifiers by using Support Vector Machine that's never been applied in analyses involving currency crisis before with the aim of increasing the indication accuracy. The proposed ensemble classifiers' performances are measured using percentage of accuracy, root mean squared error (RMSE), area under the Receiver Operating Characteristics (ROC) curve and Type II error. The performances of an ensemble of Support Vector Machine classifiers are compared with the single Support Vector Machine classifier and both of classifiers are tested on the data set from 27 countries with 12 macroeconomic indicators for each country. From our analyses, the results show that the ensemble of Support Vector Machine classifiers outperforms single Support Vector Machine classifier on the problem involving indicating a currency crisis in terms of a range of standard measures for comparing the performance of classifiers.

Prediction of successful memory encoding based on single-trial rhinal and hippocampal phase information.

PubMed

Höhne, Marlene; Jahanbekam, Amirhossein; Bauckhage, Christian; Axmacher, Nikolai; Fell, Juergen

2016-10-01

Mediotemporal EEG characteristics are closely related to long-term memory formation. It has been reported that rhinal and hippocampal EEG measures reflecting the stability of phases across trials are better suited to distinguish subsequently remembered from forgotten trials than event-related potentials or amplitude-based measures. Theoretical models suggest that the phase of EEG oscillations reflects neural excitability and influences cellular plasticity. However, while previous studies have shown that the stability of phase values across trials is indeed a relevant predictor of subsequent memory performance, the effect of absolute single-trial phase values has been little explored. Here, we reanalyzed intracranial EEG recordings from the mediotemporal lobe of 27 epilepsy patients performing a continuous word recognition paradigm. Two-class classification using a support vector machine was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies and time points. We demonstrate that it is possible to successfully predict single-trial memory formation in the majority of patients (23 out of 27) based on only three single-trial phase values given by a rhinal phase, a hippocampal phase, and a rhinal-hippocampal phase difference. Overall classification accuracy across all subjects was 69.2% choosing frequencies from the range between 0.5 and 50Hz and time points from the interval between -0.5s and 2s. For 19 patients, above chance prediction of subsequent memory was possible even when choosing only time points from the prestimulus interval (overall accuracy: 65.2%). Furthermore, prediction accuracies based on single-trial phase surpassed those based on single-trial power. Our results confirm the functional relevance of mediotemporal EEG phase for long-term memory operations and suggest that phase information may be utilized for memory enhancement applications based on deep brain stimulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Methods, systems and apparatus for optimization of third harmonic current injection in a multi-phase machine

DOEpatents

Gallegos-Lopez, Gabriel

2012-10-02

Methods, system and apparatus are provided for increasing voltage utilization in a five-phase vector controlled machine drive system that employs third harmonic current injection to increase torque and power output by a five-phase machine. To do so, a fundamental current angle of a fundamental current vector is optimized for each particular torque-speed of operating point of the five-phase machine.

A new self-regulated self-excited single-phase induction generator using a squirrel cage three-phase induction machine

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

Fukami, Tadashi; Imamura, Michinori; Kaburaki, Yuichi

1995-12-31

A new single-phase capacitor self-excited induction generator with self-regulating feature is presented. The new generator consists of a squirrel cage three-phase induction machine and three capacitors connected in series and parallel with a single phase load. The voltage regulation of this generator is very small due to the effect of the three capacitors. Moreover, since a Y-connected stator winding is employed, the waveform of the output voltage becomes sinusoidal. In this paper the system configuration and the operating principle of the new generator are explained, and the basic characteristics are also investigated by means of a simple analysis and experimentsmore » with a laboratory machine.« less

Single instruction computer architecture and its application in image processing

NASA Astrophysics Data System (ADS)

Laplante, Phillip A.

1992-03-01

A single processing computer system using only half-adder circuits is described. In addition, it is shown that only a single hard-wired instruction is needed in the control unit to obtain a complete instruction set for this general purpose computer. Such a system has several advantages. First it is intrinsically a RISC machine--in fact the 'ultimate RISC' machine. Second, because only a single type of logic element is employed the entire computer system can be easily realized on a single, highly integrated chip. Finally, due to the homogeneous nature of the computer's logic elements, the computer has possible implementations as an optical or chemical machine. This in turn suggests possible paradigms for neural computing and artificial intelligence. After showing how we can implement a full-adder, min, max and other operations using the half-adder, we use an array of such full-adders to implement the dilation operation for two black and white images. Next we implement the erosion operation of two black and white images using a relative complement function and the properties of erosion and dilation. This approach was inspired by papers by van der Poel in which a single instruction is used to furnish a complete set of general purpose instructions and by Bohm- Jacopini where it is shown that any problem can be solved using a Turing machine with one entry and one exit.

The Use of Point-of-Sale Machines in School Cafeterias as a Method of Parental Influence over Child Lunch Food Choices

ERIC Educational Resources Information Center

Andrepont, Emmy; Cullen, Karen W.; Taylor, Wendell C.

2011-01-01

Background: Computerized point-of-sale (POS) machine software that allows parents to place restrictions on their child's school meal accounts is available. Parents could restrict specific foods (e.g., chips), identify specific days the child can purchase extra foods, or set monetary limits. This descriptive study examines the use of parental…

Cutting efficiency of air-turbine burs on cast titanium and dental casting alloys.

PubMed

Watanabe, I; Ohkubo, C; Ford, J P; Atsuta, M; Okabe, T

2000-11-01

The purpose of this study was to investigate the cutting efficiency of air-turbine burs on cast free-machining titanium alloy (DT2F) and to compare the results with those for cast commercially pure (CP) Ti, Ti-6Al-4V alloy, and dental casting alloys. The cast metal (DT2F, CP Ti, Ti-6Al-4V, Type IV gold alloy and Co-Cr alloy) specimens were cut with air-turbine burs (carbide burs and diamond points) at air pressures of 138 or 207 kPa and a cutting force of 0.784 N. The cutting efficiency of each bur was evaluated as volume loss calculated from the weight loss cut for 5 s and the density of each metal. The bulk microhardness was measured to correlate the machinability and the hardness of each metal. The amounts of DT2F cut with the carbide burs were significantly (p < 0.05) greater than for the other titanium specimens at either 138 or 207 kPa. The diamond points exhibited similar machining efficiency among all metals except for Type IV gold alloy. The increase in the volume loss of Co-Cr alloy (Vitallium) cut with the diamond points showed a negative value (-29%) with an increase in air pressure from 138 to 207 kPa. There was a negative correlation between the amounts of metal removed (volume loss) and the hardness (r2 = 0.689) when the carbide burs were used. The results of this study indicated that a free-machining titanium alloy (DT2F) exhibited better machinability compared to CP Ti and Ti-6Al-4V alloy when using carbide fissure burs. When machining cast CP Ti and its alloys, carbide fissure burs possessed a greater machining efficiency than the diamond points and are recommended for titanium dental prostheses.

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults

PubMed Central

Verschueren, Sabine M. P.; Degens, Hans; Morse, Christopher I.; Onambélé, Gladys L.

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual’s physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry. PMID:29155839

Performance of thigh-mounted triaxial accelerometer algorithms in objective quantification of sedentary behaviour and physical activity in older adults.

PubMed

Wullems, Jorgen A; Verschueren, Sabine M P; Degens, Hans; Morse, Christopher I; Onambélé, Gladys L

2017-01-01

Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promising future alternative. Hence, the current study compared between cut-off point and machine learning algorithms, for optimal quantification of sedentary behaviour and physical activity intensities in the elderly. Thus, in a heterogeneous sample of forty participants (aged ≥60 years, 50% female) energy expenditure during laboratory-based activities (ranging from sedentary behaviour through to moderate-to-vigorous physical activity) was estimated by indirect calorimetry, whilst wearing triaxial thigh-mounted accelerometers. Three cut-off point algorithms and a Random Forest machine learning model were developed and cross-validated using the collected data. Detailed analyses were performed to check algorithm robustness, and examine and benchmark both overall and participant-specific balanced accuracies. This revealed that the four models can at least be used to confidently monitor sedentary behaviour and moderate-to-vigorous physical activity. Nevertheless, the machine learning algorithm outperformed the cut-off point models by being robust for all individual's physiological and non-physiological characteristics and showing more performance of an acceptable level over the whole range of physical activity intensities. Therefore, we propose that Random Forest machine learning may be optimal for objective assessment of sedentary behaviour and physical activity in older adults using thigh-mounted triaxial accelerometry.

An asymptotical machine

NASA Astrophysics Data System (ADS)

Cristallini, Achille

2016-07-01

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

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

PubMed

Liu, Shelley H; Bobb, Jennifer F; Lee, Kyu Ha; Gennings, Chris; Claus Henn, Birgit; Bellinger, David; Austin, Christine; Schnaas, Lourdes; Tellez-Rojo, Martha M; Hu, Howard; Wright, Robert O; Arora, Manish; Coull, Brent A

2018-07-01

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

Single molecule thermodynamics in biological motors.

PubMed

Taniguchi, Yuichi; Karagiannis, Peter; Nishiyama, Masayoshi; Ishii, Yoshiharu; Yanagida, Toshio

2007-04-01

Biological molecular machines use thermal activation energy to carry out various functions. The process of thermal activation has the stochastic nature of output events that can be described according to the laws of thermodynamics. Recently developed single molecule detection techniques have allowed each distinct enzymatic event of single biological machines to be characterized providing clues to the underlying thermodynamics. In this study, the thermodynamic properties in the stepping movement of a biological molecular motor have been examined. A single molecule detection technique was used to measure the stepping movements at various loads and temperatures and a range of thermodynamic parameters associated with the production of each forward and backward step including free energy, enthalpy, entropy and characteristic distance were obtained. The results show that an asymmetry in entropy is a primary factor that controls the direction in which the motor will step. The investigation on single molecule thermodynamics has the potential to reveal dynamic properties underlying the mechanisms of how biological molecular machines work.

Development of a rapid and sensitive one-step reverse transcription-nested polymerase chain reaction in a single tube using the droplet-polymerase chain reaction machine.

PubMed

Yamaguchi, Akemi; Matsuda, Kazuyuki; Sueki, Akane; Taira, Chiaki; Uehara, Masayuki; Saito, Yasunori; Honda, Takayuki

2015-08-25

Reverse transcription (RT)-nested polymerase chain reaction (PCR) is a time-consuming procedure because it has several handling steps and is associated with the risk of cross-contamination during each step. Therefore, a rapid and sensitive one-step RT-nested PCR was developed that could be performed in a single tube using a droplet-PCR machine. The K562 BCR-ABL mRNA-positive cell line as well as bone marrow aspirates from 5 patients with chronic myelogenous leukemia (CML) and 5 controls without CML were used. We evaluated one-step RT-nested PCR using the droplet-PCR machine. One-step RT-nested PCR performed in a single tube using the droplet-PCR machine enabled the detection of BCR-ABL mRNA within 40min, which was 10(3)-fold superior to conventional RT nested PCR using three steps in separate tubes. The sensitivity of the one-step RT-nested PCR was 0.001%, with sample reactivity comparable to that of the conventional assay. One-step RT-nested PCR was developed using the droplet-PCR machine, which enabled all reactions to be performed in a single tube accurately and rapidly and with high sensitivity. This one-step RT-nested PCR may be applicable to a wide spectrum of genetic tests in clinical laboratories. Copyright © 2015 Elsevier B.V. All rights reserved.

DOE-RCT-0003641 Final Technical Report

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

Wagner, Edward; Lesster, Ted

2014-07-30

This program studied novel concepts for an Axial Flux Reluctance Machine to capture energy from marine hydrokinetic sources and compared their attributes to a Radial Flux Reluctance Machine which was designed under a prior Department of Energy program for the same application. Detailed electromagnetic and mechanical analyses were performed to determine the validity of the concept and to provide a direct comparison with the existing conventional Radial Flux Switched Reluctance Machine designed during the Advanced Wave Energy Conversion Project, DE-EE0003641. The alternate design changed the machine topology so that the flux that is switched flows axially rather than radially andmore » the poles themselves are long radially, as opposed to the radial flux machine that has pole pieces that are long axially. It appeared possible to build an axial flux machine that should be considerably more compact than the radial machine. In an “apples to apples” comparison, the same rules with regard to generating magnetic force and the fundamental limitations of flux density hold, so that at the heart of the machine the same torque equations hold. The differences are in the mechanical configuration that limits or enhances the change of permeance with rotor position, in the amount of permeable iron required to channel the flux via the pole pieces to the air-gaps, and in the sizing and complexity of the electrical winding. Accordingly it was anticipated that the magnetic component weight would be similar but that better use of space would result in a shorter machine with accompanying reduction in housing and support structure. For the comparison the pole count was kept the same at 28 though it was also expected that the radial tapering of the slots between pole pieces would permit a higher pole count machine, enabling the generation of greater power at a given speed in some future design. The baseline Radial Flux Machine design was established during the previous DOE program. Its characteristics were tabulated for use in comparing to the Axial Flux Machine. Three basic conceptual designs for the Axial Flux Machine were considered: (1) a machine with a single coil at the inner diameter of the machine, (2) a machine with a single coil at the outside diameter of the machine, and (3) a machine with a coil around each tooth. Slight variations of these basic configurations were considered during the study. Analysis was performed on these configurations to determine the best candidate design to advance to preliminary design, based on size, weight, performance, cost and manufacturability. The configuration selected as the most promising was the multi-pole machine with a coil around each tooth. This configuration provided the least complexity with respect to the mechanical configuration and manufacturing, which would yield the highest reliability and lowest cost machine of the three options. A preliminary design was performed on this selected configuration. For this first ever axial design of the multi rotor configuration the 'apples to apples' comparison was based on using the same length of rotor pole as the axial length of rotor pole in the radial machine and making the mean radius of the rotor in the axial machine the same as the air gap radius in the radial machine. The tooth to slot ratio at the mean radius of the axial machine was the same as the tooth to slot ratio of the radial machine. The comparison between the original radial flux machine and the new axial flux machine indicates that for the same torque, the axial flux machine diameter will be 27% greater, but it will have 30% of the length, and 76% of the weight. Based on these results, it is concluded that an axial flux reluctance machine presents a viable option for large generators to be used for the capture of wave energy. In the analysis of Task 4, below, it is pointed out that our selection of dimensional similarity for the 'apples to apples' comparison did not produce an optimum axial flux design. There is torque capability to spare, implying we could reduce the magnetic structure, but the winding area, constrained by the pole separation at the inner pole radius has a higher resistance than desirable, implying we need more room for copper. The recommendation is to proceed via one cycle of optimization and review to correct this unbalance and then proceed to a detailed design phase to produce manufacturing drawings, followed by the construction of a prototype to test the performance of the machine against predicted results.« less

Springback effects during single point incremental forming: Optimization of the tool path

NASA Astrophysics Data System (ADS)

Giraud-Moreau, Laurence; Belchior, Jérémy; Lafon, Pascal; Lotoing, Lionel; Cherouat, Abel; Courtielle, Eric; Guines, Dominique; Maurine, Patrick

2018-05-01

Incremental sheet forming is an emerging process to manufacture sheet metal parts. This process is more flexible than conventional one and well suited for small batch production or prototyping. During the process, the sheet metal blank is clamped by a blank-holder and a small-size smooth-end hemispherical tool moves along a user-specified path to deform the sheet incrementally. Classical three-axis CNC milling machines, dedicated structure or serial robots can be used to perform the forming operation. Whatever the considered machine, large deviations between the theoretical shape and the real shape can be observed after the part unclamping. These deviations are due to both the lack of stiffness of the machine and residual stresses in the part at the end of the forming stage. In this paper, an optimization strategy of the tool path is proposed in order to minimize the elastic springback induced by residual stresses after unclamping. A finite element model of the SPIF process allowing the shape prediction of the formed part with a good accuracy is defined. This model, based on appropriated assumptions, leads to calculation times which remain compatible with an optimization procedure. The proposed optimization method is based on an iterative correction of the tool path. The efficiency of the method is shown by an improvement of the final shape.

Diamond Machining of an Off-Axis Biconic Aspherical Mirror

NASA Technical Reports Server (NTRS)

Ohl, Raymond G.; Preuss, Werner; Sohn, Alex; MacKenty, John

2009-01-01

Two diamond-machining methods have been developed as part of an effort to design and fabricate an off-axis, biconic ellipsoidal, concave aluminum mirror for an infrared spectrometer at the Kitt Peak National Observatory. Beyond this initial application, the methods can be expected to enable satisfaction of requirements for future instrument mirrors having increasingly complex (including asymmetrical), precise shapes that, heretofore, could not readily be fabricated by diamond machining or, in some cases, could not be fabricated at all. In the initial application, the mirror is prescribed, in terms of Cartesian coordinates x and y, by aperture dimensions of 94 by 76 mm, placements of -2 mm off axis in x and 227 mm off axis in y, an x radius of curvature of 377 mm, a y radius of curvature of 407 mm, an x conic constant of 0.078, and a y conic constant of 0.127. The aspect ratio of the mirror blank is about 6. One common, "diamond machining" process uses single-point diamond turning (SPDT). However, it is impossible to generate the required off-axis, biconic ellipsoidal shape by conventional SPDT because (1) rotational symmetry is an essential element of conventional SPDT and (2) the present off-axis biconic mirror shape lacks rotational symmetry. Following conventional practice, it would be necessary to make this mirror from a glass blank by computer-controlled polishing, which costs more than diamond machining and yields a mirror that is more difficult to mount to a metal bench. One of the two present diamond machining methods involves the use of an SPDT machine equipped with a fast tool servo (FTS). The SPDT machine is programmed to follow the rotationally symmetric asphere that best fits the desired off-axis, biconic ellipsoidal surface. The FTS is actuated in synchronism with the rotation of the SPDT machine to generate the difference between the desired surface and the best-fit rotationally symmetric asphere. In order to minimize the required stroke of the FTS, the blanks were positioned at a large off-axis distance and angle, and the axis of the FTS was not parallel to the axis of the spindle of the SPDT machine. The spindle was rotated at a speed of 120 rpm, and the maximum FTS speed was 8.2 mm/s.

Model-OA wind turbine generator - Failure modes and effects analysis

NASA Technical Reports Server (NTRS)

Klein, William E.; Lali, Vincent R.

1990-01-01

The results failure modes and effects analysis (FMEA) conducted for wind-turbine generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems, which are also reflected in this FMEA.

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

Forest, E.; Hirata, Kohji

A methodological discussion is given for single particle beam dynamics in circular machines. The discussions are introductory, but (or, even therefore) we avoid to rely on too much simplified concepts. We treat things from a very general and fundamental point of view, because this is the easiest and rightest way to teach how to simulate particle motion and how to analyze its results. We give some principles of particle tracking free from theoretical prejudices. We also introduce some transparent methods to deduce the necessary information from the tracking: many of the traditional beam-dynamics concepts can be abstracted from them asmore » approximate quantities which are valid in certain limiting cases.« less

Model 0A wind turbine generator FMEA

NASA Technical Reports Server (NTRS)

Klein, William E.; Lalli, Vincent R.

1989-01-01

The results of Failure Modes and Effects Analysis (FMEA) conducted for the Wind Turbine Generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems which are also reflected in this FMEA.

Relative optical navigation around small bodies via Extreme Learning Machine

NASA Astrophysics Data System (ADS)

Law, Andrew M.

To perform close proximity operations under a low-gravity environment, relative and absolute positions are vital information to the maneuver. Hence navigation is inseparably integrated in space travel. Extreme Learning Machine (ELM) is presented as an optical navigation method around small celestial bodies. Optical Navigation uses visual observation instruments such as a camera to acquire useful data and determine spacecraft position. The required input data for operation is merely a single image strip and a nadir image. ELM is a machine learning Single Layer feed-Forward Network (SLFN), a type of neural network (NN). The algorithm is developed on the predicate that input weights and biases can be randomly assigned and does not require back-propagation. The learned model is the output layer weights which are used to calculate a prediction. Together, Extreme Learning Machine Optical Navigation (ELM OpNav) utilizes optical images and ELM algorithm to train the machine to navigate around a target body. In this thesis the asteroid, Vesta, is the designated celestial body. The trained ELMs estimate the position of the spacecraft during operation with a single data set. The results show the approach is promising and potentially suitable for on-board navigation.

Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor.

PubMed

Sa, Jaewon; Choi, Younchang; Chung, Yongwha; Kim, Hee-Young; Park, Daihee; Yoon, Sukhan

2017-01-29

Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect-using electric current shape analysis-for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between "does-not-need-to-be-replaced" and "needs-to-be-replaced" shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification.

Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor

PubMed Central

Sa, Jaewon; Choi, Younchang; Chung, Yongwha; Kim, Hee-Young; Park, Daihee; Yoon, Sukhan

2017-01-01

Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect—using electric current shape analysis—for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between “does-not-need-to-be-replaced” and “needs-to-be-replaced” shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification. PMID:28146057

Determination of real machine-tool settings and minimization of real surface deviation by computerized inspection

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Kuan, Chihping; Zhang, YI

1991-01-01

A numerical method is developed for the minimization of deviations of real tooth surfaces from the theoretical ones. The deviations are caused by errors of manufacturing, errors of installment of machine-tool settings and distortion of surfaces by heat-treatment. The deviations are determined by coordinate measurements of gear tooth surfaces. The minimization of deviations is based on the proper correction of initially applied machine-tool settings. The contents of accomplished research project cover the following topics: (1) Descriptions of the principle of coordinate measurements of gear tooth surfaces; (2) Deviation of theoretical tooth surfaces (with examples of surfaces of hypoid gears and references for spiral bevel gears); (3) Determination of the reference point and the grid; (4) Determination of the deviations of real tooth surfaces at the points of the grid; and (5) Determination of required corrections of machine-tool settings for minimization of deviations. The procedure for minimization of deviations is based on numerical solution of an overdetermined system of n linear equations in m unknowns (m much less than n ), where n is the number of points of measurements and m is the number of parameters of applied machine-tool settings to be corrected. The developed approach is illustrated with numerical examples.

Tool simplifies machining of pipe ends for precision welding

NASA Technical Reports Server (NTRS)

Matus, S. T.

1969-01-01

Single tool prepares a pipe end for precision welding by simultaneously performing internal machining, end facing, and bevel cutting to specification standards. The machining operation requires only one milling adjustment, can be performed quickly, and produces the high quality pipe-end configurations required to ensure precision-welded joints.

Abstract quantum computing machines and quantum computational logics

NASA Astrophysics Data System (ADS)

Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto

2016-06-01

Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.

Design and Development of an Engineering Prototype Compact X-Ray Scanner (FMS 5000)

DTIC Science & Technology

1989-03-31

machined by "wire-EDM" (electro discharge machining ). Three different slice thicknesses can be selected from the scan menu. The set of slice thicknesses...circuit. This type of circuit is used whenever more than ten kilowatts of power are needed by a machine . For example, lathes and milling machines in a... machine shop usually use this type of input power. A three- phase circuit delivers power more efficiently than a single-phase circuit because three

Three-point compound sine plate offers cost and weight savings

NASA Technical Reports Server (NTRS)

Barras, A. P.

1972-01-01

Work piece adjustment fixture reduces size, weight and set-up complexity of alignment platforms used in metal blank machining. Design benefits designers and manufacturers of machine tools and measuring equipment.

MACHINE ROOM FROM DOORWAY TO COMMUNICATIONS ROOM, VIEW FACING SOUTHWEST. ...

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

MACHINE ROOM FROM DOORWAY TO COMMUNICATIONS ROOM, VIEW FACING SOUTHWEST. - Naval Air Station Barbers Point, World War II Command Center, Midway Street east of Lexington Avenue, Ewa, Honolulu County, HI

Software platform virtualization in chemistry research and university teaching

PubMed Central

2009-01-01

Background Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Results Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Conclusion Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide. PMID:20150997

Software platform virtualization in chemistry research and university teaching.

PubMed

Kind, Tobias; Leamy, Tim; Leary, Julie A; Fiehn, Oliver

2009-11-16

Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide.

VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

NASA Astrophysics Data System (ADS)

Ostrovski, Fernanda; McMahon, Richard G.; Connolly, Andrew J.; Lemon, Cameron A.; Auger, Matthew W.; Banerji, Manda; Hung, Johnathan M.; Koposov, Sergey E.; Lidman, Christopher E.; Reed, Sophie L.; Allam, Sahar; Benoit-Lévy, Aurélien; Bertin, Emmanuel; Brooks, David; Buckley-Geer, Elizabeth; Carnero Rosell, Aurelio; Carrasco Kind, Matias; Carretero, Jorge; Cunha, Carlos E.; da Costa, Luiz N.; Desai, Shantanu; Diehl, H. Thomas; Dietrich, Jörg P.; Evrard, August E.; Finley, David A.; Flaugher, Brenna; Fosalba, Pablo; Frieman, Josh; Gerdes, David W.; Goldstein, Daniel A.; Gruen, Daniel; Gruendl, Robert A.; Gutierrez, Gaston; Honscheid, Klaus; James, David J.; Kuehn, Kyler; Kuropatkin, Nikolay; Lima, Marcos; Lin, Huan; Maia, Marcio A. G.; Marshall, Jennifer L.; Martini, Paul; Melchior, Peter; Miquel, Ramon; Ogando, Ricardo; Plazas Malagón, Andrés; Reil, Kevin; Romer, Kathy; Sanchez, Eusebio; Santiago, Basilio; Scarpine, Vic; Sevilla-Noarbe, Ignacio; Soares-Santos, Marcelle; Sobreira, Flavia; Suchyta, Eric; Tarle, Gregory; Thomas, Daniel; Tucker, Douglas L.; Walker, Alistair R.

2017-03-01

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with IAB = 18.61 and IAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θE ˜ 1.47 arcsec, enclosed mass Menc ˜ 4 × 1011 M⊙ and a time delay of ˜52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.

Towards a molecular logic machine

NASA Astrophysics Data System (ADS)

Remacle, F.; Levine, R. D.

2001-06-01

Finite state logic machines can be realized by pump-probe spectroscopic experiments on an isolated molecule. The most elaborate setup, a Turing machine, can be programmed to carry out a specific computation. We argue that a molecule can be similarly programmed, and provide examples using two photon spectroscopies. The states of the molecule serve as the possible states of the head of the Turing machine and the physics of the problem determines the possible instructions of the program. The tape is written in an alphabet that allows the listing of the different pump and probe signals that are applied in a given experiment. Different experiments using the same set of molecular levels correspond to different tapes that can be read and processed by the same head and program. The analogy to a Turing machine is not a mechanical one and is not completely molecular because the tape is not part of the molecular machine. We therefore also discuss molecular finite state machines, such as sequential devices, for which the tape is not part of the machine. Nonmolecular tapes allow for quite long input sequences with a rich alphabet (at the level of 7 bits) and laser pulse shaping experiments provide concrete examples. Single molecule spectroscopies show that a single molecule can be repeatedly cycled through a logical operation.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Practical aspects of the use of three-phase alternating current electric machines in electricity storage system

NASA Astrophysics Data System (ADS)

Ciucur, Violeta

2015-02-01

Of three-phase alternating current electric machines, it brings into question which of them is more advantageous to be used in electrical energy storage system by pumping water. The two major categories among which are given dispute are synchronous and the asynchronous machine. To consider the synchronous machine with permanent magnet configuration because it brings advantages compared with conventional synchronous machine, first by removing the necessary additional excitation winding. From the point of view of loss of the two types of machines, the optimal adjustment of the magnetic flux density is obtained to minimize the copper loss by hysteresis and eddy currents.

Affine Transform to Reform Pixel Coordinates of EOG Signals for Controlling Robot Manipulators Using Gaze Motions

PubMed Central

Rusydi, Muhammad Ilhamdi; Sasaki, Minoru; Ito, Satoshi

2014-01-01

Biosignals will play an important role in building communication between machines and humans. One of the types of biosignals that is widely used in neuroscience are electrooculography (EOG) signals. An EOG has a linear relationship with eye movement displacement. Experiments were performed to construct a gaze motion tracking method indicated by robot manipulator movements. Three operators looked at 24 target points displayed on a monitor that was 40 cm in front of them. Two channels (Ch1 and Ch2) produced EOG signals for every single eye movement. These signals were converted to pixel units by using the linear relationship between EOG signals and gaze motion distances. The conversion outcomes were actual pixel locations. An affine transform method is proposed to determine the shift of actual pixels to target pixels. This method consisted of sequences of five geometry processes, which are translation-1, rotation, translation-2, shear and dilatation. The accuracy was approximately 0.86° ± 0.67° in the horizontal direction and 0.54° ± 0.34° in the vertical. This system successfully tracked the gaze motions not only in direction, but also in distance. Using this system, three operators could operate a robot manipulator to point at some targets. This result shows that the method is reliable in building communication between humans and machines using EOGs. PMID:24919013

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

PubMed

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

"Pack[superscript2]": VM Resource Scheduling for Fine-Grained Application SLAs in Highly Consolidated Environment

ERIC Educational Resources Information Center

Sukwong, Orathai

2013-01-01

Virtualization enables the ability to consolidate multiple servers on a single physical machine, increasing the infrastructure utilization. Maximizing the ratio of server virtual machines (VMs) to physical machines, namely the consolidation ratio, becomes an important goal toward infrastructure cost saving in a cloud. However, the consolidation…

Machine-Aided Indexing of Technical Literature

ERIC Educational Resources Information Center

Klingbiel, Paul H.

1973-01-01

To index at the Defense Documentation Center (DDC), an automated system must choose single words or phrases rapidly and economically. Automation of DDC's indexing has been machine-aided from its inception. A machine-aided indexing system is described that indexes one million words of text per hour of CPU time. (22 references) (Author/SJ)

THE ROLE OF REVIEW MATERIAL IN CONTINUOUS PROGRAMMING WITH TEACHING MACHINES.

ERIC Educational Resources Information Center

FERSTER, C.B.

STUDENTS WERE PRESENTED 61 LESSONS BY MEANS OF SEMIAUTOMATIC TEACHING MACHINES. LESSONS WERE ARRANGED SO THAT EACH PARTICIPATING STUDENT STUDIED PART OF THE COURSE MATERIAL WITH A SINGLE REPETITION AND PART WITHOUT REPETITION. DATA WERE OBTAINED FROM TWO TESTS SHOWING TEACHING-MACHINE RESULTS AND ONE FINAL COURSE EXAMINATION. NO SIGNIFICANT…

Impact of the HEALTHY study on vending machine offerings in middle schools

USDA-ARS?s Scientific Manuscript database

The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminat...

Scattering effects of machined optical surfaces

NASA Astrophysics Data System (ADS)

Thompson, Anita Kotha

1998-09-01

Optical fabrication is one of the most labor-intensive industries in existence. Lensmakers use pitch to affix glass blanks to metal chucks that hold the glass as they grind it with tools that have not changed much in fifty years. Recent demands placed on traditional optical fabrication processes in terms of surface accuracy, smoothnesses, and cost effectiveness has resulted in the exploitation of precision machining technology to develop a new generation of computer numerically controlled (CNC) optical fabrication equipment. This new kind of precision machining process is called deterministic microgrinding. The most conspicuous feature of optical surfaces manufactured by the precision machining processes (such as single-point diamond turning or deterministic microgrinding) is the presence of residual cutting tool marks. These residual tool marks exhibit a highly structured topography of periodic azimuthal or radial deterministic marks in addition to random microroughness. These distinct topographic features give rise to surface scattering effects that can significantly degrade optical performance. In this dissertation project we investigate the scattering behavior of machined optical surfaces and their imaging characteristics. In particular, we will characterize the residual optical fabrication errors and relate the resulting scattering behavior to the tool and machine parameters in order to evaluate and improve the deterministic microgrinding process. Other desired information derived from the investigation of scattering behavior is the optical fabrication tolerances necessary to satisfy specific image quality requirements. Optical fabrication tolerances are a major cost driver for any precision optical manufacturing technology. The derivation and control of the optical fabrication tolerances necessary for different applications and operating wavelength regimes will play a unique and central role in establishing deterministic microgrinding as a preferred and a cost-effective optical fabrication process. Other well understood optical fabrication processes will also be reviewed and a performance comparison with the conventional grinding and polishing technique will be made to determine any inherent advantages in the optical quality of surfaces produced by other techniques.

A Lateral Flow Biosensor for the Detection of Single Nucleotide Polymorphisms.

PubMed

Zeng, Lingwen; Xiao, Zhuo

2017-01-01

A lateral flow biosensor (LFB) is introduced for the detection of single nucleotide polymorphisms (SNPs). The assay is composed of two steps: circular strand displacement reaction and lateral flow biosensor detection. In step 1, the nucleotide at SNP site is recognized by T4 DNA ligase and the signal is amplified by strand displacement DNA polymerase, which can be accomplished at a constant temperature. In step 2, the reaction product of step 1 is detected by a lateral flow biosensor, which is a rapid and cost effective tool for nuclei acid detection. Comparing with conventional methods, it requires no complicated machines. It is suitable for the use of point of care diagnostics. Therefore, this simple, cost effective, robust, and promising LFB detection method of SNP has great potential for the detection of genetic diseases, personalized medicine, cancer related mutations, and drug-resistant mutations of infectious agents.

Trehalose and sorbitol alter the kinetic pattern of inactivation of glutamate dehydrogenase during drying in levitated microdroplets.

PubMed

Lorenzen, Elke; Lee, Geoffrey

2013-12-01

A single-droplet acoustic levitator was used to determine the drying rate and the kinetics of inactivation of glutamate dehydrogenase in the presence of added trehalose or sorbitol. The solution was also spray dried under the same process condition of drying gas temperature on a bench-top machine. Both trehalose and sorbitol delay the point of onset of enzyme inactivation which lies after the critical point of drying. Both carbohydrates also reduce the apparent rate constant of inactivation calculated during the subsequent inactivation phase. The carbohydrates stabilise, therefore, the enzyme during droplet drying and particle formation mainly during the falling rate drying period. There is no difference between the stabilising effects of the two carbohydrates when examined as levitated single droplets. This suggests the importance of water replacement as a stabilising mechanism in the levitated droplets/particles. On spray drying, the trehalose stabilises the enzyme better than does the sorbitol at a drying gas (outlet) temperature of 60°C. This suggests glass formation with the trehalose but not the sorbitol during the very rapid drying process of small-atomised droplets in the spray dryer. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Applying Workspace Limitations in a Velocity-Controlled Robotic Mechanism

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E. (Inventor); Hargrave, Brian (Inventor); Platt, Robert J., Jr. (Inventor)

2014-01-01

A robotic system includes a robotic mechanism responsive to velocity control signals, and a permissible workspace defined by a convex-polygon boundary. A host machine determines a position of a reference point on the mechanism with respect to the boundary, and includes an algorithm for enforcing the boundary by automatically shaping the velocity control signals as a function of the position, thereby providing smooth and unperturbed operation of the mechanism along the edges and corners of the boundary. The algorithm is suited for application with higher speeds and/or external forces. A host machine includes an algorithm for enforcing the boundary by shaping the velocity control signals as a function of the reference point position, and a hardware module for executing the algorithm. A method for enforcing the convex-polygon boundary is also provided that shapes a velocity control signal via a host machine as a function of the reference point position.

Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging.

PubMed

Illán, Ignacio Alvarez; Górriz, Juan Manuel; Ramírez, Javier; Lang, Elmar W; Salas-Gonzalez, Diego; Puntonet, Carlos G

2012-11-01

This paper explores the importance of the latent symmetry of the brain in computer-aided systems for diagnosing Alzheimer's disease (AD). Symmetry and asymmetry are studied from two points of view: (i) the development of an effective classifier within the scope of machine learning techniques, and (ii) the assessment of its relevance to the AD diagnosis in the early stages of the disease. The proposed methodology is based on eigenimage decomposition of single-photon emission-computed tomography images, using an eigenspace extension to accommodate odd and even eigenvectors separately. This feature extraction technique allows for support-vector-machine classification and image analysis. Identification of AD patterns is improved when the latent symmetry of the brain is considered, with an estimated 92.78% accuracy (92.86% sensitivity, 92.68% specificity) using a linear kernel and a leave-one-out cross validation strategy. Also, asymmetries may be used to define a test for AD that is very specific (90.24% specificity) but not especially sensitive. Two main conclusions are derived from the analysis of the eigenimage spectrum. Firstly, the recognition of AD patterns is improved when considering only the symmetric part of the spectrum. Secondly, asymmetries in the hypo-metabolic patterns, when present, are more pronounced in subjects with AD. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-physics CFD simulations in engineering

NASA Astrophysics Data System (ADS)

Yamamoto, Makoto

2013-08-01

Nowadays Computational Fluid Dynamics (CFD) software is adopted as a design and analysis tool in a great number of engineering fields. We can say that single-physics CFD has been sufficiently matured in the practical point of view. The main target of existing CFD software is single-phase flows such as water and air. However, many multi-physics problems exist in engineering. Most of them consist of flow and other physics, and the interactions between different physics are very important. Obviously, multi-physics phenomena are critical in developing machines and processes. A multi-physics phenomenon seems to be very complex, and it is so difficult to be predicted by adding other physics to flow phenomenon. Therefore, multi-physics CFD techniques are still under research and development. This would be caused from the facts that processing speed of current computers is not fast enough for conducting a multi-physics simulation, and furthermore physical models except for flow physics have not been suitably established. Therefore, in near future, we have to develop various physical models and efficient CFD techniques, in order to success multi-physics simulations in engineering. In the present paper, I will describe the present states of multi-physics CFD simulations, and then show some numerical results such as ice accretion and electro-chemical machining process of a three-dimensional compressor blade which were obtained in my laboratory. Multi-physics CFD simulations would be a key technology in near future.

17. Machines in middle 1904 section of Building 59, Camera ...

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

17. Machines in middle 1904 section of Building 59, Camera is pointed SW. Large wheel is part of Post Lathe, or Bull Lathe, manufactured by Oliver Machinery Co. Machine at left is a smaller Lathe made by Yates American Machinery Co., also seen in photo WA-116-A-20. - Puget Sound Naval Shipyard, Pattern Shop, Farragut Avenue, Bremerton, Kitsap County, WA

Evaluating a hybrid three-dimensional metrology system: merging data from optical and touch probe devices

NASA Astrophysics Data System (ADS)

Gerde, Janice R.; Christens-Barry, William A.

2011-08-01

In a project to meet requirements for CBP Laboratory analysis of footwear under the Harmonized Tariff Schedule of the United States (HTSUS), a hybrid metrology system comprising both optical and touch probe devices has been assembled. A unique requirement must be met: To identify the interface-typically obscured in samples of concern-of the "external surface area upper" (ESAU) and the sole without physically destroying the sample. The sample outer surface is determined by discrete point cloud coordinates obtained using laser scanner optical measurements. Measurements from the optically inaccessible insole region are obtained using a coordinate measuring machine (CMM). That surface similarly is defined by point cloud data. Mathematically, the individual CMM and scanner data sets are transformed into a single, common reference frame. Custom software then fits a polynomial surface to the insole data and extends it to intersect the mesh fitted to the outer surface point cloud. This line of intersection defines the required ESAU boundary, thus permitting further fractional area calculations to determine the percentage of materials present. With a draft method in place, and first-level method validation underway, we examine the transformation of the two dissimilar data sets into the single, common reference frame. We also will consider the six previously-identified potential error factors versus the method process. This paper reports our on-going work and discusses our findings to date.

Sensorless speed detection of squirrel-cage induction machines using stator neutral point voltage harmonics

NASA Astrophysics Data System (ADS)

Petrovic, Goran; Kilic, Tomislav; Terzic, Bozo

2009-04-01

In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.

A randomized controlled trial of chair interventions on back and hip pain among sewing machine operators: the los angeles garment study.

PubMed

Wang, Pin-Chieh; Ritz, Beate R; Janowitz, Ira; Harrison, Robert J; Yu, Fei; Chan, Jacqueline; Rempel, David M

2008-03-01

Determine whether an adjustable chair with a curved or a flat seat pan improved monthly back and hip pain scores in sewing machine operators. This 4-month intervention study randomized 293 sewing machine operators with back and hip pain. The participants in the control group received a placebo intervention, and participants in the intervention groups received the placebo intervention and one of the two intervention chairs. Compared with the control group, mean pain improvement for the flat chair intervention was 0.43 points (95% CI = 0.34, 0.51) per month, and mean pain improvement for the curved chair intervention was 0.25 points (95% CI = 0.16, 0.34) per month. A height-adjustable task chair with a swivel function can reduce back and hip pain in sewing machine operators. The findings may be relevant to workers who perform visual- and hand-intensive manufacturing jobs.

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 15: Administrative Information, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This volume developed by the Machine Tool Advanced Skill Technology (MAST) program contains key administrative documents and provides additional sources for machine tool and precision manufacturing information and important points of contact in the industry. The document contains the following sections: a foreword; grant award letter; timeline for…

Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms.

PubMed

Roetker, Nicholas S; Page, C David; Yonker, James A; Chang, Vicky; Roan, Carol L; Herd, Pamela; Hauser, Taissa S; Hauser, Robert M; Atwood, Craig S

2013-10-01

We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

Performance of a plasma fluid code on the Intel parallel computers

NASA Technical Reports Server (NTRS)

Lynch, V. E.; Carreras, B. A.; Drake, J. B.; Leboeuf, J. N.; Liewer, P.

1992-01-01

One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel (sigma) machine gives an improvement factor close to 64 over the single-processor CRAY-2.

Advanced Aircraft Interfaces: The Machine Side of the Man-Machine Interface (Les Interfaces sur les Avions de Pointe: L’Aspect Machine de l’Interface Homme-Machine)

DTIC Science & Technology

1992-10-01

Manager , Advanced Transport Operating Systems Program Office Langley Research Center Mail Stop 265 Hampton, VA 23665-5225 United States Programme Committee...J.H.Lind, and C.G.Burge Advanced Cockpit - Mission and Image Management 4 by J. Struck Aircrew Acceptance of Automation in the Cockpit 5 by M. Hicks and I...DESIGN CONCEPTS AND TOOLS A Systems Approach to the Advanced Aircraft Man-Machine Interface 23 by F. Armogida Management of Avionics Data in the Cockpit

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

40 CFR 63.3960 - By what date must I conduct performance tests and other initial compliance demonstrations?

Code of Federal Regulations, 2011 CFR

2011-07-01

... performance test of one representative magnet wire coating machine for each group of identical or very similar... you complete the performance test of a representative magnet wire coating machine. The requirements in... operations, you may, with approval, conduct a performance test of a single magnet wire coating machine that...

Impact of the HEALTHY Study on Vending Machine Offerings in Middle Schools

ERIC Educational Resources Information Center

Hartstein, Jill; Cullen, Karen W.; Virus, Amy; El Ghormli, Laure; Volpe, Stella L.; Staten, Myrlene A.; Bridgman, Jessica C.; Stadler, Diane D.; Gillis, Bonnie; McCormick, Sarah B.; Mobley, Connie C.

2011-01-01

Purpose/Objectives: The purpose of this study is to report the impact of the three-year middle school-based HEALTHY study on intervention school vending machine offerings. There were two goals for the vending machines: serve only dessert/snack foods with 200 kilocalories or less per single serving package, and eliminate 100% fruit juice and…

Machine Tests Optical Fibers In Flexure

NASA Technical Reports Server (NTRS)

Darejeh, Hadi; Thomas, Henry; Delcher, Ray

1993-01-01

Machine repeatedly flexes single optical fiber or cable or bundle of optical fibers at low temperature. Liquid nitrogen surrounds specimen as it is bent back and forth by motion of piston. Machine inexpensive to build and operate. Tests under repeatable conditions so candidate fibers, cables, and bundles evaluated for general robustness before subjected to expensive shock and vibration tests.

Scheduling Jobs and a Variable Maintenance on a Single Machine with Common Due-Date Assignment

PubMed Central

Wan, Long

2014-01-01

We investigate a common due-date assignment scheduling problem with a variable maintenance on a single machine. The goal is to minimize the total earliness, tardiness, and due-date cost. We derive some properties on an optimal solution for our problem. For a special case with identical jobs we propose an optimal polynomial time algorithm followed by a numerical example. PMID:25147861

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

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

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

Here, we apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models - the square and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-one Ising (BSI) model, and the 2D XY model, and examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow exploration of different phases and symmetry-breaking, but can distinguish phase transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which ismore » particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the 'charge' correlations (vorticity) in the BSI model (XY model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the 'antoencoder method', and demonstrate that it too can be trained to capture phase transitions and critical points.« less

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

DOE PAGES

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

2017-06-19

Here, we apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models - the square and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-one Ising (BSI) model, and the 2D XY model, and examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow exploration of different phases and symmetry-breaking, but can distinguish phase transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which ismore » particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the 'charge' correlations (vorticity) in the BSI model (XY model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the 'antoencoder method', and demonstrate that it too can be trained to capture phase transitions and critical points.« less

Discovering phases, phase transitions, and crossovers through unsupervised machine learning: A critical examination

NASA Astrophysics Data System (ADS)

Hu, Wenjian; Singh, Rajiv R. P.; Scalettar, Richard T.

2017-06-01

We apply unsupervised machine learning techniques, mainly principal component analysis (PCA), to compare and contrast the phase behavior and phase transitions in several classical spin models—the square- and triangular-lattice Ising models, the Blume-Capel model, a highly degenerate biquadratic-exchange spin-1 Ising (BSI) model, and the two-dimensional X Y model—and we examine critically what machine learning is teaching us. We find that quantified principal components from PCA not only allow the exploration of different phases and symmetry-breaking, but they can distinguish phase-transition types and locate critical points. We show that the corresponding weight vectors have a clear physical interpretation, which is particularly interesting in the frustrated models such as the triangular antiferromagnet, where they can point to incipient orders. Unlike the other well-studied models, the properties of the BSI model are less well known. Using both PCA and conventional Monte Carlo analysis, we demonstrate that the BSI model shows an absence of phase transition and macroscopic ground-state degeneracy. The failure to capture the "charge" correlations (vorticity) in the BSI model (X Y model) from raw spin configurations points to some of the limitations of PCA. Finally, we employ a nonlinear unsupervised machine learning procedure, the "autoencoder method," and we demonstrate that it too can be trained to capture phase transitions and critical points.

Improved equivalent magnetic network modeling for analyzing working points of PMs in interior permanent magnet machine

NASA Astrophysics Data System (ADS)

Guo, Liyan; Xia, Changliang; Wang, Huimin; Wang, Zhiqiang; Shi, Tingna

2018-05-01

As is well known, the armature current will be ahead of the back electromotive force (back-EMF) under load condition of the interior permanent magnet (PM) machine. This kind of advanced armature current will produce a demagnetizing field, which may make irreversible demagnetization appeared in PMs easily. To estimate the working points of PMs more accurately and take demagnetization under consideration in the early design stage of a machine, an improved equivalent magnetic network model is established in this paper. Each PM under each magnetic pole is segmented, and the networks in the rotor pole shoe are refined, which makes a more precise model of the flux path in the rotor pole shoe possible. The working point of each PM under each magnetic pole can be calculated accurately by the established improved equivalent magnetic network model. Meanwhile, the calculated results are compared with those calculated by FEM. And the effects of d-axis component and q-axis component of armature current, air-gap length and flux barrier size on working points of PMs are analyzed by the improved equivalent magnetic network model.

Multiple Cylinder Free-Piston Stirling Machinery

NASA Astrophysics Data System (ADS)

Berchowitz, David M.; Kwon, Yong-Rak

In order to improve the specific power of piston-cylinder type machinery, there is a point in capacity or power where an advantage accrues with increasing number of piston-cylinder assemblies. In the case of Stirling machinery where primary energy is transferred across the casing wall of the machine, this consideration is even more important. This is due primarily to the difference in scaling of basic power and the required heat transfer. Heat transfer is found to be progressively limited as the size of the machine increases. Multiple cylinder machines tend to preserve the surface area to volume ratio at more favorable levels. In addition, the spring effect of the working gas in the so-called alpha configuration is often sufficient to provide a high frequency resonance point that improves the specific power. There are a number of possible multiple cylinder configurations. The simplest is an opposed pair of piston-displacer machines (beta configuration). A three-cylinder machine requires stepped pistons to obtain proper volume phase relationships. Four to six cylinder configurations are also possible. A small demonstrator inline four cylinder alpha machine has been built to demonstrate both cooling operation and power generation. Data from this machine verifies theoretical expectations and is used to extrapolate the performance of future machines. Vibration levels are discussed and it is argued that some multiple cylinder machines have no linear component to the casing vibration but may have a nutating couple. Example applications are discussed ranging from general purpose coolers, computer cooling, exhaust heat power extraction and some high power engines.

Self aligning electron beam gun having enhanced thermal and mechanical stability

DOEpatents

Scarpetti, Jr., Raymond D.; Parkison, Clarence D.; Switzer, Vernon A.; Lee, Young J.; Sawyer, William C.

1995-01-01

A compact, high power electron gun having enhanced thermal and mechanical stability which incorporates a mechanically coupled, self aligning structure for the anode and cathode. The enhanced stability, and reduced need for realignment of the cathode to the anode and downstream optics during operation are achieved by use of a common support structure for the cathode and anode which requires no adjustment screws or spacers. The electron gun of the present invention also incorporates a modular design for the cathode, in which the electron emitter, its support structure, and the hardware required to attach the emitter assembly to the rest of the gun are a single element. This modular design makes replacement of the emitter simpler and requires no realignment after a new emitter has been installed. Compactness and a reduction in the possibility of high voltage breakdown are achieved by shielding the "triple point" where the electrode, insulator, and vacuum meet. The use of electric discharge machining (EDM) for fabricating the emitter allows for the accurate machining of the emitter into intricate shapes without encountering the normal stresses developed by standard emitter fabrication techniques.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

A microcomputer network for control of a continuous mining machine

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

Schiffbauer, W.H.

1993-12-31

This report details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines and installed on a continuous mining machine. The network consists of microcomputers that are connected together via a single twisted-pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers, in conjunction with the appropriate sensors, provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and control the continuous miningmore » machine. Because of the network`s generic structure, it can be installed on most mining machines.« less

A Flexure-Based Tool Holder for Sub-(micro)m Positioning of a Single Point Cutting Tool on a Four-axis Lathe

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

Bono, M J; Hibbard, R L

2005-12-05

A tool holder was designed to facilitate the machining of precision meso-scale components with complex three-dimensional shapes with sub-{micro}m accuracy on a four-axis lathe. A four-axis lathe incorporates a rotary table that allows the cutting tool to swivel with respect to the workpiece to enable the machining of complex workpiece forms, and accurately machining complex meso-scale parts often requires that the cutting tool be aligned precisely along the axis of rotation of the rotary table. The tool holder designed in this study has greatly simplified the process of setting the tool in the correct location with sub-{micro}m precision. The toolmore » holder adjusts the tool position using flexures that were designed using finite element analyses. Two flexures adjust the lateral position of the tool to align the center of the nose of the tool with the axis of rotation of the B-axis, and another flexure adjusts the height of the tool. The flexures are driven by manual micrometer adjusters, each of which provides a minimum increment of motion of 20 nm. This tool holder has simplified the process of setting a tool with sub-{micro}m accuracy, and it has significantly reduced the time required to set a tool.« less

Cultural Resources Evaluation of the Upper Atchafalaya Backwater Area, Iberville and Pointe Coupee Parishes, SOuth Louisiana

DTIC Science & Technology

2001-05-01

gathering and curing ton gins in the twentieth century (Maygarden 1994:68- of Spanish moss was also a major industry in Point 69). Coupee and Iberville...tinted whiteware; d) Clear yellow glass plate or bowl; e) Clear glass vessel, probably Vicks Cough Syrup; f) Depression glass; g) Clear yellow Owens...Hind’s Honey and Almond Cream, A. S. Hinds Co, Bloomfield, NJ); f-h) Machine-made glass bottles. was also collected. Owens and valve machines were

State-of-the-Art in Improved Parts Programming for Numerically Controlled Machines

DTIC Science & Technology

1976-10-01

than expected let sizes for IIC. Cincinnati lilbcron, Inc., has built a $1.25 million Computer Ilumerical Control ( CNC ) 1,4nufacturing Center to "rw’ t...point-to- point user. Lathe and other turning operations are essentially two-axis opera- tions, and there has been some dissatisfaction over APT’s...a.particular machi-ne (50)." "Software is the key to CNC , the costs of which are easily overlooked. The cost of software development is growing in relation to

Single bus star connected reluctance drive and method

DOEpatents

Fahimi, Babak; Shamsi, Pourya

2016-05-10

A system and methods for operating a switched reluctance machine includes a controller, an inverter connected to the controller and to the switched reluctance machine, a hysteresis control connected to the controller and to the inverter, a set of sensors connected to the switched reluctance machine and to the controller, the switched reluctance machine further including a set of phases the controller further comprising a processor and a memory connected to the processor, wherein the processor programmed to execute a control process and a generation process.

Scientific bases of human-machine communication by voice.

PubMed Central

Schafer, R W

1995-01-01

The scientific bases for human-machine communication by voice are in the fields of psychology, linguistics, acoustics, signal processing, computer science, and integrated circuit technology. The purpose of this paper is to highlight the basic scientific and technological issues in human-machine communication by voice and to point out areas of future research opportunity. The discussion is organized around the following major issues in implementing human-machine voice communication systems: (i) hardware/software implementation of the system, (ii) speech synthesis for voice output, (iii) speech recognition and understanding for voice input, and (iv) usability factors related to how humans interact with machines. PMID:7479802

Revisiting the Central Dogma One Molecule at a Time

PubMed Central

Bustamante, Carlos; Cheng, Wei; Meija, Yara

2011-01-01

The faithful relay and timely expression of genetic information depend on specialized molecular machines, many of which function as nucleic acid translocases. The emergence over the last decade of single-molecule fluorescence detection and manipulation techniques with nm and Å resolution, and their application to the study of nucleic acid translocases are painting an increasingly sharp picture of the inner workings of these machines, the dynamics and coordination of their moving parts, their thermodynamic efficiency, and the nature of their transient intermediates. Here we present an overview of the main results arrived at by the application of single-molecule methods to the study of the main machines of the central dogma. PMID:21335233

VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

DOE PAGES

Ostrovski, Fernanda; McMahon, Richard G.; Connolly, Andrew J.; ...

2016-11-17

In this paper, we present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift z s = 2.74 and image separation of 2.9 arcsec lensed by a foreground z l = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES),more » near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with i AB = 18.61 and i AB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θ E ~ 1.47 arcsec, enclosed mass M enc ~ 4 × 10 11 M ⊙ and a time delay of ~52 d. Finally, the relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.« less

VDES J2325-5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

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

Ostrovski, Fernanda; McMahon, Richard G.; Connolly, Andrew J.

In this paper, we present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift z s = 2.74 and image separation of 2.9 arcsec lensed by a foreground z l = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES),more » near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with i AB = 18.61 and i AB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θ E ~ 1.47 arcsec, enclosed mass M enc ~ 4 × 10 11 M ⊙ and a time delay of ~52 d. Finally, the relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.« less

The Impacts of Industrial Robots

DTIC Science & Technology

1981-11-01

plastics, ’and strain gauges are used to measure very small forces at a number of points on the robot’s "end effector. Except for the simplest on-off...devices, tactile sensors are not yet found on commercially available robots. Forces are sensed by using strain gauges or piezoelectric sensors to...tools: deburring, drilling , grinding,milling,routing machines ii. plastic materialsformirg and injection machines iii. metal die casting machines iv

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

PubMed Central

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

Improving air traffic control: Proving new tools or approving the joint human-machine system?

NASA Technical Reports Server (NTRS)

Gaillard, Irene; Leroux, Marcel

1994-01-01

From the description of a field problem (i.e., designing decision aids for air traffic controllers), this paper points out how a cognitive engineering approach provides the milestones for the evaluation of future joint human-machine systems.

40 CFR 438.1 - General applicability.

Code of Federal Regulations, 2013 CFR

2013-07-01

... STANDARDS (CONTINUED) METAL PRODUCTS AND MACHINERY POINT SOURCE CATEGORY § 438.1 General applicability. (a..., or maintenance of metal parts, products, or machines for use in the Metal Product & Machinery (MP&M... Metal Products; Mobile Industrial Equipment; Motor Vehicle; Office Machine; Ordnance; Precious Metals...

40 CFR 438.1 - General applicability.

Code of Federal Regulations, 2014 CFR

2014-07-01

... STANDARDS (CONTINUED) METAL PRODUCTS AND MACHINERY POINT SOURCE CATEGORY § 438.1 General applicability. (a..., or maintenance of metal parts, products, or machines for use in the Metal Product & Machinery (MP&M... Metal Products; Mobile Industrial Equipment; Motor Vehicle; Office Machine; Ordnance; Precious Metals...

40 CFR 438.1 - General applicability.

Code of Federal Regulations, 2012 CFR

2012-07-01

... STANDARDS (CONTINUED) METAL PRODUCTS AND MACHINERY POINT SOURCE CATEGORY § 438.1 General applicability. (a..., or maintenance of metal parts, products, or machines for use in the Metal Product & Machinery (MP&M... Metal Products; Mobile Industrial Equipment; Motor Vehicle; Office Machine; Ordnance; Precious Metals...

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.

Assessment of Genetic and Nongenetic Interactions for the Prediction of Depressive Symptomatology: An Analysis of the Wisconsin Longitudinal Study Using Machine Learning Algorithms

PubMed Central

Roetker, Nicholas S.; Yonker, James A.; Chang, Vicky; Roan, Carol L.; Herd, Pamela; Hauser, Taissa S.; Hauser, Robert M.

2013-01-01

Objectives. We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. Methods. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors—13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors—18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. Results. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. Conclusions. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic–environmental–sociobehavioral interactions in depressive symptoms. PMID:23927508

Microcomputer network for control of a continuous mining machine. Information circular/1993

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

Schiffbauer, W.H.

1993-01-01

The paper details a microcomputer-based control and monitoring network that was developed in-house by the U.S. Bureau of Mines, and installed on a Joy 14 continuous mining machine. The network consists of microcomputers that are connected together via a single twisted pair cable. Each microcomputer was developed to provide a particular function in the control process. Machine-mounted microcomputers in conjunction with the appropriate sensors provide closed-loop control of the machine, navigation, and environmental monitoring. Off-the-machine microcomputers provide remote control of the machine, sensor status, and a connection to the network so that external computers can access network data and controlmore » the continuous mining machine. Although the network was installed on a Joy 14 continuous mining machine, its use extends beyond it. Its generic structure lends itself to installation onto most mining machine types.« less

Development of Knitted Warm Garments from Speciality Jute Yarns

NASA Astrophysics Data System (ADS)

Roy, Alok Nath

2013-09-01

Jute-polyester blended core and textured polyester multifilament cover spun-wrapped yarn was produced using existing jute spinning machines. The spun-wrapped yarn so produced show a reduction in hairiness up to 86.1 %, improvement in specific work of rupture up to 9.8 % and specific flexural rigidity up to 23.6 % over ordinary jute-polyester blended yarn. The knitted swatch produced out of these spun-wrapped yarn using seven gauge and nine gauge needle in both single jersey and double jersey knitting machines showed very good dimensional stability even after three washing. The two-ply and three-ply yarn produced from single spun-wrapped yarn can be easily used in knitting machines and also in hand-knitting for the production of sweaters. The thermal insulation value of the sweaters produced with jute-polyester blended spun-wrapped yarn is comparable with thermal insulation value of sweaters made from 100 % acrylic and 100 % wool. However, the hand-knitted sweaters showed higher thermal insulation value than the machine-knitted sweaters due to less packing of yarn in hand knitted structure as compared to machine knitting.

Reprographics Career Ladder AFSC 703X0.

DTIC Science & Technology

1981-07-01

LINEUP AND REGISTER TABLES 39 BINDING MACHINES 36 FLOURESCENT LAMPS 36 WET PROCESS PLATEMAKERS 36 ELECTRIC STAPLERS 32 MANUAL PAPER CUTTERS 32...ELECTROSTATIC COPIERS/PLATEMAKERS 78% PAPER CUTTERS 57% ELECTRIC STAPLERS 47% BINDING MACHINES 42% SINGLE HEAD DRILLS 37% PADDING RACKS 31% PLATEMAKING...HEAD DRILLS 78% MANUAL PAPER CUTTERS 71% STATION COLLATORS 51% BINDING MACHiNES 46% ELECTRIC STAPLERS 46% PLATEMAKING CAMERAS 44% SADDLE STITCHERS 42

TELNET under Single-Connection TCP Specification

DTIC Science & Technology

1976-02-02

Manager User Oriented Systems International Business Machines Corp. K54-282, Monterey and Cottle Roads San Jose, CA 95193 Dr. Leonard Y. Liu...Manager Computer Science International Business Machines Corp. K51-282, Monterey and Cottle Roads San Jose, CA 95193 Mr. Harry Reinstein... International Business Machines Corp. 1501 California Avenue Palo Alto, Ca 94303 Illinois, University of Mr. John D. Day University of Illinois Center for

The Time Machine: Writing Historical Fiction.

ERIC Educational Resources Information Center

Karr, Kathleen

2000-01-01

Discusses historical fiction for children and young adults from a writer's point of view and equates it to a time machine into the past. Considers the books that influenced the writer; larger-than-life characters; story ideas; and research to really know and feel the setting. (LRW)

One of My Favorite Assignments: Automated Teller Machine Simulation.

ERIC Educational Resources Information Center

Oberman, Paul S.

2001-01-01

Describes an assignment for an introductory computer science class that requires the student to write a software program that simulates an automated teller machine. Highlights include an algorithm for the assignment; sample file contents; language features used; assignment variations; and discussion points. (LRW)

Condition monitoring of a prototype turbine. Description of the system and main results

NASA Astrophysics Data System (ADS)

Valero, C.; Egusquiza, E.; Presas, A.; Valentin, D.; Egusquiza, M.; Bossio, M.

2017-04-01

The fast change in new renewable energy is affecting directly the required operating range of hydropower plants. According to the present demand of electricity, it is necessary to generate different levels of power. Because of its ease to regulate and its huge storage capacity of energy, hydropower is the unique energy source that can adapt to the demand. Today, the required operating range of turbine units is expected to extend from part load to overload. These extreme operations points can cause several pressure pulsations, cavitation and vibrations in different parts of the machine. To determine the effects on the machine, vibration measurements are necessary in actual machines. Vibrations can be used for machinery protection and to identify problems in the machine (diagnosis). In this paper, some results obtained in a hydropower plant are presented. The variation of global levels and vibratory signatures has been analysed as function as gross head, transducer location and operating points.

Disruption Neutral Point Experiment on Alcator C-Mod

NASA Astrophysics Data System (ADS)

Granetz, R. S.; Nakamura, Y.

2000-10-01

Disruptions of single-null elongated plasmas generally result in loss of vertical position control, leading to a current quench occurring at the top or bottom of the machine, with all the attendant problems of halo and eddy currents flowing in divertor structures. On JT-60U, it has been found that if the plasma is operated with its magnetic axis at a particular height, called the neutral point, the initial vertical drift after a thermal quench is significantly slower than usual, and sometimes can even be arrested, thereby avoiding a current quench in the divertor region entirely. In an ongoing collaboration between MIT and JAERI, the neutral point concept is being tested in Alcator C-Mod, which has a significantly higher plasma elongation than JT-60U (1.65 vs 1.3). Calculations using TSC predict a neutral point at z~=+1 cm above the midplane (a=22 cm). The existence of a neutral point has now been experimentally confirmed, albeit at a height of z=+2.7 cm. The plasma has remained vertically stable for up to 9 ms after the disruption thermal quench, which in principle, is long enough for the PF control system to respond, if programmed appropriately. In addition, the physics of the neutral point stability on C-Mod appears to be somewhat different than that on JT-60U.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Bayesian Kernel Methods for Non-Gaussian Distributions: Binary and Multi-class Classification Problems

DTIC Science & Technology

2013-05-28

those of the support vector machine and relevance vector machine, and the model runs more quickly than the other algorithms . When one class occurs...incremental support vector machine algorithm for online learning when fewer than 50 data points are available. (a) Papers published in peer-reviewed journals...learning environments, where data processing occurs one observation at a time and the classification algorithm improves over time with new

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.

Sealing intersecting vane machines

DOEpatents

Martin, Jedd N [Providence, RI; Chomyszak, Stephen M [Attleboro, MA

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.

Single wheel testers, single track testers, and instrumented tractors

USDA-ARS?s Scientific Manuscript database

Single wheel testers and single track testers are used for determining tractive performance characteristics of tires and tracks. Instrumented tractors are useful in determining the tractive performance of tractors. These machines are also used for determining soil-tire and soil-track interactions,...

Chatter active control in a lathe machine using magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Nosouhi, R.; Behbahani, S.

2011-01-01

This paper analyzes the chatter phenomena in lathe machines. Chatter is one of the main causes of inaccuracy, reduction of life cycle of the machine and tool wear in machine tools. This phenomenon limits the depth of cut as a function of the cutting speed, which consequently reduces the material removal rate and machining efficiency. Chatter control is therefore important since it increases the stability region in machining and increases the critical depth of cut in machining case. To control the chatter in lathe machines, a magnetostrictive actuator is used. The materials with magnetostriction properties are kind of smart materials of which their length changes as a result of applying an exterior magnetic field, which make them suitable for control applications. It is assumed that the actuator applies the proper force exactly at the point where the machining force is applied on the tool. In this paper the chatter stability lobes is excelled as a result of applying a PID controller on the magnetostrictive actuator equipped-tool in turning.

Visualization and characterization of individual type III protein secretion machines in live bacteria

PubMed Central

Lara-Tejero, María; Bewersdorf, Jörg; Galán, Jorge E.

2017-01-01

Type III protein secretion machines have evolved to deliver bacterially encoded effector proteins into eukaryotic cells. Although electron microscopy has provided a detailed view of these machines in isolation or fixed samples, little is known about their organization in live bacteria. Here we report the visualization and characterization of the Salmonella type III secretion machine in live bacteria by 2D and 3D single-molecule switching superresolution microscopy. This approach provided access to transient components of this machine, which previously could not be analyzed. We determined the subcellular distribution of individual machines, the stoichiometry of the different components of this machine in situ, and the spatial distribution of the substrates of this machine before secretion. Furthermore, by visualizing this machine in Salmonella mutants we obtained major insights into the machine’s assembly. This study bridges a major resolution gap in the visualization of this nanomachine and may serve as a paradigm for the examination of other bacterially encoded molecular machines. PMID:28533372

Dental cutting behaviour of mica-based and apatite-based machinable glass-ceramics.

PubMed

Taira, M; Wakasa, K; Yamaki, M; Matsui, A

1990-09-01

Some recently developed industrial ceramics have excellent machinability properties. The objective of this study was to evaluate the dental cutting behaviour of two machinable glass-ceramics, mica-containing Macor-M and apatite- and diopside-containing Bioram-M, and to compare them with the cutting behaviour of a composite resin typodont tooth enamel and bovine enamel. Weight-load cutting tests were conducted, using a diamond point driven by an air-turbine handpiece, While the transverse load applied on the point was varied, the handpiece speed during cutting and the volume of removal upon cutting were measured. In general, an increase in the applied load caused a decrease in cutting speed and an increase in cutting volume. However, the intensity of this trend was found to differ between four workpieces. Cutting Macor-M resulted in the second-most reduced cutting speed and the maximum cutting volume. Cutting Bioram-M gave the least reduced cutting speed and the minimum cutting volume. It was suggested that two machinable glass-ceramics could be employed as typodont teeth. This study may also contribute to the development of new restorative dental ceramic materials, prepared by machining.

Surface and subsurface cracks characteristics of single crystal SiC wafer in surface machining

NASA Astrophysics Data System (ADS)

Qiusheng, Y.; Senkai, C.; Jisheng, P.

2015-03-01

Different machining processes were used in the single crystal SiC wafer machining. SEM was used to observe the surface morphology and a cross-sectional cleavages microscopy method was used for subsurface cracks detection. Surface and subsurface cracks characteristics of single crystal SiC wafer in abrasive machining were analysed. The results show that the surface and subsurface cracks system of single crystal SiC wafer in abrasive machining including radial crack, lateral crack and the median crack. In lapping process, material removal is dominated by brittle removal. Lots of chipping pits were found on the lapping surface. With the particle size becomes smaller, the surface roughness and subsurface crack depth decreases. When the particle size was changed to 1.5µm, the surface roughness Ra was reduced to 24.0nm and the maximum subsurface crack was 1.2µm. The efficiency of grinding is higher than lapping. Plastic removal can be achieved by changing the process parameters. Material removal was mostly in brittle fracture when grinding with 325# diamond wheel. Plow scratches and chipping pits were found on the ground surface. The surface roughness Ra was 17.7nm and maximum subsurface crack depth was 5.8 µm. When grinding with 8000# diamond wheel, the material removal was in plastic flow. Plastic scratches were found on the surface. A smooth surface of roughness Ra 2.5nm without any subsurface cracks was obtained. Atomic scale removal was possible in cluster magnetorheological finishing with diamond abrasive size of 0.5 µm. A super smooth surface eventually obtained with a roughness of Ra 0.4nm without any subsurface crack.

Falsely increased plasma lactate concentration due to ethylene glycol poisoning in 2 dogs.

PubMed

Hopper, Kate; Epstein, Steven E

2013-01-01

To describe false increases in plasma lactate concentration measured on point-of-care analyzers in 2 dogs with ethylene glycol (EG) intoxication. Two dogs presenting with EG intoxication had extreme increases of plasma lactate concentrations recorded on a point-of-care machine. Laboratory analysis by spectrophotometry of lactate concentration determined these lactate measurements to be erroneous. False increases in plasma lactate concentration were demonstrated in 2 out of 3 point-of-care machines tested. Glycolate, a toxic metabolite of EG, can interfere with the measurement of plasma lactate by some analyzers and this may delay the correct diagnosis of EG toxicity if not recognized. © Veterinary Emergency and Critical Care Society 2012.

Comparison between extreme learning machine and wavelet neural networks in data classification

NASA Astrophysics Data System (ADS)

Yahia, Siwar; Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

2017-03-01

Extreme learning Machine is a well known learning algorithm in the field of machine learning. It's about a feed forward neural network with a single-hidden layer. It is an extremely fast learning algorithm with good generalization performance. In this paper, we aim to compare the Extreme learning Machine with wavelet neural networks, which is a very used algorithm. We have used six benchmark data sets to evaluate each technique. These datasets Including Wisconsin Breast Cancer, Glass Identification, Ionosphere, Pima Indians Diabetes, Wine Recognition and Iris Plant. Experimental results have shown that both extreme learning machine and wavelet neural networks have reached good results.

29 CFR 1910.262 - Textiles.

Code of Federal Regulations, 2010 CFR

2010-07-01

... cutter is a machine consisting of one or more rotary blades used for the purpose of cutting textile... shall mean the point of contact between two in-running rolls. (25) Openers and pickers. Openers and... roller, doctor blades, etc. The machine is used for printing fabrics. (29) Ranges (bleaching continuous...

29 CFR 1910.262 - Textiles.

Code of Federal Regulations, 2013 CFR

2013-07-01

... cutter is a machine consisting of one or more rotary blades used for the purpose of cutting textile... shall mean the point of contact between two in-running rolls. (25) Openers and pickers. Openers and... roller, doctor blades, etc. The machine is used for printing fabrics. (29) Ranges (bleaching continuous...

29 CFR 1910.262 - Textiles.

Code of Federal Regulations, 2011 CFR

2011-07-01

... cutter is a machine consisting of one or more rotary blades used for the purpose of cutting textile... shall mean the point of contact between two in-running rolls. (25) Openers and pickers. Openers and... roller, doctor blades, etc. The machine is used for printing fabrics. (29) Ranges (bleaching continuous...

29 CFR 1910.262 - Textiles.

Code of Federal Regulations, 2014 CFR

2014-07-01

... cutter is a machine consisting of one or more rotary blades used for the purpose of cutting textile... shall mean the point of contact between two in-running rolls. (25) Openers and pickers. Openers and... roller, doctor blades, etc. The machine is used for printing fabrics. (29) Ranges (bleaching continuous...

29 CFR 1910.262 - Textiles.

Code of Federal Regulations, 2012 CFR

2012-07-01

... cutter is a machine consisting of one or more rotary blades used for the purpose of cutting textile... shall mean the point of contact between two in-running rolls. (25) Openers and pickers. Openers and... roller, doctor blades, etc. The machine is used for printing fabrics. (29) Ranges (bleaching continuous...

Single crystal diamond lapping procedure

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

Grayson, R.A.

A facility capable of resharpening quality cutting edges on single crystal diamond cutting tools was needed as the demand in precision machining of special optical surfaces became a common occurrence here at Lawrence Livermore National Laboratory. A specially constructed lapping machine using an air bearing spindle was built to achieve the required edge quality. The basic design for this lap was taken out of a technical report by W.L. Duke and R.T. Lovell of Oak Ridge Y-12 Plant Union Carbide Corp. We have also purchased two commercially built lapping machines recommended to us by Mr. Cory A. Knottenbelt, formerly ofmore » R.C.A. Diamond Lapping Facility, in Indianapolis, Indiana, now doing state-of-the-art polishing and relapping at LLNL facilities.« less

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, K.; Ignasiak, B.; Pawlak, W.; Kulik, C.; Lebowitz, H.E.

1995-12-05

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other mineral particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal. 4 figs.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, Kazimierz; Ignasiak, Boleslaw; Pawlak, Wanda; Kulik, Conrad; Lebowitz, Howard E.

1995-01-01

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, K.; Ignasiak, B.; Pawlak, W.; Kulik, C.; Lebowitz, H.E.

1997-02-11

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal. 4 figs.

Flotation machine and process for removing impurities from coals

DOEpatents

Szymocha, Kazimierz; Ignasiak, Boleslaw; Pawlak, Wanda; Kulik, Conrad; Lebowitz, Howard E.

1997-01-01

The present invention is directed to a type of flotation machine that combines three separate operations in a single unit. The flotation machine is a hydraulic separator that is capable of reducing the pyrite and other mineral matter content of a coal. When the hydraulic separator is used with a flotation system, the pyrite and certain other minerals particles that may have been entrained by hydrodynamic forces associated with conventional flotation machines and/or by the attachment forces associated with the formation of microagglomerates are washed and separated from the coal.

Dynamic provisioning of local and remote compute resources with OpenStack

NASA Astrophysics Data System (ADS)

Giffels, M.; Hauth, T.; Polgart, F.; Quast, G.

2015-12-01

Modern high-energy physics experiments rely on the extensive usage of computing resources, both for the reconstruction of measured events as well as for Monte-Carlo simulation. The Institut fur Experimentelle Kernphysik (EKP) at KIT is participating in both the CMS and Belle experiments with computing and storage resources. In the upcoming years, these requirements are expected to increase due to growing amount of recorded data and the rise in complexity of the simulated events. It is therefore essential to increase the available computing capabilities by tapping into all resource pools. At the EKP institute, powerful desktop machines are available to users. Due to the multi-core nature of modern CPUs, vast amounts of CPU time are not utilized by common desktop usage patterns. Other important providers of compute capabilities are classical HPC data centers at universities or national research centers. Due to the shared nature of these installations, the standardized software stack required by HEP applications cannot be installed. A viable way to overcome this constraint and offer a standardized software environment in a transparent manner is the usage of virtualization technologies. The OpenStack project has become a widely adopted solution to virtualize hardware and offer additional services like storage and virtual machine management. This contribution will report on the incorporation of the institute's desktop machines into a private OpenStack Cloud. The additional compute resources provisioned via the virtual machines have been used for Monte-Carlo simulation and data analysis. Furthermore, a concept to integrate shared, remote HPC centers into regular HEP job workflows will be presented. In this approach, local and remote resources are merged to form a uniform, virtual compute cluster with a single point-of-entry for the user. Evaluations of the performance and stability of this setup and operational experiences will be discussed.

Smart material screening machines using smart materials and controls

NASA Astrophysics Data System (ADS)

Allaei, Daryoush; Corradi, Gary; Waigand, Al

2002-07-01

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

Exploring a potential energy surface by machine learning for characterizing atomic transport

NASA Astrophysics Data System (ADS)

Kanamori, Kenta; Toyoura, Kazuaki; Honda, Junya; Hattori, Kazuki; Seko, Atsuto; Karasuyama, Masayuki; Shitara, Kazuki; Shiga, Motoki; Kuwabara, Akihide; Takeuchi, Ichiro

2018-03-01

We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for atomic transport. The proposed method generates numerous random samples of the entire potential energy surface (PES) from a probabilistic Gaussian process model of the PES, which enables defining the likelihood of the dominant points. The robustness and efficiency of the method are demonstrated on a dozen model cases for proton diffusion in oxides, in comparison with a conventional nudge elastic band method.

Simulation and Experimental Study on Surface Formation Mechanism in Machining of SiCp/Al Composites

NASA Astrophysics Data System (ADS)

Du, Jinguang; Zhang, Haizhen; He, Wenbin; Ma, Jun; Ming, Wuyi; Cao, Yang

2018-03-01

To intuitively reveal the surface formation mechanism in machining of SiCp/Al composites, in this paper the removal mode of reinforced particle and aluminum matrix, and their influence on surface formation mechanism were analyzed by single diamond grit cutting simulation and single diamond grit scratch experiment. Simulation and experiment results show that when the depth of cut is small, the scratched surface of the workpiece is relatively smooth; however, there are also irregular pits on the machined surface. When increasing the depth of cut, there are many obvious laminar structures on the scratched surface, and the surface appearance becomes coarser. When the cutting speed is small, the squeezing action of abrasive grit on SiC particles plays a dominant role in the extrusion of SiC particles. When increasing the cutting speed, SiC particles also occur broken or fractured; but the machined surface becomes smooth. When machining SiCp/Al composites, the SiC may happen in such removal ways, such as fracture, debonding, broken, sheared, pulled into and pulled out, etc. By means of reasonably developing micro cutting finite element simulation model of SiCp/Al composites could be used to analyze the surface formation process and particle removal way in different machining conditions.

Identifying the Root Causes of Wait States in Large-Scale Parallel Applications

DOE PAGES

Böhme, David; Geimer, Markus; Arnold, Lukas; ...

2016-07-20

Driven by growing application requirements and accelerated by current trends in microprocessor design, the number of processor cores on modern supercomputers is increasing from generation to generation. However, load or communication imbalance prevents many codes from taking advantage of the available parallelism, as delays of single processes may spread wait states across the entire machine. Moreover, when employing complex point-to-point communication patterns, wait states may propagate along far-reaching cause-effect chains that are hard to track manually and that complicate an assessment of the actual costs of an imbalance. Building on earlier work by Meira Jr. et al., we present amore » scalable approach that identifies program wait states and attributes their costs in terms of resource waste to their original cause. Ultimately, by replaying event traces in parallel both forward and backward, we can identify the processes and call paths responsible for the most severe imbalances even for runs with hundreds of thousands of processes.« less

Identifying the Root Causes of Wait States in Large-Scale Parallel Applications

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

Böhme, David; Geimer, Markus; Arnold, Lukas

Driven by growing application requirements and accelerated by current trends in microprocessor design, the number of processor cores on modern supercomputers is increasing from generation to generation. However, load or communication imbalance prevents many codes from taking advantage of the available parallelism, as delays of single processes may spread wait states across the entire machine. Moreover, when employing complex point-to-point communication patterns, wait states may propagate along far-reaching cause-effect chains that are hard to track manually and that complicate an assessment of the actual costs of an imbalance. Building on earlier work by Meira Jr. et al., we present amore » scalable approach that identifies program wait states and attributes their costs in terms of resource waste to their original cause. Ultimately, by replaying event traces in parallel both forward and backward, we can identify the processes and call paths responsible for the most severe imbalances even for runs with hundreds of thousands of processes.« less

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

Code of Federal Regulations, 2014 CFR

2014-07-01

... approved machines will be accepted in lieu of certified components. (b) A single layout drawing (see Figure... approval. A design of the approval plate will accompany the notification of approval. (Refer to §§ 18.10...

A STUDY OF DISLOCATION STRUCTURE OF SUBBOUNDARIES IN MOLYBDENUM SINGLE CRYSTALS,

DTIC Science & Technology

MOLYBDENUM, *DISLOCATIONS), GRAIN STRUCTURES(METALLURGY), SINGLE CRYSTALS, ZONE MELTING, ELECTRON BEAM MELTING, GRAIN BOUNDARIES, MATHEMATICAL ANALYSIS, ETCHED CRYSTALS, ETCHING, ELECTROEROSIVE MACHINING, CHINA

Accuracy and Reliability of a New Tennis Ball Machine

PubMed Central

Brechbuhl, Cyril; Millet, Grégoire; Schmitt, Laurent

2016-01-01

The aim was to evaluate the reliability of a newly-developed ball machine named 'Hightof', on the field and to assess its accuracy. The experiment was conducted in the collaboration of the 'Hawk-Eye' technology. The accuracy and reliability of this ball machine were assessed during an incremental test, with 1 min of exercise and 30 sec of recovery, where the frequency of the balls increased from 10 to 30 balls·min-1. The initial frequency was 10 and increased by 2 until 22, then by 1 until 30 balls·min-1. The reference points for the impact were 8.39m from the net and 2.70m from lateral line for the right side and 2.83m for the left side. The precision of the machine was similar on the right and left sides (0.63 ± 0.39 vs 0.63 ± 0.34 m). The distances to the reference point were 0.52 ± 0.42, 0.26 ± 0.19, 0.52 ± 0.37, 0.28 ± 0.19 m for the Y-right, X-right, Y-left and X-left impacts. The precision was constant and did not increase with the intensity. (e.g ball frequency). The ball velocity was 86.3 ± 1.5 and 86.5 ± 1.3 km·h-1 for the right and the left side, respectively. The coefficient of variation for the velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min-1). Conclusion: both the accuracy and the reliability of this new ball machine appear satisfying enough for field testing and training. Key points The reliability and accuracy of a new ball machine named 'Hightof' were assessed. The impact point was reproducible and similar on the right and left sides (±0.63 m). The precision was constant and did not increase with the intensity (e.g ball frequency). The coefficient of variation of the ball velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min-1). PMID:27274663

Accuracy and Reliability of a New Tennis Ball Machine.

PubMed

Brechbuhl, Cyril; Millet, Grégoire; Schmitt, Laurent

2016-06-01

The aim was to evaluate the reliability of a newly-developed ball machine named 'Hightof', on the field and to assess its accuracy. The experiment was conducted in the collaboration of the 'Hawk-Eye' technology. The accuracy and reliability of this ball machine were assessed during an incremental test, with 1 min of exercise and 30 sec of recovery, where the frequency of the balls increased from 10 to 30 balls·min(-1). The initial frequency was 10 and increased by 2 until 22, then by 1 until 30 balls·min(-1). The reference points for the impact were 8.39m from the net and 2.70m from lateral line for the right side and 2.83m for the left side. The precision of the machine was similar on the right and left sides (0.63 ± 0.39 vs 0.63 ± 0.34 m). The distances to the reference point were 0.52 ± 0.42, 0.26 ± 0.19, 0.52 ± 0.37, 0.28 ± 0.19 m for the Y-right, X-right, Y-left and X-left impacts. The precision was constant and did not increase with the intensity. (e.g ball frequency). The ball velocity was 86.3 ± 1.5 and 86.5 ± 1.3 km·h(-1) for the right and the left side, respectively. The coefficient of variation for the velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min(-1)). both the accuracy and the reliability of this new ball machine appear satisfying enough for field testing and training. Key pointsThe reliability and accuracy of a new ball machine named 'Hightof' were assessed.The impact point was reproducible and similar on the right and left sides (±0.63 m).The precision was constant and did not increase with the intensity (e.g ball frequency).The coefficient of variation of the ball velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min(-1)).

SU-F-T-284: The Effect of Linear Accelerator Output Variation On the Quality of Patient Specific Rapid Arc Verification Plans

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

Sandhu, G; Cao, F; Szpala, S

2016-06-15

Purpose: The aim of the current study is to investigate the effect of machine output variation on the delivery of the RapidArc verification plans. Methods: Three verification plans were generated using Eclipse™ treatment planning system (V11.031) with plan normalization value 100.0%. These plans were delivered on the linear accelerators using ArcCHECK− device, with machine output 1.000 cGy/MU at calibration point. These planned and delivered dose distributions were used as reference plans. Additional plans were created in Eclipse− with normalization values ranging 92.80%–102% to mimic the machine output ranging 1.072cGy/MU-0.980cGy/MU, at the calibration point. These plans were compared against the referencemore » plans using gamma indices (3%, 3mm) and (2%, 2mm). Calculated gammas were studied for its dependence on machine output. Plans were considered passed if 90% of the points satisfy the defined gamma criteria. Results: The gamma index (3%, 3mm) was insensitive to output fluctuation within the output tolerance level (2% of calibration), and showed failures, when the machine output exceeds ≥3%. Gamma (2%, 2mm) was found to be more sensitive to the output variation compared to the gamma (3%, 3mm), and showed failures, when output exceeds ≥1.7%. The variation of the gamma indices with output variability also showed dependence upon the plan parameters (e.g. MLC movement and gantry rotation). The variation of the percentage points passing gamma criteria with output variation followed a non-linear decrease beyond the output tolerance level. Conclusion: Data from the limited plans and output conditions showed that gamma (2%, 2mm) is more sensitive to the output fluctuations compared to Gamma (3%,3mm). Work under progress, including detail data from a large number of plans and a wide range of output conditions, may be able to conclude the quantitative dependence of gammas on machine output, and hence the effect on the quality of delivered rapid arc plans.« less

Method for measuring the contour of a machined part

DOEpatents

Bieg, L.F.

1995-05-30

A method is disclosed for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining. 5 figs.

Method for measuring the contour of a machined part

DOEpatents

Bieg, Lothar F.

1995-05-30

A method for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

A Microfluidic Cytometer for Complete Blood Count With a 3.2-Megapixel, 1.1- μm-Pitch Super-Resolution Image Sensor in 65-nm BSI CMOS.

PubMed

Liu, Xu; Huang, Xiwei; Jiang, Yu; Xu, Hang; Guo, Jing; Hou, Han Wei; Yan, Mei; Yu, Hao

2017-08-01

Based on a 3.2-Megapixel 1.1- μm-pitch super-resolution (SR) CMOS image sensor in a 65-nm backside-illumination process, a lens-free microfluidic cytometer for complete blood count (CBC) is demonstrated in this paper. Backside-illumination improves resolution and contrast at the device level with elimination of surface treatment when integrated with microfluidic channels. A single-frame machine-learning-based SR processing is further realized at system level for resolution correction with minimum hardware resources. The demonstrated microfluidic cytometer can detect the platelet cells (< 2 μm) required in CBC, hence is promising for point-of-care diagnostics.

Retrieval techniques and graphics displays using a computerized stellar data base

NASA Technical Reports Server (NTRS)

Mead, J.; Nagy, T. A.

1977-01-01

The paper describes a stellar data retrieval system for which the data base consists of 28 machine-readable astronomical catalogs. Eleven of these catalogs have been combined into the Goddard Cross Index (GCI), which serves as the computer entry point to these catalogs. The full data entry from any of the GCI catalogs can be retrieved in a single computer run. With this system, it is possible to prepare candidates for observation by searching the data base for stars with given characteristics. Generation of plots of all catalog stars in or near the telescope's field of view to scale of Palomar, other atlases, or to the telescope itself for use as observing charts or to aid in identifying unknown sources, can be accomplished.

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

76 FR 30200 - Forging Machines; Extension of the Office of Management and Budget's (OMB) Approval of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-24

...: 187,264. Estimated Cost (Operation and Maintenance): $0. IV. Public Participation--Submission of... ensures that information is in the desired format, reporting burden (time and costs) is minimal... operated valves and switches. Inspection of Forging Machines, Guards, and Point-of-Operation Protection...

On the integrability of the motion of 3D-Swinging Atwood machine and related problems

NASA Astrophysics Data System (ADS)

Elmandouh, A. A.

2016-03-01

In the present article, we study the problem of the motion of 3D- Swinging Atwood machine. A new integrable case for this problem is announced. We point out a new integrable case describing the motion of a heavy particle on a titled cone.

Grindability and mechanical property of ceramics

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

Guo, Changsheng; Chand, R.H.

1996-12-31

For cost-effective ceramic machining, material-specific machining methodology is needed. This requires characterizing ceramics from machining view point. In this paper, a preliminary study of the correlation between grindability and mechanical properties is reported. Results indicate that there exists complex correlations between grindability and mechanical properties such as hardness, fracture toughness and elasticity. Some ceramics of similar mechanical properties have different grindabilities, which implies that it is possible to develop ceramics of both superior mechanical properties and good grindability.

Multisensor systems today and tomorrow: Machine control, diagnosis and thermal compensation

NASA Astrophysics Data System (ADS)

Nunzio, D'Addea

2000-05-01

Multisensor techniques that deal with control of tribology test rig and with diagnosis and thermal error compensation of machine tools are the starting point for some consideration about the use of these techniques as in fuzzy and neural net systems. The author comes to conclusion that anticipatory systems and multisensor techniques will have in the next future a great improvement and a great development mainly in the thermal error compensation of machine tools.

Experiments on PIM in Support of the Development of IVA Technology for Radiography at AWE

NASA Astrophysics Data System (ADS)

Clough, Stephen G.; Thomas, Kenneth J.; Williamson, Mark C.; Phillips, Martin J.; Smith, Ian D.; Bailey, Vernon L.; Kishi, Hiroshi J.; Maenchen, John E.; Johnson, David L.

2002-12-01

The PIM machine has been designed and constructed at AWE as part of a program to investigate IVA technology for radiographic applications. PIM, as originally constructed, was a prospective single module of a 14 MV, 100 kA, ten module machine. The design of such a machine is a primary goal of the program as several are required to provide multi-axis radiography in a new Hydrodynamics Research Facility (HRF). Another goal is to design lower voltage machines (ranging from 1 to 5 MV) utilizing PIM style components. The original PIM machine consisted of a single inductive cavity pulsed by a 10 ohm water dielectric Blumlein pulse forming line (PFL) charged by a Marx generator. These components successfully achieved their design voltages and data on the prepulse was obtained showing it to be worse than expected. This information provided a basis for design work on the 14 MV HRF IVA, carried out by Titan-PSD, resulting in a proposal for a prepulse switch, a prototype of which should be installed on PIM by the end of this year. The original single, coaxial switch used to initiate the Blumlein has been replaced by a prototype laser triggered switching arrangement, also designed by Titan-PSD, which it was desired to test prior to its eventual use in the HRF. Despite problems with the laser, which will necessitate further experiments, it was determined that laser triggering with low jitter was occurring. A split oil co-ax feed has now been used to install a second cavity, in parallel with the first, on the PIM Blumlein. This two cavity configuration provides a prototype for future radiographic machines operating at up to 3 MV and a test facility for diode research.

Ultra precision machining

NASA Astrophysics Data System (ADS)

Debra, Daniel B.; Hesselink, Lambertus; Binford, Thomas

1990-05-01

There are a number of fields that require or can use to advantage very high precision in machining. For example, further development of high energy lasers and x ray astronomy depend critically on the manufacture of light weight reflecting metal optical components. To fabricate these optical components with machine tools they will be made of metal with mirror quality surface finish. By mirror quality surface finish, it is meant that the dimensions tolerances on the order of 0.02 microns and surface roughness of 0.07. These accuracy targets fall in the category of ultra precision machining. They cannot be achieved by a simple extension of conventional machining processes and techniques. They require single crystal diamond tools, special attention to vibration isolation, special isolation of machine metrology, and on line correction of imperfection in the motion of the machine carriages on their way.

A comparison of machine learning and Bayesian modelling for molecular serotyping.

PubMed

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological insights, which we illustrate with an example.

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.

Alternator control for battery charging

DOEpatents

Brunstetter, Craig A.; Jaye, John R.; Tallarek, Glen E.; Adams, Joseph B.

2015-07-14

In accordance with an aspect of the present disclosure, an electrical system for an automotive vehicle has an electrical generating machine and a battery. A set point voltage, which sets an output voltage of the electrical generating machine, is set by an electronic control unit (ECU). The ECU selects one of a plurality of control modes for controlling the alternator based on an operating state of the vehicle as determined from vehicle operating parameters. The ECU selects a range for the set point voltage based on the selected control mode and then sets the set point voltage within the range based on feedback parameters for that control mode. In an aspect, the control modes include a trickle charge mode and battery charge current is the feedback parameter and the ECU controls the set point voltage within the range to maintain a predetermined battery charge current.

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

Evolution of stacking fault tetrahedral and work hardening effect in copper single crystals

NASA Astrophysics Data System (ADS)

Liu, Hai Tao; Zhu, Xiu Fu; Sun, Ya Zhou; Xie, Wen Kun

2017-11-01

Stacking fault tetrahedral (SFT), generated in machining of copper single crystal as one type of subsurface defects, has significant influence on the performance of workpiece. In this study, molecular dynamics (MD) simulation is used to investigate the evolution of stacking fault tetrahedral in nano-cutting of copper single crystal. The result shows that SFT is nucleated at the intersection of differently oriented stacking fault (SF) planes and SFT evolves from the preform only containing incomplete surfaces into a solid defect. The evolution of SFT contains several stress fluctuations until the complete formation. Nano-indentation simulation is then employed on the machined workpiece from nano-cutting, through which the interaction between SFT and later-formed dislocations in subsurface is studied. In the meanwhile, force-depth curves obtained from nano-indentation on pristine and machined workpieces are compared to analyze the mechanical properties. By simulation of nano-cutting and nano-indentation, it is verified that SFT is a reason of the work hardening effect.

Single-molecule protein unfolding and translocation by an ATP-fueled proteolytic machine

PubMed Central

Aubin-Tam, Marie-Eve; Olivares, Adrian O.; Sauer, Robert T.; Baker, Tania A.; Lang, Matthew J.

2011-01-01

All cells employ ATP-powered proteases for protein-quality control and regulation. In the ClpXP protease, ClpX is a AAA+ machine that recognizes specific protein substrates, unfolds these molecules, and then translocates the denatured polypeptide through a central pore and into ClpP for degradation. Here, we use optical-trapping nanometry to probe the mechanics of enzymatic unfolding and translocation of single molecules of a multidomain substrate. Our experiments demonstrate the capacity of ClpXP and ClpX to perform mechanical work under load, reveal very fast and highly cooperative unfolding of individual substrate domains, suggest a translocation step size of 5–8 amino acids, and support a power-stroke model of denaturation in which successful enzyme-mediated unfolding of stable domains requires coincidence between mechanical pulling by the enzyme and a transient stochastic reduction in protein stability. We anticipate that single-molecule studies of the mechanical properties of other AAA+ proteolytic machines will reveal many shared features with ClpXP. PMID:21496645

Classifying bent radio galaxies from a mixture of point-like/extended images with Machine Learning.

NASA Astrophysics Data System (ADS)

Bastien, David; Oozeer, Nadeem; Somanah, Radhakrishna

2017-05-01

The hypothesis that bent radio sources are supposed to be found in rich, massive galaxy clusters and the avalibility of huge amount of data from radio surveys have fueled our motivation to use Machine Learning (ML) to identify bent radio sources and as such use them as tracers for galaxy clusters. The shapelet analysis allowed us to decompose radio images into 256 features that could be fed into the ML algorithm. Additionally, ideas from the field of neuro-psychology helped us to consider training the machine to identify bent galaxies at different orientations. From our analysis, we found that the Random Forest algorithm was the most effective with an accuracy rate of 92% for a classification of point and extended sources as well as an accuracy of 80% for bent and unbent classification.

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

Wang Yinan; Shi Handuo; Xiong Zhaoxi

We present a unified universal quantum cloning machine, which combines several different existing universal cloning machines together, including the asymmetric case. In this unified framework, the identical pure states are projected equally into each copy initially constituted by input and one half of the maximally entangled states. We show explicitly that the output states of those universal cloning machines are the same. One importance of this unified cloning machine is that the cloning procession is always the symmetric projection, which reduces dramatically the difficulties for implementation. Also, it is found that this unified cloning machine can be directly modified tomore » the general asymmetric case. Besides the global fidelity and the single-copy fidelity, we also present all possible arbitrary-copy fidelities.« less

Ball Machine Usage in Tennis: Movement Initiation and Swing Timing While Returning Balls from a Ball Machine and from a Real Server

PubMed Central

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-01-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers’ movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key points Players have shorter initial move time when they are facing the ball machine. Using the ball machine results in different swing timing and movement coordination. The use of the ball machine should be limited. PMID:24790483

Ball machine usage in tennis: movement initiation and swing timing while returning balls from a ball machine and from a real server.

PubMed

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-05-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers' movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key pointsPlayers have shorter initial move time when they are facing the ball machine.Using the ball machine results in different swing timing and movement coordination.The use of the ball machine should be limited.

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Zubair, Mohammad

1993-01-01

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

Revisit of Machine Learning Supported Biological and Biomedical Studies.

PubMed

Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

2018-01-01

Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

Cutting tool form compensation system and method

DOEpatents

Barkman, W.E.; Babelay, E.F. Jr.; Klages, E.J.

1993-10-19

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed. 9 figures.

Cutting tool form compensaton system and method

DOEpatents

Barkman, William E.; Babelay, Jr., Edwin F.; Klages, Edward J.

1993-01-01

A compensation system for a computer-controlled machining apparatus having a controller and including a cutting tool and a workpiece holder which are movable relative to one another along a preprogrammed path during a machining operation utilizes a camera and a vision computer for gathering information at a preselected stage of a machining operation relating to the actual shape and size of the cutting edge of the cutting tool and for altering the preprogrammed path in accordance with detected variations between the actual size and shape of the cutting edge and an assumed size and shape of the cutting edge. The camera obtains an image of the cutting tool against a background so that the cutting tool and background possess contrasting light intensities, and the vision computer utilizes the contrasting light intensities of the image to locate points therein which correspond to points along the actual cutting edge. Following a series of computations involving the determining of a tool center from the points identified along the tool edge, the results of the computations are fed to the controller where the preprogrammed path is altered as aforedescribed.

Cost Estimate for Gun Liner Emplacement

DTIC Science & Technology

2011-08-01

material. The M2 machine gun has a Stellite 21 liner that covers only about one-half of the barrel length. It has been successful in reducing the...Michael R. M2 Machine Gun Barrel Wear with SLAP Ammunition. To be published in Journal of Materials and Manufacturing Processes. 8. Miller, Mark D...case in point is the use of a Stellite 21 liner in the M2 0.50-cal machine gun . However, liners have generally been difficult to place into gun tubes

SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

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

Imae, T; Haga, A; Saotome, N

Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions ofmore » multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target.« less

Implementation of electronic locking devices for adolescents at German tobacco vending machines: intended and unintended changes of supply and demand.

PubMed

Schneider, S; Meyer, C; Yamamoto, S; Solle, D

2009-08-01

Starting from 1 January 2007, electronic locking devices based on proof-of-age (via electronic cash cards or a European driving licence) were installed in approximately 500,000 vending machines across Germany to restrict the purchase of cigarettes to those over the age of 16. To examine changes in the number of tobacco vending machines before and after the introduction of these new measures. The total number of commercial tobacco sources in 2 selected districts (70,000 inhabitants) in Cologne were recorded and mapped. This major German city was the ideal setting for this study as investigators were able to use existing sociogeographical data from the area. A complete inventory was compiled in autumn 2005 and 2007. A total of 780 students aged 12 to 15 were also interviewed in the study areas. The main outcome measures were quantities and locations of commercial tobacco sources. Between 2005 and 2007 the total number of tobacco sources decreased from 315 to 277 within the study area. Although the most obvious reduction was detected in the number of outdoor vending machines (-48%), the number of indoor vending machines also decreased by 8%. Adolescents changed from vending machines to other sources for cigarettes, particularly kiosks or friends (+31% points usage rate, p<0.001; +35% points usage rate, p<0.001, respectively). Although the number of tobacco vending machines decreased, this has not had a significant impact on cigarette acquisition by underage smokers as they were able to circumvent this new security measure in several different ways.

Contemporary machine learning: techniques for practitioners in the physical sciences

NASA Astrophysics Data System (ADS)

Spears, Brian

2017-10-01

Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Self aligning electron beam gun having enhanced thermal and mechanical stability

DOEpatents

Scarpetti, R.D. Jr.; Parkison, C.D.; Switzer, V.A.; Lee, Y.J.; Sawyer, W.C.

1995-05-16

A compact, high power electron gun is disclosed having enhanced thermal and mechanical stability which incorporates a mechanically coupled, self aligning structure for the anode and cathode. The enhanced stability, and reduced need for realignment of the cathode to the anode and downstream optics during operation are achieved by use of a common support structure for the cathode and anode which requires no adjustment screws or spacers. The electron gun of the present invention also incorporates a modular design for the cathode, in which the electron emitter, its support structure, and the hardware required to attach the emitter assembly to the rest of the gun are a single element. This modular design makes replacement of the emitter simpler and requires no realignment after a new emitter has been installed. Compactness and a reduction in the possibility of high voltage breakdown are achieved by shielding the ``triple point`` where the electrode, insulator, and vacuum meet. The use of electric discharge machining (EDM) for fabricating the emitter allows for the accurate machining of the emitter into intricate shapes without encountering the normal stresses developed by standard emitter fabrication techniques. 12 Figs.

Robust one-step catalytic machine for high fidelity anticloning and W-state generation in a multiqubit system.

PubMed

Olaya-Castro, Alexandra; Johnson, Neil F; Quiroga, Luis

2005-03-25

We propose a physically realizable machine which can either generate multiparticle W-like states, or implement high-fidelity 1-->M (M=1,2,...infinity) anticloning of an arbitrary qubit state, in a single step. This universal machine acts as a catalyst in that it is unchanged after either procedure, effectively resetting itself for its next operation. It possesses an inherent immunity to decoherence. Most importantly in terms of practical multiparty quantum communication, the machine's robustness in the presence of decoherence actually increases as the number of qubits M increases.

Law machines: scale models, forensic materiality and the making of modern patent law.

PubMed

Pottage, Alain

2011-10-01

Early US patent law was machine made. Before the Patent Office took on the function of examining patent applications in 1836, questions of novelty and priority were determined in court, within the forum of the infringement action. And at all levels of litigation, from the circuit courts up to the Supreme Court, working models were the media through which doctrine, evidence and argument were made legible, communicated and interpreted. A model could be set on a table, pointed at, picked up, rotated or upended so as to display a point of interest to a particular audience within the courtroom, and, crucially, set in motion to reveal the 'mode of operation' of a machine. The immediate object of demonstration was to distinguish the intangible invention from its tangible embodiment, but models also'machined' patent law itself. Demonstrations of patent claims with models articulated and resolved a set of conceptual tensions that still make the definition and apprehension of the invention difficult, even today, but they resolved these tensions in the register of materiality, performativity and visibility, rather than the register of conceptuality. The story of models tells us something about how inventions emerge and subsist within the context of patent litigation and patent doctrine, and it offers a starting point for renewed reflection on the question of how technology becomes property.

The LET Procedure for Prosthetic Myocontrol: Towards Multi-DOF Control Using Single-DOF Activations.

PubMed

Nowak, Markus; Castellini, Claudio

2016-01-01

Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an open problem. With the advent of commercially and clinically available multi-fingered hand prostheses there are now more independent degrees of freedom (DOFs) in prostheses than can be effectively controlled using surface electromyography (sEMG), the current standard human-machine interface for hand amputees. In particular, it is uncertain, whether several DOFs can be controlled simultaneously and proportionally by exclusively calibrating the intended activation of single DOFs. The problem is currently solved by training on all required combinations. However, as the number of available DOFs grows, this approach becomes overly long and poses a high cognitive burden on the subject. In this paper we present a novel approach to overcome this problem. Multi-DOF activations are artificially modelled from single-DOF ones using a simple linear combination of sEMG signals, which are then added to the training set. This procedure, which we named LET (Linearly Enhanced Training), provides an augmented data set to any machine-learning-based intent detection system. In two experiments involving intact subjects, one offline and one online, we trained a standard machine learning approach using the full data set containing single- and multi-DOF activations as well as using the LET-augmented data set in order to evaluate the performance of the LET procedure. The results indicate that the machine trained on the latter data set obtains worse results in the offline experiment compared to the full data set. However, the online implementation enables the user to perform multi-DOF tasks with almost the same precision as single-DOF tasks without the need of explicitly training multi-DOF activations. Moreover, the parameters involved in the system are statistically uniform across subjects.

Three independent one-dimensional margins for single-fraction frameless stereotactic radiosurgery brain cases using CBCT

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

Zhang, Qinghui; Chan, Maria F.; Burman, Chandra

2013-12-15

Purpose: Setting a proper margin is crucial for not only delivering the required radiation dose to a target volume, but also reducing the unnecessary radiation to the adjacent organs at risk. This study investigated the independent one-dimensional symmetric and asymmetric margins between the clinical target volume (CTV) and the planning target volume (PTV) for linac-based single-fraction frameless stereotactic radiosurgery (SRS).Methods: The authors assumed a Dirac delta function for the systematic error of a specific machine and a Gaussian function for the residual setup errors. Margin formulas were then derived in details to arrive at a suitable CTV-to-PTV margin for single-fractionmore » frameless SRS. Such a margin ensured that the CTV would receive the prescribed dose in 95% of the patients. To validate our margin formalism, the authors retrospectively analyzed nine patients who were previously treated with noncoplanar conformal beams. Cone-beam computed tomography (CBCT) was used in the patient setup. The isocenter shifts between the CBCT and linac were measured for a Varian Trilogy linear accelerator for three months. For each plan, the authors shifted the isocenter of the plan in each direction by ±3 mm simultaneously to simulate the worst setup scenario. Subsequently, the asymptotic behavior of the CTV V{sub 80%} for each patient was studied as the setup error approached the CTV-PTV margin.Results: The authors found that the proper margin for single-fraction frameless SRS cases with brain cancer was about 3 mm for the machine investigated in this study. The isocenter shifts between the CBCT and the linac remained almost constant over a period of three months for this specific machine. This confirmed our assumption that the machine systematic error distribution could be approximated as a delta function. This definition is especially relevant to a single-fraction treatment. The prescribed dose coverage for all the patients investigated was 96.1%± 5.5% with an extreme 3-mm setup error in all three directions simultaneously. It was found that the effect of the setup error on dose coverage was tumor location dependent. It mostly affected the tumors located in the posterior part of the brain, resulting in a minimum coverage of approximately 72%. This was entirely due to the unique geometry of the posterior head.Conclusions: Margin expansion formulas were derived for single-fraction frameless SRS such that the CTV would receive the prescribed dose in 95% of the patients treated for brain cancer. The margins defined in this study are machine-specific and account for nonzero mean systematic error. The margin for single-fraction SRS for a group of machines was also derived in this paper.« less

Financial heat machine

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2005-05-01

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

An in-situ measuring method for planar straightness error

NASA Astrophysics Data System (ADS)

Chen, Xi; Fu, Luhua; Yang, Tongyu; Sun, Changku; Wang, Zhong; Zhao, Yan; Liu, Changjie

2018-01-01

According to some current problems in the course of measuring the plane shape error of workpiece, an in-situ measuring method based on laser triangulation is presented in this paper. The method avoids the inefficiency of traditional methods like knife straightedge as well as the time and cost requirements of coordinate measuring machine(CMM). A laser-based measuring head is designed and installed on the spindle of a numerical control(NC) machine. The measuring head moves in the path planning to measure measuring points. The spatial coordinates of the measuring points are obtained by the combination of the laser triangulation displacement sensor and the coordinate system of the NC machine, which could make the indicators of measurement come true. The method to evaluate planar straightness error adopts particle swarm optimization(PSO). To verify the feasibility and accuracy of the measuring method, simulation experiments were implemented with a CMM. Comparing the measurement results of measuring head with the corresponding measured values obtained by composite measuring machine, it is verified that the method can realize high-precise and automatic measurement of the planar straightness error of the workpiece.

The development of a control system for a small high speed steam microturbine generator system

NASA Astrophysics Data System (ADS)

Alford, A.; Nichol, P.; Saunders, M.; Frisby, B.

2015-08-01

Steam is a widely used energy source. In many situations steam is generated at high pressures and then reduced in pressure through control valves before reaching point of use. An opportunity was identified to convert some of the energy at the point of pressure reduction into electricity. To take advantage of a market identified for small scale systems, a microturbine generator was designed based on a small high speed turbo machine. This machine was packaged with the necessary control valves and systems to allow connection of the machine to the grid. Traditional machines vary the speed of the generator to match the grid frequency. This was not possible due to the high speed of this machine. The characteristics of the rotating unit had to be understood to allow a control that allowed export of energy at the right frequency to the grid under the widest possible range of steam conditions. A further goal of the control system was to maximise the efficiency of generation under all conditions. A further complication was to provide adequate protection for the rotating unit in the event of the loss of connection to the grid. The system to meet these challenges is outlined with the solutions employed and tested for this application.

Classification of LIDAR Data for Generating a High-Precision Roadway Map

NASA Astrophysics Data System (ADS)

Jeong, J.; Lee, I.

2016-06-01

Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

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

Cernoch, Antonin; Soubusta, Jan; Celechovska, Lucie

We report on experimental implementation of the optimal universal asymmetric 1->2 quantum cloning machine for qubits encoded into polarization states of single photons. Our linear-optical machine performs asymmetric cloning by partially symmetrizing the input polarization state of signal photon and a blank copy idler photon prepared in a maximally mixed state. We show that the employed method of measurement of mean clone fidelities exhibits strong resilience to imperfect calibration of the relative efficiencies of single-photon detectors used in the experiment. Reliable characterization of the quantum cloner is thus possible even when precise detector calibration is difficult to achieve.

Low-cost autonomous perceptron neural network inspired by quantum computation

NASA Astrophysics Data System (ADS)

Zidan, Mohammed; Abdel-Aty, Abdel-Haleem; El-Sadek, Alaa; Zanaty, E. A.; Abdel-Aty, Mahmoud

2017-11-01

Achieving low cost learning with reliable accuracy is one of the important goals to achieve intelligent machines to save time, energy and perform learning process over limited computational resources machines. In this paper, we propose an efficient algorithm for a perceptron neural network inspired by quantum computing composite from a single neuron to classify inspirable linear applications after a single training iteration O(1). The algorithm is applied over a real world data set and the results are outer performs the other state-of-the art algorithms.

Single machine scheduling with slack due dates assignment

NASA Astrophysics Data System (ADS)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.

TRUFLO GONDOLA, USED WITH THE HUNTER 10 MOLDING MACHINE, OPERATES ...

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

TRUFLO GONDOLA, USED WITH THE HUNTER 10 MOLDING MACHINE, OPERATES THE SAME AS THE TWO LARGER TRUFLOS USED IN CONJUNCTION WITH THE TWO HUNTER 20S. EACH GONDOLA IS CONNECTED TO THE NEXT AND RIDES ON A SINGLE TRACK RAIL FROM MOLDING MACHINES THROUGH POURING AREAS CARRYING A MOLD AROUND TWICE BEFORE THE MOLD IS PUSHED OFF ONTO A VIBRATING SHAKEOUT CONVEYOR. - Southern Ductile Casting Company, Casting, 2217 Carolina Avenue, Bessemer, Jefferson County, AL

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

PubMed

Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean

2017-12-04

Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further using multiple metrics with much larger scale comparisons, prospective testing as well as assessment of different fingerprints and DNN architectures beyond those used.

Analysis of Adhesively Bonded Ceramics Using an Asymmetric Wedge Test

DTIC Science & Technology

2008-12-01

4 Figure 2. Average crack ...flexure specimen. The flaw, indicated by the white arrow, is a subsurface semi-elliptical crack induced by surface machining damage...strength-limiting orthogonal surface machining crack in an alumina flexure specimen coated with a single layer of film adhesive. The white arrow

In vivo and in vitro performance of a China-made hemodialysis machine: a multi-center prospective controlled study.

PubMed

Wang, Yong; Chen, Xiang-Mei; Cai, Guang-Yan; Li, Wen-Ge; Zhang, Ai-Hua; Hao, Li-Rong; Shi, Ming; Wang, Rong; Jiang, Hong-Li; Luo, Hui-Min; Zhang, Dong; Sun, Xue-Feng

2017-08-02

To evaluate the in vivo and in vitro performance of a China-made dialysis machine (SWS-4000). This was a multi-center prospective controlled study consisting of both long-term in vitro evaluations and cross-over in vivo tests in 132 patients. The China-made SWS-4000 dialysis machine was compared with a German-made dialysis machine (Fresenius 4008) with regard to Kt/V values, URR values, and dialysis-related adverse reactions in patients on maintenance hemodialysis, as well as the ultrafiltration rate, the concentration of electrolytes in the proportioned dialysate, the rate of heparin injection, the flow rate of the blood pump, and the rate of malfunction. The Kt/V and URR values at the 1st and 4th weeks of dialysis as well as the incidence of adverse effects did not differ between the two groups in cross-over in vivo tests (P > 0.05). There were no significant differences between the two groups in the error values of the ultrafiltration rate, the rate of heparin injection or the concentrations of electrolytes in the proportioned dialysate at different time points under different parameter settings. At weeks 2 and 24, with the flow rate of the blood pump set at 300 mL/min, the actual error of the SWS-4000 dialysis machine was significantly higher than that of the Fresenius 4008 dialysis machine (P < 0.05), but there was no significant difference at other time points or under other settings (P > 0.05). The malfunction rate was higher in the SWS-4000 group than in the Fresenius 4008 group (P < 0.05). The in vivo performance of the SWS-4000 dialysis machine is roughly comparable to that of the Fresenius 4008 dialysis machine; however, the malfunction rate of the former is higher than that of the latter in in vitro tests. The stability and long-term accuracy of the SWS-4000 dialysis machine remain to be improved.

Effect of heat treatments on machinability of gold alloy with age-hardenability at intraoral temperature.

PubMed

Watanabe, I; Baba, N; Watanabe, E; Atsuta, M; Okabe, T

2004-01-01

This study investigated the effect of heat treatment on the machinability of heat-treated cast gold alloy with age-hardenability at intraoral temperature using a handpiece engine with SiC wheels and an air-turbine handpiece with carbide burs and diamond points. Cast gold alloy specimens underwent various heat treatments [As-cast (AC); Solution treatment (ST); High-temperature aging (HA), Intraoral aging (IA)] before machinability testing. The machinability test was conducted at a constant machining force of 0.784N. The three circumferential speeds used for the handpiece engine were 500, 1,000 and 1,500 m/min. The machinability index (M-index) was determined as the amount of metal removed by machining (volume loss, mm(3)). The results were analyzed by ANOVA and Scheffé's test. When an air-turbine handpiece was used, there was no difference in the M-index of the gold alloy among the heat treatments. The air-turbine carbide burs showed significantly (p<0.05) higher M-indexes than the diamond points after any heat treatments. With the SiC wheels, increasing the circumferential speed increased the M-index values for each heat treatment. The specimens heat-treated with AC, HA and IA had similar M-indexes at the lower speeds (500 and 1,000 m/min). The ST specimens exhibited the lowest M-index at the lower speeds. However, at the highest speed (1,500 m/min), there were no significant differences in the M-indexes among the heat treatments except for HA, which showed the highest M-index. There was no effect of heat treatment on the machinability of the gold alloy using the air-turbine handpiece. The heat treatments had a small effect on the M-index of the gold alloy machined with a SiC wheel for a handpiece engine.

Catalytic aided electrical discharge machining of polycrystalline diamond - parameter analysis of finishing condition

NASA Astrophysics Data System (ADS)

Haikal Ahmad, M. A.; Zulafif Rahim, M.; Fauzi, M. F. Mohd; Abdullah, Aslam; Omar, Z.; Ding, Songlin; Ismail, A. E.; Rasidi Ibrahim, M.

2018-01-01

Polycrystalline diamond (PCD) is regarded as among the hardest material in the world. Electrical Discharge Machining (EDM) typically used to machine this material because of its non-contact process nature. This investigation was purposely done to compare the EDM performances of PCD when using normal electrode of copper (Cu) and newly proposed graphitization catalyst electrode of copper nickel (CuNi). Two level full factorial design of experiment with 4 center points technique was used to study the influence of main and interaction effects of the machining parameter namely; pulse-on, pulse-off, sparking current, and electrode materials (categorical factor). The paper shows interesting discovery in which the newly proposed electrode presented positive impact to the machining performance. With the same machining parameters of finishing, CuNi delivered more than 100% better in Ra and MRR than ordinary Cu electrode.

Towards System Calibration of Panoramic Laser Scanners from a Single Station

PubMed Central

Medić, Tomislav; Holst, Christoph; Kuhlmann, Heiner

2017-01-01

Terrestrial laser scanner measurements suffer from systematic errors due to internal misalignments. The magnitude of the resulting errors in the point cloud in many cases exceeds the magnitude of random errors. Hence, the task of calibrating a laser scanner is important for applications with high accuracy demands. This paper primarily addresses the case of panoramic terrestrial laser scanners. Herein, it is proven that most of the calibration parameters can be estimated from a single scanner station without a need for any reference information. This hypothesis is confirmed through an empirical experiment, which was conducted in a large machine hall using a Leica Scan Station P20 panoramic laser scanner. The calibration approach is based on the widely used target-based self-calibration approach, with small modifications. A new angular parameterization is used in order to implicitly introduce measurements in two faces of the instrument and for the implementation of calibration parameters describing genuine mechanical misalignments. Additionally, a computationally preferable calibration algorithm based on the two-face measurements is introduced. In the end, the calibration results are discussed, highlighting all necessary prerequisites for the scanner calibration from a single scanner station. PMID:28513548

Simultaneous measurement of sleep and feeding in individual Drosophila

PubMed Central

Murphy, Keith R.; Park, Jin Hong; Huber, Robert; Ja, William W.

2018-01-01

Drosophila is widely used for the dissection of genetic and neuronal mechanisms of behavior. Recently, flies have emerged as a model for investigating the regulation of feeding and sleep. Although typically studied in isolation, increasing evidence points to a fundamental connection between these behaviors. Thus, a system for measuring sleep and feeding simultaneously in a single integrated system is important for interpreting behavioral shifts of either state. Here, we describe the construction and use of the Activity Recording CAFE (ARC), a machine-vision based system for the integrated measurement of sleep and feeding in individual Drosophila. Flies feed on liquid food in a microcapillary and consumption is measured by automated tracking of the liquid meniscus over time. Sleep measurements are obtained from positional tracking of the animals and arousal threshold can be determined by vibrational stimulus response. Using this system, a single computer and experimenter can track diverse behaviors from up to 60 individual flies in a single integrated system. The ARC is efficiently assembled with minimal training and each experiment can be run for up to ~7 days, with a total setup and breakdown time of about 2 hours. PMID:29022943

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

Cogging Torque Minimization in Transverse Flux Machines

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

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

2017-02-16

This paper presents the design considerations in cogging torque minimization in two types of transverse flux machines. The machines have a double stator-single rotor configuration with flux concentrating ferrite magnets. One of the machines has pole windings across each leg of an E-Core stator. Another machine has quasi-U-shaped stator cores and a ring winding. The flux in the stator back iron is transverse in both machines. Different methods of cogging torque minimization are investigated. Key methods of cogging torque minimization are identified and used as design variables for optimization using a design of experiments (DOE) based on the Taguchi method.more » A three-level DOE is performed to reach an optimum solution with minimum simulations. Finite element analysis is used to study the different effects. Two prototypes are being fabricated for experimental verification.« less

Investigation of a tubular dual-stator flux-switching permanent-magnet linear generator for free-piston energy converter

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Tong, Chengde; Yu, Bin; Zhu, Shaohong; Zhu, Jianguo

2015-05-01

This paper describes a tubular dual-stator flux-switching permanent-magnet (PM) linear generator for free-piston energy converter. The operating principle, topology, and design considerations of the machine are investigated. Combining the motion characteristic of free-piston Stirling engine, a tubular dual-stator PM linear generator is designed by finite element method. Some major structural parameters, such as the outer and inner radii of the mover, PM thickness, mover tooth width, tooth width of the outer and inner stators, etc., are optimized to improve the machine performances like thrust capability and power density. In comparison with conventional single-stator PM machines like moving-magnet linear machine and flux-switching linear machine, the proposed dual-stator flux-switching PM machine shows advantages in higher mass power density, higher volume power density, and lighter mover.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Influence of coolant on ductile mode processing of binderless nanocrystalline tungsten carbide through ultraprecision diamond turning

NASA Astrophysics Data System (ADS)

Doetz, Marius; Dambon, Olaf; Klocke, Fritz; Fähnle, Oliver

2015-08-01

Molds made of tungsten carbide are typically used for the replicative mass production of glass lenses by precision glass molding. Consequently an ultra-precision grinding process with a subsequent fresh-feed polishing operation is conventionally applied. These processes are time consuming and have a relatively low reproducibility. An alternative manufacturing technology, with a high predictability and efficiency, which additionally allows a higher geometrical flexibility, is the single point diamond turning technique (SPDT). However, the extreme hardness and the chemical properties of tungsten carbide lead to significant tool wear and therefore the impossibility of machining the work pieces in an economical way. One approach to enlarge the tool life is to affect the contact zone between tool and work piece by the use of special cutting fluids. This publication emphasizes on the most recent investigations and results in direct machining of nano-grained tungsten carbide with mono crystal diamonds under the influence of various kinds of cutting fluids. Therefore basic ruling experiments on binderless nano grained tungsten carbide were performed, where the tool performed a linear movement with a steadily increasing depth of cut. As the ductile cutting mechanism is a prerequisite for the optical manufacturing of tungsten carbide these experiments serve the purpose for establish the influence of different cutting fluid characteristics on the cutting performance of mono crystal diamonds. Eventually it is shown that by adjusting the coolant fluid it is possible to significantly shift the transition point from ductile to brittle removal to larger depths of cut eventually enabling a SPDT of binderless tungsten carbide molds.

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

NASA Astrophysics Data System (ADS)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

QUEST FOR A NEW WORKING POINT IN RHIC.

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

TOMAS,R.BAI,M.FISCHER,W.PTITSYN,V.SATOGATA,T.ROSER,T.

2004-07-05

The beam-beam interaction is a limiting factor in RHIC's performance, particularly in proton operation. Changing the working point is a strategy to alleviate the beam-beam effect and improve the performance of the machine. Experiments at injection energy and simulations have been performed for a set of working points to determine the best candidates.

Feature-based three-dimensional registration for repetitive geometry in machine vision

PubMed Central

Gong, Yuanzheng; Seibel, Eric J.

2016-01-01

As an important step in three-dimensional (3D) machine vision, 3D registration is a process of aligning two or multiple 3D point clouds that are collected from different perspectives together into a complete one. The most popular approach to register point clouds is to minimize the difference between these point clouds iteratively by Iterative Closest Point (ICP) algorithm. However, ICP does not work well for repetitive geometries. To solve this problem, a feature-based 3D registration algorithm is proposed to align the point clouds that are generated by vision-based 3D reconstruction. By utilizing texture information of the object and the robustness of image features, 3D correspondences can be retrieved so that the 3D registration of two point clouds is to solve a rigid transformation. The comparison of our method and different ICP algorithms demonstrates that our proposed algorithm is more accurate, efficient and robust for repetitive geometry registration. Moreover, this method can also be used to solve high depth uncertainty problem caused by little camera baseline in vision-based 3D reconstruction. PMID:28286703

Gott Time Machines, BTZ Black Hole Formation, and Choptuik Scaling

NASA Astrophysics Data System (ADS)

Birmingham, Danny; Sen, Siddhartha

2000-02-01

We study the formation of Bañados-Teitelboim-Zanelli black holes by the collision of point particles. It is shown that the Gott time machine, originally constructed for the case of vanishing cosmological constant, provides a precise mechanism for black hole formation. As a result, one obtains an exact analytic understanding of the Choptuik scaling.

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2013 CFR

2013-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

Initial Experiences with Machine-Assisted Reconsiderative Test Scoring: A New Method for Partial Credit and Multiple Correct Responses.

ERIC Educational Resources Information Center

Anderson, Paul S.

Initial experiences with computer-assisted reconsiderative scoring are described. Reconsiderative scoring occurs when student responses are received and reviewed by the teacher before points for correctness are assigned. Manually scored completion-style questions are reconsiderative. A new method of machine assistance produces an item analysis on…

An Immanent Machine: Reconsidering Grades, Historical and Present

ERIC Educational Resources Information Center

Tocci, Charles

2010-01-01

At some point the mechanics of schooling begin running of their own accord. Such has become the case with grades (A's, B's, C's, etc.). This article reconsiders the history of grades through the concepts of immanence and abstract machines from the oeuvre of Deleuze and Guattari. In the first section, the history of grades as presently written…

Adaptive design of an X-ray magnetic circular dichroism spectroscopy experiment with Gaussian process modelling

NASA Astrophysics Data System (ADS)

Ueno, Tetsuro; Hino, Hideitsu; Hashimoto, Ai; Takeichi, Yasuo; Sawada, Masahiro; Ono, Kanta

2018-01-01

Spectroscopy is a widely used experimental technique, and enhancing its efficiency can have a strong impact on materials research. We propose an adaptive design for spectroscopy experiments that uses a machine learning technique to improve efficiency. We examined X-ray magnetic circular dichroism (XMCD) spectroscopy for the applicability of a machine learning technique to spectroscopy. An XMCD spectrum was predicted by Gaussian process modelling with learning of an experimental spectrum using a limited number of observed data points. Adaptive sampling of data points with maximum variance of the predicted spectrum successfully reduced the total data points for the evaluation of magnetic moments while providing the required accuracy. The present method reduces the time and cost for XMCD spectroscopy and has potential applicability to various spectroscopies.

Mobile Landing Platform with Core Capability Set (MLP w/CCS): Combined Initial Operational Test and Evaluation and Live Fire Test and Evaluation Report

DTIC Science & Technology

2015-07-01

annex.   iii Self-defense testing was limited to structural test firing from each machine gun mount and an ammunition resupply drill. Robust self...provided in the classified annex. Self-   8 defense testing was limited to structural test firing from each machine gun mount and a single...Caliber Machine Gun Mount Structural Test Fire November 2014 San Diego, Offshore Ship Weapons Range Operating Independently       9 Section Three

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

PubMed

Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

2012-08-01

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.

Automatic ball bar for a coordinate measuring machine

DOEpatents

Jostlein, H.

1997-07-15

An automatic ball bar for a coordinate measuring machine determines the accuracy of a coordinate measuring machine having at least one servo drive. The apparatus comprises a first and second gauge ball connected by a telescoping rigid member. The rigid member includes a switch such that inward radial movement of the second gauge ball relative to the first gauge ball causes activation of the switch. The first gauge ball is secured in a first magnetic socket assembly in order to maintain the first gauge ball at a fixed location with respect to the coordinate measuring machine. A second magnetic socket assembly secures the second gauge ball to the arm or probe holder of the coordinate measuring machine. The second gauge ball is then directed by the coordinate measuring machine to move radially inward from a point just beyond the length of the ball bar until the switch is activated. Upon switch activation, the position of the coordinate measuring machine is determined and compared to known ball bar length such that the accuracy of the coordinate measuring machine can be determined. 5 figs.

Automatic ball bar for a coordinate measuring machine

DOEpatents

Jostlein, Hans

1997-01-01

An automatic ball bar for a coordinate measuring machine determines the accuracy of a coordinate measuring machine having at least one servo drive. The apparatus comprises a first and second gauge ball connected by a telescoping rigid member. The rigid member includes a switch such that inward radial movement of the second gauge ball relative to the first gauge ball causes activation of the switch. The first gauge ball is secured in a first magnetic socket assembly in order to maintain the first gauge ball at a fixed location with respect to the coordinate measuring machine. A second magnetic socket assembly secures the second gauge ball to the arm or probe holder of the coordinate measuring machine. The second gauge ball is then directed by the coordinate measuring machine to move radially inward from a point just beyond the length of the ball bar until the switch is activated. Upon switch activation, the position of the coordinate measuring machine is determined and compared to known ball bar length such that the accuracy of the coordinate measuring machine can be determined.

Experimental research of kinetic and dynamic characteristics of temperature movements of machines

NASA Astrophysics Data System (ADS)

Parfenov, I. V.; Polyakov, A. N.

2018-03-01

Nowadays, the urgency of informational support of machines at different stages of their life cycle is increasing in the form of various experimental characteristics that determine the criteria for working capacity. The effectiveness of forming the base of experimental characteristics of machines is related directly to the duration of their field tests. In this research, the authors consider a new technique that allows reducing the duration of full-scale testing of machines by 30%. To this end, three new indicator coefficients were calculated in real time to determine the moments corresponding to the characteristic points. In the work, new terms for thermal characteristics of machine tools are introduced: kinetic and dynamic characteristics of the temperature movements of the machine. This allow taking into account not only the experimental values for the temperature displacements of the elements of the carrier system of the machine, but also their derivatives up to the third order, inclusively. The work is based on experimental data obtained in the course of full-scale thermal tests of a drilling-milling and boring CNC machine.

Food labeling; calorie labeling of articles of food in vending machines. Final rule.

PubMed

2014-12-01

To implement the vending machine food labeling provisions of the Patient Protection and Affordable Care Act of 2010 (ACA), the Food and Drug Administration (FDA or we) is establishing requirements for providing calorie declarations for food sold from certain vending machines. This final rule will ensure that calorie information is available for certain food sold from a vending machine that does not permit a prospective purchaser to examine the Nutrition Facts Panel before purchasing the article, or does not otherwise provide visible nutrition information at the point of purchase. The declaration of accurate and clear calorie information for food sold from vending machines will make calorie information available to consumers in a direct and accessible manner to enable consumers to make informed and healthful dietary choices. This final rule applies to certain food from vending machines operated by a person engaged in the business of owning or operating 20 or more vending machines. Vending machine operators not subject to the rules may elect to be subject to the Federal requirements by registering with FDA.

"Reliability Of Fiber Optic Lans"

NASA Astrophysics Data System (ADS)

Code n, Michael; Scholl, Frederick; Hatfield, W. Bryan

1987-02-01

Fiber optic Local Area Network Systems are being used to interconnect increasing numbers of nodes. These nodes may include office computer peripherals and terminals, PBX switches, process control equipment and sensors, automated machine tools and robots, and military telemetry and communications equipment. The extensive shared base of capital resources in each system requires that the fiber optic LAN meet stringent reliability and maintainability requirements. These requirements are met by proper system design and by suitable manufacturing and quality procedures at all levels of a vertically integrated manufacturing operation. We will describe the reliability and maintainability of Codenoll's passive star based systems. These include LAN systems compatible with Ethernet (IEEE 802.3) and MAP (IEEE 802.4), and software compatible with IBM Token Ring (IEEE 802.5). No single point of failure exists in this system architecture.

Multi-parameter monitoring of electrical machines using integrated fibre Bragg gratings

NASA Astrophysics Data System (ADS)

Fabian, Matthias; Hind, David; Gerada, Chris; Sun, Tong; Grattan, Kenneth T. V.

2017-04-01

In this paper a sensor system for multi-parameter electrical machine condition monitoring is reported. The proposed FBG-based system allows for the simultaneous monitoring of machine vibration, rotor speed and position, torque, spinning direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution reduces the component count of conventional sensor systems, i.e., all 48 sensing elements are contained within the machine operated by a single sensing interrogation unit. In this work, the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

Learning dominance relations in combinatorial search problems

NASA Technical Reports Server (NTRS)

Yu, Chee-Fen; Wah, Benjamin W.

1988-01-01

Dominance relations commonly are used to prune unnecessary nodes in search graphs, but they are problem-dependent and cannot be derived by a general procedure. The authors identify machine learning of dominance relations and the applicable learning mechanisms. A study of learning dominance relations using learning by experimentation is described. This system has been able to learn dominance relations for the 0/1-knapsack problem, an inventory problem, the reliability-by-replication problem, the two-machine flow shop problem, a number of single-machine scheduling problems, and a two-machine scheduling problem. It is considered that the same methodology can be extended to learn dominance relations in general.

2007 SB14 Source Reduction Plan/Report

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

Chang, L

2007-07-24

Aqueous solutions (mixed waste) generated from various LLNL operations, such as debris washing, sample preparation and analysis, and equipment maintenance and cleanout, were combined for storage in the B695 tank farm. Prior to combination the individual waste streams had different codes depending on the particular generating process and waste characteristics. The largest streams were CWC 132, 791, 134, 792. Several smaller waste streams were also included. This combined waste stream was treated at LLNL's waste treatment facility using a vacuum filtration and cool vapor evaporation process in preparation for discharge to sanitary sewer. Prior to discharge, the treated waste streammore » was sampled and the results were reviewed by LLNL's water monitoring specialists. The treated solution was discharged following confirmation that it met the discharge criteria. A major source, accounting for 50% for this waste stream, is metal machining, cutting and grinding operations in the engineering machine shops in B321/B131. An additional 7% was from similar operations in B131 and B132S. This waste stream primarily contains metal cuttings from machined parts, machining coolant and water, with small amounts of tramp oil from the machining and grinding equipment. Several waste reduction measures for the B321 machine shop have been taken, including the use of a small point-of-use filtering/tramp-oil coalescing/UV-sterilization coolant recycling unit, and improved management techniques (testing and replenishing) for coolants. The recycling unit had some operational problems during 2006. The machine shop is planning to have it repaired in the near future. A major source, accounting for 50% for this waste stream, is metal machining, cutting and grinding operations in the engineering machine shops in B321/B131. An additional 7% was from similar operations in B131 and B132S. This waste stream primarily contains metal cuttings from machined parts, machining coolant and water, with small amounts of tramp oil from the machining and grinding equipment. Several waste reduction measures for the B321 machine shop have been taken, including the use of a small point-of-use filtering/tramp-oil coalescing/UV-sterilization coolant recycling unit, and improved management techniques (testing and replenishing) for coolants. The recycling unit had some operational problems during 2006. The machine shop is planning to have it repaired in the near future. Quarterly waste generation data prepared by the Environmental Protection Department's P2 Team are regularly provided to engineering shops as well as other facilities so that generators can track the effectiveness of their waste minimization efforts.« less

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

An Analysis of Heavy-Ion Single Event Effects for a Variety of Finite State-Machine Mitigation Strategies

NASA Technical Reports Server (NTRS)

Berg, Melanie D.; Label, Kenneth A.; Kim, Hak; Phan, Anthony; Seidleck, Christina

2014-01-01

Finite state-machines (FSMs) are used to control operational flow in application specific integrated circuits (ASICs) and field programmable gate array (FPGA) devices. Because of their ease of interpretation, FSMs simplify the design and verification process and consequently are significant components in a synchronous design.

Automated Coal-Mining System

NASA Technical Reports Server (NTRS)

Gangal, M. D.; Isenberg, L.; Lewis, E. V.

1985-01-01

Proposed system offers safety and large return on investment. System, operating by year 2000, employs machines and processes based on proven principles. According to concept, line of parallel machines, connected in groups of four to service modules, attacks face of coal seam. High-pressure water jets and central auger on each machine break face. Jaws scoop up coal chunks, and auger grinds them and forces fragments into slurry-transport system. Slurry pumped through pipeline to point of use. Concept for highly automated coal-mining system increases productivity, makes mining safer, and protects health of mine workers.

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Oceanic eddy detection and lifetime forecast using machine learning methods

NASA Astrophysics Data System (ADS)

Ashkezari, Mohammad D.; Hill, Christopher N.; Follett, Christopher N.; Forget, Gaël.; Follows, Michael J.

2016-12-01

We report a novel altimetry-based machine learning approach for eddy identification and characterization. The machine learning models use daily maps of geostrophic velocity anomalies and are trained according to the phase angle between the zonal and meridional components at each grid point. The trained models are then used to identify the corresponding eddy phase patterns and to predict the lifetime of a detected eddy structure. The performance of the proposed method is examined at two dynamically different regions to demonstrate its robust behavior and region independency.

High Order Accuracy Methods for Supersonic Reactive Flows

DTIC Science & Technology

2008-06-25

k = 0, · · · , N and N is the polynomial order used. The positive constant M is chosen such that σ(N) becomes machine zero. Typically M ∼ 32. Table...function used in this study is the Exponential filter given by σ(η) = exp(−αηp), (38) where α = − ln() and is the machine zero. The spectral...respectively. All numerical experiments were run 49 on a 667 MHz Compaq Alpha machine with 1GB memory and with an Alpha internal floating point processor. 9.1

Scheduling with non-decreasing deterioration jobs and variable maintenance activities on a single machine

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Yin, Yunqiang; Wu, Chin-Chia

2017-01-01

There is a situation found in many manufacturing systems, such as steel rolling mills, fire fighting or single-server cycle-queues, where a job that is processed later consumes more time than that same job when processed earlier. The research finds that machine maintenance can improve the worsening of processing conditions. After maintenance activity, the machine will be restored. The maintenance duration is a positive and non-decreasing differentiable convex function of the total processing times of the jobs between maintenance activities. Motivated by this observation, the makespan and the total completion time minimization problems in the scheduling of jobs with non-decreasing rates of job processing time on a single machine are considered in this article. It is shown that both the makespan and the total completion time minimization problems are NP-hard in the strong sense when the number of maintenance activities is arbitrary, while the makespan minimization problem is NP-hard in the ordinary sense when the number of maintenance activities is fixed. If the deterioration rates of the jobs are identical and the maintenance duration is a linear function of the total processing times of the jobs between maintenance activities, then this article shows that the group balance principle is satisfied for the makespan minimization problem. Furthermore, two polynomial-time algorithms are presented for solving the makespan problem and the total completion time problem under identical deterioration rates, respectively.

Modeling Stochastic Kinetics of Molecular Machines at Multiple Levels: From Molecules to Modules

PubMed Central

Chowdhury, Debashish

2013-01-01

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. PMID:23746505

Machine characterization and benchmark performance prediction

NASA Technical Reports Server (NTRS)

Saavedra-Barrera, Rafael H.

1988-01-01

From runs of standard benchmarks or benchmark suites, it is not possible to characterize the machine nor to predict the run time of other benchmarks which have not been run. A new approach to benchmarking and machine characterization is reported. The creation and use of a machine analyzer is described, which measures the performance of a given machine on FORTRAN source language constructs. The machine analyzer yields a set of parameters which characterize the machine and spotlight its strong and weak points. Also described is a program analyzer, which analyzes FORTRAN programs and determines the frequency of execution of each of the same set of source language operations. It is then shown that by combining a machine characterization and a program characterization, we are able to predict with good accuracy the run time of a given benchmark on a given machine. Characterizations are provided for the Cray-X-MP/48, Cyber 205, IBM 3090/200, Amdahl 5840, Convex C-1, VAX 8600, VAX 11/785, VAX 11/780, SUN 3/50, and IBM RT-PC/125, and for the following benchmark programs or suites: Los Alamos (BMK8A1), Baskett, Linpack, Livermore Loops, Madelbrot Set, NAS Kernels, Shell Sort, Smith, Whetstone and Sieve of Erathostenes.

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

Alumina-zirconia machinable abutments for implant-supported single-tooth anterior crowns.

PubMed

Sadoun, M; Perelmuter, S

1997-01-01

Innovative materials and application techniques are constantly being developed in the ongoing search for improved restorations. This article describes a new material and the fabrication process of aesthetic machinable ceramic anterior implant abutments. The ceramic material utilized is a mixture of alumina (aluminum oxide) and ceria (cerium oxide) with partially stabilized zirconia (zirconium oxide). The initial core material is a cylinder with a 9-mm diameter and a 15-mm height, obtained by ceramic injection and presintering processes. The resultant alumina-zirconia core is porous and readily machinable. It is secured to the analog, and its design is customized by machining the abutment to suit the particular clinical circumstances. The machining is followed by glass infiltration, and the crown is finalized. The learning objective of this article is to gain a basic knowledge of the fabrication and clinical application of the custom machinable abutments.

Predicting competency in automated machine use in an acquired brain injury population using neuropsychological measures.

PubMed

Crowe, Simon F; Mahony, Kate; Jackson, Martin

2004-08-01

The purpose of the current study was to explore whether performance on standardised neuropsychological measures could predict functional ability with automated machines and services among people with an acquired brain injury (ABI). Participants were 45 individuals who met the criteria for mild, moderate or severe ABI and 15 control participants matched on demographic variables including age- and education. Each participant was required to complete a battery of neuropsychological tests, as well as performing three automated service delivery tasks: a transport automated ticketing machine, an automated teller machine (ATM) and an automated telephone service. The results showed consistently high relationship between the neuropsychological measures, both as single predictors and in combination, and level of competency with the automated machines. Automated machines are part of a relatively new phenomena in service delivery and offer an ecologically valid functional measure of performance that represents a true indication of functional disability.

Triadic split-merge sampler

NASA Astrophysics Data System (ADS)

van Rossum, Anne C.; Lin, Hai Xiang; Dubbeldam, Johan; van der Herik, H. Jaap

2018-04-01

In machine vision typical heuristic methods to extract parameterized objects out of raw data points are the Hough transform and RANSAC. Bayesian models carry the promise to optimally extract such parameterized objects given a correct definition of the model and the type of noise at hand. A category of solvers for Bayesian models are Markov chain Monte Carlo methods. Naive implementations of MCMC methods suffer from slow convergence in machine vision due to the complexity of the parameter space. Towards this blocked Gibbs and split-merge samplers have been developed that assign multiple data points to clusters at once. In this paper we introduce a new split-merge sampler, the triadic split-merge sampler, that perform steps between two and three randomly chosen clusters. This has two advantages. First, it reduces the asymmetry between the split and merge steps. Second, it is able to propose a new cluster that is composed out of data points from two different clusters. Both advantages speed up convergence which we demonstrate on a line extraction problem. We show that the triadic split-merge sampler outperforms the conventional split-merge sampler. Although this new MCMC sampler is demonstrated in this machine vision context, its application extend to the very general domain of statistical inference.

Single phase space laundry development

NASA Technical Reports Server (NTRS)

Colombo, Gerald V.; Putnam, David F.; Lunsford, Teddie D.; Streech, Neil D.; Wheeler, Richard R., Jr.; Reimers, Harold

1993-01-01

This paper describes a newly designed, 2.7 Kg (6 pound) capacity, laundry machine called the Single Phase Laundry (SPSL). The machine was designed to wash and dry crew clothing in a micro-gravity environment. A prototype unit was fabricated for NASA-JSC under a Small Business Innovated Research (SBIR) contract extending from September 1990 to January 1993. The unit employs liquid jet agitation, microwave vacuum drying, and air jet tumbling, which was perfected by KC-135 zero-g flight testing. Operation is completely automated except for loading and unloading clothes. The unit uses about 20 percent less power than a conventional household appliance.

Optical realization of optimal symmetric real state quantum cloning machine

NASA Astrophysics Data System (ADS)

Hu, Gui-Yu; Zhang, Wen-Hai; Ye, Liu

2010-01-01

We present an experimentally uniform linear optical scheme to implement the optimal 1→2 symmetric and optimal 1→3 symmetric economical real state quantum cloning machine of the polarization state of the single photon. This scheme requires single-photon sources and two-photon polarization entangled state as input states. It also involves linear optical elements and three-photon coincidence. Then we consider the realistic realization of the scheme by using the parametric down-conversion as photon resources. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Heuristic methods for the single machine scheduling problem with different ready times and a common due date

NASA Astrophysics Data System (ADS)

Birgin, Ernesto G.; Ronconi, Débora P.

2012-10-01

The single machine scheduling problem with a common due date and non-identical ready times for the jobs is examined in this work. Performance is measured by the minimization of the weighted sum of earliness and tardiness penalties of the jobs. Since this problem is NP-hard, the application of constructive heuristics that exploit specific characteristics of the problem to improve their performance is investigated. The proposed approaches are examined through a computational comparative study on a set of 280 benchmark test problems with up to 1000 jobs.

Analysis of the Laser Drilling Process for the Combination with a Single-Lip Deep Hole Drilling Process with Small Diameters

NASA Astrophysics Data System (ADS)

Biermann, Dirk; Heilmann, Markus

Due to the tendency of downsizing of components, also the industrial relevance of bore holes with small diameters and high length-to-diameter ratios rises with the growing requirements on parts. In these applications, the combination of laser pre-drilling and single-lip deep hole drilling can shorten the process chain in machining components with non-planar surfaces, or can reduce tool wear in machining case-hardened materials. In this research, the combination of these processes was realized and investigated for the very first time.

Process of making cryogenically cooled high thermal performance crystal optics

DOEpatents

Kuzay, Tuncer M.

1992-01-01

A method for constructing a cooled optic wherein one or more cavities are milled, drilled or formed using casting or ultrasound laser machining techniques in a single crystal base and filled with porous material having high thermal conductivity at cryogenic temperatures. A non-machined strain-free single crystal can be bonded to the base to produce superior optics. During operation of the cooled optic, N.sub.2 is pumped through the porous material at a sub-cooled cryogenic inlet temperature and with sufficient system pressure to prevent the fluid bulk temperature from reaching saturation.

Process of making cryogenically cooled high thermal performance crystal optics

DOEpatents

Kuzay, T.M.

1992-06-23

A method is disclosed for constructing a cooled optic wherein one or more cavities are milled, drilled or formed using casting or ultrasound laser machining techniques in a single crystal base and filled with porous material having high thermal conductivity at cryogenic temperatures. A non-machined strain-free single crystal can be bonded to the base to produce superior optics. During operation of the cooled optic, N[sub 2] is pumped through the porous material at a sub-cooled cryogenic inlet temperature and with sufficient system pressure to prevent the fluid bulk temperature from reaching saturation. 7 figs.

Dynamics of multirate sampled data control systems. [for space shuttle boost vehicle

NASA Technical Reports Server (NTRS)

Naylor, J. R.; Hynes, R. J.; Molnar, D. O.

1974-01-01

The effect was investigated of the synthesis approach (single or multirate) on the machine requirements for a digital control system for the space shuttle boost vehicle. The study encompassed four major work areas: synthesis approach trades, machine requirements trades, design analysis requirements and multirate adaptive control techniques. The primary results are two multirate autopilot designs for the low Q and maximum Q flight conditions that exhibits equal or better performance than the analog and single rate system designs. Also, a preferred technique for analyzing and synthesizing multirate digital control systems is included.

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

PubMed Central

Choi, Woong-Kirl; Kim, Seong-Hyun; Choi, Seung-Geon; Lee, Eun-Sang

2018-01-01

Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs) contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks. PMID:29351235

Prediction of Compressional, Shear, and Stoneley Wave Velocities from Conventional Well Log Data Using a Committee Machine with Intelligent Systems

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa

2012-01-01

Measurement of compressional, shear, and Stoneley wave velocities, carried out by dipole sonic imager (DSI) logs, provides invaluable data in geophysical interpretation, geomechanical studies and hydrocarbon reservoir characterization. The presented study proposes an improved methodology for making a quantitative formulation between conventional well logs and sonic wave velocities. First, sonic wave velocities were predicted from conventional well logs using artificial neural network, fuzzy logic, and neuro-fuzzy algorithms. Subsequently, a committee machine with intelligent systems was constructed by virtue of hybrid genetic algorithm-pattern search technique while outputs of artificial neural network, fuzzy logic and neuro-fuzzy models were used as inputs of the committee machine. It is capable of improving the accuracy of final prediction through integrating the outputs of aforementioned intelligent systems. The hybrid genetic algorithm-pattern search tool, embodied in the structure of committee machine, assigns a weight factor to each individual intelligent system, indicating its involvement in overall prediction of DSI parameters. This methodology was implemented in Asmari formation, which is the major carbonate reservoir rock of Iranian oil field. A group of 1,640 data points was used to construct the intelligent model, and a group of 800 data points was employed to assess the reliability of the proposed model. The results showed that the committee machine with intelligent systems performed more effectively compared with individual intelligent systems performing alone.

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

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

This paper presents the design considerations in cogging torque minimization in two types of transverse flux machines. The machines have a double stator-single rotor configuration with flux concentrating ferrite magnets. One of the machines has pole windings across each leg of an E-Core stator. Another machine has quasi-U-shaped stator cores and a ring winding. The flux in the stator back iron is transverse in both machines. Different methods of cogging torque minimization are investigated. Key methods of cogging torque minimization are identified and used as design variables for optimization using a design of experiments (DOE) based on the Taguchi method.more » A three-level DOE is performed to reach an optimum solution with minimum simulations. Finite element analysis is used to study the different effects. Two prototypes are being fabricated for experimental verification.« less

Solving the Cauchy-Riemann equations on parallel computers

NASA Technical Reports Server (NTRS)

Fatoohi, Raad A.; Grosch, Chester E.

1987-01-01

Discussed is the implementation of a single algorithm on three parallel-vector computers. The algorithm is a relaxation scheme for the solution of the Cauchy-Riemann equations; a set of coupled first order partial differential equations. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, and SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The machine architectures are briefly described. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Conclusions are presented.

Chip breaking system for automated machine tool

DOEpatents

Arehart, Theodore A.; Carey, Donald O.

1987-01-01

The invention is a rotary selectively directional valve assembly for use in an automated turret lathe for directing a stream of high pressure liquid machining coolant to the interface of a machine tool and workpiece for breaking up ribbon-shaped chips during the formation thereof so as to inhibit scratching or other marring of the machined surfaces by these ribbon-shaped chips. The valve assembly is provided by a manifold arrangement having a plurality of circumferentially spaced apart ports each coupled to a machine tool. The manifold is rotatable with the turret when the turret is positioned for alignment of a machine tool in a machining relationship with the workpiece. The manifold is connected to a non-rotational header having a single passageway therethrough which conveys the high pressure coolant to only the port in the manifold which is in registry with the tool disposed in a working relationship with the workpiece. To position the machine tools the turret is rotated and one of the tools is placed in a material-removing relationship of the workpiece. The passageway in the header and one of the ports in the manifold arrangement are then automatically aligned to supply the machining coolant to the machine tool workpiece interface for breaking up of the chips as well as cooling the tool and workpiece during the machining operation.

The cleaning of ward floors and the bacteriological study of floor-cleaning machines

PubMed Central

Bate, J. G.

1961-01-01

Current trends in ward flooring materials and cleaning methods are considered from the point of view of the hospital bacteriologist. Methods employed in an investigation into the bacteriological safety of a number of floor-cleaning machines are described, and some considerations governing the choice of vacuum cleaners for ward use are discussed. Images PMID:13687726

Automatic microseismic event picking via unsupervised machine learning

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-01-01

Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

A novel device for head gesture measurement system in combination with eye-controlled human machine interface

NASA Astrophysics Data System (ADS)

Lin, Chern-Sheng; Ho, Chien-Wa; Chang, Kai-Chieh; Hung, San-Shan; Shei, Hung-Jung; Yeh, Mau-Shiun

2006-06-01

This study describes the design and combination of an eye-controlled and a head-controlled human-machine interface system. This system is a highly effective human-machine interface, detecting head movement by changing positions and numbers of light sources on the head. When the users utilize the head-mounted display to browse a computer screen, the system will catch the images of the user's eyes with CCD cameras, which can also measure the angle and position of the light sources. In the eye-tracking system, the program in the computer will locate each center point of the pupils in the images, and record the information on moving traces and pupil diameters. In the head gesture measurement system, the user wears a double-source eyeglass frame, so the system catches images of the user's head by using a CCD camera in front of the user. The computer program will locate the center point of the head, transferring it to the screen coordinates, and then the user can control the cursor by head motions. We combine the eye-controlled and head-controlled human-machine interface system for the virtual reality applications.

Technology of welding aluminum alloys-II

NASA Technical Reports Server (NTRS)

1978-01-01

Step-by-step procedures were developed for high integrity manual and machine welding of aluminum alloys. Detailed instructions are given for each step with tables and graphs to specify materials and dimensions. Throughout work sequence, processing procedure designates manufacturing verification points and inspection points.

An integer batch scheduling model considering learning, forgetting, and deterioration effects for a single machine to minimize total inventory holding cost

NASA Astrophysics Data System (ADS)

Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.

2018-03-01

This research deals with a single machine batch scheduling model considering the influenced of learning, forgetting, and machine deterioration effects. The objective of the model is to minimize total inventory holding cost, and the decision variables are the number of batches (N), batch sizes (Q[i], i = 1, 2, .., N) and the sequence of processing the resulting batches. The parts to be processed are received at the right time and the right quantities, and all completed parts must be delivered at a common due date. We propose a heuristic procedure based on the Lagrange method to solve the problem. The effectiveness of the procedure is evaluated by comparing the resulting solution to the optimal solution obtained from the enumeration procedure using the integer composition technique and shows that the average effectiveness is 94%.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Research on the magnetorheological finishing of large aperture off-axis aspheric optical surfaces for zinc sulfide

NASA Astrophysics Data System (ADS)

Zhang, Yunfei; Huang, Wen; Zheng, Yongcheng; Ji, Fang; Xu, Min; Duan, Zhixin; Luo, Qing; Liu, Qian; Xiao, Hong

2016-03-01

Zinc sulfide is a kind of typical infrared optical material, commonly produced using single point diamond turning (SPDT). SPDT can efficiently produce zinc sulfide aspheric surfaces with micro-roughness and acceptable figure error. However the tool marks left by the diamond turning process cause high micro-roughness that degrades the optical performance when used in the visible region of the spectrum. Magnetorheological finishing (MRF) is a deterministic, sub-aperture polishing technology that is very helpful in improving both surface micro-roughness and surface figure.This paper mainly investigates the MRF technology of large aperture off-axis aspheric optical surfaces for zinc sulfide. The topological structure and coordinate transformation of a MRF machine tool PKC1200Q2 are analyzed and its kinematics is calculated, then the post-processing algorithm model of MRF for an optical lens is established. By taking the post-processing of off-axis aspheric surfacefor example, a post-processing algorithm that can be used for a raster tool path is deduced and the errors produced by the approximate treatment are analyzed. A polishing algorithm of trajectory planning and dwell time based on matrix equation and optimization theory is presented in this paper. Adopting this algorithm an experiment is performed to machining a large-aperture off-axis aspheric surface on the MRF machine developed by ourselves. After several times' polishing, the figure accuracy PV is proved from 3.3λ to 2.0λ and RMS from 0.451λ to 0.327λ. This algorithm is used to polish the other shapes including spheres, aspheres and prisms.

ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

PubMed

Wang, Shuangquan; Sun, Huiyong; Liu, Hui; Li, Dan; Li, Youyong; Hou, Tingjun

2016-08-01

Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is quite important to reduce the risk of cardiotoxicity-related attritions in the later development stages. In this study, pharmacophore modeling and machine learning approaches were combined to construct classification models to distinguish hERG active from inactive compounds based on a diverse data set. First, an optimal ensemble of pharmacophore hypotheses that had good capability to differentiate hERG active from inactive compounds was identified by the recursive partitioning (RP) approach. Then, the naive Bayesian classification (NBC) and support vector machine (SVM) approaches were employed to construct classification models by integrating multiple important pharmacophore hypotheses. The integrated classification models showed improved predictive capability over any single pharmacophore hypothesis, suggesting that the broad binding polyspecificity of hERG can only be well characterized by multiple pharmacophores. The best SVM model achieved the prediction accuracies of 84.7% for the training set and 82.1% for the external test set. Notably, the accuracies for the hERG blockers and nonblockers in the test set reached 83.6% and 78.2%, respectively. Analysis of significant pharmacophores helps to understand the multimechanisms of action of hERG blockers. We believe that the combination of pharmacophore modeling and SVM is a powerful strategy to develop reliable theoretical models for the prediction of potential hERG liability.

Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

PubMed Central

Lee, Jonguk; Choi, Heesu; Park, Daihee; Chung, Yongwha; Kim, Hee-Young; Yoon, Sukhan

2016-01-01

Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs) from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs) for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods. PMID:27092509

Modeling of a production system using the multi-agent approach

NASA Astrophysics Data System (ADS)

Gwiazda, A.; Sękala, A.; Banaś, W.

2017-08-01

The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the other type of agent that are utilized in the described simulation. The article presents the idea of an integrated program approach and shows the resulting production layout as a virtual model. This model was developed in the NetLogo multi-agent program environment.

Toward a Theory of Conversational Style: The Machine-Gun Question.

ERIC Educational Resources Information Center

Tannen, Deborah

This paper, part of a larger study, focuses on a single linguistic device, the "machine-gun question," which was used by three of six participants in a Thanksgiving dinner conversation. This conversational device is characteristic of a style that seems to grow out of the need to have others approve of one's wants. It is a style…

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

Diamond Smoothing Tools

NASA Technical Reports Server (NTRS)

Voronov, Oleg

2007-01-01

Diamond smoothing tools have been proposed for use in conjunction with diamond cutting tools that are used in many finish-machining operations. Diamond machining (including finishing) is often used, for example, in fabrication of precise metal mirrors. A diamond smoothing tool according to the proposal would have a smooth spherical surface. For a given finish machining operation, the smoothing tool would be mounted next to the cutting tool. The smoothing tool would slide on the machined surface left behind by the cutting tool, plastically deforming the surface material and thereby reducing the roughness of the surface, closing microcracks and otherwise generally reducing or eliminating microscopic surface and subsurface defects, and increasing the microhardness of the surface layer. It has been estimated that if smoothing tools of this type were used in conjunction with cutting tools on sufficiently precise lathes, it would be possible to reduce the roughness of machined surfaces to as little as 3 nm. A tool according to the proposal would consist of a smoothing insert in a metal holder. The smoothing insert would be made from a diamond/metal functionally graded composite rod preform, which, in turn, would be made by sintering together a bulk single-crystal or polycrystalline diamond, a diamond powder, and a metallic alloy at high pressure. To form the spherical smoothing tip, the diamond end of the preform would be subjected to flat grinding, conical grinding, spherical grinding using diamond wheels, and finally spherical polishing and/or buffing using diamond powders. If the diamond were a single crystal, then it would be crystallographically oriented, relative to the machining motion, to minimize its wear and maximize its hardness. Spherically polished diamonds could also be useful for purposes other than smoothing in finish machining: They would likely also be suitable for use as heat-resistant, wear-resistant, unlubricated sliding-fit bearing inserts.

Benchmark tests on the digital equipment corporation Alpha AXP 21164-based AlphaServer 8400, including a comparison of optimized vector and superscalar processing

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

Wasserman, H.J.

1996-02-01

The second generation of the Digital Equipment Corp. (DEC) DECchip Alpha AXP microprocessor is referred to as the 21164. From the viewpoint of numerically-intensive computing, the primary difference between it and its predecessor, the 21064, is that the 21164 has twice the multiply/add throughput per clock period (CP), a maximum of two floating point operations (FLOPS) per CP vs. one for 21064. The AlphaServer 8400 is a shared-memory multiprocessor server system that can accommodate up to 12 CPUs and up to 14 GB of memory. In this report we will compare single processor performance of the 8400 system with thatmore » of the International Business Machines Corp. (IBM) RISC System/6000 POWER-2 microprocessor running at 66 MHz, the Silicon Graphics, Inc. (SGI) MIPS R8000 microprocessor running at 75 MHz, and the Cray Research, Inc. CRAY J90. The performance comparison is based on a set of Fortran benchmark codes that represent a portion of the Los Alamos National Laboratory supercomputer workload. The advantage of using these codes, is that the codes also span a wide range of computational characteristics, such as vectorizability, problem size, and memory access pattern. The primary disadvantage of using them is that detailed, quantitative analysis of performance behavior of all codes on all machines is difficult. One important addition to the benchmark set appears for the first time in this report. Whereas the older version was written for a vector processor, the newer version is more optimized for microprocessor architectures. Therefore, we have for the first time, an opportunity to measure performance on a single application using implementations that expose the respective strengths of vector and superscalar architecture. All results in this report are from single processors. A subsequent article will explore shared-memory multiprocessing performance of the 8400 system.« less

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

No time machine construction in open 2+1 gravity with timelike total energy-momentum

NASA Astrophysics Data System (ADS)

Tiglio, Manuel H.

1998-09-01

It is shown that in (2+1)-dimensional gravity an open spacetime with timelike sources and total energy momentum cannot have a stable compactly generated Cauchy horizon. This constitutes a proof of a version of Kabat's conjecture and shows, in particular, that not only a Gott time machine cannot be formed from processes such as the decay of a single cosmic string as has been shown by Carroll et al., but that, in a precise sense, a time machine cannot be constructed at all.

Control coil arrangement for a rotating machine rotor

DOEpatents

Shah, Manoj R.; Lewandowsk, Chad R.

2001-07-31

A rotating machine (e.g., a turbine, motor or generator) is provided wherein a fixed solenoid or other coil configuration is disposed adjacent to one or both ends of the active portion of the machine rotor for producing an axially directed flux in the active portion so as to provide planar axial control at single or multiple locations for rotor balance, levitation, centering, torque and thrust action. Permanent magnets can be used to produce an axial bias magnetic field. The rotor can include magnetic disks disposed in opposed, facing relation to the coil configuration.

A consideration of the operation of automatic production machines.

PubMed

Hoshi, Toshiro; Sugimoto, Noboru

2015-01-01

At worksites, various automatic production machines are in use to release workers from muscular labor or labor in the detrimental environment. On the other hand, a large number of industrial accidents have been caused by automatic production machines. In view of this, this paper considers the operation of automatic production machines from the viewpoint of accident prevention, and points out two types of machine operation - operation for which quick performance is required (operation that is not permitted to be delayed) - and operation for which composed performance is required (operation that is not permitted to be performed in haste). These operations are distinguished by operation buttons of suitable colors and shapes. This paper shows that these characteristics are evaluated as "asymmetric on the time-axis". Here, in order for workers to accept the risk of automatic production machines, it is preconditioned in general that harm should be sufficiently small or avoidance of harm is easy. In this connection, this paper shows the possibility of facilitating the acceptance of the risk of automatic production machines by enhancing the asymmetric on the time-axis.

A consideration of the operation of automatic production machines

PubMed Central

HOSHI, Toshiro; SUGIMOTO, Noboru

2015-01-01

At worksites, various automatic production machines are in use to release workers from muscular labor or labor in the detrimental environment. On the other hand, a large number of industrial accidents have been caused by automatic production machines. In view of this, this paper considers the operation of automatic production machines from the viewpoint of accident prevention, and points out two types of machine operation − operation for which quick performance is required (operation that is not permitted to be delayed) − and operation for which composed performance is required (operation that is not permitted to be performed in haste). These operations are distinguished by operation buttons of suitable colors and shapes. This paper shows that these characteristics are evaluated as “asymmetric on the time-axis”. Here, in order for workers to accept the risk of automatic production machines, it is preconditioned in general that harm should be sufficiently small or avoidance of harm is easy. In this connection, this paper shows the possibility of facilitating the acceptance of the risk of automatic production machines by enhancing the asymmetric on the time-axis. PMID:25739898

A simplified concept for controlling oxygen mixtures in the anaesthetic machine--better, cheaper and more user-friendly?

PubMed

Berge, J A; Gramstad, L; Grimnes, S

1995-05-01

Modern anaesthetic machines are equipped with several safety components to prevent delivery of hypoxic mixtures. However, such a technical development has increased the complexity of the equipment. We report a reconstructed anaesthetic machine in which a paramagnetic oxygen analyzer has provided the means to simplify the apparatus. The new machine is devoid of several components conventionally included to prevent hypoxic mixtures: oxygen failure protection device, reservoir O2 alarm, N2O/air selector, and proportioning system for oxygen/nitrous oxide delivery. These devices have been replaced by a simple safety system using a paramagnetic oxygen analyzer at the common gas outlet, which in a feed-back system cuts off the supply of nitrous oxide whenever the oxygen concentration falls below 25%. The simplified construction of the anaesthetic machine has important consequences for safety, cost and user-friendliness. Reducing the complexity of the construction also simplifies the pre-use checkout procedure, and an efficient 5-point check list is presented for the new machine.

Wear of dental tissues and materials.

PubMed

Craig, R G; Powers, J M

1976-06-01

Wear may result from physiological or pathological conditions and may be desirable, as in the reduction of an overcontoured restoration, or undesirable as in the production of cervical abrasion cavities. A variety of methods, including clinical testing, the use of wear machines and the measurement of related properties such as hardness or coefficient of friction have been used to investigate wear of tooth tissue and of dental materials. Because these methods may not reveal the nature of the wear process recent work has been directed to the study of surface failure resulting from a single sliding contact. Many clinical studies have been conducted but they are time consuming and difficult to quantify, nor do they allow of evaluation of different parameters contributing to the wear. Laboratory simulation of wear has been shown to be valuable in comparing materials of the same group but between-group comparisons may give anomalous results. The most rewarding studies have been those using a single or small number of passes of a suitable abrading point over the material since these permit determination of the actual process by which wear is produced.

Investigation of Low-Cycle Bending Fatigue of AISI 9310 Steel Spur Gears

NASA Technical Reports Server (NTRS)

Handschuh, Robert F.; Krantz, Timothy L.; Lerch, Bradley A.; Burke, Christopher S.

2007-01-01

An investigation of the low-cycle bending fatigue of spur gears made from AISI 9310 gear steel was completed. Tests were conducted using the single-tooth bending method to achieve crack initiation and propagation. Tests were conducted on spur gears in a fatigue test machine using a dedicated gear test fixture. Test loads were applied at the highest point of single tooth contact. Gear bending stresses for a given testing load were calculated using a linear-elastic finite element model. Test data were accumulated from 1/4 cycle to several thousand cycles depending on the test stress level. The relationship of stress and cycles for crack initiation was found to be semi-logarithmic. The relationship of stress and cycles for crack propagation was found to be linear. For the range of loads investigated, the crack propagation phase is related to the level of load being applied. Very high loads have comparable crack initiation and propagation times whereas lower loads can have a much smaller number of cycles for crack propagation cycles as compared to crack initiation.

Evaluation of the SPAR thermal analyzer on the CYBER-203 computer

NASA Technical Reports Server (NTRS)

Robinson, J. C.; Riley, K. M.; Haftka, R. T.

1982-01-01

The use of the CYBER 203 vector computer for thermal analysis is investigated. Strengths of the CYBER 203 include the ability to perform, in vector mode using a 64 bit word, 50 million floating point operations per second (MFLOPS) for addition and subtraction, 25 MFLOPS for multiplication and 12.5 MFLOPS for division. The speed of scalar operation is comparable to that of a CDC 7600 and is some 2 to 3 times faster than Langley's CYBER 175s. The CYBER 203 has 1,048,576 64-bit words of real memory with an 80 nanosecond (nsec) access time. Memory is bit addressable and provides single error correction, double error detection (SECDED) capability. The virtual memory capability handles data in either 512 or 65,536 word pages. The machine has 256 registers with a 40 nsec access time. The weaknesses of the CYBER 203 include the amount of vector operation overhead and some data storage limitations. In vector operations there is a considerable amount of time before a single result is produced so that vector calculation speed is slower than scalar operation for short vectors.

Advantages offered by high average power picosecond lasers

NASA Astrophysics Data System (ADS)

Moorhouse, C.

2011-03-01

As electronic devices shrink in size to reduce material costs, device size and weight, thinner material thicknesses are also utilized. Feature sizes are also decreasing, which is pushing manufacturers towards single step laser direct write process as an attractive alternative to conventional, multiple step photolithography processes by eliminating process steps and the cost of chemicals. The fragile nature of these thin materials makes them difficult to machine either mechanically or with conventional nanosecond pulsewidth, Diode Pumped Solids State (DPSS) lasers. Picosecond laser pulses can cut materials with reduced damage regions and selectively remove thin films due to the reduced thermal effects of the shorter pulsewidth. Also, the high repetition rate allows high speed processing for industrial applications. Selective removal of thin films for OLED patterning, silicon solar cells and flat panel displays is discussed, as well as laser cutting of transparent materials with low melting point such as Polyethylene Terephthalate (PET). For many of these thin film applications, where low pulse energy and high repetition rate are required, throughput can be increased by the use of a novel technique to using multiple beams from a single laser source is outlined.

Investigation of Low-Cycle Bending Fatigue of AISI 9310 Steel Spur Gears

NASA Technical Reports Server (NTRS)

Handschuh, Robert F.; Krantz, Timothy L.; Lerch, Bradley A.; Burke, Christopher S.

2007-01-01

An investigation of the low-cycle bending fatigue of spur gears made from AISI 9310 gear steel was completed. Tests were conducted using the single-tooth bending method to achieve crack initiation and propagation. Tests were conducted on spur gears in a fatigue test machine using a dedicated gear test fixture. Test loads were applied at the highest point of single tooth contact. Gear bending stresses for a given testing load were calculated using a linear-elastic finite element model. Test data were accumulated from 1/4 cycle to several thousand cycles depending on the test stress level. The relationship of stress and cycles for crack initiation was found to be semilogarithmic. The relationship of stress and cycles for crack propagation was found to be linear. For the range of loads investigated, the crack propagation phase is related to the level of load being applied. Very high loads have comparable crack initiation and propagation times whereas lower loads can have a much smaller number of cycles for crack propagation cycles as compared to crack initiation.

Using human brain activity to guide machine learning.

PubMed

Fong, Ruth C; Scheirer, Walter J; Cox, David D

2018-03-29

Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

Design of an ultraprecision computerized numerical control chemical mechanical polishing machine and its implementation

NASA Astrophysics Data System (ADS)

Zhang, Chupeng; Zhao, Huiying; Zhu, Xueliang; Zhao, Shijie; Jiang, Chunye

2018-01-01

The chemical mechanical polishing (CMP) is a key process during the machining route of plane optics. To improve the polishing efficiency and accuracy, a CMP model and machine tool were developed. Based on the Preston equation and the axial run-out error measurement results of the m circles on the tin plate, a CMP model that could simulate the material removal at any point on the workpiece was presented. An analysis of the model indicated that lower axial run-out error led to lower material removal but better polishing efficiency and accuracy. Based on this conclusion, the CMP machine was designed, and the ultraprecision gas hydrostatic guideway and rotary table as well as the Siemens 840Dsl numerical control system were incorporated in the CMP machine. To verify the design principles of machine, a series of detection and machining experiments were conducted. The LK-G5000 laser sensor was employed for detecting the straightness error of the gas hydrostatic guideway and the axial run-out error of the gas hydrostatic rotary table. A 300-mm-diameter optic was chosen for the surface profile machining experiments performed to determine the CMP efficiency and accuracy.

Modeling stochastic kinetics of molecular machines at multiple levels: from molecules to modules.

PubMed

Chowdhury, Debashish

2013-06-04

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Method for machining steel with diamond tools

DOEpatents

Casstevens, J.M.

1984-01-01

The present invention is directed to a method for machine optical quality finishes and contour accuracies of workpieces of carbon-containing metals such as steel with diamond tooling. The wear rate of the diamond tooling is significantly reduced by saturating the atmosphere at the interface of the workpiece and the diamond tool with a gaseous hydrocarbon during the machining operation. The presence of the gaseous hydrocarbon effectively eliminates the deterioration of the diamond tool by inhibiting or preventing the conversion of the diamond carbon to graphite carbon at the point of contact between the cutting tool and the workpiece.

Method for machining steel with diamond tools

DOEpatents

Casstevens, John M.

1986-01-01

The present invention is directed to a method for machining optical quality inishes and contour accuracies of workpieces of carbon-containing metals such as steel with diamond tooling. The wear rate of the diamond tooling is significantly reduced by saturating the atmosphere at the interface of the workpiece and the diamond tool with a gaseous hydrocarbon during the machining operation. The presence of the gaseous hydrocarbon effectively eliminates the deterioration of the diamond tool by inhibiting or preventing the conversion of the diamond carbon to graphite carbon at the point of contact between the cutting tool and the workpiece.

University NanoSat Program: AggieSat3

DTIC Science & Technology

2009-06-01

commercially available product for stereo machine vision developed by Point Grey Research. The current binocular BumbleBee2® system incorporates two...and Fellow of the American Society of Mechanical Engineers (ASME) in 1997. She was awarded the 2007 J. Leland "Lee" Atwood Award from the ASEE...AggieSat2 satellite programs. Additional experience gained in the area of drawing standards, machining capabilities, solid modeling, safety

Modeling of heat transfer in compacted machining chips during friction consolidation process

NASA Astrophysics Data System (ADS)

Abbas, Naseer; Deng, Xiaomin; Li, Xiao; Reynolds, Anthony

2018-04-01

The current study aims to provide an understanding of the heat transfer process in compacted aluminum alloy AA6061 machining chips during the friction consolidation process (FCP) through experimental investigations and mathematical modelling and numerical simulation. Compaction and friction consolidation of machining chips is the first stage of the Friction Extrusion Process (FEP), which is a novel method for recycling machining chips to produce useful products such as wires. In this study, compacted machining chips are modelled as a continuum whose material properties vary with density during friction consolidation. Based on density and temperature dependent thermal properties, the temperature field in the chip material and process chamber caused by frictional heating during the friction consolidation process is predicted. The predicted temperature field is found to compare well with temperature measurements at select points where such measurements can be made using thermocouples.

Legionellosis Outbreak Associated with Asphalt Paving Machine, Spain, 2009

PubMed Central

Fenollar, José; Escribano, Isabel; González-Candelas, Fernando

2010-01-01

From 1999 through 2005 in Alcoi, Spain, incidence of legionellosis was continually high. Over the next 4 years, incidence was lower, but an increase in July 2009 led health authorities to declare an epidemic outbreak. A molecular epidemiology investigation showed that the allelic profiles for all Legionella pneumophila samples from the 2009 outbreak patients were the same, thus pointing to a common genetic origin for their infections, and that they were identical to that of the organism that had caused the previous outbreaks. Spatial-temporal and sequence-based typing analyses indicated a milling machine used in street asphalt repaving and its water tank as the most likely sources. As opposed to other machines used for street cleaning, the responsible milling machine used water from a natural spring. When the operation of this machine was prohibited and cleaning measures were adopted, infections ceased. PMID:20735921

[Cyclic fatigue of Vita mark II machinable ceramics under Hertzian's contact].

PubMed

Liu, Wei-Cai; Zhang, Zhi-Shen; Huang, Cheng-Min; Chao, Yong-Lie; Wan, Qian-Bing

2006-08-01

To investigate the cyclic fatigue modes of Vita mark II machinable ceramics under Hertzian's contact. Hertzian's contact technique (WC spheres r = 3.18 mm) was used to investigate the cyclic fatigue of Vita mark II machinable ceramic. All specimens were fatigued by cyclic loading in moist environment, furthermore, surviving strength was examined by three point test and morphology damage observation. In homogeneous Vita mark II machinable ceramics, two fatigue damage modes existed after cyclic loading with spheres under moist environment, including conventional tensile-driven cone cracking (brittle mode) and shear-driven microdamage accumulation (quasi-plastic mode). The latter generated radial cracks and deeply penetrating secondary cone crack. Initial strength degradation were caused by the cone cracks, subsequent and much more deleterious loss was caused by radial cracks. Cyclic fatigue modes of Vita mark II machinable ceramics includes brittle and quasi-plastic mode.

Applications of random forest feature selection for fine-scale genetic population assignment.

PubMed

Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G

2018-02-01

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

Engineering model for ultrafast laser microprocessing

NASA Astrophysics Data System (ADS)

Audouard, E.; Mottay, E.

2016-03-01

Ultrafast laser micro-machining relies on complex laser-matter interaction processes, leading to a virtually athermal laser ablation. The development of industrial ultrafast laser applications benefits from a better understanding of these processes. To this end, a number of sophisticated scientific models have been developed, providing valuable insights in the physics of the interaction. Yet, from an engineering point of view, they are often difficult to use, and require a number of adjustable parameters. We present a simple engineering model for ultrafast laser processing, applied in various real life applications: percussion drilling, line engraving, and non normal incidence trepanning. The model requires only two global parameters. Analytical results are derived for single pulse percussion drilling or simple pass engraving. Simple assumptions allow to predict the effect of non normal incident beams to obtain key parameters for trepanning drilling. The model is compared to experimental data on stainless steel with a wide range of laser characteristics (time duration, repetition rate, pulse energy) and machining conditions (sample or beam speed). Ablation depth and volume ablation rate are modeled for pulse durations from 100 fs to 1 ps. Trepanning time of 5.4 s with a conicity of 0.15° is obtained for a hole of 900 μm depth and 100 μm diameter.

Performance analysis of single stage libr-water absorption machine operated by waste thermal energy of internal combustion engine: Case study

NASA Astrophysics Data System (ADS)

Sharif, Hafiz Zafar; Leman, A. M.; Muthuraman, S.; Salleh, Mohd Najib Mohd; Zakaria, Supaat

2017-09-01

Combined heating, cooling, and power is also known as Tri-generation. Tri-generation system can provide power, hot water, space heating and air -conditioning from single source of energy. The objective of this study is to propose a method to evaluate the characteristic and performance of a single stage lithium bromide-water (LiBr-H2O) absorption machine operated with waste thermal energy of internal combustion engine which is integral part of trigeneration system. Correlations for computer sensitivity analysis are developed in data fit software for (P-T-X), (H-T-X), saturated liquid (water), saturated vapor, saturation pressure and crystallization temperature curve of LiBr-H2O Solution. Number of equations were developed with data fit software and exported into excel work sheet for the evaluation of number of parameter concerned with the performance of vapor absorption machine such as co-efficient of performance, concentration of solution, mass flow rate, size of heat exchangers of the unit in relation to the generator, condenser, absorber and evaporator temperatures. Size of vapor absorption machine within its crystallization limits for cooling and heating by waste energy recovered from exhaust gas, and jacket water of internal combustion engine also presented in this study to save the time and cost for the facilities managers who are interested to utilize the waste thermal energy of their buildings or premises for heating and air conditioning applications.

Application of machine learning on brain cancer multiclass classification

NASA Astrophysics Data System (ADS)

Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

Biomechanical differences of the anterior and posterior bands of the ulnar collateral ligament of the elbow.

PubMed

Jackson, Timothy J; Jarrell, Shelby E; Adamson, Gregory J; Chung, Kyung Chil; Lee, Thay Q

2016-07-01

The main purpose of this study was to examine the functional characteristics of the anterior and posterior bands of the anterior bundle of the ulnar collateral ligament (UCL). Six cadaveric elbows were tested using a digital tracking system to measure the strain in the anterior band and posterior band of the anterior bundle of the UCL throughout a flexion/extension arc. The specimens were then placed in an Instron materials testing machine and loaded to failure to determine yield load and ultimate load of the UCL. The posterior band showed a linear increase in strain with increasing degrees of elbow flexion while the anterior band showed minimal change in strain throughout. The bands showed similar strain at yield load and ultimate load, demonstrating similar intrinsic properties. The anterior band of the anterior bundle of the UCL shows an isometric strain pattern through elbow range of motion, while the posterior band shows an increasing strain pattern in higher degrees of elbow flexion. Both bands show similar strain in a load to failure model, indicating insertion point, not intrinsic differences, of the bands determine the function of the anterior bundle of the UCL. This demonstrates a biomechanical rationale for UCL reconstructions using single point anatomical insertion points.

Multiple kernel SVR based on the MRE for remote sensing water depth fusion detection

NASA Astrophysics Data System (ADS)

Wang, Jinjin; Ma, Yi; Zhang, Jingyu

2018-03-01

Remote sensing has an important means of water depth detection in coastal shallow waters and reefs. Support vector regression (SVR) is a machine learning method which is widely used in data regression. In this paper, SVR is used to remote sensing multispectral bathymetry. Aiming at the problem that the single-kernel SVR method has a large error in shallow water depth inversion, the mean relative error (MRE) of different water depth is retrieved as a decision fusion factor with single kernel SVR method, a multi kernel SVR fusion method based on the MRE is put forward. And taking the North Island of the Xisha Islands in China as an experimentation area, the comparison experiments with the single kernel SVR method and the traditional multi-bands bathymetric method are carried out. The results show that: 1) In range of 0 to 25 meters, the mean absolute error(MAE)of the multi kernel SVR fusion method is 1.5m,the MRE is 13.2%; 2) Compared to the 4 single kernel SVR method, the MRE of the fusion method reduced 1.2% (1.9%) 3.4% (1.8%), and compared to traditional multi-bands method, the MRE reduced 1.9%; 3) In 0-5m depth section, compared to the single kernel method and the multi-bands method, the MRE of fusion method reduced 13.5% to 44.4%, and the distribution of points is more concentrated relative to y=x.

Public Data Set: Control and Automation of the Pegasus Multi-point Thomson Scattering System

DOE Data Explorer

Bodner, Grant M. [University of Wisconsin-Madison] (ORCID:0000000324979172); Bongard, Michael W. [University of Wisconsin-Madison] (ORCID:0000000231609746); Fonck, Raymond J. [University of Wisconsin-Madison] (ORCID:0000000294386762); Reusch, Joshua A. [University of Wisconsin-Madison] (ORCID:0000000284249422); Rodriguez Sanchez, Cuauhtemoc [University of Wisconsin-Madison] (ORCID:0000000334712586); Schlossberg, David J. [University of Wisconsin-Madison] (ORCID:0000000287139448)

2016-08-12

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in G.M. Bodner et al., 'Control and Automation of the Pegasus Multi-point Thomson Scattering System,' Rev. Sci. Instrum. 87, 11E523 (2016).

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.

MOD-2 wind turbine farm stability study

NASA Technical Reports Server (NTRS)

Hinrichsen, E. N.

1980-01-01

The dynamics of single and multiple 2.5 ME, Boeing MOD-2 wind turbine generators (WTGs) connected to utility power systems were investigated. The analysis was based on digital simulation. Both time response and frequency response methods were used. The dynamics of this type of WTG are characterized by two torsional modes, a low frequency 'shaft' mode below 1 Hz and an 'electrical' mode at 3-5 Hz. High turbine inertia and low torsional stiffness between turbine and generator are inherent features. Turbine control is based on electrical power, not turbine speed as in conventional utility turbine generators. Multi-machine dynamics differ very little from single machine dynamics.

An algorithm for a single machine scheduling problem with sequence dependent setup times and scheduling windows

NASA Technical Reports Server (NTRS)

Moore, J. E.

1975-01-01

An enumeration algorithm is presented for solving a scheduling problem similar to the single machine job shop problem with sequence dependent setup times. The scheduling problem differs from the job shop problem in two ways. First, its objective is to select an optimum subset of the available tasks to be performed during a fixed period of time. Secondly, each task scheduled is constrained to occur within its particular scheduling window. The algorithm is currently being used to develop typical observational timelines for a telescope that will be operated in earth orbit. Computational times associated with timeline development are presented.

Single-machine common/slack due window assignment problems with linear decreasing processing times

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Lin, Win-Chin; Wu, Wen-Hsiang; Wu, Chin-Chia

2017-08-01

This paper studies linear non-increasing processing times and the common/slack due window assignment problems on a single machine, where the actual processing time of a job is a linear non-increasing function of its starting time. The aim is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Some optimality results are discussed for the common/slack due window assignment problems and two O(n log n) time algorithms are presented to solve the two problems. Finally, two examples are provided to illustrate the correctness of the corresponding algorithms.

Resource Sharing in Montana: A Study of Interlibrary Loan and Alternatives for a Montana Union Catalog.

ERIC Educational Resources Information Center

Matthews, Joseph R.

This study recommends a variety of actions to create and maintain a Montana union catalog (MONCAT) for more effective usage of in-state resources and library funds. Specifically, it advocates (1) merger of existing COM, machine readable bibliographic records, and OCLC tapes into a single microform catalog; (2) acceptance of only machine readable…

Estimation of Teacher Practices Based on Text Transcripts of Teacher Speech Using a Support Vector Machine Algorithm

ERIC Educational Resources Information Center

Araya, Roberto; Plana, Francisco; Dartnell, Pablo; Soto-Andrade, Jorge; Luci, Gina; Salinas, Elena; Araya, Marylen

2012-01-01

Teacher practice is normally assessed by observers who watch classes or videos of classes. Here, we analyse an alternative strategy that uses text transcripts and a support vector machine classifier. For each one of the 710 videos of mathematics classes from the 2005 Chilean National Teacher Assessment Programme, a single 4-minute slice was…

Universal Tool Grinder Operator Instructor's Guide. Part of Single-Tool Skills Program Machine Industries Occupations.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Div. of Curriculum Development.

The document is an instructor's guide for a course on universal tool grinder operation. The course is designed to train people in making complicated machine setups and precision in the grinding operations and, although intended primarily for adult learners, it can be adapted for high school use. The guide is divided into three parts: (1) the…

Many Molecular Properties from One Kernel in Chemical Space

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

Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

We introduce property-independent kernels for machine learning modeling of arbitrarily many molecular properties. The kernels encode molecular structures for training sets of varying size, as well as similarity measures sufficiently diffuse in chemical space to sample over all training molecules. Corresponding molecular reference properties provided, they enable the instantaneous generation of ML models which can systematically be improved through the addition of more data. This idea is exemplified for single kernel based modeling of internal energy, enthalpy, free energy, heat capacity, polarizability, electronic spread, zero-point vibrational energy, energies of frontier orbitals, HOMOLUMO gap, and the highest fundamental vibrational wavenumber. Modelsmore » of these properties are trained and tested using 112 kilo organic molecules of similar size. Resulting models are discussed as well as the kernels’ use for generating and using other property models.« less

Deflection Shape Reconstructions of a Rotating Five-blade Helicopter Rotor from TLDV Measurements

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

Fioretti, A.; Castellini, P.; Tomasini, E. P.

2010-05-28

Helicopters are aircraft machines which are subjected to high level of vibrations, mainly due to spinning rotors. These are made of two or more blades attached by hinges to a central hub, which can make the dynamic behaviour difficult to study. However, they share some common dynamic properties with the ones expected in bladed discs, thereby the analytical modelling of rotors can be performed using some assumptions as the ones adopted for the bladed discs. This paper presents results of a vibrations study performed on a scaled helicopter rotor model which was rotating at a fix rotational speed and excitedmore » by an air jet. A simplified analytical model of that rotor was also produced to help the identifications of the vibration patterns measured using a single point tracking-SLDV measurement method.« less

Assessment of Multiaxial Mechanical Response of Rigid Polyurethane Foams

NASA Astrophysics Data System (ADS)

Pettarin, Valeria; Fasce, Laura A.; Frontini, Patricia M.

2014-02-01

Multiaxial deformation behavior and failure surface of rigid polyurethane foams were determined using standard experimental facilities. Two commercial foams of different densities were assayed under uniaxial, biaxial, and triaxial stress states. These different stress states were reached in a uniaxial universal testing machine using suitable testing configurations which imply the use of special grips and lateral restricted samples. Actual strains were monitored with a video extensometer. Polyurethane foams exhibited typical isotropic brittle behavior, except under compressive loads where the response turned out to be ductile. A general failure surface in the stress space which accounts for density effects could be successfully generated. All of failure data, determined at the loss of linear elasticity point, collapsed in a single locus defined as the combination of a brittle crushing of closed-cell cellular materials criterion capped by an elastic buckling criterion.

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.

A control technology evaluation of state-of-the-art, perchloroethylene dry-cleaning machines.

PubMed

Earnest, G Scott

2002-05-01

NIOSH researchers evaluated the ability of fifth-generation dry-cleaning machines to control occupational exposure to perchloroethylene (PERC). Use of these machines is mandated in some countries; however, less than 1 percent of all U.S. shops have them. A study was conducted at a U.S. dry-cleaning shop where two fifth-generation machines were used. Both machines had a refrigerated condenser as a primary control and a carbon adsorber as a secondary control to recover PERC vapors during the dry cycle. These machines were designed to lower the PERC concentration in the cylinder at the end of the dry cycle to below 290 ppm. A single-beam infrared photometer continuously monitors the PERC concentration in the machine cylinder, and a door interlock prevents opening until the concentration is below 290 ppm. Personal breathing zone air samples were measured for the machine operator and presser. The operator had time-weighted average (TWA) PERC exposures that were less than 2 ppm. Highest exposures occurred during loading and unloading the machine and when performing routine machine maintenance. All presser samples were below the limit of detection. Real-time video exposure monitoring showed that the operator had peak exposures near 160 ppm during loading and unloading the machine (below the OSHA maximum of 300 ppm). This exposure (160 ppm) is an order of magnitude lower than exposures with more traditional machines that are widely used in the United States. The evaluated machines were very effective at reducing TWA PERC exposures as well as peak exposures that occur during machine loading and unloading. State-of-the-art dry-cleaning machines equipped with refrigerated condensers, carbon adsorbers, drum monitors, and door interlocks can provide substantially better protection than more traditional machines that are widely used in the United States.

Development of a coordinate measuring machine (CMM) touch probe using a multi-axis force sensor

NASA Astrophysics Data System (ADS)

Park, Jae-jun; Kwon, Kihwan; Cho, Nahmgyoo

2006-09-01

Traditional touch trigger probes are widely used on most commercial coordinate measuring machines (CMMs). However, the CMMs with these probes have a systematic error due to the shape of the probe tip and elastic deformation of the stylus resulting from contact pressure with the specimen. In this paper, a new touch probe with a three degrees-of-freedom force sensor is proposed. From relationships between an obtained contact force vector and the geometric shape of the probe, it is possible to calculate the coordinates of the exact probe-specimen contact points. An empirical model of the probe is applied to calculate the coordinates of the contact points and the amount of pretravel. With the proposed probing system, the measuring error induced by the indeterminateness of the probe-specimen contact point and the pretravel can be estimated and compensated for successfully.

A Machine-Checked Proof of A State-Space Construction Algorithm

NASA Technical Reports Server (NTRS)

Catano, Nestor; Siminiceanu, Radu I.

2010-01-01

This paper presents the correctness proof of Saturation, an algorithm for generating state spaces of concurrent systems, implemented in the SMART tool. Unlike the Breadth First Search exploration algorithm, which is easy to understand and formalise, Saturation is a complex algorithm, employing a mutually-recursive pair of procedures that compute a series of non-trivial, nested local fixed points, corresponding to a chaotic fixed point strategy. A pencil-and-paper proof of Saturation exists, but a machine checked proof had never been attempted. The key element of the proof is the characterisation theorem of saturated nodes in decision diagrams, stating that a saturated node represents a set of states encoding a local fixed-point with respect to firing all events affecting only the node s level and levels below. For our purpose, we have employed the Prototype Verification System (PVS) for formalising the Saturation algorithm, its data structures, and for conducting the proofs.

Measuring FLOPS Using Hardware Performance Counter Technologies on LC systems

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

Ahn, D H

2008-09-05

FLOPS (FLoating-point Operations Per Second) is a commonly used performance metric for scientific programs that rely heavily on floating-point (FP) calculations. The metric is based on the number of FP operations rather than instructions, thereby facilitating a fair comparison between different machines. A well-known use of this metric is the LINPACK benchmark that is used to generate the Top500 list. It measures how fast a computer solves a dense N by N system of linear equations Ax=b, which requires a known number of FP operations, and reports the result in millions of FP operations per second (MFLOPS). While running amore » benchmark with known FP workloads can provide insightful information about the efficiency of a machine's FP pipelines in relation to other machines, measuring FLOPS of an arbitrary scientific application in a platform-independent manner is nontrivial. The goal of this paper is twofold. First, we explore the FP microarchitectures of key processors that are underpinning the LC machines. Second, we present the hardware performance monitoring counter-based measurement techniques that a user can use to get the native FLOPS of his or her program, which are practical solutions readily available on LC platforms. By nature, however, these native FLOPS metrics are not directly comparable across different machines mainly because FP operations are not consistent across microarchitectures. Thus, the first goal of this paper represents the base reference by which a user can interpret the measured FLOPS more judiciously.« less

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

A Machine Learning Approach to Identifying Placebo Responders in Late-Life Depression Trials.

PubMed

Zilcha-Mano, Sigal; Roose, Steven P; Brown, Patrick J; Rutherford, Bret R

2018-01-11

Despite efforts to identify characteristics associated with medication-placebo differences in antidepressant trials, few consistent findings have emerged to guide participant selection in drug development settings and differential therapeutics in clinical practice. Limitations in the methodologies used, particularly searching for a single moderator while treating all other variables as noise, may partially explain the failure to generate consistent results. The present study tested whether interactions between pretreatment patient characteristics, rather than a single-variable solution, may better predict who is most likely to benefit from placebo versus medication. Data were analyzed from 174 patients aged 75 years and older with unipolar depression who were randomly assigned to citalopram or placebo. Model-based recursive partitioning analysis was conducted to identify the most robust significant moderators of placebo versus citalopram response. The greatest signal detection between medication and placebo in favor of medication was among patients with fewer years of education (≤12) who suffered from a longer duration of depression since their first episode (>3.47 years) (B = 2.53, t(32) = 3.01, p = 0.004). Compared with medication, placebo had the greatest response for those who were more educated (>12 years), to the point where placebo almost outperformed medication (B = -0.57, t(96) = -1.90, p = 0.06). Machine learning approaches capable of evaluating the contributions of multiple predictor variables may be a promising methodology for identifying placebo versus medication responders. Duration of depression and education should be considered in the efforts to modulate placebo magnitude in drug development settings and in clinical practice. Copyright © 2018 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Neurocognitive pattern analysis reveals classificatory hierarchy of attention deficits in schizophrenia.

PubMed

Shen, Christina; Popescu, Florin C; Hahn, Eric; Ta, Tam T M; Dettling, Michael; Neuhaus, Andres H

2014-07-01

Attention deficits, among other cognitive deficits, are frequently observed in schizophrenia. Although valid and reliable neurocognitive tasks have been established to assess attention deficits in schizophrenia, the hierarchical value of those tests as diagnostic discriminants on a single-subject level remains unclear. Thus, much research is devoted to attention deficits that are unlikely to be translated into clinical practice. On the other hand, a clear hierarchy of attention deficits in schizophrenia could considerably aid diagnostic decisions and may prove beneficial for longitudinal monitoring of therapeutic advances. To propose a diagnostic hierarchy of attention deficits in schizophrenia, we investigated several facets of attention in 86 schizophrenia patients and 86 healthy controls using a set of established attention tests. We applied state-of-the-art machine learning algorithms to determine attentive test variables that enable an automated differentiation between schizophrenia patients and healthy controls. After feature preranking, hypothesis building, and hypothesis validation, the polynomial support vector machine classifier achieved a classification accuracy of 90.70% ± 2.9% using psychomotor speed and 3 different attention parameters derived from sustained and divided attention tasks. Our study proposes, to the best of our knowledge, the first hierarchy of attention deficits in schizophrenia by identifying the most discriminative attention parameters among a variety of attention deficits found in schizophrenia patients. Our results offer a starting point for hierarchy building of schizophrenia-associated attention deficits and contribute to translating these concepts into diagnostic and therapeutic practice on a single-subject level. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

Arc fusion splicing of photonic crystal fibers to standard single mode fibers

NASA Astrophysics Data System (ADS)

Borzycki, Krzysztof; Kobelke, Jens; Schuster, Kay; Wójcik, Jan

2010-04-01

Coupling a photonic crystal fiber (PCF) to measuring instruments or optical subsystems is often done by splicing it to short lengths of single mode fiber (SMF) used for interconnections, as SMF is standardized, widely available and compatible with most fiber optic components and measuring instruments. This paper presents procedures and results of loss measurements during fusion splicing of five PCFs tested at NIT laboratory within activities of COST Action 299 "FIDES". Investigated silica-based fibers had 80-200 μm cladding diameter and were designed as single mode. A standard splicing machine designed for telecom fibers was used, but splicing procedure and arc power were tailored to each PCF. Splice loss varied between 0.7 and 2.8 dB at 1550 nm. Splices protected with heat-shrinkable sleeves served well for gripping fibers during mechanical tests and survived temperature cycling from -30°C to +70°C with stable loss. Collapse of holes in the PCF was limited by reducing fusion time to 0.2-0.5 s; additional measures included reduction of discharge power and shifting SMF-PCF contact point away from the axis of electrodes. Unfortunately, short fusion time sometimes precluded proper smoothing of glass surface, leading to a trade-off between splice loss and strength.

A Framework to Guide the Assessment of Human-Machine Systems.

PubMed

Stowers, Kimberly; Oglesby, James; Sonesh, Shirley; Leyva, Kevin; Iwig, Chelsea; Salas, Eduardo

2017-03-01

We have developed a framework for guiding measurement in human-machine systems. The assessment of safety and performance in human-machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human-machine systems. As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human-machine systems, giving a snapshot of the state of science on human-machine system safety and performance. Using this information, we created a framework of safety and performance in human-machine systems. This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human-machine systems. This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems. This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.

Python Spectral Analysis Tool (PySAT) for Preprocessing, Multivariate Analysis, and Machine Learning with Point Spectra

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S.; Graff, T.; Morris, R. V.; Laura, J.

2017-06-01

We present a Python-based library and graphical interface for the analysis of point spectra. The tool is being developed with a focus on methods used for ChemCam data, but is flexible enough to handle spectra from other instruments.

27 CFR 479.41 - Single sale.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2014-04-01 2014-04-01 false Single sale. 479.41 Section 479.41 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS, AND EXPLOSIVES, DEPARTMENT OF JUSTICE FIREARMS AND AMMUNITION MACHINE GUNS, DESTRUCTIVE DEVICES, AND CERTAIN...

27 CFR 479.41 - Single sale.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2010-04-01 2010-04-01 false Single sale. 479.41 Section 479.41 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS, AND EXPLOSIVES, DEPARTMENT OF JUSTICE FIREARMS AND AMMUNITION MACHINE GUNS, DESTRUCTIVE DEVICES, AND CERTAIN...

27 CFR 479.41 - Single sale.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2013-04-01 2013-04-01 false Single sale. 479.41 Section 479.41 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS, AND EXPLOSIVES, DEPARTMENT OF JUSTICE FIREARMS AND AMMUNITION MACHINE GUNS, DESTRUCTIVE DEVICES, AND CERTAIN...

Preparation of superhydrophobic copper surface by a novel silk-screen printing aided electrochemical machining method

NASA Astrophysics Data System (ADS)

Yan, X. Y.; Chen, G. X.; Liu, J. W.

2018-03-01

A kind of superhydrophobic copper surface with micro-nanocomposite structure has been successfully fabricated by employing a silk-screen printing aided electrochemical machining method. At first silk-screen printing technology has been used to form a column point array mask, and then the microcolumn array would be fabricated by electrochemical machining (ECM) effect. In this study, the drop contact angles have been studied and scanning electron microscopy (SEM) has been used to study the surface characteristic of the workpiece. The experiment results show that the micro-nanocomposite structure with cylindrical array can be successfully fabricated on the metal surface. And the maximum contact angle is 151° when the fluoroalkylsilane ethanol solution was used to modify the machined surface in this study.

Summary of REAC Experience

DTIC Science & Technology

1949-09-08

error from this source can be substantially reduced by the use of polystyrene insulating materials in the plugboard system of problem patching (Section...present at some point in the machine (see Section 5b). -10- ( 1 d ~ PLUGBOARD Our experience ·with the operation of the REAC indicates that...utilization of the machine could be very significantly increased by a drastic revision of the patch bay. We propose to install a separable plugboard which

Ceramic Life Prediction Parameters

DTIC Science & Technology

1980-05-01

preferential. A standard creep testing Satec machine with a modified load train assembly was used for tensile stress-rupture testing. The specimen is...to the standard Satec machine head which includes crossed (90°) knife edges. The assembly procedure includes hanging the load train parts from...the Satec head as influenced by gravity. At this point the lower Satec crossarm is lowered to snub the train in this position. The load train

APOLLO: a quality assessment service for single and multiple protein models.

PubMed

Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

2011-06-15

We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

Stochastic scheduling on a repairable manufacturing system

NASA Astrophysics Data System (ADS)

Li, Wei; Cao, Jinhua

1995-08-01

In this paper, we consider some stochastic scheduling problems with a set of stochastic jobs on a manufacturing system with a single machine that is subject to multiple breakdowns and repairs. When the machine processing a job fails, the job processing must restart some time later when the machine is repaired. For this typical manufacturing system, we find the optimal policies that minimize the following objective functions: (1) the weighed sum of the completion times; (2) the weighed number of late jobs having constant due dates; (3) the weighted number of late jobs having random due dates exponentially distributed, which generalize some previous results.

The Design of the Automatic Control System of the Gripping-Belt Speed in Long-Rootstalk Traditional Chinese Herbal Harvester

NASA Astrophysics Data System (ADS)

Huang, Jinxia; Wang, Junfa; Yu, Yonghong

This article aims to design a kind of gripping-belt speed automatic tracking system of traditional Chinese herbal harvester by AT89C52 single-chip micro computer as a core combined with fuzzy PID control algorithm. The system can adjust the gripping-belt speed in accordance with the variation of the machine's operation, so there is a perfect matching between the machine operation speed and the gripping-belt speed. The harvesting performance of the machine can be improved greatly. System design includes hardware and software.

Principle and design of small-sized and high-definition x-ray machine

NASA Astrophysics Data System (ADS)

Zhao, Anqing

2010-10-01

The paper discusses the circuit design and working principles of VMOS PWM type 75KV10mA high frequency X-ray machine. The system mainly consists of silicon controlled rectifier, VMOS tube PWM type high-frequency and highvoltage inverter circuit, filament inverter circuit, high-voltage rectifier filter circuit and as X-ray tube. The working process can be carried out under the control of a single-chip microcomputer. Due to the small size and high resolution in imaging, the X-ray machine is mostly adopted for emergent medical diagnosis and specific circumstances where nondestructive tests are conducted.

Tribology and energy efficiency: from molecules to lubricated contacts to complete machines.

PubMed

Taylor, Robert Ian

2012-01-01

The impact of lubricants on energy efficiency is considered. Molecular details of base oils used in lubricants can have a great impact on the lubricant's physical properties which will affect the energy efficiency performance of a lubricant. In addition, molecular details of lubricant additives can result in significant differences in measured friction coefficients for machine elements operating in the mixed/boundary lubrication regime. In single machine elements, these differences will result in lower friction losses, and for complete systems (such as cars, trucks, hydraulic circuits, industrial gearboxes etc.) lower fuel consumption or lower electricity consumption can result.

A parallel-machine scheduling problem with two competing agents

NASA Astrophysics Data System (ADS)

Lee, Wen-Chiung; Chung, Yu-Hsiang; Wang, Jen-Ya

2017-06-01

Scheduling with two competing agents has become popular in recent years. Most of the research has focused on single-machine problems. This article considers a parallel-machine problem, the objective of which is to minimize the total completion time of jobs from the first agent given that the maximum tardiness of jobs from the second agent cannot exceed an upper bound. The NP-hardness of this problem is also examined. A genetic algorithm equipped with local search is proposed to search for the near-optimal solution. Computational experiments are conducted to evaluate the proposed genetic algorithm.

Rotating magnetizations in electrical machines: Measurements and modeling

NASA Astrophysics Data System (ADS)

Thul, Andreas; Steentjes, Simon; Schauerte, Benedikt; Klimczyk, Piotr; Denke, Patrick; Hameyer, Kay

2018-05-01

This paper studies the magnetization process in electrical steel sheets for rotational magnetizations as they occur in the magnetic circuit of electrical machines. A four-pole rotational single sheet tester is used to generate the rotating magnetic flux inside the sample. A field-oriented control scheme is implemented to improve the control performance. The magnetization process of different non-oriented materials is analyzed and compared.

Process Parameters Optimization in Single Point Incremental Forming

NASA Astrophysics Data System (ADS)

Gulati, Vishal; Aryal, Ashmin; Katyal, Puneet; Goswami, Amitesh

2016-04-01

This work aims to optimize the formability and surface roughness of parts formed by the single-point incremental forming process for an Aluminium-6063 alloy. The tests are based on Taguchi's L18 orthogonal array selected on the basis of DOF. The tests have been carried out on vertical machining center (DMC70V); using CAD/CAM software (SolidWorks V5/MasterCAM). Two levels of tool radius, three levels of sheet thickness, step size, tool rotational speed, feed rate and lubrication have been considered as the input process parameters. Wall angle and surface roughness have been considered process responses. The influential process parameters for the formability and surface roughness have been identified with the help of statistical tool (response table, main effect plot and ANOVA). The parameter that has the utmost influence on formability and surface roughness is lubrication. In the case of formability, lubrication followed by the tool rotational speed, feed rate, sheet thickness, step size and tool radius have the influence in descending order. Whereas in surface roughness, lubrication followed by feed rate, step size, tool radius, sheet thickness and tool rotational speed have the influence in descending order. The predicted optimal values for the wall angle and surface roughness are found to be 88.29° and 1.03225 µm. The confirmation experiments were conducted thrice and the value of wall angle and surface roughness were found to be 85.76° and 1.15 µm respectively.

Automatic detection of anatomical regions in frontal x-ray images: comparing convolutional neural networks to random forest

NASA Astrophysics Data System (ADS)

Olory Agomma, R.; Vázquez, C.; Cresson, T.; De Guise, J.

2018-02-01

Most algorithms to detect and identify anatomical structures in medical images require either to be initialized close to the target structure, or to know that the structure is present in the image, or to be trained on a homogeneous database (e.g. all full body or all lower limbs). Detecting these structures when there is no guarantee that the structure is present in the image, or when the image database is heterogeneous (mixed configurations), is a challenge for automatic algorithms. In this work we compared two state-of-the-art machine learning techniques in order to determine which one is the most appropriate for predicting targets locations based on image patches. By knowing the position of thirteen landmarks points, labelled by an expert in EOS frontal radiography, we learn the displacement between salient points detected in the image and these thirteen landmarks. The learning step is carried out with a machine learning approach by exploring two methods: Convolutional Neural Network (CNN) and Random Forest (RF). The automatic detection of the thirteen landmarks points in a new image is then obtained by averaging the positions of each one of these thirteen landmarks estimated from all the salient points in the new image. We respectively obtain for CNN and RF, an average prediction error (both mean and standard deviation in mm) of 29 +/-18 and 30 +/- 21 for the thirteen landmarks points, indicating the approximate location of anatomical regions. On the other hand, the learning time is 9 days for CNN versus 80 minutes for RF. We provide a comparison of the results between the two machine learning approaches.

Ductile and brittle transition behavior of titanium alloys in ultra-precision machining.

PubMed

Yip, W S; To, S

2018-03-02

Titanium alloys are extensively applied in biomedical industries due to their excellent material properties. However, they are recognized as difficult to cut materials due to their low thermal conductivity, which induces a complexity to their deformation mechanisms and restricts precise productions. This paper presents a new observation about the removal regime of titanium alloys. The experimental results, including the chip formation, thrust force signal and surface profile, showed that there was a critical cutting distance to achieve better surface integrity of machined surface. The machined areas with better surface roughness were located before the clear transition point, defining as the ductile to brittle transition. The machined area at the brittle region displayed the fracture deformation which showed cracks on the surface edge. The relationship between depth of cut and the ductile to brittle transaction behavior of titanium alloys in ultra-precision machining(UPM) was also revealed in this study, it showed that the ductile to brittle transaction behavior of titanium alloys occurred mainly at relatively small depth of cut. The study firstly defines the ductile to brittle transition behavior of titanium alloys in UPM, contributing the information of ductile machining as an optimal machining condition for precise productions of titanium alloys.

The machinability of cast titanium and Ti-6Al-4V.

PubMed

Ohkubo, C; Watanabe, I; Ford, J P; Nakajima, H; Hosoi, T; Okabe, T

2000-02-01

This study investigated the machinability (ease of metal removal) of commercially pure (CP) titanium and Ti-6Al-4V alloy. Both CP Ti and Ti-6Al-4V were cast into magnesia molds. Two types of specimens (with alpha-case and without alpha-case) were made for CP Ti and Ti-6Al-4V. Machinability (n = 5) was evaluated as volume loss (mm3) by cutting/grinding the 3.0 mm surface using fissure burs and silicon carbide (SiC) under two machining conditions: (1) two machining forces (100 or 300 gf) at two rotational speeds (15000 or 30000 rpm) for 1 min, and (2) constant machining force of 100 gf and rotational speed of 15000 rpm for 1, 2, 5, 10, and 30 min. As controls, conventionally cast Co-Cr and Type IV gold alloys were evaluated in the same manner as the titanium. When fissure burs were used, there was a significant difference in the machinability between CP titanium with alpha-case and without alpha-case. On the other hand, there was no appreciable difference in the amount of metal removed for each tested metal when using the SiC points.

27 CFR 479.41 - Single sale.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2012-04-01 2010-04-01 true Single sale. 479.41 Section 479.41 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS, AND EXPLOSIVES, DEPARTMENT OF JUSTICE FIREARMS AND AMMUNITION MACHINE GUNS, DESTRUCTIVE DEVICES, AND CERTAIN OTHER FIREARMS...

27 CFR 479.41 - Single sale.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 27 Alcohol, Tobacco Products and Firearms 3 2011-04-01 2010-04-01 true Single sale. 479.41 Section 479.41 Alcohol, Tobacco Products, and Firearms BUREAU OF ALCOHOL, TOBACCO, FIREARMS, AND EXPLOSIVES, DEPARTMENT OF JUSTICE FIREARMS AND AMMUNITION MACHINE GUNS, DESTRUCTIVE DEVICES, AND CERTAIN OTHER FIREARMS...

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

Using machine learning to identify structural breaks in single-group interrupted time series designs.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.