Full-band error control and crack-free surface fabrication techniques for ultra-precision fly cutting of large-aperture KDP crystals

NASA Astrophysics Data System (ADS)

Zhang, F. H.; Wang, S. F.; An, C. H.; Wang, J.; Xu, Q.

2017-06-01

Large-aperture potassium dihydrogen phosphate (KDP) crystals are widely used in the laser path of inertial confinement fusion (ICF) systems. The most common method of manufacturing half-meter KDP crystals is ultra-precision fly cutting. When processing KDP crystals by ultra-precision fly cutting, the dynamic characteristics of the fly cutting machine and fluctuations in the fly cutting environment are translated into surface errors at different spatial frequency bands. These machining errors should be suppressed effectively to guarantee that KDP crystals meet the full-band machining accuracy specified in the evaluation index. In this study, the anisotropic machinability of KDP crystals and the causes of typical surface errors in ultra-precision fly cutting of the material are investigated. The structures of the fly cutting machine and existing processing parameters are optimized to improve the machined surface quality. The findings are theoretically and practically important in the development of high-energy laser systems in China.

Artificial Intelligence and Expert Systems.

ERIC Educational Resources Information Center

Lawlor, Joseph

Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

Modeling of industrial stream and resources of machine-building enterpriser complex of wood preparation

NASA Astrophysics Data System (ADS)

Sereda, T. G.; Kostarev, S. N.

2018-03-01

Theoretical bases of linkage of material streams of the machine-building enterprise and the automated system of decision-making are developed. The process of machine-building manufacture is submitted by the existential system. The equation of preservation of movement is based on calculation of volume of manufacture. The basis of resource variables includes capacities and operators of the equipment. Indignations such as a defect and failure are investigated in the existential basis. The equation of a stream of details on a manufacturing route is made. The received analytical expression expresses a condition of a stream of movement of details in view of influence of work of the equipment and traumatism of the personnel.

Design and Analysis of Linear Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Xu, Liang; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis. PMID:24982959

Design and analysis of linear fault-tolerant permanent-magnet vernier machines.

PubMed

Xu, Liang; Ji, Jinghua; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis.

Natural Language Processing.

ERIC Educational Resources Information Center

Chowdhury, Gobinda G.

2003-01-01

Discusses issues related to natural language processing, including theoretical developments; natural language understanding; tools and techniques; natural language text processing systems; abstracting; information extraction; information retrieval; interfaces; software; Internet, Web, and digital library applications; machine translation for…

Molecular, metabolic, and genetic control: An introduction

NASA Astrophysics Data System (ADS)

Tyson, John J.; Mackey, Michael C.

2001-03-01

The living cell is a miniature, self-reproducing, biochemical machine. Like all machines, it has a power supply, a set of working components that carry out its necessary tasks, and control systems that ensure the proper coordination of these tasks. In this Special Issue, we focus on the molecular regulatory systems that control cell metabolism, gene expression, environmental responses, development, and reproduction. As for the control systems in human-engineered machines, these regulatory networks can be described by nonlinear dynamical equations, for example, ordinary differential equations, reaction-diffusion equations, stochastic differential equations, or cellular automata. The articles collected here illustrate (i) a range of theoretical problems presented by modern concepts of cellular regulation, (ii) some strategies for converting molecular mechanisms into dynamical systems, (iii) some useful mathematical tools for analyzing and simulating these systems, and (iv) the sort of results that derive from serious interplay between theory and experiment.

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.

Cryogenic engineering

NASA Astrophysics Data System (ADS)

Beliakov, V. P.

Recent developments and trends in cryogenic engineering are reviewed, with emphasis on the role of cryogenics in power generation, machine building, chemistry, and metallurgy. Several cryogenic systems are described, including air-separation apparatus, cryogenic storage systems, cryothermovacuum devices, and the cryogenic systems of superconducting devices. The theoretical principles underlying the design of cryogenic systems are examined, along with the theory for the processes involved.

Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

NASA Technical Reports Server (NTRS)

Dalton, Shelly D.; Daley, Philip C.

1988-01-01

As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

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.

Tactical Aviation Mission System Simulation Situational Awareness Project

DTIC Science & Technology

2004-04-01

prototyping and exercising human-machine systems and for measuring the impact of new technologies in a dynamic simulation environment. Theoretical...31 2.4.1 The Impact of an ERSTA-Like System on the CH-146 Mission Commander...was proven to be an effective platform for prototyping and exercising systems and for measuring the impact of new technologies in a dynamic simulation

Two-stage approach to keyword spotting in handwritten documents

NASA Astrophysics Data System (ADS)

Haji, Mehdi; Ameri, Mohammad R.; Bui, Tien D.; Suen, Ching Y.; Ponson, Dominique

2013-12-01

Separation of keywords from non-keywords is the main problem in keyword spotting systems which has traditionally been approached by simplistic methods, such as thresholding of recognition scores. In this paper, we analyze this problem from a machine learning perspective, and we study several standard machine learning algorithms specifically in the context of non-keyword rejection. We propose a two-stage approach to keyword spotting and provide a theoretical analysis of the performance of the system which gives insights on how to design the classifier in order to maximize the overall performance in terms of F-measure.

Contribution a l'etude et a la conception d'une machine synchrone a flux transverse destinee au degivrage d'aeronefs en cours de vol

NASA Astrophysics Data System (ADS)

Boussetoua, Mohammed

During winter, the climate in the northern region is known for its icing and freezing conditions. However, emergency services often use helicopters to reach isolated locations. The difficult situations, generally experiences in the North particularly in Quebec, may prevent rescuers to intervene. The main reason preventing such operations is the lack of a de-icing system in the small helicopter blades. The overall objective of the project is research, development, design and manufacture of a system composed of an on-board rotating low speed generator and heating elements. It consumes a part of the power supplied by the turbine through the axis of the main rotor of the small aircraft and converts it to electrical power to be used by the heating elements. This innovation will allow to fly safely everywhere throughout the year protect the lives of the users even in the worst weather conditions. Firstly, the research focuses on the identification of problems related to the use of protection systems against the hoarfrost on main rotor blades of different aircrafts during flight. In this phase, we specifically focused on the difficulties encountered by the aircraft companies using the existing and operational systems for protection against hoarfrost. Main rotor blades are difficult to protect on helicopters. Several systems were considered by the helicopter manufacturers, such as electrothermal systems, pneumatic systems or using anti-icing fluids. In the current state of technological knowledge, all helicopters that have been certified to fly in icing conditions use electrothermal systems for protection against hoarfrost on their main rotor Small helicopters addressed by this work, are forbidden to fly in icing conditions due to lack of energy source to operate these systems. The electrothermal system has been considered for this thesis work to protect the main rotor blades of small aircraft in-flight. The second part of this thesis is based on the source of power feeding the hearting system. In recent years, numerous research studies have started on the development of electromechanical system converters for various applications, such as transport by road, rail or aviation. The development of new low-speed, low-weight electric machines and their very high degree of compactness has become a very promising alternative. This project strongly interests many industries in the field of air transport. The transverse flux machine is considered as a compact structure having better mass power compared to other electrical machines. The design of transverse flux machine was the subject of an electromagnetic study. Also, the analytical study helped to determine the overall dimensions of the machine. The study was followed by a validation phase of the analytical model using numerical simulations. These two studies were intended to determine changes in the characteristics of the transverse flux machine according to the different geometric dimensions of its active parts. From the calculations made using analytical and numerical models, a prototype of the transverse flux machine (600 W, 320 RPM) was designed and manufactured in the AMIL laboratory at the Universite du Quebec a Chicoutimi (UQAC). A bench test was conducted to compare the theoretical and experimental results. The measurements obtained on this prototype were compared with the theoretical results. This phase of the study demonstrates with satisfaction, the reliability of the theoretical models developed. Finally, a new configuration of this machine has been proposed. Numerical simulation results of this structure are particularly encouraging and require further investigations. For logistical and financial reasons, the prototype of this configuration has not been manufactured. (Abstract shortened by UMI.)

Is extreme learning machine feasible? A theoretical assessment (part I).

PubMed

Liu, Xia; Lin, Shaobo; Fang, Jian; Xu, Zongben

2015-01-01

An extreme learning machine (ELM) is a feedforward neural network (FNN) like learning system whose connections with output neurons are adjustable, while the connections with and within hidden neurons are randomly fixed. Numerous applications have demonstrated the feasibility and high efficiency of ELM-like systems. It has, however, been open if this is true for any general applications. In this two-part paper, we conduct a comprehensive feasibility analysis of ELM. In Part I, we provide an answer to the question by theoretically justifying the following: 1) for some suitable activation functions, such as polynomials, Nadaraya-Watson and sigmoid functions, the ELM-like systems can attain the theoretical generalization bound of the FNNs with all connections adjusted, i.e., they do not degrade the generalization capability of the FNNs even when the connections with and within hidden neurons are randomly fixed; 2) the number of hidden neurons needed for an ELM-like system to achieve the theoretical bound can be estimated; and 3) whenever the activation function is taken as polynomial, the deduced hidden layer output matrix is of full column-rank, therefore the generalized inverse technique can be efficiently applied to yield the solution of an ELM-like system, and, furthermore, for the nonpolynomial case, the Tikhonov regularization can be applied to guarantee the weak regularity while not sacrificing the generalization capability. In Part II, however, we reveal a different aspect of the feasibility of ELM: there also exists some activation functions, which makes the corresponding ELM degrade the generalization capability. The obtained results underlie the feasibility and efficiency of ELM-like systems, and yield various generalizations and improvements of the systems as well.

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

NASA Astrophysics Data System (ADS)

Zhang, Ying-Zhi; Liu, Jin-Tong; Shen, Gui-Xiang; Long, Zhe; Sun, Shu-Guang

2017-07-01

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

"Your Model Is Predictive-- but Is It Useful?" Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation

ERIC Educational Resources Information Center

González-Brenes, José P.; Huang, Yun

2015-01-01

Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

Two-qubit quantum cloning machine and quantum correlation broadcasting

NASA Astrophysics Data System (ADS)

Kheirollahi, Azam; Mohammadi, Hamidreza; Akhtarshenas, Seyed Javad

2016-11-01

Due to the axioms of quantum mechanics, perfect cloning of an unknown quantum state is impossible. But since imperfect cloning is still possible, a question arises: "Is there an optimal quantum cloning machine?" Buzek and Hillery answered this question and constructed their famous B-H quantum cloning machine. The B-H machine clones the state of an arbitrary single qubit in an optimal manner and hence it is universal. Generalizing this machine for a two-qubit system is straightforward, but during this procedure, except for product states, this machine loses its universality and becomes a state-dependent cloning machine. In this paper, we propose some classes of optimal universal local quantum state cloners for a particular class of two-qubit systems, more precisely, for a class of states with known Schmidt basis. We then extend our machine to the case that the Schmidt basis of the input state is deviated from the local computational basis of the machine. We show that more local quantum coherence existing in the input state corresponds to less fidelity between the input and output states. Also we present two classes of a state-dependent local quantum copying machine. Furthermore, we investigate local broadcasting of two aspects of quantum correlations, i.e., quantum entanglement and quantum discord, defined, respectively, within the entanglement-separability paradigm and from an information-theoretic perspective. The results show that although quantum correlation is, in general, very fragile during the broadcasting procedure, quantum discord is broadcasted more robustly than quantum entanglement.

A Grammar Library for Information Structure

ERIC Educational Resources Information Center

Song, Sanghoun

2014-01-01

This dissertation makes substantial contributions to both the theoretical and computational treatment of information structure, with an eye toward creating natural language processing applications such as multilingual machine translation systems. The aim of the present dissertation is to create a grammar library of information structure for the…

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

An assessment of support vector machines for land cover classification

USGS Publications Warehouse

Huang, C.; Davis, L.S.; Townshend, J.R.G.

2002-01-01

The support vector machine (SVM) is a group of theoretically superior machine learning algorithms. It was found competitive with the best available machine learning algorithms in classifying high-dimensional data sets. This paper gives an introduction to the theoretical development of the SVM and an experimental evaluation of its accuracy, stability and training speed in deriving land cover classifications from satellite images. The SVM was compared to three other popular classifiers, including the maximum likelihood classifier (MLC), neural network classifiers (NNC) and decision tree classifiers (DTC). The impacts of kernel configuration on the performance of the SVM and of the selection of training data and input variables on the four classifiers were also evaluated in this experiment.

Configurable software for satellite graphics

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

Hartzman, P D

An important goal in interactive computer graphics is to provide users with both quick system responses for basic graphics functions and enough computing power for complex calculations. One solution is to have a distributed graphics system in which a minicomputer and a powerful large computer share the work. The most versatile type of distributed system is an intelligent satellite system in which the minicomputer is programmable by the application user and can do most of the work while the large remote machine is used for difficult computations. At New York University, the hardware was configured from available equipment. The levelmore » of system intelligence resulted almost completely from software development. Unlike previous work with intelligent satellites, the resulting system had system control centered in the satellite. It also had the ability to reconfigure software during realtime operation. The design of the system was done at a very high level using set theoretic language. The specification clearly illustrated processor boundaries and interfaces. The high-level specification also produced a compact, machine-independent virtual graphics data structure for picture representation. The software was written in a systems implementation language; thus, only one set of programs was needed for both machines. A user can program both machines in a single language. Tests of the system with an application program indicate that is has very high potential. A major result of this work is the demonstration that a gigantic investment in new hardware is not necessary for computing facilities interested in graphics.« less

Special-purpose computing for dense stellar systems

NASA Astrophysics Data System (ADS)

Makino, Junichiro

2007-08-01

I'll describe the current status of the GRAPE-DR project. The GRAPE-DR is the next-generation hardware for N-body simulation. Unlike the previous GRAPE hardwares, it is programmable SIMD machine with a large number of simple processors integrated into a single chip. The GRAPE-DR chip consists of 512 simple processors and operates at the clock speed of 500 MHz, delivering the theoretical peak speed of 512/226 Gflops (single/double precision). As of August 2006, the first prototype board with the sample chip successfully passed the test we prepared. The full GRAPE-DR system will consist of 4096 chips, reaching the theoretical peak speed of 2 Pflops.

Introducing systems change in the schools: the case of school luncheons and vending machines.

PubMed

Suarez-Balcazar, Yolanda; Redmond, Ladonna; Kouba, Joanne; Hellwig, Maureen; Davis, Rochelle; Martinez, Louise I; Jones, Lara

2007-06-01

A major public health crisis facing America's society is the increase in child and youth obesity, which has seen a fourfold increase in the last four decades. Major concerns include what children eat for school lunch and what other foods are available in schools. This paper illustrates efforts towards systems change in the luncheon program and food vending machines in the Chicago Public Schools. We discuss the different factors that lead to such changes using the framework of the social ecological model and the soft systems methodology, and we analyze how the resulting innovation was implemented and evaluated. First, we present a theoretical perspective to explain factors that influence children's eating patterns from a systems approach. Second, we discuss the antecedent factors that lead to systems change. Finally, we examine challenges to systems change, such as resistance to change, different stakeholder priorities, lack of resources, institutional bureaucracy, and unrealistic funder expectations.

Nonlinear Control of the Doubly Fed Induction Motor with Copper Losses Minimization for Electrical Vehicle

NASA Astrophysics Data System (ADS)

Drid, S.; Nait-Said, M.-S.; Tadjine, M.; Makouf, A.

2008-06-01

There is an increasing interest in electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved propulsion system for electric vehicles applications with minimal power losses. This paper deals with the high efficient vector control for the reduction of copper losses of the doubly fed motor. Firstly, the feedback linearization control based on Lyapunov approach is employed to design the underlying controller achieving the double fluxes orientation. The fluxes controllers are designed independently of the speed. The speed controller is designed using the Lyapunov method especially employed to the unknown load torques. The global asymptotic stability of the overall system is theoretically proven. Secondly, a new Torque Copper Losses Factor is proposed to deal with the problem of the machine copper losses. Its main function is to optimize the torque in keeping the machine saturation at an acceptable level. This leads to a reduction in machine currents and therefore their accompanied copper losses guaranteeing improved machine efficiency. The simulation results in comparative presentation confirm largely the effectiveness of the proposed DFIM control with a very interesting energy saving contribution.

Data Mining in Earth System Science (DMESS 2011)

Treesearch

Forrest M. Hoffman; J. Walter Larson; Richard Tran Mills; Bhorn-Gustaf Brooks; Auroop R. Ganguly; William Hargrove; et al

2011-01-01

From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques—such as cluster analysis, singular value decomposition, block entropy, Fourier and...

Machine Translation in Post-Contemporary Era

ERIC Educational Resources Information Center

Lin, Grace Hui Chin

2010-01-01

This article focusing on translating techniques via personal computer or laptop reports updated artificial intelligence progresses before 2010. Based on interpretations and information for field of MT [Machine Translation] by Yorick Wilks' book, "Machine Translation, Its scope and limits," this paper displays understandable theoretical frameworks…

Chaos and Order in Weakly Coupled Systems of Nonlinear Oscillators

NASA Astrophysics Data System (ADS)

Bruhn, B.

1987-01-01

We consider in this paper perturbations of two degree of freedom Hamiltonian systems which contain periodic and heteroclinic orbits. The Melnikov-Keener condition is used to proof the existence of horseshoes in the dynamics. The same condition is applied to prove a high degree of order in the motion of the swinging Atwood's machine. For some selected parameter values the theoretical predictions are checked by numerical calculations.

Multi-Stage Convex Relaxation Methods for Machine Learning

DTIC Science & Technology

2013-03-01

Many problems in machine learning can be naturally formulated as non-convex optimization problems. However, such direct nonconvex formulations have...original nonconvex formulation. We will develop theoretical properties of this method and algorithmic consequences. Related convex and nonconvex machine learning methods will also be investigated.

Method of Optimizing the Construction of Machining, Assembly and Control Devices

NASA Astrophysics Data System (ADS)

Iordache, D. M.; Costea, A.; Niţu, E. L.; Rizea, A. D.; Babă, A.

2017-10-01

Industry dynamics, driven by economic and social requirements, must generate more interest in technological optimization, capable of ensuring a steady development of advanced technical means to equip machining processes. For these reasons, the development of tools, devices, work equipment and control, as well as the modernization of machine tools, is the certain solution to modernize production systems that require considerable time and effort. This type of approach is also related to our theoretical, experimental and industrial applications of recent years, presented in this paper, which have as main objectives the elaboration and use of mathematical models, new calculation methods, optimization algorithms, new processing and control methods, as well as some structures for the construction and configuration of technological equipment with a high level of performance and substantially reduced costs..

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

Electrical machines with superconducting windings. Part 3: Homopolar dc machines

NASA Astrophysics Data System (ADS)

Kullman, D.; Henninger, P.

1981-01-01

The losses in rotating liquid metal contacts and the problems in including liquid metals were theoretically and experimentally studied. These machines are shown realiable. For electric ship propulsion, they are a more efficient method of power transmission than mechanical gearboxes. However, weight reduction as compared to mechanical gearboxes can hardly be achieved with machines fully shielded by magnetic iron.

Design and analysis of a sub-aperture scanning machine for the transmittance measurements of large-aperture optical system

NASA Astrophysics Data System (ADS)

He, Yingwei; Li, Ping; Feng, Guojin; Cheng, Li; Wang, Yu; Wu, Houping; Liu, Zilong; Zheng, Chundi; Sha, Dingguo

2010-11-01

For measuring large-aperture optical system transmittance, a novel sub-aperture scanning machine with double-rotating arms (SSMDA) was designed to obtain sub-aperture beam spot. Optical system full-aperture transmittance measurements can be achieved by applying sub-aperture beam spot scanning technology. The mathematical model of the SSMDA based on a homogeneous coordinate transformation matrix is established to develop a detailed methodology for analyzing the beam spot scanning errors. The error analysis methodology considers two fundamental sources of scanning errors, namely (1) the length systematic errors and (2) the rotational systematic errors. As the systematic errors of the parameters are given beforehand, computational results of scanning errors are between -0.007~0.028mm while scanning radius is not lager than 400.000mm. The results offer theoretical and data basis to the research on transmission characteristics of large optical system.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Experiments on a non-smoothly-forced oscillator

NASA Astrophysics Data System (ADS)

Virgin, Lawrence N.; George, Christopher; Kini, Ashwath

2015-12-01

This paper describes some typical behavior encountered in the response of a harmonically-excited mechanical system in which a severe nonlinearity occurs due to an impact. Although such systems have received considerable recent attention (most of it from a theoretical viewpoint), the system scrutinized in this paper also involves a discrete input of energy at the impact condition. That is, it is kicked when contact is made. One of the motivations for this work is related to a classic pinball machine in which a ball striking a bumper experiences a sudden impulse, introducing additional unpredictability to the motion of the ball. A one-dimensional analog of a pinball machine was the subject of a detailed mathematical study in Pring and Budd (2011), and the current paper details behavior obtained from a mechanical experiment and describes dynamics not observed in a conventional (passive) impact oscillator.

Interlocking Mechanism between Molecular Gears Attached to Surfaces.

PubMed

Zhao, Rundong; Zhao, Yan-Ling; Qi, Fei; Hermann, Klaus E; Zhang, Rui-Qin; Van Hove, Michel A

2018-03-27

While molecular machines play an increasingly significant role in nanoscience research and applications, there remains a shortage of investigations and understanding of the molecular gear (cogwheel), which is an indispensable and fundamental component to drive a larger correlated molecular machine system. Employing ab initio calculations, we investigate model systems consisting of molecules adsorbed on metal or graphene surfaces, ranging from very simple triple-arm gears such as PF 3 and NH 3 to larger multiarm gears based on carbon rings. We explore in detail the transmission of slow rotational motion from one gear to the next by these relatively simple molecules, so as to isolate and reveal the mechanisms of the relevant intermolecular interactions. Several characteristics of molecular gears are discussed, in particular the flexibility of the arms and the slipping and skipping between interlocking arms of adjacent gears, which differ from familiar macroscopic rigid gears. The underlying theoretical concepts suggest strongly that other analogous structures may also exhibit similar behavior which may inspire future exploration in designing large correlated molecular machines.

Static Measurements on HTS Coils of Fully Superconducting AC Electric Machines for Aircraft Electric Propulsion System

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.; Hunker, Keith R.; Hartwig, Jason; Brown, Gerald V.

2017-01-01

The NASA Glenn Research Center (GRC) has been developing the high efficiency and high-power density superconducting (SC) electric machines in full support of electrified aircraft propulsion (EAP) systems for a future electric aircraft. A SC coil test rig has been designed and built to perform static and AC measurements on BSCCO, (RE)BCO, and YBCO high temperature superconducting (HTS) wire and coils at liquid nitrogen (LN2) temperature. In this paper, DC measurements on five SC coil configurations of various geometry in zero external magnetic field are measured to develop good measurement technique and to determine the critical current (Ic) and the sharpness (n value) of the super-to-normal transition. Also, standard procedures for coil design, fabrication, coil mounting, micro-volt measurement, cryogenic testing, current control, and data acquisition technique were established. Experimentally measured critical currents are compared with theoretical predicted values based on an electric-field criterion (Ec). Data here are essential to quantify the SC electric machine operation limits where the SC begins to exhibit non-zero resistance. All test data will be utilized to assess the feasibility of using HTS coils for the fully superconducting AC electric machine development for an aircraft electric propulsion system.

"Machine" consciousness and "artificial" thought: an operational architectonics model guided approach.

PubMed

Fingelkurts, Andrew A; Fingelkurts, Alexander A; Neves, Carlos F H

2012-01-05

Instead of using low-level neurophysiology mimicking and exploratory programming methods commonly used in the machine consciousness field, the hierarchical operational architectonics (OA) framework of brain and mind functioning proposes an alternative conceptual-theoretical framework as a new direction in the area of model-driven machine (robot) consciousness engineering. The unified brain-mind theoretical OA model explicitly captures (though in an informal way) the basic essence of brain functional architecture, which indeed constitutes a theory of consciousness. The OA describes the neurophysiological basis of the phenomenal level of brain organization. In this context the problem of producing man-made "machine" consciousness and "artificial" thought is a matter of duplicating all levels of the operational architectonics hierarchy (with its inherent rules and mechanisms) found in the brain electromagnetic field. We hope that the conceptual-theoretical framework described in this paper will stimulate the interest of mathematicians and/or computer scientists to abstract and formalize principles of hierarchy of brain operations which are the building blocks for phenomenal consciousness and thought. Copyright © 2010 Elsevier B.V. All rights reserved.

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

Sciarrino, Fabio; Dipartimento di Fisica and Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia, Universita 'La Sapienza', Rome 00185; De Martini, Francesco

The optimal phase-covariant quantum cloning machine (PQCM) broadcasts the information associated to an input qubit into a multiqubit system, exploiting a partial a priori knowledge of the input state. This additional a priori information leads to a higher fidelity than for the universal cloning. The present article first analyzes different innovative schemes to implement the 1{yields}3 PQCM. The method is then generalized to any 1{yields}M machine for an odd value of M by a theoretical approach based on the general angular momentum formalism. Finally different experimental schemes based either on linear or nonlinear methods and valid for single photon polarizationmore » encoded qubits are discussed.« less

70% efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence.

PubMed

Schneider, Thomas D

2010-10-01

The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is [Formula in text] joules per bit (kB is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln 2=0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal.

70% efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence

PubMed Central

Schneider, Thomas D.

2010-01-01

The relationship between information and energy is key to understanding biological systems. We can display the information in DNA sequences specifically bound by proteins by using sequence logos, and we can measure the corresponding binding energy. These can be compared by noting that one of the forms of the second law of thermodynamics defines the minimum energy dissipation required to gain one bit of information. Under the isothermal conditions that molecular machines function this is joules per bit ( is Boltzmann's constant and T is the absolute temperature). Then an efficiency of binding can be computed by dividing the information in a logo by the free energy of binding after it has been converted to bits. The isothermal efficiencies of not only genetic control systems, but also visual pigments are near 70%. From information and coding theory, the theoretical efficiency limit for bistate molecular machines is ln 2 = 0.6931. Evolutionary convergence to maximum efficiency is limited by the constraint that molecular states must be distinct from each other. The result indicates that natural molecular machines operate close to their information processing maximum (the channel capacity), and implies that nanotechnology can attain this goal. PMID:20562221

Using Machine Learning in Adversarial Environments.

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

Warren Leon Davis

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

A proposal of an architecture for the coordination level of intelligent machines

NASA Technical Reports Server (NTRS)

Beard, Randall; Farah, Jeff; Lima, Pedro

1993-01-01

The issue of obtaining a practical, structured, and detailed description of an architecture for the Coordination Level of Center for Intelligent Robotic Systems for Sapce Exploration (CIRSSE) Testbed Intelligent Controller is addressed. Previous theoretical and implementation works were the departure point for the discussion. The document is organized as follows: after this introductory section, section 2 summarizes the overall view of the Intelligent Machine (IM) as a control system, proposing a performance measure on which to base its design. Section 3 addresses with some detail implementation issues. An hierarchic petri-net with feedback-based learning capabilities is proposed. Finally, section 4 is an attempt to address the feedback problem. Feedback is used for two functions: error recovery and reinforcement learning of the correct translations for the petri-net transitions.

The Time Machine in Our Mind

ERIC Educational Resources Information Center

Stocker, Kurt

2012-01-01

This article provides the first comprehensive conceptual account for the imagistic mental machinery that allows us to travel through time--for the time machine in our mind. It is argued that language reveals this imagistic machine and how we use it. Findings from a range of cognitive fields are theoretically unified and a recent proposal about…

Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

PubMed Central

2014-01-01

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

Application of a movable active vibration control system on a floating raft

NASA Astrophysics Data System (ADS)

Wang, Zhen; Mak, Cheuk Ming

2018-02-01

This paper presents a theoretical study of an inertial actuator connected to an accelerometer by a local feedback loop for active vibration control on a floating raft. On the criterion of the minimum power transmission from the vibratory machines to the flexible foundation in the floating raft, the best mounting positions for the inertial actuator on the intermediate mass of the floating raft are investigated. Simulation results indicate that the best mounting positions for the inertial actuator vary with frequency. To control time-varying excitations of vibratory machines on a floating raft effectively, an automatic control system based on real-time measurement of a cost function and automatically searching the best mounting position of the inertial actuator is proposed. To the best of our knowledge, it is the first time that an automatic control system is proposed to move an actuator automatically for controlling a time-varying excitation.

Efficient machining of ultra precise steel moulds with freeform surfaces

NASA Astrophysics Data System (ADS)

Bulla, B.; Robertson, D. J.; Dambon, O.; Klocke, F.

2013-09-01

Ultra precision diamond turning of hardened steel to produce optical quality surfaces can be realized by applying an ultrasonic assisted process. With this technology optical moulds used typically for injection moulding can be machined directly from steel without the requirement to overcoat the mould with a diamond machinable material such as Nickel Phosphor. This has both the advantage of increasing the mould tool lifetime and also reducing manufacture costs by dispensing with the relatively expensive plating process. This publication will present results we have obtained for generating free form moulds in hardened steel by means of ultrasonic assisted diamond turning with a vibration frequency of 80 kHz. To provide a baseline with which to characterize the system performance we perform plane cutting experiments on different steel alloys with different compositions. The baseline machining results provides us information on the surface roughness and on tool wear caused during machining and we relate these to material composition. Moving on to freeform surfaces, we will present a theoretical background to define the machine program parameters for generating free forms by applying slow slide servo machining techniques. A solution for optimal part generation is introduced which forms the basis for the freeform machining experiments. The entire process chain, from the raw material through to ultra precision machining is presented, with emphasis on maintaining surface alignment when moving a component from CNC pre-machining to final machining using ultrasonic assisted diamond turning. The free form moulds are qualified on the basis of the surface roughness measurements and a form error map comparing the machined surface with the originally defined surface. These experiments demonstrate the feasibility of efficient free form machining applying ultrasonic assisted diamond turning of hardened steel.

Bellco Formula Domus Home Care System.

PubMed

Trewin, Elizabeth

2004-01-01

There are certain characteristics in a dialysis machine that would be desirable for use in home and limited care environments. These features relate to safety, ease of use, consideration of physical space, and reliability. The Bellco Formula Domus Home Care System was designed to meet all these requirements. Bellco's philosophy of patient treatment centers on global biocompatibility. This is evident in the design of the Formula Domus Home Care System. It has the smallest hydraulic fluid pathway of any dialysis machine on the market. Formula is capable of preparing ultrapure dialysate. The ultrafiltration measurement mechanism, the patented Coriolis flow meter, measures the mass of the dialysate, not the volume. For this reason it is the only dialysis machine that detects actual backfiltration, not just the theoretical possibility of it based on transmembrane pressure. The Coriolis flow meter also ensures that dialysate flow is a true single pass. The operator interface is a single window operating control. It is possible to select up to 14 different languages. There is an online help key to assist patients with troubleshooting. Programmable start-up and shutdown times save time for the patient. Formula is the only dialysis machine to offer a backup battery feature. Formula is capable of communicating with any software available. The focus on global biocompatibility ensures the best quality dialysis treatments for a population of patients who will likely remain on dialysis for a longer period of time than conventional dialysis patients.

Implementing finite state machines in a computer-based teaching system

NASA Astrophysics Data System (ADS)

Hacker, Charles H.; Sitte, Renate

1999-09-01

Finite State Machines (FSM) are models for functions commonly implemented in digital circuits such as timers, remote controls, and vending machines. Teaching FSM is core in the curriculum of many university digital electronic or discrete mathematics subjects. Students often have difficulties grasping the theoretical concepts in the design and analysis of FSM. This has prompted the author to develop an MS-WindowsTM compatible software, WinState, that provides a tutorial style teaching aid for understanding the mechanisms of FSM. The animated computer screen is ideal for visually conveying the required design and analysis procedures. WinState complements other software for combinatorial logic previously developed by the author, and enhances the existing teaching package by adding sequential logic circuits. WinState enables the construction of a students own FSM, which can be simulated, to test the design for functionality and possible errors.

Temperature based Restricted Boltzmann Machines

NASA Astrophysics Data System (ADS)

Li, Guoqi; Deng, Lei; Xu, Yi; Wen, Changyun; Wang, Wei; Pei, Jing; Shi, Luping

2016-01-01

Restricted Boltzmann machines (RBMs), which apply graphical models to learning probability distribution over a set of inputs, have attracted much attention recently since being proposed as building blocks of multi-layer learning systems called deep belief networks (DBNs). Note that temperature is a key factor of the Boltzmann distribution that RBMs originate from. However, none of existing schemes have considered the impact of temperature in the graphical model of DBNs. In this work, we propose temperature based restricted Boltzmann machines (TRBMs) which reveals that temperature is an essential parameter controlling the selectivity of the firing neurons in the hidden layers. We theoretically prove that the effect of temperature can be adjusted by setting the parameter of the sharpness of the logistic function in the proposed TRBMs. The performance of RBMs can be improved by adjusting the temperature parameter of TRBMs. This work provides a comprehensive insights into the deep belief networks and deep learning architectures from a physical point of view.

[Design of Complex Cavity Structure in Air Route System of Automated Peritoneal Dialysis Machine].

PubMed

Quan, Xiaoliang

2017-07-30

This paper introduced problems about Automated Peritoneal Dialysis machine(APD) that the lack of technical issues such as the structural design of the complex cavities. To study the flow characteristics of this special structure, the application of ANSYS CFX software is used with k-ε turbulence model as the theoretical basis of fluid mechanics. The numerical simulation of flow field simulation result in the internal model can be gotten after the complex structure model is imported into ANSYS CFX module. Then, it will present the distribution of complex cavities inside the flow field and the flow characteristics parameter, which will provide an important reference design for APD design.

Department of Cybernetic Acoustics

NASA Astrophysics Data System (ADS)

The development of the theory, instrumentation and applications of methods and systems for the measurement, analysis, processing and synthesis of acoustic signals within the audio frequency range, particularly of the speech signal and the vibro-acoustic signal emitted by technical and industrial equipments treated as noise and vibration sources was discussed. The research work, both theoretical and experimental, aims at applications in various branches of science, and medicine, such as: acoustical diagnostics and phoniatric rehabilitation of pathological and postoperative states of the speech organ; bilateral ""man-machine'' speech communication based on the analysis, recognition and synthesis of the speech signal; vibro-acoustical diagnostics and continuous monitoring of the state of machines, technical equipments and technological processes.

Investigation the gas film in micro scale induced error on the performance of the aerostatic spindle in ultra-precision machining

NASA Astrophysics Data System (ADS)

Chen, Dongju; Huo, Chen; Cui, Xianxian; Pan, Ri; Fan, Jinwei; An, Chenhui

2018-05-01

The objective of this work is to study the influence of error induced by gas film in micro-scale on the static and dynamic behavior of a shaft supported by the aerostatic bearings. The static and dynamic balance models of the aerostatic bearing are presented by the calculated stiffness and damping in micro scale. The static simulation shows that the deformation of aerostatic spindle system in micro scale is decreased. For the dynamic behavior, both the stiffness and damping in axial and radial directions are increased in micro scale. The experiments of the stiffness and rotation error of the spindle show that the deflection of the shaft resulting from the calculating parameters in the micro scale is very close to the deviation of the spindle system. The frequency information in transient analysis is similar to the actual test, and they are also higher than the results from the traditional case without considering micro factor. Therefore, it can be concluded that the value considering micro factor is closer to the actual work case of the aerostatic spindle system. These can provide theoretical basis for the design and machining process of machine tools.

Coherent Ising machines—optical neural networks operating at the quantum limit

NASA Astrophysics Data System (ADS)

Yamamoto, Yoshihisa; Aihara, Kazuyuki; Leleu, Timothee; Kawarabayashi, Ken-ichi; Kako, Satoshi; Fejer, Martin; Inoue, Kyo; Takesue, Hiroki

2017-12-01

In this article, we will introduce the basic concept and the quantum feature of a novel computing system, coherent Ising machines, and describe their theoretical and experimental performance. We start with the discussion how to construct such physical devices as the quantum analog of classical neuron and synapse, and end with the performance comparison against various classical neural networks implemented in CPU and supercomputers.

The Simplest Chronoscope V: A Theory of Dual Primary and Secondary Reaction Time Systems.

PubMed

Montare, Alberto

2016-12-01

Extending work by Montare, visual simple reaction time, choice reaction time, discriminative reaction time, and overall reaction time scores obtained from college students by the simplest chronoscope (a falling meterstick) method were significantly faster as well as significantly less variable than scores of the same individuals from electromechanical reaction timers (machine method). Results supported the existence of dual reaction time systems: an ancient primary reaction time system theoretically activating the V5 parietal area of the dorsal visual stream that evolved to process significantly faster sensory-motor reactions to sudden stimulations arising from environmental objects in motion, and a secondary reaction time system theoretically activating the V4 temporal area of the ventral visual stream that subsequently evolved to process significantly slower sensory-perceptual-motor reactions to sudden stimulations arising from motionless colored objects. © The Author(s) 2016.

Development of a systems theoretical procedure for evaluation of the work organization of the cockpit crew of a civil transport airplane

NASA Technical Reports Server (NTRS)

Fricke, M.; Vees, C.

1983-01-01

To achieve optimum design for the man machine interface with aircraft, a description of the interaction and work organization of the cockpit crew is needed. The development of system procedure to evaluate the work organization of pilots while structuring the work process is examined. Statistical data are needed to simulate sequences of pilot actions on the computer. Investigations of computer simulation and applicability for evaluation of crew concepts are discussed.

A New Approach to Geoengineering: Manna From Heaven

NASA Astrophysics Data System (ADS)

Ellery, Alex

2015-04-01

Geo-engineering, although controversial, has become an emerging factor in coping with climate change. Although most are terrestrial-based technologies, I focus on a space-based approach implemented through a solar shield system. I present several new elements that essentially render the high-cost criticism moot. Of special relevance are two seemingly unrelated technologies - the Resource Prospector Mission (RPM) to the Moon in 2018 that shall implement a technology demonstration of simple material resource extraction from lunar regolith, and the emergence of multi-material 3D printing technology that promises unprecedented robotic manufacturing capabilities. My research group has begun theoretical and experimentation work in developing the concept of a 3D printed electric motor system from lunar-type resources. The electric motor underlies every universal mechanical machine. Together with 3D printed electronics, I submit that this would enable self-replicating machines to be realised. A detailed exposition on how this may be achieved will be outlined. Such self-replicating machines could construct the spacecraft required to implement a solar shield and solar power satellites in large numbers from lunar resources with the same underlying technologies at extremely low cost.

Multiphase complete exchange on Paragon, SP2 and CS-2

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

The overhead of interprocessor communication is a major factor in limiting the performance of parallel computer systems. The complete exchange is the severest communication pattern in that it requires each processor to send a distinct message to every other processor. This pattern is at the heart of many important parallel applications. On hypercubes, multiphase complete exchange has been developed and shown to provide optimal performance over varying message sizes. Most commercial multicomputer systems do not have a hypercube interconnect. However, they use special purpose hardware and dedicated communication processors to achieve very high performance communication and can be made to emulate the hypercube quite well. Multiphase complete exchange has been implemented on three contemporary parallel architectures: the Intel Paragon, IBM SP2 and Meiko CS-2. The essential features of these machines are described and their basic interprocessor communication overheads are discussed. The performance of multiphase complete exchange is evaluated on each machine. It is shown that the theoretical ideas developed for hypercubes are also applicable in practice to these machines and that multiphase complete exchange can lead to major savings in execution time over traditional solutions.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Myths and legends in learning classification rules

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

A discussion is presented of machine learning theory on empirically learning classification rules. Six myths are proposed in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, universal learning algorithms, and interactive learning. Some of the problems raised are also addressed from a Bayesian perspective. Questions are suggested that machine learning researchers should be addressing both theoretically and experimentally.

Cellular automata in photonic cavity arrays.

PubMed

Li, Jing; Liew, T C H

2016-10-31

We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.

A machine learning approach to graph-theoretical cluster expansions of the energy of adsorbate layers

NASA Astrophysics Data System (ADS)

Vignola, Emanuele; Steinmann, Stephan N.; Vandegehuchte, Bart D.; Curulla, Daniel; Stamatakis, Michail; Sautet, Philippe

2017-08-01

The accurate description of the energy of adsorbate layers is crucial for the understanding of chemistry at interfaces. For heterogeneous catalysis, not only the interaction of the adsorbate with the surface but also the adsorbate-adsorbate lateral interactions significantly affect the activation energies of reactions. Modeling the interactions of the adsorbates with the catalyst surface and with each other can be efficiently achieved in the cluster expansion Hamiltonian formalism, which has recently been implemented in a graph-theoretical kinetic Monte Carlo (kMC) scheme to describe multi-dentate species. Automating the development of the cluster expansion Hamiltonians for catalytic systems is challenging and requires the mapping of adsorbate configurations for extended adsorbates onto a graphical lattice. The current work adopts machine learning methods to reach this goal. Clusters are automatically detected based on formalized, but intuitive chemical concepts. The corresponding energy coefficients for the cluster expansion are calculated by an inversion scheme. The potential of this method is demonstrated for the example of ethylene adsorption on Pd(111), for which we propose several expansions, depending on the graphical lattice. It turns out that for this system, the best description is obtained as a combination of single molecule patterns and a few coupling terms accounting for lateral interactions.

Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

PubMed

Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C

2015-01-01

Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Trends in extreme learning machines: a review.

PubMed

Huang, Gao; Huang, Guang-Bin; Song, Shiji; You, Keyou

2015-01-01

Extreme learning machine (ELM) has gained increasing interest from various research fields recently. In this review, we aim to report the current state of the theoretical research and practical advances on this subject. We first give an overview of ELM from the theoretical perspective, including the interpolation theory, universal approximation capability, and generalization ability. Then we focus on the various improvements made to ELM which further improve its stability, sparsity and accuracy under general or specific conditions. Apart from classification and regression, ELM has recently been extended for clustering, feature selection, representational learning and many other learning tasks. These newly emerging algorithms greatly expand the applications of ELM. From implementation aspect, hardware implementation and parallel computation techniques have substantially sped up the training of ELM, making it feasible for big data processing and real-time reasoning. Due to its remarkable efficiency, simplicity, and impressive generalization performance, ELM have been applied in a variety of domains, such as biomedical engineering, computer vision, system identification, and control and robotics. In this review, we try to provide a comprehensive view of these advances in ELM together with its future perspectives.

Underestimating extreme events in power-law behavior due to machine-dependent cutoffs

NASA Astrophysics Data System (ADS)

Radicchi, Filippo

2014-11-01

Power-law distributions are typical macroscopic features occurring in almost all complex systems observable in nature. As a result, researchers in quantitative analyses must often generate random synthetic variates obeying power-law distributions. The task is usually performed through standard methods that map uniform random variates into the desired probability space. Whereas all these algorithms are theoretically solid, in this paper we show that they are subject to severe machine-dependent limitations. As a result, two dramatic consequences arise: (i) the sampling in the tail of the distribution is not random but deterministic; (ii) the moments of the sample distribution, which are theoretically expected to diverge as functions of the sample sizes, converge instead to finite values. We provide quantitative indications for the range of distribution parameters that can be safely handled by standard libraries used in computational analyses. Whereas our findings indicate possible reinterpretations of numerical results obtained through flawed sampling methodologies, they also pave the way for the search for a concrete solution to this central issue shared by all quantitative sciences dealing with complexity.

Design and verification of a novel hollow vibrating module for laser machining.

PubMed

Wang, Zhaozhao; Jang, Seungbong; Kim, EunHee; Jeon, Yongho; Lee, Soo-Hun; Lee, Moon G

2015-04-01

If a vibration module is added on laser machining system, the quality of surface finish and aspect ratio on metals can be significantly enhanced. In this study, a single mobility model of vibrating laser along the path of laser beam was put forward. In order to realize the desired unidirectional motion, a resonance type vibration module with optical lens was designed and manufactured. This cylindrical module was composed of curved-beam flexure elements. The cylindrical coordinate system was established to describe the relationship of a curved-beam flexure element's motion and deformation. In addition, the stiffness matrix of the curved-beam element was obtained. Finite element method and dynamical modeling were provided to analyze the resonance frequency and the displacement of the motion. The feasibility of the design was demonstrated with the help of experiments on frequency response. Experimental results show good agreement with theoretical analysis and simulation predictions.

Neural-network quantum state tomography

NASA Astrophysics Data System (ADS)

Torlai, Giacomo; Mazzola, Guglielmo; Carrasquilla, Juan; Troyer, Matthias; Melko, Roger; Carleo, Giuseppe

2018-05-01

The experimental realization of increasingly complex synthetic quantum systems calls for the development of general theoretical methods to validate and fully exploit quantum resources. Quantum state tomography (QST) aims to reconstruct the full quantum state from simple measurements, and therefore provides a key tool to obtain reliable analytics1-3. However, exact brute-force approaches to QST place a high demand on computational resources, making them unfeasible for anything except small systems4,5. Here we show how machine learning techniques can be used to perform QST of highly entangled states with more than a hundred qubits, to a high degree of accuracy. We demonstrate that machine learning allows one to reconstruct traditionally challenging many-body quantities—such as the entanglement entropy—from simple, experimentally accessible measurements. This approach can benefit existing and future generations of devices ranging from quantum computers to ultracold-atom quantum simulators6-8.

Mutual information, neural networks and the renormalization group

NASA Astrophysics Data System (ADS)

Koch-Janusz, Maciej; Ringel, Zohar

2018-06-01

Physical systems differing in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains `slow' degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine-learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowledge about the system. We introduce an artificial neural network based on a model-independent, information-theoretic characterization of a real-space RG procedure, which performs this task. We apply the algorithm to classical statistical physics problems in one and two dimensions. We demonstrate RG flow and extract the Ising critical exponent. Our results demonstrate that machine-learning techniques can extract abstract physical concepts and consequently become an integral part of theory- and model-building.

Practical research on the teaching of Optical Design

NASA Astrophysics Data System (ADS)

Fan, Changjiang; Ren, Zhijun; Ying, Chaofu; Peng, Baojin

2017-08-01

Optical design, together with applied optics, forms a complete system from basic theory to application theory, and it plays a very important role in professional education. In order to improve senior undergraduates' understanding of optical design, this course is divided into three parts: theoretical knowledge, software design and product processing. Through learning theoretical knowledge, students can master the aberration theory and the design principles of typical optical system. By using ZEMAX(an imaging design software), TRACEPRO(a lighting optical design software), SOLIDWORKS or PROE( mechanical design software), student can establish a complete model of optical system. Student can use carving machine located in lab or cooperative units to process the model. Through the above three parts, student can learn necessary practical knowledge and get improved in their learning and analysis abilities, thus they can also get enough practice to prompt their creative abilities, then they could gradually change from scientific theory learners to an Optics Engineers.

Myths and legends in learning classification rules

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

The operation of large computer-controlled manufacturing systems

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

Upton, D.M.

1988-01-01

This work examines methods for operation of large computer-controlled manufacturing systems, with more than 50 or so disparate CNC machines in congregation. The central theme is the development of a distributed control system, which requires minimal central supervision, and allows manufacturing system re-configuration without extensive control software re-writes. Provision is made for machines to learn from their experience and provide estimates of the time necessary to effect various tasks. Routing is opportunistic, with varying degrees of myopia depending on the prevailing situation. Necessary curtailments of opportunism are built in to the system, in order to provide a society of machinesmore » that operate in unison rather than in chaos. Negotiation and contention resolution are carried out using a UHF radio communications network, along with processing capability on both pallets and tools. Graceful and robust error recovery is facilitated by ensuring adequate pessimistic consideration of failure modes at each stage in the scheme. Theoretical models are developed and an examination is made of fundamental characteristics of auction-based scheduling methods.« less

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Analysis and design of asymmetrical reluctance machine

NASA Astrophysics Data System (ADS)

Harianto, Cahya A.

Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.

Equal-area criterion in power systems revisited

NASA Astrophysics Data System (ADS)

Sun, Yong; Ma, Jinpeng; Kurths, Jürgen; Zhan, Meng

2018-02-01

The classic equal-area criterion (EAC) is of key importance in power system analysis, and provides a powerful, pictorial and quantitative means of analysing transient stability (i.e. the system's ability to maintain stable operation when subjected to a large disturbance). Based on the traditional EAC, it is common sense in engineering that there is a critical cleaning time (CCT); namely, a power system is stable (unstable) if a fault is cleared before (after) this CCT. We regard this form of CCT as bipartite. In this paper, we revisit the EAC theory and, surprisingly, find different kinds of transient stability behaviour. Based on these analyses, we discover that the bipartite CCT is only one type among four major types, and, actually, the forms of CCT can be diversified. In particular, under some circumstances, a system may have no CCT or show a periodic CCT. Our theoretical analysis is verified by numerical simulations in a single-machine-infinite-bus system and also in multi-machine systems. Thus, our study provides a panoramic framework for diverse transient stability behaviour in power systems and also may have a significant impact on applications of multi-stability in various other systems, such as neuroscience, climatology or photonics.

Online learning control using adaptive critic designs with sparse kernel machines.

PubMed

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Mu-2 ranging

NASA Technical Reports Server (NTRS)

Martin, W. L.; Zygielbaum, A. I.

1977-01-01

The Mu-II Dual-Channel Sequential Ranging System designed as a model for future Deep Space Network ranging equipment is described. A list of design objectives is followed by a theoretical explanation of the digital demodulation techniques first employed in this machine. Hardware and software implementation are discussed, together with the details relating to the construction of the device. Two appendixes are included relating to the programming and operation of this equipment to yield the maximum scientific data.

MACHINE TRANSLATION RESEARCH DURING THE PAST TWO YEARS.

ERIC Educational Resources Information Center

LEHMANN, W.P.

THE AUTHOR RECOUNTS THE RISE IN IMPORTANCE OF MACHINE TRANSLATION, WHICH TOGETHER WITH LANGUAGE LEARNING AND TEACHING COMPRISE THE MAJOR FIELDS OF APPLIED LINGUISTICS. MUCH OF THE RECENT THEORETICAL WORK ON LANGUAGE DEALS WITH THE PROBLEM OF THE RELATIONSHIP BETWEEN THE SURFACE SYNTACTIC STRUCTURE OF LANGUAGE AND THE UNDERLYING STRUCTURE. THE…

Deformation of products cut on AWJ x-y tables and its suppression

NASA Astrophysics Data System (ADS)

Hlaváč, L. M.; Hlaváčová, I. M.; Plančár, Š.; Krenický, T.; Geryk, V.

2018-02-01

The aim of this study is namely investigation of the abrasive water jet (AWJ) cutting of column pieces on commercial x-y cutting machines with AWJ. The shape deformation in curved and/or stepped parts of cutting trajectories caused by both the trailback (declination angle) and the taper (inclination of cut walls) can be calculated from submitted analytical model. Some of the results were compared with data measured on samples cut on two types of commercial tables. The main motivation of this investigation is determination of the percentage difference between predicted and real distortion of cutting product, i.e. accuracy of prepared analytical model. Subsequently, the possibility of reduction of the distortion can be studied through implementation of the theoretical model into the control systems of the cutting machines with the system for cutting head tilting. Despite some limitations of the used AWJ machines the comparison of calculated dimensions with the real ones shows very good correlation of model and experimental data lying within the range of measurement uncertainty. Results on special device demonstrated that the shape deformation in curved parts of the cutting trajectory can be substantially reduced through tilting of the cutting head.

Analysis of machining accuracy during free form surface milling simulation for different milling strategies

NASA Astrophysics Data System (ADS)

Matras, A.; Kowalczyk, R.

2014-11-01

The analysis results of machining accuracy after the free form surface milling simulations (based on machining EN AW- 7075 alloys) for different machining strategies (Level Z, Radial, Square, Circular) are presented in the work. Particular milling simulations were performed using CAD/CAM Esprit software. The accuracy of obtained allowance is defined as a difference between the theoretical surface of work piece element (the surface designed in CAD software) and the machined surface after a milling simulation. The difference between two surfaces describes a value of roughness, which is as the result of tool shape mapping on the machined surface. Accuracy of the left allowance notifies in direct way a surface quality after the finish machining. Described methodology of usage CAD/CAM software can to let improve a time design of machining process for a free form surface milling by a 5-axis CNC milling machine with omitting to perform the item on a milling machine in order to measure the machining accuracy for the selected strategies and cutting data.

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

NASA Astrophysics Data System (ADS)

Szymański, Zygmunt

2015-03-01

In the paper present's an analysis of suitableness an application of compact and hybrid drive system in hoisting machine. In the paper presented the review of constructional solutions of hoisting machines drive system, driving with AC and DC motor. In the paper presented conception of modern, energy sparing hoisting machine supply system, composed with compact motor, an supplied with transistor or thyristor converter supply system, and intelligent control system composed with multilevel microprocessor controller. In the paper present's also analysis of suitableness application an selected method of artificial intelligent in hoisting machine control system, automation system, and modern diagnostic system. In the paper one limited to analysis of: fuzzy logic method, genetic algorithms method, and modern neural net II and III generation. That method enables realization of complex control algorithms of hosting machine with insurance of energy sparing exploitation conditions, monitoring of exploitation parameters, and prediction diagnostic of hoisting machine technical state, minimization a number of failure states. In the paper present's a conception of control and diagnostic system of the hoisting machine based on fuzzy logic neural set control. In the chapter presented also a selected control algorithms and results of computer simulations realized for particular mathematical models of hoisting machine. Results of theoretical investigation were partly verified in laboratory and industrial experiments. Przedstawiono analizę celowości wprowadzania, napędów zintegrowanych oraz napędów hybrydowych, do układów napędowych maszyn wyciągowych. Zamieszczono przegląd rozwiązań konstrukcyjnych wybranych hybrydowych oraz zintegrowanych napędów maszyn wyciągowych z silnikami DC i AC. Opisano koncepcję nowoczesnego, energooszczędnego układu zasilania górniczych maszyny wyciągowej, złożonego z silnika zintegrowanego, (tranzystorowego lub tyrystorowego) zasilacza przekształtnikowego, oraz inteligentnego obwodu sterowania zbudowanego na wielopoziomowych sterownikach mikroprocesorowych. Przedstawiono analizę możliwości zastosowania wybranych metod sztucznej inteligencji w układach sterowania, automatyki oraz diagnostyki maszyn wyciągowych. W referacie ograniczono się do analizy metod sterowania rozmytego, metod algorytmów genetycznych oraz nowoczesnych sieci neuronowych II oraz III generacji. Metody te zapewniają realizację złożonych algorytmów sterowania maszyną wyciągową z zapewnieniem energooszczędnych warunków eksploatacyjnych, monitoringu parametrów eksploatacyjnych oraz predykcyjną diagnostykę stanu technicznego maszyny wyciągowej, minimalizującą liczbę stanów awaryjnych. Przedstawiono koncepcję układu sterowania i diagnostyki maszyny bazującej na metodzie: fuzzy-logic neuro set control system (sterowanie rozmyte w sieciach neuronowych). Przedstawiono wybrane algorytmy sterowania oraz wyniki analiz komputerowych wybranych modeli matematycznych maszyny wyciągowej. Wyniki rozważań teoretycznych zostały częściowo sprawdzone w warunkach laboratoryjnych oraz przemysłowych.

Advances in molecular dynamics simulation of ultra-precision machining of hard and brittle materials

NASA Astrophysics Data System (ADS)

Guo, Xiaoguang; Li, Qiang; Liu, Tao; Kang, Renke; Jin, Zhuji; Guo, Dongming

2017-03-01

Hard and brittle materials, such as silicon, SiC, and optical glasses, are widely used in aerospace, military, integrated circuit, and other fields because of their excellent physical and chemical properties. However, these materials display poor machinability because of their hard and brittle properties. Damages such as surface micro-crack and subsurface damage often occur during machining of hard and brittle materials. Ultra-precision machining is widely used in processing hard and brittle materials to obtain nanoscale machining quality. However, the theoretical mechanism underlying this method remains unclear. This paper provides a review of present research on the molecular dynamics simulation of ultra-precision machining of hard and brittle materials. The future trends in this field are also discussed.

Method of surface error visualization using laser 3D projection technology

NASA Astrophysics Data System (ADS)

Guo, Lili; Li, Lijuan; Lin, Xuezhu

2017-10-01

In the process of manufacturing large components, such as aerospace, automobile and shipping industry, some important mold or stamped metal plate requires precise forming on the surface, which usually needs to be verified, if necessary, the surface needs to be corrected and reprocessed. In order to make the correction of the machined surface more convenient, this paper proposes a method based on Laser 3D projection system, this method uses the contour form of terrain contour, directly showing the deviation between the actually measured data and the theoretical mathematical model (CAD) on the measured surface. First, measure the machined surface to get the point cloud data and the formation of triangular mesh; secondly, through coordinate transformation, unify the point cloud data to the theoretical model and calculate the three-dimensional deviation, according to the sign (positive or negative) and size of the deviation, use the color deviation band to denote the deviation of three-dimensional; then, use three-dimensional contour lines to draw and represent every coordinates deviation band, creating the projection files; finally, import the projection files into the laser projector, and make the contour line projected to the processed file with 1:1 in the form of a laser beam, compare the Full-color 3D deviation map with the projection graph, then, locate and make quantitative correction to meet the processing precision requirements. It can display the trend of the machined surface deviation clearly.

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

The time machine in our mind.

PubMed

Stocker, Kurt

2012-04-01

This article provides the first comprehensive conceptual account for the imagistic mental machinery that allows us to travel through time--for the time machine in our mind. It is argued that language reveals this imagistic machine and how we use it. Findings from a range of cognitive fields are theoretically unified and a recent proposal about spatialized mental time travel is elaborated on. The following novel distinctions are offered: external versus internal viewing of time; ''watching" time versus projective ''travel" through time; optional versus obligatory mental time travel; mental time travel into anteriority or posteriority versus mental time travel into the past or future; single mental time travel versus nested dual mental time travel; mental time travel in episodic memory versus mental time travel in semantic memory; and ''seeing" versus ''sensing" mental imagery. Theoretical, empirical, and applied implications are discussed. Copyright © 2012 Cognitive Science Society, Inc.

Machine learning molecular dynamics for the simulation of infrared spectra.

PubMed

Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

2017-10-01

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

Operational alternatives for LANDSAT in California

NASA Technical Reports Server (NTRS)

Wilson, P.; Gialdini, M. J.

1981-01-01

Data integration is defined and examined as the means of promoting data sharing among the various governmental and private geobased information systems in California. Elements of vertical integration considered included technical factors (such as resolution and classification) and institutional factors (such as organizational control, and legal and political barriers). Attempts are made to fit the theoretical elements of vertical integration into a meaningful structure for looking at the problem from a statewide focus. Both manual (mapped) and machine readable data systems are included. Special attention is given to LANDSAT imagery because of its strong potential for integrated use and its primary in the California Integrated Remote Sensing System program.

The Co-Emergence of Machine Techniques, Paper-and-Pencil Techniques, and Theoretical Reflection: A Study of CAS Use in Secondary School Algebra

ERIC Educational Resources Information Center

Kieran, Carolyn; Drijvers, Paul

2006-01-01

This paper addresses the dialectical relation between theoretical thinking and technique, as they co-emerge in a combined computer algebra (CAS) and paper-and-pencil environment. The theoretical framework in this ongoing study consists of the instrumental approach to tool use and an adaptation of Chevallard's anthropological theory. The main aim…

Quantitative characterisation of audio data by ordinal symbolic dynamics

NASA Astrophysics Data System (ADS)

Aschenbrenner, T.; Monetti, R.; Amigó, J. M.; Bunk, W.

2013-06-01

Ordinal symbolic dynamics has developed into a valuable method to describe complex systems. Recently, using the concept of transcripts, the coupling behaviour of systems was assessed, combining the properties of the symmetric group with information theoretic ideas. In this contribution, methods from the field of ordinal symbolic dynamics are applied to the characterisation of audio data. Coupling complexity between frequency bands of solo violin music, as a fingerprint of the instrument, is used for classification purposes within a support vector machine scheme. Our results suggest that coupling complexity is able to capture essential characteristics, sufficient to distinguish among different violins.

Analysis on the multi-dimensional spectrum of the thrust force for the linear motor feed drive system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Ma, Chengfang; Zhang, Jun; Zhao, Wanhua

2017-01-01

The motor thrust force has lots of harmonic components due to the nonlinearity of drive circuit and motor itself in the linear motor feed drive system. What is more, in the motion process, these thrust force harmonics may vary with the position, velocity, acceleration and load, which affects the displacement fluctuation of the feed drive system. Therefore, in this paper, on the basis of the thrust force spectrum obtained by the Maxwell equation and the electromagnetic energy method, the multi-dimensional variation of each thrust harmonic is analyzed under different motion parameters. Then the model of the servo system is established oriented to the dynamic precision. The influence of the variation of the thrust force spectrum on the displacement fluctuation is discussed. At last the experiments are carried out to verify the theoretical analysis above. It can be found that the thrust harmonics show multi-dimensional spectrum characteristics under different motion parameters and loads, which should be considered to choose the motion parameters and optimize the servo control parameters in the high-speed and high-precision machine tools equipped with the linear motor feed drive system.

Data Science in the Research Domain Criteria Era: Relevance of Machine Learning to the Study of Stress Pathology, Recovery, and Resilience

PubMed Central

Galatzer-Levy, Isaac R.; Ruggles, Kelly; Chen, Zhe

2017-01-01

Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals. PMID:29527592

Bifurcation analysis of eight coupled degenerate optical parametric oscillators

NASA Astrophysics Data System (ADS)

Ito, Daisuke; Ueta, Tetsushi; Aihara, Kazuyuki

2018-06-01

A degenerate optical parametric oscillator (DOPO) network realized as a coherent Ising machine can be used to solve combinatorial optimization problems. Both theoretical and experimental investigations into the performance of DOPO networks have been presented previously. However a problem remains, namely that the dynamics of the DOPO network itself can lower the search success rates of globally optimal solutions for Ising problems. This paper shows that the problem is caused by pitchfork bifurcations due to the symmetry structure of coupled DOPOs. Some two-parameter bifurcation diagrams of equilibrium points express the performance deterioration. It is shown that the emergence of non-ground states regarding local minima hampers the system from reaching the ground states corresponding to the global minimum. We then describe a parametric strategy for leading a system to the ground state by actively utilizing the bifurcation phenomena. By adjusting the parameters to break particular symmetry, we find appropriate parameter sets that allow the coherent Ising machine to obtain the globally optimal solution alone.

Design and experimental validation for direct-drive fault-tolerant permanent-magnet vernier machines.

PubMed

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis.

Is extreme learning machine feasible? A theoretical assessment (part II).

PubMed

Lin, Shaobo; Liu, Xia; Fang, Jian; Xu, Zongben

2015-01-01

An extreme learning machine (ELM) can be regarded as a two-stage feed-forward neural network (FNN) learning system that randomly assigns the connections with and within hidden neurons in the first stage and tunes the connections with output neurons in the second stage. Therefore, ELM training is essentially a linear learning problem, which significantly reduces the computational burden. Numerous applications show that such a computation burden reduction does not degrade the generalization capability. It has, however, been open that whether this is true in theory. The aim of this paper is to study the theoretical feasibility of ELM by analyzing the pros and cons of ELM. In the previous part of this topic, we pointed out that via appropriately selected activation functions, ELM does not degrade the generalization capability in the sense of expectation. In this paper, we launch the study in a different direction and show that the randomness of ELM also leads to certain negative consequences. On one hand, we find that the randomness causes an additional uncertainty problem of ELM, both in approximation and learning. On the other hand, we theoretically justify that there also exist activation functions such that the corresponding ELM degrades the generalization capability. In particular, we prove that the generalization capability of ELM with Gaussian kernel is essentially worse than that of FNN with Gaussian kernel. To facilitate the use of ELM, we also provide a remedy to such a degradation. We find that the well-developed coefficient regularization technique can essentially improve the generalization capability. The obtained results reveal the essential characteristic of ELM in a certain sense and give theoretical guidance concerning how to use ELM.

Self-propulsion and interactions of catalytic particles in a chemically active medium.

PubMed

Banigan, Edward J; Marko, John F

2016-01-01

Enzymatic "machines," such as catalytic rods or colloids, can self-propel and interact by generating gradients of their substrates. We theoretically investigate the behaviors of such machines in a chemically active environment where their catalytic substrates are continuously synthesized and destroyed, as occurs in living cells. We show how the kinetic properties of the medium modulate self-propulsion and pairwise interactions between machines, with the latter controlled by a tunable characteristic interaction range analogous to the Debye screening length in an electrolytic solution. Finally, we discuss the effective force arising between interacting machines and possible biological applications, such as partitioning of bacterial plasmids.

The mothers' experiences in the pediatrics hemodialysis unit.

PubMed

Mieto, Fernanda Stella Risseto; Bousso, Regina Szylit

2014-01-01

The need for hemodialysis exerts a deep impact on the lives of children and adolescents with end-stage kidney chronic failure and their mothers, who predominantly assume the care related to treatment. The hemodialysis requires that the mother accompanies the child during sessions at least three times a week and, since it is not a healing practice, they also experience the waiting for a kidney transplant, attributing different meanings to this experience. To understand what it means for the mothers to accompany the child in a Pediatric Hemodialysis Unit and to construct a theoretical model representing this experience. The Symbolic Interactionism was adopted as a theoretical model and the Grounded Theory as a methodological framework. Data were collected through interviews with 11 mothers. The comparative analysis of the data enabled the identification of two phenomena that compose the experience: "Seeing the child´s life being sucked by the hemodialysis machine" expresses the experiences of the mothers that generates new demands to comprehend the new health conditions of their children and "Giving new meaning to the dependence of the hemodialysis machine" that represents the strategies employed to endure the experience. The relationship of these phenomena allowed the identification of the main category: "Having the mother's life imprisoned by the hemodialysis machine", from which we propose a new theoretical model. The results of the study allow us to provide a theoretical ground for planning an assistance that meets the real needs of the mothers, identifying aspects that require intervention.

Parallel matrix multiplication on the Connection Machine

NASA Technical Reports Server (NTRS)

Tichy, Walter F.

1988-01-01

Matrix multiplication is a computation and communication intensive problem. Six parallel algorithms for matrix multiplication on the Connection Machine are presented and compared with respect to their performance and processor usage. For n by n matrices, the algorithms have theoretical running times of O(n to the 2nd power log n), O(n log n), O(n), and O(log n), and require n, n to the 2nd power, n to the 2nd power, and n to the 3rd power processors, respectively. With careful attention to communication patterns, the theoretically predicted runtimes can indeed be achieved in practice. The parallel algorithms illustrate the tradeoffs between performance, communication cost, and processor usage.

European public deliberation on brain machine interface technology: five convergence seminars.

PubMed

Jebari, Karim; Hansson, Sven-Ove

2013-09-01

We present a novel procedure to engage the public in ethical deliberations on the potential impacts of brain machine interface technology. We call this procedure a convergence seminar, a form of scenario-based group discussion that is founded on the idea of hypothetical retrospection. The theoretical background of this procedure and the results of five seminars are presented.

The Arithmetical Machine Zero + 1 in Mathematics Laboratory: Instrumental Genesis and Semiotic Mediation

ERIC Educational Resources Information Center

Maschietto, Michela

2015-01-01

This paper presents the analysis of two teaching experiments carried out in the context of the mathematics laboratory in a primary school (grades 3 and 4) with the use of the pascaline Zero + 1, an arithmetical machine. The teaching experiments are analysed by coordinating two theoretical frameworks, i.e. the instrumental approach and the Theory…

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.

Learning Physical Domains: Toward a Theoretical Framework.

ERIC Educational Resources Information Center

Forbus, Kenneth D.; Gentner, Dedre

People use and extend their knowledge of the physical world constantly. Understanding how this fluency is achieved would be an important milestone in understanding human learning and intelligence, as well as a useful guide for constructing machines that learn. This paper presents a theoretical framework that is being developed in an attempt to…

Tunable mechanical monolithic sensor with interferometric readout for low frequency seismic noise measurement

NASA Astrophysics Data System (ADS)

Acernese, F.; De Rosa, R.; Giordano, G.; Romano, R.; Barone, F.

2008-03-01

This paper describes a mechanical monolithic sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric-discharge-machining, that can be used both as seismometer and, in a force-feedback configuration, as accelerometer. The monolithic mechanical design and the introduction of laser interferometric techniques for the readout implementation make it a very compact instrument, very sensitive in the low-frequency seismic noise band, with a very good immunity to environmental noises. Many changes have been produced since last version (2007), mainly aimed to the improvement of the mechanics and of the optical readout of the instrument. In fact, we have developed and tested a prototype with elliptical hinges and mechanical tuning of the resonance frequency together with a laser optical lever and a new laser interferometer readout system. The theoretical sensitivity curve both for both laser optical lever and laser interferometric readouts, evaluated on the basis of suitable theoretical models, shows a very good agreement with the experimental measurements. Very interesting scientific result, for example, is that the measured natural resonance frequency of the instrument is 70 mHz with a Q = 140 in air without thermal stabilization, demonstrating the feasibility of a monolithic FP sensor with a natural resonance frequency of the order of mHz with a more refined mechanical tuning. Results on the readout system based on polarimetric homodyne Michelson interferometer is discussed.

Information-theoretic limitations on approximate quantum cloning and broadcasting

NASA Astrophysics Data System (ADS)

Lemm, Marius; Wilde, Mark M.

2017-07-01

We prove quantitative limitations on any approximate simultaneous cloning or broadcasting of mixed states. The results are based on information-theoretic (entropic) considerations and generalize the well-known no-cloning and no-broadcasting theorems. We also observe and exploit the fact that the universal cloning machine on the symmetric subspace of n qudits and symmetrized partial trace channels are dual to each other. This duality manifests itself both in the algebraic sense of adjointness of quantum channels and in the operational sense that a universal cloning machine can be used as an approximate recovery channel for a symmetrized partial trace channel and vice versa. The duality extends to give control of the performance of generalized universal quantum cloning machines (UQCMs) on subspaces more general than the symmetric subspace. This gives a way to quantify the usefulness of a priori information in the context of cloning. For example, we can control the performance of an antisymmetric analog of the UQCM in recovering from the loss of n -k fermionic particles.

High-efficiency machining methods for aviation materials

NASA Astrophysics Data System (ADS)

Kononov, V. K.

1991-07-01

The papers contained in this volume present results of theoretical and experimental studies aimed at increasing the efficiency of cutting tools during the machining of high-temperature materials and titanium alloys. Specific topics discussed include a study of the performance of disk cutters during the machining of flexible parts of a high-temperature alloy, VZhL14N; a study of the wear resistance of cutters of hard alloys of various types; effect of a deformed electric field on the precision of the electrochemical machining of gas turbine engine components; and efficient machining of parts of composite materials. The discussion also covers the effect of the technological process structure on the residual stress distribution in the blades of gas turbine engines; modeling of the multiparameter assembly of engineering products for a specified priority of geometrical output parameters; and a study of the quality of the surface and surface layer of specimens machined by a high-temperature pulsed plasma.

Classification of large-sized hyperspectral imagery using fast machine learning algorithms

NASA Astrophysics Data System (ADS)

Xia, Junshi; Yokoya, Naoto; Iwasaki, Akira

2017-07-01

We present a framework of fast machine learning algorithms in the context of large-sized hyperspectral images classification from the theoretical to a practical viewpoint. In particular, we assess the performance of random forest (RF), rotation forest (RoF), and extreme learning machine (ELM) and the ensembles of RF and ELM. These classifiers are applied to two large-sized hyperspectral images and compared to the support vector machines. To give the quantitative analysis, we pay attention to comparing these methods when working with high input dimensions and a limited/sufficient training set. Moreover, other important issues such as the computational cost and robustness against the noise are also discussed.

The Body-Machine Interface: A new perspective on an old theme

PubMed Central

Casadio, Maura; Ranganathan, Rajiv; Mussa-Ivaldi, Ferdinando A.

2012-01-01

Body-machine interfaces establish a way to interact with a variety of devices, allowing their users to extend the limits of their performance. Recent advances in this field, ranging from computer-interfaces to bionic limbs, have had important consequences for people with movement disorders. In this article, we provide an overview of the basic concepts underlying the body-machine interface with special emphasis on their use for rehabilitation and for operating assistive devices. We outline the steps involved in building such an interface and we highlight the critical role of body-machine interfaces in addressing theoretical issues in motor control as well as their utility in movement rehabilitation. PMID:23237465

Design and Experimental Validation for Direct-Drive Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis. PMID:25045729

Investigating the Impact of a LEGO(TM)-Based, Engineering-Oriented Curriculum Compared to an Inquiry-Based Curriculum on Fifth Graders' Content Learning of Simple Machines

ERIC Educational Resources Information Center

Marulcu, Ismail

2010-01-01

This mixed method study examined the impact of a LEGO-based, engineering-oriented curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. This study takes a social constructivist theoretical stance that science learning involves learning scientific concepts and their relations to each other. From…

Room-Temperature Quantum Cloning Machine with Full Coherent Phase Control in Nanodiamond

PubMed Central

Chang, Yan-Chun; Liu, Gang-Qin; Liu, Dong-Qi; Fan, Heng; Pan, Xin-Yu

2013-01-01

In contrast to the classical world, an unknown quantum state cannot be cloned ideally, as stated by the no-cloning theorem. However, it is expected that approximate or probabilistic quantum cloning will be necessary for different applications, and thus various quantum cloning machines have been designed. Phase quantum cloning is of particular interest because it can be used to attack the Bennett-Brassard 1984 (BB84) states used in quantum key distribution for secure communications. Here, we report the first room-temperature implementation of quantum phase cloning with a controllable phase in a solid-state system: the nitrogen-vacancy centre of a nanodiamond. The phase cloner works well for all qubits located on the equator of the Bloch sphere. The phase is controlled and can be measured with high accuracy, and the experimental results are consistent with theoretical expectations. This experiment provides a basis for phase-controllable quantum information devices. PMID:23511233

Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

NASA Technical Reports Server (NTRS)

Saha, Bhaskar; Goebel, kai

2007-01-01

Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

New Theoretical Frameworks for Machine Learning

DTIC Science & Technology

2008-09-15

New York, 1974. 6.3 [52] G.M. Benedek and A. Itai . Learnability by fixed distributions. In Proc. 1st Workshop Computat. Learning Theory, pages 80–90...1988. 3.4.3 [53] G.M. Benedek and A. Itai . Learnability with respect to a fixed distribution. Theoretical Computer Science, 86:377–389, 1991. 2.1, 2.1.1

Data characterizing tensile behavior of cenosphere/HDPE syntactic foam.

PubMed

Kumar, B R Bharath; Doddamani, Mrityunjay; Zeltmann, Steven E; Gupta, Nikhil; Ramakrishna, Seeram

2016-03-01

The data set presented is related to the tensile behavior of cenosphere reinforced high density polyethylene syntactic foam composites "Processing of cenosphere/HDPE syntactic foams using an industrial scale polymer injection molding machine" (Bharath et al., 2016) [1]. The focus of the work is on determining the feasibility of using an industrial scale polymer injection molding (PIM) machine for fabricating syntactic foams. The fabricated syntactic foams are investigated for microstructure and tensile properties. The data presented in this article is related to optimization of the PIM process for syntactic foam manufacture, equations and procedures to develop theoretical estimates for properties of cenospheres, and microstructure of syntactic foams before and after failure. Included dataset contains values obtained from the theoretical model.

[Anesthesia simulators and training devices].

PubMed

Hartmannsgruber, M; Good, M; Carovano, R; Lampotang, S; Gravenstein, J S

1993-07-01

Simulators and training devices are used extensively by educators in 'high-tech' occupations, especially those requiring an understanding of complex systems and co-ordinated psychomotor skills. Because of advances in computer technology, anaesthetised patients can now be realistically simulated. This paper describes several training devices and a simulator currently being employed in the training of anaesthesia personnel at the University of Florida. This Gainesville Anesthesia Simulator (GAS) comprises a patient mannequin, anaesthesia gas machine, and a full set of normally operating monitoring instruments. The patient can spontaneously breathe, has audible heart and breath sounds, and palpable pulses. The mannequin contains a sophisticated lung model that consumes and eliminates gas according to physiological principles. Interconnected computers controlling the physical signs of the mannequin enable the presentation of a multitude of clinical signs. In addition, the anaesthesia machine, which is functionally intact, has hidden fault activators to challenge the user to correct equipment malfunctions. Concealed sensors monitor the users' actions and responses. A robust data acquisition and control system and a user-friendly scripting language for programming simulation scenarios are key features of GAS and make this system applicable for the training of both the beginning resident and the experienced practitioner. GAS enhances clinical education in anaesthesia by providing a non-threatening environment that fosters learning by doing. Exercises with the simulator are supported by sessions on a number of training devices. These present theoretical and practical interactive courses on the anaesthesia machine and on monitors. An extensive system, for example, introduces the student to the physics and clinical application of transoesophageal echocardiography.(ABSTRACT TRUNCATED AT 250 WORDS)

Petri net modelling of buffers in automated manufacturing systems.

PubMed

Zhou, M; Dicesare, F

1996-01-01

This paper presents Petri net models of buffers and a methodology by which buffers can be included in a system without introducing deadlocks or overflows. The context is automated manufacturing. The buffers and models are classified as random order or order preserved (first-in-first-out or last-in-first-out), single-input-single-output or multiple-input-multiple-output, part type and/or space distinguishable or indistinguishable, and bounded or safe. Theoretical results for the development of Petri net models which include buffer modules are developed. This theory provides the conditions under which the system properties of boundedness, liveness, and reversibility are preserved. The results are illustrated through two manufacturing system examples: a multiple machine and multiple buffer production line and an automatic storage and retrieval system in the context of flexible manufacturing.

Theoretical study of cut area of reduction of large surfaces of rotation parts on machines with rotary cutters “Extra”

NASA Astrophysics Data System (ADS)

Bondarenko, J. A.; Fedorenko, M. A.; Pogonin, A. A.

2018-03-01

Large parts can be treated without disassembling machines using “Extra”, having technological and design challenges, which differ from the challenges in the processing of these components on the stationary machine. Extension machines are used to restore large parts up to the condition allowing one to use them in a production environment. To achieve the desired accuracy and surface roughness parameters, the surface after rotary grinding becomes recoverable, which greatly increases complexity. In order to improve production efficiency and productivity of the process, the qualitative rotary processing of the machined surface is applied. The rotary cutting process includes a continuous change of the cutting edge surfaces. The kinematic parameters of a rotary cutting define its main features and patterns, the cutting operation of the rotary cutting instrument.

Safety issues in high speed machining

NASA Astrophysics Data System (ADS)

1994-05-01

There are several risks related to High-Speed Milling, but they have not been systematically determined or studied so far. Increased loads by high centrifugal forces may result in dramatic hazards. Flying tools or fragments from a tool with high kinetic energy may damage surrounding people, machines and devices. In the project, mechanical risks were evaluated, theoretic values for kinetic energies of rotating tools were calculated, possible damages of the flying objects were determined and terms to eliminate the risks were considered. The noise levels of the High-Speed Machining center owned by the Helsinki University of Technology (HUT) and the Technical Research Center of Finland (VTT) in practical machining situation were measured and the results were compared to those after basic preventive measures were taken.

Atomistic Design and Simulations of Nanoscale Machines and Assembly

NASA Technical Reports Server (NTRS)

Goddard, William A., III; Cagin, Tahir; Walch, Stephen P.

2000-01-01

Over the three years of this project, we made significant progress on critical theoretical and computational issues in nanoscale science and technology, particularly in:(1) Fullerenes and nanotubes, (2) Characterization of surfaces of diamond and silicon for NEMS applications, (3) Nanoscale machine and assemblies, (4) Organic nanostructures and dendrimers, (5) Nanoscale confinement and nanotribology, (6) Dynamic response of nanoscale structures nanowires (metals, tubes, fullerenes), (7) Thermal transport in nanostructures.

MapReduce SVM Game

DOE PAGES

Vineyard, Craig M.; Verzi, Stephen J.; James, Conrad D.; ...

2015-08-10

Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently andmore » recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.« less

Differentially Private Empirical Risk Minimization

PubMed Central

Chaudhuri, Kamalika; Monteleoni, Claire; Sarwate, Anand D.

2011-01-01

Privacy-preserving machine learning algorithms are crucial for the increasingly common setting in which personal data, such as medical or financial records, are analyzed. We provide general techniques to produce privacy-preserving approximations of classifiers learned via (regularized) empirical risk minimization (ERM). These algorithms are private under the ε-differential privacy definition due to Dwork et al. (2006). First we apply the output perturbation ideas of Dwork et al. (2006), to ERM classification. Then we propose a new method, objective perturbation, for privacy-preserving machine learning algorithm design. This method entails perturbing the objective function before optimizing over classifiers. If the loss and regularizer satisfy certain convexity and differentiability criteria, we prove theoretical results showing that our algorithms preserve privacy, and provide generalization bounds for linear and nonlinear kernels. We further present a privacy-preserving technique for tuning the parameters in general machine learning algorithms, thereby providing end-to-end privacy guarantees for the training process. We apply these results to produce privacy-preserving analogues of regularized logistic regression and support vector machines. We obtain encouraging results from evaluating their performance on real demographic and benchmark data sets. Our results show that both theoretically and empirically, objective perturbation is superior to the previous state-of-the-art, output perturbation, in managing the inherent tradeoff between privacy and learning performance. PMID:21892342

MapReduce SVM Game

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

Vineyard, Craig M.; Verzi, Stephen J.; James, Conrad D.

Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently andmore » recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.« less

Biomolecular Dynamics: Order-Disorder Transitions and Energy Landscapes

PubMed Central

Whitford, Paul C.; Sanbonmatsu, Karissa Y.; Onuchic, José N.

2013-01-01

While the energy landscape theory of protein folding is now a widely accepted view for understanding how relatively-weak molecular interactions lead to rapid and cooperative protein folding, such a framework must be extended to describe the large-scale functional motions observed in molecular machines. In this review, we discuss 1) the development of the energy landscape theory of biomolecular folding, 2) recent advances towards establishing a consistent understanding of folding and function, and 3) emerging themes in the functional motions of enzymes, biomolecular motors, and other biomolecular machines. Recent theoretical, computational, and experimental lines of investigation are providing a very dynamic picture of biomolecular motion. In contrast to earlier ideas, where molecular machines were thought to function similarly to macroscopic machines, with rigid components that move along a few degrees of freedom in a deterministic fashion, biomolecular complexes are only marginally stable. Since the stabilizing contribution of each atomic interaction is on the order of the thermal fluctuations in solution, the rigid body description of molecular function must be revisited. An emerging theme is that functional motions encompass order-disorder transitions and structural flexibility provide significant contributions to the free-energy. In this review, we describe the biological importance of order-disorder transitions and discuss the statistical-mechanical foundation of theoretical approaches that can characterize such transitions. PMID:22790780

Language extraction from zinc sulfide

NASA Astrophysics Data System (ADS)

Varn, Dowman Parks

2001-09-01

Recent advances in the analysis of one-dimensional temporal and spacial series allow for detailed characterization of disorder and computation in physical systems. One such system that has defied theoretical understanding since its discovery in 1912 is polytypism. Polytypes are layered compounds, exhibiting crystallinity in two dimensions, yet having complicated stacking sequences in the third direction. They can show both ordered and disordered sequences, sometimes each in the same specimen. We demonstrate a method for extracting two-layer correlation information from ZnS diffraction patterns and employ a novel technique for epsilon-machine reconstruction. We solve a long-standing problem---that of determining structural information for disordered materials from their diffraction patterns---for this special class of disorder. Our solution offers the most complete possible statistical description of the disorder. Furthermore, from our reconstructed epsilon-machines we find the effective range of the interlayer interaction in these materials, as well as the configurational energy of both ordered and disordered specimens. Finally, we can determine the 'language' (in terms of the Chomsky Hierarchy) these small rocks speak, and we find that regular languages are sufficient to describe them.

Mimicking Nonequilibrium Steady States with Time-Periodic Driving

NASA Astrophysics Data System (ADS)

Raz, O.; Subaşı, Y.; Jarzynski, C.

2016-04-01

Under static conditions, a system satisfying detailed balance generically relaxes to an equilibrium state in which there are no currents. To generate persistent currents, either detailed balance must be broken or the system must be driven in a time-dependent manner. A stationary system that violates detailed balance evolves to a nonequilibrium steady state (NESS) characterized by fixed currents. Conversely, a system that satisfies instantaneous detailed balance but is driven by the time-periodic variation of external parameters—also known as a stochastic pump (SP)—reaches a periodic state with nonvanishing currents. In both cases, these currents are maintained at the cost of entropy production. Are these two paradigmatic scenarios effectively equivalent? For discrete-state systems, we establish a mapping between nonequilibrium stationary states and stochastic pumps. Given a NESS characterized by a particular set of stationary probabilities, currents, and entropy production rates, we show how to construct a SP with exactly the same (time-averaged) values. The mapping works in the opposite direction as well. These results establish a proof of principle: They show that stochastic pumps are able to mimic the behavior of nonequilibrium steady states, and vice versa, within the theoretical framework of discrete-state stochastic thermodynamics. Nonequilibrium steady states and stochastic pumps are often used to model, respectively, biomolecular motors driven by chemical reactions and artificial molecular machines steered by the variation of external, macroscopic parameters. Our results loosely suggest that anything a biomolecular machine can do, an artificial molecular machine can do equally well. We illustrate this principle by showing that kinetic proofreading, a NESS mechanism that explains the low error rates in biochemical reactions, can be effectively mimicked by a constrained periodic driving.

Optimal quantum cloning based on the maximin principle by using a priori information

NASA Astrophysics Data System (ADS)

Kang, Peng; Dai, Hong-Yi; Wei, Jia-Hua; Zhang, Ming

2016-10-01

We propose an optimal 1 →2 quantum cloning method based on the maximin principle by making full use of a priori information of amplitude and phase about the general cloned qubit input set, which is a simply connected region enclosed by a "longitude-latitude grid" on the Bloch sphere. Theoretically, the fidelity of the optimal quantum cloning machine derived from this method is the largest in terms of the maximin principle compared with that of any other machine. The problem solving is an optimization process that involves six unknown complex variables, six vectors in an uncertain-dimensional complex vector space, and four equality constraints. Moreover, by restricting the structure of the quantum cloning machine, the optimization problem is simplified as a three-real-parameter suboptimization problem with only one equality constraint. We obtain the explicit formula for a suboptimal quantum cloning machine. Additionally, the fidelity of our suboptimal quantum cloning machine is higher than or at least equal to that of universal quantum cloning machines and phase-covariant quantum cloning machines. It is also underlined that the suboptimal cloning machine outperforms the "belt quantum cloning machine" for some cases.

A new digitized reverse correction method for hypoid gears based on a one-dimensional probe

NASA Astrophysics Data System (ADS)

Li, Tianxing; Li, Jubo; Deng, Xiaozhong; Yang, Jianjun; Li, Genggeng; Ma, Wensuo

2017-12-01

In order to improve the tooth surface geometric accuracy and transmission quality of hypoid gears, a new digitized reverse correction method is proposed based on the measurement data from a one-dimensional probe. The minimization of tooth surface geometrical deviations is realized from the perspective of mathematical analysis and reverse engineering. Combining the analysis of complex tooth surface generation principles and the measurement mechanism of one-dimensional probes, the mathematical relationship between the theoretical designed tooth surface, the actual machined tooth surface and the deviation tooth surface is established, the mapping relation between machine-tool settings and tooth surface deviations is derived, and the essential connection between the accurate calculation of tooth surface deviations and the reverse correction method of machine-tool settings is revealed. Furthermore, a reverse correction model of machine-tool settings is built, a reverse correction strategy is planned, and the minimization of tooth surface deviations is achieved by means of the method of numerical iterative reverse solution. On this basis, a digitized reverse correction system for hypoid gears is developed by the organic combination of numerical control generation, accurate measurement, computer numerical processing, and digitized correction. Finally, the correctness and practicability of the digitized reverse correction method are proved through a reverse correction experiment. The experimental results show that the tooth surface geometric deviations meet the engineering requirements after two trial cuts and one correction.

Productivity improvement using discrete events simulation

NASA Astrophysics Data System (ADS)

Hazza, M. H. F. Al; Elbishari, E. M. Y.; Ismail, M. Y. Bin; Adesta, E. Y. T.; Rahman, Nur Salihah Binti Abdul

2018-01-01

The increasing in complexity of the manufacturing systems has increased the cost of investment in many industries. Furthermore, the theoretical feasibility studies are not enough to take the decision in investing for that particular area. Therefore, the development of the new advanced software is protecting the manufacturer from investing money in production lines that may not be sufficient and effective with their requirement in terms of machine utilization and productivity issue. By conducting a simulation, using accurate model will reduce and eliminate the risk associated with their new investment. The aim of this research is to prove and highlight the importance of simulation in decision-making process. Delmia quest software was used as a simulation program to run a simulation for the production line. A simulation was first done for the existing production line and show that the estimated production rate is 261 units/day. The results have been analysed based on utilization percentage and idle time. Two different scenarios have been proposed based on different objectives. The first scenario is by focusing on low utilization machines and their idle time, this was resulted in minimizing the number of machines used by three with the addition of the works who maintain them without having an effect on the production rate. The second scenario is to increase the production rate by upgrading the curing machine which lead to the increase in the daily productivity by 7% from 261 units to 281 units.

An investigation of the effects of measurement noise in the use of instantaneous angular speed for machine diagnosis

NASA Astrophysics Data System (ADS)

Gu, Fengshou; Yesilyurt, Isa; Li, Yuhua; Harris, Georgina; Ball, Andrew

2006-08-01

In order to discriminate small changes for early fault diagnosis of rotating machines, condition monitoring demands that the measurement of instantaneous angular speed (IAS) of the machines be as accurate as possible. This paper develops the theoretical basis and practical implementation of IAS data acquisition and IAS estimation when noise influence is included. IAS data is modelled as a frequency modulated signal of which the signal-to-noise ratio can be improved by using a high-resolution encoder. From this signal model and analysis, optimal configurations for IAS data collection are addressed for high accuracy IAS measurement. Simultaneously, a method based on analytic signal concept and fast Fourier transform is also developed for efficient and accurate estimation of IAS. Finally, a fault diagnosis is carried out on an electric induction motor driving system using IAS measurement. The diagnosis results show that using a high-resolution encoder and a long data stream can achieve noise reduction by more than 10 dB in the frequency range of interest, validating the model and algorithm developed. Moreover, the results demonstrate that IAS measurement outperforms conventional vibration in diagnosis of incipient faults of motor rotor bar defects and shaft misalignment.

Effects of temperature on the removal efficiency of KDP crystal during the process of magnetorheological water-dissolution polishing.

PubMed

Zhang, Yifan; Dai, Yifan; Tie, Guipeng; Hu, Hao

2016-10-10

As a kind of important nonlinear optical element, KDP crystal has great demand in the inertial confinement fusion system. Based on the dissolution mechanism of solid materials, the factors that affect the material removal rate of KDP crystal in magnetorheological (MR) water-dissolution polishing are investigated to improve the machining efficiency. It is found that the material removal rate is proportional to the product of the saturation concentration and diffusion coefficient, and the relationship between the removal efficiency and the temperature meets the unilateral Gaussian function. Polishing experiments are carried out on a magnetorheological finishing (MRF) machine with self-designed MRF fluid heating devices. The experimental results show that practical efficiency-temperature curve is consistent with the theoretical curve, and the maximum machining efficiency increases by about 50% with the rise of temperature from 294 to 302 K. Meanwhile, when the MR fluid temperature is lower than 308 K, the crystal surface quality and surface roughness in different processing temperatures have no remarkable difference with constant crystal temperature (294 K). This research indicates that it is feasible to drastically improve KDP crystal MRF efficiency by controlling the processing temperature.

LDRD Report: Topological Design Optimization of Convolutes in Next Generation Pulsed Power Devices.

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

Cyr, Eric C.; von Winckel, Gregory John; Kouri, Drew Philip

This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of thismore » exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.« less

Numerical simulation of polishing U-tube based on solid-liquid two-phase

NASA Astrophysics Data System (ADS)

Li, Jun-ye; Meng, Wen-qing; Wu, Gui-ling; Hu, Jing-lei; Wang, Bao-zuo

2018-03-01

As the advanced technology to solve the ultra-precision machining of small hole structure parts and complex cavity parts, the abrasive grain flow processing technology has the characteristics of high efficiency, high quality and low cost. So this technology in many areas of precision machining has an important role. Based on the theory of solid-liquid two-phase flow coupling, a solid-liquid two-phase MIXTURE model is used to simulate the abrasive flow polishing process on the inner surface of U-tube, and the temperature, turbulent viscosity and turbulent dissipation rate in the process of abrasive flow machining of U-tube were compared and analyzed under different inlet pressure. In this paper, the influence of different inlet pressure on the surface quality of the workpiece during abrasive flow machining is studied and discussed, which provides a theoretical basis for the research of abrasive flow machining process.

Research on carrying capacity of hydrostatic slideway on heavy-duty gantry CNC machine

NASA Astrophysics Data System (ADS)

Cui, Chao; Guo, Tieneng; Wang, Yijie; Dai, Qin

2017-05-01

Hydrostatic slideway is a key part in the heavy-duty gantry CNC machine, which supports the total weight of the gantry and moves smoothly along the table. Therefore, the oil film between sliding rails plays an important role on the carrying capacity and precision of machine. In this paper, the oil film in no friction is simulated with three-dimensional CFD. The carrying capacity of heavy hydrostatic slideway, pressure and velocity characteristic of the flow field are analyzed. The simulation result is verified through comparing with the experimental data obtained from the heavy-duty gantry machine. For the requirement of engineering, the oil film carrying capacity is analyzed with simplified theoretical method. The precision of the simplified method is evaluated and the effectiveness is verified with the experimental data. The simplified calculation method is provided for designing oil pad on heavy-duty gantry CNC machine hydrostatic slideway.

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

PubMed Central

Burriel-Valencia, Jordi; Martinez-Roman, Javier; Sapena-Bano, Angel

2018-01-01

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources. PMID:29316650

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window.

PubMed

Burriel-Valencia, Jordi; Puche-Panadero, Ruben; Martinez-Roman, Javier; Sapena-Bano, Angel; Pineda-Sanchez, Manuel

2018-01-06

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

3-D Human body models in C.A.D. : Anthropometric Aspects

NASA Astrophysics Data System (ADS)

Renaud, C.; Steck, R.; Pineau, J. C.

1986-07-01

Modeling and simulation methods of man-machine systems are developed at the laboratory by interactive infography and C.A.D. technics. In order to better apprehend the morphological variability of populations we have enriched the 3-D model with a parametric function using classical anthropometric dimensions. We have selected reference, associate and complementary dimensions : lengths, breadths, circumferences and depths, which depend on operator's tasks and characteristics of workplaces. All anthropometric values come from the International Data Bank of Human Biometry of ERGODATA System. The utilization of the parametric function brings a quick and accurate description of morphology for theoretic subjects and can be used in C.A.D. analysis.

[Research on infrared safety protection system for machine tool].

PubMed

Zhang, Shuan-Ji; Zhang, Zhi-Ling; Yan, Hui-Ying; Wang, Song-De

2008-04-01

In order to ensure personal safety and prevent injury accident in machine tool operation, an infrared machine tool safety system was designed with infrared transmitting-receiving module, memory self-locked relay and voice recording-playing module. When the operator does not enter the danger area, the system has no response. Once the operator's whole or part of body enters the danger area and shades the infrared beam, the system will alarm and output an control signal to the machine tool executive element, and at the same time, the system makes the machine tool emergency stop to prevent equipment damaged and person injured. The system has a module framework, and has many advantages including safety, reliability, common use, circuit simplicity, maintenance convenience, low power consumption, low costs, working stability, easy debugging, vibration resistance and interference resistance. It is suitable for being installed and used in different machine tools such as punch machine, pour plastic machine, digital control machine, armor plate cutting machine, pipe bending machine, oil pressure machine etc.

Descartes' pineal neuropsychology.

PubMed

Smith, C U

1998-02-01

The year 1996 marked the quattrocentenary of Descartes' birth. This paper reviews his pineal neuropsychology. It demonstrates that Descartes understood the true anatomical position of the pineal. His intraventricular pineal (or glande H) was a theoretical construct which allowed him to describe the operations of his man-like "earthen machine." In the Treatise of Man he shows how all the behaviors of such machines could then be accounted for without the presence of self-consciousness. Infrahuman animals are "conscious automata." In Passions of the Soul he adds, but only for humans, self-consciousness to the machine. In a modern formulation, only humans not only know but know that they know. Copyright 1998 Academic Press.

Influence of magnet eddy current on magnetization characteristics of variable flux memory machine

NASA Astrophysics Data System (ADS)

Yang, Hui; Lin, Heyun; Zhu, Z. Q.; Lyu, Shukang

2018-05-01

In this paper, the magnet eddy current characteristics of a newly developed variable flux memory machine (VFMM) is investigated. Firstly, the machine structure, non-linear hysteresis characteristics and eddy current modeling of low coercive force magnet are described, respectively. Besides, the PM eddy current behaviors when applying the demagnetizing current pulses are unveiled and investigated. The mismatch of the required demagnetization currents between the cases with or without considering the magnet eddy current is identified. In addition, the influences of the magnet eddy current on the demagnetization effect of VFMM are analyzed. Finally, a prototype is manufactured and tested to verify the theoretical analyses.

Impact of oscillations of shafts on machining accuracy using non-stationary machines

NASA Astrophysics Data System (ADS)

Fedorenko, M. A.; Bondarenko, J. A.; Pogonin, A. A.

2018-03-01

The solution of the problem of restoring parts and units of equipment of the large mass and size is possible on the basis of the development of the research base, including the development of models and theoretical relations, revealing complex reasons for causes of damage and equipment failure. This allows one to develop new effective technologies of maintenance and repair, implementation of which ensures the efficiency and durability of the machines. The development of new forms of technical maintenance and repair of equipment, based on a systematic evaluation of its technical condition with the help of modern diagnostic tools can significantly reduce the duration of the downtime.

Differential spatial activity patterns of acupuncture by a machine learning based analysis

NASA Astrophysics Data System (ADS)

You, Youbo; Bai, Lijun; Xue, Ting; Zhong, Chongguang; Liu, Zhenyu; Tian, Jie

2011-03-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

Experiences and results multitasking a hydrodynamics code on global and local memory machines

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

Mandell, D.

1987-01-01

A one-dimensional, time-dependent Lagrangian hydrodynamics code using a Godunov solution method has been multitasked for the Cray X-MP/48, the Intel iPSC hypercube, the Alliant FX series and the IBM RP3 computers. Actual multitasking results have been obtained for the Cray, Intel and Alliant computers and simulated results were obtained for the Cray and RP3 machines. The differences in the methods required to multitask on each of the machines is discussed. Results are presented for a sample problem involving a shock wave moving down a channel. Comparisons are made between theoretical speedups, predicted by Amdahl's law, and the actual speedups obtained.more » The problems of debugging on the different machines are also described.« less

Computer Aided Simulation Machining Programming In 5-Axis Nc Milling Of Impeller Leaf

NASA Astrophysics Data System (ADS)

Huran, Liu

At present, cad/cam (computer-aided design and manufacture) have fine wider and wider application in mechanical industry. For the complex surfaces, the traditional machine tool can no longer satisfy the requirement of such complex task. Only by the help of cad/cam can fulfill the requirement. The machining of the vane surface of the impeller leaf has been considered as the hardest challenge. Because of their complex shape, the 5-axis cnc machine tool is needed for the machining of such parts. The material is hard to cut, the requirement for the surface finish and clearance is very high, so that the manufacture quality of impeller leaf represent the level of 5-axis machining. This paper opened a new field in machining the complicated surface, based on a relatively more rigid mathematical basis. The theory presented here is relatively more systematical. Since the lack of theoretical guidance, in the former research, people have to try in machining many times. Such case will be changed. The movement of the cutter determined by this method is definite, and the residual is the smallest while the times of travel is the fewest. The criterion is simple and the calculation is easy.

Mechanical monolithic horizontal sensor for low frequency seismic noise measurement

NASA Astrophysics Data System (ADS)

Acernese, Fausto; Giordano, Gerardo; Romano, Rocco; De Rosa, Rosario; Barone, Fabrizio

2008-07-01

This paper describes a mechanical monolithic horizontal sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric discharge machining, that can be used both as seismometer and, in a force-feedback configuration, as accelerometer. The monolithic mechanical design and the introduction of laser interferometric techniques for the readout implementation makes it a very compact instrument, very sensitive in the low frequency seismic noise band, with a very good immunity to environmental noises. Many changes have been produced since last version (2007), mainly aimed to the improvement of the mechanics and of the optical readout of the instrument. In fact, we have developed and tested a prototype with elliptical hinges and mechanical tuning of the resonance frequency together with a laser optical lever and a new laser interferometer readout system. The theoretical sensitivity curve for both laser optical lever and laser interferometric readouts, evaluated on the basis of suitable theoretical models, shows a very good agreement with the experimental measurements. Very interesting scientific result is the measured natural resonance frequency of the instrument of 70mHz with a Q =140 in air without thermal stabilization. This result demonstrates the feasibility of a monolithic folded pendulum sensor with a natural resonance frequency of the order of millihertz with a more refined mechanical tuning.

Mechanical monolithic sensor for low frequency seismic noise measurement

NASA Astrophysics Data System (ADS)

Acernese, Fausto; De Rosa, Rosario; Giordano, Gerardo; Romano, Rocco; Barone, Fabrizio

2007-10-01

This paper describes a mechanical monolithic sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric-discharge-machining, that can be used both as seismometer and, in a force-feedback configuration, as accelerometer. The monolithic mechanical design and the introduction of laser interferometric techniques for the readout implementation make it a very compact instrument, very sensitive in the low-frequency seismic noise band, with a very good immunity to environmental noises. Many changes have been produced since last version (2006), mainly aimed to the improvement of the mechanics and of the optical readout of the instrument. In fact, we have developed and tested a prototype with elliptical hinges and mechanical tuning of the resonance frequency together with a new laser optical lever and laser interferometer readout system. The theoretical sensitivity curve for both laser optical lever and laser interferometric readouts, calculated on the basis of suitable theoretical models, shows a very good agreement with the experimental measurements. Very interesting scientific result is that the measured natural resonance frequency of the instrument is ~ 70mHz with a Q ~ 140 in air without thermal stabilization, demonstrating the feasibility of a monolithic FP sensor with a natural resonance frequency of the order of 5 mHz with a more refined mechanical tuning.

Mechanical monolithic horizontal sensor for low frequency seismic noise measurement.

PubMed

Acernese, Fausto; Giordano, Gerardo; Romano, Rocco; De Rosa, Rosario; Barone, Fabrizio

2008-07-01

This paper describes a mechanical monolithic horizontal sensor for geophysical applications developed at the University of Salerno. The instrument is basically a monolithic tunable folded pendulum, shaped with precision machining and electric discharge machining, that can be used both as seismometer and, in a force-feedback configuration, as accelerometer. The monolithic mechanical design and the introduction of laser interferometric techniques for the readout implementation makes it a very compact instrument, very sensitive in the low frequency seismic noise band, with a very good immunity to environmental noises. Many changes have been produced since last version (2007), mainly aimed to the improvement of the mechanics and of the optical readout of the instrument. In fact, we have developed and tested a prototype with elliptical hinges and mechanical tuning of the resonance frequency together with a laser optical lever and a new laser interferometer readout system. The theoretical sensitivity curve for both laser optical lever and laser interferometric readouts, evaluated on the basis of suitable theoretical models, shows a very good agreement with the experimental measurements. Very interesting scientific result is the measured natural resonance frequency of the instrument of 70 mHz with a Q=140 in air without thermal stabilization. This result demonstrates the feasibility of a monolithic folded pendulum sensor with a natural resonance frequency of the order of millihertz with a more refined mechanical tuning.

The development of a multi-target compiler-writing system for flight software development

NASA Technical Reports Server (NTRS)

Feyock, S.; Donegan, M. K.

1977-01-01

A wide variety of systems designed to assist the user in the task of writing compilers has been developed. A survey of these systems reveals that none is entirely appropriate to the purposes of the MUST project, which involves the compilation of one or at most a small set of higher-order languages to a wide variety of target machines offering little or no software support. This requirement dictates that any compiler writing system employed must provide maximal support in the areas of semantics specification and code generation, the areas in which existing compiler writing systems as well as theoretical underpinnings are weakest. This paper describes an ongoing research and development effort to create a compiler writing system which will overcome these difficulties, thus providing a software system which makes possible the fast, trouble-free creation of reliable compilers for a wide variety of target computers.

Fault tolerant operation of switched reluctance machine

NASA Astrophysics Data System (ADS)

Wang, Wei

The energy crisis and environmental challenges have driven industry towards more energy efficient solutions. With nearly 60% of electricity consumed by various electric machines in industry sector, advancement in the efficiency of the electric drive system is of vital importance. Adjustable speed drive system (ASDS) provides excellent speed regulation and dynamic performance as well as dramatically improved system efficiency compared with conventional motors without electronics drives. Industry has witnessed tremendous grow in ASDS applications not only as a driving force but also as an electric auxiliary system for replacing bulky and low efficiency auxiliary hydraulic and mechanical systems. With the vast penetration of ASDS, its fault tolerant operation capability is more widely recognized as an important feature of drive performance especially for aerospace, automotive applications and other industrial drive applications demanding high reliability. The Switched Reluctance Machine (SRM), a low cost, highly reliable electric machine with fault tolerant operation capability, has drawn substantial attention in the past three decades. Nevertheless, SRM is not free of fault. Certain faults such as converter faults, sensor faults, winding shorts, eccentricity and position sensor faults are commonly shared among all ASDS. In this dissertation, a thorough understanding of various faults and their influence on transient and steady state performance of SRM is developed via simulation and experimental study, providing necessary knowledge for fault detection and post fault management. Lumped parameter models are established for fast real time simulation and drive control. Based on the behavior of the faults, a fault detection scheme is developed for the purpose of fast and reliable fault diagnosis. In order to improve the SRM power and torque capacity under faults, the maximum torque per ampere excitation are conceptualized and validated through theoretical analysis and experiments. With the proposed optimal waveform, torque production is greatly improved under the same Root Mean Square (RMS) current constraint. Additionally, position sensorless operation methods under phase faults are investigated to account for the combination of physical position sensor and phase winding faults. A comprehensive solution for position sensorless operation under single and multiple phases fault are proposed and validated through experiments. Continuous position sensorless operation with seamless transition between various numbers of phase fault is achieved.

Solution of magnetic field and eddy current problem induced by rotating magnetic poles (abstract)

NASA Astrophysics Data System (ADS)

Liu, Z. J.; Low, T. S.

1996-04-01

The magnetic field and eddy current problems induced by rotating permanent magnet poles occur in electromagnetic dampers, magnetic couplings, and many other devices. Whereas numerical techniques, for example, finite element methods can be exploited to study various features of these problems, such as heat generation and drag torque development, etc., the analytical solution is always of interest to the designers since it helps them to gain the insight into the interdependence of the parameters involved and provides an efficient tool for designing. Some of the previous work showed that the solution of the eddy current problem due to the linearly moving magnet poles can give satisfactory approximation for the eddy current problem due to rotating fields. However, in many practical cases, especially when the number of magnet poles is small, there is significant effect of flux focusing due to the geometry. The above approximation can therefore lead to marked errors in the theoretical predictions of the device performance. Bernot et al. recently described an analytical solution in a polar coordinate system where the radial field is excited by a time-varying source. A discussion of an analytical solution of the magnetic field and eddy current problems induced by moving magnet poles in radial field machines will be given in this article. The theoretical predictions obtained from this method is compared with the results obtained from finite element calculations. The validity of the method is also checked by the comparison of the theoretical predictions and the measurements from a test machine. It is shown that the introduced solution leads to a significant improvement in the air gap field prediction as compared with the results obtained from the analytical solution that models the eddy current problems induced by linearly moving magnet poles.

Energetic particle instabilities in fusion plasmas

NASA Astrophysics Data System (ADS)

Sharapov, S. E.; Alper, B.; Berk, H. L.; Borba, D. N.; Breizman, B. N.; Challis, C. D.; Classen, I. G. J.; Edlund, E. M.; Eriksson, J.; Fasoli, A.; Fredrickson, E. D.; Fu, G. Y.; Garcia-Munoz, M.; Gassner, T.; Ghantous, K.; Goloborodko, V.; Gorelenkov, N. N.; Gryaznevich, M. P.; Hacquin, S.; Heidbrink, W. W.; Hellesen, C.; Kiptily, V. G.; Kramer, G. J.; Lauber, P.; Lilley, M. K.; Lisak, M.; Nabais, F.; Nazikian, R.; Nyqvist, R.; Osakabe, M.; Perez von Thun, C.; Pinches, S. D.; Podesta, M.; Porkolab, M.; Shinohara, K.; Schoepf, K.; Todo, Y.; Toi, K.; Van Zeeland, M. A.; Voitsekhovich, I.; White, R. B.; Yavorskij, V.; TG, ITPA EP; Contributors, JET-EFDA

2013-10-01

Remarkable progress has been made in diagnosing energetic particle instabilities on present-day machines and in establishing a theoretical framework for describing them. This overview describes the much improved diagnostics of Alfvén instabilities and modelling tools developed world-wide, and discusses progress in interpreting the observed phenomena. A multi-machine comparison is presented giving information on the performance of both diagnostics and modelling tools for different plasma conditions outlining expectations for ITER based on our present knowledge.

Chemometrics and Intelligent Laboratory Systems, Volume 10, Numbers 1-2, February 1991. Proceedings of the Mathematics in Chemistry Conference Held in College Station, Texas on 8-10 November 1989

DTIC Science & Technology

1991-02-01

from a small group of speak- Four quite different subjects were tors, were well described. As these ers. This arrangement meant that discussed: local...ACKNOWLEDGEMENTS 6 M Gerloch and RG Woolley. The functional group m igand-field studies the empircal and theoretical status of It is a pleasure to thank...Al) Babes 26 3 43 add about three or four observable c.,mponents. Learning 26 0 44 0 In this study we applied SIMCA. nearest machine neighbor, Bayes

Dynamical Systems in Psychology: Linguistic Approaches

NASA Astrophysics Data System (ADS)

Sulis, William

Major goals for psychoanalysis and psychology are the description, analysis, prediction, and control of behaviour. Natural language has long provided the medium for the formulation of our theoretical understanding of behavior. But with the advent of nonlinear dynamics, a new language has appeared which offers promise to provide a quantitative theory of behaviour. In this paper, some of the limitations of natural and formal languages are discussed. Several approaches to understanding the links between natural and formal languages, as applied to the study of behavior, are discussed. These include symbolic dynamics, Moore's generalized shifts, Crutchfield's ɛ machines, and dynamical automata.

[Biophilosophical and epistemological problems in the study of living beings: reflections on the views of Humberto Maturana].

PubMed

Serani-Merlo, A

2001-01-01

Theories on the nature of living beings have been present in our culture since the beginnings of science and philosophy in ancient Greece. The two major theoretical approaches to living beings, philosophical mechanism and Aristotelian realism, appear today with renewed force in almost every confrontation concerning the theoretical considerations of life. In recent times a strong and prolific school of thought has risen, headed by the Chilean neurobiologist Humberto Maturana. This author and his school have developed a complex and articulated theoretical system beginning with a theory of living beings and a 'biology of cognition,' and extending to ethical, political, and even metaphysical considerations. This work is one of the first efforts to perform a scholarly analysis of Maturana's doctrines on living beings, starting with the analysis of "On machines and living beings". The book's introduction is placed under scrutiny in this paper. A strongly mechanist philosophical manifesto is dogmatically stated at the beginning of a supposedly purely scientific approach. The challenges for a rational foundation of philosophical mechanism are critically highlighted and briefly discussed.

Towards an internal model in pilot training.

PubMed

Braune, R J; Trollip, S R

1982-10-01

Optimal decision making requires an information seeking behavior which reflects the comprehension of the overall system dynamics. Research in the area of human monitors in man-machine systems supports the notion of an internal model with built-in expectancies. It is doubtful that the current approach to pilot training helps develop this internal model in the most efficient way. But this is crucial since the role of the pilot is changing to a systems' manager and decision maker. An extension of the behavioral framework of pilot training might help to prepare the pilot better for the increasingly complex flight environment. This extension is based on the theoretical model of schema theory, which evolved out of psychological research. The technological advances in aircraft simulators and in-flight performance measurement devices allow investigation of the still-unresolved issues.

Some foundational aspects of quantum computers and quantum robots.

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

Benioff, P.; Physics

1998-01-01

This paper addresses foundational issues related to quantum computing. The need for a universally valid theory such as quantum mechanics to describe to some extent its own validation is noted. This includes quantum mechanical descriptions of systems that do theoretical calculations (i.e. quantum computers) and systems that perform experiments. Quantum robots interacting with an environment are a small first step in this direction. Quantum robots are described here as mobile quantum systems with on-board quantum computers that interact with environments. Included are discussions on the carrying out of tasks and the division of tasks into computation and action phases. Specificmore » models based on quantum Turing machines are described. Differences and similarities between quantum robots plus environments and quantum computers are discussed.« less

Proceedings of the Workshop on Space Telerobotics, volume 1

NASA Technical Reports Server (NTRS)

Rodriguez, G. (Editor)

1987-01-01

These proceedings report the results of a workshop on space telerobotics, which was held at the Jet Propulsion Laboratory, January 20-22, 1987. Sponsored by the NASA Office of Aeronautics and Space Technology (OAST), the Workshop reflected NASA's interest in developing new telerobotics technology for automating the space systems planned for the 1990s and beyond. The workshop provided a window into NASA telerobotics research, allowing leading researchers in telerobotics to exchange ideas on manipulation, control, system architectures, artificial intelligence, and machine sensing. One of the objectives was to identify important unsolved problems of current interest. The workshop consisted of surveys, tutorials, and contributed papers of both theoretical and practical interest. Several sessions were held on the themes of sensing and perception, control execution, operator interface, planning and reasoning, and system architecture.

Theoretical Analysis of Spacing Parameters of Anisotropic 3D Surface Roughness

NASA Astrophysics Data System (ADS)

Rudzitis, J.; Bulaha, N.; Lungevics, J.; Linins, O.; Berzins, K.

2017-04-01

The authors of the research have analysed spacing parameters of anisotropic 3D surface roughness crosswise to machining (friction) traces RSm1 and lengthwise to machining (friction) traces RSm2. The main issue arises from the RSm2 values being limited by values of sampling length l in the measuring devices; however, on many occasions RSm2 values can exceed l values. Therefore, the mean spacing values of profile irregularities in the longitudinal direction in many cases are not reliable and they should be determined by another method. Theoretically, it is proved that anisotropic surface roughness anisotropy coefficient c=RSm1/RSm2 equals texture aspect ratio Str, which is determined by surface texture standard EN ISO 25178-2. This allows using parameter Str to determine mean spacing of profile irregularities and estimate roughness anisotropy.

Toward Intelligent Machine Learning Algorithms

DTIC Science & Technology

1988-05-01

Machine learning is recognized as a tool for improving the performance of many kinds of systems, yet most machine learning systems themselves are not...directed systems, and with the addition of a knowledge store for organizing and maintaining knowledge to assist learning, a learning machine learning (L...ML) algorithm is possible. The necessary components of L-ML systems are presented along with several case descriptions of existing machine learning systems

The Necessity of Machine Learning and Epistemology in the Development of Categorization Theories: A Case Study in Prototype-Exemplar Debate

NASA Astrophysics Data System (ADS)

Gagliardi, Francesco

In the present paper we discuss some aspects of the development of categorization theories concerning cognitive psychology and machine learning. We consider the thirty-year debate between prototype-theory and exemplar-theory in the studies of cognitive psychology regarding the categorization processes. We propose this debate is ill-posed, because it neglects some theoretical and empirical results of machine learning about the bias-variance theorem and the existence of some instance-based classifiers which can embed models subsuming both prototype and exemplar theories. Moreover this debate lies on a epistemological error of pursuing a, so called, experimentum crucis. Then we present how an interdisciplinary approach, based on synthetic method for cognitive modelling, can be useful to progress both the fields of cognitive psychology and machine learning.

Performance prediction: A case study using a multi-ring KSR-1 machine

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhu, Jianping

1995-01-01

While computers with tens of thousands of processors have successfully delivered high performance power for solving some of the so-called 'grand-challenge' applications, the notion of scalability is becoming an important metric in the evaluation of parallel machine architectures and algorithms. In this study, the prediction of scalability and its application are carefully investigated. A simple formula is presented to show the relation between scalability, single processor computing power, and degradation of parallelism. A case study is conducted on a multi-ring KSR1 shared virtual memory machine. Experimental and theoretical results show that the influence of topology variation of an architecture is predictable. Therefore, the performance of an algorithm on a sophisticated, heirarchical architecture can be predicted and the best algorithm-machine combination can be selected for a given application.

Application of variable teeth pitch face mill as chatter suppression method for non-rigid technological system

NASA Astrophysics Data System (ADS)

Svinin, V. M.; Savilov, A. V.

2018-03-01

The article describes the results of experimental studies on the effects of variation type for variable teeth pitches on low-rigidity workpiece chatter suppression efficiency in a feed direction and in a direction of the normal to the machined surface. Mill operation performance was identified by comparing the amplitudes of dominant chatter harmonics using constant and variable teeth pitches. The following variable pitch formation variants were studied: alternative, linear rising, and linear rising falling. The angle difference of adjacent teeth pitches ranged from 0 to 10°, from 5 to 8° and from 5 to 10° with interval of 1°. The experiments showed that for all variants, machining dynamics performance resulted from the difference of adjacent pitches corresponding to a half the chatter wavelength along the cutting surface. The alternative nature of a variable teeth pitch is most efficient as it almost completely suppresses the chatters. Theoretical explanations of the results are presented

Cascades in Compartments: En Route to Machine-Assisted Biotechnology.

PubMed

Rabe, Kersten S; Müller, Joachim; Skoupi, Marc; Niemeyer, Christof M

2017-10-23

Biological compartmentalization is a fundamental principle of life that allows cells to metabolize, propagate, or communicate with their environment. Much research is devoted to understanding this basic principle and to harness biomimetic compartments and catalytic cascades as tools for technological processes. This Review summarizes the current state-of-the-art of these developments, with a special emphasis on length scales, mass transport phenomena, and molecular scaffolding approaches, ranging from small cross-linkers over proteins and nucleic acids to colloids and patterned surfaces. We conclude that the future exploration and exploitation of these complex systems will largely benefit from technical solutions for the integrated, machine-assisted development and maintenance of a next generation of biotechnological processes. These goals should be achievable by implementing microfluidics, robotics, and added manufacturing techniques supplemented by theoretical simulations as well as computer-aided process modeling based on big data obtained from multiscale experimental analyses. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sensory motor remapping of space in human–machine interfaces

PubMed Central

Mussa-Ivaldi, Ferdinando A.; Casadio, Maura; Danziger, Zachary C.; Mosier, Kristine M.; Scheidt, Robert A.

2012-01-01

Studies of adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. These studies have also pointed out that adaptation to novel dynamics is aimed at preserving the trajectories of a controlled endpoint, either the hand of a subject or a transported object. We review some of these experiments and present more recent studies aimed at understanding how the motor system forms representations of the physical space in which actions take place. An extensive line of investigations in visual information processing has dealt with the issue of how the Euclidean properties of space are recovered from visual signals that do not appear to possess these properties. The same question is addressed here in the context of motor behavior and motor learning by observing how people remap hand gestures and body motions that control the state of an external device. We present some theoretical considerations and experimental evidence about the ability of the nervous system to create novel patterns of coordination that are consistent with the representation of extrapersonal space. We also discuss the perspective of endowing human–machine interfaces with learning algorithms that, combined with human learning, may facilitate the control of powered wheelchairs and other assistive devices. PMID:21741543

Fundamental studies on initiation and evolution of multi-channel discharges and their application to next generation pulsed power machines.

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

Schwarz, Jens; Savage, Mark E.; Lucero, Diego Jose

Future pulsed power systems may rely on linear transformer driver (LTD) technology. The LTD's will be the building blocks for a driver that can deliver higher current than the Z-Machine. The LTD's would require tens of thousands of low inductance ( %3C 85nH), high voltage (200 kV DC) switches with high reliability and long lifetime ( 10 4 shots). Sandia's Z-Machine employs 36 megavolt class switches that are laser triggered by a single channel discharge. This is feasible for tens of switches but the high inductance and short switch life- time associated with the single channel discharge are undesirable formore » future machines. Thus the fundamental problem is how to lower inductance and losses while increasing switch life- time and reliability. These goals can be achieved by increasing the number of current-carrying channels. The rail gap switch is ideal for this purpose. Although those switches have been extensively studied during the past decades, each effort has only characterized a particular switch. There is no comprehensive understanding of the underlying physics that would allow predictive capability for arbitrary switch geometry. We have studied rail gap switches via an extensive suite of advanced diagnostics in synergy with theoretical physics and advanced modeling capability. Design and topology of multichannel switches as they relate to discharge dynamics are investigated. This involves electrically and optically triggered rail gaps, as well as discrete multi-site switch concepts.« less

Disc-geometry homopolar synchronous machine

NASA Astrophysics Data System (ADS)

Evans, P. D.; Eastham, J. F.

1980-09-01

Results of an experimental and theoretical investigation of a disc-geometry homopolar synchronous machine with field excitation on the primary side are presented. The unlaminated mild-steel rotor contains no windings and is brushless. The prototype machine produces approximately 7.5 kW of mechanical output at 3000 rev/min, with a product of power factor and efficiency greater than 0.7. The construction of the stator core is unusual and incorporates both laminated and unlaminated portions. The magnetic circuit is also arranged to minimize the axial force between the stator and rotor. A novel rotor design which achieves a reduced quadrature-axis reactance is shown experimentally to be superior to the conventional homopolar rotor.

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.

Machine learning with quantum relative entropy

NASA Astrophysics Data System (ADS)

Tsuda, Koji

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

NASA Astrophysics Data System (ADS)

Khawaja, Taimoor Saleem

A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior and any abnormal or novel data during real-time operation. The results of the scheme are interpreted as a posterior probability of health (1 - probability of fault). As shown through two case studies in Chapter 3, the scheme is well suited for diagnosing imminent faults in dynamical non-linear systems. Finally, the failure prognosis scheme is based on an incremental weighted Bayesian LS-SVR machine. It is particularly suited for online deployment given the incremental nature of the algorithm and the quick optimization problem solved in the LS-SVR algorithm. By way of kernelization and a Gaussian Mixture Modeling (GMM) scheme, the algorithm can estimate "possibly" non-Gaussian posterior distributions for complex non-linear systems. An efficient regression scheme associated with the more rigorous core algorithm allows for long-term predictions, fault growth estimation with confidence bounds and remaining useful life (RUL) estimation after a fault is detected. The leading contributions of this thesis are (a) the development of a novel Bayesian Anomaly Detector for efficient and reliable Fault Detection and Identification (FDI) based on Least Squares Support Vector Machines, (b) the development of a data-driven real-time architecture for long-term Failure Prognosis using Least Squares Support Vector Machines, (c) Uncertainty representation and management using Bayesian Inference for posterior distribution estimation and hyper-parameter tuning, and finally (d) the statistical characterization of the performance of diagnosis and prognosis algorithms in order to relate the efficiency and reliability of the proposed schemes.

Man-systems integration and the man-machine interface

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

1990-01-01

Viewgraphs on man-systems integration and the man-machine interface are presented. Man-systems integration applies the systems' approach to the integration of the user and the machine to form an effective, symbiotic Man-Machine System (MMS). A MMS is a combination of one or more human beings and one or more physical components that are integrated through the common purpose of achieving some objective. The human operator interacts with the system through the Man-Machine Interface (MMI).

Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

PubMed Central

Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

2016-01-01

Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing.

PubMed

Fujiwara, M; Waseda, A; Nojima, R; Moriai, S; Ogata, W; Sasaki, M

2016-07-01

Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir's (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

A game theoretic framework for incentive-based models of intrinsic motivation in artificial systems

PubMed Central

Merrick, Kathryn E.; Shafi, Kamran

2013-01-01

An emerging body of research is focusing on understanding and building artificial systems that can achieve open-ended development influenced by intrinsic motivations. In particular, research in robotics and machine learning is yielding systems and algorithms with increasing capacity for self-directed learning and autonomy. Traditional software architectures and algorithms are being augmented with intrinsic motivations to drive cumulative acquisition of knowledge and skills. Intrinsic motivations have recently been considered in reinforcement learning, active learning and supervised learning settings among others. This paper considers game theory as a novel setting for intrinsic motivation. A game theoretic framework for intrinsic motivation is formulated by introducing the concept of optimally motivating incentive as a lens through which players perceive a game. Transformations of four well-known mixed-motive games are presented to demonstrate the perceived games when players' optimally motivating incentive falls in three cases corresponding to strong power, affiliation and achievement motivation. We use agent-based simulations to demonstrate that players with different optimally motivating incentive act differently as a result of their altered perception of the game. We discuss the implications of these results both for modeling human behavior and for designing artificial agents or robots. PMID:24198797

A game theoretic framework for incentive-based models of intrinsic motivation in artificial systems.

PubMed

Merrick, Kathryn E; Shafi, Kamran

2013-01-01

An emerging body of research is focusing on understanding and building artificial systems that can achieve open-ended development influenced by intrinsic motivations. In particular, research in robotics and machine learning is yielding systems and algorithms with increasing capacity for self-directed learning and autonomy. Traditional software architectures and algorithms are being augmented with intrinsic motivations to drive cumulative acquisition of knowledge and skills. Intrinsic motivations have recently been considered in reinforcement learning, active learning and supervised learning settings among others. This paper considers game theory as a novel setting for intrinsic motivation. A game theoretic framework for intrinsic motivation is formulated by introducing the concept of optimally motivating incentive as a lens through which players perceive a game. Transformations of four well-known mixed-motive games are presented to demonstrate the perceived games when players' optimally motivating incentive falls in three cases corresponding to strong power, affiliation and achievement motivation. We use agent-based simulations to demonstrate that players with different optimally motivating incentive act differently as a result of their altered perception of the game. We discuss the implications of these results both for modeling human behavior and for designing artificial agents or robots.

Context-aware brain-computer interfaces: exploring the information space of user, technical system and environment

NASA Astrophysics Data System (ADS)

Zander, T. O.; Jatzev, S.

2012-02-01

Brain-computer interface (BCI) systems are usually applied in highly controlled environments such as research laboratories or clinical setups. However, many BCI-based applications are implemented in more complex environments. For example, patients might want to use a BCI system at home, and users without disabilities could benefit from BCI systems in special working environments. In these contexts, it might be more difficult to reliably infer information about brain activity, because many intervening factors add up and disturb the BCI feature space. One solution for this problem would be adding context awareness to the system. We propose to augment the available information space with additional channels carrying information about the user state, the environment and the technical system. In particular, passive BCI systems seem to be capable of adding highly relevant context information—otherwise covert aspects of user state. In this paper, we present a theoretical framework based on general human-machine system research for adding context awareness to a BCI system. Building on that, we present results from a study on a passive BCI, which allows access to the covert aspect of user state related to the perceived loss of control. This study is a proof of concept and demonstrates that context awareness could beneficially be implemented in and combined with a BCI system or a general human-machine system. The EEG data from this experiment are available for public download at www.phypa.org. Parts of this work have already been presented in non-journal publications. This will be indicated specifically by appropriate references in the text.

Biomechanical consequences of callus development in Hoffmann, Wagner, Orthofix and Ilizarov external fixators.

PubMed

Juan, J A; Prat, J; Vera, P; Hoyos, J V; Sánchez-Lacuesta, J; Peris, J L; Dejoz, R; Alepuz, R

1992-09-01

A theoretical analysis by a finite elements model (FEM) of some external fixators (Hoffmann, Wagner, Orthofix and Ilizarov) was carried out. This study considered a logarithmic progress of callus elastic characteristics. A standard configuration of each fixator was defined where design and application characteristics were modified. A comparison among standard configurations and influence of every variation was made with regard to displacement and load transmission at the fracture site. An experimental evaluation of standard configurations was performed with a testing machine. After experimental validation of the theoretical model was achieved, an application of physiological loads which act on a fractured limb during normal gait was analysed. A minimal contribution from an external fixator to the total rigidity of the bone-callus-fixator system was assessed when a callus showing minimum elastic characteristics had just been established. Insufficient rigidity from the fixation devices to assure an adequate immobilization during the early stages of fracture healing was verified. However, regardless of the external fixator, callus development was the overriding element for the rigidity of the fixator-bone system.

Recognizing sights, smells, and sounds with gnostic fields.

PubMed

Kanan, Christopher

2013-01-01

Mammals rely on vision, audition, and olfaction to remotely sense stimuli in their environment. Determining how the mammalian brain uses this sensory information to recognize objects has been one of the major goals of psychology and neuroscience. Likewise, researchers in computer vision, machine audition, and machine olfaction have endeavored to discover good algorithms for stimulus classification. Almost 50 years ago, the neuroscientist Jerzy Konorski proposed a theoretical model in his final monograph in which competing sets of "gnostic" neurons sitting atop sensory processing hierarchies enabled stimuli to be robustly categorized, despite variations in their presentation. Much of what Konorski hypothesized has been remarkably accurate, and neurons with gnostic-like properties have been discovered in visual, aural, and olfactory brain regions. Surprisingly, there have not been any attempts to directly transform his theoretical model into a computational one. Here, I describe the first computational implementation of Konorski's theory. The model is not domain specific, and it surpasses the best machine learning algorithms on challenging image, music, and olfactory classification tasks, while also being simpler. My results suggest that criticisms of exemplar-based models of object recognition as being computationally intractable due to limited neural resources are unfounded.

Recognizing Sights, Smells, and Sounds with Gnostic Fields

PubMed Central

Kanan, Christopher

2013-01-01

Mammals rely on vision, audition, and olfaction to remotely sense stimuli in their environment. Determining how the mammalian brain uses this sensory information to recognize objects has been one of the major goals of psychology and neuroscience. Likewise, researchers in computer vision, machine audition, and machine olfaction have endeavored to discover good algorithms for stimulus classification. Almost 50 years ago, the neuroscientist Jerzy Konorski proposed a theoretical model in his final monograph in which competing sets of “gnostic” neurons sitting atop sensory processing hierarchies enabled stimuli to be robustly categorized, despite variations in their presentation. Much of what Konorski hypothesized has been remarkably accurate, and neurons with gnostic-like properties have been discovered in visual, aural, and olfactory brain regions. Surprisingly, there have not been any attempts to directly transform his theoretical model into a computational one. Here, I describe the first computational implementation of Konorski's theory. The model is not domain specific, and it surpasses the best machine learning algorithms on challenging image, music, and olfactory classification tasks, while also being simpler. My results suggest that criticisms of exemplar-based models of object recognition as being computationally intractable due to limited neural resources are unfounded. PMID:23365648

Damping torque analysis of VSC-based system utilizing power synchronization control

NASA Astrophysics Data System (ADS)

Fu, Q.; Du, W. J.; Zheng, K. Y.; Wang, H. F.

2017-05-01

Power synchronization control is a new control strategy of VSC-HVDC for connecting a weak power system. Different from the vector control method, this control method utilizes the internal synchronization mechanism in ac systems, in principle, similar to the operation of a synchronous machine. So that the parameters of controllers in power synchronization control will change the electromechanical oscillation modes and make an impact on the transient stability of power system. This paper present a mathematical model for small-signal stability analysis of VSC station used power synchronization control and analyse the impact of the dynamic interactions by calculating the contribution of the damping torque from the power synchronization control, besides, the parameters of controllers which correspond to damping torque and synchronous torque in the power synchronization control is defined respectively. At the end of the paper, an example power system is presented to demonstrate and validate the theoretical analysis and associated conclusions are made.

Data Structures in Natural Computing: Databases as Weak or Strong Anticipatory Systems

NASA Astrophysics Data System (ADS)

Rossiter, B. N.; Heather, M. A.

2004-08-01

Information systems anticipate the real world. Classical databases store, organise and search collections of data of that real world but only as weak anticipatory information systems. This is because of the reductionism and normalisation needed to map the structuralism of natural data on to idealised machines with von Neumann architectures consisting of fixed instructions. Category theory developed as a formalism to explore the theoretical concept of naturality shows that methods like sketches arising from graph theory as only non-natural models of naturality cannot capture real-world structures for strong anticipatory information systems. Databases need a schema of the natural world. Natural computing databases need the schema itself to be also natural. Natural computing methods including neural computers, evolutionary automata, molecular and nanocomputing and quantum computation have the potential to be strong. At present they are mainly at the stage of weak anticipatory systems.

Manufacturing Laboratory for Next Generation Engineers

DTIC Science & Technology

2013-12-16

automated CNC machines, rapid prototype systems, robotic assembly systems, metrology , and non-traditional systems such as a waterjet cutter, EDM machine...CNC machines, rapid prototype systems, robotic assembly systems, metrology , and non-traditional systems such as a waterjet cutter, EDM machine, plasma...System Metrology and Quality Control Equipment - This area already had a CMM and other well known quality control instrumentation. It has been enhanced

In-situ roundness measurement and correction for pin journals in oscillating grinding machines

NASA Astrophysics Data System (ADS)

Yu, Hongxiang; Xu, Mengchen; Zhao, Jie

2015-01-01

In the mass production of vehicle-engine crankshafts, pin chasing grinding using oscillating grinding machines is a widely accepted method to achieve flexible and efficient performance. However, the eccentric movement of pin journals makes it difficult to develop an in-process roundness measurement scheme for the improvement of contour precision. Here, a new in-situ roundness measurement strategy is proposed with high scanning speed. The measuring mechanism is composed of a V-block and an adaptive telescopic support. The swing pattern of the telescopic support and the V-block is analysed for an equal angle-interval signal sampling. Hence roundness error signal is extracted in frequency domain using a small-signal model of the V-block roundness measurement method and the Fast Fourier Transformation. To implement the roundness data in the CNC coordinate system of an oscillating grinding machine, a transformation function is derived according to the motion model of pin chasing grinding methodology. Computer simulation reveals the relationship between the rotational position of the crankshaft component and the scanning angle of the displacement probe on the V-block, as well as the influence introduced by the rotation centre drift. Prototype investigation indicates the validity of the theoretical analysis and the feasibility of the new strategy.

Biocompatibility of hydroxyapatite scaffolds processed by lithography-based additive manufacturing.

PubMed

Tesavibul, Passakorn; Chantaweroad, Surapol; Laohaprapanon, Apinya; Channasanon, Somruethai; Uppanan, Paweena; Tanodekaew, Siriporn; Chalermkarnnon, Prasert; Sitthiseripratip, Kriskrai

2015-01-01

The fabrication of hydroxyapatite scaffolds for bone tissue engineering applications by using lithography-based additive manufacturing techniques has been introduced due to the abilities to control porous structures with suitable resolutions. In this research, the use of hydroxyapatite cellular structures, which are processed by lithography-based additive manufacturing machine, as a bone tissue engineering scaffold was investigated. The utilization of digital light processing system for additive manufacturing machine in laboratory scale was performed in order to fabricate the hydroxyapatite scaffold, of which biocompatibilities were eventually evaluated by direct contact and cell-culturing tests. In addition, the density and compressive strength of the scaffolds were also characterized. The results show that the hydroxyapatite scaffold at 77% of porosity with 91% of theoretical density and 0.36 MPa of the compressive strength are able to be processed. In comparison with a conventionally sintered hydroxyapatite, the scaffold did not present any cytotoxic signs while the viability of cells at 95.1% was reported. After 14 days of cell-culturing tests, the scaffold was able to be attached by pre-osteoblasts (MC3T3-E1) leading to cell proliferation and differentiation. The hydroxyapatite scaffold for bone tissue engineering was able to be processed by the lithography-based additive manufacturing machine while the biocompatibilities were also confirmed.

The laser micro-machining system for diamond anvil cell experiments and general precision machining applications at the High Pressure Collaborative Access Team

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

Hrubiak, Rostislav; Sinogeikin, Stanislav; Rod, Eric

We have designed and constructed a new system for micro-machining parts and sample assemblies used for diamond anvil cells and general user operations at the High Pressure Collaborative Access Team, sector 16 of the Advanced Photon Source. The new micro-machining system uses a pulsed laser of 400 ps pulse duration, ablating various materials without thermal melting, thus leaving a clean edge. With optics designed for a tight focus, the system can machine holes any size larger than 3 μm in diameter. Unlike a standard electrical discharge machining drill, the new laser system allows micro-machining of non-conductive materials such as: amorphousmore » boron and silicon carbide gaskets, diamond, oxides, and other materials including organic materials such as polyimide films (i.e., Kapton). An important feature of the new system is the use of gas-tight or gas-flow environmental chambers which allow the laser micro-machining to be done in a controlled (e.g., inert gas) atmosphere to prevent oxidation and other chemical reactions in air sensitive materials. The gas-tight workpiece enclosure is also useful for machining materials with known health risks (e.g., beryllium). Specialized control software with a graphical interface enables micro-machining of custom 2D and 3D shapes. The laser-machining system was designed in a Class 1 laser enclosure, i.e., it includes laser safety interlocks and computer controls and allows for routine operation. Though initially designed mainly for machining of the diamond anvil cell gaskets, the laser-machining system has since found many other micro-machining applications, several of which are presented here.« less

Computer network defense system

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

Urias, Vincent; Stout, William M. S.; Loverro, Caleb

A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves networkmore » connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.« less

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-10

... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in Underground Coal... Detection Systems for Continuous Mining Machines in Underground Coal Mines. MSHA conducted hearings on...

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

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... Agency's proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in... proposed rule for Proximity Detection Systems on Continuous Mining Machines in Underground Coal Mines. Due...

Compact Microscope Imaging System with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The figure presents selected views of a compact microscope imaging system (CMIS) that includes a miniature video microscope, a Cartesian robot (a computer- controlled three-dimensional translation stage), and machine-vision and control subsystems. The CMIS was built from commercial off-the-shelf instrumentation, computer hardware and software, and custom machine-vision software. The machine-vision and control subsystems include adaptive neural networks that afford a measure of artificial intelligence. The CMIS can perform several automated tasks with accuracy and repeatability . tasks that, heretofore, have required the full attention of human technicians using relatively bulky conventional microscopes. In addition, the automation and control capabilities of the system inherently include a capability for remote control. Unlike human technicians, the CMIS is not at risk of becoming fatigued or distracted: theoretically, it can perform continuously at the level of the best human technicians. In its capabilities for remote control and for relieving human technicians of tedious routine tasks, the CMIS is expected to be especially useful in biomedical research, materials science, inspection of parts on industrial production lines, and space science. The CMIS can automatically focus on and scan a microscope sample, find areas of interest, record the resulting images, and analyze images from multiple samples simultaneously. Automatic focusing is an iterative process: The translation stage is used to move the microscope along its optical axis in a succession of coarse, medium, and fine steps. A fast Fourier transform (FFT) of the image is computed at each step, and the FFT is analyzed for its spatial-frequency content. The microscope position that results in the greatest dispersal of FFT content toward high spatial frequencies (indicating that the image shows the greatest amount of detail) is deemed to be the focal position.

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.

A mechanical Turing machine: blueprint for a biomolecular computer

PubMed Central

Shapiro, Ehud

2012-01-01

We describe a working mechanical device that embodies the theoretical computing machine of Alan Turing, and as such is a universal programmable computer. The device operates on three-dimensional building blocks by applying mechanical analogues of polymer elongation, cleavage and ligation, movement along a polymer, and control by molecular recognition unleashing allosteric conformational changes. Logically, the device is not more complicated than biomolecular machines of the living cell, and all its operations are part of the standard repertoire of these machines; hence, a biomolecular embodiment of the device is not infeasible. If implemented, such a biomolecular device may operate in vivo, interacting with its biochemical environment in a program-controlled manner. In particular, it may ‘compute’ synthetic biopolymers and release them into its environment in response to input from the environment, a capability that may have broad pharmaceutical and biological applications. PMID:22649583

Survey of Mass Storage Systems

DTIC Science & Technology

1975-09-01

software that Pre- cision Instruments can provide. System Name: IBM 3850 Mass Storage System Manufacturer and Location: International Business Machines...34 Datamation, pp. 52-58, October 1973. 15 17. International Business Machines, IBM 3850 Mass Storage System Facts Folder, White Plains, NY, n.d. 18... International Business Machines, Introduction to the IBM 3850 Mass Storage System (MSS), White Plains, NY, n.d. 19. International Business Machines

Physics through the 1990s: Plasmas and fluids

NASA Technical Reports Server (NTRS)

1986-01-01

The volume contains recommendations for programs in, and government support of, plasma and fluid physics. Four broad areas are covered: the physics of fluids, general plasma physics, fusion, and space and astrophysical plasmas. In the first section, the accomplishments of fluid physics and a detailed review of its sub-fields, such as combustion, non-Newtonian fluids, turbulence, aerodynamics, and geophysical fluid dynamics, are described. The general plasma physics section deals with the wide scope of the theoretical concepts involved in plasma research, and with the machines; intense beam systems, collective and laser-driven accelerators, and the associated diagnostics. The section on the fusion plasma research program examines confinement and heating systems, such as Tokamaks, magnetic mirrors, and inertial-confinement systems, and several others. Finally, theory and experiment in space and astrophysical plasma research is detailed, ranging from the laboratory to the solar system and beyond. A glossary is included.

Modified Mahalanobis Taguchi System for Imbalance Data Classification

PubMed Central

2017-01-01

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

Foundations and Emerging Paradigms for Computing in Living Cells.

PubMed

Ma, Kevin C; Perli, Samuel D; Lu, Timothy K

2016-02-27

Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits. Copyright © 2016. Published by Elsevier Ltd.

Eddy current loss analysis of open-slot fault-tolerant permanent-magnet machines based on conformal mapping method

NASA Astrophysics Data System (ADS)

Ji, Jinghua; Luo, Jianhua; Lei, Qian; Bian, Fangfang

2017-05-01

This paper proposed an analytical method, based on conformal mapping (CM) method, for the accurate evaluation of magnetic field and eddy current (EC) loss in fault-tolerant permanent-magnet (FTPM) machines. The aim of modulation function, applied in CM method, is to change the open-slot structure into fully closed-slot structure, whose air-gap flux density is easy to calculate analytically. Therefore, with the help of Matlab Schwarz-Christoffel (SC) Toolbox, both the magnetic flux density and EC density of FTPM machine are obtained accurately. Finally, time-stepped transient finite-element method (FEM) is used to verify the theoretical analysis, showing that the proposed method is able to predict the magnetic flux density and EC loss precisely.

Rotational magnetization: Problems in experimental and theoretical studies of electrical steels and amorphous magnetic materials

NASA Astrophysics Data System (ADS)

Moses, A. J.

1994-03-01

Flux rotating in the plane of laminations of amorphous materials or electrical steels can cause additional losses in electrical machines. To make full use of laboratory rotational magnetization studies, a better understanding of the nature of rotational flux in machine cores is needed. This paper highlights the need for careful laboratory simulation of the conditions which occur in actual machines. Single specimen tests must produce uniform flux over a given measuring region and output from field and flux sensors need careful analysis. Differences between thermal and flux sensing methods are shown as well as anomalies caused when the magnetisation direction is reversed in an anistropic specimen. Methods of overcoming these problems are proposed.

A biologically consistent hierarchical framework for self-referencing survivalist computation

NASA Astrophysics Data System (ADS)

Cottam, Ron; Ranson, Willy; Vounckx, Roger

2000-05-01

Extensively scaled formally rational hardware and software are indirectly fallible, at the very least through temporal restrictions on the evaluation of their correctness. In addition, the apparent inability of formal rationality to successfully describe living systems as anything other than inanimate structures suggests that the development of self-referencing computational machines will require a different approach. There is currently a strong movement towards the adoption of semiotics as a descriptive medium in theoretical biology. We present a related computational semiosic construction (1, 2) consistent with evolutionary hierarchical emergence (3), which may serve as a framework for implementing anticipatory-oriented survivalist processing in real environments.

Asymmetry identification in rigid rotating bodies—Theory and experiment

NASA Astrophysics Data System (ADS)

Bucher, Izhak; Shomer, Ofer

2013-12-01

Asymmetry and anisotropy are important parameters in rotating devices that can cause instability; indicate a manufacturing defect or a developing fault. The present paper discusses an identification method capable of detecting minute levels of asymmetry by exploiting the unique dynamics of parametric excitation caused by asymmetry and rotation. The detection relies on rigid body dynamics without resorting to nonlinear vibration analysis, and the natural dynamics of elastically supported systems is exploited in order to increase the sensitivity to asymmetry. It is possible to isolate asymmetry from other rotation-induced phenomena like unbalance. An asymmetry detection machine which was built in the laboratory demonstrates the method alongside theoretical analysis.

Minimization of deviations of gear real tooth surfaces determined by coordinate measurements

NASA Technical Reports Server (NTRS)

Litvin, F. L.; Kuan, C.; Wang, J.-C.; Handschuh, R. F.; Masseth, J.; Maruyama, N.

1992-01-01

The deviations of a gear's real tooth surface from the theoretical surface are determined by coordinate measurements at the grid of the surface. A method was developed to transform the deviations from Cartesian coordinates to those along the normal at the measurement locations. Equations are derived that relate the first order deviations with the adjustment to the manufacturing machine-tool settings. The deviations of the entire surface are minimized. The minimization is achieved by application of the least-square method for an overdetermined system of linear equations. The proposed method is illustrated with a numerical example for hypoid gear and pinion.

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA

PubMed Central

Currin, Andrew; Korovin, Konstantin; Ababi, Maria; Roper, Katherine; Kell, Douglas B.; Day, Philip J.

2017-01-01

The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and in vitro molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman ‘there's plenty of room at the bottom’. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy. PMID:28250099

Computer Associates International, CA-ACF2/VM Release 3.1

DTIC Science & Technology

1987-09-09

Associates CA-ACF2/VM Bibliography International Business Machines Corporation, IBM Virtual Machine/Directory Maintenance Program Logic Manual...publication number LY20-0889 International Business Machines International Business Machines Corporation, IBM System/370 Principles of Operation...publication number GA22-7000 International Business Machines Corporation, IBM Virtual Machine/Directory Maintenance Installation and System Administrator’s

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, William H.; Ganoe, Carl W.

1999-01-01

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation thereof. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine.

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, W.H.; Ganoe, C.W.

1999-08-17

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine. 3 figs.

The Critical Compression Load for a Universal Testing Machine When the Specimen Is Loaded Through Knife Edges

NASA Technical Reports Server (NTRS)

Lundquist, Eugene E; Schwartz, Edward B

1942-01-01

The results of a theoretical and experimental investigation to determine the critical compression load for a universal testing machine are presented for specimens loaded through knife edges. The critical load for the testing machine is the load at which one of the loading heads becomes laterally instable in relation to the other. For very short specimens the critical load was found to be less than the rated capacity given by the manufacturer for the machine. A load-length diagram is proposed for defining the safe limits of the test region for the machine. Although this report is particularly concerned with a universal testing machine of a certain type, the basic theory which led to the derivation of the general equation for the critical load, P (sub cr) = alpha L can be applied to any testing machine operated in compression where the specimen is loaded through knife edges. In this equation, L is the length of the specimen between knife edges and alpha is the force necessary to displace the upper end of the specimen unit horizontal distance relative to the lower end of the specimen in a direction normal to the knife edges through which the specimen is loaded.

Theoretical Investigation of oxides for batteries and fuel cell applications

NASA Astrophysics Data System (ADS)

Ganesh, Panchapakesan; Lubimtsev, Andrew A.; Balachandran, Janakiraman

I will present theoretical studies of Li-ion and proton-conducting oxides using a combination of theory and computations that involve Density Functional Theory based atomistic modeling, cluster-expansion based studies, global optimization, high-throughput computations and machine learning based investigation of ionic transport in oxide materials. In Li-ion intercalated oxides, we explain the experimentally observed (Nature Materials 12, 518-522 (2013)) 'intercalation pseudocapacitance' phenomenon, and explain why Nb2O5 is special to show this behavior when Li-ions are intercalated (J. Mater. Chem. A, 2013,1, 14951-14956), but not when Na-ions are used. In addition, we explore Li-ion intercalation theoretically in VO2 (B) phase, which is somewhat structurally similar to Nb2O5 and predict an interesting role of site-trapping on the voltage and capacity of the material, validated by ongoing experiments. Computations of proton conducting oxides explain why Y-doped BaZrO3 , one of the fastest proton conducting oxide, shows a decrease in conductivity above 20% Y-doping. Further, using high throughput computations and machine learning tools we discover general principles to improve proton conductivity. Acknowledgements: LDRD at ORNL and CNMS at ORNL

Development of a 3-D X-ray system

NASA Astrophysics Data System (ADS)

Evans, James Paul Owain

The interpretation of standard two-dimensional x-ray images by humans is often very difficult. This is due to the lack of visual cues to depth in an image which has been produced by transmitted radiation. The solution put forward in this research is to introduce binocular parallax, a powerful physiological depth cue, into the resultant shadowgraph x-ray image. This has been achieved by developing a binocular stereoscopic x-ray imaging technique, which can be used for both visual inspection by human observers and also for the extraction of three-dimensional co-ordinate information. The technique is implemented in the design and development of two experimental x-ray systems and also the development of measurement algorithms. The first experimental machine is based on standard linear x-ray detector arrays and was designed as an optimum configuration for visual inspection by human observers. However, it was felt that a combination of the 3-D visual inspection capability together with a measurement facility would enhance the usefulness of the technique. Therefore, both a theoretical and an empirical analysis of the co-ordinate measurement capability of the machine has been carried out. The measurement is based on close-range photogrammetric techniques. The accuracy of the measurement has been found to be of the order of 4mm in x, 3mm in y and 6mm in z. A second experimental machine was developed and based on the same technique as that used for the first machine. However, a major departure has been the introduction of a dual energy linear x-ray detector array which will allow, in general, the discrimination between organic and inorganic substances. The second design is a compromise between ease of visual inspection for human observers and optimum three-dimensional co-ordinate measurement capability. The system is part of an on going research programme into the possibility of introducing psychological depth cues into the resultant x-ray images. The research presented in this thesis was initiated to enhance the visual interpretation of complex x-ray images, specifically in response to problems encountered in the routine screening of freight by HM. Customs and Excise. This phase of the work culminated in the development of the first experimental machine. During this work the security industry was starting to adopt a new type of x-ray detector, namely the dual energy x-ray sensor. The Department of Transport made available funding to the Police Scientific Development Branch (P.S.D.B.), part of The Home Office Science and Technology Group, to investigate the possibility of utilising the dual energy sensor in a 3-D x-ray screening system. This phase of the work culminated in the development of the second experimental machine.

Machining of bone: Analysis of cutting force and surface roughness by turning process.

PubMed

Noordin, M Y; Jiawkok, N; Ndaruhadi, P Y M W; Kurniawan, D

2015-11-01

There are millions of orthopedic surgeries and dental implantation procedures performed every year globally. Most of them involve machining of bones and cartilage. However, theoretical and analytical study on bone machining is lagging behind its practice and implementation. This study views bone machining as a machining process with bovine bone as the workpiece material. Turning process which makes the basis of the actually used drilling process was experimented. The focus is on evaluating the effects of three machining parameters, that is, cutting speed, feed, and depth of cut, to machining responses, that is, cutting forces and surface roughness resulted by the turning process. Response surface methodology was used to quantify the relation between the machining parameters and the machining responses. The turning process was done at various cutting speeds (29-156 m/min), depths of cut (0.03 -0.37 mm), and feeds (0.023-0.11 mm/rev). Empirical models of the resulted cutting force and surface roughness as the functions of cutting speed, depth of cut, and feed were developed. Observation using the developed empirical models found that within the range of machining parameters evaluated, the most influential machining parameter to the cutting force is depth of cut, followed by feed and cutting speed. The lowest cutting force was obtained at the lowest cutting speed, lowest depth of cut, and highest feed setting. For surface roughness, feed is the most significant machining condition, followed by cutting speed, and with depth of cut showed no effect. The finest surface finish was obtained at the lowest cutting speed and feed setting. © IMechE 2015.

Pulsed Nd:YAG laser beam drilling: A review

NASA Astrophysics Data System (ADS)

Gautam, Girish Dutt; Pandey, Arun Kumar

2018-03-01

Laser beam drilling (LBD) is one of non contact type unconventional machining process that are employed in machining of stiff and high-strength materials, high strength temperature resistance materials such as; metal alloys, ceramics, composites and superalloys. Most of these materials are difficult-to-machine by using conventional machining methods. Also, the complex and precise holes may not be obtained by using the conventional machining processes which may be obtained by using unconventional machining processes. The laser beam drilling in one of the most important unconventional machining process that may be used for the machining of these materials with satisfactorily. In this paper, the attention is focused on the experimental and theoretical investigations on the pulsed Nd:YAG laser drilling of different categories of materials such as ferrous materials, non-ferrous materials, superalloys, composites and Ceramics. Moreover, the review has been emphasized by the use of pulsed Nd:YAG laser drilling of different materials in order to enhance productivity of this process without adverse effects on the drilled holes quality characteristics. Finally, the review is concluded with the possible scope in the area of pulsed Nd:YAG laser drilling. This review work may be very useful to the subsequent researchers in order to give an insight in the area of pulsed Nd:YAG laser drilling of different materials and research gaps available in this area.

Characteristics of Navy Medium-Weight High-Impact Shock Machine

DTIC Science & Technology

1951-09-14

Ar 2-4~ -C 0 ofoL "- oili 0jit -1 b. V’ A . -- c- MC a y - w CmLUA ~ E~8.9. - flb. A 9 Er IL v II - W43 4P " It IIf ~NRL REPORT I CHARACTERISTICS OF...this machine under specification operation. A comnarison of datta is intended to correlate this shock to shipboard shock experienced in actual combat...table reversal are discussed, and it is shown that this secondsry shock can be the largest under certain condition. Theoretical equations of motion are

Structural mechanics of 3-D braided preforms for composites. IV - The 4-step tubular braiding

NASA Technical Reports Server (NTRS)

Hammad, M.; El-Messery, M.; El-Shiekh, A.

1991-01-01

This paper presents the fundamentals of the 4-step 3D tubular braiding process and the structure of the preforms produced. Based on an idealized structural model, geometric relations between the structural parameters of the preform are analytically established. The effects of machine arrangement and operating conditions are discussed. Yarn retraction, yarn surface angle, outside diameter, and yarn volume fraction of the preform in terms of the pitch length, the inner diameter, and the machine arrangement are theoretically predicted and experimentally verified.

The in-situ 3D measurement system combined with CNC machine tools

NASA Astrophysics Data System (ADS)

Zhao, Huijie; Jiang, Hongzhi; Li, Xudong; Sui, Shaochun; Tang, Limin; Liang, Xiaoyue; Diao, Xiaochun; Dai, Jiliang

2013-06-01

With the development of manufacturing industry, the in-situ 3D measurement for the machining workpieces in CNC machine tools is regarded as the new trend of efficient measurement. We introduce a 3D measurement system based on the stereovision and phase-shifting method combined with CNC machine tools, which can measure 3D profile of the machining workpieces between the key machining processes. The measurement system utilizes the method of high dynamic range fringe acquisition to solve the problem of saturation induced by specular lights reflected from shiny surfaces such as aluminum alloy workpiece or titanium alloy workpiece. We measured two workpieces of aluminum alloy on the CNC machine tools to demonstrate the effectiveness of the developed measurement system.

Web Mining: Machine Learning for Web Applications.

ERIC Educational Resources Information Center

Chen, Hsinchun; Chau, Michael

2004-01-01

Presents an overview of machine learning research and reviews methods used for evaluating machine learning systems. Ways that machine-learning algorithms were used in traditional information retrieval systems in the "pre-Web" era are described, and the field of Web mining and how machine learning has been used in different Web mining…

Improved transistor-controlled and commutated brushless DC motors for electric vehicle propulsion

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Miller, R. H.; Nehl, T. W.; Nyamusa, T. A.

1983-01-01

The development, design, construction, and testing processes of two electronically (transistor) controlled and commutated permanent magnet brushless dc machine systems, for propulsion of electric vehicles are detailed. One machine system was designed and constructed using samarium cobalt for permanent magnets, which supply the rotor (field) excitation. Meanwhile, the other machine system was designed and constructed with strontium ferrite permanent magnets as the source of rotor (field) excitation. These machine systems were designed for continuous rated power output of 15 hp (11.2 kw), and a peak one minute rated power output of 35 hp (26.1 kw). Both power ratings are for a rated voltage of 115 volts dc, assuming a voltage drop in the source (battery) of about 5 volts. That is, an internal source voltage of 120 volts dc. Machine-power conditioner system computer-aided simulations were used extensively in the design process. These simulations relied heavily on the magnetic field analysis in these machines using the method of finite elements, as well as methods of modeling of the machine power conditioner system dynamic interaction. These simulation processes are detailed. Testing revealed that typical machine system efficiencies at 15 hp (11.2 kw) were about 88% and 84% for the samarium cobalt and strontium ferrite based machine systems, respectively. Both systems met the peak one minute rating of 35 hp.

Design and implementation of a system for laser assisted milling of advanced materials

NASA Astrophysics Data System (ADS)

Wu, Xuefeng; Feng, Gaocheng; Liu, Xianli

2016-09-01

Laser assisted machining is an effective method to machine advanced materials with the added benefits of longer tool life and increased material removal rates. While extensive studies have investigated the machining properties for laser assisted milling(LAML), few attempts have been made to extend LAML to machining parts with complex geometric features. A methodology for continuous path machining for LAML is developed by integration of a rotary and movable table into an ordinary milling machine with a laser beam system. The machining strategy and processing path are investigated to determine alignment of the machining path with the laser spot. In order to keep the material removal temperatures above the softening temperature of silicon nitride, the transformation is coordinated and the temperature interpolated, establishing a transient thermal model. The temperatures of the laser center and cutting zone are also carefully controlled to achieve optimal machining results and avoid thermal damage. These experiments indicate that the system results in no surface damage as well as good surface roughness, validating the application of this machining strategy and thermal model in the development of a new LAML system for continuous path processing of silicon nitride. The proposed approach can be easily applied in LAML system to achieve continuous processing and improve efficiency in laser assisted machining.

Development of TIF based figuring algorithm for deterministic pitch tool polishing

NASA Astrophysics Data System (ADS)

Yi, Hyun-Su; Kim, Sug-Whan; Yang, Ho-Soon; Lee, Yun-Woo

2007-12-01

Pitch is perhaps the oldest material used for optical polishing, leaving superior surface texture, and has been used widely in the optics shop floor. However, for its unpredictable controllability of removal characteristics, the pitch tool polishing has been rarely analysed quantitatively and many optics shops rely heavily on optician's "feel" even today. In order to bring a degree of process controllability to the pitch tool polishing, we added motorized tool motions to the conventional Draper type polishing machine and modelled the tool path in the absolute machine coordinate. We then produced a number of Tool Influence Function (TIF) both from an analytical model and a series of experimental polishing runs using the pitch tool. The theoretical TIFs agreed well with the experimental TIFs to the profile accuracy of 79 % in terms of its shape. The surface figuring algorithm was then developed in-house utilizing both theoretical and experimental TIFs. We are currently undertaking a series of trial figuring experiments to prove the performance of the polishing algorithm, and the early results indicate that the highly deterministic material removal control with the pitch tool can be achieved to a certain level of form error. The machine renovation, TIF theory and experimental confirmation, figuring simulation results are reported together with implications to deterministic polishing.

Security-aware Virtual Machine Allocation in the Cloud: A Game Theoretic Approach

DTIC Science & Technology

2015-01-13

predecessor, however, this paper used empirical evidence and actual data from running experiments on the Amazon EC2 cloud . They began by running all 5...is through effective VM allocation management of the cloud provider to ensure delivery of maximum security for all cloud users. The negative... Cloud : A Game Theoretic Approach 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

NASA Astrophysics Data System (ADS)

Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

2018-04-01

Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods through the evolutionary algorithms. In addition, experimental and statistical significance tests are carried out to study the applicability and effectiveness of the reviewed methods.

Teaching Camera Calibration by a Constructivist Methodology

ERIC Educational Resources Information Center

Samper, D.; Santolaria, J.; Pastor, J. J.; Aguilar, J. J.

2010-01-01

This article describes the Metrovisionlab simulation software and practical sessions designed to teach the most important machine vision camera calibration aspects in courses for senior undergraduate students. By following a constructivist methodology, having received introductory theoretical classes, students use the Metrovisionlab application to…

Variable geometry Darrieus wind machine

NASA Astrophysics Data System (ADS)

Pytlinski, J. T.; Serrano, D.

1983-08-01

A variable geometry Darrieus wind machine is proposed. The lower attachment of the blades to the rotor can move freely up and down the axle allowing the blades of change shape during rotation. Experimental data for a 17 m. diameter Darrieus rotor and a theoretical model for multiple streamtube performance prediction were used to develop a computer simulation program for studying parameters that affect the machine's performance. This new variable geometry concept is described and interrelated with multiple streamtube theory through aerodynamic parameters. The computer simulation study shows that governor behavior of a Darrieus turbine can not be attained by a standard turbine operating within normally occurring rotational velocity limits. A second generation variable geometry Darrieus wind turbine which uses a telescopic blade is proposed as a potential improvement on the studied concept.

Study on magnetic force of electromagnetic levitation circular knitting machine

NASA Astrophysics Data System (ADS)

Wu, X. G.; Zhang, C.; Xu, X. S.; Zhang, J. G.; Yan, N.; Zhang, G. Z.

2018-06-01

The structure of the driving coil and the electromagnetic force of the test prototype of electromagnetic-levitation (EL) circular knitting machine are studied. In this paper, the driving coil’s structure and working principle of the EL circular knitting machine are firstly introduced, then the mathematical modelling analysis of the driving electromagnetic force is carried out, and through the Ansoft Maxwell finite element simulation software the coil’s magnetic induction intensity and the needle’s electromagnetic force is simulated, finally an experimental platform is built to measure the coil’s magnetic induction intensity and the needle’s electromagnetic force. The results show that the theoretical analysis, the simulation analysis and the results of the test are very close, which proves the correctness of the proposed model.

Tokamak foundation in USSR/Russia 1950-1990

NASA Astrophysics Data System (ADS)

Smirnov, V. P.

2010-01-01

In the USSR, nuclear fusion research began in 1950 with the work of I.E. Tamm, A.D. Sakharov and colleagues. They formulated the principles of magnetic confinement of high temperature plasmas, that would allow the development of a thermonuclear reactor. Following this, experimental research on plasma initiation and heating in toroidal systems began in 1951 at the Kurchatov Institute. From the very first devices with vessels made of glass, porcelain or metal with insulating inserts, work progressed to the operation of the first tokamak, T-1, in 1958. More machines followed and the first international collaboration in nuclear fusion, on the T-3 tokamak, established the tokamak as a promising option for magnetic confinement. Experiments continued and specialized machines were developed to test separately improvements to the tokamak concept needed for the production of energy. At the same time, research into plasma physics and tokamak theory was being undertaken which provides the basis for modern theoretical work. Since then, the tokamak concept has been refined by a world-wide effort and today we look forward to the successful operation of ITER.

Active chatter suppression with displacement-only measurement in turning process

NASA Astrophysics Data System (ADS)

Ma, Haifeng; Wu, Jianhua; Yang, Liuqing; Xiong, Zhenhua

2017-08-01

Regenerative chatter is a major hindrance for achieving high quality and high production rate in machining processes. Various active controllers have been proposed to mitigate chatter. However, most of existing controllers were developed on the basis of multi-states feedback of the system and state observers were usually needed. Moreover, model parameters of the machining process (mass, damping and stiffness) were required in existing active controllers. In this study, an active sliding mode controller, which employs a dynamic output feedback sliding surface for the unmatched condition and an adaptive law for disturbance estimation, is designed, analyzed, and validated for chatter suppression in turning process. Only displacement measurement is required by this approach. Other sensors and state observers are not needed. Moreover, it facilitates a rapid implementation since the designed controller is established without using model parameters of the turning process. Theoretical analysis, numerical simulations and experiments on a computer numerical control (CNC) lathe are presented. It shows that the chatter can be substantially attenuated and the chatter-free region can be significantly expanded with the presented method.

A Tailored Ontology Supporting Sensor Implementation for the Maintenance of Industrial Machines.

PubMed

Maleki, Elaheh; Belkadi, Farouk; Ritou, Mathieu; Bernard, Alain

2017-09-08

The longtime productivity of an industrial machine is improved by condition-based maintenance strategies. To do this, the integration of sensors and other cyber-physical devices is necessary in order to capture and analyze a machine's condition through its lifespan. Thus, choosing the best sensor is a critical step to ensure the efficiency of the maintenance process. Indeed, considering the variety of sensors, and their features and performance, a formal classification of a sensor's domain knowledge is crucial. This classification facilitates the search for and reuse of solutions during the design of a new maintenance service. Following a Knowledge Management methodology, the paper proposes and develops a new sensor ontology that structures the domain knowledge, covering both theoretical and experimental sensor attributes. An industrial case study is conducted to validate the proposed ontology and to demonstrate its utility as a guideline to ease the search of suitable sensors. Based on the ontology, the final solution will be implemented in a shared repository connected to legacy CAD (computer-aided design) systems. The selection of the best sensor is, firstly, obtained by the matching of application requirements and sensor specifications (that are proposed by this sensor repository). Then, it is refined from the experimentation results. The achieved solution is recorded in the sensor repository for future reuse. As a result, the time and cost of the design process of new condition-based maintenance services is reduced.

Methods, systems and apparatus for controlling operation of two alternating current (AC) machines

DOEpatents

Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA

2012-06-05

A system is provided for controlling two alternating current (AC) machines via a five-phase PWM inverter module. The system comprises a first control loop, a second control loop, and a current command adjustment module. The current command adjustment module operates in conjunction with the first control loop and the second control loop to continuously adjust current command signals that control the first AC machine and the second AC machine such that they share the input voltage available to them without compromising the target mechanical output power of either machine. This way, even when the phase voltage available to either one of the machines decreases, that machine outputs its target mechanical output power.

Electric machine and current source inverter drive system

DOEpatents

Hsu, John S

2014-06-24

A drive system includes an electric machine and a current source inverter (CSI). This integration of an electric machine and an inverter uses the machine's field excitation coil for not only flux generation in the machine but also for the CSI inductor. This integration of the two technologies, namely the U machine motor and the CSI, opens a new chapter for the component function integration instead of the traditional integration by simply placing separate machine and inverter components in the same housing. Elimination of the CSI inductor adds to the CSI volumetric reduction of the capacitors and the elimination of PMs for the motor further improve the drive system cost, weight, and volume.

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed Central

Tsotsos, John K.

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide. PMID:28848458

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed

Tsotsos, John K

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide.

Dynamic provisioning of a HEP computing infrastructure on a shared hybrid HPC system

NASA Astrophysics Data System (ADS)

Meier, Konrad; Fleig, Georg; Hauth, Thomas; Janczyk, Michael; Quast, Günter; von Suchodoletz, Dirk; Wiebelt, Bernd

2016-10-01

Experiments in high-energy physics (HEP) rely on elaborate hardware, software and computing systems to sustain the high data rates necessary to study rare physics processes. The Institut fr Experimentelle Kernphysik (EKP) at KIT is a member of the CMS and Belle II experiments, located at the LHC and the Super-KEKB accelerators, respectively. These detectors share the requirement, that enormous amounts of measurement data must be processed and analyzed and a comparable amount of simulated events is required to compare experimental results with theoretical predictions. Classical HEP computing centers are dedicated sites which support multiple experiments and have the required software pre-installed. Nowadays, funding agencies encourage research groups to participate in shared HPC cluster models, where scientist from different domains use the same hardware to increase synergies. This shared usage proves to be challenging for HEP groups, due to their specialized software setup which includes a custom OS (often Scientific Linux), libraries and applications. To overcome this hurdle, the EKP and data center team of the University of Freiburg have developed a system to enable the HEP use case on a shared HPC cluster. To achieve this, an OpenStack-based virtualization layer is installed on top of a bare-metal cluster. While other user groups can run their batch jobs via the Moab workload manager directly on bare-metal, HEP users can request virtual machines with a specialized machine image which contains a dedicated operating system and software stack. In contrast to similar installations, in this hybrid setup, no static partitioning of the cluster into a physical and virtualized segment is required. As a unique feature, the placement of the virtual machine on the cluster nodes is scheduled by Moab and the job lifetime is coupled to the lifetime of the virtual machine. This allows for a seamless integration with the jobs sent by other user groups and honors the fairshare policies of the cluster. The developed thin integration layer between OpenStack and Moab can be adapted to other batch servers and virtualization systems, making the concept also applicable for other cluster operators. This contribution will report on the concept and implementation of an OpenStack-virtualized cluster used for HEP workflows. While the full cluster will be installed in spring 2016, a test-bed setup with 800 cores has been used to study the overall system performance and dedicated HEP jobs were run in a virtualized environment over many weeks. Furthermore, the dynamic integration of the virtualized worker nodes, depending on the workload at the institute's computing system, will be described.

Global Positioning System (GPS) and Geographic Information System (GIS) analysis of mobile harvesting equipment and sediment delivery to streams during forest harvest operations on steep terrain: Experimental design

Treesearch

Daniel Bowker; Jeff Stringer; Chris Barton; Songlin Fei

2011-01-01

Sediment mobilized by forest harvest machine traffic contributes substantially to the degradation of headwater stream systems. This study monitored forest harvest machine traffic to analyze how it affects sediment delivery to stream channels. Harvest machines were outfitted with global positioning system (GPS) dataloggers, recording machine movements and working status...

Study of Thread Level Parallelism in a Video Encoding Application for Chip Multiprocessor Design

NASA Astrophysics Data System (ADS)

Debes, Eric; Kaine, Greg

2002-11-01

In media applications there is a high level of available thread level parallelism (TLP). In this paper we study the intra TLP in a video encoder. We show that a well-distributed highly optimized encoder running on a symmetric multiprocessor (SMP) system can run 3.2 faster on a 4-way SMP machine than on a single processor. The multithreaded encoder running on an SMP system is then used to understand the requirements of a chip multiprocessor (CMP) architecture, which is one possible architectural direction to better exploit TLP. In the framework of this study, we use a software approach to evaluate the dataflow between processors for the video encoder running on an SMP system. An estimation of the dataflow is done with L2 cache miss event counters using Intel® VTuneTM performance analyzer. The experimental measurements are compared to theoretical results.

Modeling and measurement of the performance of a branched conduit sampling system in a mass spectrometer leak detector

NASA Technical Reports Server (NTRS)

Russell, John M.

1994-01-01

In the leak testing of a large engineering system, one may distinguish three stages, namely leakage measurement by an overall enclosure, leak location, and leakage measurement by a local enclosure. Sniffer probes attached to helium mass spectrometer leak detectors are normally designed for leak location, a qualitative inspection technique intended to pinpoint where a leak is but not to quantify its rate of discharge. The main conclusion of the present effort is that local leakage measurement by a leak detector with a sniffer probe is feasible provided one has: (1) quantitative data on the performance of the mass separator cell (a device interior to the unit where the stream of fluid in the sample line branches); and (2) a means of stabilizing the mass transfer boundary layer that is created near a local leak site when a sniffer probe is placed in its immediate vicinity. Theoretical models of the mass separator cell are provided and measurements of the machine-specific parameters in the formulas are presented. A theoretical model of a porous probe end for stabilizing the mass transfer boundary is also presented.

Wavelength selection for portable noninvasive blood component measurement system based on spectral difference coefficient and dynamic spectrum

NASA Astrophysics Data System (ADS)

Feng, Ximeng; Li, Gang; Yu, Haixia; Wang, Shaohui; Yi, Xiaoqing; Lin, Ling

2018-03-01

Noninvasive blood component analysis by spectroscopy has been a hotspot in biomedical engineering in recent years. Dynamic spectrum provides an excellent idea for noninvasive blood component measurement, but studies have been limited to the application of broadband light sources and high-resolution spectroscopy instruments. In order to remove redundant information, a more effective wavelength selection method has been presented in this paper. In contrast to many common wavelength selection methods, this method is based on sensing mechanism which has a clear mechanism and can effectively avoid the noise from acquisition system. The spectral difference coefficient was theoretically proved to have a guiding significance for wavelength selection. After theoretical analysis, the multi-band spectral difference coefficient-wavelength selection method combining with the dynamic spectrum was proposed. An experimental analysis based on clinical trial data from 200 volunteers has been conducted to illustrate the effectiveness of this method. The extreme learning machine was used to develop the calibration models between the dynamic spectrum data and hemoglobin concentration. The experiment result shows that the prediction precision of hemoglobin concentration using multi-band spectral difference coefficient-wavelength selection method is higher compared with other methods.

Modeling and measurement of the performance of a branched conduit sampling system in a mass spectrometer leak detector

NASA Astrophysics Data System (ADS)

Russell, John M.

1994-10-01

In the leak testing of a large engineering system, one may distinguish three stages, namely leakage measurement by an overall enclosure, leak location, and leakage measurement by a local enclosure. Sniffer probes attached to helium mass spectrometer leak detectors are normally designed for leak location, a qualitative inspection technique intended to pinpoint where a leak is but not to quantify its rate of discharge. The main conclusion of the present effort is that local leakage measurement by a leak detector with a sniffer probe is feasible provided one has: (1) quantitative data on the performance of the mass separator cell (a device interior to the unit where the stream of fluid in the sample line branches); and (2) a means of stabilizing the mass transfer boundary layer that is created near a local leak site when a sniffer probe is placed in its immediate vicinity. Theoretical models of the mass separator cell are provided and measurements of the machine-specific parameters in the formulas are presented. A theoretical model of a porous probe end for stabilizing the mass transfer boundary is also presented.

Machine vision systems using machine learning for industrial product inspection

NASA Astrophysics Data System (ADS)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Simplified and Yet Turing Universal Spiking Neural P Systems with Communication on Request.

PubMed

Wu, Tingfang; Bîlbîe, Florin-Daniel; Păun, Andrei; Pan, Linqiang; Neri, Ferrante

2018-04-02

Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural P system where the spikes are requested from neighboring neurons. SNQ P systems have previously been proved to be universal (computationally equivalent to Turing machines) when two types of spikes are considered. This paper studies a simplified version of SNQ P systems, i.e. SNQ P systems with one type of spike. It is proved that one type of spike is enough to guarantee the Turing universality of SNQ P systems. Theoretical results are shown in the cases of the SNQ P system used in both generating and accepting modes. Furthermore, the influence of the number of unbounded neurons (the number of spikes in a neuron is not bounded) on the computation power of SNQ P systems with one type of spike is investigated. It is found that SNQ P systems functioning as number generating devices with one type of spike and four unbounded neurons are Turing universal.

FOREWORD: The XXV IAHR Symposium on Hydraulic Machinery and Systems marks half a century tradition

NASA Astrophysics Data System (ADS)

Susan-Resiga, Romeo

2010-05-01

IAHR75_logoUPT90_logoARFT_logo International Association of Hydro-Environment Engineering and Research'Politehnica' University of TimisoaraRomanian Academy - Timisoara Branch The 25th edition of the IAHR Symposium on Hydraulic Machinery and Systems, held in Timisoara, Romania, 20-24 September 2010, jointly organized by the 'Politehnica' University of Timisoara and the Romanian Academy - Timisoara Branch, marks a half century tradition of these prestigious symposia. However, it is the first time that Romania hosts such a symposium, and for good reasons. The Romanian electrical power system has a total of 20,630 MW installed power, out of which 6,422 MW in hydropower plants. The energy produced in hydropower facilities was in 2008 of 17,105 GWh from a total of 64,772 GWh electrical energy production. Moreover, for the period 2009-2015, new hydropower capacities are going to be developed, with a total of 2,157 MW installed power and an estimated 5,770 GWh/year energy production. Within the same period of time, the refurbishment, modernization and repair programs will increase the actual hydropower production with an estimated 349 GWh/year. The 'Politehnica' University of Timisoara is proud to host the 25th IAHR Symposium on Hydraulic Machinery and Systems, in the year of its 90th anniversary. The 'Politehnica' University of Timisoara is one of the largest and most well-known technical universities from Central and Eastern Europe. It was founded in 1920, a short time after the union into one state of all the Romanian territories, following the end of the First World War, in order to respond to the need engineers felt by the Romanian society at that time, within the economical development framework. During its 90 years of existence, 'Politehnica' University of Timisoara educated over 100,000 engineers, greatly appreciated both in Romania and abroad, for their competence and seriousness. King Ferdinand I of Romania said while visiting the recently established 'Politehnica' of Timisoara in 1923 'It is not the walls that make a school, but the spirit living inside'. A particular trademark of the 'Politehnica' of Timisoara was the continuous effort to answer industrial problems by training the students not only on theoretical aspects but also in design and manufacturing, as well as in laboratory works. Developing modern laboratories, where students can observe and understand first hand the engineering applications along the years a priority for Timisoara 'Politehnica' University. The School of Hydraulic Machinery within the 'Politehnica' University of Timisoara was established in early 1930 by Professor Aurel Barglazan (1905-1960), and further developed by Professor Ioan Anton (born 1924), both members of the Romanian Academy. The Laboratory of Hydraulic Machines from Timisoara (LMHT) started back in 1928 in a small hut, with a test rig for Francis and Kaplan turbines manufactured by J M Voith. LMHT was continuously developed and was officially recognized in 1959 as being one of the leading research and developing laboratories in Romania. It was the foundation of the Romanian efforts of designing and manufacturing hydraulic turbines starting in 1960 at the Resita Machine Building Factory. Under the leadership of Professor Ioan Anton, the Timisoara School in Hydraulic Machinery has focused the basic and development research activities on the following main topics: (i) Turbine Hydrodynamics, (ii) Hydrofoil Cascade Hydrodynamics, (iii) Cavitation in Hydraulic Machines and Equipments, (iv) Scale-up Effects in Hydraulic Machines. With the establishment in the year 2000 of the National Center for Engineering of Systems with Complex Fluids, within the 'Politehnica' University of Timisoara, the research in turbomachinery hydrodynamics and cavitation included high performance computing for flows in hydraulic machines, as well as the development of novel technologies to mitigate the self-induced flow instabilities in hydraulic turbines operated far from the best efficiency regime. The traditional partnership with the Romanian Academy - Timisoara Branch, Laboratory for Hydrodynamics and Cavitation, led to complex projects that combine both basic theoretical developments with advanced experimental investigations leading to practical engineering solutions for modern hydraulic machines. The International Association of Hydro-Environment Engineering and Research (IAHR) celebrates its 75th anniversary this year. IAHR particularly promotes the advancement and exchange of knowledge through working groups, specialty symposia, congresses, and publications on water resources, river and coastal hydraulics, risk analysis, energy, environment, disaster prevention, industrial processes. The IAHR - Committee on Hydraulic Machinery and Systems deals with the advancement of technology associated with the understanding of steady and unsteady flow characteristics in hydraulic machinery and conduit systems connected to the machinery. The technology elements include the fluid behaviour within machine components, hydro-elastic behaviour of machine components, cavitation, and two phase flow in turbines and pumps, hydraulic machine and plant control systems, the use of hydraulic machines to improve water quality, and even considerations to improve fish survival in their passage through hydro plants. The main emphases of the IAHR Committee on Hydraulic Machinery and Systems are to stimulate research and understanding of the technologies associated with hydraulic machinery and to promote interaction between the machine designers, machine users, the academic community, and the community at large. Hydraulic machinery is both cost effective and environmentally responsible. The increasing atmospheric content of carbon dioxide related to pollution from thermal power plants, is one of the most significant threats to our global ecology. The problem is exacerbated by the need for increased energy production in third world countries. This results in rising global temperatures and dramatic changes in climate which may also result in flooding in parts of our globe. Energy conservation together with replacement of coal and oil-fired power plants are, therefore, needed. The development and installation of more efficient hydroelectric power plants which work hand in hand with water storage and flood protection is part of this strategy. Waterpower is the most significant 'renewable resource'. The goals of this IAHR - Committee on Hydraulic Machinery and Systems are to improve the value of hydraulic machinery to the end user and to society and to improve society's understanding and appreciation of that value. The series of IAHR Symposia on Hydraulic Machinery and Cavitation started with the 1st edition in Nice in 1960 in France. Within the past decade, all the symposia were focused on an extended portfolio of topics under the name of 'Hydraulic Machinery and Systems', such as the 20th edition in 2000, Charlotte, USA, the 21st in 2002, Lausanne, Switzerland, the 22nd in 2004, Stockholm, Sweden, the 23rd in 2006, Yokohama, Japan, and the 24th in 2008, Foz do Iguassu, Brasil. The 25th IAHR Symposium on Hydraulic Machinery and Systems brings together more than 150 scientists and researchers from 24 countries, affiliated with universities , technology centres and industry to debate topics related to advanced technologies for hydraulic machinery and systems, which will enhance the sustainable development of water resources and hydropower production. The Scientific Committee has selected 118 papers, out of 238 abstracts submitted, on the following topics: (i) Hydraulic Turbines and Pumps, (ii) Sustainable hydropower, (iii) Hydraulic Systems, (iv) Advances in Computational and Experimental Techniques, (v) Innovative Technology, to be presented at the symposium and to be included in the proceedings. All papers published in this Volume 12 of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the editors of the 25th IAHR Symposium on Hydraulic Machinery and Systems proceedings, Professor Romeo Susan-Resiga, Dr Sebastian Muntean and Dr Sandor Bernad. We hope that this anniversary edition of the series of symposia on Hydraulic Machinery and Systems will be a significant step forward in the worldwide efforts to address the present challenges facing the modern hydraulic machines. Professor Romeo Susan-Resiga Chairman of the Organizing Committee 25th IAHR Symposium on Hydraulic Machinery and Systems

Chemical sensors from the cooperative actuation of multistep electrochemical molecular machines of polypyrrole: potentiostatic study. Trying to replicate muscle’s fatigue signals

NASA Astrophysics Data System (ADS)

Beaumont, Samuel; Otero, Toribio F.

2018-07-01

Polypyrrole film electrodes are constituted by multielectronic electrochemical molecular machines (every polymeric molecule) counterions and water, mimicking the intracellular matrix of muscular cells. The influence of the electrolyte concentration on the reversible oxidation/reduction of polypyrrole films was studied in NaCl aqueous solutions by consecutive square potential waves. The consumed redox charge and the consumed electrical energy change as a function of the concentration. That means that the extension (the consumed charge) of the reaction involving conformational, or allosteric, movements of the reacting polymeric chains (molecular machines) responds to (senses) the chemical energy of the reaction ambient. A theoretical description of the attained empirical results is presented getting the sensing equations and the concomitant sensitivities. Those results could indicate the origin and nature of the neural signals sent to the brain from biological haptic muscles working by cooperative actuation of the actin-myosin molecular machines driven by chemical reactions and sensing, simultaneously, the fatigue state of the muscle.

The influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface

NASA Astrophysics Data System (ADS)

Wu, Mingtao; Guo, Bing; Zhao, Qingliang; Fan, Rongwei; Dong, Zhiwei; Yu, Xin

2018-06-01

Micro-structured surface on diamond is widely used in microelectronics, optical elements, MEMS and NEMS components, ultra-precision machining tools, etc. The efficient micro-structuring of diamond material is still a challenging task. In this article, the influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface were researched. At the beginning, the ablation threshold and its incubation effect of monocrystalline diamond were determined and discussed. As the accumulated laser pulses ranged from 40 to 5000, the laser ablation threshold decreased from 1.48 J/cm2 to 0.97 J/cm2. Subsequently, the variation of the ablation width and ablation depth in laser machining were studied. With enough pulse energy, the ablation width mainly depended on the laser propagation attributes while the ablation depth was a complex function of the focus position. Raman analysis was used to detect the variation of the laser machined diamond surface after the laser machining experiments. Graphite formation was discovered on the machined diamond surface and graphitization was enhanced after the defocusing quantity exceeded 45 μm. At last, several micro-structured surfaces were successfully fabricated on diamond surface with the defined micro-structure patterns and structuring ratios just by adjusting the defocusing quantity. The experimental structuring ratio was consistent with the theoretical analysis.

The Security of Machine Learning

DTIC Science & Technology

2008-04-24

Machine learning has become a fundamental tool for computer security, since it can rapidly evolve to changing and complex situations. That...adaptability is also a vulnerability: attackers can exploit machine learning systems. We present a taxonomy identifying and analyzing attacks against machine ...We use our framework to survey and analyze the literature of attacks against machine learning systems. We also illustrate our taxonomy by showing

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.

Data-Driven Approaches to Empirical Discovery

DTIC Science & Technology

1988-10-31

if nece ry and identify by block number) empirical discovery history of science data-driven heuristics numeric laws theoretical terms scope of laws...to the normative side. Machine Discovery and the History of Science The history of science studies the actual path followed by scientists over the

Enhancing Manufacturing Process Education via Computer Simulation and Visualization

ERIC Educational Resources Information Center

Manohar, Priyadarshan A.; Acharya, Sushil; Wu, Peter

2014-01-01

Industrially significant metal manufacturing processes such as melting, casting, rolling, forging, machining, and forming are multi-stage, complex processes that are labor, time, and capital intensive. Academic research develops mathematical modeling of these processes that provide a theoretical framework for understanding the process variables…

Fluid flow dynamics in MAS systems

NASA Astrophysics Data System (ADS)

Wilhelm, Dirk; Purea, Armin; Engelke, Frank

2015-08-01

The turbine system and the radial bearing of a high performance magic angle spinning (MAS) probe with 1.3 mm-rotor diameter has been analyzed for spinning rates up to 67 kHz. We focused mainly on the fluid flow properties of the MAS system. Therefore, computational fluid dynamics (CFD) simulations and fluid measurements of the turbine and the radial bearings have been performed. CFD simulation and measurement results of the 1.3 mm-MAS rotor system show relatively low efficiency (about 25%) compared to standard turbo machines outside the realm of MAS. However, in particular, MAS turbines are mainly optimized for speed and stability instead of efficiency. We have compared MAS systems for rotor diameter of 1.3-7 mm converted to dimensionless values with classical turbomachinery systems showing that the operation parameters (rotor diameter, inlet mass flow, spinning rate) are in the favorable range. This dimensionless analysis also supports radial turbines for low speed MAS probes and diagonal turbines for high speed MAS probes. Consequently, a change from Pelton type MAS turbines to diagonal turbines might be worth considering for high speed applications. CFD simulations of the radial bearings have been compared with basic theoretical values proposing considerably smaller frictional loss values. The discrepancies might be due to the simple linear flow profile employed for the theoretical model. Frictional losses generated inside the radial bearings result in undesired heat-up of the rotor. The rotor surface temperature distribution computed by CFD simulations show a large temperature gradient over the rotor.

Koopman operator theory: Past, present, and future

NASA Astrophysics Data System (ADS)

Brunton, Steven; Kaiser, Eurika; Kutz, Nathan

2017-11-01

Koopman operator theory has emerged as a dominant method to represent nonlinear dynamics in terms of an infinite-dimensional linear operator. The Koopman operator acts on the space of all possible measurement functions of the system state, advancing these measurements with the flow of the dynamics. A linear representation of nonlinear dynamics has tremendous potential to enable the prediction, estimation, and control of nonlinear systems with standard textbook methods developed for linear systems. Dynamic mode decomposition has become the leading data-driven method to approximate the Koopman operator, although there are still open questions and challenges around how to obtain accurate approximations for strongly nonlinear systems. This talk will provide an introductory overview of modern Koopman operator theory, reviewing the basics and describing recent theoretical and algorithmic developments. Particular emphasis will be placed on the use of data-driven Koopman theory to characterize and control high-dimensional fluid dynamic systems. This talk will also address key advances in the rapidly growing fields of machine learning and data science that are likely to drive future developments.

Introduction to System Health Engineering and Management in Aerospace

NASA Technical Reports Server (NTRS)

Johnson, Stephen B.

2005-01-01

This paper provides a technical overview of Integrated System Health Engineering and Management (ISHEM). We define ISHEM as "the paper provides a techniques, and technologies used to design, analyze, build, verify, and operate a system to prevent faults and/or minimize their effects." This includes design and manufacturing techniques as well operational and managerial methods. ISHEM is not a "purely technical issue" as it also involves and must account for organizational, communicative, and cognitive f&ms of humans as social beings and as individuals. Thus the paper will discuss in more detail why all of these elements, h m the technical to the cognitive and social, are necessary to build dependable human-machine systems. The paper outlines a functional homework and architecture for ISHEM operations, describes the processes needed to implement ISHEM in the system life-cycle, and provides a theoretical framework to understand the relationship between the different aspects of the discipline. It then derives from these and the social and cognitive bases a set of design and operational principles for ISHEM.

Automated packing systems: review of industrial implementations

NASA Astrophysics Data System (ADS)

Whelan, Paul F.; Batchelor, Bruce G.

1993-08-01

A rich theoretical background to the problems that occur in the automation of material handling can be found in operations research, production engineering, systems engineering and automation, more specifically machine vision, literature. This work has contributed towards the design of intelligent handling systems. This paper will review the application of these automated material handling and packing techniques to industrial problems. The discussion will also highlight the systems integration issues involved in these applications. An outline of one such industrial application, the automated placement of shape templates on to leather hides, is also discussed. The purpose of this system is to arrange shape templates on a leather hide in an efficient manner, so as to minimize the leather waste, before they are automatically cut from the hide. These pieces are used in the furniture and car manufacturing industries for the upholstery of high quality leather chairs and car seats. Currently this type of operation is semi-automated. The paper will outline the problems involved in the full automation of such a procedure.

48 CFR 908.7117 - Tabulating machine cards.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 5 2011-10-01 2011-10-01 false Tabulating machine cards. 908.7117 Section 908.7117 Federal Acquisition Regulations System DEPARTMENT OF ENERGY COMPETITION... Tabulating machine cards. DOE offices shall acquire tabulating machine cards in accordance with FPMR 41 CFR...

48 CFR 908.7117 - Tabulating machine cards.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Tabulating machine cards. 908.7117 Section 908.7117 Federal Acquisition Regulations System DEPARTMENT OF ENERGY COMPETITION... Tabulating machine cards. DOE offices shall acquire tabulating machine cards in accordance with FPMR 41 CFR...

Ada (Trade Name) Compiler Validation Summary Report: International Business Machines Corporation. IBM Development System for the Ada Language System, Version 1.1.0, IBM 4381 under MVS.

DTIC Science & Technology

1988-05-22

TITLE (andSubtile) 5. TYPE OF REPORT & PERIOD COVERED Ada Compler Validation Summary Report: 22 May 1987 to 22 May 1988 International Business Machines...IBM Development System for the Ada Language System, Version 1.1.0, International Business Machines Corporation, Wright-Patterson AFB. IBM 4381 under...SUMMARY REPORT: International Business Machines Corporation IBM Development System f’or the Ada Language System, Version 1.1.0 IBM 4381 under MVS

Support vector machine in machine condition monitoring and fault diagnosis

NASA Astrophysics Data System (ADS)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

A computer method of finding valuations forcing validity of LC formulae

NASA Astrophysics Data System (ADS)

Godlewski, Łukasz; Świetorzecka, Kordula; Mulawka, Jan

2014-11-01

The purpose of this paper is to present the computer implementation of a system known as LC temporal logic [1]. Firstly, to become familiar with some theoretical issues, a short introduction to this logic is discussed. The algorithms allowing a deep analysis of the formulae of LC logic are considered. In particular we discuss how to determine if a formula is a tautology, contrtautology or it is satisfable. Next, we show how to find all valuations to satisfy the formula. Finally, we consider finding histories generated by the formula and transforming these histories into the state machine. Moreover, a description of the experiments that verify the implementation are briefly presented.

Cybersemiotics: a transdisciplinary framework for information studies.

PubMed

Brier, S

1998-04-01

This paper summarizes recent attempts by this author to create a transdisciplinary, non-Cartesian and non-reductionistic framework for information studies in natural, social, and technological systems. To confront, in a scientific way, the problems of modern information technology where phenomenological man is dealing with socially constructed texts in algorithmically based digital bit-machines we need a theoretical framework spanning from physics over biology and technological design to phenomenological and social production of signification and meaning. I am working with such pragmatic theories as second order cybernetics (coupled with autopolesis theory), Lakoffs biologically oriented cognitive semantics, Peirce's triadic semiotics, and Wittgenstein's pragmatic language game theory. A coherent synthesis of these theories is what the cybersemiotic framework attempts to accomplish.

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

Synchronous machines have traditionally acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, with the increased integration of distributed renewable resources and energy-storage technologies, there is a need to systematically acknowledge the dynamics of power-electronics inverters - the primary energy-conversion interface in such systems - in all aspects of modeling, analysis, and control of the bulk power network. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. The inverter model is formulatedmore » such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

Machine learning in the rational design of antimicrobial peptides.

PubMed

Rondón-Villarreal, Paola; Sierra, Daniel A; Torres, Rodrigo

2014-01-01

One of the most important public health issues is the microbial and bacterial resistance to conventional antibiotics by pathogen microorganisms. In recent years, many researches have been focused on the development of new antibiotics. Among these, antimicrobial peptides (AMPs) have raised as a promising alternative to combat antibioticresistant microorganisms. For this reason, many theoretical efforts have been done in the development of new computational tools for the rational design of both better and effective AMPs. In this review, we present an overview of the rational design of AMPs using machine learning techniques and new research fields.

Efficient forced vibration reanalysis method for rotating electric machines

NASA Astrophysics Data System (ADS)

Saito, Akira; Suzuki, Hiromitsu; Kuroishi, Masakatsu; Nakai, Hideo

2015-01-01

Rotating electric machines are subject to forced vibration by magnetic force excitation with wide-band frequency spectrum that are dependent on the operating conditions. Therefore, when designing the electric machines, it is inevitable to compute the vibration response of the machines at various operating conditions efficiently and accurately. This paper presents an efficient frequency-domain vibration analysis method for the electric machines. The method enables the efficient re-analysis of the vibration response of electric machines at various operating conditions without the necessity to re-compute the harmonic response by finite element analyses. Theoretical background of the proposed method is provided, which is based on the modal reduction of the magnetic force excitation by a set of amplitude-modulated standing-waves. The method is applied to the forced response vibration of the interior permanent magnet motor at a fixed operating condition. The results computed by the proposed method agree very well with those computed by the conventional harmonic response analysis by the FEA. The proposed method is then applied to the spin-up test condition to demonstrate its applicability to various operating conditions. It is observed that the proposed method can successfully be applied to the spin-up test conditions, and the measured dominant frequency peaks in the frequency response can be well captured by the proposed approach.

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

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

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

From the inception of power systems, synchronous machines have acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, power electronics interfaces are playing a growing role as they are the primary interface for several types of renewable energy sources and storage technologies. As the role of power electronics in systems continues to grow, it is crucial to investigate the properties of bulk power systems in low inertia settings. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator,more » three-phase inverter, and a load. Furthermore, the inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings and, hence, differing levels of inertia. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the interaction between the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

Evaluation of an Integrated Multi-Task Machine Learning System with Humans in the Loop

DTIC Science & Technology

2007-01-01

machine learning components natural language processing, and optimization...was examined with a test explicitly developed to measure the impact of integrated machine learning when used by a human user in a real world setting...study revealed that integrated machine learning does produce a positive impact on overall performance. This paper also discusses how specific machine learning components contributed to human-system

Nonlinear oscillation of a rigid body over high- Tc superconductors supported by electro-magnetic forces

NASA Astrophysics Data System (ADS)

Sugiura, T.; Ogawa, S.; Ura, H.

2005-10-01

Characteristics of high- Tc superconducting levitation systems are no contact support and stable levitation without control. They can be applied to supporting mechanisms in machines, such as linear-drives and magnetically levitated trains. But small damping due to noncontact support and nonlinearity in the magnetic force can easily cause complicated phenomena of nonlinear dynamics. This research deals with nonlinear oscillation of a rigid bar supported at its both ends by electro-magnetic forces between superconductors and permanent magnets as a simple modeling of the above application. Deriving the equation of motion, we discussed an effect of nonlinearity in the magnetic force on dynamics of the levitated body: occurrence of combination resonance in the asymmetrical system. Numerical analyses and experiments were also carried out, and their results confirmed the above theoretical prediction.

Exploring Energy Landscapes

NASA Astrophysics Data System (ADS)

Wales, David J.

2018-04-01

Recent advances in the potential energy landscapes approach are highlighted, including both theoretical and computational contributions. Treating the high dimensionality of molecular and condensed matter systems of contemporary interest is important for understanding how emergent properties are encoded in the landscape and for calculating these properties while faithfully representing barriers between different morphologies. The pathways characterized in full dimensionality, which are used to construct kinetic transition networks, may prove useful in guiding such calculations. The energy landscape perspective has also produced new procedures for structure prediction and analysis of thermodynamic properties. Basin-hopping global optimization, with alternative acceptance criteria and generalizations to multiple metric spaces, has been used to treat systems ranging from biomolecules to nanoalloy clusters and condensed matter. This review also illustrates how all this methodology, developed in the context of chemical physics, can be transferred to landscapes defined by cost functions associated with machine learning.

Recent Developments in Social Science Research

ERIC Educational Resources Information Center

Jenness, David

1978-01-01

In this discussion of recent theoretical and methodological developments in three selected areas of the social sciences--social indicators, social experimentation and evaluation, and longitudinal studies, attention is given to the growing availability of machine-readable data sets and to special archives and resources of interest to librarians.…

Tactics for mechanized reasoning: a commentary on Milner (1984) ‘The use of machines to assist in rigorous proof’

PubMed Central

Gordon, M. J. C.

2015-01-01

Robin Milner's paper, ‘The use of machines to assist in rigorous proof’, introduces methods for automating mathematical reasoning that are a milestone in the development of computer-assisted theorem proving. His ideas, particularly his theory of tactics, revolutionized the architecture of proof assistants. His methodology for automating rigorous proof soundly, particularly his theory of type polymorphism in programing, led to major contributions to the theory and design of programing languages. His citation for the 1991 ACM A.M. Turing award, the most prestigious award in computer science, credits him with, among other achievements, ‘probably the first theoretically based yet practical tool for machine assisted proof construction’. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. PMID:25750147

Ada (Tradename) Compiler Validation Summary Report. International Business Machines Corporation. IBM Development System for the Ada Language for VM/CMS, Version 1.0. IBM 4381 (IBM System/370) under VM/CMS.

DTIC Science & Technology

1986-04-29

COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM Development System for the Ada Language for VM/CMS, Version 1.0 IBM 4381...tested using command scripts provided by International Business Machines Corporation. These scripts were reviewed by the validation team. Test.s were run...s): IBM 4381 (System/370) Operating System: VM/CMS, release 3.6 International Business Machines Corporation has made no deliberate extensions to the

Model-based chatter stability prediction and detection for the turning of a flexible workpiece

NASA Astrophysics Data System (ADS)

Lu, Kaibo; Lian, Zisheng; Gu, Fengshou; Liu, Hunju

2018-02-01

Machining long slender workpieces still presents a technical challenge on the shop floor due to their low stiffness and damping. Regenerative chatter is a major hindrance in machining processes, reducing the geometric accuracies and dynamic stability of the cutting system. This study has been motivated by the fact that chatter occurrence is generally in relation to the cutting position in straight turning of slender workpieces, which has seldom been investigated comprehensively in literature. In the present paper, a predictive chatter model of turning a tailstock supported slender workpiece considering the cutting position change during machining is explored. Based on linear stability analysis and stiffness distribution at different cutting positions along the workpiece, the effect of the cutting tool movement along the length of the workpiece on chatter stability is studied. As a result, an entire stability chart for a single cutting pass is constructed. Through this stability chart the critical cutting condition and the chatter onset location along the workpiece in a turning operation can be estimated. The difference between the predicted tool locations and the experimental results was within 9% at high speed cutting. Also, on the basis of the predictive model the dynamic behavior during chatter that when chatter arises at some cutting location it will continue for a period of time until another specified location is arrived at, can be inferred. The experimental observation is in good agreement with the theoretical inference. In chatter detection respect, besides the delay strategy and overlap processing technique, a relative threshold algorithm is proposed to detect chatter by comparing the spectrum and variance of the acquired acceleration signals with the reference saved during stable cutting. The chatter monitoring method has shown reliability for various machining conditions.

Swept Mechanism of Micro-Milling Tool Geometry Effect on Machined Oxygen Free High Conductivity Copper (OFHC) Surface Roughness

PubMed Central

Shi, Zhenyu; Liu, Zhanqiang; Li, Yuchao; Qiao, Yang

2017-01-01

Cutting tool geometry should be very much considered in micro-cutting because it has a significant effect on the topography and accuracy of the machined surface, particularly considering the uncut chip thickness is comparable to the cutting edge radius. The objective of this paper was to clarify the influence of the mechanism of the cutting tool geometry on the surface topography in the micro-milling process. Four different cutting tools including two two-fluted end milling tools with different helix angles of 15° and 30° cutting tools, as well as two three-fluted end milling tools with different helix angles of 15° and 30° were investigated by combining theoretical modeling analysis with experimental research. The tool geometry was mathematically modeled through coordinate translation and transformation to make all three cutting edges at the cutting tool tip into the same coordinate system. Swept mechanisms, minimum uncut chip thickness, and cutting tool run-out were considered on modeling surface roughness parameters (the height of surface roughness Rz and average surface roughness Ra) based on the established mathematical model. A set of cutting experiments was carried out using four different shaped cutting tools. It was found that the sweeping volume of the cutting tool increases with the decrease of both the cutting tool helix angle and the flute number. Great coarse machined surface roughness and more non-uniform surface topography are generated when the sweeping volume increases. The outcome of this research should bring about new methodologies for micro-end milling tool design and manufacturing. The machined surface roughness can be improved by appropriately selecting the tool geometrical parameters. PMID:28772479

Toward Harnessing User Feedback For Machine Learning

DTIC Science & Technology

2006-10-02

machine learning systems. If this resource-the users themselves-could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved and the users? understanding and trust of the system could improve as well. We conducted a think-aloud study to see how willing users were to provide feedback and to understand what kinds of feedback users could give. Users were shown explanations of machine learning predictions and asked to provide feedback to improve the predictions. We found that users

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.

Quality Control by Artificial Vision

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

Lam, Edmond Y.; Gleason, Shaun Scott; Niel, Kurt S.

2010-01-01

Computational technology has fundamentally changed many aspects of our lives. One clear evidence is the development of artificial-vision systems, which have effectively automated many manual tasks ranging from quality inspection to quantitative assessment. In many cases, these machine-vision systems are even preferred over manual ones due to their repeatability and high precision. Such advantages come from significant research efforts in advancing sensor technology, illumination, computational hardware, and image-processing algorithms. Similar to the Special Section on Quality Control by Artificial Vision published two years ago in Volume 17, Issue 3 of the Journal of Electronic Imaging, the present one invited papersmore » relevant to fundamental technology improvements to foster quality control by artificial vision, and fine-tuned the technology for specific applications. We aim to balance both theoretical and applied work pertinent to this special section theme. Consequently, we have seven high-quality papers resulting from the stringent peer-reviewing process in place at the Journal of Electronic Imaging. Some of the papers contain extended treatment of the authors work presented at the SPIE Image Processing: Machine Vision Applications conference and the International Conference on Quality Control by Artificial Vision. On the broad application side, Liu et al. propose an unsupervised texture image segmentation scheme. Using a multilayer data condensation spectral clustering algorithm together with wavelet transform, they demonstrate the effectiveness of their approach on both texture and synthetic aperture radar images. A problem related to image segmentation is image extraction. For this, O'Leary et al. investigate the theory of polynomial moments and show how these moments can be compared to classical filters. They also show how to use the discrete polynomial-basis functions for the extraction of 3-D embossed digits, demonstrating superiority over Fourier-basis functions for this task. Image registration is another important task for machine vision. Bingham and Arrowood investigate the implementation and results in applying Fourier phase matching for projection registration, with a particular focus on nondestructive testing using computed tomography. Readers interested in enriching their arsenal of image-processing algorithms for machine-vision tasks should find these papers enriching. Meanwhile, we have four papers dealing with more specific machine-vision tasks. The first one, Yahiaoui et al., is quantitative in nature, using machine vision for real-time passenger counting. Occulsion is a common problem in counting objects and people, and they circumvent this issue with a dense stereovision system, achieving 97 to 99% accuracy in their tests. On the other hand, the second paper by Oswald-Tranta et al. focuses on thermographic crack detection. An infrared camera is used to detect inhomogeneities, which may indicate surface cracks. They describe the various steps in developing fully automated testing equipment aimed at a high throughput. Another paper describing an inspection system is Molleda et al., which handles flatness inspection of rolled products. They employ optical-laser triangulation and 3-D surface reconstruction for this task, showing how these can be achieved in real time. Last but not least, Presles et al. propose a way to monitor the particle-size distribution of batch crystallization processes. This is achieved through a new in situ imaging probe and image-analysis methods. While it is unlikely any reader may be working on these four specific problems at the same time, we are confident that readers will find these papers inspiring and potentially helpful to their own machine-vision system developments.« less

Challenges and Requirements for the Application of Industry 4.0: A Special Insight with the Usage of Cyber-Physical System

NASA Astrophysics Data System (ADS)

Mueller, Egon; Chen, Xiao-Li; Riedel, Ralph

2017-09-01

Considered as a top priority of industrial development, Industry 4.0 (or Industrie 4.0 as the German version) has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in different countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and prototypes based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.

Calculating utilization rates for rubber tired grapple skidders in the Southern United States

Treesearch

Jason D. Thompson

2001-01-01

Utilization rate is an important factor in calculating machine rates for forest harvesting machines. Machine rates allow an evaluation of harvesting system costs and facilitate comparisons between different systems and machines. There are many factors that affect utilization rate. These include mechanical delays, non-mechanical delays, operational lost time, and...

Research on the tool holder mode in high speed machining

NASA Astrophysics Data System (ADS)

Zhenyu, Zhao; Yongquan, Zhou; Houming, Zhou; Xiaomei, Xu; Haibin, Xiao

2018-03-01

High speed machining technology can improve the processing efficiency and precision, but also reduce the processing cost. Therefore, the technology is widely regarded in the industry. With the extensive application of high-speed machining technology, high-speed tool system has higher and higher requirements on the tool chuck. At present, in high speed precision machining, several new kinds of clip heads are as long as there are heat shrinkage tool-holder, high-precision spring chuck, hydraulic tool-holder, and the three-rib deformation chuck. Among them, the heat shrinkage tool-holder has the advantages of high precision, high clamping force, high bending rigidity and dynamic balance, etc., which are widely used. Therefore, it is of great significance to research the new requirements of the machining tool system. In order to adapt to the requirement of high speed machining precision machining technology, this paper expounds the common tool holder technology of high precision machining, and proposes how to select correctly tool clamping system in practice. The characteristics and existing problems are analyzed in the tool clamping system.

The dynamic analysis of drum roll lathe for machining of rollers

NASA Astrophysics Data System (ADS)

Qiao, Zheng; Wu, Dongxu; Wang, Bo; Li, Guo; Wang, Huiming; Ding, Fei

2014-08-01

An ultra-precision machine tool for machining of the roller has been designed and assembled, and due to the obvious impact which dynamic characteristic of machine tool has on the quality of microstructures on the roller surface, the dynamic characteristic of the existing machine tool is analyzed in this paper, so is the influence of circumstance that a large scale and slender roller is fixed in the machine on dynamic characteristic of the machine tool. At first, finite element model of the machine tool is built and simplified, and based on that, the paper carries on with the finite element mode analysis and gets the natural frequency and shaking type of four steps of the machine tool. According to the above model analysis results, the weak stiffness systems of machine tool can be further improved and the reasonable bandwidth of control system of the machine tool can be designed. In the end, considering the shock which is caused by Z axis as a result of fast positioning frequently to feeding system and cutting tool, transient analysis is conducted by means of ANSYS analysis in this paper. Based on the results of transient analysis, the vibration regularity of key components of machine tool and its impact on cutting process are explored respectively.

Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

NASA Astrophysics Data System (ADS)

Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

2018-03-01

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

Theory of a peristaltic pump for fermionic quantum fluids

NASA Astrophysics Data System (ADS)

Romeo, F.; Citro, R.

2018-05-01

Motivated by the recent developments in fermionic cold atoms and in nanostructured systems, we propose the model of a peristaltic quantum pump. Differently from the Thouless paradigm, a peristaltic pump is a quantum device that generates a particle flux as the effect of a sliding finite-size microlattice. A one-dimensional tight-binding Hamiltonian model of this quantum machine is formulated and analyzed within a lattice Green's function formalism on the Keldysh contour. The pump observables, as, e.g., the pumped particles per cycle, are studied as a function of the pumping frequency, the width of the pumping potential, the particles mean free path, and system temperature. The proposed analysis applies to arbitrary peristaltic potentials acting on fermionic quantum fluids confined to one dimension. These confinement conditions can be realized in nanostructured systems or, in a more controllable way, in cold atoms experiments. In view of the validation of the theoretical results, we describe the outcomes of the model considering a fermionic cold atoms system as a paradigmatic example.

Label-free detection and identification of waterborne parasites using a microfluidic multi-angle laser scattering system

NASA Astrophysics Data System (ADS)

Huang, Wei; Yang, Limei; Lei, Lei; Li, Feng

2017-10-01

A microfluidic-based multi-angle laser scattering (MALS) system capable of acquiring scattering patterns of a single particle is designed and demonstrated. The system includes a sheathless nozzle microfluidic glass chip, and an on-chip MALS unit being in alignment with the nozzle exit in the chip. The size and relative refractive indices (RI) of polystyrene (PS) microspheres were deduced with accuracies of 60 nm and 0.002 by comparing the experimental scattering patterns with theoretical ones. We measured scattering patterns of waterborne parasites i.e., Cryptosporidium parvum (C.parvum) and Giardia lamblia (G. lamblia), and some other representative species suspended in deionized water at a maximum flow rate of 12 μL/min, and a maximum of 3000 waterborne parasites can be identified within one minute with a mean accuracy higher than 96% by classification of distinctive scattering patterns using a support-vector-machine (SVM) algorithm. The system provides a promising tool for label-free detection of waterborne parasites and other biological contaminants.

Notes on a storage manager for the Clouds kernel

NASA Technical Reports Server (NTRS)

Pitts, David V.; Spafford, Eugene H.

1986-01-01

The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

Detecting Abnormal Machine Characteristics in Cloud Infrastructures

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Das, Kamalika; Matthews, Bryan L.

2011-01-01

In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

ML-o-Scope: A Diagnostic Visualization System for Deep Machine Learning Pipelines

DTIC Science & Technology

2014-05-16

ML-o-scope: a diagnostic visualization system for deep machine learning pipelines Daniel Bruckner Electrical Engineering and Computer Sciences... machine learning pipelines 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f...the system as a support for tuning large scale object-classification pipelines. 1 Introduction A new generation of pipelined machine learning models

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Teleoperators - Manual/automatic system requirements.

NASA Technical Reports Server (NTRS)

Janow, C.; Malone, T. B.

1973-01-01

The teleoperator is defined as a remotely controlled, cybernetic, man-machine system designed to extend and augment man's sensory, manipulative, and cognitive capabilities. The teleoperator system incorporates the decision making, adaptive intelligence without requiring its presence. The man and the machine work as a team, each contributing unique and significant capabilities, and each depending on the other to achieve a common goal. Some of the more significant requirements associated with the development of teleoperator systems technology for space, industry, and medicine are examined. Emphasis is placed on the requirement to more effectively use the man and the machine in any man-machine system.

Supervisory Control System Architecture for Advanced Small Modular Reactors

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

Cetiner, Sacit M; Cole, Daniel L; Fugate, David L

2013-08-01

This technical report was generated as a product of the Supervisory Control for Multi-Modular SMR Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (SMR) Research and Development Program of the U.S. Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular advanced SMR (AdvSMR) plants. This research activity advances the state-of-the art by incorporating decision making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides a brief history ofmore » hierarchical functional architectures and the current state-of-the-art, describes a reference AdvSMR to show the dependencies between systems, presents a hierarchical structure for supervisory control, indicates the importance of understanding trip setpoints, applies a new theoretic approach for comparing architectures, identifies cyber security controls that should be addressed early in system design, and describes ongoing work to develop system requirements and hardware/software configurations.« less

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...

Man Machine Systems in Education.

ERIC Educational Resources Information Center

Sall, Malkit S.

This review of the research literature on the interaction between humans and computers discusses how man machine systems can be utilized effectively in the learning-teaching process, especially in secondary education. Beginning with a definition of man machine systems and comments on the poor quality of much of the computer-based learning material…

Machine Translation Project

NASA Technical Reports Server (NTRS)

Bajis, Katie

1993-01-01

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

Effective Dust Control Systems on Concrete Dowel Drilling Machinery

PubMed Central

Echt, Alan S.; Sanderson, Wayne T.; Mead, Kenneth R.; Feng, H. Amy; Farwick, Daniel R.; Farwick, Dawn Ramsey

2016-01-01

Rotary-type percussion dowel drilling machines, which drill horizontal holes in concrete pavement, have been documented to produce respirable crystalline silica concentrations above recommended exposure criteria. This places operators at potential risk for developing health effects from exposure. United States manufacturers of these machines offer optional dust control systems. The effectiveness of the dust control systems to reduce respirable dust concentrations on two types of drilling machines was evaluated under controlled conditions with the machines operating inside large tent structures in an effort to eliminate secondary exposure sources not related to the dowel-drilling operation. Area air samples were collected at breathing zone height at three locations around each machine. Through equal numbers of sampling rounds with the control systems randomly selected to be on or off, the control systems were found to significantly reduce respirable dust concentrations from a geometric mean of 54 mg per cubic meter to 3.0 mg per cubic meter on one machine and 57 mg per cubic meter to 5.3 mg per cubic meter on the other machine. This research shows that the dust control systems can dramatically reduce respirable dust concentrations by over 90% under controlled conditions. However, these systems need to be evaluated under actual work conditions to determine their effectiveness in reducing worker exposures to crystalline silica below hazardous levels. PMID:27074062

FSW of Aluminum Tailor Welded Blanks across Machine Platforms

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

Hovanski, Yuri; Upadhyay, Piyush; Carlson, Blair

2015-02-16

Development and characterization of friction stir welded aluminum tailor welded blanks was successfully carried out on three separate machine platforms. Each was a commercially available, gantry style, multi-axis machine designed specifically for friction stir welding. Weld parameters were developed to support high volume production of dissimilar thickness aluminum tailor welded blanks at speeds of 3 m/min and greater. Parameters originally developed on an ultra-high stiffness servo driven machine where first transferred to a high stiffness servo-hydraulic friction stir welding machine, and subsequently transferred to a purpose built machine designed to accommodate thin sheet aluminum welding. The inherent beam stiffness, bearingmore » compliance, and control system for each machine were distinctly unique, which posed specific challenges in transferring welding parameters across machine platforms. This work documents the challenges imposed by successfully transferring weld parameters from machine to machine, produced from different manufacturers and with unique control systems and interfaces.« less

Derivative Free Optimization of Complex Systems with the Use of Statistical Machine Learning Models

DTIC Science & Technology

2015-09-12

AFRL-AFOSR-VA-TR-2015-0278 DERIVATIVE FREE OPTIMIZATION OF COMPLEX SYSTEMS WITH THE USE OF STATISTICAL MACHINE LEARNING MODELS Katya Scheinberg...COMPLEX SYSTEMS WITH THE USE OF STATISTICAL MACHINE LEARNING MODELS 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-11-1-0239 5c.  PROGRAM ELEMENT...developed, which has been the focus of our research. 15. SUBJECT TERMS optimization, Derivative-Free Optimization, Statistical Machine Learning 16. SECURITY

Vacation model for Markov machine repair problem with two heterogeneous unreliable servers and threshold recovery

NASA Astrophysics Data System (ADS)

Jain, Madhu; Meena, Rakesh Kumar

2018-03-01

Markov model of multi-component machining system comprising two unreliable heterogeneous servers and mixed type of standby support has been studied. The repair job of broken down machines is done on the basis of bi-level threshold policy for the activation of the servers. The server returns back to render repair job when the pre-specified workload of failed machines is build up. The first (second) repairman turns on only when the work load of N1 (N2) failed machines is accumulated in the system. The both servers may go for vacation in case when all the machines are in good condition and there are no pending repair jobs for the repairmen. Runge-Kutta method is implemented to solve the set of governing equations used to formulate the Markov model. Various system metrics including the mean queue length, machine availability, throughput, etc., are derived to determine the performance of the machining system. To provide the computational tractability of the present investigation, a numerical illustration is provided. A cost function is also constructed to determine the optimal repair rate of the server by minimizing the expected cost incurred on the system. The hybrid soft computing method is considered to develop the adaptive neuro-fuzzy inference system (ANFIS). The validation of the numerical results obtained by Runge-Kutta approach is also facilitated by computational results generated by ANFIS.

Distributed communications and control network for robotic mining

NASA Technical Reports Server (NTRS)

Schiffbauer, William H.

1989-01-01

The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.

Research on computer systems benchmarking

NASA Technical Reports Server (NTRS)

Smith, Alan Jay (Principal Investigator)

1996-01-01

This grant addresses the topic of research on computer systems benchmarking and is more generally concerned with performance issues in computer systems. This report reviews work in those areas during the period of NASA support under this grant. The bulk of the work performed concerned benchmarking and analysis of CPUs, compilers, caches, and benchmark programs. The first part of this work concerned the issue of benchmark performance prediction. A new approach to benchmarking and machine characterization was reported, using a machine characterizer that measures the performance of a given system in terms of a Fortran abstract machine. Another report focused on analyzing compiler performance. The performance impact of optimization in the context of our methodology for CPU performance characterization was based on the abstract machine model. Benchmark programs are analyzed in another paper. A machine-independent model of program execution was developed to characterize both machine performance and program execution. By merging these machine and program characterizations, execution time can be estimated for arbitrary machine/program combinations. The work was continued into the domain of parallel and vector machines, including the issue of caches in vector processors and multiprocessors. All of the afore-mentioned accomplishments are more specifically summarized in this report, as well as those smaller in magnitude supported by this grant.

Knowledge-based load leveling and task allocation in human-machine systems

NASA Technical Reports Server (NTRS)

Chignell, M. H.; Hancock, P. A.

1986-01-01

Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

A system framework of inter-enterprise machining quality control based on fractal theory

NASA Astrophysics Data System (ADS)

Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng

2014-03-01

In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.

Energy Survey of Machine Tools: Separating Power Information of the Main Transmission System During Machining Process

NASA Astrophysics Data System (ADS)

Liu, Shuang; Liu, Fei; Hu, Shaohua; Yin, Zhenbiao

The major power information of the main transmission system in machine tools (MTSMT) during machining process includes effective output power (i.e. cutting power), input power and power loss from the mechanical transmission system, and the main motor power loss. These information are easy to obtain in the lab but difficult to evaluate in a manufacturing process. To solve this problem, a separation method is proposed here to extract the MTSMT power information during machining process. In this method, the energy flow and the mathematical models of major power information of MTSMT during the machining process are set up first. Based on the mathematical models and the basic data tables obtained from experiments, the above mentioned power information during machining process can be separated just by measuring the real time total input power of the spindle motor. The operation program of this method is also given.

A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

1990-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

A model predictive current control of flux-switching permanent magnet machines for torque ripple minimization

NASA Astrophysics Data System (ADS)

Huang, Wentao; Hua, Wei; Yu, Feng

2017-05-01

Due to high airgap flux density generated by magnets and the special double salient structure, the cogging torque of the flux-switching permanent magnet (FSPM) machine is considerable, which limits the further applications. Based on the model predictive current control (MPCC) and the compensation control theory, a compensating-current MPCC (CC-MPCC) scheme is proposed and implemented to counteract the dominated components in cogging torque of an existing three-phase 12/10 FSPM prototyped machine, and thus to alleviate the influence of the cogging torque and improve the smoothness of electromagnetic torque as well as speed, where a comprehensive cost function is designed to evaluate the switching states. The simulated results indicate that the proposed CC-MPCC scheme can suppress the torque ripple significantly and offer satisfactory dynamic performances by comparisons with the conventional MPCC strategy. Finally, experimental results validate both the theoretical and simulated predictions.

Self-replicating machines in continuous space with virtual physics.

PubMed

Smith, Arnold; Turney, Peter; Ewaschuk, Robert

2003-01-01

JohnnyVon is an implementation of self-replicating machines in continuous two-dimensional space. Two types of particles drift about in a virtual liquid. The particles are automata with discrete internal states but continuous external relationships. Their internal states are governed by finite state machines, but their external relationships are governed by a simulated physics that includes Brownian motion, viscosity, and springlike attractive and repulsive forces. The particles can be assembled into patterns that can encode arbitrary strings of bits. We demonstrate that, if an arbitrary seed pattern is put in a soup of separate individual particles, the pattern will replicate by assembling the individual particles into copies of itself. We also show that, given sufficient time, a soup of separate individual particles will eventually spontaneously form self-replicating patterns. We discuss the implications of JohnnyVon for research in nanotechnology, theoretical biology, and artificial life.

The design and test of collecting device and film purge device joint work of residual film recovery machine based on Solidworks & Adams

NASA Astrophysics Data System (ADS)

Zhai, Haozhou; Jian, Jianming; Hou, Shulin; San, Yunlong; Guo, Wensong; Sun, Yue; Gao, Mingqing

2018-03-01

The twine of residual film is an essential issue in the process of remnant residue recovery of the residual film recovery machine. It is difficult to clean up the residual film in the residual film recovery operation and to influence the subsequent film efficiency. Therefore, in response to this problem a composite tooth pocket residual film recovery device was designed. In this paper, the structure of the film recovery device design, theoretical analysis, simulation experiments, get the most appropriate film recovery device parameters. In addition, the residual film rate of the membrane is dramatically low, reaching about 1.3% only, and the operation of the whole machine is smoother, and the stability of the work is promoted. The operation of the film recovery device is very obvious. Lifting, in addition to the film rate has also been significantly improved to 93.88%

CFD Aided Design and Production of Hydraulic Turbines

NASA Astrophysics Data System (ADS)

Kaplan, Alper; Cetinturk, Huseyin; Demirel, Gizem; Ayli, Ece; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

2014-11-01

Hydraulic turbines are turbo machines which produce electricity from hydraulic energy. Francis type turbines are the most common one in use today. The design of these turbines requires high engineering effort since each turbine is tailor made due to different head and discharge. Therefore each component of the turbine is designed specifically. During the last decades, Computational Fluid Dynamics (CFD) has become very useful tool to predict hydraulic machinery performance and save time and money for designers. This paper describes a design methodology to optimize a Francis turbine by integrating theoretical and experimental fundamentals of hydraulic machines and commercial CFD codes. Specific turbines are designed and manufactured with the help of a collaborative CFD/CAD/CAM methodology based on computational fluid dynamics and five-axis machining for hydraulic electric power plants. The details are presented in this study. This study is financially supported by Turkish Ministry of Development.

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution

PubMed Central

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis. PMID:26958271

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

PubMed

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis.

Quantum machine learning.

PubMed

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

2017-09-13

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

Quantum machine learning

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Mesoplasticity approach to studies of the cutting mechanism in ultra-precision machining

NASA Astrophysics Data System (ADS)

Lee, Rongbin W. B.; Wang, Hao; To, Suet; Cheung, Chi Fai; Chan, Chang Yuen

2014-03-01

There have been various theoretical attempts by researchers worldwide to link up different scales of plasticity studies from the nano-, micro- and macro-scale of observation, based on molecular dynamics, crystal plasticity and continuum mechanics. Very few attempts, however, have been reported in ultra-precision machining studies. A mesoplasticity approach advocated by Lee and Yang is adopted by the authors and is successfully applied to studies of the micro-cutting mechanisms in ultra-precision machining. Traditionally, the shear angle in metal cutting, as well as the cutting force variation, can only be determined from cutting tests. In the pioneering work of the authors, the use of mesoplasticity theory enables prediction of the fluctuation of the shear angle and micro-cutting force, shear band formation, chip morphology in diamond turning and size effect in nano-indentation. These findings are verified by experiments. The mesoplasticity formulation opens up a new direction of studies to enable how the plastic behaviour of materials and their constitutive representations in deformation processing, such as machining can be predicted, assessed and deduced from the basic properties of the materials measurable at the microscale.

Equivalent model of a dually-fed machine for electric drive control systems

NASA Astrophysics Data System (ADS)

Ostrovlyanchik, I. Yu; Popolzin, I. Yu

2018-05-01

The article shows that the mathematical model of a dually-fed machine is complicated because of the presence of a controlled voltage source in the rotor circuit. As a method of obtaining a mathematical model, the method of a generalized two-phase electric machine is applied and a rotating orthogonal coordinate system is chosen that is associated with the representing vector of a stator current. In the chosen coordinate system in the operator form the differential equations of electric equilibrium for the windings of the generalized machine (the Kirchhoff equation) are written together with the expression for the moment, which determines the electromechanical energy transformation in the machine. Equations are transformed so that they connect the currents of the windings, that determine the moment of the machine, and the voltages on these windings. The structural diagram of the machine is assigned to the written equations. Based on the written equations and accepted assumptions, expressions were obtained for the balancing the EMF of windings, and on the basis of these expressions an equivalent mathematical model of a dually-fed machine is proposed, convenient for use in electric drive control systems.

Embedded control system for computerized franking machine

NASA Astrophysics Data System (ADS)

Shi, W. M.; Zhang, L. B.; Xu, F.; Zhan, H. W.

2007-12-01

This paper presents a novel control system for franking machine. A methodology for operating a franking machine using the functional controls consisting of connection, configuration and franking electromechanical drive is studied. A set of enabling technologies to synthesize postage management software architectures driven microprocessor-based embedded systems is proposed. The cryptographic algorithm that calculates mail items is analyzed to enhance the postal indicia accountability and security. The study indicated that the franking machine is reliability, performance and flexibility in printing mail items.

Operating System For Numerically Controlled Milling Machine

NASA Technical Reports Server (NTRS)

Ray, R. B.

1992-01-01

OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

Ada (Tradename) Compiler Validation Summary Report. International Business Machines Corporation. IBM Development System for the Ada Language for MVS, Version 1.0. IBM 4381 (IBM System/370) under MVS.

DTIC Science & Technology

1986-05-05

AVF-VSR-36.0187 Ada" COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM Development System for the Ada Language for...withdrawn from ACVC Version 1.7 were not run. The compiler was tested using command scripts provided by International Business Machines Corporation. These...APPENDIX A COMPLIANCE STATEMENT International Business Machines Corporation has submitted the following compliance statement concerning the IBM

Methods, systems and apparatus for synchronous current regulation of a five-phase machine

DOEpatents

Gallegos-Lopez, Gabriel; Perisic, Milun

2012-10-09

Methods, systems and apparatus are provided for controlling operation of and regulating current provided to a five-phase machine when one or more phases has experienced a fault or has failed. In one implementation, the disclosed embodiments can be used to synchronously regulate current in a vector controlled motor drive system that includes a five-phase AC machine, a five-phase inverter module coupled to the five-phase AC machine, and a synchronous current regulator.

Switching Circuit for Shop Vacuum System

NASA Technical Reports Server (NTRS)

Burley, R. K.

1987-01-01

No internal connections to machine tools required. Switching circuit controls vacuum system draws debris from grinders and sanders in machine shop. Circuit automatically turns on vacuum system whenever at least one sander or grinder operating. Debris safely removed, even when operator neglects to turn on vacuum system manually. Pickup coils sense alternating magnetic fields just outside operating machines. Signal from any coil or combination of coils causes vacuum system to be turned on.

Navy Acquisition. SUBACS (Submarine Advanced Combat System) Problems May Adversely Affect Navy Attack Submarine Programs.

DTIC Science & Technology

1985-11-01

also the combat system design for the proposed new attack submarine class, SSN 21. In December 1983, the Navy awarded the International Business Machines...VI: Comments From International Business 35 Machines Corporation Abbreviations DNSARC Department of the Navy Systems Acquisition Review Council DSARC...Defense Systems Acquisition Review Council GAO General Accounting Office IBM International Business Machines Corporation NAVsEA Naval Sea Systems

77 FR 7 - Revisions to Labeling Requirements for Blood and Blood Components, Including Source Plasma

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-03

... requirements will facilitate the use of a labeling system using machine-readable information that would be... components. Furthermore, we proposed the use of a labeling system using machine-readable information that...; Facilitates the use of a labeling system using machine- readable information that would be acceptable as a...

Karaoke for quads: a new application of an old recreation with potential therapeutic benefits for people with disabilities.

PubMed

Batavia, A I; Batavia, M

2003-03-18

Karaoke is a recreational activity whereby individuals sing into a microphone along with the melodies and lyrics provided both visually and auditorily by a machine. The potential therapeutic benefits of karaoke are explored in terms of increased respiratory strength, endurance, control, and capacity, as well as emotional and physical release for people with disabilities. Although many individuals with disabilities could benefit from this activity, it is likely to be particularly beneficial to people with compromised respiratory systems, such as persons with high-level quadriplegia (tetraplegia). This article examines theoretical considerations and proposes a research agenda. Empirical research would be valuable to confirm the potential benefits of karaoke for people with disabilities.

Biologische Wirkungen der Bestrahlung mit schweren Ionen

NASA Astrophysics Data System (ADS)

Kiefer, Jürgen

1982-06-01

Experiments with accelerated heavy ions may contribute to the understanding of biological radiation action. After outlining the theoretical background experiments are described which were carried out at the UNILAC-machine (Gesellschaft für Schwerionenforschung, Darmstadt, Germany) where ions up to uranium can be accelerated to maximal specific energies of 10 MeV/u. Yeast cells served as biological test systems with the synthesis of ribosomal RNA (r-RNA), colony-forming ability and mutation induction as experimental endpoints. A relationship between action and energy deposition by individual particles can be demonstrated for the inhibition of r-RNA synthesis, in other cases the ion energy plays also an important role indicating that the interaction of δ-electrons from different particles contributes significantly to the biological effect.

Fluid flow dynamics in MAS systems.

PubMed

Wilhelm, Dirk; Purea, Armin; Engelke, Frank

2015-08-01

The turbine system and the radial bearing of a high performance magic angle spinning (MAS) probe with 1.3mm-rotor diameter has been analyzed for spinning rates up to 67kHz. We focused mainly on the fluid flow properties of the MAS system. Therefore, computational fluid dynamics (CFD) simulations and fluid measurements of the turbine and the radial bearings have been performed. CFD simulation and measurement results of the 1.3mm-MAS rotor system show relatively low efficiency (about 25%) compared to standard turbo machines outside the realm of MAS. However, in particular, MAS turbines are mainly optimized for speed and stability instead of efficiency. We have compared MAS systems for rotor diameter of 1.3-7mm converted to dimensionless values with classical turbomachinery systems showing that the operation parameters (rotor diameter, inlet mass flow, spinning rate) are in the favorable range. This dimensionless analysis also supports radial turbines for low speed MAS probes and diagonal turbines for high speed MAS probes. Consequently, a change from Pelton type MAS turbines to diagonal turbines might be worth considering for high speed applications. CFD simulations of the radial bearings have been compared with basic theoretical values proposing considerably smaller frictional loss values. The discrepancies might be due to the simple linear flow profile employed for the theoretical model. Frictional losses generated inside the radial bearings result in undesired heat-up of the rotor. The rotor surface temperature distribution computed by CFD simulations show a large temperature gradient over the rotor. Copyright © 2015 Elsevier Inc. All rights reserved.

Massively parallel first-principles simulation of electron dynamics in materials

DOE PAGES

Draeger, Erik W.; Andrade, Xavier; Gunnels, John A.; ...

2017-08-01

Here we present a highly scalable, parallel implementation of first-principles electron dynamics coupled with molecular dynamics (MD). By using optimized kernels, network topology aware communication, and by fully distributing all terms in the time-dependent Kohn–Sham equation, we demonstrate unprecedented time to solution for disordered aluminum systems of 2000 atoms (22,000 electrons) and 5400 atoms (59,400 electrons), with wall clock time as low as 7.5 s per MD time step. Despite a significant amount of non-local communication required in every iteration, we achieved excellent strong scaling and sustained performance on the Sequoia Blue Gene/Q supercomputer at LLNL. We obtained up tomore » 59% of the theoretical sustained peak performance on 16,384 nodes and performance of 8.75 Petaflop/s (43% of theoretical peak) on the full 98,304 node machine (1,572,864 cores). Lastly, scalable explicit electron dynamics allows for the study of phenomena beyond the reach of standard first-principles MD, in particular, materials subject to strong or rapid perturbations, such as pulsed electromagnetic radiation, particle irradiation, or strong electric currents.« less

Massively parallel first-principles simulation of electron dynamics in materials

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

Draeger, Erik W.; Andrade, Xavier; Gunnels, John A.

Here we present a highly scalable, parallel implementation of first-principles electron dynamics coupled with molecular dynamics (MD). By using optimized kernels, network topology aware communication, and by fully distributing all terms in the time-dependent Kohn–Sham equation, we demonstrate unprecedented time to solution for disordered aluminum systems of 2000 atoms (22,000 electrons) and 5400 atoms (59,400 electrons), with wall clock time as low as 7.5 s per MD time step. Despite a significant amount of non-local communication required in every iteration, we achieved excellent strong scaling and sustained performance on the Sequoia Blue Gene/Q supercomputer at LLNL. We obtained up tomore » 59% of the theoretical sustained peak performance on 16,384 nodes and performance of 8.75 Petaflop/s (43% of theoretical peak) on the full 98,304 node machine (1,572,864 cores). Lastly, scalable explicit electron dynamics allows for the study of phenomena beyond the reach of standard first-principles MD, in particular, materials subject to strong or rapid perturbations, such as pulsed electromagnetic radiation, particle irradiation, or strong electric currents.« less

[Neurophysiological Foundations and Practical Realizations of the Brain-Machine Interfaces the Technology in Neurological Rehabilitation].

PubMed

Kaplan, A Ya

2016-01-01

Technology brain-computer interface (BCI) based on the registration and interpretation of EEG has recently become one of the most popular developments in neuroscience and psychophysiology. This is due not only to the intended future use of these technologies in many areas of practical human activity, but also to the fact that IMC--is a completely new paradigm in psychophysiology, allowing test hypotheses about the possibilities of the human brain to the development of skills of interaction with the outside world without the mediation of the motor system, i.e. only with the help of voluntary modulation of EEG generators. This paper examines the theoretical and experimental basis, the current state and prospects of development of training, communicational and assisting complexes based on BCI to control them without muscular effort on the basis of mental commands detected in the EEG of patients with severely impaired speech and motor system.

Analytic study of a rolling sphere on a rough surface

NASA Astrophysics Data System (ADS)

Florea, Olivia A.; Rosca, Ileana C.

2016-11-01

In this paper it is realized an analytic study of the rolling's sphere on a rough horizontal plane under the action of its own gravity. The necessities of integration of the system of dynamical equations of motion lead us to find a reference system where the motion equations should be transformed into simpler expressions and which, in the presence of some significant hypothesis to permit the application of some original methods of analytical integration. In technical applications, the bodies may have a free rolling motion or a motion constrained by geometrical relations in assemblies of parts and machine parts. This study involves a lot of investigations in the field of tribology and of applied dynamics accompanied by experiments. Multiple recordings of several trajectories of the sphere, as well as their treatment of images, also followed by statistical processing experimental data allowed highlighting a very good agreement between the theoretical findings and experimental results.

Preliminary Results of the 115 kJ Dense Plasma Focus Device IR-MPF-100

NASA Astrophysics Data System (ADS)

Salehizadeh, A.; Sadighzadeh, A.; Movahhed, M. Sedaghat; Zaeem, A. A.; Heidarnia, A.; Sabri, R.; Mahmoudi, M. Bakhshzad; Rahimi, H.; Rahimi, S.; Johari, E.; Torabi, M.; Damideh, V.

2013-04-01

This work summarizes the design and construction of the first Iranian 115 kJ Mather type plasma focus (PF) machine (IR-MPF-100). This machine consists of a 6.25 cm radius and 22 cm height brass made anode with a 50 mm height insulator which separates the anode and cathode electrodes. Twelve copper made 22 cm height rods play the role of cathode with 10.2 cm radius. Twenty four 6 μF capacitors were used with the maximum charging voltage of 40 kV (maximum energy of 115 kJ) as the capacitor bank and maximum theoretical current around 1.224 MA. The total inductance of the system is 120 nH. By using NE-102 plastic Scintillator, Rogowski coil, current and voltage probes, hard X-ray, current derivative, current and voltage signals of IR-MPF-100 were measured. The primary result of neutron detection by neutron activation counter represents approximately 109 neutrons per shot at 65 kJ discharge energy while using deuterium filling gas. Also IR-MPF-100 PF has been tested successfully at 90 kJ by using the argon gas.

Torque Production in a Halbach Machine

NASA Technical Reports Server (NTRS)

Eichenberg, Dennis J.; Gallo, Christopher A.; Thompson, William K.; Vrnak, Daniel R.

2006-01-01

The NASA John H. Glenn Research Center initiated the investigation of torque production in a Halbach machine for the Levitated Ducted Fan (LDF) Project to obtain empirical data in determining the feasibility of using a Halbach motor for the project. LDF is a breakthrough technology for "Electric Flight" with the development of a clean, quiet, electric propulsor system. Benefits include zero emissions, decreased dependence on fossil fuels, increased efficiency, increased reliability, reduced maintenance, and decreased operating noise levels. A commercial permanent magnet brushless motor rotor was tested with a custom stator. An innovative rotor utilizing a Halbach array was designed and developed to fit directly into the same stator. The magnets are oriented at 90deg to the adjacent magnet, which cancels the magnetic field on the inside of the rotor and strengthens the field on the outside of the rotor. A direct comparison of the commercial rotor and the Halbach rotor was made. In addition, various test models were designed and developed to validate the basic principles described, and the theoretical work that was performed. The report concludes that a Halbach array based motor can provide significant improvements in electric motor performance and reliability.

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

PubMed

Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2018-06-12

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

1992-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

Neural Networks for Modeling and Control of Particle Accelerators

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

Edelen, A. L.; Biedron, S. G.; Chase, B. E.

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Neural Networks for Modeling and Control of Particle Accelerators

NASA Astrophysics Data System (ADS)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Networks for Modeling and Control of Particle Accelerators

DOE PAGES

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

2016-04-01

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Proceeding of human exoskeleton technology and discussions on future research

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Xie, Hanxing; Li, Weilin; Yao, Zheng

2014-05-01

After more than half a century of intense efforts, the development of exoskeleton has seen major advances, and several remarkable achievements have been made. Reviews of developing history of exoskeleton are presented, both in active and passive categories. Major models are introduced, and typical technologies are commented on. Difficulties in control algorithm, driver system, power source, and man-machine interface are discussed. Current researching routes and major developing methods are mapped and critically analyzed, and in the process, some key problems are revealed. First, the exoskeleton is totally different from biped robot, and relative studies based on the robot technologies are considerably incorrect. Second, biomechanical studies are only used to track the motion of the human body, the interaction between human and machines are seldom studied. Third, the traditional developing ways which focused on servo-controlling have inborn deficiency from making portable systems. Research attention should be shifted to the human side of the coupling system, and the human ability to learn and adapt should play a more significant role in the control algorithms. Having summarized the major difficulties, possible future works are discussed. It is argued that, since a distinct boundary cannot be drawn in such strong-coupling human-exoskeleton system, the more complex the control system gets, the more difficult it is for the user to learn to use. It is suggested that the exoskeleton should be treated as a simple wearable tool, and downgrading its automatic level may be a change toward a brighter research outlook. This effort at simplification is definitely not easy, as it necessitates theoretical supports from fields such as biomechanics, ergonomics, and bionics.

Effective dust control systems on concrete dowel drilling machinery.

PubMed

Echt, Alan S; Sanderson, Wayne T; Mead, Kenneth R; Feng, H Amy; Farwick, Daniel R; Farwick, Dawn Ramsey

2016-09-01

Rotary-type percussion dowel drilling machines, which drill horizontal holes in concrete pavement, have been documented to produce respirable crystalline silica concentrations above recommended exposure criteria. This places operators at potential risk for developing health effects from exposure. United States manufacturers of these machines offer optional dust control systems. The effectiveness of the dust control systems to reduce respirable dust concentrations on two types of drilling machines was evaluated under controlled conditions with the machines operating inside large tent structures in an effort to eliminate secondary exposure sources not related to the dowel-drilling operation. Area air samples were collected at breathing zone height at three locations around each machine. Through equal numbers of sampling rounds with the control systems randomly selected to be on or off, the control systems were found to significantly reduce respirable dust concentrations from a geometric mean of 54 mg per cubic meter to 3.0 mg per cubic meter on one machine and 57 mg per cubic meter to 5.3 mg per cubic meter on the other machine. This research shows that the dust control systems can dramatically reduce respirable dust concentrations by over 90% under controlled conditions. However, these systems need to be evaluated under actual work conditions to determine their effectiveness in reducing worker exposures to crystalline silica below hazardous levels.

Study of Man-Machine Communications Systems for the Handicapped. Volume III. Final Report.

ERIC Educational Resources Information Center

Kafafian, Haig

The report describes a series of studies conducted to determine the extent to which severly handicapped students who were able to comprehend language and language structure but who were not able to write or type could communicate using various man-machine systems. Included among the systems tested were specialized electric typewriting machines, a…

Performance evaluation of the croissant production line with reparable machines

NASA Astrophysics Data System (ADS)

Tsarouhas, Panagiotis H.

2015-03-01

In this study, the analytical probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system's behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.

Interferometric correction system for a numerically controlled machine

DOEpatents

Burleson, Robert R.

1978-01-01

An interferometric correction system for a numerically controlled machine is provided to improve the positioning accuracy of a machine tool, for example, for a high-precision numerically controlled machine. A laser interferometer feedback system is used to monitor the positioning of the machine tool which is being moved by command pulses to a positioning system to position the tool. The correction system compares the commanded position as indicated by a command pulse train applied to the positioning system with the actual position of the tool as monitored by the laser interferometer. If the tool position lags the commanded position by a preselected error, additional pulses are added to the pulse train applied to the positioning system to advance the tool closer to the commanded position, thereby reducing the lag error. If the actual tool position is leading in comparison to the commanded position, pulses are deleted from the pulse train where the advance error exceeds the preselected error magnitude to correct the position error of the tool relative to the commanded position.

User-Driven Sampling Strategies in Image Exploitation

DOE PAGES

Harvey, Neal R.; Porter, Reid B.

2013-12-23

Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-drivenmore » sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. We discovered that in user-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. Furthermore, in preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.« less

User-driven sampling strategies in image exploitation

NASA Astrophysics Data System (ADS)

Harvey, Neal; Porter, Reid

2013-12-01

Visual analytics and interactive machine learning both try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human-computer interaction. This paper focuses on one aspect of the human-computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteration, we investigate situations where the user selects which data is to be labeled at each iteration. User-driven sampling strategies can emerge in many visual analytics applications but they have not been fully developed in machine learning. User-driven sampling strategies suggest new theoretical and practical research questions for both visualization science and machine learning. In this paper we identify and quantify the potential benefits of these strategies in a practical image analysis application. We find user-driven sampling strategies can sometimes provide significant performance gains by steering tools towards local minima that have lower error than tools trained with all of the data. In preliminary experiments we find these performance gains are particularly pronounced when the user is experienced with the tool and application domain.

A comparative analysis of support vector machines and extreme learning machines.

PubMed

Liu, Xueyi; Gao, Chuanhou; Li, Ping

2012-09-01

The theory of extreme learning machines (ELMs) has recently become increasingly popular. As a new learning algorithm for single-hidden-layer feed-forward neural networks, an ELM offers the advantages of low computational cost, good generalization ability, and ease of implementation. Hence the comparison and model selection between ELMs and other kinds of state-of-the-art machine learning approaches has become significant and has attracted many research efforts. This paper performs a comparative analysis of the basic ELMs and support vector machines (SVMs) from two viewpoints that are different from previous works: one is the Vapnik-Chervonenkis (VC) dimension, and the other is their performance under different training sample sizes. It is shown that the VC dimension of an ELM is equal to the number of hidden nodes of the ELM with probability one. Additionally, their generalization ability and computational complexity are exhibited with changing training sample size. ELMs have weaker generalization ability than SVMs for small sample but can generalize as well as SVMs for large sample. Remarkably, great superiority in computational speed especially for large-scale sample problems is found in ELMs. The results obtained can provide insight into the essential relationship between them, and can also serve as complementary knowledge for their past experimental and theoretical comparisons. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Research on axisymmetric aspheric surface numerical design and manufacturing technology

NASA Astrophysics Data System (ADS)

Wang, Zhen-zhong; Guo, Yin-biao; Lin, Zheng

2006-02-01

The key technology for aspheric machining offers exact machining path and machining aspheric lens with high accuracy and efficiency, in spite of the development of traditional manual manufacturing into nowadays numerical control (NC) machining. This paper presents a mathematical model between virtual cone and aspheric surface equations, and discusses the technology of uniform wear of grinding wheel and error compensation in aspheric machining. Finally, a software system for high precision aspheric surface manufacturing is designed and realized, based on the mentioned above. This software system can work out grinding wheel path according to input parameters and generate machining NC programs of aspheric surfaces.

Self-assembled software and method of overriding software execution

DOEpatents

Bouchard, Ann M.; Osbourn, Gordon C.

2013-01-08

A computer-implemented software self-assembled system and method for providing an external override and monitoring capability to dynamically self-assembling software containing machines that self-assemble execution sequences and data structures. The method provides an external override machine that can be introduced into a system of self-assembling machines while the machines are executing such that the functionality of the executing software can be changed or paused without stopping the code execution and modifying the existing code. Additionally, a monitoring machine can be introduced without stopping code execution that can monitor specified code execution functions by designated machines and communicate the status to an output device.

48 CFR 908.7103 - Office machines.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Office machines. 908.7103 Section 908.7103 Federal Acquisition Regulations System DEPARTMENT OF ENERGY COMPETITION ACQUISITION PLANNING REQUIRED SOURCES OF SUPPLIES AND SERVICES Acquisition of Special Items 908.7103 Office machines...

Cooperating reduction machines

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

Kluge, W.E.

1983-11-01

This paper presents a concept and a system architecture for the concurrent execution of program expressions of a concrete reduction language based on lamda-expressions. If formulated appropriately, these expressions are well-suited for concurrent execution, following a demand-driven model of computation. In particular, recursive program expressions with nonlinear expansion may, at run time, recursively be partitioned into a hierarchy of independent subexpressions which can be reduced by a corresponding hierarchy of virtual reduction machines. This hierarchy unfolds and collapses dynamically, with virtual machines recursively assuming the role of masters that create and eventually terminate, or synchronize with, slaves. The paper alsomore » proposes a nonhierarchically organized system of reduction machines, each featuring a stack architecture, that effectively supports the allocation of virtual machines to the real machines of the system in compliance with their hierarchical order of creation and termination. 25 references.« less

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

Identification of dynamic characteristics of flexible rotors as dynamic inverse problem

NASA Technical Reports Server (NTRS)

Roisman, W. P.; Vajingortin, L. D.

1991-01-01

The problem of dynamic and balancing of flexible rotors were considered, which were set and solved as the problem of the identification of flexible rotor systems, which is the same as the inverse problem of the oscillation theory dealing with the task of the identifying the outside influences and system parameters on the basis of the known laws of motion. This approach to the problem allows the disclosure the picture of disbalances throughout the rotor-under-test (which traditional methods of flexible rotor balancing, based on natural oscillations, could not provide), and identify dynamic characteristics of the system, which correspond to a selected mathematical model. Eventually, various methods of balancing were developed depending on the special features of the machines as to their design, technology, and operation specifications. Also, theoretical and practical methods are given for the flexible rotor balancing at far from critical rotation frequencies, which does not necessarily require the knowledge forms of oscillation, dissipation, and elasticity and inertia characteristics, and to use testing masses.

Proceedings of the 1986 IEEE international conference on systems, man and cybernetics

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

Not Available

1986-01-01

This book presents the papers given at a conference on man-machine systems. Topics considered at the conference included neural model-based cognitive theory and engineering, user interfaces, adaptive and learning systems, human interaction with robotics, decision making, the testing and evaluation of expert systems, software development, international conflict resolution, intelligent interfaces, automation in man-machine system design aiding, knowledge acquisition in expert systems, advanced architectures for artificial intelligence, pattern recognition, knowledge bases, and machine vision.

Water spray ventilator system for continuous mining machines

DOEpatents

Page, Steven J.; Mal, Thomas

1995-01-01

The invention relates to a water spray ventilator system mounted on a continuous mining machine to streamline airflow and provide effective face ventilation of both respirable dust and methane in underground coal mines. This system has two side spray nozzles mounted one on each side of the mining machine and six spray nozzles disposed on a manifold mounted to the underside of the machine boom. The six spray nozzles are angularly and laterally oriented on the manifold so as to provide non-overlapping spray patterns along the length of the cutter drum.

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10066 International Business Machines Corporation, IBM Development System for the Ada Language, AIX/RT Ada Compiler, Version 1.1.1, IBM RT PC 6150-125

DTIC Science & Technology

1989-04-20

International Business Machines Corporation, IBM Development System. for the Ada Language AIX/RT Ada Compiler, Version 1.1.1, Wright-Patterson APB...Certificate Number: 890420V1.10066 International Business Machines Corporation IBM Development System for the Ada Language AIX/RT Ada Compiler, Version 1.1.1...TEST INFORMATION The compiler was tested using command scripts provided by International Business Machines Corporation and reviewed by the validation

Arc detection for the ICRF system on ITER

NASA Astrophysics Data System (ADS)

D'Inca, R.

2011-12-01

The ICRF system for ITER is designed to respect the high voltage breakdown limits. However arcs can still statistically happen and must be quickly detected and suppressed by shutting the RF power down. For the conception of a reliable and efficient detector, the analysis of the mechanism of arcs is necessary to find their unique signature. Numerous systems have been conceived to address the issues of arc detection. VSWR-based detectors, RF noise detectors, sound detectors, optical detectors, S-matrix based detectors. Until now, none of them has succeeded in demonstrating the fulfillment of all requirements and the studies for ITER now follow three directions: improvement of the existing concepts to fix their flaws, development of new theoretically fully compliant detectors (like the GUIDAR) and combination of several detectors to benefit from the advantages of each of them. Together with the physical and engineering challenges, the development of an arc detection system for ITER raises methodological concerns to extrapolate the results from basic experiments and present machines to the ITER scale ICRF system and to conduct a relevant risk analysis.

Human evolution in the age of the intelligent machine

NASA Technical Reports Server (NTRS)

Mclaughlin, W. I.

1983-01-01

A systems analysis of the future evolution of man can be conducted by analyzing the biological material of the galaxy into three subsystems: man, intelligent machines, and intelligent extraterrestrial organisms. A binomial interpretation is applied to this system wherein each of the subsystems is assigned a designation of success or failure. For man the two alternatives are, respectively, 'decline' or 'flourish', for machine they are 'become intelligent' or 'stay dumb', while for extraterrestrial intelligence the dichotomy is that of 'existence' or 'nonexistence'. The choices for each of three subsystems yield a total of eight possible states for the system. The relative lack of integration between brain components makes man a weak evolutionary contestant compared to machines. It is judged that machines should become dominant on earth within 100 years, probably by means of continuing development of existing man-machine systems. Advanced forms of extraterrestrial intelligence may exist but are too difficult to observe. The prospects for communication with extraterrestrial intelligence are reviewed.

Human evolution in the age of the intelligent machine

NASA Astrophysics Data System (ADS)

McLaughlin, W. I.

A systems analysis of the future evolution of man can be conducted by analyzing the biological material of the galaxy into three subsystems: man, intelligent machines, and intelligent extraterrestrial organisms. A binomial interpretation is applied to this system wherein each of the subsystems is assigned a designation of success or failure. For man the two alternatives are, respectively, 'decline' or 'flourish', for machine they are 'become intelligent' or 'stay dumb', while for extraterrestrial intelligence the dichotomy is that of 'existence' or 'nonexistence'. The choices for each of three subsystems yield a total of eight possible states for the system. The relative lack of integration between brain components makes man a weak evolutionary contestant compared to machines. It is judged that machines should become dominant on earth within 100 years, probably by means of continuing development of existing man-machine systems. Advanced forms of extraterrestrial intelligence may exist but are too difficult to observe. The prospects for communication with extraterrestrial intelligence are reviewed.

Quantum Computation

NASA Astrophysics Data System (ADS)

Aharonov, Dorit

In the last few years, theoretical study of quantum systems serving as computational devices has achieved tremendous progress. We now have strong theoretical evidence that quantum computers, if built, might be used as a dramatically powerful computational tool, capable of performing tasks which seem intractable for classical computers. This review is about to tell the story of theoretical quantum computation. I l out the developing topic of experimental realizations of the model, and neglected other closely related topics which are quantum information and quantum communication. As a result of narrowing the scope of this paper, I hope it has gained the benefit of being an almost self contained introduction to the exciting field of quantum computation. The review begins with background on theoretical computer science, Turing machines and Boolean circuits. In light of these models, I define quantum computers, and discuss the issue of universal quantum gates. Quantum algorithms, including Shor's factorization algorithm and Grover's algorithm for searching databases, are explained. I will devote much attention to understanding what the origins of the quantum computational power are, and what the limits of this power are. Finally, I describe the recent theoretical results which show that quantum computers maintain their complexity power even in the presence of noise, inaccuracies and finite precision. This question cannot be separated from that of quantum complexity because any realistic model will inevitably be subjected to such inaccuracies. I tried to put all results in their context, asking what the implications to other issues in computer science and physics are. In the end of this review, I make these connections explicit by discussing the possible implications of quantum computation on fundamental physical questions such as the transition from quantum to classical physics.

Multitasking runtime systems for the Cedar Multiprocessor

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

Guzzi, M.D.

1986-07-01

The programming of a MIMD machine is more complex than for SISD and SIMD machines. The multiple computational resources of the machine must be made available to the programming language compiler and to the programmer so that multitasking programs may be written. This thesis will explore the additional complexity of programming a MIMD machine, the Cedar Multiprocessor specifically, and the multitasking runtime system necessary to provide multitasking resources to the user. First, the problem will be well defined: the Cedar machine, its operating system, the programming language, and multitasking concepts will be described. Second, a solution to the problem, calledmore » macrotasking, will be proposed. This solution provides multitasking facilities to the programmer at a very coarse level with many visible machine dependencies. Third, an alternate solution, called microtasking, will be proposed. This solution provides multitasking facilities of a much finer grain. This solution does not depend so rigidly on the specific architecture of the machine. Finally, the two solutions will be compared for effectiveness. 12 refs., 16 figs.« less

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.

Implementation and performance of parallel Prolog interpreter

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

Wei, S.; Kale, L.V.; Balkrishna, R.

1988-01-01

In this paper, the authors discuss the implementation of a parallel Prolog interpreter on different parallel machines. The implementation is based on the REDUCE--OR process model which exploits both AND and OR parallelism in logic programs. It is machine independent as it runs on top of the chare-kernel--a machine-independent parallel programming system. The authors also give the performance of the interpreter running a diverse set of benchmark pargrams on parallel machines including shared memory systems: an Alliant FX/8, Sequent and a MultiMax, and a non-shared memory systems: Intel iPSC/32 hypercube, in addition to its performance on a multiprocessor simulation system.

Automation and robotics technology for intelligent mining systems

NASA Technical Reports Server (NTRS)

Welsh, Jeffrey H.

1989-01-01

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

Machine-Aided Indexing at NASA.

ERIC Educational Resources Information Center

Silvester, June P.; And Others

1994-01-01

Describes the National Aeronautics and Space Administration (NASA) Lexical Dictionary (NLD), a machine-aided indexing system used online at the NASA Center for AeroSpace Information (CASI). The functions of NLD system components are described in detail, and production and quality benefits resulting from machine-aided indexing at CASI are…

A Senior Project-Based Multiphase Motor Drive System Development

ERIC Educational Resources Information Center

Abdel-Khalik, Ayman S.; Massoud, Ahmed M.; Ahmed, Shehab

2016-01-01

Adjustable-speed drives based on multiphase motors are of significant interest for safety-critical applications that necessitate wide fault-tolerant capabilities and high system reliability. Although multiphase machines are based on the same conceptual theory as three-phase machines, most undergraduate electrical machines and electric drives…

Motor proteins and molecular motors: how to operate machines at the nanoscale.

PubMed

Kolomeisky, Anatoly B

2013-11-20

Several classes of biological molecules that transform chemical energy into mechanical work are known as motor proteins or molecular motors. These nanometer-sized machines operate in noisy stochastic isothermal environments, strongly supporting fundamental cellular processes such as the transfer of genetic information, transport, organization and functioning. In the past two decades motor proteins have become a subject of intense research efforts, aimed at uncovering the fundamental principles and mechanisms of molecular motor dynamics. In this review, we critically discuss recent progress in experimental and theoretical studies on motor proteins. Our focus is on analyzing fundamental concepts and ideas that have been utilized to explain the non-equilibrium nature and mechanisms of molecular motors.

Design and optimize of 3-axis filament winding machine

NASA Astrophysics Data System (ADS)

Quanjin, Ma; Rejab, M. R. M.; Idris, M. S.; Bachtiar, B.; Siregar, J. P.; Harith, M. N.

2017-10-01

Filament winding technique is developed as the primary process for composite cylindrical structures fabrication at low cost. Fibres are wound on a rotating mandrel by a filament winding machine where resin impregnated fibres pass through a pay-out eye. This paper aims to develop and optimize a 3-axis, lightweight, practical, efficient, portable filament winding machine to satisfy the customer demand, which can fabricate pipes and round shape cylinders with resins. There are 3 main units on the 3-axis filament winding machine, which are the rotary unit, the delivery unit and control system unit. Comparison with previous existing filament winding machines in the factory, it has 3 degrees of freedom and can fabricate more complex shape specimens based on the mandrel shape and particular control system. The machine has been designed and fabricated on 3 axes movements with control system. The x-axis is for movement of the carriage, the y-axis is the rotation of mandrel and the z-axis is the movement of the pay-out eye. Cylindrical specimens with different dimensions and winding angles were produced. 3-axis automated filament winding machine has been successfully designed with simple control system.

2011 International Infantry and Joint Services Small Arms Systems Symposium, Exhibition and Firing Demonstration

DTIC Science & Technology

2011-05-26

Machine Gun 24 12.7mm NATO Nominated Weapon United States – General Dynamics M2 Heavy Barrel Machine Gun 25...Explosively-Clad Refractory Barrel Liners for Small Caliber Machine Guns , Dr. Douglas Taylor, TPL, Inc. 12299 - The HAMR Project, Mr. Xavier Gavage, FN Herstal... Barrel Liners for Small Caliber Machine Guns Dr. Douglas Taylor, TPL, Inc. 12330 - 40mm Low Velocity Air-Burst Munitions System Mr.

Preprocessor with spline interpolation for converting stereolithography into cutter location source data

NASA Astrophysics Data System (ADS)

Nagata, Fusaomi; Okada, Yudai; Sakamoto, Tatsuhiko; Kusano, Takamasa; Habib, Maki K.; Watanabe, Keigo

2017-06-01

The authors have developed earlier an industrial machining robotic system for foamed polystyrene materials. The developed robotic CAM system provided a simple and effective interface without the need to use any robot language between operators and the machining robot. In this paper, a preprocessor for generating Cutter Location Source data (CLS data) from Stereolithography (STL data) is first proposed for robotic machining. The preprocessor enables to control the machining robot directly using STL data without using any commercially provided CAM system. The STL deals with a triangular representation for a curved surface geometry. The preprocessor allows machining robots to be controlled through a zigzag or spiral path directly calculated from STL data. Then, a smart spline interpolation method is proposed and implemented for smoothing coarse CLS data. The effectiveness and potential of the developed approaches are demonstrated through experiments on actual machining and interpolation.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

A Machine Vision Quality Control System for Industrial Acrylic Fibre Production

NASA Astrophysics Data System (ADS)

Heleno, Paulo; Davies, Roger; Correia, Bento A. Brázio; Dinis, João

2002-12-01

This paper describes the implementation of INFIBRA, a machine vision system used in the quality control of acrylic fibre production. The system was developed by INETI under a contract with a leading industrial manufacturer of acrylic fibres. It monitors several parameters of the acrylic production process. This paper presents, after a brief overview of the system, a detailed description of the machine vision algorithms developed to perform the inspection tasks unique to this system. Some of the results of online operation are also presented.

Superconducting Coil Winding Machine Control System

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

Nogiec, J. M.; Kotelnikov, S.; Makulski, A.

The Spirex coil winding machine is used at Fermilab to build coils for superconducting magnets. Recently this ma-chine was equipped with a new control system, which al-lows operation from both a computer and a portable remote control unit. This control system is distributed between three layers, implemented on a PC, real-time target, and FPGA, providing respectively HMI, operational logic and direct controls. The system controls motion of all mechan-ical components and regulates the cable tension. Safety is ensured by a failsafe, redundant system.

Analytical model for force prediction when machining metal matrix composites

NASA Astrophysics Data System (ADS)

Sikder, Snahungshu

Metal Matrix Composites (MMC) offer several thermo-mechanical advantages over standard materials and alloys which make them better candidates in different applications. Their light weight, high stiffness, and strength have attracted several industries such as automotive, aerospace, and defence for their wide range of products. However, the wide spread application of Meal Matrix Composites is still a challenge for industry. The hard and abrasive nature of the reinforcement particles is responsible for rapid tool wear and high machining costs. Fracture and debonding of the abrasive reinforcement particles are the considerable damage modes that directly influence the tool performance. It is very important to find highly effective way to machine MMCs. So, it is important to predict forces when machining Metal Matrix Composites because this will help to choose perfect tools for machining and ultimately save both money and time. This research presents an analytical force model for predicting the forces generated during machining of Metal Matrix Composites. In estimating the generated forces, several aspects of cutting mechanics were considered including: shearing force, ploughing force, and particle fracture force. Chip formation force was obtained by classical orthogonal metal cutting mechanics and the Johnson-Cook Equation. The ploughing force was formulated while the fracture force was calculated from the slip line field theory and the Griffith theory of failure. The predicted results were compared with previously measured data. The results showed very good agreement between the theoretically predicted and experimentally measured cutting forces.

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

PubMed Central

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-01-01

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing. PMID:27854322

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

PubMed

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-11-16

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Reliability Evaluation and Improvement Approach of Chemical Production Man - Machine - Environment System

NASA Astrophysics Data System (ADS)

Miao, Yongchun; Kang, Rongxue; Chen, Xuefeng

2017-12-01

In recent years, with the gradual extension of reliability research, the study of production system reliability has become the hot topic in various industries. Man-machine-environment system is a complex system composed of human factors, machinery equipment and environment. The reliability of individual factor must be analyzed in order to gradually transit to the research of three-factor reliability. Meanwhile, the dynamic relationship among man-machine-environment should be considered to establish an effective blurry evaluation mechanism to truly and effectively analyze the reliability of such systems. In this paper, based on the system engineering, fuzzy theory, reliability theory, human error, environmental impact and machinery equipment failure theory, the reliabilities of human factor, machinery equipment and environment of some chemical production system were studied by the method of fuzzy evaluation. At last, the reliability of man-machine-environment system was calculated to obtain the weighted result, which indicated that the reliability value of this chemical production system was 86.29. Through the given evaluation domain it can be seen that the reliability of man-machine-environment integrated system is in a good status, and the effective measures for further improvement were proposed according to the fuzzy calculation results.

A Theoretical Model of EGM Problem Gambling: More than a Cognitive Escape

ERIC Educational Resources Information Center

Thomas, Anna Christina; Sullivan, Gavin Brent; Allen, Felicity Catherine Louise

2009-01-01

Although electronic gaming machine (EGM) gambling is established as a particularly risky form of gambling (Dowling, Smith and Thomas, "Addiction" 100:33-45, 2005), models of problem gambling continue to be generalist so factors and processes specific to EGM gambling can be overlooked. This study conducted semi-structured interviews with 13 EGM…

Circular sawing experiments on a radial arm saw

Treesearch

Charles W. McMillin; J.L. Lubxin

1959-01-01

Several years ago, the American Machine and Foundry Co. decided to conduct a comprehensive investigation in the field of cutting processes. The initial emphasis has been on circular sawing because of the product line of the company's DeWalt Division. As a nevessary antecedent to theoretical and experimental investigations, an extensive review of the literature on...

On Periodicity of Trigonometric Functions and Connections with Elementary Number Theoretic Ideas

ERIC Educational Resources Information Center

Stupel, Moshe

2012-01-01

The notion of periodicity stands for regular recurrence of phenomena in a particular order in nature or in the actions of man, machine, etc. Many examples can be given from daily life featuring periodicity. Mathematically the meaning of periodicity is that some value recurs with a constant frequency. Students learn about the periodicity of the…

Mechanical Design Handbook for Elastomers

NASA Technical Reports Server (NTRS)

Darlow, M.; Zorzi, E.

1986-01-01

Mechanical Design Handbook for Elastomers reviews state of art in elastomer-damper technology with particular emphasis on applications of highspeed rotor dampers. Self-contained reference but includes some theoretical discussion to help reader understand how and why dampers used for rotating machines. Handbook presents step-by-step procedure for design of elastomer dampers and detailed examples of actual elastomer damper applications.

Spin dynamics in storage rings and linear accelerators

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

Irwin, J.

1994-12-01

The purpose of these lectures is to survey the subject of spin dynamics in accelerators: to give a sense of the underlying physics, the typical analytic and numeric methods used, and an overview of results achieved. Consideration will be limited to electrons and protons. Examples of experimental and theoretical results in both linear and circular machines are included.

12 CFR 205.16 - Disclosures at automated teller machines.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 2 2011-01-01 2011-01-01 false Disclosures at automated teller machines. 205.16 Section 205.16 Banks and Banking FEDERAL RESERVE SYSTEM BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM ELECTRONIC FUND TRANSFERS (REGULATION E) § 205.16 Disclosures at automated teller machines. (a...

Purchasing a Computer System for the Small Construction Company,

DTIC Science & Technology

1983-06-08

October 1982. . . . . . . .. i. i...< ..- . ,. .-: i. i? ,. . .-- i * i . . . ., r77- 7 *,~ .- -- 36 IBM - International Business Machines...Corporation, "Small Systems Solutions: An Introduction to Business Computing," Pamphlet SC21-5205-0, Atlanta, Georgia, January 1979. International Business Machines...Corporation, "IBM System/34 Introduction," Pamphlet GC21-5153-5, File No. S34-00, Atlanta, Georgia, January 1979. International Business Machines

Annual Symposium on Machine Processing of Remotely Sensed Data, 4th, Purdue University, West Lafayette, Ind., June 21-23, 1977, Proceedings

NASA Technical Reports Server (NTRS)

Morrison, D. B. (Editor); Scherer, D. J.

1977-01-01

Papers are presented on a variety of techniques for the machine processing of remotely sensed data. Consideration is given to preprocessing methods such as the correction of Landsat data for the effects of haze, sun angle, and reflectance and to the maximum likelihood estimation of signature transformation algorithm. Several applications of machine processing to agriculture are identified. Various types of processing systems are discussed such as ground-data processing/support systems for sensor systems and the transfer of remotely sensed data to operational systems. The application of machine processing to hydrology, geology, and land-use mapping is outlined. Data analysis is considered with reference to several types of classification methods and systems.

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

Proceedings of the NASA Conference on Space Telerobotics, volume 3

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor); Seraji, Homayoun (Editor)

1989-01-01

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research.

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

PubMed

Punsawad, Yunyong; Wongsawat, Yodchanan; Parnichkun, Manukid

2010-01-01

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

Ada (Trade Name) Compiler Validation Summary Report: International Business Machines Corporation. IBM Development System for the Ada Language System, Version 1.1.0, IBM 4381 under VM/SP CMS Host, IBM 4381 under MVS Target

DTIC Science & Technology

1988-05-20

AVF Control Number: AVF-VSR-84.1087 ’S (0 87-03-10-TEL I- Ada® COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM...System, Version 1.1.0, International Business Machines Corporation, Wright-Patterson AFB. IBM 4381 under VM/SP CMS, Release 3.6 (host) and IBM 4381...an IBM 4381 operating under MVS, Release 3.8. On-site testing was performed 18 May 1987 through 20 May 1987 at International Business Machines

Ada Compiler Validation Summary Report: Certificate Number: 880318W1. 09041, International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM 4381 under VM/HPO, Host and Target

DTIC Science & Technology

1988-03-28

International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under VM/HPO, host and target DTIC...necessary and identify by block number) International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM...in the compiler listed in this declaration. I declare that International Business Machines Corporation is the owner of record of the object code of the

Ada Compiler Validation Summary Report: Certificate Number 89020W1. 10073: International Business Machines Corporation, IBM Development System for the Ada Language, VM/CMS Ada Compiler, Version 2.1.1, IBM 3083 (Host and Target)

DTIC Science & Technology

1989-04-20

International Business Machines Corporation) IBM Development System for the Ada Language, VN11/CMS Ada Compiler, Version 2.1.1, Wright-Patterson AFB, IBM 3083...890420W1.10073 International Business Machines Corporation IBM Development System for the Ada Language VM/CMS Ada Compiler Version 2.1.1 IBM 3083... International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all default option settings except for the

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10075 International Business Machines Corporation. IBM Development System, for the Ada Language CMS/MVS Ada Cross Compiler, Version 2.1.1 IBM 3083 Host and IBM 4381 Target

DTIC Science & Technology

1989-04-20

International business Machines Corporati,:i IBM Development System for the Ada Language, CMS/MVS Ada Cross Compiler, Version 2.1.1, Wright-Patterson AFB, IBM...VALIDATION SUMMARY REPORT: Certificate Number: 890420W1.10075 International Business Machines Corporation IBM Development System for the Ada Language CMS...command scripts provided by International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all default

Lunar regolith bagging system

NASA Technical Reports Server (NTRS)

Cannon, Reuben; Henninger, Scott; Levandoski, Mark; Perkins, Jim; Pitchon, Jack; Swats, Robin; Wessels, Roger

1990-01-01

A design of a lunar regolith bag and bagging system is described. The bags of regolith are to be used for construction applications on the lunar surface. The machine is designed to be used in conjunction with the lunar SKITTER currently under development. The bags for this system are 1 cu ft volume and are made from a fiberglass composite weave. The machinery is constructed mostly from a boron/aluminum composite. The machine can fill 120 bags per hour and work for 8 hours a day. The man hours to machine hours ratio to operate the machine is .5/8.

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

NASA Technical Reports Server (NTRS)

Bose, Bimal K.; Kim, Min-Huei

1995-01-01

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

Task-focused modeling in automated agriculture

NASA Astrophysics Data System (ADS)

Vriesenga, Mark R.; Peleg, K.; Sklansky, Jack

1993-01-01

Machine vision systems analyze image data to carry out automation tasks. Our interest is in machine vision systems that rely on models to achieve their designed task. When the model is interrogated from an a priori menu of questions, the model need not be complete. Instead, the machine vision system can use a partial model that contains a large amount of information in regions of interest and less information elsewhere. We propose an adaptive modeling scheme for machine vision, called task-focused modeling, which constructs a model having just sufficient detail to carry out the specified task. The model is detailed in regions of interest to the task and is less detailed elsewhere. This focusing effect saves time and reduces the computational effort expended by the machine vision system. We illustrate task-focused modeling by an example involving real-time micropropagation of plants in automated agriculture.

Methods And Systms For Analyzing The Degradation And Failure Of Mechanical Systems

DOEpatents

Jarrell, Donald B.; Sisk, Daniel R.; Hatley, Darrel D.; Kirihara, Leslie J.; Peters, Timothy J.

2005-02-08

Methods and systems for identifying, understanding, and predicting the degradation and failure of mechanical systems are disclosed. The methods include measuring and quantifying stressors that are responsible for the activation of degradation mechanisms in the machine component of interest. The intensity of the stressor may be correlated with the rate of physical degradation according to some determinable function such that a derivative relationship exists between the machine performance, degradation, and the underlying stressor. The derivative relationship may be used to make diagnostic and prognostic calculations concerning the performance and projected life of the machine. These calculations may be performed in real time to allow the machine operator to quickly adjust the operational parameters of the machinery in order to help minimize or eliminate the effects of the degradation mechanism, thereby prolonging the life of the machine. Various systems implementing the methods are also disclosed.

Method and system for controlling a synchronous machine over full operating range

DOEpatents

Walters, James E.; Gunawan, Fani S.; Xue, Yanhong

2002-01-01

System and method for controlling a synchronous machine are provided. The method allows for calculating a stator voltage index. The method further allows for relating the magnitude of the stator voltage index against a threshold voltage value. An offset signal is generated based on the results of the relating step. A respective state of operation of the machine is determined. The offset signal is processed based on the respective state of the machine.

Pain Intensity Recognition Rates via Biopotential Feature Patterns with Support Vector Machines

PubMed Central

Gruss, Sascha; Treister, Roi; Werner, Philipp; Traue, Harald C.; Crawcour, Stephen; Andrade, Adriano; Walter, Steffen

2015-01-01

Background The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient’s report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (NRS) count among the most common tools, which are restricted to patients with normal mental abilities. There also exist instruments for pain assessment in people with verbal and / or cognitive impairments and instruments for pain assessment in people who are sedated and automated ventilated. However, all these diagnostic methods either have limited reliability and validity or are very time-consuming. In contrast, biopotentials can be automatically analyzed with machine learning algorithms to provide a surrogate measure of pain intensity. Methods In this context, we created a database of biopotentials to advance an automated pain recognition system, determine its theoretical testing quality, and optimize its performance. Eighty-five participants were subjected to painful heat stimuli (baseline, pain threshold, two intermediate thresholds, and pain tolerance threshold) under controlled conditions and the signals of electromyography, skin conductance level, and electrocardiography were collected. A total of 159 features were extracted from the mathematical groupings of amplitude, frequency, stationarity, entropy, linearity, variability, and similarity. Results We achieved classification rates of 90.94% for baseline vs. pain tolerance threshold and 79.29% for baseline vs. pain threshold. The most selected pain features stemmed from the amplitude and similarity group and were derived from facial electromyography. Conclusion The machine learning measurement of pain in patients could provide valuable information for a clinical team and thus support the treatment assessment. PMID:26474183

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

Adapting the Euler-Lagrange equation to study one-dimensional motions under the action of a constant force

NASA Astrophysics Data System (ADS)

Dias, Clenilda F.; Araújo, Maria A. S.; Carvalho-Santos, Vagson L.

2018-01-01

The Euler-Lagrange equations (ELE) are very important in the theoretical description of several physical systems. In this work we have used a simplified form of ELE to study one-dimensional motions under the action of a constant force. From the use of the definition of partial derivative, we have proposed two operators, here called mean delta operators, which may be used to solve the ELE in a simplest way. We have applied this simplification to solve three simple mechanical problems in which the particle is under the action of the gravitational field: a free fall body, the Atwood’s machine and the inclined plan. The proposed simplification can be used to introduce the lagrangian formalism in teaching classical mechanics in introductory physics courses.

Error analysis of stochastic gradient descent ranking.

PubMed

Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

2013-06-01

Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

A self-defining hierarchical data system

NASA Technical Reports Server (NTRS)

Bailey, J.

1992-01-01

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

Space Station man-machine automation trade-off analysis

NASA Technical Reports Server (NTRS)

Zimmerman, W. F.; Bard, J.; Feinberg, A.

1985-01-01

The man machine automation tradeoff methodology presented is of four research tasks comprising the autonomous spacecraft system technology (ASST) project. ASST was established to identify and study system level design problems for autonomous spacecraft. Using the Space Station as an example spacecraft system requiring a certain level of autonomous control, a system level, man machine automation tradeoff methodology is presented that: (1) optimizes man machine mixes for different ground and on orbit crew functions subject to cost, safety, weight, power, and reliability constraints, and (2) plots the best incorporation plan for new, emerging technologies by weighing cost, relative availability, reliability, safety, importance to out year missions, and ease of retrofit. A fairly straightforward approach is taken by the methodology to valuing human productivity, it is still sensitive to the important subtleties associated with designing a well integrated, man machine system. These subtleties include considerations such as crew preference to retain certain spacecraft control functions; or valuing human integration/decision capabilities over equivalent hardware/software where appropriate.

Open architecture CNC system

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

Tal, J.; Lopez, A.; Edwards, J.M.

1995-04-01

In this paper, an alternative solution to the traditional CNC machine tool controller has been introduced. Software and hardware modules have been described and their incorporation in a CNC control system has been outlined. This type of CNC machine tool controller demonstrates that technology is accessible and can be readily implemented into an open architecture machine tool controller. Benefit to the user is greater controller flexibility, while being economically achievable. PC based, motion as well as non-motion features will provide flexibility through a Windows environment. Up-grading this type of controller system through software revisions will keep the machine tool inmore » a competitive state with minimal effort. Software and hardware modules are mass produced permitting competitive procurement and incorporation. Open architecture CNC systems provide diagnostics thus enhancing maintainability, and machine tool up-time. A major concern of traditional CNC systems has been operator training time. Training time can be greatly minimized by making use of Windows environment features.« less

Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

PubMed

Nouretdinov, Ilia; Costafreda, Sergi G; Gammerman, Alexander; Chervonenkis, Alexey; Vovk, Vladimir; Vapnik, Vladimir; Fu, Cynthia H Y

2011-05-15

There is rapidly accumulating evidence that the application of machine learning classification to neuroimaging measurements may be valuable for the development of diagnostic and prognostic prediction tools in psychiatry. However, current methods do not produce a measure of the reliability of the predictions. Knowing the risk of the error associated with a given prediction is essential for the development of neuroimaging-based clinical tools. We propose a general probabilistic classification method to produce measures of confidence for magnetic resonance imaging (MRI) data. We describe the application of transductive conformal predictor (TCP) to MRI images. TCP generates the most likely prediction and a valid measure of confidence, as well as the set of all possible predictions for a given confidence level. We present the theoretical motivation for TCP, and we have applied TCP to structural and functional MRI data in patients and healthy controls to investigate diagnostic and prognostic prediction in depression. We verify that TCP predictions are as accurate as those obtained with more standard machine learning methods, such as support vector machine, while providing the additional benefit of a valid measure of confidence for each prediction. Copyright © 2010 Elsevier Inc. All rights reserved.

An open CAM system for dentistry on the basis of China-made 5-axis simultaneous contouring CNC machine tool and industrial CAM software.

PubMed

Lu, Li; Liu, Shusheng; Shi, Shenggen; Yang, Jianzhong

2011-10-01

China-made 5-axis simultaneous contouring CNC machine tool and domestically developed industrial computer-aided manufacture (CAM) technology were used for full crown fabrication and measurement of crown accuracy, with an attempt to establish an open CAM system for dental processing and to promote the introduction of domestic dental computer-aided design (CAD)/CAM system. Commercially available scanning equipment was used to make a basic digital tooth model after preparation of crown, and CAD software that comes with the scanning device was employed to design the crown by using domestic industrial CAM software to process the crown data in order to generate a solid model for machining purpose, and then China-made 5-axis simultaneous contouring CNC machine tool was used to complete machining of the whole crown and the internal accuracy of the crown internal was measured by using 3D-MicroCT. The results showed that China-made 5-axis simultaneous contouring CNC machine tool in combination with domestic industrial CAM technology can be used for crown making and the crown was well positioned in die. The internal accuracy was successfully measured by using 3D-MicroCT. It is concluded that an open CAM system for dentistry on the basis of China-made 5-axis simultaneous contouring CNC machine tool and domestic industrial CAM software has been established, and development of the system will promote the introduction of domestically-produced dental CAD/CAM system.

Human Machine Learning Symbiosis

ERIC Educational Resources Information Center

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

2017-01-01

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

Study of Man-Machine Communications Systems for Disabled Persons (The Handicapped). Volume IV. Final Report.

ERIC Educational Resources Information Center

Kafafian, Haig

The volume contains experimental instructional materials designed for teacher and handicapped student use with two man-machine communications systems, Cybertype and Cyber-Go-Round, developed as educational aids for the severely handicapped. Cybertype is a writing machine with various possible configurations of portable keyboards with a reduced…

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)

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

40 CFR 63.322 - Standards.

Code of Federal Regulations, 2013 CFR

2013-07-01

... at each opening at all times that the machine is operating. (b) The owner or operator of each new dry... articles to or from the machine, and shall keep the door closed at all other times. (d) The owner or... existing dry cleaning system and of each new transfer machine system and its ancillary equipment installed...

40 CFR 63.322 - Standards.

Code of Federal Regulations, 2012 CFR

2012-07-01

... at each opening at all times that the machine is operating. (b) The owner or operator of each new dry... articles to or from the machine, and shall keep the door closed at all other times. (d) The owner or... existing dry cleaning system and of each new transfer machine system and its ancillary equipment installed...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

30 CFR 75.209 - Automated Temporary Roof Support (ATRS) systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... paragraphs (b) and (c) of this section, an ATRS system shall be used with roof bolting machines and continuous-mining machines with integral roof bolters operated in a working section. The requirements of this paragraph shall be met according to the following schedule: (1) All new machines ordered after March 28...

Bypassing the Kohn-Sham equations with machine learning.

PubMed

Brockherde, Felix; Vogt, Leslie; Li, Li; Tuckerman, Mark E; Burke, Kieron; Müller, Klaus-Robert

2017-10-11

Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields. Machine learning holds the promise of learning the energy functional via examples, bypassing the need to solve the Kohn-Sham equations. This should yield substantial savings in computer time, allowing larger systems and/or longer time-scales to be tackled, but attempts to machine-learn this functional have been limited by the need to find its derivative. The present work overcomes this difficulty by directly learning the density-potential and energy-density maps for test systems and various molecules. We perform the first molecular dynamics simulation with a machine-learned density functional on malonaldehyde and are able to capture the intramolecular proton transfer process. Learning density models now allows the construction of accurate density functionals for realistic molecular systems.Machine learning allows electronic structure calculations to access larger system sizes and, in dynamical simulations, longer time scales. Here, the authors perform such a simulation using a machine-learned density functional that avoids direct solution of the Kohn-Sham equations.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.

PubMed

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-10-20

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

PubMed Central

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-01-01

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. PMID:27775625

Development and validation of a machine learning algorithm and hybrid system to predict the need for life-saving interventions in trauma patients.

PubMed

Liu, Nehemiah T; Holcomb, John B; Wade, Charles E; Batchinsky, Andriy I; Cancio, Leopoldo C; Darrah, Mark I; Salinas, José

2014-02-01

Accurate and effective diagnosis of actual injury severity can be problematic in trauma patients. Inherent physiologic compensatory mechanisms may prevent accurate diagnosis and mask true severity in many circumstances. The objective of this project was the development and validation of a multiparameter machine learning algorithm and system capable of predicting the need for life-saving interventions (LSIs) in trauma patients. Statistics based on means, slopes, and maxima of various vital sign measurements corresponding to 79 trauma patient records generated over 110,000 feature sets, which were used to develop, train, and implement the system. Comparisons among several machine learning models proved that a multilayer perceptron would best implement the algorithm in a hybrid system consisting of a machine learning component and basic detection rules. Additionally, 295,994 feature sets from 82 h of trauma patient data showed that the system can obtain 89.8 % accuracy within 5 min of recorded LSIs. Use of machine learning technologies combined with basic detection rules provides a potential approach for accurately assessing the need for LSIs in trauma patients. The performance of this system demonstrates that machine learning technology can be implemented in a real-time fashion and potentially used in a critical care environment.

Optimizing the way kinematical feed chains with great distance between slides are chosen for CNC machine tools

NASA Astrophysics Data System (ADS)

Lucian, P.; Gheorghe, S.

2017-08-01

This paper presents a new method, based on FRISCO formula, for optimizing the choice of the best control system for kinematical feed chains with great distance between slides used in computer numerical controlled machine tools. Such machines are usually, but not limited to, used for machining large and complex parts (mostly in the aviation industry) or complex casting molds. For such machine tools the kinematic feed chains are arranged in a dual-parallel drive structure that allows the mobile element to be moved by the two kinematical branches and their related control systems. Such an arrangement allows for high speed and high rigidity (a critical requirement for precision machining) during the machining process. A significant issue for such an arrangement it’s the ability of the two parallel control systems to follow the same trajectory accurately in order to address this issue it is necessary to achieve synchronous motion control for the two kinematical branches ensuring that the correct perpendicular position it’s kept by the mobile element during its motion on the two slides.

Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

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

Liu, Zheng; Ukida, H.; Niel, Kurt

Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a bettermore » performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.« less

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.

Towards a first implementation of the WLIMES approach in living system studies advancing the diagnostics and therapy in augmented personalized medicine.

PubMed

Simeonov, Plamen L

2017-12-01

The goal of this paper is to advance an extensible theory of living systems using an approach to biomathematics and biocomputation that suitably addresses self-organized, self-referential and anticipatory systems with multi-temporal multi-agents. Our first step is to provide foundations for modelling of emergent and evolving dynamic multi-level organic complexes and their sustentative processes in artificial and natural life systems. Main applications are in life sciences, medicine, ecology and astrobiology, as well as robotics, industrial automation, man-machine interface and creative design. Since 2011 over 100 scientists from a number of disciplines have been exploring a substantial set of theoretical frameworks for a comprehensive theory of life known as Integral Biomathics. That effort identified the need for a robust core model of organisms as dynamic wholes, using advanced and adequately computable mathematics. The work described here for that core combines the advantages of a situation and context aware multivalent computational logic for active self-organizing networks, Wandering Logic Intelligence (WLI), and a multi-scale dynamic category theory, Memory Evolutive Systems (MES), hence WLIMES. This is presented to the modeller via a formal augmented reality language as a first step towards practical modelling and simulation of multi-level living systems. Initial work focuses on the design and implementation of this visual language and calculus (VLC) and its graphical user interface. The results will be integrated within the current methodology and practices of theoretical biology and (personalized) medicine to deepen and to enhance the holistic understanding of life. Copyright © 2017 Elsevier B.V. All rights reserved.

State Machine Modeling of the Space Launch System Solid Rocket Boosters

NASA Technical Reports Server (NTRS)

Harris, Joshua A.; Patterson-Hine, Ann

2013-01-01

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

Automated fiber pigtailing machine

DOEpatents

Strand, Oliver T.; Lowry, Mark E.

1999-01-01

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectonic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems.

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.

The ultrastructural characteristics of porcine hepatocytes donated after cardiac death and preserved with warm machine perfusion preservation.

PubMed

Bochimoto, Hiroki; Matsuno, Naoto; Ishihara, Yo; Shonaka, Tatsuya; Koga, Daisuke; Hira, Yoshiki; Nishikawa, Yuji; Furukawa, Hiroyuki; Watanabe, Tsuyoshi

2017-01-01

The effects of warm machine perfusion preservation of liver grafts donated after cardiac death on the intracellular three-dimensional ultrastructure of the organelles in hepatocytes remain unclear. Here we analyzed comparatively the ultrastructure of the endomembrane systems in porcine hepatocytes under warm ischemia and successive hypothermic and midthermic machine perfusion preservation, a type of the warm machine perfusion. Porcine liver grafts which had a warm ischemia time of 60 minutes were perfused for 4 hours with modified University of Wisconsin gluconate solution. Group A grafts were preserved with hypothermic machine perfusion preservation at 8°C constantly for 4 hours. Group B grafts were preserved with rewarming up to 22°C by warm machine perfusion preservation for 4 hours. An analysis of hepatocytes after 60 minutes of warm ischemia by scanning electron microscope revealed the appearance of abnormal vacuoles and invagination of mitochondria. In the hepatocytes preserved by subsequent hypothermic machine perfusion preservation, strongly swollen mitochondria were observed. In contrast, the warm machine perfusion preservation could preserve the functional appearance of mitochondria in hepatocytes. Furthermore, abundant vacuoles and membranous structures sequestrating cellular organelles like autophagic vacuoles were frequently observed in hepatocytes after warm machine perfusion preservation. In conclusion, the ultrastructure of the endomembrane systems in the hepatocytes of liver grafts changed in accordance with the temperature conditions of machine perfusion preservation. In addition, temperature condition of the machine perfusion preservation may also affect the condition of the hepatic graft attributed to autophagy systems, and consequently alleviate the damage of the hepatocytes.

Electric machine for hybrid motor vehicle

DOEpatents

Hsu, John Sheungchun

2007-09-18

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

Optical design of laser transmission system

NASA Astrophysics Data System (ADS)

Zhang, Yulan; Feng, Jinliang; Li, Yongliang; Yang, Jiandong

1998-08-01

This paper discusses a design of optical transfer system used in carbon-dioxide laser therapeutic machine. The design of this system is according to the requirement of the therapeutic machine. The therapeutic machine requires the movement of laser transfer system is similar to the movement of human beings arms, which possesses 7 rotating hinges. We use optical hinges, which is composed of 45 degree mirrors. Because the carbon-dioxide laser mode is not good, light beam diameter at focus and divergence angle dissemination are big, we use a collecting lens at the transfer system output part in order to make the light beam diameter at focus in 0.2 to approximately 0.3 mm. For whole system the focus off-axis error is less than 0.5 mm, the transfer power consumption is smaller than 10%. The system can move in three dimension space freely and satisfies the therapeutic machine requirement.

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

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

Machine vision system for inspecting characteristics of hybrid rice seed

NASA Astrophysics Data System (ADS)

Cheng, Fang; Ying, Yibin

2004-03-01

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

A Structural Perspective on the Dynamics of Kinesin Motors

PubMed Central

Hyeon, Changbong; Onuchic, José N.

2011-01-01

Despite significant fluctuation under thermal noise, biological machines in cells perform their tasks with exquisite precision. Using molecular simulation of a coarse-grained model and theoretical arguments, we envisaged how kinesin, a prototype of biological machines, generates force and regulates its dynamics to sustain persistent motor action. A structure-based model, which can be versatile in adapting its structure to external stresses while maintaining its native fold, was employed to account for several features of kinesin dynamics along the biochemical cycle. This analysis complements our current understandings of kinesin dynamics and connections to experiments. We propose a thermodynamic cycle for kinesin that emphasizes the mechanical and regulatory role of the neck linker and clarify issues related to the motor directionality, and the difference between the external stalling force and the internal tension responsible for the head-head coordination. The comparison between the thermodynamic cycle of kinesin and macroscopic heat engines highlights the importance of structural change as the source of work production in biomolecular machines. PMID:22261064

Feasibility study of solid surface subreflector production techniques

NASA Technical Reports Server (NTRS)

1982-01-01

The principal effort was to study technical feasibility and cost aspects of the production technique of spin forming a subreflector reflective surface to a desired surface of revolution, back the surface with fiberglass to stabilize it sufficiently so that it may be machined to the target surface tolerance of .008 inches Root Mean Square (RMS) with a goal of .003 inches RMS. To verify this production technique, analyses was performed to define the production procedure. A price estimate for a 150 inch diameter subreflector for a 34 meter cassegrain antenna. During this feasibility study, numerous production processes were evaluated theoretically as production approaches for single surface, non-welded subreflectors. The first successful was the principal process of spin forming the reflective surface, backing with fiberglass and machining to a final contour. The second successful process was spin forming or bump forming a thicker reflective surface, with an integral (welded in) structure as a backing and machining the mounting pads and reflector to a final configuration.

Induced sadness increases persistence in a simulated slot machine task among recreational gamblers.

PubMed

Devos, Gaëtan; Clark, Luke; Maurage, Pierre; Billieux, Joël

2018-05-01

Gambling may constitute a strategy for coping with depressive mood, but a direct influence of depressive mood on gambling behaviors has never been tested via realistic experimental designs in gamblers. The current study tested whether experimentally induced sadness increases persistence on a simulated slot machine task using real monetary reinforcement in recreational gamblers. Sixty participants were randomly assigned to an experimental (sadness induction) or control (no emotional induction) condition, and then performed a slot machine task consisting of a mandatory phase followed by a persistence phase. Potential confounding variables (problem gambling symptoms, impulsivity traits, gambling cognitions) were measured to ensure that the experimental and control groups were comparable. The study showed that participants in the sadness condition displayed greater gambling persistence than control participants (p = .011). These data support the causal role of negative affect in decisions to gamble and persistence, which bears important theoretical and clinical implications. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Recent study of beam stability in the PSR

NASA Astrophysics Data System (ADS)

Wang, T. S. F.; Cooper, R.; Fitzgerald, D.; Frankle, S.; Hardek, T.; Hutson, R.; Macek, R.; Ohmori, C.; Plum, M.; Thiessen, H.

1993-05-01

A fast transverse instability with beam loss has been observed in the 800 MeV Los Alamos Pro Ring (PSR) when the injected beam intensity reaches 2 - 4(10)(exp 13) protons per pulse. Previous observations indicate that the instability is most likely driven by electrons trapped within the proton beam. Theoretical study shown that beam leakage into the inter-bunch gap leads to electron trapping. Recent experiments were carried out by using the newly implemented 'pinger' and by varying the machine transition gamma to explore further the 'e-p' instability and the nature of the instability. This paper summarizes some of these recent experimental results and theoretical studies.

Transferability of glass lens molding

NASA Astrophysics Data System (ADS)

Katsuki, Masahide

2006-02-01

Sphere lenses have been used for long time. But it is well known that sphere lenses theoretically have spherical aberration, coma and so on. And, aspheric lenses attract attention recently. Plastic lenses are molded easily with injection machines, and are relatively low cost. They are suitable for mass production. On the other hand, glass lenses have several excellent features such as high refractive index, heat resistance and so on. Many aspheric glass lenses came to be used for the latest digital camera and mobile phone camera module. It is very difficult to produce aspheric glass lenses by conventional process of curve generating and polishing. For the solution of this problem, Glass Molding Machine was developed and is spreading through the market. High precision mold is necessary to mold glass lenses with Glass Molding Machine. The mold core is ground or turned by high precision NC aspheric generator. To obtain higher transferability of the mold core, the function of the molding machine and the conditions of molding are very important. But because of high molding temperature, there are factors of thermal expansion and contraction of the mold and glass material. And it is hard to avoid the factors. In this session, I introduce following items. [1] Technology of glass molding and the machine is introduced. [2] The transferability of glass molding is analyzed with some data of glass lenses molded. [3] Compensation of molding shape error is discussed with examples.

In-process fault detection for textile fabric production: onloom imaging

NASA Astrophysics Data System (ADS)

Neumann, Florian; Holtermann, Timm; Schneider, Dorian; Kulczycki, Ashley; Gries, Thomas; Aach, Til

2011-05-01

Constant and traceable high fabric quality is of high importance both for technical and for high-quality conventional fabrics. Usually, quality inspection is carried out by trained personal, whose detection rate and maximum period of concentration are limited. Low resolution automated fabric inspection machines using texture analysis were developed. Since 2003, systems for the in-process inspection on weaving machines ("onloom") are commercially available. With these defects can be detected, but not measured quantitative precisely. Most systems are also prone to inevitable machine vibrations. Feedback loops for fault prevention are not established. Technology has evolved since 2003: Camera and computer prices dropped, resolutions were enhanced, recording speeds increased. These are the preconditions for real-time processing of high-resolution images. So far, these new technological achievements are not used in textile fabric production. For efficient use, a measurement system must be integrated into the weaving process; new algorithms for defect detection and measurement must be developed. The goal of the joint project is the development of a modern machine vision system for nondestructive onloom fabric inspection. The system consists of a vibration-resistant machine integration, a high-resolution machine vision system, and new, reliable, and robust algorithms with quality database for defect documentation. The system is meant to detect, measure, and classify at least 80 % of economically relevant defects. Concepts for feedback loops into the weaving process will be pointed out.

Managing virtual machines with Vac and Vcycle

NASA Astrophysics Data System (ADS)

McNab, A.; Love, P.; MacMahon, E.

2015-12-01

We compare the Vac and Vcycle virtual machine lifecycle managers and our experiences in providing production job execution services for ATLAS, CMS, LHCb, and the GridPP VO at sites in the UK, France and at CERN. In both the Vac and Vcycle systems, the virtual machines are created outside of the experiment's job submission and pilot framework. In the case of Vac, a daemon runs on each physical host which manages a pool of virtual machines on that host, and a peer-to-peer UDP protocol is used to achieve the desired target shares between experiments across the site. In the case of Vcycle, a daemon manages a pool of virtual machines on an Infrastructure-as-a-Service cloud system such as OpenStack, and has within itself enough information to create the types of virtual machines to achieve the desired target shares. Both systems allow unused shares for one experiment to temporarily taken up by other experiements with work to be done. The virtual machine lifecycle is managed with a minimum of information, gathered from the virtual machine creation mechanism (such as libvirt or OpenStack) and using the proposed Machine/Job Features API from WLCG. We demonstrate that the same virtual machine designs can be used to run production jobs on Vac and Vcycle/OpenStack sites for ATLAS, CMS, LHCb, and GridPP, and that these technologies allow sites to be operated in a reliable and robust way.

A comparative analysis of dynamic grids vs. virtual grids using the A3pviGrid framework.

PubMed

Shankaranarayanan, Avinas; Amaldas, Christine

2010-11-01

With the proliferation of Quad/Multi-core micro-processors in mainstream platforms such as desktops and workstations; a large number of unused CPU cycles can be utilized for running virtual machines (VMs) as dynamic nodes in distributed environments. Grid services and its service oriented business broker now termed cloud computing could deploy image based virtualization platforms enabling agent based resource management and dynamic fault management. In this paper we present an efficient way of utilizing heterogeneous virtual machines on idle desktops as an environment for consumption of high performance grid services. Spurious and exponential increases in the size of the datasets are constant concerns in medical and pharmaceutical industries due to the constant discovery and publication of large sequence databases. Traditional algorithms are not modeled at handing large data sizes under sudden and dynamic changes in the execution environment as previously discussed. This research was undertaken to compare our previous results with running the same test dataset with that of a virtual Grid platform using virtual machines (Virtualization). The implemented architecture, A3pviGrid utilizes game theoretic optimization and agent based team formation (Coalition) algorithms to improve upon scalability with respect to team formation. Due to the dynamic nature of distributed systems (as discussed in our previous work) all interactions were made local within a team transparently. This paper is a proof of concept of an experimental mini-Grid test-bed compared to running the platform on local virtual machines on a local test cluster. This was done to give every agent its own execution platform enabling anonymity and better control of the dynamic environmental parameters. We also analyze performance and scalability of Blast in a multiple virtual node setup and present our findings. This paper is an extension of our previous research on improving the BLAST application framework using dynamic Grids on virtualization platforms such as the virtual box.

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

PubMed

Varshney, Kush R; Alemzadeh, Homa

2017-09-01

Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.

An intelligent CNC machine control system architecture

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

Miller, D.J.; Loucks, C.S.

1996-10-01

Intelligent, agile manufacturing relies on automated programming of digitally controlled processes. Currently, processes such as Computer Numerically Controlled (CNC) machining are difficult to automate because of highly restrictive controllers and poor software environments. It is also difficult to utilize sensors and process models for adaptive control, or to integrate machining processes with other tasks within a factory floor setting. As part of a Laboratory Directed Research and Development (LDRD) program, a CNC machine control system architecture based on object-oriented design and graphical programming has been developed to address some of these problems and to demonstrate automated agile machining applications usingmore » platform-independent software.« less

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

Ada Compiler Validation Summary Report. Certificate Number: 891129W1. 10198 International Business Machines Corporation, the IBM Development System for the Ada Language AIX/RT Follow-on, Version 1.1 IBM RT Follow-on. Completion of On-Site Testing: 29 November 1989

DTIC Science & Technology

1989-11-29

nvmbe’j International Business Machines Corporation Wright-Patterson AFB, The IBM Development System for the Ada Language AIX/RT follow-on, Version 1.1...Certificate Number: 891129W1.10198 International Business Machines Corporation The IBM Development System for the Ada Language AIX/RT Follow-on, Version 1.1 IBM...scripts provided by International Business Machines Corporation and reviewed by the validation team. The compiler was tested using all the following

Industrial machine systems risk assessment: a critical review of concepts and methods.

PubMed

Etherton, John R

2007-02-01

Reducing the risk of work-related death and injury to machine operators and maintenance personnel poses a continuing occupational safety challenge. The risk of injury from machinery in U.S. workplaces is high. Between 1992 and 2001, there were, on average, 520 fatalities per year involving machines and, on average, 3.8 cases per 10,000 workers of nonfatal caught-in-running-machine injuries involving lost workdays. A U.S. task group recently developed a technical reference guideline, ANSI B11 TR3, "A Guide to Estimate, Evaluate, & Reduce Risks Associated with Machine Tools," that is intended to bring machine tool risk assessment practice in the United States up to or above the level now required by the international standard, ISO 14121. The ANSI guideline emphasizes identifying tasks and hazards not previously considered, particularly those associated with maintenance; and it further emphasizes teamwork among line workers, engineers, and safety professionals. The value of this critical review of concepts and methods resides in (1) its linking current risk theory to machine system risk assessment and (2) its exploration of how various risk estimation tools translate into risk-informed decisions on industrial machine system design and use. The review was undertaken to set the stage for a field evaluation study on machine risk assessment among users of the ANSI B11 TR3 method.

Conversion of Mass Storage Hierarchy in an IBM Computer Network

DTIC Science & Technology

1989-03-01

storage devices GUIDE IBM users’ group for DOS operating systems IBM International Business Machines IBM 370/145 CPU introduced in 1970 IBM 370/168 CPU...February 12, 1985, Information Systems Group, International Business Machines Corporation. "IBM 3090 Processor Complex" and 񓼪 Mass Storage System...34 Mainframe Journal, pp. 15-26, 64-65, Dallas, Texas, September-October 1987. 3. International Business Machines Corporation, Introduction to IBM 3S80 Storage

Study on the adjustment capability of the excitation system located inside superconducting machine electromagnetic shield

NASA Astrophysics Data System (ADS)

Xia, D.; Xia, Z.

2017-12-01

The ability for the excitation system to adjust quickly plays a very important role in maintaining the normal operation of superconducting machines and power systems. However, the eddy currents in the electromagnetic shield of superconducting machines hinder the exciting magnetic field change and weaken the adjustment capability of the excitation system. To analyze this problem, a finite element calculation model for the transient electromagnetic field with moving parts is established. The effects of three different electromagnetic shields on the exciting magnetic field are analyzed using finite element method. The results show that the electromagnetic shield hinders the field changes significantly, the better its conductivity, the greater the effect on the superconducting machine excitation.

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

NASA Astrophysics Data System (ADS)

Koptev, V. Yu

2017-02-01

The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

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.

Parameterizing Phrase Based Statistical Machine Translation Models: An Analytic Study

ERIC Educational Resources Information Center

Cer, Daniel

2011-01-01

The goal of this dissertation is to determine the best way to train a statistical machine translation system. I first develop a state-of-the-art machine translation system called Phrasal and then use it to examine a wide variety of potential learning algorithms and optimization criteria and arrive at two very surprising results. First, despite the…

Study of Man-Machine Communications Systems for Disabled Persons (The Handicapped). Volume V. Final Report.

ERIC Educational Resources Information Center

Kafafian, Haig

Instructions are given for teaching severely physically and/or neurologically handicapped students to use the 14-key Cybertype man-machine communications system, an electric writing machine with a simplified keyboard to enable persons with limited motor ability or coordination to communicate in written form. Explained are the various possible…

Robotic Technology: An Assessment and Forecast,

DTIC Science & Technology

1984-07-01

Research Associates# Inc. Dr. Roger Nagel# Lehigh University Dr. Charles Rosen# Machine Intelligence Corporations and Mr. Jack Thornton# Robot Insider...amr (Subcontractors: systems for assembly and Adopt Technology# inspection Stanford University. SRI) AFSC MANTECH o McDonnell Douglas o Machine ...supervisory controls man- machine interaction and system integration. - .. _ - Foreign R& The U.S. faces a strong technological challenge in robotics from

Research in Second Language Acquisition: Selected Papers of the Los Angeles Second Language Acquisition Research Forum. Issues In Second Language Research.

ERIC Educational Resources Information Center

Scarcella, Robin C., Ed.; Krashen, Stephen D., Ed.

The following papers are included: (1) "The Theoretical and Practical Relevance of Simple Codes in Second Language Acquisition" (Krashen); (2) "Talking to Foreigners versus Talking to Children: Similarities and Differences" (Freed); (3) "The Levertov Machine" (Stevick); (4) "Acquiring a Second Language when You're Not the Underdog" (Edelsky and…

Designing Microstructures/Structures for Desired Functional Material and Local Fields

DTIC Science & Technology

2015-12-02

utilized to engineer multifunctional soft materials for multi-sensing, multi- actuating , human-machine interfaces. [3] Establish a theoretical framework...model for surface elasticity, (ii) derived a new type of Maxwell stress in soft materials due to quantum mechanical-elasticity coupling and...elucidated its ramification in engineering multifunctional soft materials, and (iii) demonstrated the possibility of concurrent magnetoelectricity and

A noncoherent optical analog image processor.

PubMed

Swindell, W

1970-11-01

The description of a machine that performs a variety of image processing operations is given, together with a theoretical discussion of its operation. Spatial processing is performed by corrective convolution techniques. Density processing is achieved by means of an electrical transfer function generator included in the video circuit. Examples of images processed for removal of image motion blur, defocus, and atmospheric seeing blur are shown.

A predictive machine learning approach for microstructure optimization and materials design

NASA Astrophysics Data System (ADS)

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; Agrawal, Ankit; Sundararaghavan, Veera; Choudhary, Alok

2015-06-01

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniqueness of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. Experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.

Chain Experiment competition inspires learning of physics

NASA Astrophysics Data System (ADS)

Dziob, Daniel; Górska, Urszula; Kołodziej, Tomasz

2017-05-01

The Chain Experiment is an annual competition which originated in Slovenia in 2005 and later expanded to Poland in 2013. For the purpose of the event, each participating team designs and builds a contraption that transports a small steel ball from one end to the other. At the same time the constructed machine needs to use a number of interesting phenomena and physics laws. In the competition’s finale, all contraptions are connected to each other to form a long chain transporting steel balls. In brief, they are all evaluated for qualities such as: creativity and advance in theoretical background, as well as the reliability of the constructed machine to work without human help. In this article, we present the contraptions developed by students taking part in the competition in order to demonstrate the advance in theoretical basis together with creativity in design and outstanding engineering skills of its participants. Furthermore, we situate the Chain Experiment in the context of other group competitions, at the same time demonstrating that—besides activating numerous group work skills—it also improves the ability to think critically and present one’s knowledge to a broader audience. We discussed it in the context of problem based learning, gamification and collaborative testing.

Quality aspects of ex vivo root canal treatments done by undergraduate dental students using four different endodontic treatment systems.

PubMed

Jungnickel, Luise; Kruse, Casper; Vaeth, Michael; Kirkevang, Lise-Lotte

2018-04-01

To evaluate factors associated with treatment quality of ex vivo root canal treatments performed by undergraduate dental students using different endodontic treatment systems. Four students performed root canal treatment on 80 extracted human teeth using four endodontic treatment systems in designated treatment order following a Latin square design. Lateral seal and length of root canal fillings was radiographically assessed; for lateral seal, a graded visual scale was used. Treatment time was measured separately for access preparation, biomechanical root canal preparation, obturation and for the total procedure. Mishaps were registered. An ANOVA mirroring the Latin square design was performed. Use of machine-driven nickel-titanium systems resulted in overall better quality scores for lateral seal than use of the manual stainless-steel system. Among systems with machine-driven files, scores did not significantly differ. Use of machine-driven instruments resulted in shorter treatment time than manual instrumentation. Machine-driven systems with few files achieved shorter treatment times. With increasing number of treatments, root canal-filling quality increased, treatment time decreased; a learning curve was plotted. No root canal shaping file separated. The use of endodontic treatment systems with machine-driven files led to higher quality lateral seal compared to the manual system. The three contemporary machine-driven systems delivered comparable results regarding quality of root canal fillings; they were safe to use and provided a more efficient workflow than the manual technique. Increasing experience had a positive impact on the quality of root canal fillings while treatment time decreased.

48 CFR 908.7103 - Office machines.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 5 2011-10-01 2011-10-01 false Office machines. 908.7103... PLANNING REQUIRED SOURCES OF SUPPLIES AND SERVICES Acquisition of Special Items 908.7103 Office machines. Acquisitions of office machines by DOE offices and its authorized contractors shall be in accordance with FPMR...

Research on ARM Numerical Control System

NASA Astrophysics Data System (ADS)

Wei, Xu; JiHong, Chen

Computerized Numerical Control (CNC) machine tools is the foundation of modern manufacturing systems, whose advanced digital technology is the key to solve the problem of sustainable development of machine tool manufacturing industry. The paper is to design CNC system embedded on ARM and indicates the hardware design and the software systems supported. On the hardware side: the driving chip of the motor control unit, as the core of components, is MCX314AL of DSP motion control which is developed by NOVA Electronics Co., Ltd. of Japan. It make convenient to control machine because of its excellent performance, simple interface, easy programming. On the Software side, the uC/OS-2 is selected as the embedded operating system of the open source, which makes a detailed breakdown of the modules of the CNC system. Those priorities are designed according to their actual requirements. The ways of communication between the module and the interrupt response are so different that it guarantees real-time property and reliability of the numerical control system. Therefore, it not only meets the requirements of the current social precision machining, but has good man-machine interface and network support to facilitate a variety of craftsmen use.

Machine vision system for online inspection of freshly slaughtered chickens

USDA-ARS?s Scientific Manuscript database

A machine vision system was developed and evaluated for the automation of online inspection to differentiate freshly slaughtered wholesome chickens from systemically diseased chickens. The system consisted of an electron-multiplying charge-coupled-device camera used with an imaging spectrograph and ...

The evolution and practical application of machine translation system (1)

NASA Astrophysics Data System (ADS)

Tominaga, Isao; Sato, Masayuki

This paper describes a development, practical applicatioin, problem of a system, evaluation of practical system, and development trend of machine translation. Most recent system contains next four problems. 1) the vagueness of a text, 2) a difference of the definition of the terminology between different language, 3) the preparing of a large-scale translation dictionary, 4) the development of a software for the logical inference. Machine translation system is already used practically in many industry fields. However, many problems are not solved. The implementation of an ideal system will be after 15 years. Also, this paper described seven evaluation items detailedly. This English abstract was made by Mu system.

Food Safety by Using Machine Learning for Automatic Classification of Seeds of the South-American Incanut Plant

NASA Astrophysics Data System (ADS)

Lemanzyk, Thomas; Anding, Katharina; Linss, Gerhard; Rodriguez Hernández, Jorge; Theska, René

2015-02-01

The following paper deals with the classification of seeds and seed components of the South-American Incanut plant and the modification of a machine to handle this task. Initially the state of the art is being illustrated. The research was executed in Germany and with a relevant part in Peru and Ecuador. Theoretical considerations for the solution of an automatically analysis of the Incanut seeds were specified. The optimization of the analyzing software and the separation unit of the mechanical hardware are carried out with recognition results. In a final step the practical application of the analysis of the Incanut seeds is held on a trial basis and rated on the bases of statistic values.

Binomial distribution for quantification of protein subunits in biological Nanoassemblies and functional nanomachines

PubMed Central

Fang, Huaming; Zhang, Peng; Huang, Lisa P.; Zhao, Zhengyi; Pi, Fengmei; Montemagno, Carlo; Guo, Peixuan

2014-01-01

Living systems produce ordered structures and nanomachines that inspire the development of biomimetic nanodevices such as chips, MEMS, actuators, sensors, sorters, and apparatuses for single-pore DNA sequencing, disease diagnosis, drug or therapeutic RNA delivery. Determination of the copy numbers of subunits that build these machines is challenging due to small size. Here we report a simple mathematical method to determine the stoichiometry, using phi29 DNA-packaging nanomotor as a model to elucidate the application of a formula ∑M=0Z(ZM)pZ−MqM, where p and q are the percentage of wild-type and inactive mutant in the empirical assay; M is the copy numbers of mutant and Z is the stoichiometry in question. Variable ratios of mutants and wild-type were mixed to inhibit motor function. Empirical data were plotted over the theoretical curves to determine the stoichiometry and the value of K, which is the number of mutant needed in each machine to block the function, all based on the condition that wild-type and mutant are equal in binding affinity. Both Z and K from 1–12 were investigated. The data precisely confirmed that phi29 motor contains six copies (Z) of the motor ATPase gp16, and K = 1. PMID:24650885

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

PubMed

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-02-06

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

PubMed Central

Luo, Gang; Min, Wanli

2007-01-01

Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884

Modeling and dynamic properties of dual-chamber solid and liquid mixture vibration isolator

NASA Astrophysics Data System (ADS)

Li, F. S.; Chen, Q.; Zhou, J. H.

2016-07-01

The dual-chamber solid and liquid mixture (SALiM) vibration isolator, mainly proposed for vibration isolation of heavy machines with low frequency, consists of four principle parts: SALiM working media including elastic elements and incompressible oil, multi-layers bellows container, rigid reservoir and the oil tube connecting the two vessels. The isolation system under study is governed by a two-degrees-of-freedom (2-DOF) nonlinear equation including quadratic damping. Simplifying the nonlinear damping into viscous damping, the equivalent stiffness and damping model is derived from the equation for the response amplitude. Theoretical analysis and numerical simulation reveal that the isolator's stiffness and damping have multiple properties with different parameters, among which the effects of exciting frequency, vibrating amplitude, quadratic damping coefficient and equivalent stiffness of the two chambers on the isolator's dynamics are discussed in depth. Based on the boundary characteristics of stiffness and damping and the main causes for stiffness hardening effect, improvement strategies are proposed to obtain better dynamic properties. At last, experiments were implemented and the test results were generally consistent with the theoretical ones, which verified the reliability of the nonlinear dynamic model.

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.

High slot utilization systems for electric machines

DOEpatents

Hsu, John S

2009-06-23

Two new High Slot Utilization (HSU) Systems for electric machines enable the use of form wound coils that have the highest fill factor and the best use of magnetic materials. The epoxy/resin/curing treatment ensures the mechanical strength of the assembly of teeth, core, and coils. In addition, the first HSU system allows the coil layers to be moved inside the slots for the assembly purpose. The second system uses the slided-in teeth instead of the plugged-in teeth. The power density of the electric machine that uses either system can reach its highest limit.

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.

Automated planning for intelligent machines in energy-related applications

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

Weisbin, C.R.; de Saussure, G.; Barhen, J.

1984-01-01

This paper discusses the current activities of the Center for Engineering Systems Advanced Research (CESAR) program related to plan generation and execution by an intelligent machine. The system architecture for the CESAR mobile robot (named HERMIES-1) is described. The minimal cut-set approach is developed to reduce the tree search time of conventional backward chaining planning techniques. Finally, a real-time concept of an Intelligent Machine Operating System is presented in which planning and reasoning is embedded in a system for resource allocation and process management.

Automated fiber pigtailing machine

DOEpatents

Strand, O.T.; Lowry, M.E.

1999-01-05

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectronic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems. 26 figs.

Needs of ergonomic design at control units in production industries.

PubMed

Levchuk, I; Schäfer, A; Lang, K-H; Gebhardt, Hj; Klussmann, A

2012-01-01

During the last decades, an increasing use of innovative technologies in manufacturing areas was monitored. A huge amount of physical workload was replaced by the change from conventional machine tools to computer-controlled units. CNC systems spread in current production processes. Because of this, machine operators today mostly have an observational function. This caused increasing of static work (e.g., standing, sitting) and cognitive demands (e.g., process observation). Machine operators have a high responsibility, because mistakes may lead to human injuries as well as to product losses - and in consequence may lead to high monetary losses (for the company) as well. Being usable often means for a CNC machine being efficient. An intuitive usability and an ergonomic organization of CNC workplaces can be an essential basis to reduce the risk of failures in operation as well as physical complaints (e.g. pain or diseases because of bad body posture during work). In contrast to conventional machines, CNC machines are equipped both with hardware and software. An intuitive and clear-sighted operating of CNC systems is a requirement for quick learning of new systems. Within this study, a survey was carried out among trainees learning the operation of CNC machines.

Interlock system for machine protection of the KOMAC 100-MeV proton linac

NASA Astrophysics Data System (ADS)

Song, Young-Gi

2015-02-01

The 100-MeV proton linear accelerator of the Korea Multi-purpose Accelerator Complex (KOMAC) has been developed. The beam service started this year after performing the beam commissioning. If the very sensitive and essential equipment is to be protected during machine operation, a machine interlock system is required, and the interlock system has been implemented. The purpose of the interlock system is to shut off the beam when the radio-frequency (RF) and ion source are unstable or a beam loss occurs. The interlock signal of the KOMAC linac includes a variety of sources, such as the beam loss, RF and high-voltage converter modulator faults, and fast closing valves of the vacuum window at the beam lines and so on. This system consists of a hardware-based interlock system using analog circuits and a software-based interlock system using an industrial programmable logic controller (PLC). The hardware-based interlock system has been fabricated, and the requirement has been satisfied with the results being within 10 µs. The software logic interlock system using the PLC has been connected to the framework of with the experimental physics and industrial control system (EPICS) to integrate a variety of interlock signals and to control the machine components when an interlock occurs. This paper will describe the design and the construction of the machine interlock system for the KOMAC 100-MeV linac.

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

Hessell, Steven M.; Morris, Robert L.; McGrogan, Sean W.

A powertrain including an engine and torque machines is configured to transfer torque through a multi-mode transmission to an output member. A method for controlling the powertrain includes employing a closed-loop speed control system to control torque commands for the torque machines in response to a desired input speed. Upon approaching a power limit of a power storage device transferring power to the torque machines, power limited torque commands are determined for the torque machines in response to the power limit and the closed-loop speed control system is employed to determine an engine torque command in response to the desiredmore » input speed and the power limited torque commands for the torque machines.« less

System and method for cooling a superconducting rotary machine

DOEpatents

Ackermann, Robert Adolf [Schenectady, NY; Laskaris, Evangelos Trifon [Schenectady, NY; Huang, Xianrui [Clifton Park, NY; Bray, James William [Niskayuna, NY

2011-08-09

A system for cooling a superconducting rotary machine includes a plurality of sealed siphon tubes disposed in balanced locations around a rotor adjacent to a superconducting coil. Each of the sealed siphon tubes includes a tubular body and a heat transfer medium disposed in the tubular body that undergoes a phase change during operation of the machine to extract heat from the superconducting coil. A siphon heat exchanger is thermally coupled to the siphon tubes for extracting heat from the siphon tubes during operation of the machine.

Evaluation and selection of refrigeration systems for lunar surface and space applications

NASA Technical Reports Server (NTRS)

Copeland, R. J.; Blount, T. D.; Williams, J. L.

1971-01-01

Evaluated are the various refrigeration machines which could be used to provide heat rejection in environmental control systems for lunar surface and spacecraft applications, in order to select the best refrigeration machine for satisfying each individual application and the best refrigeration machine for satisfying all of the applications. The refrigeration machine considered include: (1) vapor comparison cycle (work-driven); (2) vapor adsorption cycle (heat-driven); (3) vapor absorption cycle (heat-driven); (4) thermoelectric (electrically-driven); (5) gas cycle (work driven); (6) steam-jet (heat-driven).

Ada Compiler Validation Summary Report: Certificate Number: 890420W1. 10074 International Business Machines Corporation, IBM Development System for the Ada Language MVS Ada Compiler, Version 2.1.1 IBM 4381 (Host and Target)

DTIC Science & Technology

1989-04-20

20. ARS1AAI . (Contimne on reverse side olnetessary *rwenPtif) by bfoci nur~be’) International Business Machines Corporation, IBM Development System...Number: AVF-VSR-261.0789 89-01-26-TEL Ada COMPILER VALIDATION SUMMARY REPORT: Certificate Number: 890420W1.10074 International Business Machines...computer. The compiler was tested using command scripts provided by International Business Machines Corporation and reviewed by the validation team. The

Ada Compiler Validation Summary Report: Certificate Number 880318W1. 09042, International Business Machines Corporation, IBM Development System for the Ada Language, Version 2.1.0, IBM 4381 under MVS/XA, Host and Target

DTIC Science & Technology

1988-03-28

International Business Machines Corporation IBM Development System for the Ada Language, Version 2.1.0 IBM 4381 under MVS/XA, host and target Completion...Joint Program Office, AJPO 20. ABSTRACT (Continue on reverse side if necessary and identify by block number) International Business Machines Corporation...in the compiler listed in this declaration. I declare that International Business Machines Corporation is the owner of record of the object code of

Long-range nanopositioning and nanomeasuring machine for application to micro- and nanotechnology

NASA Astrophysics Data System (ADS)

Jäger, Gerd; Hausotte, Tino; Büchner, Hans-Joachim; Manske, Eberhard; Schmidt, Ingomar; Mastylo, Rostyslav

2006-03-01

The paper describes the operation of a high-precision long range three-dimensional nanopositioning and nanomeasuring machine (NPM-Machine). The NPM-Machine has been developed by the Institute of Process Measurement and Sensor Technology of the Technische Universität Ilmenau. The machine was successfully tested and continually improved in the last few years. The machines are operating successfully in several German and foreign research institutes including the Physikalisch-Technische Bundesanstalt (PTB). Three plane mirror miniature interferometers are installed into the NPM-machine having a resolution of less than 0,1 nm over the entire positioning and measuring range of 25 mm x 25 mm x 5 mm. An Abbe offset-free design of the three miniature plane mirror interferometers and applying a new concept for compensating systematic errors resulting from mechanical guide systems provide extraordinary accuracy with an expanded uncertainty of only 5 - 10 nm. The integration of several, optical and tactile probe systems and nanotools makes the NPM-Machine suitable for various tasks, such as large-area scanning probe microscopy, mask and wafer inspection, nanostructuring, biotechnology and genetic engineering as well as measuring mechanical precision workpieces, precision treatment and for engineering new material. Various developed probe systems have been integrated into the NPM-Machine. The measurement results of a focus sensor, metrological AFM, white light sensor, tactile stylus probe and of a 3D-micro-touch-probe are presented. Single beam-, double beam- and triple beam interferometers built in the NPM-Machine for six degrees of freedom measurements are described.

Methods, systems and apparatus for adjusting duty cycle of pulse width modulated (PWM) waveforms

DOEpatents

Gallegos-Lopez, Gabriel; Kinoshita, Michael H; Ransom, Ray M; Perisic, Milun

2013-05-21

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a vector controlled motor drive system when the multi-phase machine operates in an overmodulation region. The disclosed embodiments provide a mechanism for adjusting a duty cycle of PWM waveforms so that the correct phase voltage command signals are applied at the angle transitions. This can reduce variations/errors in the phase voltage command signals applied to the multi-phase machine so that phase current may be properly regulated thus reducing current/torque oscillation, which can in turn improve machine efficiency and performance, as well as utilization of the DC voltage source.

Proceedings of the NASA Conference on Space Telerobotics, volume 2

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor); Seraji, Homayoun (Editor)

1989-01-01

These proceedings contain papers presented at the NASA Conference on Space Telerobotics held in Pasadena, January 31 to February 2, 1989. The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research.

Machine Learning

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

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

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

Mathematical defense method of networked servers with controlled remote backups

NASA Astrophysics Data System (ADS)

Kim, Song-Kyoo

2006-05-01

The networked server defense model is focused on reliability and availability in security respects. The (remote) backup servers are hooked up by VPN (Virtual Private Network) with high-speed optical network and replace broken main severs immediately. The networked server can be represent as "machines" and then the system deals with main unreliable, spare, and auxiliary spare machine. During vacation periods, when the system performs a mandatory routine maintenance, auxiliary machines are being used for back-ups; the information on the system is naturally delayed. Analog of the N-policy to restrict the usage of auxiliary machines to some reasonable quantity. The results are demonstrated in the network architecture by using the stochastic optimization techniques.

Present and Future of M2M

NASA Astrophysics Data System (ADS)

Ono, Satoru; Watanabe, Takashi

In recent years, the rapid progress in the development of hardware and software technologies enables tiny and low cost information devices hereinafter referred to as Machine to be widely available. M2M (Machine to Machine) has been of much attention where many tiny machines are connected to each other through networks with minimal human intervention to provide smooth and intelligent management. M2M is a promising core technology providing timely, flexible, efficient and comprehensive service at low cost. M2M has wide variety of applications including energy management system, environmental monitoring system, intelligent transport system, industrial automation system and other applications. M2M consists of terminals and networks that connect them. In this paper, we mainly focus on M2M networking and mention the future direction of the technology.

Application of Electro Chemical Machining for materials used in extreme conditions

NASA Astrophysics Data System (ADS)

Pandilov, Z.

2018-03-01

Electro-Chemical Machining (ECM) is the generic term for a variety of electrochemical processes. ECM is used to machine work pieces from metal and metal alloys irrespective of their hardness, strength or thermal properties, through the anodic dissolution, in aerospace, automotive, construction, medical equipment, micro-systems and power supply industries. The Electro Chemical Machining is extremely suitable for machining of materials used in extreme conditions. General overview of the Electro-Chemical Machining and its application for different materials used in extreme conditions is presented.

PREFACE: Biomimetics, Artificial Muscles & Nano-Bio 2007: Scientists Meet Doctors

NASA Astrophysics Data System (ADS)

Fernández Otero, Toribio

2008-02-01

Science is one of the most robust conceptual constructs developed by human beings. Theoretical physical models have been developed involving the smallest and the largest systems over the full scale of the universe. At both extremes the models are predictive and include constant interactions between components. Life evolved from systems of intermediate size in relation to the extremes of universal scale. Life, biological organs and cells only develop functions under chemical driving conditions. Natural organs can be considered as biological devices which are very efficient at transforming chemical energy at constant temperature into functions, unlike machines' servitude to the Carnot cycle. Inside any living cell thousands of simultaneous reactions occur. Every reaction promotes changes from reactants to products with subsequent changes to hundreds of intramolecular and intermolecular interactions. Moreover, most of those reactions link conformational changes of biopolymers with ionic and electronic movement driving water flow. Chemical reactions, intermolecular and intramolecular interactions involving conformational movements are outside the possibilities of current theoretical models. Theoretical descriptions of any living cell and predictions of its behaviour when unhealthy are unavailable within our scientific models. Actuation of natural organs such as muscles involves, moreover, the chemical reaction ATP hydrolysis—simultaneous sensing processes which provide living creatures with a perfect consciousness of both the characteristics of their mechanical movements and their interactions with their environment: they are intelligent machines. This constitutes the proximity paradox. We have been able to develop good and predictive theoretical models for subatomic or galactic systems, far removed from our everyday surroundings. Nevertheless, we are unable to predict the behaviour of the cells and organs that constitute our life and everyday environment, when invaded by a new virus. A very expensive trial and error (still pseudo-alchemic) procedure has to be initiated to try to enable ill people to get better. Nowadays models from chemical kinetics do not include any quantification of either changes to the molecular interactions inside the system during reaction or structural information about the conformational changes brought about by enzymes or reactive proteins. From our point of view this is one the most important scientific challenges for the 21st century, involving responses to questions related to life, health and illness. Those responses, due to the magnitude of the challenge, can only be obtained by cooperative work involving chemists, physicist, engineers, biologists and clinicians. Figure Figure showing the full distance inside the universe. Small and large systems are submitted as `constant physical' interactions affording quite predictive models. Life is based on chemistry giving rise to simultaneous changes on all the molecular interactions included in the system: their interpretation is outside current chemical or physical models. Most technological advances developed by human beings are inspired by biological systems, organs, or mechanisms present in living creatures. The main difference between human technology and natural organs is the changes in chemical composition occurring inside the wet natural organ during actuation: they are reactive, soft and wet materials. Our artificial machines are constructed of dry materials that maintain a constant composition under actuation. This is the context proposed for the consecutive World Congresses on Biomimetics, Artificial Muscles & Nano-Bio and more specifically for the IVth Congress held in Torre Pacheco, Spain, 6-9 November 2007. The papers selected for this volume of Journal of Physics: Conference Series includes: dry and wet materials, chemically reactive or physically reactive materials, organic and inorganic materials, macroscopic films and nanoparticles. Different biomimicking devices: artificial muscles and actuators, sensors, electrochromic materials, and microscopic magnetic control of fluids are described under different experimental conditions. New models, including or avoiding chemical reactions are presented here. In this way new steps are being presented in an attempt to model biomimicking materials and devices. We expect that those biomimicking devices and models will, in the future, open the way to predict the behaviour of cells. Thanks are due to the editorial and production team of Journal of Physics: Conference Series for their continued support and management of the review and preparation process in an entirely efficient and professional manner. Thanks are due to those institutions that have contributed in different ways to the final success of the meeting: MEC, ISE, UPCT, IBERNAM and the Autonomous Government of the Murcia Region. Special thanks go to all the participants who have contributed to this volume of Journal of Physics: Conference Series who are at the forefront of progress towards the biomimetics of materials, properties and models. Toribio Fernández Otero

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1990-01-01

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Experimental investigation of the tip based micro/nano machining

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Development and testing of a computer assisted remote-control system for the compact loader-trammer. Report of Investigations/1992

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

Ruff, T.M.

1992-01-01

A prototype mucking machine designed to operate in narrow vein stopes was developed by Foster-Miller, Inc., Waltham, MA, under contract with the U.S. Bureau of Mines. The machine, called a compact loader/trammer, or minimucker, was designed to replace slusher muckers in narrow-vein underground mines. The minimucker is a six-wheel-drive, skid-steered, load-haul-dump machine that loads muck at the front with a novel slide-bucket system and ejects it out the rear so that the machine does not have to be turned around. To correct deficiencies of the tether remote control system, a computer-based, radio remote control was retrofitted to the minimucker. Initialmore » tests indicated a need to assist the operator in guiding the machine in narrow stopes and an automatic guidance system that used ultrasonic ranging sensors and a wall-following algorithm was installed. Additional tests in a simulated test stope showed that these changes improved the operation of the minimucker. The design and functions of the minimucker and its computer-based, remote control system are reviewed, and an ultrasonic, sensor-based guidance system is described.« less

Development of hand rehabilitation system for paralysis patient - universal design using wire-driven mechanism.

PubMed

Yamaura, Hiroshi; Matsushita, Kojiro; Kato, Ryu; Yokoi, Hiroshi

2009-01-01

We have developed a hand rehabilitation system for patients suffering from paralysis or contracture. It consists of two components: a hand rehabilitation machine, which moves human finger joints with motors, and a data glove, which provides control of the movement of finger joints attached to the rehabilitation machine. The machine is based on the arm structure type of hand rehabilitation machine; a motor indirectly moves a finger joint via a closed four-link mechanism. We employ a wire-driven mechanism and develop a compact design that can control all three joints (i.e., PIP, DIP and MP ) of a finger and that offers a wider range of joint motion than conventional systems. Furthermore, we demonstrate the hand rehabilitation process, finger joints of the left hand attached to the machine are controlled by the finger joints of the right hand wearing the data glove.

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

Ken L. Stratton

The objective of this project is to investigate the applicability of a combined Global Positioning System and Inertial Measurement Unit (GPS/IMU) for information based displays on earthmoving machines and for automated earthmoving machines in the future. This technology has the potential of allowing an information-based product like Caterpillar's Computer Aided Earthmoving System (CAES) to operate in areas with satellite shading. Satellite shading is an issue in open pit mining because machines are routinely required to operate close to high walls, which reduces significantly the amount of the visible sky to the GPS antenna mounted on the machine. An inertial measurementmore » unit is a product, which provides data for the calculation of position based on sensing accelerations and rotation rates of the machine's rigid body. When this information is coupled with GPS it results in a positioning system that can maintain positioning capability during time periods of shading.« less

A Real-Time Tool Positioning Sensor for Machine-Tools

PubMed Central

Ruiz, Antonio Ramon Jimenez; Rosas, Jorge Guevara; Granja, Fernando Seco; Honorato, Jose Carlos Prieto; Taboada, Jose Juan Esteve; Serrano, Vicente Mico; Jimenez, Teresa Molina

2009-01-01

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations. PMID:22408472

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.