A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

Directory of Open Access Journals (Sweden)

Li Zhen

2008-05-01

Full Text Available Abstract Background Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex in vitro/in vivo datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML methods. Results The classification performance of Artificial Neural Networks (ANN, K-Nearest Neighbors (KNN, Linear Discriminant Analysis (LDA, Naïve Bayes (NB, Recursive Partitioning and Regression Trees (RPART, and Support Vector Machines (SVM in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated in vitro assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5 were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA. Conclusion We have developed a novel simulation model to evaluate machine learning methods for the

Optimization of Gas Composition Used in Plasma Chemical Vaporization Machining for Figuring of Reaction-Sintered Silicon Carbide with Low Surface Roughness.

Science.gov (United States)

Sun, Rongyan; Yang, Xu; Ohkubo, Yuji; Endo, Katsuyoshi; Yamamura, Kazuya

2018-02-05

In recent years, reaction-sintered silicon carbide (RS-SiC) has been of interest in many engineering fields because of its excellent properties, such as its light weight, high rigidity, high heat conductance and low coefficient of thermal expansion. However, RS-SiC is difficult to machine owing to its high hardness and chemical inertness and because it contains multiple components. To overcome the problem of the poor machinability of RS-SiC in conventional machining, the application of atmospheric-pressure plasma chemical vaporization machining (AP-PCVM) to RS-SiC was proposed. As a highly efficient and damage-free figuring technique, AP-PCVM has been widely applied for the figuring of single-component materials, such as Si, SiC, quartz crystal wafers, and so forth. However, it has not been applied to RS-SiC since it is composed of multiple components. In this study, we investigated the AP-PCVM etching characteristics for RS-SiC by optimizing the gas composition. It was found that the different etching rates of the different components led to a large surface roughness. A smooth surface was obtained by applying the optimum gas composition, for which the etching rate of the Si component was equal to that of the SiC component.

Adaptive machine and its thermodynamic costs

Science.gov (United States)

Allahverdyan, Armen E.; Wang, Q. A.

2013-03-01

We study the minimal thermodynamically consistent model for an adaptive machine that transfers particles from a higher chemical potential reservoir to a lower one. This model describes essentials of the inhomogeneous catalysis. It is supposed to function with the maximal current under uncertain chemical potentials: if they change, the machine tunes its own structure fitting it to the maximal current under new conditions. This adaptation is possible under two limitations: (i) The degree of freedom that controls the machine's structure has to have a stored energy (described via a negative temperature). The origin of this result is traced back to the Le Chatelier principle. (ii) The machine has to malfunction at a constant environment due to structural fluctuations, whose relative magnitude is controlled solely by the stored energy. We argue that several features of the adaptive machine are similar to those of living organisms (energy storage, aging).

In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.

Science.gov (United States)

Cheng, Feixiong; Shen, Jie; Yu, Yue; Li, Weihua; Liu, Guixia; Lee, Philip W; Tang, Yun

2011-03-01

There is an increasing need for the rapid safety assessment of chemicals by both industries and regulatory agencies throughout the world. In silico techniques are practical alternatives in the environmental hazard assessment. It is especially true to address the persistence, bioaccumulative and toxicity potentials of organic chemicals. Tetrahymena pyriformis toxicity is often used as a toxic endpoint. In this study, 1571 diverse unique chemicals were collected from the literature and composed of the largest diverse data set for T. pyriformis toxicity. Classification predictive models of T. pyriformis toxicity were developed by substructure pattern recognition and different machine learning methods, including support vector machine (SVM), C4.5 decision tree, k-nearest neighbors and random forest. The results of a 5-fold cross-validation showed that the SVM method performed better than other algorithms. The overall predictive accuracies of the SVM classification model with radial basis functions kernel was 92.2% for the 5-fold cross-validation and 92.6% for the external validation set, respectively. Furthermore, several representative substructure patterns for characterizing T. pyriformis toxicity were also identified via the information gain analysis methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development of novel tungsten processing technologies for electro-chemical machining (ECM) of plasma facing components

International Nuclear Information System (INIS)

Holstein, Nils; Krauss, Wolfgang; Konys, Juergen

2011-01-01

Plasma facing components for fusion applications must exhibit long-term stability under extreme conditions, and therefore material imperfections cannot be tolerated due to a high risk of technical failures. To prevent or abolish defects in refractory metals components during the manufacturing process, some methods of electro-chemical machining as S-ECM and C-ECM were developed, enabling both the processing of smooth plain defect-free surfaces of different geometry and the removal of bulk material for the shaping of three-dimensional structures, also without cracks. It is discussed, that tungsten ablation with accurate electro-chemical molding is very sensitive to the kind of electric current, and therefore current investigations focused also on the effects of frequency profiles on the sharpness of edge rounding.

Machining of titanium alloys

CERN Document Server

2014-01-01

This book presents a collection of examples illustrating the resent research advances in the machining of titanium alloys. These materials have excellent strength and fracture toughness as well as low density and good corrosion resistance; however, machinability is still poor due to their low thermal conductivity and high chemical reactivity with cutting tool materials. This book presents solutions to enhance machinability in titanium-based alloys and serves as a useful reference to professionals and researchers in aerospace, automotive and biomedical fields.

From Chemical Topology to Molecular Machines (Nobel Lecture).

Science.gov (United States)

Sauvage, Jean-Pierre

2017-09-04

To a large extent, the field of "molecular machines" started after several groups were able to prepare, reasonably easily, interlocking ring compounds (named catenanes for compounds consisting of interlocking rings and rotaxanes for rings threaded by molecular filaments or axes). Important families of molecular machines not belonging to the interlocking world were also designed, prepared, and studied but, for most of them, their elaboration was more recent than that of catenanes or rotaxanes. Since the creation of interlocking ring molecules is so important in relation to the molecular machinery area, we will start with this aspect of our work. The second part will naturally be devoted to the dynamic properties of such systems and to the compounds for which motions can be directed in a controlled manner from the outside, that is, molecular machines. We will restrict our discussion to a very limited number of examples which we consider as particularly representative of the field. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

Science.gov (United States)

Yang, Hongbin; Sun, Lixia; Li, Weihua; Liu, Guixia; Tang, Yun

2018-02-01

For a drug, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future.

In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts

Directory of Open Access Journals (Sweden)

Hongbin Yang

2018-02-01

Full Text Available During drug development, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future.

In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts.

Science.gov (United States)

Yang, Hongbin; Sun, Lixia; Li, Weihua; Liu, Guixia; Tang, Yun

2018-01-01

During drug development, safety is always the most important issue, including a variety of toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial phases. This review article at first simply introduced the computational methods used in prediction of chemical toxicity for drug design, including machine learning methods and structural alerts. Machine learning methods have been widely applied in qualitative classification and quantitative regression studies, while structural alerts can be regarded as a complementary tool for lead optimization. The emphasis of this article was put on the recent progress of predictive models built for various toxicities. Available databases and web servers were also provided. Though the methods and models are very helpful for drug design, there are still some challenges and limitations to be improved for drug safety assessment in the future.

Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

International Nuclear Information System (INIS)

Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; Lilienfeld, O. Anatole von; Müller, Klaus-Robert; Tkatchenko, Alexandre

2015-01-01

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies

Bias-Free Chemically Diverse Test Sets from Machine Learning.

Science.gov (United States)

Swann, Ellen T; Fernandez, Michael; Coote, Michelle L; Barnard, Amanda S

2017-08-14

Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal analysis and K-means clustering have previously been used to summarize large sets of nanoparticles however molecules are more diverse and not as easily characterized by descriptors. In this work, we compare three sets of descriptors based on the one-, two-, and three-dimensional structure of a molecule. Using data from the NIST Computational Chemistry Comparison and Benchmark Database and machine learning techniques, we demonstrate the functional relationship between these structural descriptors and the electronic energy of molecules. Archetypes and prototypes found with topological or Coulomb matrix descriptors can be used to identify smaller, statistically significant test sets that better capture the diversity of chemical space. We apply this same method to find a diverse subset of organic molecules to demonstrate how the methods can easily be reapplied to individual research projects. Finally, we use our bias-free test sets to assess the performance of density functional theory and quantum Monte Carlo methods.

THE INFLUENCE OF CHEMICAL COMPOSITION OF HIGH-CHROMIUM CAST IRONS ON THE MACHINABILITY

Directory of Open Access Journals (Sweden)

V. V. Netrebko

2016-02-01

Full Text Available Purpose. This research is aimed to obtain the regression dependence of the machinability on the chemical composition of pig iron (C, Cr, Mn and Ni in cast state. Methodology. The method of active experiment planning was used to build a mathematical model. Cast irons of composition 1.09…3.91 % С; 11.43…25.57 % Cr; 0.6…5.4 % Mn; 0.19…3.01 % Ni were studied. Cutting tools with plates 10х10 mm out of ВК8 according to State Standard 19051-80 were used for turning. Cutting modes: cutting depth – 0.8 mm, longitudinal feed – 0.15 mm/rot., spindle’s rotation frequency during turning – 200…360 rot./min. Lubricating and cooling liquids were not applied. Evaluation of iron workability was produced by determining the linear tool flank wear per unit length of the cutting path. Findings. Mathematically probabilistic equation of the regression dependence of the cutting tool’s wear on the C, Cr, Mn and Ni content in the machined cast iron were obtained. It was established that with the increase of Cr content in the cast iron to 14.8 % the cutting tool’s wear decreased as a result of formation of carbide eutectic which destroyed the doped ledeburite continuous frame. Further increase of chromium content promoted appearing of chromic carbides with high microhardness which considerably increased the tool’s wear. The conducted research shown that the minimum cutting tool’s wear 0,18 mkm/m was observed during the machining of cast iron containing: 1.09 % C, 14.8 % Cr, 2.3 % Mn and 1.2 % Ni; and the maximum wear is 48,96 mkm/m – when the content was: 3.91 % C, 11.43 % Cr, 5.4 % Mn and 0.19 % Ni. The tool’s wear reached 47.61 mkm/m during the treatment of cast iron containing 3.91 % C, 25.57 % Cr, 5.4 % Mn and 0.19 % Ni. Originality. Mathematically probabilistic model of the dependence of the cutting tool’s wear on the C, Cr, Mn and Ni content in the machined cast iron has been elaborated by the author. Practical value. The model

The modelling of dynamic chemical state of paper machine unit operations; Dynaamisen kemiallisen tilan mallintaminen paperikoneen yksikkoeoperaatioissa - MPKT 04

Energy Technology Data Exchange (ETDEWEB)

Ylen, J.P.; Jutila, P. [Helsinki Univ. of Technology, Otaniemi (Finland)

1998-12-31

The chemical state of paper mass is considered to be a key factor to the smooth operation of the paper machine. There are simulators that have been developed either for dynamic energy and mass balances or for static chemical phenomena, but the combination of these is not a straight forward task. Control Engineering Laboratory of Helsinki University of Technology has studied the paper machine wet end phenomena with the emphasis on pH-modelling. VTT (Technical Research Centre of Finland) Process Physics has used thermodynamical modelling successfully in e.g. Bleaching processes. In this research the different approaches are combined in order to get reliable dynamical models and modelling procedures for various unit operations. A flexible pilot process will be constructed and different materials will be processed starting from simple inorganic substances (e.g. Calcium carbonate and distilled water) working towards more complex masses (thick pulp with process waters and various reagents). The pilot process is well instrumented with ion selective electrodes, total calcium analysator and all basic measurements. (orig.)

The modelling of dynamic chemical state of paper machine unit operations; Dynaamisen kemiallisen tilan mallintaminen paperikoneen yksikkoeoperaatioissa - MPKT 04

Energy Technology Data Exchange (ETDEWEB)

Ylen, J P; Jutila, P [Helsinki Univ. of Technology, Otaniemi (Finland)

1999-12-31

The chemical state of paper mass is considered to be a key factor to the smooth operation of the paper machine. There are simulators that have been developed either for dynamic energy and mass balances or for static chemical phenomena, but the combination of these is not a straight forward task. Control Engineering Laboratory of Helsinki University of Technology has studied the paper machine wet end phenomena with the emphasis on pH-modelling. VTT (Technical Research Centre of Finland) Process Physics has used thermodynamical modelling successfully in e.g. Bleaching processes. In this research the different approaches are combined in order to get reliable dynamical models and modelling procedures for various unit operations. A flexible pilot process will be constructed and different materials will be processed starting from simple inorganic substances (e.g. Calcium carbonate and distilled water) working towards more complex masses (thick pulp with process waters and various reagents). The pilot process is well instrumented with ion selective electrodes, total calcium analysator and all basic measurements. (orig.)

Electronic spectra from TDDFT and machine learning in chemical space

International Nuclear Information System (INIS)

Ramakrishnan, Raghunathan; Hartmann, Mia; Tapavicza, Enrico; Lilienfeld, O. Anatole von

2015-01-01

Due to its favorable computational efficiency, time-dependent (TD) density functional theory (DFT) enables the prediction of electronic spectra in a high-throughput manner across chemical space. Its predictions, however, can be quite inaccurate. We resolve this issue with machine learning models trained on deviations of reference second-order approximate coupled-cluster (CC2) singles and doubles spectra from TDDFT counterparts, or even from DFT gap. We applied this approach to low-lying singlet-singlet vertical electronic spectra of over 20 000 synthetically feasible small organic molecules with up to eight CONF atoms. The prediction errors decay monotonously as a function of training set size. For a training set of 10 000 molecules, CC2 excitation energies can be reproduced to within ±0.1 eV for the remaining molecules. Analysis of our spectral database via chromophore counting suggests that even higher accuracies can be achieved. Based on the evidence collected, we discuss open challenges associated with data-driven modeling of high-lying spectra and transition intensities

Electronic spectra from TDDFT and machine learning in chemical space

Energy Technology Data Exchange (ETDEWEB)

Ramakrishnan, Raghunathan [Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel (Switzerland); Hartmann, Mia; Tapavicza, Enrico, E-mail: Enrico.Tapavicza@csulb.edu [Department of Chemistry and Biochemistry, California State University, 1250 Bellflower Boulevard, Long Beach, California 90840 (United States); Lilienfeld, O. Anatole von, E-mail: anatole.vonlilienfeld@unibas.ch [Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel (Switzerland); Argonne Leadership Computing Facility, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, Illinois 60439 (United States)

2015-08-28

Due to its favorable computational efficiency, time-dependent (TD) density functional theory (DFT) enables the prediction of electronic spectra in a high-throughput manner across chemical space. Its predictions, however, can be quite inaccurate. We resolve this issue with machine learning models trained on deviations of reference second-order approximate coupled-cluster (CC2) singles and doubles spectra from TDDFT counterparts, or even from DFT gap. We applied this approach to low-lying singlet-singlet vertical electronic spectra of over 20 000 synthetically feasible small organic molecules with up to eight CONF atoms. The prediction errors decay monotonously as a function of training set size. For a training set of 10 000 molecules, CC2 excitation energies can be reproduced to within ±0.1 eV for the remaining molecules. Analysis of our spectral database via chromophore counting suggests that even higher accuracies can be achieved. Based on the evidence collected, we discuss open challenges associated with data-driven modeling of high-lying spectra and transition intensities.

Machining refractory alloys: an overview

International Nuclear Information System (INIS)

Christopher, J.D.

1984-01-01

Nontraditional machining is a generic term for those material removal processes that differ drastically from the historic operations such as turning, milling, drilling, tapping, and grinding. The use of primary energy modes other than mechanical, such as thermal, electrical, and chemical, sets these operations apart and reinforces their nontraditional label. Several of these newer processes have been very successful in machining close tolerance parts from refractory materials. This paper provides a general overview of both traditional and nontraditional aspects of machining refractory materials. 11 figures, 7 tables

A nanoplasmonic switch based on molecular machines

KAUST Repository

Zheng, Yue Bing

2009-06-01

We aim to develop a molecular-machine-driven nanoplasmonic switch for its use in future nanophotonic integrated circuits (ICs) that have applications in optical communication, information processing, biological and chemical sensing. Experimental data show that an Au nanodisk array, coated with rotaxane molecular machines, switches its localized surface plasmon resonances (LSPR) reversibly when it is exposed to chemical oxidants and reductants. Conversely, bare Au nanodisks and disks coated with mechanically inert control compounds, do not display the same switching behavior. Along with calculations based on time-dependent density functional theory (TDDFT), these observations suggest that the nanoscale movements within surface-bound "molecular machines" can be used as the active components in plasmonic devices. ©2009 IEEE.

Molecular machines open cell membranes.

Science.gov (United States)

García-López, Víctor; Chen, Fang; Nilewski, Lizanne G; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B; Robinson, Jacob T; Wang, Gufeng; Pal, Robert; Tour, James M

2017-08-30

Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

Molecular machines open cell membranes

Science.gov (United States)

García-López, Víctor; Chen, Fang; Nilewski, Lizanne G.; Duret, Guillaume; Aliyan, Amir; Kolomeisky, Anatoly B.; Robinson, Jacob T.; Wang, Gufeng; Pal, Robert; Tour, James M.

2017-08-01

Beyond the more common chemical delivery strategies, several physical techniques are used to open the lipid bilayers of cellular membranes. These include using electric and magnetic fields, temperature, ultrasound or light to introduce compounds into cells, to release molecular species from cells or to selectively induce programmed cell death (apoptosis) or uncontrolled cell death (necrosis). More recently, molecular motors and switches that can change their conformation in a controlled manner in response to external stimuli have been used to produce mechanical actions on tissue for biomedical applications. Here we show that molecular machines can drill through cellular bilayers using their molecular-scale actuation, specifically nanomechanical action. Upon physical adsorption of the molecular motors onto lipid bilayers and subsequent activation of the motors using ultraviolet light, holes are drilled in the cell membranes. We designed molecular motors and complementary experimental protocols that use nanomechanical action to induce the diffusion of chemical species out of synthetic vesicles, to enhance the diffusion of traceable molecular machines into and within live cells, to induce necrosis and to introduce chemical species into live cells. We also show that, by using molecular machines that bear short peptide addends, nanomechanical action can selectively target specific cell-surface recognition sites. Beyond the in vitro applications demonstrated here, we expect that molecular machines could also be used in vivo, especially as their design progresses to allow two-photon, near-infrared and radio-frequency activation.

Stereodivergent synthesis with a programmable molecular machine

Science.gov (United States)

Kassem, Salma; Lee, Alan T. L.; Leigh, David A.; Marcos, Vanesa; Palmer, Leoni I.; Pisano, Simone

2017-09-01

It has been convincingly argued that molecular machines that manipulate individual atoms, or highly reactive clusters of atoms, with Ångström precision are unlikely to be realized. However, biological molecular machines routinely position rather less reactive substrates in order to direct chemical reaction sequences, from sequence-specific synthesis by the ribosome to polyketide synthases, where tethered molecules are passed from active site to active site in multi-enzyme complexes. Artificial molecular machines have been developed for tasks that include sequence-specific oligomer synthesis and the switching of product chirality, a photo-responsive host molecule has been described that is able to mechanically twist a bound molecular guest, and molecular fragments have been selectively transported in either direction between sites on a molecular platform through a ratchet mechanism. Here we detail an artificial molecular machine that moves a substrate between different activating sites to achieve different product outcomes from chemical synthesis. This molecular robot can be programmed to stereoselectively produce, in a sequential one-pot operation, an excess of any one of four possible diastereoisomers from the addition of a thiol and an alkene to an α,β-unsaturated aldehyde in a tandem reaction process. The stereodivergent synthesis includes diastereoisomers that cannot be selectively synthesized through conventional iminium-enamine organocatalysis. We anticipate that future generations of programmable molecular machines may have significant roles in chemical synthesis and molecular manufacturing.

Nontraditional machining processes research advances

CERN Document Server

2013-01-01

Nontraditional machining employs processes that remove material by various methods involving thermal, electrical, chemical and mechanical energy or even combinations of these. Nontraditional Machining Processes covers recent research and development in techniques and processes which focus on achieving high accuracies and good surface finishes, parts machined without burrs or residual stresses especially with materials that cannot be machined by conventional methods. With applications to the automotive, aircraft and mould and die industries, Nontraditional Machining Processes explores different aspects and processes through dedicated chapters. The seven chapters explore recent research into a range of topics including laser assisted manufacturing, abrasive water jet milling and hybrid processes. Students and researchers will find the practical examples and new processes useful for both reference and for developing further processes. Industry professionals and materials engineers will also find Nontraditional M...

Non-equilibrium quantum heat machines

Science.gov (United States)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-11-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound.

Non-equilibrium quantum heat machines

International Nuclear Information System (INIS)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-01-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound. (paper)

Predictive Toxicology: Modeling Chemical Induced Toxicological Response Combining Circular Fingerprints with Random Forest and Support Vector Machine

Directory of Open Access Journals (Sweden)

Alexios eKoutsoukas

2016-03-01

Full Text Available Modern drug discovery and toxicological research are under pressure, as the cost of developing and testing new chemicals for potential toxicological risk is rising. Extensive evaluation of chemical products for potential adverse effects is a challenging task, due to the large number of chemicals and the possible hazardous effects on human health. Safety regulatory agencies around the world are dealing with two major challenges. First, the growth of chemicals introduced every year in household products and medicines that need to be tested, and second the need to protect public welfare. Hence, alternative and more efficient toxicological risk assessment methods are in high demand. The Toxicology in the 21st Century (Tox21 consortium a collaborative effort was formed to develop and investigate alternative assessment methods. A collection of 10,000 compounds composed of environmental chemicals and approved drugs were screened for interference in biochemical pathways and released for crowdsourcing data analysis. The physicochemical space covered by Tox21 library was explored, measured by Molecular Weight (MW and the octanol/water partition coefficient (cLogP. It was found that on average chemical structures had MW of 272.6 Daltons. In case of cLogP the average value was 2.476. Next relationships between assays were examined based on compounds activity profiles across the assays utilizing the Pearson correlation coefficient r. A cluster was observed between the Androgen and Estrogen Receptors and their ligand bind domains accordingly indicating presence of cross talks among the receptors. The highest correlations observed were between NR.AR and NR.AR_LBD, where it was r=0.66 and between NR.ER and NR.ER_LBD, where it was r=0.5.Our approach to model the Tox21 data consisted of utilizing circular molecular fingerprints combined with Random Forest and Support Vector Machine by modeling each assay independently. In all of the 12 sub-challenges our modeling

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

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

Effect of some types of machining processes on beryllium fatigue strength properties

International Nuclear Information System (INIS)

Armbruster, M.

1977-01-01

The aim of this work, which is sponsored by the French D.G.R.S.T., is to determine a machining process giving both the highest tensile strength and the highest fatigue limit to beryllium parts. A comparison is made of the effects of : mechanical machining, electro discharge machining, electro-chemical machining, electrolytical and chemical polishing, glass shot peening, on the mechanical strength and fatigue limits of samples taken from hot pressed and extruded rods and from cast ingot sheets, either notched or not as required. Complementary examinations are performed principally by fractographic study. The results show that for beryllium, electrochemical machining followed by glass shot peening gives the best results; however mechanical machining with electrolytical polishing followed by glass shot peening are also satisfactory. (author)

Preliminary study on rotary ultrasonic machining of Bk-7 optical glass rod

International Nuclear Information System (INIS)

Hamzah, E.; Izman, S.; Khoo, C.Y.; Zainal Abidin, N.N.

2007-01-01

This paper presents an experimental observation on rotary ultrasonic machining (RUM) of BK7 optical glass rod. BK7 is a common technical optical glass for high quality optical components due to its high linear optical transmission in the visible range and is chemically stable. RUM is a hybrid machining process that combines the material removal mechanisms of diamond grinding and ultrasonic machining (USM) and it is non-thermal, non-chemical, creates no change in the microstructure, chemical or physical properties of the work piece. In the RUM, a controlled static load is applied to the rotating core drill with metal bonded diamond abrasive and is ultrasonically vibrated in the axial direction. A water-soluble coolant was used to cool the tool and sample during machining processes. By using DOE (Design of Experiment) approach, the effect of spindle speed and feed rate to the ultrasonic machinability had been developed. The main effects and two-factor interactions of process parameters (spindle speed) and feed rate) on output variables (MRR, surface roughness, opaqueness, chipping thickness and chipping size) are studied. (author)

Dynamics and Thermodynamics of Molecular Machines

DEFF Research Database (Denmark)

Golubeva, Natalia

2014-01-01

to their microscopic size, molecular motors are governed by principles fundamentally different from those describing the operation of man-made motors such as car engines. In this dissertation the dynamic and thermodynamic properties of molecular machines are studied using the tools of nonequilibrium statistical......Molecular machines, or molecular motors, are small biophysical devices that perform a variety of essential metabolic processes such as DNA replication, protein synthesis and intracellular transport. Typically, these machines operate by converting chemical energy into motion and mechanical work. Due...... mechanics. The first part focuses on noninteracting molecular machines described by a paradigmatic continuum model with the aim of comparing and contrasting such a description to the one offered by the widely used discrete models. Many molecular motors, for example, kinesin involved in cellular cargo...

Drinking water quality concerns and water vending machines

International Nuclear Information System (INIS)

McSwane, D.Z.; Oleckno, W.A.; Eils, L.M.

1994-01-01

Drinking water quality is a vital public health concern to consumers and regulators alike. This article describes some of the current microbiological, chemical, and radiological concerns about drinking water and the evolution of water vending machines. Also addressed are the typical treatment processes used in water vending machines and their effectiveness, as well as a brief examination of a certification program sponsored by the National Automatic Merchandising Association (NAMA), which provides a uniform standard for the design and construction of food and beverage vending machines. For some consumers, the water dispensed from vending machines is an attractive alternative to residential tap water which may be objectionable for aesthetic or other reasons

Chemical Equilibrium And Transport (CET)

Science.gov (United States)

Mcbride, B. J.

1991-01-01

Powerful, machine-independent program calculates theoretical thermodynamic properties of chemical systems. Aids in design of compressors, turbines, engines, heat exchangers, and chemical processing equipment.

Automatic welding machine for piping

International Nuclear Information System (INIS)

Yoshida, Kazuhiro; Koyama, Takaichi; Iizuka, Tomio; Ito, Yoshitoshi; Takami, Katsumi.

1978-01-01

A remotely controlled automatic special welding machine for piping was developed. This machine is utilized for long distance pipe lines, chemical plants, thermal power generating plants and nuclear power plants effectively from the viewpoint of good quality control, reduction of labor and good controllability. The function of this welding machine is to inspect the shape and dimensions of edge preparation before welding work by the sense of touch, to detect the temperature of melt pool, inspect the bead form by the sense of touch, and check the welding state by ITV during welding work, and to grind the bead surface and inspect the weld metal by ultrasonic test automatically after welding work. The construction of this welding system, the main specification of the apparatus, the welding procedure in detail, the electrical source of this welding machine, the cooling system, the structure and handling of guide ring, the central control system and the operating characteristics are explained. The working procedure and the effect by using this welding machine, and the application to nuclear power plants and the other industrial field are outlined. The HIDIC 08 is used as the controlling computer. This welding machine is useful for welding SUS piping as well as carbon steel piping. (Nakai, Y.)

Machinability of structural steels with calcium addition

International Nuclear Information System (INIS)

Pytel, S.; Zadecki, M.

2003-01-01

The machinability of the plain carbon and low alloy structural steels with carbon content of 0.1-0.6% is briefly discussed in the first part of the paper. In the experimental part a dependence between the addition of calcium and some changes in sulphide and oxide inclusions morphology is presented. The Volvo test for measurement of machinability index B i has been applied. Using the multiple regression methods two relationships between machinability index B i and stereological parameters of non-metallic inclusions as well as hardness of the steels have been calculated. The authors have reached the conclusion that owing to the changes in inclusion chemical composition and geometry as result of calcium addition the machinability index of the steel can be higher. (author)

Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti; Buus, Ole Thomsen; Larsen, Jan

2017-01-01

We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling...... of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction...... in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions...

Classifying chemical mode of action using gene networks and machine learning: a case study with the herbicide linuron.

Science.gov (United States)

Ornostay, Anna; Cowie, Andrew M; Hindle, Matthew; Baker, Christopher J O; Martyniuk, Christopher J

2013-12-01

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. © 2013.

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Science.gov (United States)

Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

2016-01-01

Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

Machine learning of molecular properties: Locality and active learning

Science.gov (United States)

Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.

2018-06-01

In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.

A review of machines and devices to potentize homeopathic medicines.

Science.gov (United States)

Basu, Abhirup; Suresh, Akkihebbal Krishnamurthy; Kane, Shantaram Govind; Bellare, Jayesh Ramesh

2017-11-01

Potentization, consisting of serial dilution and succussion, is a key step in the manufacture of homeopathic medicines. Originally prescribed as a manual process, several attempts at mechanization have been published, patented and even commercialised in order to remove the human element and introduce reproducibility without drudgery. Various machines have been used over the years to prepare homeopathic medicines. Although these machines follow the same principles, i.e. energetically mixing the medicines and diluting them significantly, their mode of operation is different from each other. This review paper surveys the main methods of preparation of homeopathic medicines. The main machines discussed are: Boericke's potentizer, Tyler Kent's instrument, John Alphonse's machine and the fluxion potentizer, which were used in the past, as well as more recent potentizers like arm-and-weight instruments, the K-Tronic potentizer and Quinn's machine. We review the construction and operating principle of each of these machines, along with their advantages and limitations. A scheme for relative performance assessment of these machines is proposed based on the parameters mechanical efficiency, physico-chemical efficiency, turbulence generation, energy dissipation, and accuracy of dilution. Quinn's machine and the arm-and-weight potentizer perform well for generating turbulence due to high impaction forces, while John Alphonse's machine is much more accurate in diluting the homeopathic medicines at every step. Both the commercial potentizers, Quinn's machine and the K-Tronic potentizer, are completely automated and therefore reduce the manual labour and variation in succussive forces during each step, which may produce uniformity in physico-chemical changes within the resulting homeopathic medicines. Copyright © 2017. Published by Elsevier Ltd.

Machinability of a Stainless Steel by Electrochemical Discharge Microdrilling

International Nuclear Information System (INIS)

Coteata, Margareta; Pop, Nicolae; Slatineanu, Laurentiu; Schulze, Hans-Peter; Besliu, Irina

2011-01-01

Due to the chemical elements included in their structure for ensuring an increased resistance to the environment action, the stainless steels are characterized by a low machinability when classical machining methods are applied. For this reason, sometimes non-traditional machining methods are applied, one of these being the electrochemical discharge machining. To obtain microholes and to evaluate the machinability by electrochemical discharge microdrilling, test pieces of stainless steel were used for experimental research. The electrolyte was an aqueous solution of sodium silicate with different densities. A complete factorial plan was designed to highlight the influence of some input variables on the sizes of the considered machinability indexes (electrode tool wear, material removal rate, depth of the machined hole). By mathematically processing of experimental data, empirical functions were established both for stainless steel and carbon steel. Graphical representations were used to obtain more suggestive vision concerning the influence exerted by the considered input variables on the size of the machinability indexes.

A nanoplasmonic switch based on molecular machines

KAUST Repository

Zheng, Yue Bing; Yang, Ying-Wei; Jensen, Lasse; Fang, Lei; Juluri, Bala Krishna; Weiss, Paul S.; Stoddart, J. Fraser; Huang, Tony Jun

2009-01-01

We aim to develop a molecular-machine-driven nanoplasmonic switch for its use in future nanophotonic integrated circuits (ICs) that have applications in optical communication, information processing, biological and chemical sensing. Experimental

Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

International Nuclear Information System (INIS)

Sun Zhong-Hua; Jiang Fan

2010-01-01

In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

Serum levels of chemical elements in esophageal squamous cell carcinoma in Anyang, China: a case-control study based on machine learning methods.

Science.gov (United States)

Lin, Tong; Liu, Tiebing; Lin, Yucheng; Zhang, Chaoting; Yan, Lailai; Chen, Zhongxue; He, Zhonghu; Wang, Jingyu

2017-09-24

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal carcinoma with extremely aggressive nature and low survival rate. The risk factors for ESCC in the high-incidence areas of China remain unclear. We used machine learning methods to investigate whether there was an association between the alterations of serum levels of certain chemical elements and ESCC. Primary healthcare unit in Anyang city, Henan Province of China. 100 patients with ESCC and 100 healthy controls matched for age, sex and region were included. Primary outcome was the classification accuracy. Secondary outcome was the p Value of the t-test or rank-sum test. Both traditional statistical methods of t-test and rank-sum test and fashionable machine learning approaches were employed. Random Forest achieves the best accuracy of 98.38% on the original feature vectors (without dimensionality reduction), and support vector machine outperforms other classifiers by yielding accuracy of 96.56% on embedding spaces (with dimensionality reduction). All six classifiers can achieve accuracies more than 90% based on the single most important element Sr. The other two elements with distinctive difference are S and P, providing accuracies around 80%. More than half of chemical elements were found to be significantly different between patients with ESCC and the controls. These results suggest clear differences between patients with ESCC and controls, implying some potential promising applications in diagnosis, prognosis, pharmacy and nutrition of ESCC. However, the results should be interpreted with caution due to the retrospective design nature, limited sample size and the lack of several potential confounding factors (including obesity, nutritional status, and fruit and vegetable consumption and potential regional carcinogen contacts). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted

Electrical discharge machining of carbon nanomaterials in air: machining characteristics and the advanced field emission applications

International Nuclear Information System (INIS)

Ok, Jong Girl; Kim, Bo Hyun; Chung, Do Kwan; Sung, Woo Yong; Lee, Seung Min; Lee, Se Won; Kim, Wal Jun; Park, Jin Woo; Chu, Chong Nam; Kim, Yong Hyup

2008-01-01

A reliable and precise machining process, electrical discharge machining (EDM), was investigated in depth as a novel method for the engineering of carbon nanomaterials. The machining characteristics of EDM applied to carbon nanomaterials 'in air' were systematically examined using scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), energy-dispersive x-ray spectroscopy (EDS), x-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. The EDM process turned out to 'melt' carbon nanomaterials with the thermal energy generated by electrical discharge, which makes both the materially and geometrically unrestricted machining of nanomaterials possible. Since the EDM process conducted in air requires neither direct contact nor chemical agents, it protects the carbon nanomaterial workpieces against physical damage and unnecessary contamination. From this EDM method, several advanced field emission applications including 'top-down' patterning and the creative lateral comb-type triode device were derived, while our previously reported study on emission uniformity enhancement by the EDM method was also referenced. The EDM method has great potential as a clean, effective and practical way to utilize carbon nanomaterials for various uses

In silico machine learning methods in drug development.

Science.gov (United States)

Dobchev, Dimitar A; Pillai, Girinath G; Karelson, Mati

2014-01-01

Machine learning (ML) computational methods for predicting compounds with pharmacological activity, specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties are being increasingly applied in drug discovery and evaluation. Recently, machine learning techniques such as artificial neural networks, support vector machines and genetic programming have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic targets. These methods are particularly useful for screening compound libraries of diverse chemical structures, "noisy" and high-dimensional data to complement QSAR methods, and in cases of unavailable receptor 3D structure to complement structure-based methods. A variety of studies have demonstrated the potential of machine-learning methods for predicting compounds as potential drug candidates. The present review is intended to give an overview of the strategies and current progress in using machine learning methods for drug design and the potential of the respective model development tools. We also regard a number of applications of the machine learning algorithms based on common classes of diseases.

Introducing Stable Radicals into Molecular Machines.

Science.gov (United States)

Wang, Yuping; Frasconi, Marco; Stoddart, J Fraser

2017-09-27

Ever since their discovery, stable organic radicals have received considerable attention from chemists because of their unique optical, electronic, and magnetic properties. Currently, one of the most appealing challenges for the chemical community is to develop sophisticated artificial molecular machines that can do work by consuming external energy, after the manner of motor proteins. In this context, radical-pairing interactions are important in addressing the challenge: they not only provide supramolecular assistance in the synthesis of molecular machines but also open the door to developing multifunctional systems relying on the various properties of the radical species. In this Outlook, by taking the radical cationic state of 1,1'-dialkyl-4,4'-bipyridinium (BIPY •+ ) as an example, we highlight our research on the art and science of introducing radical-pairing interactions into functional systems, from prototypical molecular switches to complex molecular machines, followed by a discussion of the (i) limitations of the current systems and (ii) future research directions for designing BIPY •+ -based molecular machines with useful functions.

Machine Learning Optimization of Evolvable Artificial Cells

DEFF Research Database (Denmark)

Caschera, F.; Rasmussen, S.; Hanczyc, M.

2011-01-01

can be explored. A machine learning approach (Evo-DoE) could be applied to explore this experimental space and define optimal interactions according to a specific fitness function. Herein an implementation of an evolutionary design of experiments to optimize chemical and biochemical systems based...... on a machine learning process is presented. The optimization proceeds over generations of experiments in iterative loop until optimal compositions are discovered. The fitness function is experimentally measured every time the loop is closed. Two examples of complex systems, namely a liposomal drug formulation...

Analysis of machining and machine tools

CERN Document Server

Liang, Steven Y

2016-01-01

This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

Making and Operating Molecular Machines: A Multidisciplinary Challenge.

Science.gov (United States)

Baroncini, Massimo; Casimiro, Lorenzo; de Vet, Christiaan; Groppi, Jessica; Silvi, Serena; Credi, Alberto

2018-02-01

Movement is one of the central attributes of life, and a key feature in many technological processes. While artificial motion is typically provided by macroscopic engines powered by internal combustion or electrical energy, movement in living organisms is produced by machines and motors of molecular size that typically exploit the energy of chemical fuels at ambient temperature to generate forces and ultimately execute functions. The progress in several areas of chemistry, together with an improved understanding of biomolecular machines, has led to the development of a large variety of wholly synthetic molecular machines. These systems have the potential to bring about radical innovations in several areas of technology and medicine. In this Minireview, we discuss, with the help of a few examples, the multidisciplinary aspects of research on artificial molecular machines and highlight its translational character.

Toxicological characterization of chemicals produced from laser irradiation of graphite composite materials

International Nuclear Information System (INIS)

Kwan, J.

1990-11-01

One of the major potential hazards associated with laser machining of graphite composite materials is the toxic fumes and gases that are generated. When exposed to the intense energy of the laser beam, the organic polymer matrix of the composite material may decompose into various toxic by-products. To advance the understanding of the laser machining process from a health and safety viewpoint, this particular study consisted of the following steps: collect and analyze gaseous by-products generated during laser machining; collect particulates generated during laser machining and chemically extract them to determine the chemical species that may have absorbed or recondensed onto these particles; and review and evaluate the toxicity of the identified chemical species

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Science.gov (United States)

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Directory of Open Access Journals (Sweden)

Christelle Reynès

2010-03-01

Full Text Available Protein-protein interactions (PPIs may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific. Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

Science.gov (United States)

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is

Effect of Heat Treatment on Machining Properties of the AlSi9Cu3(Fe Alloy

Directory of Open Access Journals (Sweden)

Wieroński P.

2016-09-01

Full Text Available Automation of machining operations, being result of mass volume production of components, imposes more restrictive requirements concerning mechanical properties of starting materials, inclusive of machinability mainly. In stage of preparation of material, the machinability is influenced by such factors as chemical composition, structure, mechanical properties, plastic working and heat treatment, as well as a factors present during machining operations, as machining type, cutting parameters, material and geometry of cutting tools, stiffness of the system: workpiece – machine tool – fixture and cutting tool.

Computational Approaches to Chemical Hazard Assessment

Science.gov (United States)

Luechtefeld, Thomas; Hartung, Thomas

2018-01-01

Summary Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models. PMID:29101769

Improvement of the thickness distribution of a quartz crystal wafer by numerically controlled plasma chemical vaporization machining

International Nuclear Information System (INIS)

Shibahara, Masafumi; Yamamura, Kazuya; Sano, Yasuhisa; Sugiyama, Tsuyoshi; Endo, Katsuyoshi; Mori, Yuzo

2005-01-01

To improve the thickness uniformity of thin quartz crystal wafer, a new machining process that utilizes an atmospheric pressure plasma was developed. In an atmospheric pressure plasma process, since the kinetic energy of ions that impinge to the wafer surface is small and the density of the reactive species is large, high-efficiency machining without damage is realized, and the thickness distribution is corrected by numerically controlled scanning of the quartz wafer to the localized high-density plasma. By using our developed machining process, the thickness distribution of an AT cut wafer was improved from 174 nm [peak to valley (p-v)] to 67 nm (p-v) within 94 s. Since there are no unwanted spurious modes in the machined quartz wafer, it was proved that the developed machining method has a high machining efficiency without any damage

Machine rates for selected forest harvesting machines

Science.gov (United States)

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

2002-01-01

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

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

Science.gov (United States)

Hrubiak, Rostislav; Sinogeikin, Stanislav; Rod, Eric; Shen, Guoyin

2015-07-01

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: amorphous 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.

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

International Nuclear Information System (INIS)

Hrubiak, Rostislav; Sinogeikin, Stanislav; Rod, Eric; Shen, Guoyin

2015-01-01

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: amorphous 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

ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

Science.gov (United States)

Kayala, Matthew A; Baldi, Pierre

2012-10-22

Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of Reaction

Finishing aeronautical planetary herringbone gear wheels in container vibrating smoothing machine

Directory of Open Access Journals (Sweden)

Jacek MICHALSKI

2015-12-01

Full Text Available The paper presents the technological process of abrasive-chemical machining wheel bearing surface of the cylindrical herringbone gears planetary gear in vibrating container smoothing machine according to Isotropic Finishing ISF® technology of the REM Chemicals Inc. company. Gear wheels are made of stainless Pyrowear 53 and subjected to carburizing, hardening, cold working and low tempering. The change in value of deviation indicators for the kinematic accuracy, smoothness and geometric structure of the machined surfaces of the gear teeth after smoothing compared with the contoured grinding were analyzed. The findings are different a characteristic performance on the surface of the tooth side along the outline, especially with a higher value at the head of the tooths. This creates a need for appropriate modification of the lateral surface of the teeth in the process of contoured grinding. The results of the mechanical strength of the samples gear wheel after the smoothing process and evaluating the hydrogen embrittlement are presented.

Improved detection of chemical substances from colorimetric sensor data using probabilistic machine learning

Science.gov (United States)

Mølgaard, Lasse L.; Buus, Ole T.; Larsen, Jan; Babamoradi, Hamid; Thygesen, Ida L.; Laustsen, Milan; Munk, Jens Kristian; Dossi, Eleftheria; O'Keeffe, Caroline; Lässig, Lina; Tatlow, Sol; Sandström, Lars; Jakobsen, Mogens H.

2017-05-01

We present a data-driven machine learning approach to detect drug- and explosives-precursors using colorimetric sensor technology for air-sampling. The sensing technology has been developed in the context of the CRIM-TRACK project. At present a fully- integrated portable prototype for air sampling with disposable sensing chips and automated data acquisition has been developed. The prototype allows for fast, user-friendly sampling, which has made it possible to produce large datasets of colorimetric data for different target analytes in laboratory and simulated real-world application scenarios. To make use of the highly multi-variate data produced from the colorimetric chip a number of machine learning techniques are employed to provide reliable classification of target analytes from confounders found in the air streams. We demonstrate that a data-driven machine learning method using dimensionality reduction in combination with a probabilistic classifier makes it possible to produce informative features and a high detection rate of analytes. Furthermore, the probabilistic machine learning approach provides a means of automatically identifying unreliable measurements that could produce false predictions. The robustness of the colorimetric sensor has been evaluated in a series of experiments focusing on the amphetamine pre-cursor phenylacetone as well as the improvised explosives pre-cursor hydrogen peroxide. The analysis demonstrates that the system is able to detect analytes in clean air and mixed with substances that occur naturally in real-world sampling scenarios. The technology under development in CRIM-TRACK has the potential as an effective tool to control trafficking of illegal drugs, explosive detection, or in other law enforcement applications.

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

Science.gov (United States)

Iwasaki, N

2001-06-01

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

RNA interference and Register Machines (extended abstract

Directory of Open Access Journals (Sweden)

Masahiro Hamano

2012-11-01

Full Text Available RNA interference (RNAi is a mechanism whereby small RNAs (siRNAs directly control gene expression without assistance from proteins. This mechanism consists of interactions between RNAs and small RNAs both of which may be single or double stranded. The target of the mechanism is mRNA to be degraded or aberrated, while the initiator is double stranded RNA (dsRNA to be cleaved into siRNAs. Observing the digital nature of RNAi, we represent RNAi as a Minsky register machine such that (i The two registers hold single and double stranded RNAs respectively, and (ii Machine's instructions are interpreted by interactions of enzyme (Dicer, siRNA (with RISC com- plex and polymerization (RdRp to the appropriate registers. Interpreting RNAi as a computational structure, we can investigate the computational meaning of RNAi, especially its complexity. Initially, the machine is configured as a Chemical Ground Form (CGF, which generates incorrect jumps. To remedy this problem, the system is remodeled as recursive RNAi, in which siRNA targets not only mRNA but also the machine instructional analogues of Dicer and RISC. Finally, probabilistic termination is investigated in the recursive RNAi system.

The Machine within the Machine

CERN Multimedia

Katarina Anthony

2014-01-01

Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

Low temperature wetting and cleanup of alkali metal-advanced electrical machine systems

International Nuclear Information System (INIS)

Gass, W.R.; Witkowski, R.E.; Burrow, G.C.

1980-01-01

Advanced homopolar electrical machines employing high electrical current density, liquid metal sliprings for current transfer utilize NaK/sub 78/ (78 w/o potassium, 22 w/o sodium) for the conducting fluid. Experiments have been performed to improve alkali metal/oxide clean-up procedures. Studies have also confirmed chemical and materials compatibility between barium doped NaK/sub 78/ and typical machine structural materials. 4 refs

Electro-chemical grinding

Science.gov (United States)

Feagans, P. L.

1972-01-01

Electro-chemical grinding technique has rotation speed control, constant feed rates, and contour control. Hypersonic engine parts of nickel alloys can be almost 100% machined, keeping tool pressure at virtual zero. Technique eliminates galling and permits constant surface finish and burr-free interrupted cutting.

High speed dry machining of MMCs with diamond tools

International Nuclear Information System (INIS)

Collins, J.L.

2001-01-01

The increasing use of metal matrix composites (MMCs) has raised new issues in their machining. Industrial demands for higher speed and dry machining of MMCs with improved component production to closer tolerances have driven the development of new tool materials. In particular, the wear characteristics of synthetic diamond tooling satisfy many of the requirements imposed in cutting these highly abrasive workpieces. The use of diamond tool materials, such as polycrystalline diamond (PCD), has resulted in tool life improvements which, allied with environmental considerations, show great potential for the development of dry cutting. This paper explores the wear characteristics of PCD, which is highly suited to the dry machining of particulate silicon carbide MMCs. Also, two further diamond tool materials are evaluated - chemical vapor deposition (CVD) thick layer diamond and synthetic single crystal diamond. Their suitability for the efficient machining of high volume fraction MMC materials is shown and their potential impact an the subsequent acceptance and integration of MMCs into engineering components is discussed. (author)

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

Inverse Problems in Geodynamics Using Machine Learning Algorithms

Science.gov (United States)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R. N.

2018-01-01

During the past few decades numerical studies have been widely employed to explore the style of circulation and mixing in the mantle of Earth and other planets. However, in geodynamical studies there are many properties from mineral physics, geochemistry, and petrology in these numerical models. Machine learning, as a computational statistic-related technique and a subfield of artificial intelligence, has rapidly emerged recently in many fields of sciences and engineering. We focus here on the application of supervised machine learning (SML) algorithms in predictions of mantle flow processes. Specifically, we emphasize on estimating mantle properties by employing machine learning techniques in solving an inverse problem. Using snapshots of numerical convection models as training samples, we enable machine learning models to determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at midmantle depths. Employing support vector machine algorithms, we show that SML techniques can successfully predict the magnitude of mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex geodynamic problems in mantle dynamics by employing deep learning algorithms for putting constraints on properties such as viscosity, elastic parameters, and the nature of thermal and chemical anomalies.

Characterization of thermoset and thermoplastic polyurethane pads, and molded and non-optimized machined grooving methods for oxide chemical mechanical planarization applications

International Nuclear Information System (INIS)

Sampurno, Yasa; Borucki, Leonard; Zhuang, Yun; Misra, Sudhanshu; Holland, Karey; Boning, Duane; Philipossian, Ara

2009-01-01

This paper systematically studies the effect of pad material, grooving method and grooving pattern on interlayer dielectric chemical mechanical planarization. The tested polishing pads consist of thermoplastic and thermoset polyurethanes synthesized using two different processes. Grooves created using a molding technique are compared with grooves formed by mechanical cutting. The concentric groove design is also compared with the logarithmic positive spiral positive grooving design. Experimental data collected include removal rate, coefficient of friction, shear force variance, pad temperature and dynamic mechanical analyzer measurements. Scanning electron microscope images are used to correlate grooving methods with coefficient of friction and shear force variance measurements. Results show that all of the pads polish wafers in boundary lubrication mode with unique friction coefficient, shear force variance and pad temperature characteristics. Simulations using a two-step removal rate mechanism are performed to estimate the chemical and mechanical rate constants. The analysis indicates that the thermoplastic pad is more mechanically controlled than the thermoset pad and that molded grooving induces a more mechanically controlled process than non-optimized machined grooving

Improved fabrication of HgI2 nuclear radiation detectors by machine-cleaving

International Nuclear Information System (INIS)

Levi, A.; Burger, A.; Schieber, M.; Vandenberg, L.; Yellon, W.B.; Alkire, R.W.

1982-01-01

The perfection of machine-cleaved sections from HgI 2 bulk crystals was examined. The perfection of the machine-cleaved sections as established by gamma diffraction rocking curves was found to be much better than the perfection of hand-cleaved sections or as grown thin platelets, reaching a perfection similar to that of the wire-sawn sections of HgI 2 . A correlation between the perfection and the thickness of the machine-cleaved section was also found, i.e., the thicker the cleaved-section the more perfect it is. The reproducibility of the fabrication was significantly improved by using machine cleaving in the process of fabrication. Large single crystals of HgI 2 weighing 20 to 200 g, can be grown from the vapor phase using the TOM Technique. In order to fabricate nuclear radiation detectors from these single crystals, thin sections of about 0.4 to 0.8 mm thickness have to be prepared. Up till now, the state-of-the-art of fabricating HgI 2 nuclear radiation detectors involved two methods to get thin sections from the large single crystals: (1) hand-cleaving using a razor-blade and (2) solution wire sawing. The chemical wire sawing method involves a loss of about 50% of the crystal volume and is usually followed by a chemical polishing process which involves a significant loss of volume of the original volume. This procedure is complicated and wasteful. The traditional fabrication method, i.e., hand-cleaving followed by rapid nonselective chemical etching, is simpler and less wasteful

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Prediction of Chemical Function: Model Development and ...

Science.gov (United States)

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Sample preparation of metal alloys by electric discharge machining

Science.gov (United States)

Chapman, G. B., II; Gordon, W. A.

1976-01-01

Electric discharge machining was investigated as a noncontaminating method of comminuting alloys for subsequent chemical analysis. Particulate dispersions in water were produced from bulk alloys at a rate of about 5 mg/min by using a commercially available machining instrument. The utility of this approach was demonstrated by results obtained when acidified dispersions were substituted for true acid solutions in an established spectrochemical method. The analysis results were not significantly different for the two sample forms. Particle size measurements and preliminary results from other spectrochemical methods which require direct aspiration of liquid into flame or plasma sources are reported.

Environmentally Friendly Machining

CERN Document Server

Dixit, U S; Davim, J Paulo

2012-01-01

Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

Micro-machined resonator oscillator

Science.gov (United States)

Koehler, Dale R.; Sniegowski, Jeffry J.; Bivens, Hugh M.; Wessendorf, Kurt O.

1994-01-01

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a "telemetered sensor beacon" that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20-100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available.

Classification of carcinogenic and mutagenic properties using machine learning method

DEFF Research Database (Denmark)

Moorthy, N. S.Hari Narayana; Kumar, Surendra; Poongavanam, Vasanthanathan

2017-01-01

An accurate calculation of carcinogenicity of chemicals became a serious challenge for the health assessment authority around the globe because of not only increased cost for experiments but also various ethical issues exist using animal models. In this study, we provide machine learning...

Catalysis of heat-to-work conversion in quantum machines

Science.gov (United States)

Ghosh, A.; Latune, C. L.; Davidovich, L.; Kurizki, G.

2017-11-01

We propose a hitherto-unexplored concept in quantum thermodynamics: catalysis of heat-to-work conversion by quantum nonlinear pumping of the piston mode which extracts work from the machine. This concept is analogous to chemical reaction catalysis: Small energy investment by the catalyst (pump) may yield a large increase in heat-to-work conversion. Since it is powered by thermal baths, the catalyzed machine adheres to the Carnot bound, but may strongly enhance its efficiency and power compared with its noncatalyzed counterparts. This enhancement stems from the increased ability of the squeezed piston to store work. Remarkably, the fraction of piston energy that is convertible into work may then approach unity. The present machine and its counterparts powered by squeezed baths share a common feature: Neither is a genuine heat engine. However, a squeezed pump that catalyzes heat-to-work conversion by small investment of work is much more advantageous than a squeezed bath that simply transduces part of the work invested in its squeezing into work performed by the machine.

Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?

Science.gov (United States)

Lee, Ernest Y; Lee, Michelle W; Fulan, Benjamin M; Ferguson, Andrew L; Wong, Gerard C L

2017-12-06

Antimicrobial peptides (AMPs) are a diverse class of well-studied membrane-permeating peptides with important functions in innate host defense. In this short review, we provide a historical overview of AMPs, summarize previous applications of machine learning to AMPs, and discuss the results of our studies in the context of the latest AMP literature. Much work has been recently done in leveraging computational tools to design new AMP candidates with high therapeutic efficacies for drug-resistant infections. We show that machine learning on AMPs can be used to identify essential physico-chemical determinants of AMP functionality, and identify and design peptide sequences to generate membrane curvature. In a broader scope, we discuss the implications of our findings for the discovery of membrane-active peptides in general, and uncovering membrane activity in new and existing peptide taxonomies.

Abbreviated machining schedule for fabricating beryllium parts free of surface damage

International Nuclear Information System (INIS)

Beitscher, S.; Capes, J.F.; Leslie, W.W.; Luckow, J.R.; Riegel, R.L.

1979-01-01

This study was performed to develop a more economical method of machining damage-free beryllium components at Rocky Flats. The present method involves a 9-pass schedule of lathe turning followed by a chemical etch. Prototype beryllium hemispherical shell parts and cylindrical tensile specimens machined to simulate the parts were utilized in this study. The main investigative methods used to evaluate the amount of machining damage were metallography and tensile tests. It was found that damage-free parts could be produced by carefully controlled machining if the number of machining passes was reduced to 4 or even 3, if followed by the standard etching treatment. These findings were made on Select S-65 grade beryllium, and probably apply to other common grades of powder source beryllium but not necessarily to ingot-source beryllium. It is recommended that the 4-pass schedule becomes the standard method to produce damage-free beryllium derived from powder. Significant savings in time, labor, and equipment can be realized by this change in method without decreasing the quality of the product

Construction technique for a chemical plant (I)

International Nuclear Information System (INIS)

1978-08-01

This book mentions the order of plant construction, building plant and related regulations, basic engineering design data, provide of equipment, plan and management on building plant, quality control, the budget and contract for building plant, public works for building chemical plant like road construction, basic plan and building for a chemical plant, introduction and principle on foundation improvement method, including pile foundation and design for footing, construction and installation for a chemical plant and a rotary machine for a chemical plant.

Tritium decontamination of machine components and walls

International Nuclear Information System (INIS)

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

1991-01-01

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

A Grid-Based Cyber Infrastructure for High Performance Chemical Dynamics Simulations

Directory of Open Access Journals (Sweden)

Khadka Prashant

2008-10-01

Full Text Available Chemical dynamics simulation is an effective means to study atomic level motions of molecules, collections of molecules, liquids, surfaces, interfaces of materials, and chemical reactions. To make chemical dynamics simulations globally accessible to a broad range of users, recently a cyber infrastructure was developed that provides an online portal to VENUS, a popular chemical dynamics simulation program package, to allow people to submit simulation jobs that will be executed on the web server machine. In this paper, we report new developments of the cyber infrastructure for the improvement of its quality of service by dispatching the submitted simulations jobs from the web server machine onto a cluster of workstations for execution, and by adding an animation tool, which is optimized for animating the simulation results. The separation of the server machine from the simulation-running machine improves the service quality by increasing the capacity to serve more requests simultaneously with even reduced web response time, and allows the execution of large scale, time-consuming simulation jobs on the powerful workstation cluster. With the addition of an animation tool, the cyber infrastructure automatically converts, upon the selection of the user, some simulation results into an animation file that can be viewed on usual web browsers without requiring installation of any special software on the user computer. Since animation is essential for understanding the results of chemical dynamics simulations, this animation capacity provides a better way for understanding simulation details of the chemical dynamics. By combining computing resources at locations under different administrative controls, this cyber infrastructure constitutes a grid environment providing physically and administratively distributed functionalities through a single easy-to-use online portal

Machine terms dictionary

Energy Technology Data Exchange (ETDEWEB)

NONE

1979-04-15

This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

Review: Physical, physical chemistries, chemical and sensorial characteristics of the several fruits and vegetables chips by low-temperature vacuum frying machine

Directory of Open Access Journals (Sweden)

AHMAD DWI SETYAWAN

2013-11-01

Full Text Available Setyawan AD, Sugiyarto, Solichatun, Susilowati A. 2013. Review: Physical, physical chemistries, chemical and sensorial characteristics of the several fruits and vegetables chips by low-temperature vacuum frying machine. Nusantara Bioscience 5: 84-100. Frying process is one of the oldest cooking methods and most widely practiced in the world. Frying process is considered as a dry cooking method because the process does not involve water. In frying process, oil conduction occurs at high temperature pressing water out of food in the form of bubbles. Fried foods last longer due to reduced water levels lead less decomposition by microbes, even fried foods can be enhanced nutritional value and quality of appearance. Food frying technology can extend the shelf life of fruits and vegetables and frying oil enhances the flavors of the products, however, improper frying oil can have harmful effects on human health. Vacuum frying is a promising technology that may be an option for the production of novel snacks such as fruit and vegetable crisps that present the desired quality and respond to new health trends. This technique fry food at a low temperature and pressure so that the nutritional quality of the food is maintained and the quality of the used oil does not quickly declined and became saturated oils that are harmful to human health. This technique produces chips that have physical, physico-chemical, chemical, and sensory generally better than conventional deep-fat frying methods.

Molecular active plasmonics: controlling plasmon resonances with molecular machines

KAUST Repository

Zheng, Yue Bing

2009-08-26

The paper studies the molecular-level active control of localized surface plasmon resonances (LSPRs) of Au nanodisk arrays with molecular machines. Two types of molecular machines - azobenzene and rotaxane - have been demonstrated to enable the reversible tuning of the LSPRs via the controlled mechanical movements. Azobenzene molecules have the property of trans-cis photoisomerization and enable the photo-induced nematic (N)-isotropic (I) phase transition of the liquid crystals (LCs) that contain the molecules as dopant. The phase transition of the azobenzene-doped LCs causes the refractive-index difference of the LCs, resulting in the reversible peak shift of the LSPRs of the embedded Au nanodisks due to the sensitivity of the LSPRs to the disks\\' surroundings\\' refractive index. Au nanodisk array, coated with rotaxanes, switches its LSPRs reversibly when it is exposed to chemical oxidants and reductants alternatively. The correlation between the peak shift of the LSPRs and the chemically driven mechanical movement of rotaxanes is supported by control experiments and a time-dependent density functional theory (TDDFT)-based, microscopic model.

Adsorbent cartridge for the exhaust of diazo process machines

International Nuclear Information System (INIS)

Michlin, N.; Thies, E.J.

1982-01-01

A disposable cartridge filled with a chemical composition that acts as an adsorbent for ammonia vapor is adapted to be used in connection with a diazo process printing machine having a vacuum exhausted chamber. Exhaust from the chamber is passed through the cartridge to remove the noxious ammonia vapors and then is vented into the atmosphere. The cartridge is housed in an elongated rectangular cardboard box having three end flaps formed at each of its opposed open ends. Two opposed flaps of each set are formed with central holes and a plastic screen section adhered between these flaps to retain and allow access to the center section of the box which contains the adsorbent chemical. The center end flaps have knock-outs or tear strips that allow holes to be formed in their centers. These center end flaps cover the screens during shipment and when the cartridge is ready for use the center sections of these end flaps are knocked-out to allow the machine exhaust to be vented into and out of the cartridge

Molecular active plasmonics: controlling plasmon resonances with molecular machines

KAUST Repository

Zheng, Yue Bing; Yang, Ying-Wei; Jensen, Lasse; Fang, Lei; Juluri, Bala Krishna; Flood, Amar H.; Weiss, Paul S.; Stoddart, J. Fraser; Huang, Tony Jun

2009-01-01

The paper studies the molecular-level active control of localized surface plasmon resonances (LSPRs) of Au nanodisk arrays with molecular machines. Two types of molecular machines - azobenzene and rotaxane - have been demonstrated to enable the reversible tuning of the LSPRs via the controlled mechanical movements. Azobenzene molecules have the property of trans-cis photoisomerization and enable the photo-induced nematic (N)-isotropic (I) phase transition of the liquid crystals (LCs) that contain the molecules as dopant. The phase transition of the azobenzene-doped LCs causes the refractive-index difference of the LCs, resulting in the reversible peak shift of the LSPRs of the embedded Au nanodisks due to the sensitivity of the LSPRs to the disks' surroundings' refractive index. Au nanodisk array, coated with rotaxanes, switches its LSPRs reversibly when it is exposed to chemical oxidants and reductants alternatively. The correlation between the peak shift of the LSPRs and the chemically driven mechanical movement of rotaxanes is supported by control experiments and a time-dependent density functional theory (TDDFT)-based, microscopic model.

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

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.

“Investigations on the machinability of Waspaloy under dry environment”

Science.gov (United States)

Deepu, J.; Kuppan, P.; SBalan, A. S.; Oyyaravelu, R.

2016-09-01

Nickel based superalloy, Waspaloy is extensively used in gas turbine, aerospace and automobile industries because of their unique combination of properties like high strength at elevated temperatures, resistance to chemical degradation and excellent wear resistance in many hostile environments. It is considered as one of the difficult to machine superalloy due to excessive tool wear and poor surface finish. The present paper is an attempt for removing cutting fluids from turning process of Waspaloy and to make the processes environmentally safe. For this purpose, the effect of machining parameters such as cutting speed and feed rate on the cutting force, cutting temperature, surface finish and tool wear were investigated barrier. Consequently, the strength and tool wear resistance and tool life increased significantly. Response Surface Methodology (RSM) has been used for developing and analyzing a mathematical model which describes the relationship between machining parameters and output variables. Subsequently ANOVA was used to check the adequacy of the regression model as well as each machining variables. The optimal cutting parameters were determined based on multi-response optimizations by composite desirability approach in order to minimize cutting force, average surface roughness and maximum flank wear. The results obtained from the experiments shown that machining of Waspaloy using coated carbide tool with special ranges of parameters, cutting fluid could be completely removed from machining process

A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys

Energy Technology Data Exchange (ETDEWEB)

Kumar, Sanjeev; Batish, Ajay [Thapar University, Patiala (India); Singh, Rupinder [GNDEC, Ludhiana (India); Singh, T. P. [Symbiosis Institute of Technology, Pune (India)

2014-07-15

In the present study, electric discharge machining process was used for machining of titanium alloys. Eight process parameters were varied during the process. Experimental results showed that current and pulse-on-time significantly affected the performance characteristics. Artificial neural network coupled with Taguchi approach was applied for optimization and prediction of surface roughness. The experimental results and the predicted results showed good agreement. SEM was used to investigate the surface integrity. Analysis for migration of different chemical elements and formation of compounds on the surface was performed using EDS and XRD pattern. The results showed that high discharge energy caused surface defects such as cracks, craters, thick recast layer, micro pores, pin holes, residual stresses and debris. Also, migration of chemical elements both from electrode and dielectric media were observed during EDS analysis. Presence of carbon was seen on the machined surface. XRD results showed formation of titanium carbide compound which precipitated on the machined surface.

The Basics of Stellites in Machining Perspective

Directory of Open Access Journals (Sweden)

Md Shahanur Hasan

2016-12-01

Full Text Available Stellites are cobalt (Co-based superalloys available in two main combinations: (a a Tungsten (W group with composition of Co-Cr-W-C, and (b a Molybdenum (Mo group containing Co-Cr-Mo-C. Stellites possess outstanding corrosion resistance, oxidation resistance, wear resistance, heat resistance, and low magnetic permeability. Components made of stellites work well in highly corrosive environments and maintain these advantageous properties at elevated temperatures. Components made of stellites are widely used in the oil and gas, automotive, nuclear power, paper and pulp, chemical and petrochemical, refineries, automobile, aerospace and aircraft industries. By virtue of their nonmagnetic, anticorrosive and non-reactivity to human body-fluid properties, stellites are used in medical surgery and in surgical tools, tooth and bone implants and replacements, heart valves, and in heart pacemakers. The hardness range of stellites is from 32 to 55 HRC, which makes stellites brittle materials but they have a low Young’s modulus. Due to their high hardness, dense but non-homogeneous molecular structure and lower thermal conductivity, machining operations for parts made of stellites are extremely difficult, categorising stellites as difficult-to-machine materials like Ti-alloys, inconels, composites and stainless steels. Usually, machine components made of stellites are produced by a deposition method onto steel substrates instead of expensive solid stellite bars. The rough surfaces of deposited stellites are then finished by grinding, rather than some other economic machining process, which is costly and time-consuming, making stellite products very expensive. This paper provides a basic overview of stellites applicable in engineering, their significances and specific applications, advantages and disadvantages in respect of machining processes. A brief review on experimental research on economically rational cutting parameters for turning operations of

Machine learning algorithms for mode-of-action classification in toxicity assessment.

Science.gov (United States)

Zhang, Yile; Wong, Yau Shu; Deng, Jian; Anton, Cristina; Gabos, Stephan; Zhang, Weiping; Huang, Dorothy Yu; Jin, Can

2016-01-01

Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probing the mode of action (MOA) of the testing substances. In this paper, we present machine learning approaches for MOA assessment. Computational tools based on artificial neural network (ANN) and support vector machine (SVM) are developed to analyze the time-concentration response curves (TCRCs) of human cell lines responding to tested chemicals. The techniques are capable of learning data from given TCRCs with known MOA information and then making MOA classification for the unknown toxicity. A novel data processing step based on wavelet transform is introduced to extract important features from the original TCRC data. From the dose response curves, time interval leading to higher classification success rate can be selected as input to enhance the performance of the machine learning algorithm. This is particularly helpful when handling cases with limited and imbalanced data. The validation of the proposed method is demonstrated by the supervised learning algorithm applied to the exposure data of HepG2 cell line to 63 chemicals with 11 concentrations in each test case. Classification success rate in the range of 85 to 95 % are obtained using SVM for MOA classification with two clusters to cases up to four clusters. Wavelet transform is capable of capturing important features of TCRCs for MOA classification. The proposed SVM scheme incorporated with wavelet transform has a great potential for large scale MOA classification and high-through output chemical screening.

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

Machine tool structures

CERN Document Server

Koenigsberger, F

1970-01-01

Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

Electricity of machine tool

International Nuclear Information System (INIS)

Gijeon media editorial department

1977-10-01

This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

Machine medical ethics

CERN Document Server

Pontier, Matthijs

2015-01-01

The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

Toxicity challenges in environmental chemicals: Prediction of ...

Science.gov (United States)

Physiologically based pharmacokinetic (PBPK) models bridge the gap between in vitro assays and in vivo effects by accounting for the adsorption, distribution, metabolism, and excretion of xenobiotics, which is especially useful in the assessment of human toxicity. Quantitative structure-activity relationships (QSAR) serve as a vital tool for the high-throughput prediction of chemical-specific PBPK parameters, such as the fraction of a chemical unbound by plasma protein (Fub). The presented work explores the merit of utilizing experimental pharmaceutical Fub data for the construction of a universal QSAR model, in order to compensate for the limited range of high-quality experimental Fub data for environmentally relevant chemicals, such as pollutants, pesticides, and consumer products. Independent QSAR models were constructed with three machine-learning algorithms, k nearest neighbors (kNN), random forest (RF), and support vector machine (SVM) regression, from a large pharmaceutical training set (~1000) and assessed with independent test sets of pharmaceuticals (~200) and environmentally relevant chemicals in the ToxCast program (~400). Small descriptor sets yielded the optimal balance of model complexity and performance, providing insight into the biochemical factors of plasma protein binding, while preventing over fitting to the training set. Overlaps in chemical space between pharmaceutical and environmental compounds were considered through applicability of do

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

Evaluation of the Technical-Economic Potential of Particle- Reinforced Aluminum Matrix Composites and Electrochemical Machining

International Nuclear Information System (INIS)

Schubert, A; Hackert-Oschätzchen, M; Lehnert, N; Götze, U; Herold, F; Schmidt, A; Meichsner, G

2016-01-01

Compared to conventional cutting, the processing of materials by electrochemical machining offers some technical advantages like high surface quality, no thermal or mechanical impact on the work piece and preservation of the microstructure of the work piece material. From the economic point of view, the possibility of process parallelization and the absence of any process-related tool wear are mentionable advantages of electrochemical machining. In this study, based on experimental results, it will be evaluated to what extent the electrochemical machining is technically and economically suitable for the finish-machining of particle- reinforced aluminum matrix composites (AMCs). Initial studies showed that electrochemical machining - in contrast to other machining processes - has the potential to fulfil demanding requirements regarding precision and surface quality of products or components especially when applied to AMCs. In addition, the investigations show that processing of AMCs by electrochemical machining requires less energy than the electrochemical machining of stainless steel. Therefore, an evaluation of electrochemically machined AMCs - compared to stainless steel - from a technical and an economic perspective will be presented in this paper. The results show the potential of electro-chemically machined AMCs and contribute to the enhancement of instruments for technical-economic evaluations as well as a comprehensive innovation control. (paper)

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

Science.gov (United States)

Bereau, Tristan; DiStasio, Robert A.; Tkatchenko, Alexandre; von Lilienfeld, O. Anatole

2018-06-01

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

Science.gov (United States)

Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole

2015-05-12

Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.

Code-expanded radio access protocol for machine-to-machine communications

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

Operation of micro and molecular machines: a new concept with its origins in interface science.

Science.gov (United States)

Ariga, Katsuhiko; Ishihara, Shinsuke; Izawa, Hironori; Xia, Hong; Hill, Jonathan P

2011-03-21

A landmark accomplishment of nanotechnology would be successful fabrication of ultrasmall machines that can work like tweezers, motors, or even computing devices. Now we must consider how operation of micro- and molecular machines might be implemented for a wide range of applications. If these machines function only under limited conditions and/or require specialized apparatus then they are useless for practical applications. Therefore, it is important to carefully consider the access of functionality of the molecular or nanoscale systems by conventional stimuli at the macroscopic level. In this perspective, we will outline the position of micro- and molecular machines in current science and technology. Most of these machines are operated by light irradiation, application of electrical or magnetic fields, chemical reactions, and thermal fluctuations, which cannot always be applied in remote machine operation. We also propose strategies for molecular machine operation using the most conventional of stimuli, that of macroscopic mechanical force, achieved through mechanical operation of molecular machines located at an air-water interface. The crucial roles of the characteristics of an interfacial environment, i.e. connection between macroscopic dimension and nanoscopic function, and contact of media with different dielectric natures, are also described.

Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

Science.gov (United States)

Wu, Jingheng; Shen, Lin; Yang, Weitao

2017-10-28

Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

Simple machines

CERN Document Server

Graybill, George

2007-01-01

Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

1998-03-19

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

Superconducting rotating machines

International Nuclear Information System (INIS)

Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

1975-01-01

The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

Sustainable machining

CERN Document Server

2017-01-01

This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

Directory of Open Access Journals (Sweden)

Ming Cheng

2015-09-01

Full Text Available The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs. Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG. Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

Machine Shop Lathes.

Science.gov (United States)

Dunn, James

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

Advancing Consumer Product Composition and Chemical ...

Science.gov (United States)

This presentation describes EPA efforts to collect, model, and measure publically available consumer product data for use in exposure assessment. The development of the ORD Chemicals and Products database will be described, as will machine-learning based models for predicting chemical function. Finally, the talk describes new mass spectrometry-based methods for measuring chemicals in formulation and articles. This presentation is an invited talk to the ICCA-LRI workshop "Fit-For-Purpose Exposure Assessments For Risk-Based Decision Making". The talk will share EPA efforts to characterize the components of consumer products for use in exposure assessment with the international exposure science community.

The machinability of nickel-based alloys in high-pressure jet assisted (HPJA turning

Directory of Open Access Journals (Sweden)

D. Kramar

2013-10-01

Full Text Available Due to their mechanical, thermal and chemical properties, nickel-based alloys are generally included among materials that are hard to machine. An experimental study has been performed to investigate the capabilities of conventional and high-pressure jet assisted (HPJA turning of hard-to-machine materials, namely Inconel 718. The capabilities of different hard turning procedures are compared by means of chip breakability. The obtained results show that HPJA method offers a significant increase in chip breakability, under the same cutting conditions (cutting speed, feed rate, depth of cut.

Designing anticancer peptides by constructive machine learning.

Science.gov (United States)

Grisoni, Francesca; Neuhaus, Claudia; Gabernet, Gisela; Müller, Alex; Hiss, Jan; Schneider, Gisbert

2018-04-21

Constructive machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a generative model to design membranolytic anticancer peptides (ACPs) de novo. A recurrent neural network with long short-term memory cells was trained on alpha-helical cationic amphipathic peptide sequences and then fine-tuned with 26 known ACPs. This optimized model was used to generate unique and novel amino acid sequences. Twelve of the peptides were synthesized and tested for their activity on MCF7 human breast adenocarcinoma cells and selectivity against human erythrocytes. Ten of these peptides were active against cancer cells. Six of the active peptides killed MCF7 cancer cells without affecting human erythrocytes with at least threefold selectivity. These results advocate constructive machine learning for the automated design of peptides with desired biological activities. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals.

Science.gov (United States)

Pereira, Florbela; Xiao, Kaixia; Latino, Diogo A R S; Wu, Chengcheng; Zhang, Qingyou; Aires-de-Sousa, Joao

2017-01-23

Machine learning algorithms were explored for the fast estimation of HOMO and LUMO orbital energies calculated by DFT B3LYP, on the basis of molecular descriptors exclusively based on connectivity. The whole project involved the retrieval and generation of molecular structures, quantum chemical calculations for a database with >111 000 structures, development of new molecular descriptors, and training/validation of machine learning models. Several machine learning algorithms were screened, and an applicability domain was defined based on Euclidean distances to the training set. Random forest models predicted an external test set of 9989 compounds achieving mean absolute error (MAE) up to 0.15 and 0.16 eV for the HOMO and LUMO orbitals, respectively. The impact of the quantum chemical calculation protocol was assessed with a subset of compounds. Inclusion of the orbital energy calculated by PM7 as an additional descriptor significantly improved the quality of estimations (reducing the MAE in >30%).

Structural and Conformational Chemistry from Electrochemical Molecular Machines. Replicating Biological Functions. A Review.

Science.gov (United States)

Otero, Toribio F

2017-12-14

Each constitutive chain of a conducting polymer electrode acts as a reversible multi-step electrochemical molecular motor: reversible reactions drive reversible conformational movements of the chain. The reaction-driven cooperative actuation of those molecular machines generates, or destroys, inside the film the free volume required to lodge/expel balancing counterions and solvent: reactions drive reversible film volume variations, which basic structural components are here identified and quantified from electrochemical responses. The content of the reactive dense gel (chemical molecular machines, ions and water) mimics that of the intracellular matrix in living functional cells. Reaction-driven properties (composition-dependent properties) and devices replicate biological functions and organs. An emerging technological world of soft, wet, reaction-driven, multifunctional and biomimetic devices and the concomitant zoomorphic or anthropomorphic robots is presented. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Quantum machine learning.

Science.gov (United States)

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.

Machine protection systems

CERN Document Server

Macpherson, A L

2010-01-01

A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

An artificial molecular machine that builds an asymmetric catalyst

Science.gov (United States)

De Bo, Guillaume; Gall, Malcolm A. Y.; Kuschel, Sonja; De Winter, Julien; Gerbaux, Pascal; Leigh, David A.

2018-05-01

Biomolecular machines perform types of complex molecular-level tasks that artificial molecular machines can aspire to. The ribosome, for example, translates information from the polymer track it traverses (messenger RNA) to the new polymer it constructs (a polypeptide)1. The sequence and number of codons read determines the sequence and number of building blocks incorporated into the biomachine-synthesized polymer. However, neither control of sequence2,3 nor the transfer of length information from one polymer to another (which to date has only been accomplished in man-made systems through template synthesis)4 is easily achieved in the synthesis of artificial macromolecules. Rotaxane-based molecular machines5-7 have been developed that successively add amino acids8-10 (including β-amino acids10) to a growing peptide chain by the action of a macrocycle moving along a mono-dispersed oligomeric track derivatized with amino-acid phenol esters. The threaded macrocycle picks up groups that block its path and links them through successive native chemical ligation reactions11 to form a peptide sequence corresponding to the order of the building blocks on the track. Here, we show that as an alternative to translating sequence information, a rotaxane molecular machine can transfer the narrow polydispersity of a leucine-ester-derivatized polystyrene chain synthesized by atom transfer radical polymerization12 to a molecular-machine-made homo-leucine oligomer. The resulting narrow-molecular-weight oligomer folds to an α-helical secondary structure13 that acts as an asymmetric catalyst for the Juliá-Colonna epoxidation14,15 of chalcones.

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

Study of on-machine error identification and compensation methods for micro machine tools

International Nuclear Information System (INIS)

Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

2016-01-01

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

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

Science.gov (United States)

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

2015-11-01

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

A scalable machine-learning approach to recognize chemical names within large text databases

Directory of Open Access Journals (Sweden)

Wren Jonathan D

2006-09-01

Full Text Available Abstract Motivation The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database curation, report summarization, tagging of named entities and keywords, or the development/curation of reference databases. Results A first-order Markov Model (MM was evaluated for its ability to distinguish chemical names from words, yielding ~93% recall in recognizing chemical terms and ~99% precision in rejecting non-chemical terms on smaller test sets. However, because total false-positive events increase with the number of words analyzed, the scalability of name recognition was measured by processing 13.1 million MEDLINE records. The method yielded precision ranges from 54.7% to 100%, depending upon the cutoff score used, averaging 82.7% for approximately 1.05 million putative chemical terms extracted. Extracted chemical terms were analyzed to estimate the number of spelling variants per term, which correlated with the total number of times the chemical name appeared in MEDLINE. This variability in term construction was found to affect both information retrieval and term mapping when using PubMed and Ovid.

Non-conventional electrical machines

CERN Document Server

Rezzoug, Abderrezak

2013-01-01

The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

Effect of surface machining on corrosion behavior of SA182-304 in simulated

International Nuclear Information System (INIS)

Zhang Zhiming; Wang Jianqiu; Han Enhou; Ke Wei

2015-01-01

Different machining processes of mechanical parts can cause surface damage layers with different levels. The surface deformed layer can affect the corrosion behavior and service life of these mechanical parts a lot during the following service process. As a result, it is a key issue for the fabrication of the mechanical parts with long life that the selection of proper machining parameters and the removal of surface damage. The purpose of this study is to study the influence of different turning parameters on the corrosion behavior of nuclear grade SA182-304 stainless steel widely used in the advanced pressured water reactors (PWRs). 6 kinds of samples with different surface state are prepared by a lathe with different machining parameters, such as the feed, cutting speed and back engagement of the cutting edge. The high temperature and high pressure immersion test of these samples in the simulated PWR primary watershows that machining processes can affect the microstructure and chemical composition of the formed surface oxide scales a lot. According to the experimental results, the proper machining parameters for the studied SA182-304 are suggested. (authors)

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

Surface structuring of boron doped CVD diamond by micro electrical discharge machining

Science.gov (United States)

Schubert, A.; Berger, T.; Martin, A.; Hackert-Oschätzchen, M.; Treffkorn, N.; Kühn, R.

2018-05-01

Boron doped diamond materials, which are generated by Chemical Vapor Deposition (CVD), offer a great potential for the application on highly stressed tools, e. g. in cutting or forming processes. As a result of the CVD process rough surfaces arise, which require a finishing treatment in particular for the application in forming tools. Cutting techniques such as milling and grinding are hardly applicable for the finish machining because of the high strength of diamond. Due to its process principle of ablating material by melting and evaporating, Electrical Discharge Machining (EDM) is independent of hardness, brittleness or toughness of the workpiece material. EDM is a suitable technology for machining and structuring CVD diamond, since boron doped CVD diamond is electrically conductive. In this study the ablation characteristics of boron doped CVD diamond by micro electrical discharge machining are investigated. Experiments were carried out to investigate the influence of different process parameters on the machining result. The impact of tool-polarity, voltage and discharge energy on the resulting erosion geometry and the tool wear was analyzed. A variation in path overlapping during the erosion of planar areas leads to different microstructures. The results show that micro EDM is a suitable technology for finishing of boron doped CVD diamond.

Machine Learning and Inverse Problem in Geodynamics

Science.gov (United States)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

2017-12-01

During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques

Machinability of titanium metal matrix composites (Ti-MMCs)

Science.gov (United States)

Aramesh, Maryam

Titanium metal matrix composites (Ti-MMCs), as a new generation of materials, have various potential applications in aerospace and automotive industries. The presence of ceramic particles enhances the physical and mechanical properties of the alloy matrix. However, the hard and abrasive nature of these particles causes various issues in the field of their machinability. Severe tool wear and short tool life are the most important drawbacks of machining this class of materials. There is very limited work in the literature regarding the machinability of this class of materials especially in the area of tool life estimation and tool wear. By far, polycrystalline diamond (PCD) tools appear to be the best choice for machining MMCs from researchers' point of view. However, due to their high cost, economical alternatives are sought. Cubic boron nitride (CBN) inserts, as the second hardest available tools, show superior characteristics such as great wear resistance, high hardness at elevated temperatures, a low coefficient of friction and a high melting point. Yet, so far CBN tools have not been studied during machining of Ti-MMCs. In this study, a comprehensive study has been performed to explore the tool wear mechanisms of CBN inserts during turning of Ti-MMCs. The unique morphology of the worn faces of the tools was investigated for the first time, which led to new insights in the identification of chemical wear mechanisms during machining of Ti-MMCs. Utilizing the full tool life capacity of cutting tools is also very crucial, due to the considerable costs associated with suboptimal replacement of tools. This strongly motivates development of a reliable model for tool life estimation under any cutting conditions. In this study, a novel model based on the survival analysis methodology is developed to estimate the progressive states of tool wear under any cutting conditions during machining of Ti-MMCs. This statistical model takes into account the machining time in

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

Machine Learning in Computer-Aided Synthesis Planning.

Science.gov (United States)

Coley, Connor W; Green, William H; Jensen, Klavs F

2018-05-15

Computer-aided synthesis planning (CASP) is focused on the goal of accelerating the process by which chemists decide how to synthesize small molecule compounds. The ideal CASP program would take a molecular structure as input and output a sorted list of detailed reaction schemes that each connect that target to purchasable starting materials via a series of chemically feasible reaction steps. Early work in this field relied on expert-crafted reaction rules and heuristics to describe possible retrosynthetic disconnections and selectivity rules but suffered from incompleteness, infeasible suggestions, and human bias. With the relatively recent availability of large reaction corpora (such as the United States Patent and Trademark Office (USPTO), Reaxys, and SciFinder databases), consisting of millions of tabulated reaction examples, it is now possible to construct and validate purely data-driven approaches to synthesis planning. As a result, synthesis planning has been opened to machine learning techniques, and the field is advancing rapidly. In this Account, we focus on two critical aspects of CASP and recent machine learning approaches to both challenges. First, we discuss the problem of retrosynthetic planning, which requires a recommender system to propose synthetic disconnections starting from a target molecule. We describe how the search strategy, necessary to overcome the exponential growth of the search space with increasing number of reaction steps, can be assisted through a learned synthetic complexity metric. We also describe how the recursive expansion can be performed by a straightforward nearest neighbor model that makes clever use of reaction data to generate high quality retrosynthetic disconnections. Second, we discuss the problem of anticipating the products of chemical reactions, which can be used to validate proposed reactions in a computer-generated synthesis plan (i.e., reduce false positives) to increase the likelihood of experimental success

Quantification of human error and common-mode failures in man-machine systems

International Nuclear Information System (INIS)

Lisboa, J.J.

1988-01-01

Quantification of human performance, particularly the determination of human error, is essential for realistic assessment of overall system performance of man-machine systems. This paper presents an analysis of human errors in nuclear power plant systems when measured against common-mode failures (CMF). Human errors evaluated are improper testing, inadequate maintenance strategy, and miscalibration. The methodology presented in the paper represents a positive contribution to power plant systems availability by identifying sources of common-mode failure when operational functions are involved. It is also applicable to other complex systems such as chemical plants, aircraft and motor industries; in fact, any large man-created, man-machine system could be included

Machine translation

Energy Technology Data Exchange (ETDEWEB)

Nagao, M

1982-04-01

Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

Bayesian molecular design with a chemical language model

Science.gov (United States)

Ikebata, Hisaki; Hongo, Kenta; Isomura, Tetsu; Maezono, Ryo; Yoshida, Ryo

2017-04-01

The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes' law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.

Cytocompatibility of a free machining titanium alloy containing lanthanum.

Science.gov (United States)

Feyerabend, Frank; Siemers, Carsten; Willumeit, Regine; Rösler, Joachim

2009-09-01

Titanium alloys like Ti6Al4V are widely used in medical engineering. However, the mechanical and chemical properties of titanium alloys lead to poor machinability, resulting in high production costs of medical products. To improve the machinability of Ti6Al4V, 0.9% of the rare earth element lanthanum (La) was added. The microstructure, the mechanical, and the corrosion properties were determined. Lanthanum containing alloys exhibited discrete particles of cubic lanthanum. The mechanical properties and corrosion resistance were slightly decreased but are still sufficient for many applications in the field of medical engineering. In vitro experiments with mouse macrophages (RAW 264.7) and human bone-derived cells (MG-63, HBDC) were performed and revealed that macrophages showed a dose response below and above a LaCl3 concentration of 200 microM, while MG-63 and HBDC tolerated three times higher concentrations without reduction of viability. The viability of cells cultured on disks of the materials showed no differences between the reference and the lanthanum containing alloy. We therefore propose that lanthanum containing alloy appears to be a good alternative for biomedical applications, where machining of parts is necessary.

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

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

2013-01-01

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

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

Your Sewing Machine.

Science.gov (United States)

Peacock, Marion E.

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

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...

Coldness production and heat revalorization: particular machines; Production de froid et revalorisation de la chaleur: machines particulieres

Energy Technology Data Exchange (ETDEWEB)

Feidt, M. [Universite Henri Poincare - Nancy-1, 54 - Nancy (France)

2003-10-01

The machines presented in this article are not the common reverse cycle machines. They use some systems based on different physical principles which have some consequences on the analysis of cycles: 1 - permanent gas machines (thermal separators, pulse gas tube, thermal-acoustic machines); 2 - phase change machines (mechanical vapor compression machines, absorption machines, ejection machines, adsorption machines); 3 - thermoelectric machines (thermoelectric effects, thermodynamic model of a thermoelectric machine). (J.S.)

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

Science.gov (United States)

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

2015-01-01

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

‘Machinic Trajectories’: Appropriated Devices as Post-Digital Drawing Machines

Directory of Open Access Journals (Sweden)

Andres Wanner

2014-12-01

Full Text Available This article presents a series of works called Machinic Trajectories, consisting of domestic devices appropriated as mechanical drawing machines. These are contextualized within the post-digital discourse, which integrates messy analog conditions into the digital realm. The role of eliciting and examining glitches for investigating a technology is pointed out. Glitches are defined as short-lived, unpremeditated aesthetic results of a failure; they are mostly known as digital phenomena, but I argue that the concept is equally applicable to the output of mechanical machines. Three drawing machines will be presented: The Opener, The Mixer and The Ventilator. In analyzing their drawings, emergent patterns consisting of unpremeditated visual artifacts will be identified and connected to irregularities of the specific technologies. Several other artists who work with mechanical and robotic drawing machines are introduced, to situate the presented works and reflections in a larger context of practice and to investigate how glitch concepts are applicable to such mechanical systems. 

Self-Improving CNC Milling Machine

OpenAIRE

Spilling, Torjus

2014-01-01

This thesis is a study of the ability of a CNC milling machine to create parts for itself, and an evaluation of whether or not the machine is able to improve itself by creating new machine parts. This will be explored by using off-the-shelf parts to build an initial machine, using 3D printing/rapid prototyping to create any special parts needed for the initial build. After an initial working machine is completed, the design of the machine parts will be adjusted so that the machine can start p...

Machinability and scratch wear resistance of carbon-coated WC inserts

Energy Technology Data Exchange (ETDEWEB)

Pazhanivel, B., E-mail: palcecri@yahoo.co.in; Kumar, T. Prem; Sozhan, G.

2015-03-15

Highlights: • Cemented WC inserts were coated with carbon by CVD. • The deposits were either loosely held MWCNTs or adherent carbides. • Co-efficient of friction (ramp load; 1–13 N); 0.2 and 0.1 μ, respectively, for the uncoated and carbide-coated inserts. • The carbide-coated insert exhibited better machinability and surface finish than a commercial TiCN-coated insert. - Abstract: In this work, cemented tungsten carbide (WC) inserts were coated with nanocarbons/carbides by chemical vapor deposition (CVD) and their machinability and scratch wear resistance were investigated. The hardness and surface conditions of the WC substrate were studied before and after coating. The CVD-generated nanocarbons on the insert surfaces were examined by SEM, FE-SEM and TEM. The electron microscopic images revealed that the carbons generated were multi-walled carbon nanotubes (MWCNTs) or carbides depending on the experimental conditions. In both the cases, the cutting edges of the inserts had dense deposits. Scratch wear test with the coated inserts showed that the co-efficient of friction was 0.1 μ as against 0.2 μ for the uncoated inserts under a ramp load of 1–13 N. The machinability characteristics of commercially available TiCN-coated inserts and the carbon-coated WC inserts were compared by using a CNC machine and a Rapid I vision inspection system. It was found that the carbide-coated inserts exhibited machinability with better surface finish comparable to that of the TiCN-coated inserts while the MWCNT-coated inserts showed inferior adhesion properties.

Machine Learning.

Science.gov (United States)

Kirrane, Diane E.

1990-01-01

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

Machining of Metal Matrix Composites

CERN Document Server

2012-01-01

Machining of Metal Matrix Composites provides the fundamentals and recent advances in the study of machining of metal matrix composites (MMCs). Each chapter is written by an international expert in this important field of research. Machining of Metal Matrix Composites gives the reader information on machining of MMCs with a special emphasis on aluminium matrix composites. Chapter 1 provides the mechanics and modelling of chip formation for traditional machining processes. Chapter 2 is dedicated to surface integrity when machining MMCs. Chapter 3 describes the machinability aspects of MMCs. Chapter 4 contains information on traditional machining processes and Chapter 5 is dedicated to the grinding of MMCs. Chapter 6 describes the dry cutting of MMCs with SiC particulate reinforcement. Finally, Chapter 7 is dedicated to computational methods and optimization in the machining of MMCs. Machining of Metal Matrix Composites can serve as a useful reference for academics, manufacturing and materials researchers, manu...

Machine technology: a survey

International Nuclear Information System (INIS)

Barbier, M.M.

1981-01-01

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

Characteristics of laser assisted machining for silicon nitride ceramic according to machining parameters

International Nuclear Information System (INIS)

Kim, Jong Do; Lee, Su Jin; Suh, Jeong

2011-01-01

This paper describes the Laser Assisted Machining (LAM) that cuts and removes softened parts by locally heating the ceramic with laser. Silicon nitride ceramics can be machined with general machining tools as well, because YSiAlON, which was made up ceramics, is soften at about 1,000 .deg. C. In particular, the laser, which concentrates on highly dense energy, can locally heat materials and very effectively control the temperature of the heated part of specimen. Therefore, this paper intends to propose an efficient machining method of ceramic by deducing the machining governing factors of laser assisted machining and understanding its mechanism. While laser power is the machining factor that controls the temperature, the CBN cutting tool could cut the material more easily as the material gets deteriorated from the temperature increase by increasing the laser power, but excessive oxidation can negatively affect the quality of the material surface after machining. As the feed rate and cutting depth increase, the cutting force increases and tool lifespan decreases, but surface oxidation also decreases. In this experiment, the material can be cut to 3 mm of cutting depth. And based on the results of the experiment, the laser assisted machining mechanism is clarified

Energy-efficient electrical machines by new materials. Superconductivity in large electrical machines

International Nuclear Information System (INIS)

Frauenhofer, Joachim; Arndt, Tabea; Grundmann, Joern

2013-01-01

The implementation of superconducting materials in high-power electrical machines results in significant advantages regarding efficiency, size and dynamic behavior when compared to conventional machines. The application of HTS (high-temperature superconductors) in electrical machines allows significantly higher power densities to be achieved for synchronous machines. In order to gain experience with the new technology, Siemens carried out a series of development projects. A 400 kW model motor for the verification of a concept for the new technology was followed by a 4000 kV A generator as highspeed machine - as well as a low-speed 4000 kW propeller motor with high torque. The 4000 kVA generator is still employed to carry out long-term tests and to check components. Superconducting machines have significantly lower weight and envelope dimensions compared to conventional machines, and for this reason alone, they utilize resources better. At the same time, operating losses are slashed to about half and the efficiency increases. Beyond this, they set themselves apart as a result of their special features in operation, such as high overload capability, stiff alternating load behavior and low noise. HTS machines provide significant advantages where the reduction of footprint, weight and losses or the improved dynamic behavior results in significant improvements of the overall system. Propeller motors and generators,for ships, offshore plants, in wind turbine and hydroelectric plants and in large power stations are just some examples. HTS machines can therefore play a significant role when it comes to efficiently using resources and energy as well as reducing the CO 2 emissions.

wACSF—Weighted atom-centered symmetry functions as descriptors in machine learning potentials

Science.gov (United States)

Gastegger, M.; Schwiedrzik, L.; Bittermann, M.; Berzsenyi, F.; Marquetand, P.

2018-06-01

We introduce weighted atom-centered symmetry functions (wACSFs) as descriptors of a chemical system's geometry for use in the prediction of chemical properties such as enthalpies or potential energies via machine learning. The wACSFs are based on conventional atom-centered symmetry functions (ACSFs) but overcome the undesirable scaling of the latter with an increasing number of different elements in a chemical system. The performance of these two descriptors is compared using them as inputs in high-dimensional neural network potentials (HDNNPs), employing the molecular structures and associated enthalpies of the 133 855 molecules containing up to five different elements reported in the QM9 database as reference data. A substantially smaller number of wACSFs than ACSFs is needed to obtain a comparable spatial resolution of the molecular structures. At the same time, this smaller set of wACSFs leads to a significantly better generalization performance in the machine learning potential than the large set of conventional ACSFs. Furthermore, we show that the intrinsic parameters of the descriptors can in principle be optimized with a genetic algorithm in a highly automated manner. For the wACSFs employed here, we find however that using a simple empirical parametrization scheme is sufficient in order to obtain HDNNPs with high accuracy.

VIRTUAL MACHINES IN EDUCATION – CNC MILLING MACHINE WITH SINUMERIK 840D CONTROL SYSTEM

Directory of Open Access Journals (Sweden)

Ireneusz Zagórski

2014-11-01

Full Text Available Machining process nowadays could not be conducted without its inseparable element: cutting edge and frequently numerically controlled milling machines. Milling and lathe machining centres comprise standard equipment in many companies of the machinery industry, e.g. automotive or aircraft. It is for that reason that tertiary education should account for this rising demand. This entails the introduction into the curricula the forms which enable visualisation of machining, milling process and virtual production as well as virtual machining centres simulation. Siemens Virtual Machine (Virtual Workshop sets an example of such software, whose high functionality offers a range of learning experience, such as: learning the design of machine tools, their configuration, basic operation functions as well as basics of CNC.

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

Science.gov (United States)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

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

Safety concerns in composite manufacturing and machining

Science.gov (United States)

Asmatulu, Eylem; Alonayni, Abdullah; Alamir, Mohammed

2018-03-01

Because of the superior properties, composites have been used in many industrial applications, including aerospace, wind turbines, ships, cars, fishing rods, storage tanks, swimming pool panels, and baseball bats. Each application may require different combinations of reinforcements and matrices, which make the manufacturing safety even more challenging while working on these substances. In this study, safety issues in composite manufacturing and machining were investigated in detail, and latest developments were provided for workers. The materials most frequently used in composite manufacturing, such as matrix (polyester, vinylester, phenolic, epoxies, methyl ethyl ketone peroxide, benzoil peroxide, hardeners, and solvents), and reinforcement materials (carbon, glass and Kevlar fibers, honeycomb and foams) can be highly toxic to human body. These materials can also be very toxic to the environment when dumped out uncontrollably, creating major future health and environmental concerns. Throughout the manufacturing process, workers inhale vapors of the liquid matrix, hardeners and solvents / thinners, as well as reinforcement materials (chopped fibers and particles) in airborne. Milling, cutting and machining of the composites can further increase the toxic inhalations of airborne composite particles, resulting in major rashes, irritation, skin disorders, coughing, severe eye and lung injury and other serious illnesses. The major portions of these hazardous materials can be controlled using appropriate personal protective equipment for the chemicals and materials used in composite manufacturing and machining. This study provides best possible safety practices utilized in composite manufacturing facilities for workers, engineers and other participants.

Machine-to-machine communications architectures, technology, standards, and applications

CERN Document Server

Misic, Vojislav B

2014-01-01

With the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including its integration with current technology.Presenting the work of a different group of international experts in each chapter, the book begins by supplying an overview of M2M technology. It considers proposed standards, cutting-edge applications, architectures, and traffic modeling and includes case studies that highlight the differences between traditional and M2M communications technology.Details a practical scheme for the forward error correction code designInvestigates the effectiveness of the IEEE 802.15.4 low data rate wireless personal area network standard for use in M2M communicationsIdentifies algorithms that will ensure functionality, performance, reliability, ...

Nonplanar machines

International Nuclear Information System (INIS)

Ritson, D.

1989-05-01

This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

Ultraprecision machining. Cho seimitsu kako

Energy Technology Data Exchange (ETDEWEB)

Suga, T [The Univ. of Tokyo, Tokyo (Japan). Research Center for Advanced Science and Technology

1992-10-05

It is said that the image of ultraprecision improved from 0.1[mu]m to 0.01[mu]m within recent years. Ultraprecision machining is a production technology which forms what is called nanotechnology with ultraprecision measuring and ultraprecision control. Accuracy means average machined sizes close to a required value, namely the deflection errors are small; precision means the scattered errors of machined sizes agree very closely. The errors of machining are related to both of the above errors and ultraprecision means the combined errors are very small. In the present ultraprecision machining, the relative precision to the size of a machined object is said to be in the order of 10[sup -6]. The flatness of silicon wafers is usually less than 0.5[mu]m. It is the fact that the appearance of atomic scale machining is awaited as the limit of ultraprecision machining. The machining of removing and adding atomic units using scanning probe microscopes are expected to reach the limit actually. 2 refs.

Theory and practice in machining systems

CERN Document Server

Ito, Yoshimi

2017-01-01

This book describes machining technology from a wider perspective by considering it within the machining space. Machining technology is one of the metal removal activities that occur at the machining point within the machining space. The machining space consists of structural configuration entities, e.g., the main spindle, the turret head and attachments such the chuck and mandrel, and also the form-generating movement of the machine tool itself. The book describes fundamental topics, including the form-generating movement of the machine tool and the important roles of the attachments, before moving on to consider the supply of raw materials into the machining space, and the discharge of swarf from it, and then machining technology itself. Building on the latest research findings “Theory and Practice in Machining System” discusses current challenges in machining. Thus, with the inclusion of introductory and advanced topics, the book can be used as a guide and survey of machining technology for students an...

Design and production of a novel sand materials strength testing machine for foundry applications

DEFF Research Database (Denmark)

Nwaogu, Ugochukwu Chibuzoh; Hansen, K. S.; Tiedje, Niels Skat

2012-01-01

testing machine was designed and built for both green sand and chemically-bonded sand materials. This machine measures and presents the loading response as a force-displacement profile from which the mechanical properties of the moulding materials can be deduced. The system was interfaced to a computer......In the foundry, existing strength testing machines are used to measure only the maximum fracture strength of mould and core materials. With traditionally used methods, the loading history to ascertain deformation of the material is not available. In this paper, a novel moulding material strength...... with a commercial PC based-control and data acquisition software. The testing conditions and operations are specified in the user interface and the data acquisition is made according to specifications. The force and displacements were calibrated to ensure consistency and reliability of the measurement data...

Face machines

Energy Technology Data Exchange (ETDEWEB)

Hindle, D.

1999-06-01

The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

Tattoo machines, needles and utilities.

Science.gov (United States)

Rosenkilde, Frank

2015-01-01

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

Design of rotating electrical machines

CERN Document Server

Pyrhonen , Juha; Hrabovcova , Valeria

2013-01-01

In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

Directory of Open Access Journals (Sweden)

POPESCU Adrian

2015-11-01

Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

MITS machine operations

International Nuclear Information System (INIS)

Flinchem, J.

1980-01-01

This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

Coordinate measuring machines

DEFF Research Database (Denmark)

De Chiffre, Leonardo

This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceabilit...... and uncertainty during coordinate measurements, 3) Digitalisation and Reverse Engineering. This document contains a short description of each step in the exercise and schemes with room for taking notes of the results.......This document is used in connection with three exercises of 2 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercises concern three aspects of coordinate measuring: 1) Measuring and verification of tolerances on coordinate measuring machines, 2) Traceability...

Electric machine

Science.gov (United States)

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

2012-07-17

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

Machine Learning and Radiology

Science.gov (United States)

Wang, Shijun; Summers, Ronald M.

2012-01-01

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

Tribology in machine design

CERN Document Server

Stolarski, Tadeusz

1999-01-01

""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen

Some regularities of structure and surface layer properties changing of metal materials after electro-erosion machining

International Nuclear Information System (INIS)

Khvostyntsev, K.I.; Kuz'mina, T.S.; Kruglov, V.V.; Lukovkin, G.F.

1982-01-01

Effect of electoerosion machining on the surface state of pearlitic class steel of the 12KhN4MFA type, bronzes BrAMts 9-2 and BrAZhNMts 9-4-4-1, of the alloy PT-3V has been studied. As a result of electroerosion machining (EEM) a transformed layer, presenting overheated and partially melted metal, the structure and hardness of which depend on chemical composition of the materials treated, their tendency to phase transformatins and saturation with introduction elements, is formed on the surface of metal materials

Some regularities of structure and surface layer properties changing of metal materials after electro-erosion machining

Energy Technology Data Exchange (ETDEWEB)

Khvostyntsev, K.I.; Kuz' mina, T.S.; Kruglov, V.V.; Lukovkin, G.F.

1982-01-01

Effect of electoerosion machining on the surface state of pearlitic class steel of the 12KhN4MFA type, bronzes BrAMts 9-2 and BrAZhNMts 9-4-4-1, of the alloy PT-3V has been studied. As a result of electroerosion machining (EEM) a transformed layer, presenting overheated and partially melted metal, the structure and hardness of which depend on chemical composition of the materials treated, their tendency to phase transformatins and saturation with introduction elements, is formed on the surface of metal materials.

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

Directory of Open Access Journals (Sweden)

Woong-Kirl Choi

2018-01-01

Full Text Available Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks.

A Universal Reactive Machine

DEFF Research Database (Denmark)

Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.

1997-01-01

Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...

Consequences of heavy machining vis à vis the machine structure – typical applications

International Nuclear Information System (INIS)

Leuch, M

2011-01-01

StarragHeckert has built 5 axis machines since the middle of the 80s for heavy duty milling. The STC-Centres are predominantly utilised in the aerospace industry, especially for milling structural workpieces, casings or Impellers made out of titanium and steel. StarragHeckert has a history of building machines for high performance milling. The machining of these components includes high forces thus spreading the wheat from the chaff. Although FEM calculations and multi-body simulations are carried out in the early stages of development, this paper will illustrate how the real process stability with modal analysis and cutting trials is determined. The experiment observes chatter stability to identify if the machine devices are adequate for the application or if the design has to be improved. Machining parameters of industrial applications are demonstrating the process stability for five axis heavy duties milling of StarragHeckert machine.

Virtual Machine in Automation Projects

OpenAIRE

Xing, Xiaoyuan

2010-01-01

Virtual machine, as an engineering tool, has recently been introduced into automation projects in Tetra Pak Processing System AB. The goal of this paper is to examine how to better utilize virtual machine for the automation projects. This paper designs different project scenarios using virtual machine. It analyzes installability, performance and stability of virtual machine from the test results. Technical solutions concerning virtual machine are discussed such as the conversion with physical...

The Buttonhole Machine. Module 13.

Science.gov (United States)

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

This module on the bottonhole machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers two topics: performing special operations on the buttonhole machine (parts and purpose) and performing special operations on the buttonhole machine (gauged buttonholes). For each topic these components are…

Introduction to machine learning.

Science.gov (United States)

Baştanlar, Yalin; Ozuysal, Mustafa

2014-01-01

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

Applied machining technology

CERN Document Server

Tschätsch, Heinz

2010-01-01

Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

2017-04-21

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 Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

Machine Protection

International Nuclear Information System (INIS)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

Machine Protection

Energy Technology Data Exchange (ETDEWEB)

Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

2012-07-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Machine Protection

CERN Document Server

Zerlauth, Markus; Wenninger, Jörg

2012-01-01

The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

Dictionary of machine terms

International Nuclear Information System (INIS)

1990-06-01

This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.

HTS machine laboratory prototype

DEFF Research Database (Denmark)

machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...

Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

Science.gov (United States)

Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

2011-01-01

Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

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

OpenAIRE

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

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

Machine vision systems using machine learning for industrial product inspection

Science.gov (United States)

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.

Machine Directional Register System Modeling for Shaft-Less Drive Gravure Printing Machines

Directory of Open Access Journals (Sweden)

Shanhui Liu

2013-01-01

Full Text Available In the latest type of gravure printing machines referred to as the shaft-less drive system, each gravure printing roller is driven by an individual servo motor, and all motors are electrically synchronized. The register error is regulated by a speed difference between the adjacent printing rollers. In order to improve the control accuracy of register system, an accurate mathematical model of the register system should be investigated for the latest machines. Therefore, the mathematical model of the machine directional register (MDR system is studied for the multicolor gravure printing machines in this paper. According to the definition of the MDR error, the model is derived, and then it is validated by the numerical simulation and experiments carried out in the experimental setup of the four-color gravure printing machines. The results show that the established MDR system model is accurate and reliable.

Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

Science.gov (United States)

Krishnamurthy, Narayanan; Maddali, Siddharth; Romanov, Vyacheslav; Hawk, Jeffrey

We present some structural properties of multi-component steel alloys as predicted by a random forest machine-learning model. These non-parametric models are trained on high-dimensional data sets defined by features such as chemical composition, pre-processing temperatures and environmental influences, the latter of which are based upon standardized testing procedures for tensile, creep and rupture properties as defined by the American Society of Testing and Materials (ASTM). We quantify the goodness of fit of these models as well as the inferred relative importance of each of these features, all with a conveniently defined metric and scale. The models are tested with synthetic data points, generated subject to the appropriate mathematical constraints for the various features. By this we highlight possible trends in the increase or degradation of the structural properties with perturbations in the features of importance. This work is presented as part of the Data Science Initiative at the National Energy Technology Laboratory, directed specifically towards the computational design of steel alloys.

Machine learning and radiology.

Science.gov (United States)

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Machining with abrasives

CERN Document Server

Jackson, Mark J

2011-01-01

Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

The Knife Machine. Module 15.

Science.gov (United States)

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

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Mechanical properties of chemically bonded sand core materials dipped in sol-gel coating impregnated with filter

DEFF Research Database (Denmark)

Nwaogu, Ugochukwu Chibuzoh; Tiedje, Niels Skat

2012-01-01

A novel sol-gel coating impregnated with filter dust was applied on chemically bonded sand core materials by dipping. After curing, the strengths of the core materials were measured under uniaxial loading using a new strength testing machine (STM). The STM presents the loading history as a force-...... of the chemically bonded sand core materials, a combination of flexural and compression tests is suggested for improving the casting quality. © 2012 W. S. Maney & Son Ltd.......A novel sol-gel coating impregnated with filter dust was applied on chemically bonded sand core materials by dipping. After curing, the strengths of the core materials were measured under uniaxial loading using a new strength testing machine (STM). The STM presents the loading history as a force...... the strengths were increased under compression. The mode of fracture of the chemically bonded sand core materials was observed to be intergranular through the binder. The stiffness of the chemically bonded sand core materials was determined. For better understanding of the mechanical properties...

Restrictions of process machine retooling at machine-building enterprises

Directory of Open Access Journals (Sweden)

Kuznetsova Elena

2017-01-01

Full Text Available The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of up-to-date equipment, and drop in its use efficiency. The article investigates and classifies the main restrictions of the manufacturing equipment renewal process, such as regulatory and legislative, financial, organizational, competency-based. The economic consequences of the revealed restrictions influence on the machine-building enterprises activity are shown.

Mechanical design of machine components

CERN Document Server

Ugural, Ansel C

2015-01-01

Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

Soft computing in machine learning

CERN Document Server

Park, Jooyoung; Inoue, Atsushi

2014-01-01

As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train machines to perform some things, so that they can automatically detect, diagnose, and solve a variety of problems. The intelligent systems have made rapid progress in developing the state of the art in machine learning based on smart and deep perception. Using machine learning, the intelligent systems make widely applications in automated speech recognition, natural language processing, medical diagnosis, bioinformatics, and robot locomotion. This book aims at introducing how to treat a substantial amount of data, to teach machines and to improve decision making models. And this book specializes in the developments of advanced intelligent systems through machine learning. It...

MRR and TWR evaluation on electrical discharge machining of Ti-6Al-4V using tungsten : copper composite electrode

Science.gov (United States)

Prasanna, J.; Rajamanickam, S.; Amith Kumar, O.; Karthick Raj, G.; Sathya Narayanan, P. V. V.

2017-05-01

In this paper Ti-6Al-4V used as workpiece material and it is keenly seen in variety of field including medical, chemical, marine, automotive, aerospace, aviation, electronic industries, nuclear reactor, consumer products etc., The conventional machining of Ti-6Al-4V is very difficult due to its distinctive properties. The Electrical Discharge Machining (EDM) is right choice of machining this material. The tungsten copper composite material is employed as tool material. The gap voltage, peak current, pulse on time and duty factor is considered as the machining parameter to analyze the machining characteristics Material Removal Rate (MRR) and Tool Wear Rate (TWR). The Taguchi method is provided to work for finding the significant parameter of EDM. It is found that for MRR significant parameters rated in the following order Gap Voltage, Pulse On-Time, Peak Current and Duty Factor. On the other hand for TWR significant parameters are listed in line of Gap Voltage, Duty Factor, Peak Current and Pulse On-Time.

Mankind, machines and people

Energy Technology Data Exchange (ETDEWEB)

Hugli, A

1984-01-01

The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.

A Concrete Framework for Environment Machines

DEFF Research Database (Denmark)

Biernacka, Malgorzata; Danvy, Olivier

2007-01-01

calculus with explicit substitutions), we extend it minimally so that it can also express one-step reduction strategies, and we methodically derive a series of environment machines from the specification of two one-step reduction strategies for the lambda-calculus: normal order and applicative order....... The derivation extends Danvy and Nielsen’s refocusing-based construction of abstract machines with two new steps: one for coalescing two successive transitions into one, and the other for unfolding a closure into a term and an environment in the resulting abstract machine. The resulting environment machines...... include both the Krivine machine and the original version of Krivine’s machine, Felleisen et al.’s CEK machine, and Leroy’s Zinc abstract machine....

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

Science.gov (United States)

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

2016-09-01

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

Research on the proficient machine system. Theoretical part; Jukutatsu machine system no chosa kenkyu. Rironhen

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

The basic theory of the proficient machine system to be developed was studied. Important proficient techniques in manufacturing industries are becoming extinct because of insufficient succession to next generation. The proficient machine system was proposed to cope with such situation. This machine system includes the mechanism for progress and evolution of techniques and sensibilities to be adaptable to environmental changes by learning and recognizing various motions such as work and process. Consequently, the basic research fields are composed of thought, learning, perception and action. This machine requires not only deigned fixed functions but also introduction of the same proficient concept as human being to be adaptable to changes in situation, purpose, time and machine`s complexity. This report explains in detail the basic concept, system principle, approaching procedure and practical elemental technologies of the proficient machine system, and also describes the future prospect. 133 refs., 110 figs., 7 tabs.

Machining of uranium and uranium alloys

International Nuclear Information System (INIS)

Morris, T.O.

1981-01-01

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

[Comparison of machinability of two types of dental machinable ceramic].

Science.gov (United States)

Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

2002-11-01

In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

Graphene-based bimorphs for micron-sized, autonomous origami machines.

Science.gov (United States)

Miskin, Marc Z; Dorsey, Kyle J; Bircan, Baris; Han, Yimo; Muller, David A; McEuen, Paul L; Cohen, Itai

2018-01-16

Origami-inspired fabrication presents an attractive platform for miniaturizing machines: thinner layers of folding material lead to smaller devices, provided that key functional aspects, such as conductivity, stiffness, and flexibility, are persevered. Here, we show origami fabrication at its ultimate limit by using 2D atomic membranes as a folding material. As a prototype, we bond graphene sheets to nanometer-thick layers of glass to make ultrathin bimorph actuators that bend to micrometer radii of curvature in response to small strain differentials. These strains are two orders of magnitude lower than the fracture threshold for the device, thus maintaining conductivity across the structure. By patterning 2-[Formula: see text]m-thick rigid panels on top of bimorphs, we localize bending to the unpatterned regions to produce folds. Although the graphene bimorphs are only nanometers thick, they can lift these panels, the weight equivalent of a 500-nm-thick silicon chip. Using panels and bimorphs, we can scale down existing origami patterns to produce a wide range of machines. These machines change shape in fractions of a second when crossing a tunable pH threshold, showing that they sense their environments, respond, and perform useful functions on time and length scales comparable with microscale biological organisms. With the incorporation of electronic, photonic, and chemical payloads, these basic elements will become a powerful platform for robotics at the micrometer scale.

MACHINE LEARNING METHODS IN DIGITAL AGRICULTURE: ALGORITHMS AND CASES

Directory of Open Access Journals (Sweden)

Aleksandr Vasilyevich Koshkarov

2018-05-01

Full Text Available Ensuring food security is a major challenge in many countries. With a growing global population, the issues of improving the efficiency of agriculture have become most relevant. Farmers are looking for new ways to increase yields, and governments of different countries are developing new programs to support agriculture. This contributes to a more active implementation of digital technologies in agriculture, helping farmers to make better decisions, increase yields and take care of the environment. The central point is the collection and analysis of data. In the industry of agriculture, data can be collected from different sources and may contain useful patterns that identify potential problems or opportunities. Data should be analyzed using machine learning algorithms to extract useful insights. Such methods of precision farming allow the farmer to monitor individual parts of the field, optimize the consumption of water and chemicals, and identify problems quickly. Purpose: to make an overview of the machine learning algorithms used for data analysis in agriculture. Methodology: an overview of the relevant literature; a survey of farmers. Results: relevant algorithms of machine learning for the analysis of data in agriculture at various levels were identified: soil analysis (soil assessment, soil classification, soil fertility predictions, weather forecast (simulation of climate change, temperature and precipitation prediction, and analysis of vegetation (weed identification, vegetation classification, plant disease identification, crop forecasting. Practical implications: agriculture, crop production.

Nonlinear machine learning in soft materials engineering and design

Science.gov (United States)

Ferguson, Andrew

The inherently many-body nature of molecular folding and colloidal self-assembly makes it challenging to identify the underlying collective mechanisms and pathways governing system behavior, and has hindered rational design of soft materials with desired structure and function. Fundamentally, there exists a predictive gulf between the architecture and chemistry of individual molecules or colloids and the collective many-body thermodynamics and kinetics. Integrating machine learning techniques with statistical thermodynamics provides a means to bridge this divide and identify emergent folding pathways and self-assembly mechanisms from computer simulations or experimental particle tracking data. We will survey a few of our applications of this framework that illustrate the value of nonlinear machine learning in understanding and engineering soft materials: the non-equilibrium self-assembly of Janus colloids into pinwheels, clusters, and archipelagos; engineering reconfigurable ''digital colloids'' as a novel high-density information storage substrate; probing hierarchically self-assembling onjugated asphaltenes in crude oil; and determining macromolecular folding funnels from measurements of single experimental observables. We close with an outlook on the future of machine learning in soft materials engineering, and share some personal perspectives on working at this disciplinary intersection. We acknowledge support for this work from a National Science Foundation CAREER Award (Grant No. DMR-1350008) and the Donors of the American Chemical Society Petroleum Research Fund (ACS PRF #54240-DNI6).

Advanced Electrical Machines and Machine-Based Systems for Electric and Hybrid Vehicles

OpenAIRE

Ming Cheng; Le Sun; Giuseppe Buja; Lihua Song

2015-01-01

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator perm...

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

Science.gov (United States)

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

2016-01-01

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

Machine Tool Software

Science.gov (United States)

1988-01-01

A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

Characterization and Prediction of Chemical Functions and ...

Science.gov (United States)

Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

Machine Ethics: Creating an Ethical Intelligent Agent

OpenAIRE

Anderson, Michael; Anderson, Susan Leigh

2007-01-01

The newly emerging field of machine ethics (Anderson and Anderson 2006) is concerned with adding an ethical dimension to machines. Unlike computer ethics -- which has traditionally focused on ethical issues surrounding humans' use of machines -- machine ethics is concerned with ensuring that the behavior of machines toward human users, and perhaps other machines as well, is ethically acceptable. In this article we discuss the importance of machine ethics, the need for machines that represent ...

Nanocomposites for Machining Tools

Directory of Open Access Journals (Sweden)

Daria Sidorenko

2017-10-01

Full Text Available Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance.

Machine learning with R

CERN Document Server

Lantz, Brett

2013-01-01

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

The effect of thermal conductivity of the tool electrode in spark-assisted chemical engraving gravity-feed micro-drilling

International Nuclear Information System (INIS)

Mousa, M; Allagui, A; Ng, H D; Wüthrich, R

2009-01-01

Spark-assisted chemical engraving (SACE) is a non-traditional micro-machining technology based on electrochemical discharge phenomena. In SACE gravity-feed micro-drilling, various parameters including the thermal properties of the tool electrode play a significant role in the process. Based on a series of experiments using tool electrodes with different thermal properties, the effect in SACE gravity-feed micro-drilling is discussed. It is demonstrated that machining with higher thermal conductivity tool electrodes results in faster machining during the discharge regime and slower machining during the hydrodynamic regime of SACE gravity-feed micro-drilling

Restrictions of process machine retooling at machine-building enterprises

OpenAIRE

Kuznetsova Elena; Tipner Ludmila; Ershov Alexey

2017-01-01

The competitiveness of the national economy depends on the technological level of the machine-building enterprises production equipment. Today in Russia there are objective and subjective restrictions for the optimum policy formation of the manufacturing equipment renewal. The analysis of the manufacturing equipment age structure dynamics in the Russian machine-building complex indicates the negative tendencies intensification: increase in the equipment service life, reduction in the share of...

Pattern recognition & machine learning

CERN Document Server

Anzai, Y

1992-01-01

This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

Machining tools in AISI M2 high-speed steel obtained by spray forming process

International Nuclear Information System (INIS)

Jesus, Edilson Rosa Barbosa de.

2004-01-01

The aim of the present work was the obtention of AISI M2 high-speed steel by spray forming technique and the material evaluation when used as machining tool. The obtained material was hot rolled at 50% and 72% reduction ratios, and from which it was manufactured inserts for machining tests. The performance of inserts made of the spray formed material was compared to inserts obtained from conventional and powder metallurgy (MP) processed materials. The spray formed material was chemical, physical, mechanical and microstructural characterised. For further characterisation, the materials were submitted to machining tests for performance evaluation under real work condition. The results of material characterisation highlight the potential of the spray forming technique, in the obtention of materials with good characteristics and properties. Under the current processing, hot rolling and heat treatments condition, the analysis of the results of the machining tests revealed a very similar behaviour among the tested materials. Proceeding a criterious analysis of the machining results tests, it was verified that the performance presented by the powder metallurgy material (MP) was slight superior, followed by conventional obtained material (MConv), which presented a insignificant advantage over the spray formed and hot rolled (72% reduction ratio) material. The worst result was encountered for the spray forming and hot rolled (50% reduction ratio) material that presented the highest wear values. (author)

Principles of control automation of soil compacting machine operating mechanism

Science.gov (United States)

Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

2018-03-01

The relevance of the qualitative compaction of soil bases in the erection of embankment and foundations in building and structure construction is given.The quality of the compactible gravel and sandy soils provides the bearing capability and, accordingly, the strength and durability of constructed buildings.It has been established that the compaction quality depends on many external actions, such as surface roughness and soil moisture; granulometry, chemical composition and degree of elasticity of originalfilled soil for compaction.The analysis of technological processes of soil bases compaction of foreign and domestic information sources showed that the solution of such important problem as a continuous monitoring of soil compaction actual degree in the process of machine operation carry out only with the use of modern means of automation. An effective vibrodynamic method of gravel and sand material sealing for the building structure foundations for various applications was justified and suggested.The method of continuous monitoring the soil compaction by measurement of the amplitudes and frequencies of harmonic oscillations on the compactible surface was determined, which allowed to determine the basic elements of facilities of soil compacting machine monitoring system of operating, etc. mechanisms: an accelerometer, a bandpass filter, a vibro-harmonics, an on-board microcontroller. Adjustable parameters have been established to improve the soil compaction degree and the soil compacting machine performance, and the adjustable parameter dependences on the overall indexhave been experimentally determined, which is the soil compaction degree.A structural scheme of automatic control of the soil compacting machine control mechanism and theoperation algorithm has been developed.

Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints

Directory of Open Access Journals (Sweden)

Cuixia Miao

2015-01-01

Full Text Available We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme for the two-machine problem. Furthermore, we extended the dynamic programming algorithm to the total weighted completion time minimization problem.

The Hooey Machine.

Science.gov (United States)

Scarnati, James T.; Tice, Craig J.

1992-01-01

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

Machine Vision Handbook

CERN Document Server

2012-01-01

The automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook  equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture – lenses, cameras, scanners and light sources – are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in insp...

Effect of the Machined Surfaces of AISI 4337 Steel to Cutting Conditions on Dry Machining Lathe

Science.gov (United States)

Rahim, Robbi; Napid, Suhardi; Hasibuan, Abdurrozzaq; Rahmah Sibuea, Siti; Yusmartato, Y.

2018-04-01

The objective of the research is to obtain a cutting condition which has a good chance of realizing dry machining concept on AISI 4337 steel material by studying surface roughness, microstructure and hardness of machining surface. The data generated from the experiment were then processed and analyzed using the standard Taguchi method L9 (34) orthogonal array. Testing of dry and wet machining used surface test and micro hardness test for each of 27 test specimens. The machining results of the experiments showed that average surface roughness (Raavg) was obtained at optimum cutting conditions when VB 0.1 μm, 0.3 μm and 0.6 μm respectively 1.467 μm, 2.133 μm and 2,800 μm fo r dry machining while which was carried out by wet machining the results obtained were 1,833 μm, 2,667 μm and 3,000 μm. It can be concluded that dry machining provides better surface quality of machinery results than wet machining. Therefore, dry machining is a good choice that may be realized in the manufacturing and automotive industries.

Evaluation of machinability and flexural strength of a novel dental machinable glass-ceramic.

Science.gov (United States)

Qin, Feng; Zheng, Shucan; Luo, Zufeng; Li, Yong; Guo, Ling; Zhao, Yunfeng; Fu, Qiang

2009-10-01

To evaluate the machinability and flexural strength of a novel dental machinable glass-ceramic (named PMC), and to compare the machinability property with that of Vita Mark II and human enamel. The raw batch materials were selected and mixed. Four groups of novel glass-ceramics were formed at different nucleation temperatures, and were assigned to Group 1, Group 2, Group 3 and Group 4. The machinability of the four groups of novel glass-ceramics, Vita Mark II ceramic and freshly extracted human premolars were compared by means of drilling depth measurement. A three-point bending test was used to measure the flexural strength of the novel glass-ceramics. The crystalline phases of the group with the best machinability were identified by X-ray diffraction. In terms of the drilling depth, Group 2 of the novel glass-ceramics proves to have the largest drilling depth. There was no statistical difference among Group 1, Group 4 and the natural teeth. The drilling depth of Vita MK II was statistically less than that of Group 1, Group 4 and the natural teeth. Group 3 had the least drilling depth. In respect of the flexural strength, Group 2 exhibited the maximum flexural strength; Group 1 was statistically weaker than Group 2; there was no statistical difference between Group 3 and Group 4, and they were the weakest materials. XRD of Group 2 ceramic showed that a new type of dental machinable glass-ceramic containing calcium-mica had been developed by the present study and was named PMC. PMC is promising for application as a dental machinable ceramic due to its good machinability and relatively high strength.

Silicon nanowire arrays as learning chemical vapour classifiers

International Nuclear Information System (INIS)

Niskanen, A O; Colli, A; White, R; Li, H W; Spigone, E; Kivioja, J M

2011-01-01

Nanowire field-effect transistors are a promising class of devices for various sensing applications. Apart from detecting individual chemical or biological analytes, it is especially interesting to use multiple selective sensors to look at their collective response in order to perform classification into predetermined categories. We show that non-functionalised silicon nanowire arrays can be used to robustly classify different chemical vapours using simple statistical machine learning methods. We were able to distinguish between acetone, ethanol and water with 100% accuracy while methanol, ethanol and 2-propanol were classified with 96% accuracy in ambient conditions.

Machine learning of parameters for accurate semiempirical quantum chemical calculations

International Nuclear Information System (INIS)

Dral, Pavlo O.; Lilienfeld, O. Anatole von; Thiel, Walter

2015-01-01

We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C 7 H 10 O 2 , for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules

An HTS machine laboratory prototype

DEFF Research Database (Denmark)

Mijatovic, Nenad; Jensen, Bogi Bech; Træholt, Chresten

2012-01-01

This paper describes Superwind HTS machine laboratory setup which is a small scale HTS machine designed and build as a part of the efforts to identify and tackle some of the challenges the HTS machine design may face. One of the challenges of HTS machines is a Torque Transfer Element (TTE) which...... conduction compared to a shaft. The HTS machine was successfully cooled to 77K and tests have been performed. The IV curves of the HTS field winding employing 6 HTS coils indicate that two of the coils had been damaged. The maximal value of the torque during experiments of 78Nm was recorded. Loaded with 33...

Applicability of Machine-Learning Enabled LIBS in Post Irradiation Nuclear Forensic Analysis of High Level Waste

International Nuclear Information System (INIS)

Onkongi, J.; Maina, D.; Angeyo, H.K.

2017-01-01

Nuclear Forensics seeks Information to determine; Chemical Composition, Routes of transit, Origin (Provenance) and Intended use. Post Irradiation/Post detonation NF In a post-detonation event could you get clues/signatures from glass debris, minute sample sizes? Nuclear Forensic Technique Should be State-of -the art that is Rapid, Non-invasive, Remote ability and Non-destructive. Laser Induced Breakdown Spectroscopy (LIBS) unlike other Analytic Techniques that require tedious sample preparations such as Dissolution, digestion & matrix removal, which generate additional nuclear wastes that require proper Procedures for handling, storage & ultimate disposal, LIBS overcomes these limitations. Utility of Machine Learning Techniques employed include; Artificial Neural Networks, ANN (Regression/Modelling), Principal component Analysis, PCA (Classification) and Support Vector Machine SVM (Comparative study/Classification Machine Learning coupled with LIBS gives a state of the art analytic method. Utility of the technic in safeguards security and non-proliferation

LHC Report: machine development

CERN Multimedia

Rogelio Tomás García for the LHC team

2015-01-01

Machine development weeks are carefully planned in the LHC operation schedule to optimise and further study the performance of the machine. The first machine development session of Run 2 ended on Saturday, 25 July. Despite various hiccoughs, it allowed the operators to make great strides towards improving the long-term performance of the LHC.   The main goals of this first machine development (MD) week were to determine the minimum beam-spot size at the interaction points given existing optics and collimation constraints; to test new beam instrumentation; to evaluate the effectiveness of performing part of the beam-squeezing process during the energy ramp; and to explore the limits on the number of protons per bunch arising from the electromagnetic interactions with the accelerator environment and the other beam. Unfortunately, a series of events reduced the machine availability for studies to about 50%. The most critical issue was the recurrent trip of a sextupolar corrector circuit –...

Probability distribution of machining center failures

International Nuclear Information System (INIS)

Jia Yazhou; Wang Molin; Jia Zhixin

1995-01-01

Through field tracing research for 24 Chinese cutter-changeable CNC machine tools (machining centers) over a period of one year, a database of operation and maintenance for machining centers was built, the failure data was fitted to the Weibull distribution and the exponential distribution, the effectiveness was tested, and the failure distribution pattern of machining centers was found. Finally, the reliability characterizations for machining centers are proposed

Student Modeling and Machine Learning

OpenAIRE

Sison , Raymund; Shimura , Masamichi

1998-01-01

After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

The Newest Machine Material

International Nuclear Information System (INIS)

Seo, Yeong Seop; Choe, Byeong Do; Bang, Meong Sung

2005-08-01

This book gives descriptions of machine material with classification of machine material and selection of machine material, structure and connection of material, coagulation of metal and crystal structure, equilibrium diagram, properties of metal material, elasticity and plasticity, biopsy of metal, material test and nondestructive test. It also explains steel material such as heat treatment of steel, cast iron and cast steel, nonferrous metal materials, non metallic materials, and new materials.

Introduction to machine learning

OpenAIRE

Baştanlar, Yalın; Özuysal, Mustafa

2014-01-01

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning app...

Support vector machines applications

CERN Document Server

Guo, Guodong

2014-01-01

Support vector machines (SVM) have both a solid mathematical background and good performance in practical applications. This book focuses on the recent advances and applications of the SVM in different areas, such as image processing, medical practice, computer vision, pattern recognition, machine learning, applied statistics, business intelligence, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications, especially some recent advances.

Machinability of advanced materials

CERN Document Server

Davim, J Paulo

2014-01-01

Machinability of Advanced Materials addresses the level of difficulty involved in machining a material, or multiple materials, with the appropriate tooling and cutting parameters.  A variety of factors determine a material's machinability, including tool life rate, cutting forces and power consumption, surface integrity, limiting rate of metal removal, and chip shape. These topics, among others, and multiple examples comprise this research resource for engineering students, academics, and practitioners.

Battery recycling machine; Maquina recicladora de pilas

Energy Technology Data Exchange (ETDEWEB)

Higuera Gonzalez, R.M; Esquivel Montes, C.E; Perez Razo, E; Sanchez Guerrero, O.A. [Tecnologico de Estudios Superiores de Ixtapaluca, Ixtapaluca, Estado de Mexico (Mexico)

2013-03-15

Batteries pollute the environment and therefore require special treatment or confine recycling in appropriate places, Mexico only has places for confining the batteries and send them to other countries for recycling. The purpose of this project is to reduce the contamination of soil and create a culture for the recycling of batteries. The prototype performs the separation of metals and chemical residues, so that later they can be processed separately. The machine is divided into two parts, mechanics and electronics, the mechanical part was designed to disarm it for easy maintenance, another advantage in the field of electronics and security is to control the machine from a computer at a distance significantly reducing accidents. To automate the machine will use a PLC clock for easy programming. [Spanish] Las pilas contaminan el medio ambiente y por ello requieren un tratamiento especial de reciclaje o confinarlos en lugares adecuados, Mexico solo cuenta con lugares para confinar las pilas y mandarlas a otros paises para su reciclaje. El proposito de este proyecto es reducir la contaminacion del suelo y crear una cultura para el reciclaje de pilas. El prototipo realiza la separacion de metales y residuos quimicos, para que mas adelante se puedan procesar por separado. La maquina se divide en dos partes; la mecanica y la electronica, la parte mecanica fue disenada para desarmarse esto para su facil mantenimiento, otra de las ventajas en el campo de electronica y seguridad es poder controlar el prototipo desde una computadora, a una distancia considerable reduciendo asi los accidentes. Para automatizar la maquina se utilizo un reloj PLC por su facil programacion.

Flexible human machine interface for process diagnostics

International Nuclear Information System (INIS)

Reifman, J.; Graham, G.E.; Wei, T.Y.C.; Brown, K.R.; Chin, R.Y.

1996-01-01

A flexible human machine interface to design and display graphical and textual process diagnostic information is presented. The system operates on different computer hardware platforms, including PCs under MS Windows and UNIX Workstations under X-Windows, in a client-server architecture. The interface system is customized for specific process applications in a graphical user interface development environment by overlaying the image of the process piping and instrumentation diagram with display objects that are highlighted in color during diagnostic display. Customization of the system is presented for Commonwealth Edison's Braidwood PWR Chemical and Volume Control System with transients simulated by a full-scale operator-training simulator and diagnosed by a computer-based system

Nuclear reactor machine refuelling system

International Nuclear Information System (INIS)

Cashen, W.S.; Erwin, D.

1977-01-01

Part of an on-line fuelling machine for a CANDU pressure-tube reactor is described. The present invention provides a refuelling machine wherein the fuelling components, including the fuel carrier and the closure adapter, are positively positioned and retained within the machine magazine or positively secured to the machine charge tube head, and cannot be accidentally disengaged as in former practice. The positive positioning devices include an arcuate keeper plate. Simplified hooked fingers are used. (NDH)

Machine Translation Effect on Communication

DEFF Research Database (Denmark)

Jensen, Mika Yasuoka; Bjørn, Pernille

2011-01-01

Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...

Exploring the influence of constitutive models and associated parameters for the orthogonal machining of Ti6Al4V

Science.gov (United States)

Pervaiz, S.; Anwar, S.; Kannan, S.; Almarfadi, A.

2018-04-01

Ti6Al4V is known as difficult-to-cut material due to its inherent properties such as high hot hardness, low thermal conductivity and high chemical reactivity. Though, Ti6Al4V is utilized by industrial sectors such as aeronautics, energy generation, petrochemical and bio-medical etc. For the metal cutting community, competent and cost-effective machining of Ti6Al4V is a challenging task. To optimize cost and machining performance for the machining of Ti6Al4V, finite element based cutting simulation can be a very useful tool. The aim of this paper is to develop a finite element machining model for the simulation of Ti6Al4V machining process. The study incorporates material constitutive models namely Power Law (PL) and Johnson – Cook (JC) material models to mimic the mechanical behaviour of Ti6Al4V. The study investigates cutting temperatures, cutting forces, stresses, and plastic strains with respect to different PL and JC material models with associated parameters. In addition, the numerical study also integrates different cutting tool rake angles in the machining simulations. The simulated results will be beneficial to draw conclusions for improving the overall machining performance of Ti6Al4V.

Machining of Complex Sculptured Surfaces

CERN Document Server

2012-01-01

The machining of complex sculptured surfaces is a global technological topic in modern manufacturing with relevance in both industrialized and emerging in countries particularly within the moulds and dies sector whose applications include highly technological industries such as the automotive and aircraft industry. Machining of Complex Sculptured Surfaces considers new approaches to the manufacture of moulds and dies within these industries. The traditional technology employed in the manufacture of moulds and dies combined conventional milling and electro-discharge machining (EDM) but this has been replaced with  high-speed milling (HSM) which has been applied in roughing, semi-finishing and finishing of moulds and dies with great success. Machining of Complex Sculptured Surfaces provides recent information on machining of complex sculptured surfaces including modern CAM systems and process planning for three and five axis machining as well as explanations of the advantages of HSM over traditional methods ra...

Formal modeling of virtual machines

Science.gov (United States)

Cremers, A. B.; Hibbard, T. N.

1978-01-01

Systematic software design can be based on the development of a 'hierarchy of virtual machines', each representing a 'level of abstraction' of the design process. The reported investigation presents the concept of 'data space' as a formal model for virtual machines. The presented model of a data space combines the notions of data type and mathematical machine to express the close interaction between data and control structures which takes place in a virtual machine. One of the main objectives of the investigation is to show that control-independent data type implementation is only of limited usefulness as an isolated tool of program development, and that the representation of data is generally dictated by the control context of a virtual machine. As a second objective, a better understanding is to be developed of virtual machine state structures than was heretofore provided by the view of the state space as a Cartesian product.

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

Science.gov (United States)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

Permutation parity machines for neural synchronization

International Nuclear Information System (INIS)

Reyes, O M; Kopitzke, I; Zimmermann, K-H

2009-01-01

Synchronization of neural networks has been studied in recent years as an alternative to cryptographic applications such as the realization of symmetric key exchange protocols. This paper presents a first view of the so-called permutation parity machine, an artificial neural network proposed as a binary variant of the tree parity machine. The dynamics of the synchronization process by mutual learning between permutation parity machines is analytically studied and the results are compared with those of tree parity machines. It will turn out that for neural synchronization, permutation parity machines form a viable alternative to tree parity machines

Manipulator for plasma-assisted machining of components made of materials with low machinability

International Nuclear Information System (INIS)

Lyaoshchukov, M.M.; Agadzhanyan, R.A.

1984-01-01

The All-Union Scientific-Research and Technological Institute of Pump Engineering developed, and the ''Uralgidromash'' Production Association has adopted, a manipulator with remote control for the plasma-assisted machining (PAM) of components made of materials with low machinability. The manipulator is distinguished by its universal design and can be used for machining both external and internal surfaces of the bodies of revolution and also end faces and various curvilinear surfaces

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

Science.gov (United States)

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

29 CFR 1910.218 - Forging machines.

Science.gov (United States)

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Forging machines. 1910.218 Section 1910.218 Labor... OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.218 Forging machines. (a... other identifier, for the forging machine which was inspected. (ii) Scheduling and recording the...

The achievements of the Z-machine

International Nuclear Information System (INIS)

Larousserie, D.

2008-01-01

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Vector control of induction machines

CERN Document Server

Robyns, Benoit

2012-01-01

After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for

Finding protein sites using machine learning methods

Directory of Open Access Journals (Sweden)

Jaime Leonardo Bobadilla Molina

2003-07-01

Full Text Available The increasing amount of protein three-dimensional (3D structures determined by x-ray and NMR technologies as well as structures predicted by computational methods results in the need for automated methods to provide inital annotations. We have developed a new method for recognizing sites in three-dimensional protein structures. Our method is based on a previosly reported algorithm for creating descriptions of protein microenviroments using physical and chemical properties at multiple levels of detail. The recognition method takes three inputs: 1. A set of control nonsites that share some structural or functional role. 2. A set of control nonsites that lack this role. 3. A single query site. A support vector machine classifier is built using feature vectors where each component represents a property in a given volume. Validation against an independent test set shows that this recognition approach has high sensitivity and specificity. We also describe the results of scanning four calcium binding proteins (with the calcium removed using a three dimensional grid of probe points at 1.25 angstrom spacing. The system finds the sites in the proteins giving points at or near the blinding sites. Our results show that property based descriptions along with support vector machines can be used for recognizing protein sites in unannotated structures.

The Chainstitch Machine. Module 18.

Science.gov (United States)

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

This module on the chainstitch machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the chainstitch machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and…

Machine Shop Fundamentals: Part I.

Science.gov (United States)

Kelly, Michael G.; And Others

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

Machining dynamics fundamentals, applications and practices

CERN Document Server

Cheng, Kai

2008-01-01

Machining dynamics are vital to the performance of machine tools and machining processes in manufacturing. This book discusses the state-of-the-art applications, practices and research in machining dynamics. It presents basic theory, analysis and control methodology. It is useful for manufacturing engineers, supervisors, engineers and designers.

Investigation of permanent magnet machines for downhole applications: Design, prototype and testing of a flux-switching permanent magnet machine

Energy Technology Data Exchange (ETDEWEB)

Chen, Anyuan

2011-01-15

The current standard electrical downhole machine is the induction machine which is relatively inefficient. Permanent magnet (PM) machines, having higher efficiencies, higher torque densities and smaller volumes, have widely employed in industrial applications to replace conventional machines, but few have been developed for downhole applications due to the high ambient temperatures in deep wells and the low temperature stability of PM materials over time. Today, with the development of variable speed drives and the applications of high temperature magnet materials, it is increasingly interesting for oil and gas industries to develop PM machines for downhole applications. Recently, some PM machines applications have been presented for downhole applications, which are normally addressed on certain specific downhole case. In this thesis the focus has been put on the performance investigation of different PM machines for general downhole cases, in which the machine outer diameter is limited to be small by well size, while the machine axial length may be relatively long. The machine reliability is the most critical requirement while high torque density and high efficiency are also desirable. The purpose is to understand how the special constraints in downhole condition affect the performances of different machines. First of all, three basic machine concepts, which are the radial, axial and transverse flux machines, are studied in details by analytical method. Their torque density, efficiency, power factor and power capability are investigated with respect to the machine axial length and pole number. The presented critical performance comparisons of the machines provide an indication of machines best suitable with respect to performance and size for downhole applications. Conventional radial flux permanent magnet (RFPM) machines with the PMs on the rotor can provide high torque density and high efficiency. This type of machine has been suggested for several different

Electrical machining method of insulating ceramics

International Nuclear Information System (INIS)

Fukuzawa, Y.; Mohri, N.; Tani, T.

1999-01-01

This paper describes a new electrical discharge machining method for insulating ceramics using an assisting electrode with either a sinking electrical discharge machine or a wire electrical discharge machine. In this method, the metal sheet or mesh is attached to the ceramic surface as an assisting material for the discharge generation around the insulator surface. When the machining condition changes from the attached material to the workpiece, a cracked carbon layer is formed on the workpiece surface. As this layer has an electrical conductivity, electrical discharge occurs in working oil between the tool electrode and the surface of the workpiece. The carbon is formed from the working oil during this electrical discharge. Even after the material is machined, an electrical discharge occurs in the gap region between the tool electrode and the ceramic because an electrically conductive layer is generated continuously. Insulating ceramics can be machined by the electrical discharge machining method using the above mentioned surface modification phenomenon. In this paper the authors show a machined example demonstrating that the proposed method is available for machining a complex shape on insulating ceramics. Copyright (1999) AD-TECH - International Foundation for the Advancement of Technology Ltd

Mastering the non-equilibrium assembly and operation of molecular machines.

Science.gov (United States)

Pezzato, Cristian; Cheng, Chuyang; Stoddart, J Fraser; Astumian, R Dean

2017-09-18

In mechanically interlocked compounds, such as rotaxanes and catenanes, the molecules are held together by mechanical rather than chemical bonds. These compounds can be engineered to have several well-defined mechanical states by incorporating recognition sites between the different components. The rates of the transitions between the recognition sites can be controlled by introducing steric "speed bumps" or electrostatically switchable gates. A mechanism for the absorption of energy can also be included by adding photoactive, catalytically active, or redox-active recognition sites, or even charges and dipoles. At equilibrium, these Mechanically Interlocked Molecules (MIMs) undergo thermally activated transitions continuously between their different mechanical states where every transition is as likely as its microscopic reverse. External energy, for example, light, external modulation of the chemical and/or physical environment or catalysis of an exergonic reaction, drives the system away from equilibrium. The absorption of energy from these processes can be used to favour some, and suppress other, transitions so that completion of a mechanical cycle in a direction in which work is done on the environment - the requisite of a molecular machine - is more likely than completion in a direction in which work is absorbed from the environment. In this Tutorial Review, we discuss the different design principles by which molecular machines can be engineered to use different sources of energy to carry out self-organization and the performance of work in their environments.

Advanced SLARette delivery machine

International Nuclear Information System (INIS)

Bodner, R.R.

1995-01-01

SLARette 1 equipment, comprising of a SLARette Delivery Machine, SLAR Tools, SLAR power supplies and SLAR Inspection Systems was designed, developed and manufactured to service fuel channels of CANDU 6 stations during the regular yearly station outages. The Mark 2 SLARette Delivery Machine uses a Push Tube system to provide the axial and rotary movements of the SLAR Tool. The Push Tubes are operated remotely but must be attached and removed manually. Since this operation is performed at the Reactor face, there is radiation dose involved for the workers. An Advanced SLARette Delivery Machine which incorporates a computer controlled telescoping Ram in the place of the Push Tubes has been recently designed and manufactured. Utilization of the Advanced SLARette Delivery Machine significantly reduces the amount of radiation dose picked up by the workers because the need to have workers at the face of the Reactor during the SLARette operation is greatly reduced. This paper describes the design, development and manufacturing process utilized to produce the Advanced SLARette Delivery Machine and the experience gained during the Gentilly-2 NGS Spring outage. (author)

Modification of structural graphite machining

International Nuclear Information System (INIS)

Lavrenev, M.M.

1979-01-01

Studied are machining procedures for structural graphites (GMZ, MG, MG-1, PPG) most widely used in industry, of the article mass being about 50 kg. Presented are dependences necessary for the calculation of cross sections of chip suction tappers and duster pipelines in machine shops for structural graphite machining

Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

Directory of Open Access Journals (Sweden)

Dazi Li

2015-01-01

Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

Machines and Metaphors

Directory of Open Access Journals (Sweden)

Ángel Martínez García-Posada

2016-10-01

Full Text Available The edition La ley del reloj. Arquitectura, máquinas y cultura moderna (Cátedra, Madrid, 2016 registers the useful paradox of the analogy between architecture and technique. Its author, the architect Eduardo Prieto, also a philosopher, professor and writer, acknowledges the obvious distance from machines to buildings, so great that it can only be solved using strange comparisons, since architecture does not move nor are the machines habitable, however throughout the book, from the origin of the metaphor of the machine, with clarity in his essay and enlightening erudition, he points out with certainty some concomitances of high interest, drawing throughout history a beautiful cartography of the fruitful encounter between organics and mechanics.

OptiCentric lathe centering machine

Science.gov (United States)

Buß, C.; Heinisch, J.

2013-09-01

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

Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics

DEFF Research Database (Denmark)

Bratholm, Lars Andersen

to within 3 A. Furthermore, a fast quantum mechanics based chemical shift predictor was developed together with methodology for using chemical shifts in structure simulations. The developed predictor was used for renement of several protein structures and for reducing the computational cost of quantum...... mechanics / molecular mechanics (QM/MM) computations of chemical shieldings. Several improvements to the predictor is ongoing, where among other things, kernel based machine learning techniques have successfully been used to improve the quantum mechanical level of theory used in the predictions....

Machine Shop Grinding Machines.

Science.gov (United States)

Dunn, James

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

''Diagonalization'' of a compound Atwood machine

International Nuclear Information System (INIS)

Crawford, F.S.

1987-01-01

We consider a simple Atwood machine consisting of a massless frictionless pulley no. 0 supporting two masses m 1 and m 2 connected by a massless flexible string. We show that the string that supports massless pulley no. 0 ''thinks'' it is simply supporting a mass m 0 , with m 0 = 4m 1 m 2 /(m 1 +m 2 ). This result, together with Einstein's equivalence principle, allows us to solve easily those compound Atwood machines created by replacing one or both of m 1 and m 2 in machine no. 0 by an Atwood machine. We may then replacing the masses in these new machines by machines, etc. The complete solution can be written down immediately, without solving simultaneous equations. Finally we give the effective mass of an Atwood machine whose pulley has nonzero mass and moment of inertia

Adaptive Machine Aids to Learning.

Science.gov (United States)

Starkweather, John A.

With emphasis on man-machine relationships and on machine evolution, computer-assisted instruction (CAI) is examined in this paper. The discussion includes the background of machine assistance to learning, the current status of CAI, directions of development, the development of criteria for successful instruction, meeting the needs of users,…

Brain versus Machine Control.

Directory of Open Access Journals (Sweden)

Jose M Carmena

2004-12-01

Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface

Applicability of Machine-Learning Enabled LIBS in Post Irradiation Nuclear Forensic Analysis of High Level Nuclear Waste

International Nuclear Information System (INIS)

Onkongi, J.; Maina, D.; Angeyo, H. K.

2017-01-01

Nuclear Forensics seeks Information to determine; Chemical Composition, Routes of transit, Origin (Provenance) and Intended use. Post Irradiation/Post detonation NF In a post-detonation event could you get clues/signatures from glass debris, minute sample sizes? Nuclear Forensic Technique Should be State-of -the art that is Rapid, Non-invasive, Remote ability and Non-destructive. Laser Induced Breakdown Spectroscopy (LIBS) unlike other Analytic Techniques that require tedious sample preparations such as Dissolution, digestion & matrix removal, which generate additional nuclear wastes that require proper Procedures for handling, storage & ultimate disposal, LIBS overcomes these limitations. Utility of Machine Learning Techniques employed include; Artificial Neural Networks, ANN (Regression/Modelling), Principal component Analysis, PCA (Classification) and Support Vector Machine SVM (Comparative study/Classification Machine Learning coupled with LIBS gives a state of the art analytic method. Utility of the technic in safeguards security and non-proliferation

5-axes modular CNC machining center

Directory of Open Access Journals (Sweden)

Breaz Radu-Eugen

2017-01-01

Full Text Available The paper presents the development of a 5-axes CNC machining center. The main goal of the machine was to provide the students a practical layout for training in advanced CAM techniques. The mechanical structure of the machine was built in a modular way by a specialized company, which also implemented the CNC controller. The authors of this paper developed the geometric and kinematic model of the CNC machining center and the post-processor, in order to use the machine in a CAM environment.

Anisotropic wetting characteristics versus roughness on machined surfaces of hydrophilic and hydrophobic materials

International Nuclear Information System (INIS)

Liang, Yande; Shu, Liming; Natsu, Wataru; He, Fuben

2015-01-01

Graphical abstract: - Highlights: • The aim is to investigate the influence of roughness on anisotropic wetting on machined surfaces. • The relationship between roughness and anisotropic wetting is modeled by thermodynamical analysis. • The effect of roughness on anisotropic wetting on hydrophilic materials is stronger than that on hydrophobic materials. • The energy barrier existing in the direction perpendicular to the lay is one of the main reasons for the anisotropic wetting. • The contact angle in the parallel direction is larger than that in the perpendicular direction. - Abstract: Anisotropic wetting of machined surfaces is widely applied in industries which can be greatly affected by roughness and solid's chemical properties. However, there has not been much work on it. A free-energy thermodynamic model is presented by analyzing geometry morphology of machined surfaces (2-D model surfaces), which demonstrates the influence of roughness on anisotropic wetting. It can be concluded that the energy barrier is one of the main reasons for the anisotropic wetting existing in the direction perpendicular to the lay. In addition, experiments in investigating anisotropic wetting, which was characterized by the static contact angle and droplet's distortion, were performed on machined surfaces with different roughness on hydrophilic and hydrophobic materials. The droplet's anisotropy found on machined surfaces increased with mean slope of roughness profile Kr. It indicates that roughness on anisotropic wetting on hydrophilic materials has a stronger effect than that on hydrophobic materials. Furthermore, the contact angles predicted by the model are basically consistent with the experimentally ones

15 CFR 5.5 - Vending machines.

Science.gov (United States)

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Vending machines. 5.5 Section 5.5... machines. (a) The income from any vending machines which are located within reasonable proximity to and are... shall be assigned to the operator of such stand. (b) If a vending machine vends articles of a type...

An art history of machines?

Directory of Open Access Journals (Sweden)

Daniel Bridgman

2016-12-01

Full Text Available A toast offered in honor of Donald Preziosi on the cusp of his seventy-fifth birthday, this essay considers a range of machine metaphors, their art historical settings, and their implications. Addressing the mythography of Daedalus and his wonder machines in relation to art history’s machinic enterprises, an ancient art-archaeology seminar Preziosi directed at UCLA (in 1988 and the book, Rethinking Art History: Meditations on a Coy Science (1989 form the focus of my thinking about Preziosi’s work. At issue across the essay is the work of recursion, when machines make machines and in so doing create a recessive subjectivity for the maker. The essay ends with the speculation that art history’s disciplinary machinery may owe its generative strength to a perpetual need for replacement parts.

Machinability of Stellite 6 hardfacing

Directory of Open Access Journals (Sweden)

Dudzinski D.

2010-06-01

Full Text Available This paper reports some experimental findings concerning the machinability at high cutting speed of nickel-base weld-deposited hardfacings for the manufacture of hot tooling. The forging work involves extreme impacts, forces, stresses and temperatures. Thus, mould dies must be extremely resistant. The aim of the project is to create a rapid prototyping process answering to forging conditions integrating a Stellite 6 hardfacing deposed PTA process. This study talks about the dry machining of the hardfacing, using a two tips machining tool and a high speed milling machine equipped by a power consumption recorder Wattpilote. The aim is to show the machinability of the hardfacing, measuring the power and the tip wear by optical microscope and white light interferometer, using different strategies and cutting conditions.

Toroidal helical quartz forming machine

International Nuclear Information System (INIS)

Hanks, K.W.; Cole, T.R.

1977-01-01

The Scyllac fusion experimental machine used 10 cm diameter smooth bore discharge tubes formed into a simple toroidal shape prior to 1974. At about that time, it was discovered that a discharge tube was required to follow the convoluted shape of the load coil. A machine was designed and built to form a fused quartz tube with a toroidal shape. The machine will accommodate quartz tubes from 5 cm to 20 cm diameter forming it into a 4 m toroidal radius with a 1 to 5 cm helical displacement. The machine will also generate a helical shape on a linear tube. Two sets of tubes with different helical radii and wavelengths have been successfully fabricated. The problems encountered with the design and fabrication of this machine are discussed

Influence of chemical pretreatment of hard metal substrates for diamond deposition

International Nuclear Information System (INIS)

Buck, V.; Kluwe, H.; Schmiler, B.; Deuerler, F.

2001-01-01

Diamond coated cutting tools are of increasing importance in the fields of high speed cutting, dry machining or machining of special materials such as metal-matrix-composites. A well known problem is the poor adhesion of diamond films on hard metals due to the Co- or Ni-binder that catalyzes the formation of graphite. Several methods - such as the application of intermediate layers or mechanical or chemical pretreatment of the hard metal substrate - have been developed to overcome this effect. Usually chemical pretreatment is used in order to reduce the concentration of binder phase on the surface that is to be coated. Surprisingly pretreatment with agents such as Murakami's solution result in improved adhesion and nucleation of diamond films while the concentration of the binder phase on the surface is enhanced. This 'contradiction' can be explained by proving that the surface is converted into a very thin oxide/hydroxide film. (author)

Determination of electroless deposition by chemical nickeling

Directory of Open Access Journals (Sweden)

M. Badida

2013-07-01

Full Text Available Increasing of technical level and reliability of machine products in compliance with the economical and ecological terms belongs to the main trends of the industrial development. During the utilisation of these products there arise their each other contacts and the interaction with the environment. That is the reason for their surface degradation by wear effect, corrosion and other influences. The chemical nickel-plating allows autocatalytic deposition of nickel from water solutions in the form of coherent, technically very profitable coating without usage of external source of electric current. The research was aimed at evaluating the surface changes after chemical nickel-plating at various changes of technological parameters.

Decomposition of the compound Atwood machine

Science.gov (United States)

Lopes Coelho, R.

2017-11-01

Non-standard solving strategies for the compound Atwood machine problem have been proposed. The present strategy is based on a very simple idea. Taking an Atwood machine and replacing one of its bodies by another Atwood machine, we have a compound machine. As this operation can be repeated, we can construct any compound Atwood machine. This rule of construction is transferred to a mathematical model, whereby the equations of motion are obtained. The only difference between the machine and its model is that instead of pulleys and bodies, we have reference frames that move solidarily with these objects. This model provides us with the accelerations in the non-inertial frames of the bodies, which we will use to obtain the equations of motion. This approach to the problem will be justified by the Lagrange method and exemplified by machines with six and eight bodies.

A Peer-Reviewed Journal about Machine Research

OpenAIRE

Cox, G; Ganesh, MI; Gil-Fournier, A; Herrie, MB; Hill, J; House, B; Jones, N; Skinner, S; Young, D; Anon

2017-01-01

Edited by Christian Ulrik Andersen and Geoff Cox This publication is about MACHINE RESEARCH – research on machines, research with machines, and research as a machine. It thus explores machinic perspectives to suggest a situation where the humanities are put into a critical perspective by machine driven ecologies, ontologies and epistemologies of thinking and acting. It aims to engage research and artistic practice that takes into account the new materialist conditions implied by nonhuman t...

The learning machine in quantitative chemical analysis : Part I. Anodic Stripping Voltammetry of Cadmium, Lead and Thallium

NARCIS (Netherlands)

Bos, M.; Jasink, G.

1978-01-01

The linear learning machine method was applied to the determination of cadmium, lead and thallium down to 10-8 M by anodic stripping voltammetry at a hanging mercury drop electrode. With a total of three trained multicategory classifiers, concentrations of Cd, Pb and Tl could be predicted with an

Viscoelastic machine elements elastomers and lubricants in machine systems

CERN Document Server

MOORE, D F

2015-01-01

Viscoelastic Machine Elements, which encompass elastomeric elements (rubber-like components), fluidic elements (lubricating squeeze films) and their combinations, are used for absorbing vibration, reducing friction and improving energy use. Examplesinclude pneumatic tyres, oil and lip seals, compliant bearings and races, and thin films. This book sets out to show that these elements can be incorporated in machine analysis, just as in the case of conventional elements (e.g. gears, cogs, chaindrives, bearings). This is achieved by introducing elementary theory and models, by describing new an

Teletherapy machine

International Nuclear Information System (INIS)

Panyam, Vinatha S.; Rakshit, Sougata; Kulkarni, M.S.; Pradeepkumar, K.S.

2017-01-01

Radiation Standards Section (RSS), RSSD, BARC is the national metrology institute for ionizing radiation. RSS develops and maintains radiation standards for X-ray, beta, gamma and neutron radiations. In radiation dosimetry, traceability, accuracy and consistency of radiation measurements is very important especially in radiotherapy where the success of patient treatment is dependent on the accuracy of the dose delivered to the tumour. Cobalt teletherapy machines have been used in the treatment of cancer since the early 1950s and India had its first cobalt teletherapy machine installed at the Cancer Institute, Chennai in 1956

Creativity in Machine Learning

OpenAIRE

Thoma, Martin

2016-01-01

Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

The Complexity of Abstract Machines

Directory of Open Access Journals (Sweden)

Beniamino Accattoli

2017-01-01

Full Text Available The lambda-calculus is a peculiar computational model whose definition does not come with a notion of machine. Unsurprisingly, implementations of the lambda-calculus have been studied for decades. Abstract machines are implementations schema for fixed evaluation strategies that are a compromise between theory and practice: they are concrete enough to provide a notion of machine and abstract enough to avoid the many intricacies of actual implementations. There is an extensive literature about abstract machines for the lambda-calculus, and yet—quite mysteriously—the efficiency of these machines with respect to the strategy that they implement has almost never been studied. This paper provides an unusual introduction to abstract machines, based on the complexity of their overhead with respect to the length of the implemented strategies. It is conceived to be a tutorial, focusing on the case study of implementing the weak head (call-by-name strategy, and yet it is an original re-elaboration of known results. Moreover, some of the observation contained here never appeared in print before.

On-machine measurement of a slow slide servo diamond-machined 3D microstructure with a curved substrate

International Nuclear Information System (INIS)

Zhu, Wu-Le; Yang, Shunyao; Ju, Bing-Feng; Jiang, Jiacheng; Sun, Anyu

2015-01-01

A scanning tunneling microscope-based multi-axis measuring system is specially developed for the on-machine measurement of three-dimensional (3D) microstructures, to address the quality control difficulty with the traditional off-line measurement process. A typical 3D microstructure of the curved compound eye was diamond-machined by the slow slide servo technique, and then the whole surface was on-machine scanned three-dimensionally based on the tip-tracking strategy by utilizing a spindle, two linear motion stages, and an additional rotary stage. The machined surface profile and its shape deviation were accurately measured on-machine. The distortion of imaged ommatidia on the curved substrate was distinctively evaluated based on the characterized points extracted from the measured surface. Furthermore, the machining errors were investigated in connection with the on-machine measured surface and its characteristic parameters. Through experiments, the proposed measurement system is demonstrated to feature versatile on-machine measurement of 3D microstructures with a curved substrate, which is highly meaningful for quality control in the fabrication field. (paper)

An asymptotical machine

Science.gov (United States)

Cristallini, Achille

2016-07-01

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

Apparel Manufacturing (Course Outline), Industrial Single Needle Machines and Machine Practice: 9377.02.

Science.gov (United States)

Dade County Public Schools, Miami, FL.

This course includes a study of the industrial single needle machine, its principal parts, general care, threading, and basic skills in machine practice. Instructional materials include films, illustration, information sheets, and other materials. (CK)

Comparison Between a Reference Torque Standard Machine and a Deadweight Torque Standard Machine to BE Used in Torque Calibration

Science.gov (United States)

Meng, Feng; Zhang, Zhimin; Lin, Jing

The paper describes the reference torque standard machine with high accuracy and multifunction, developed by our institute, and introduces the structure and working principle of this machine. It has three main functions. The first function is the hydraulic torque wrench calibration function. The second function is torque multiply calibration function. The third function is reference torque standard machine function. We can calibrate the torque multipliers, hydraulic wrenches and transducers by this machine. A comparison experiment has been done between this machine and a deadweight torque standard machine. The consistency between the 30 kNm reference torque machine and the 2000 Nm dead-weight torque standard machine under the claimed uncertainties was verified.

Effect of machining fluid on the process performance of wire electrical discharge machining of nanocomposite ceramic

Directory of Open Access Journals (Sweden)

Zhang Chengmao

2015-01-01

Full Text Available Wire electric discharge machining (WEDM promise to be effective and economical techniques for the production of tools and parts from conducting ceramic blanks. However, the manufacturing of nanocomposite ceramics blanks with these processes is a long and costly process. This paper presents a new process of machining nanocomposite ceramics using WEDM. WEDM uses water based emulsion, polyvinyl alcohol and distilled water as the machining fluid. Machining fluid is a primary factor that affects the material removal rate and surface quality of WEDM. The effects of emulsion concentration, polyvinyl alcohol concentration and distilled water of the machining fluid on the process performance have been investigated.

A document processing pipeline for annotating chemical entities in scientific documents.

Science.gov (United States)

Campos, David; Matos, Sérgio; Oliveira, José L

2015-01-01

The recognition of drugs and chemical entities in text is a very important task within the field of biomedical information extraction, given the rapid growth in the amount of published texts (scientific papers, patents, patient records) and the relevance of these and other related concepts. If done effectively, this could allow exploiting such textual resources to automatically extract or infer relevant information, such as drug profiles, relations and similarities between drugs, or associations between drugs and potential drug targets. The objective of this work was to develop and validate a document processing and information extraction pipeline for the identification of chemical entity mentions in text. We used the BioCreative IV CHEMDNER task data to train and evaluate a machine-learning based entity recognition system. Using a combination of two conditional random field models, a selected set of features, and a post-processing stage, we achieved F-measure results of 87.48% in the chemical entity mention recognition task and 87.75% in the chemical document indexing task. We present a machine learning-based solution for automatic recognition of chemical and drug names in scientific documents. The proposed approach applies a rich feature set, including linguistic, orthographic, morphological, dictionary matching and local context features. Post-processing modules are also integrated, performing parentheses correction, abbreviation resolution and filtering erroneous mentions using an exclusion list derived from the training data. The developed methods were implemented as a document annotation tool and web service, freely available at http://bioinformatics.ua.pt/becas-chemicals/.

A reversible, unidirectional molecular rotary motor driven by chemical energy

NARCIS (Netherlands)

Fletcher, SP; Dumur, F; Pollard, MM; Feringa, BL

2005-01-01

With the long-term goal of producing nanometer-scale machines, we describe here the unidirectional rotary motion of a synthetic molecular structure fueled by chemical conversions. The basis of the rotation is the movement,of a phenyl rotor relative to a naphthyl stator about a single bond axle. The

Singer CNC sewing and embroidery machine

Directory of Open Access Journals (Sweden)

Lokodi Zsolt

2011-12-01

Full Text Available This paper presents the adaptation of a classic foot pedal operated Singer sewing machine to a computerized numerical control (CNC sewing and embroidery machine. This machine is composed of a Singer sewing machine and a two-degrees-of-freedom XY stage designed specifically for this application. The whole system is controlled from a PC using adequate CNC control software.

Automating horizontal boring and milling machine

International Nuclear Information System (INIS)

Naqvi, S.A.R.; Mahmood, T.; Choudhry, M.A.; Hanif, A.

2012-01-01

Aiming at the requirements of modification for many old import machine tools in industry, the schemes suited to the renovation are presented in this paper. A horizontal boring and milling machine (HBM) involved in machining of tank Al-Khalid has been modified using Mitsubishi FX-1N and FX-2N PLC. The developed software is for control of all the functions of the said machine. These functions include power on/off oil pump, spindle rotation and machine movement in all axes. All the decisions required by the machine for actuation of instructions are based on the data acquired from the control panel, timers and limit switches. Also the developed software minimize the down time, safety of operator and error free actuation of instructions. (author)

Molecular machines with bio-inspired mechanisms.

Science.gov (United States)

Zhang, Liang; Marcos, Vanesa; Leigh, David A

2018-02-26

The widespread use of molecular-level motion in key natural processes suggests that great rewards could come from bridging the gap between the present generation of synthetic molecular machines-which by and large function as switches-and the machines of the macroscopic world, which utilize the synchronized behavior of integrated components to perform more sophisticated tasks than is possible with any individual switch. Should we try to make molecular machines of greater complexity by trying to mimic machines from the macroscopic world or instead apply unfamiliar (and no doubt have to discover or invent currently unknown) mechanisms utilized by biological machines? Here we try to answer that question by exploring some of the advances made to date using bio-inspired machine mechanisms.

Foreign Language Translation of Chemical Nomenclature by Computer

Science.gov (United States)

2009-01-01

Chemical compound names remain the primary method for conveying molecular structures between chemists and researchers. In research articles, patents, chemical catalogues, government legislation, and textbooks, the use of IUPAC and traditional compound names is universal, despite efforts to introduce more machine-friendly representations such as identifiers and line notations. Fortunately, advances in computing power now allow chemical names to be parsed and generated (read and written) with almost the same ease as conventional connection tables. A significant complication, however, is that although the vast majority of chemistry uses English nomenclature, a significant fraction is in other languages. This complicates the task of filing and analyzing chemical patents, purchasing from compound vendors, and text mining research articles or Web pages. We describe some issues with manipulating chemical names in various languages, including British, American, German, Japanese, Chinese, Spanish, Swedish, Polish, and Hungarian, and describe the current state-of-the-art in software tools to simplify the process. PMID:19239237

Model-based machine learning.

Science.gov (United States)

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Reactor refueling machine simulator

International Nuclear Information System (INIS)

Rohosky, T.L.; Swidwa, K.J.

1987-01-01

This patent describes in combination: a nuclear reactor; a refueling machine having a bridge, trolley and hoist each driven by a separate motor having feedback means for generating a feedback signal indicative of movement thereof. The motors are operable to position the refueling machine over the nuclear reactor for refueling the same. The refueling machine also has a removable control console including means for selectively generating separate motor signals for operating the bridge, trolley and hoist motors and for processing the feedback signals to generate an indication of the positions thereof, separate output leads connecting each of the motor signals to the respective refueling machine motor, and separate input leads for connecting each of the feedback means to the console; and a portable simulator unit comprising: a single simulator motor; a single simulator feedback signal generator connected to the simulator motor for generating a simulator feedback signal in response to operation of the simulator motor; means for selectively connecting the output leads of the console to the simulator unit in place of the refueling machine motors, and for connecting the console input leads to the simulator unit in place of the refueling machine motor feedback means; and means for driving the single simulator motor in response to any of the bridge, trolley or hoist motor signals generated by the console and means for applying the simulator feedback signal to the console input lead associated with the motor signal being generated by the control console

The Bearingless Electrical Machine

Science.gov (United States)

Bichsel, J.

1992-01-01

Electromagnetic bearings allow the suspension of solids. For rotary applications, the most important physical effect is the force of a magnetic circuit to a high permeable armature, called the MAXWELL force. Contrary to the commonly used MAXWELL bearings, the bearingless electrical machine will take advantage of the reaction force of a conductor carrying a current in a magnetic field. This kind of force, called Lorentz force, generates the torque in direct current, asynchronous and synchronous machines. The magnetic field, which already exists in electrical machines and helps to build up the torque, can also be used for the suspension of the rotor. Besides the normal winding of the stator, a special winding was added, which generates forces for levitation. So a radial bearing, which is integrated directly in the active part of the machine, and the motor use the laminated core simultaneously. The winding was constructed for the levitating forces in a special way so that commercially available standard ac inverters for drives can be used. Besides wholly magnetic suspended machines, there is a wide range of applications for normal drives with ball bearings. Resonances of the rotor, especially critical speeds, can be damped actively.

High-pressure coolant effect on the surface integrity of machining titanium alloy Ti-6Al-4V: a review

Science.gov (United States)

Liu, Wentao; Liu, Zhanqiang

2018-03-01

Machinability improvement of titanium alloy Ti-6Al-4V is a challenging work in academic and industrial applications owing to its low thermal conductivity, low elasticity modulus and high chemical affinity at high temperatures. Surface integrity of titanium alloys Ti-6Al-4V is prominent in estimating the quality of machined components. The surface topography (surface defects and surface roughness) and the residual stress induced by machining Ti-6Al-4V occupy pivotal roles for the sustainability of Ti-6Al-4V components. High-pressure coolant (HPC) is a potential choice in meeting the requirements for the manufacture and application of Ti-6Al-4V. This paper reviews the progress towards the improvements of Ti-6Al4V surface integrity under HPC. Various researches of surface integrity characteristics have been reported. In particularly, surface roughness, surface defects, residual stress as well as work hardening are investigated in order to evaluate the machined surface qualities. Several coolant parameters (including coolant type, coolant pressure and the injection position) deserve investigating to provide the guidance for a satisfied machined surface. The review also provides a clear roadmap for applications of HPC in machining Ti-6Al4V. Experimental studies and analysis are reviewed to better understand the surface integrity under HPC machining process. A distinct discussion has been presented regarding the limitations and highlights of the prospective for machining Ti-6Al4V under HPC.

Quantum cloning machines and the applications

Energy Technology Data Exchange (ETDEWEB)

Fan, Heng, E-mail: hfan@iphy.ac.cn [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Collaborative Innovation Center of Quantum Matter, Beijing 100190 (China); Wang, Yi-Nan; Jing, Li [School of Physics, Peking University, Beijing 100871 (China); Yue, Jie-Dong [Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu [School of Physics, Peking University, Beijing 100871 (China)

2014-11-20

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results.

Quantum cloning machines and the applications

International Nuclear Information System (INIS)

Fan, Heng; Wang, Yi-Nan; Jing, Li; Yue, Jie-Dong; Shi, Han-Duo; Zhang, Yong-Liang; Mu, Liang-Zhu

2014-01-01

No-cloning theorem is fundamental for quantum mechanics and for quantum information science that states an unknown quantum state cannot be cloned perfectly. However, we can try to clone a quantum state approximately with the optimal fidelity, or instead, we can try to clone it perfectly with the largest probability. Thus various quantum cloning machines have been designed for different quantum information protocols. Specifically, quantum cloning machines can be designed to analyze the security of quantum key distribution protocols such as BB84 protocol, six-state protocol, B92 protocol and their generalizations. Some well-known quantum cloning machines include universal quantum cloning machine, phase-covariant cloning machine, the asymmetric quantum cloning machine and the probabilistic quantum cloning machine. In the past years, much progress has been made in studying quantum cloning machines and their applications and implementations, both theoretically and experimentally. In this review, we will give a complete description of those important developments about quantum cloning and some related topics. On the other hand, this review is self-consistent, and in particular, we try to present some detailed formulations so that further study can be taken based on those results

EDM machinability of SiCw/Al composites

Science.gov (United States)

Ramulu, M.; Taya, M.

1989-01-01

Machinability of high temperature composites was investigated. Target materials, 15 and 25 vol pct SiC whisker-2124 aluminum composites, were machined by electrodischarge sinker machining and diamond saw. The machined surfaces of these metal matrix composites were examined by SEM and profilometry to determine the surface finish. Microhardness measurements were also performed on the as-machined composites.

Machine learning and medical imaging

CERN Document Server

Shen, Dinggang; Sabuncu, Mert

2016-01-01

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, a...

Fundamentals of machine design

CERN Document Server

Karaszewski, Waldemar

2011-01-01

A forum of researchers, educators and engineers involved in various aspects of Machine Design provided the inspiration for this collection of peer-reviewed papers. The resultant dissemination of the latest research results, and the exchange of views concerning the future research directions to be taken in this field will make the work of immense value to all those having an interest in the topics covered. The book reflects the cooperative efforts made in seeking out the best strategies for effecting improvements in the quality and the reliability of machines and machine parts and for extending

Machine Learning for Hackers

CERN Document Server

Conway, Drew

2012-01-01

If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation. Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyz

Machine Learning for Medical Imaging.

Science.gov (United States)

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

Failure Identification of Hacksaw Machine REMOR 400

International Nuclear Information System (INIS)

Paidjo; Abdul Hafid; Sagino

2007-01-01

REMOR 400 Hack sawing machine is one of machines type has been old age. For arrange of cutting pressure and repeat lifting load after cutting process by using the hydraulic system. Beside of worn-out of hacksaw blade, failure cutting earn also because of leakage from the hydraulic system of machine. Leakage of hydraulic system occurs because of over load factor using or aging. Base on inspection result, hacksaw machine REMOR 400 fault on hydraulic system in the 2006 year. This matter will be seen from its seal brittle from the machine. For activate to return machine so much replacement repeat the seals used by machine. (author)

Permutation parity machines for neural cryptography.

Science.gov (United States)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-06-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Permutation parity machines for neural cryptography

International Nuclear Information System (INIS)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-01-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

High-throughput screening of chemicals as functional ...

Science.gov (United States)

Identifying chemicals that provide a specific function within a product, yet have minimal impact on the human body or environment, is the goal of most formulation chemists and engineers practicing green chemistry. We present a methodology to identify potential chemical functional substitutes from large libraries of chemicals using machine learning based models. We collect and analyze publicly available information on the function of chemicals in consumer products or industrial processes to identify a suite of harmonized function categories suitable for modeling. We use structural and physicochemical descriptors for these chemicals to build 41 quantitative structure–use relationship (QSUR) models for harmonized function categories using random forest classification. We apply these models to screen a library of nearly 6400 chemicals with available structure information for potential functional substitutes. Using our Functional Use database (FUse), we could identify uses for 3121 chemicals; 4412 predicted functional uses had a probability of 80% or greater. We demonstrate the potential application of the models to high-throughput (HT) screening for “candidate alternatives” by merging the valid functional substitute classifications with hazard metrics developed from HT screening assays for bioactivity. A descriptor set could be obtained for 6356 Tox21 chemicals that have undergone a battery of HT in vitro bioactivity screening assays. By applying QSURs, we wer

Machine assembly with a new material handling mechanism in the sewing machine

Directory of Open Access Journals (Sweden)

Umarova Z.M.

2017-05-01

Full Text Available the paper presents the dynamic model of the machine assembly with a recommended mechanism for moving material and the definition of the law of rails motion under various system parameters. The author has suggested the solution implemented by the system of differential equations numerically on the PC and the system describing the motion of the machine set. Recommended values ​​of the parameters of elastic links of material transfer mechanism have been obtained. The researcher has developed the methods of kinematic and dynamic analysis of the material transfer mechanism with elastic elements of the sewing machine and has approved the parameters and development of the design.

Abstract quantum computing machines and quantum computational logics

Science.gov (United States)

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

2016-06-01

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

Nanocomposites for Machining Tools

DEFF Research Database (Denmark)

Sidorenko, Daria; Loginov, Pavel; Mishnaevsky, Leon

2017-01-01

Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials...

Machine intelligence and signal processing

CERN Document Server

Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

2016-01-01

This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

Learning Activity Packets for Milling Machines. Unit I--Introduction to Milling Machines.

Science.gov (United States)

Oklahoma State Board of Vocational and Technical Education, Stillwater. Curriculum and Instructional Materials Center.

This learning activity packet (LAP) outlines the study activities and performance tasks covered in a related curriculum guide on milling machines. The course of study in this LAP is intended to help students learn to identify parts and attachments of vertical and horizontal milling machines, identify work-holding devices, state safety rules, and…

Human-machine interactions

Science.gov (United States)

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Electrical Discharge Machining (EDM: A Review

Directory of Open Access Journals (Sweden)

Asfana Banu

2016-09-01

Full Text Available Electro discharge machining (EDM process is a non-conventional and non-contact machining operation which is used in industry for high precision products. EDM is known for machining hard and brittle conductivematerials since it can melt any electrically conductive material regardless of its hardness. The workpiece machined by EDM depends on thermal conductivity, electrical resistivity, and melting points of the materials. The tool and the workpiece are adequately both immersed in a dielectric medium, such as, kerosene, deionised water or any other suitable fluid. This paper is reviewed comprehensively on types of EDM operation. A brief discussion is also done on the machining responses and mathematical modelling.

Fabrication Process for Machined and Shrink-Fitted Impactor-Type Liners for the LOS Alamos Hedp Program

Science.gov (United States)

Randolph, B.

2004-11-01

Composite liners have been fabricated for the Los Alamos liner-driven High Energy Density Physics (HEDP) experiments using impactors formed by physical vapor deposition, and by machining and shrink fitting. Chemical vapor deposition has been proposed for some ATLAS liner applications. This paper describes the processes used to fabricate machined and shrink-fitted impactors; these processes have been used for copper impactors in 1100 aluminum liners and for 6061 T-6 aluminum impactors in 1100 aluminum liners. The most successful processes have been largely empirically developed and rely upon a combination of shrink-fitting and light press fitting. The processes used to date will be described along with some considerations for future composite liners for the HEDP Program.

Human-machine interface upgrade

International Nuclear Information System (INIS)

Kropik, M.; Matejka, K.; Sklenka, L.; Chab, V.

2002-01-01

The article describes a new human-machine interface that was installed at the VR-1 training reactor. The human-machine interface upgrade was completed in the summer 2001. The interface was designed with respect to functional, ergonomic and aesthetic requirements. The interface is based on a personal computer equipped with two displays. One display enables alphanumeric communication between the reactor operator and the nuclear reactor I and C. The second display is a graphical one. It presents the status of the reactor, principal parameters (as power, period), control rods positions, course of the reactor power. Furthermore, it is possible to set parameters, to show the active core configuration, to perform reactivity calculations, etc. The software for the new human-machine interface was produced with the InTouch developing tool of the Wonder-Ware Company. It is possible to switch the language of the interface between Czech and English because of many foreign students and visitors to the reactor. Microcomputer based communication units with proper software were developed to connect the new human-machine interface with the present reactor I and C. The new human-machine interface at the VR-1 training reactor improves the comfort and safety of the reactor utilisation, facilitates experiments and training, and provides better support for foreign visitors. (orig.)

Game-powered machine learning.

Science.gov (United States)

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

Surface Nano Structures Manufacture Using Batch Chemical Processing Methods for Tooling Applications

DEFF Research Database (Denmark)

Tosello, Guido; Calaon, Matteo; Gavillet, J.

2011-01-01

The patterning of large surface areas with nano structures by using chemical batch processes to avoid using highenergy intensive nano machining processes was investigated. The capability of different surface treatment methods of creating micro and nano structured adaptable mould inserts for subse...

Finding New Perovskite Halides via Machine learning

Directory of Open Access Journals (Sweden)

Ghanshyam ePilania

2016-04-01

Full Text Available Advanced materials with improved properties have the potential to fuel future technological advancements. However, identification and discovery of these optimal materials for a specific application is a non-trivial task, because of the vastness of the chemical search space with enormous compositional and configurational degrees of freedom. Materials informatics provides an efficient approach towards rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning via building a support vector machine (SVM based classifier that uses elemental features (or descriptors to predict the formability of a given ABX3 halide composition (where A and B represent monovalent and divalent cations, respectively, and X is F, Cl, Br or I anion in the perovskite crystal structure. The classification model is built by learning from a dataset of 181 experimentally known ABX3 compounds. After exploring a wide range of features, we identify ionic radii, tolerance factor and octahedral factor to be the most important factors for the classification, suggesting that steric and geometric packing effects govern the stability of these halides. The trained and validated models then predict, with a high degree of confidence, several novel ABX3 compositions with perovskite crystal structure.

Finding New Perovskite Halides via Machine learning

Science.gov (United States)

Pilania, Ghanshyam; Balachandran, Prasanna V.; Kim, Chiho; Lookman, Turab

2016-04-01

Advanced materials with improved properties have the potential to fuel future technological advancements. However, identification and discovery of these optimal materials for a specific application is a non-trivial task, because of the vastness of the chemical search space with enormous compositional and configurational degrees of freedom. Materials informatics provides an efficient approach towards rational design of new materials, via learning from known data to make decisions on new and previously unexplored compounds in an accelerated manner. Here, we demonstrate the power and utility of such statistical learning (or machine learning) via building a support vector machine (SVM) based classifier that uses elemental features (or descriptors) to predict the formability of a given ABX3 halide composition (where A and B represent monovalent and divalent cations, respectively, and X is F, Cl, Br or I anion) in the perovskite crystal structure. The classification model is built by learning from a dataset of 181 experimentally known ABX3 compounds. After exploring a wide range of features, we identify ionic radii, tolerance factor and octahedral factor to be the most important factors for the classification, suggesting that steric and geometric packing effects govern the stability of these halides. The trained and validated models then predict, with a high degree of confidence, several novel ABX3 compositions with perovskite crystal structure.

X-ray evaluation of residual stress distributions within surface machined layer generated by surface machining and sequential welding

International Nuclear Information System (INIS)

Taniguchi, Yuu; Okano, Shigetaka; Mochizuki, Masahito

2017-01-01

The excessive tensile residual stress generated by welding after surface machining may be an important factor to cause stress corrosion cracking (SCC) in nuclear power plants. Therefore we need to understand and control the residual stress distribution appropriately. In this study, residual stress distributions within surface machined layer generated by surface machining and sequential welding were evaluated by X-ray diffraction method. Depth directional distributions were also investigated by electrolytic polishing. In addition, to consider the effect of work hardened layer on the residual stress distributions, we also measured full width at half maximum (FWHM) obtained from X-ray diffraction. Testing material was a low-carbon austenitic stainless steel type SUS316L. Test specimens were prepared by surface machining with different cutting conditions. Then, bead-on-plate welding under the same welding condition was carried out on the test specimens with different surface machined layer. As a result, the tensile residual stress generated by surface machining increased with increasing cutting speed and showed nearly uniform distributions on the surface. Furthermore, the tensile residual stress drastically decreased with increasing measurement depth within surface machined layer. Then, the residual stress approached 0 MPa after the compressive value showed. FWHM also decreased drastically with increasing measurement depth and almost constant value from a certain depth, which was almost equal regardless of the machining condition, within surface machined layer in all specimens. After welding, the transverse distribution of the longitudinal residual stress varied in the area apart from the weld center according to machining conditions and had a maximum value in heat affected zone. The magnitude of the maximum residual stress was almost equal regardless of the machining condition and decreased with increasing measurement depth within surface machined layer. Finally, the

Electromechanical model of machine for vibroabrasive treatment of machine parts

OpenAIRE

Gorbatiyk, Ruslan; Palamarchuk, Igor; Chubyk, Roman

2015-01-01

A lot of operations on trimming clean and finishing – stripping up treatment, first of all, removing of burrs, rounding and processing of borders, until recently time was carried out by hand, and hardly exposed to automation and became a serious obstacle in subsequent growth of the labor productivity. Machines with free kinematics connection between a tool and the treating parts is provided by the printing-down of all of the surface of the machine parts, that allows us to effectively treat bo...

Experimental Investigation – Magnetic Assisted Electro Discharge Machining

Science.gov (United States)

Kesava Reddy, Chirra; Manzoor Hussain, M.; Satyanarayana, S.; Krishna, M. V. S. Murali

2018-04-01

Emerging technology needs advanced machined parts with high strength and temperature resistance, high fatigue life at low production cost with good surface quality to fit into various industrial applications. Electro discharge machine is one of the extensively used machines to manufacture advanced machined parts which cannot be machined by other traditional machine with high precision and accuracy. Machining of DIN 17350-1.2080 (High Carbon High Chromium steel), using electro discharge machining has been discussed in this paper. In the present investigation an effort is made to use permanent magnet at various positions near the spark zone to improve surface quality of the machined surface. Taguchi methodology is used to obtain optimal choice for each machining parameter such as peak current, pulse duration, gap voltage and Servo reference voltage etc. Process parameters have significant influence on machining characteristics and surface finish. Improvement in surface finish is observed when process parameters are set at optimum condition under the influence of magnetic field at various positions.

Machine safety: proper safeguarding techniques.

Science.gov (United States)

Martin, K J

1992-06-01

1. OSHA mandates certain safeguarding of machinery to prevent accidents and protect machine operators. OSHA specifies moving parts that must be guarded and sets criteria for the guards. 2. A 1989 OSHA standard for lockout/tagout requires locking the energy source during maintenance, periodically inspecting for power transmission, and training maintenance workers. 3. In an amputation emergency, first aid for cardiopulmonary resuscitation, shock, and bleeding are the first considerations. The amputated part should be wrapped in moist gauze, placed in a sealed plastic bag, and placed in a container of 50% water and 50% ice for transport. 4. The role of the occupational health nurse in machine safety is to conduct worksite analyses to identify proper safeguarding and to communicate deficiencies to appropriate personnel; to train workers in safe work practices and observe compliance in the use of machine guards; to provide care to workers injured by machines; and to reinforce safe work practices among machine operators.

The deleuzian abstract machines

DEFF Research Database (Denmark)

Werner Petersen, Erik

2005-01-01

To most people the concept of abstract machines is connected to the name of Alan Turing and the development of the modern computer. The Turing machine is universal, axiomatic and symbolic (E.g. operating on symbols). Inspired by Foucault, Deleuze and Guattari extended the concept of abstract...

Man-machine interactions 3

CERN Document Server

Czachórski, Tadeusz; Kozielski, Stanisław

2014-01-01

Man-Machine Interaction is an interdisciplinary field of research that covers many aspects of science focused on a human and machine in conjunction.  Basic goal of the study is to improve and invent new ways of communication between users and computers, and many different subjects are involved to reach the long-term research objective of an intuitive, natural and multimodal way of interaction with machines.  The rapid evolution of the methods by which humans interact with computers is observed nowadays and new approaches allow using computing technologies to support people on the daily basis, making computers more usable and receptive to the user's needs.   This monograph is the third edition in the series and presents important ideas, current trends and innovations in  the man-machine interactions area.  The aim of this book is to introduce not only hardware and software interfacing concepts, but also to give insights into the related theoretical background. Reader is provided with a compilation of high...

The recycling through melting machining chips: preliminary results

Energy Technology Data Exchange (ETDEWEB)

Pereira, Luiz A.T.; Rossi, Jesualdo L., E-mail: luiz.atp@uol.com.br, E-mail: jelrossi@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil). Centro de Ciência e Tecnologia de Materiais

2017-07-01

PWR (Pressurized Water Reactor) reactors employ as nuclear fuel UO{sub 2} pellets packed in zirconium alloy tubes, called cladding. In the manufacture of the tubes, machining chips are generated which cannot be discarded, since the recycling of this material is strategic in terms of nuclear technology, legislation, economics and the environment. These nuclear alloys are very expensive and are not produced in Brazil and are imported for the manufacture of nuclear fuel. In this work, it will examined methods not yet studied to recycle Zircaloy chips using electron beam furnace in order to obtain ingots. In addition, it is intended to carry out the melting of new Zircaloy alloys, from the melting of zirconium sponge obtained in IPEN and imported and Zircaloy bars. The mechanical properties and the present phases of the material should be determined, as well as, the characterization of the microstructures by optical microscopy. This work, therefore, aims at the creation of a new line of research where methods will be approached to recycle the Zircaloy chips and to reduce in 30 times the volume by means of melting the enormous amount of material stored in the form of machining chips, being able to do others components for nuclear or chemical industry use, as well as conducting basic development research. (author)

Hydraulic Power Plant Machine Dynamic Diagnosis

Directory of Open Access Journals (Sweden)

Hans Günther Poll

2006-01-01

Full Text Available A method how to perform an entire structural and hydraulic diagnosis of prototype Francis power machines is presented and discussed in this report. Machine diagnosis of Francis units consists on a proper evaluation of acquired mechanical, thermal and hydraulic data obtained in different operating conditions of several rotary and non rotary machine components. Many different physical quantities of a Francis machine such as pressure, strains, vibration related data, water flow, air flow, position of regulating devices and displacements are measured in a synchronized way so that a relation of cause an effect can be developed for each operating condition and help one to understand all phenomena that are involved with such kind of machine. This amount of data needs to be adequately post processed in order to allow correct interpretation of the machine dynamics and finally these data must be compared with the expected calculated data not only to fine tuning the calculation methods but also to accomplish fully understanding of the influence of the water passages on such machines. The way how the power plant owner has to operate its Francis machines, many times also determined by a central dispatcher, has a high influence on the fatigue life time of the machine components. The diagnostic method presented in this report helps one to understand the importance of adequate operation to allow a low maintenance cost for the entire power plant. The method how to acquire these quantities is discussed in details together with the importance of correct sensor balancing, calibration and adequate correlation with the physical quantities. Typical results of the dynamic machine behavior, with adequate interpretation, obtained in recent measurement campaigns of some important hydraulic turbines were presented. The paper highlights the investigation focus of the hydraulic machine behavior and how to tailor the measurement strategy to accomplish all goals. Finally some

Towards Massive Machine Type Cellular Communications

OpenAIRE

Dawy, Zaher; Saad, Walid; Ghosh, Arunabha; Andrews, Jeffrey G.; Yaacoub, Elias

2015-01-01

Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters - often referred to as machine-to-machine (M2M) or machine-type communications (MTC) - introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently support...

Diamond turning machine controller implementation

Energy Technology Data Exchange (ETDEWEB)

Garrard, K.P.; Taylor, L.W.; Knight, B.F.; Fornaro, R.J.

1988-12-01

The standard controller for a Pnuemo ASG 2500 Diamond Turning Machine, an Allen Bradley 8200, has been replaced with a custom high-performance design. This controller consists of four major components. Axis position feedback information is provided by a Zygo Axiom 2/20 laser interferometer with 0.1 micro-inch resolution. Hardware interface logic couples the computers digital and analog I/O channels to the diamond turning machine`s analog motor controllers, the laser interferometer, and other machine status and control information. It also provides front panel switches for operator override of the computer controller and implement the emergency stop sequence. The remaining two components, the control computer hardware and software, are discussed in detail below.

Integrated Inverter For Driving Multiple Electric Machines

Science.gov (United States)

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

2006-04-04

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

Quantum Machine Learning

OpenAIRE

Romero García, Cristian

2017-01-01

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

Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

Science.gov (United States)

Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

2017-12-26

Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

49 CFR 173.174 - Refrigerating machines.

Science.gov (United States)

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Refrigerating machines. 173.174 Section 173.174 Transportation Other Regulations Relating to Transportation PIPELINE AND HAZARDOUS MATERIALS SAFETY... Refrigerating machines. A refrigerating machine assembled for shipment and containing 7 kg (15 pounds) or less...

Challenges for coexistence of machine to machine and human to human applications in mobile network

DEFF Research Database (Denmark)

Sanyal, R.; Cianca, E.; Prasad, Ramjee

2012-01-01

A key factor for the evolution of the mobile networks towards 4G is to bring to fruition high bandwidth per mobile node. Eventually, due to the advent of a new class of applications, namely, Machine-to-Machine, we foresee new challenges where bandwidth per user is no more the primal driver...... be evolved to address various nuances of the mobile devices used by man and machines. The bigger question is as follows. Is the state-of-the-art mobile network designed optimally to cater both the Human-to-Human and Machine-to-Machine applications? This paper presents the primary challenges....... As an immediate impact of the high penetration of M2M devices, we envisage a surge in the signaling messages for mobility and location management. The cell size will shrivel due to high tele-density resulting in even more signaling messages related to handoff and location updates. The mobile network should...

Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.

Science.gov (United States)

Hepworth, Philip J; Nefedov, Alexey V; Muchnik, Ilya B; Morgan, Kenton L

2012-08-07

Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide.

Optimization of pocket machining strategy in HSM

OpenAIRE

Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher

2012-01-01

International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...

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

Science.gov (United States)

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

2018-07-01

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

Machine learning with R cookbook

CERN Document Server

Chiu, Yu-Wei

2015-01-01

If you want to learn how to use R for machine learning and gain insights from your data, then this book is ideal for you. Regardless of your level of experience, this book covers the basics of applying R to machine learning through to advanced techniques. While it is helpful if you are familiar with basic programming or machine learning concepts, you do not require prior experience to benefit from this book.

Autocoding State Machine in Erlang

DEFF Research Database (Denmark)

Guo, Yu; Hoffman, Torben; Gunder, Nicholas

2008-01-01

This paper presents an autocoding tool suit, which supports development of state machine in a model-driven fashion, where models are central to all phases of the development process. The tool suit, which is built on the Eclipse platform, provides facilities for the graphical specification...... of a state machine model. Once the state machine is specified, it is used as input to a code generation engine that generates source code in Erlang....

Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.

Science.gov (United States)

Blasco, José; Munera, Sandra; Aleixos, Nuria; Cubero, Sergio; Molto, Enrique

Individual items of any agricultural commodity are different from each other in terms of colour, shape or size. Furthermore, as they are living thing, they change their quality attributes over time, thereby making the development of accurate automatic inspection machines a challenging task. Machine vision-based systems and new optical technologies make it feasible to create non-destructive control and monitoring tools for quality assessment to ensure adequate accomplishment of food standards. Such systems are much faster than any manual non-destructive examination of fruit and vegetable quality, thus allowing the whole production to be inspected with objective and repeatable criteria. Moreover, current technology makes it possible to inspect the fruit in spectral ranges beyond the sensibility of the human eye, for instance in the ultraviolet and near-infrared regions. Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. This chapter summarises the current state of the art in these techniques, starting with systems based on colour images for the inspection of conventional colour, shape or external defects and then goes on to consider recent developments in spectral image analysis for internal quality assessment or contaminant detection.

New tool holder design for cryogenic machining of Ti6Al4V

Science.gov (United States)

Bellin, Marco; Sartori, Stefano; Ghiotti, Andrea; Bruschi, Stefania

2017-10-01

The renewed demand of increasing the machinability of the Ti6Al4V titanium alloy to produce biomedical and aerospace parts working at high temperature has recently led to the application of low-temperature coolants instead of conventional cutting fluids to increase both the tool life and the machined surface integrity. In particular, the liquid nitrogen directed to the tool rake face has shown a great capability of reducing the temperature at the chip-tool interface, as well as the chemical interaction between the tool coating and the titanium to be machined, therefore limiting the tool crater wear, and improving, at the same time, the chip breakability. Furthermore, the nitrogen is a safe, non-harmful, non-corrosive, odorless, recyclable, non-polluting and abundant gas, characteristics that further qualify it as an environmental friendly coolant to be applied to machining processes. However, the behavior of the system composed by the tool and the tool holder, exposed to the cryogenics temperatures may represent a critical issue in order to obtain components within the required geometrical tolerances. On this basis, the paper aims at presenting the design of an innovative tool holder installed on a CNC lathe, which includes the cryogenic coolant provision system, and which is able to hinder the part possible distortions due to the liquid nitrogen adduction by stabilizing its dimensions through the use of heating cartridges and appropriate sensors to monitor the temperature evolution of the tool holder.

Radiolytic production of chemical fuels in fusion reactor systems

Energy Technology Data Exchange (ETDEWEB)

Fish, J D

1977-06-01

Miley's energy flow diagram for fusion reactor systems is extended to include radiolytic production of chemical fuel. Systematic study of the economics and the overall efficiencies of fusion reactor systems leads to a criterion for evaluating the potential of radiolytic production of chemical fuel as a means of enhancing the performance of a fusion reactor system. The ecumenicity of the schema is demonstrated by application to (1) tokamaks, (2) mirror machines, (3) theta-pinch reactors, (4) laser-heated solenoids, and (5) inertially confined, laser-pellet devices. Pure fusion reactors as well as fusion-fission hybrids are considered.

Radiolytic production of chemical fuels in fusion reactor systems

International Nuclear Information System (INIS)

Fish, J.D.

1977-06-01

Miley's energy flow diagram for fusion reactor systems is extended to include radiolytic production of chemical fuel. Systematic study of the economics and the overall efficiencies of fusion reactor systems leads to a criterion for evaluating the potential of radiolytic production of chemical fuel as a means of enhancing the performance of a fusion reactor system. The ecumenicity of the schema is demonstrated by application to (1) tokamaks, (2) mirror machines, (3) theta-pinch reactors, (4) laser-heated solenoids, and (5) inertially confined, laser-pellet devices. Pure fusion reactors as well as fusion-fission hybrids are considered

Finite Element Method in Machining Processes

CERN Document Server

Markopoulos, Angelos P

2013-01-01

Finite Element Method in Machining Processes provides a concise study on the way the Finite Element Method (FEM) is used in the case of manufacturing processes, primarily in machining. The basics of this kind of modeling are detailed to create a reference that will provide guidelines for those who start to study this method now, but also for scientists already involved in FEM and want to expand their research. A discussion on FEM, formulations and techniques currently in use is followed up by machining case studies. Orthogonal cutting, oblique cutting, 3D simulations for turning and milling, grinding, and state-of-the-art topics such as high speed machining and micromachining are explained with relevant examples. This is all supported by a literature review and a reference list for further study. As FEM is a key method for researchers in the manufacturing and especially in the machining sector, Finite Element Method in Machining Processes is a key reference for students studying manufacturing processes but al...

Superconducting three element synchronous ac machine

International Nuclear Information System (INIS)

Boyer, L.; Chabrerie, J.P.; Mailfert, A.; Renard, M.

1975-01-01

There is a growing interest in ac superconducting machines. Of several new concepts proposed for these machines in the last years one of the most promising seems to be the ''three elements'' concept which allows the cancellation of the torque acting on the superconducting field winding, thus overcoming some of the major contraints. This concept leads to a device of induction-type generator. A synchronous, three element superconducting ac machine is described, in which a room temperature, dc fed rotating winding is inserted between the superconducting field winding and the ac armature. The steady-state machine theory is developed, the flux linkages are established, and the torque expressions are derived. The condition for zero torque on the field winding, as well as the resulting electrical equations of the machine, are given. The theoretical behavior of the machine is studied, using phasor diagrams and assuming for the superconducting field winding either a constant current or a constant flux condition

Discovery of Intermetallic Compounds from Traditional to Machine-Learning Approaches.

Science.gov (United States)

Oliynyk, Anton O; Mar, Arthur

2018-01-16

Intermetallic compounds are bestowed by diverse compositions, complex structures, and useful properties for many materials applications. How metallic elements react to form these compounds and what structures they adopt remain challenging questions that defy predictability. Traditional approaches offer some rational strategies to prepare specific classes of intermetallics, such as targeting members within a modular homologous series, manipulating building blocks to assemble new structures, and filling interstitial sites to create stuffed variants. Because these strategies rely on precedent, they cannot foresee surprising results, by definition. Exploratory synthesis, whether through systematic phase diagram investigations or serendipity, is still essential for expanding our knowledge base. Eventually, the relationships may become too complex for the pattern recognition skills to be reliably or practically performed by humans. Complementing these traditional approaches, new machine-learning approaches may be a viable alternative for materials discovery, not only among intermetallics but also more generally to other chemical compounds. In this Account, we survey our own efforts to discover new intermetallic compounds, encompassing gallides, germanides, phosphides, arsenides, and others. We apply various machine-learning methods (such as support vector machine and random forest algorithms) to confront two significant questions in solid state chemistry. First, what crystal structures are adopted by a compound given an arbitrary composition? Initial efforts have focused on binary equiatomic phases AB, ternary equiatomic phases ABC, and full Heusler phases AB 2 C. Our analysis emphasizes the use of real experimental data and places special value on confirming predictions through experiment. Chemical descriptors are carefully chosen through a rigorous procedure called cluster resolution feature selection. Predictions for crystal structures are quantified by evaluating

Metabolic Profiling and Classification of Propolis Samples from Southern Brazil: An NMR-Based Platform Coupled with Machine Learning.

Science.gov (United States)

Maraschin, Marcelo; Somensi-Zeggio, Amélia; Oliveira, Simone K; Kuhnen, Shirley; Tomazzoli, Maíra M; Raguzzoni, Josiane C; Zeri, Ana C M; Carreira, Rafael; Correia, Sara; Costa, Christopher; Rocha, Miguel

2016-01-22

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching ∼90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Asymmetric quantum cloning machines

International Nuclear Information System (INIS)

Cerf, N.J.

1998-01-01

A family of asymmetric cloning machines for quantum bits and N-dimensional quantum states is introduced. These machines produce two approximate copies of a single quantum state that emerge from two distinct channels. In particular, an asymmetric Pauli cloning machine is defined that makes two imperfect copies of a quantum bit, while the overall input-to-output operation for each copy is a Pauli channel. A no-cloning inequality is derived, characterizing the impossibility of copying imposed by quantum mechanics. If p and p ' are the probabilities of the depolarizing channels associated with the two outputs, the domain in (√p,√p ' )-space located inside a particular ellipse representing close-to-perfect cloning is forbidden. This ellipse tends to a circle when copying an N-dimensional state with N→∞, which has a simple semi-classical interpretation. The symmetric Pauli cloning machines are then used to provide an upper bound on the quantum capacity of the Pauli channel of probabilities p x , p y and p z . The capacity is proven to be vanishing if (√p x , √p y , √p z ) lies outside an ellipsoid whose pole coincides with the depolarizing channel that underlies the universal cloning machine. Finally, the tradeoff between the quality of the two copies is shown to result from a complementarity akin to Heisenberg uncertainty principle. (author)

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

International Nuclear Information System (INIS)

Dastgir, G.

2012-01-01

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

48 CFR 908.7103 - Office machines.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 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...

20 CFR 368.3 - Vending machines.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Vending machines. 368.3 Section 368.3 Employees' Benefits RAILROAD RETIREMENT BOARD INTERNAL ADMINISTRATION, POLICY AND PROCEDURES PROHIBITION OF CIGARETTE SALES TO MINORS § 368.3 Vending machines. The sale of tobacco products in vending machines is...

Machine learning an artificial intelligence approach

CERN Document Server

Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

1983-01-01

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

Microsoft Azure machine learning

CERN Document Server

Mund, Sumit

2015-01-01

The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

Coil Optimization for HTS Machines

DEFF Research Database (Denmark)

Mijatovic, Nenad; Jensen, Bogi Bech; Abrahamsen, Asger Bech

An optimization approach of HTS coils in HTS synchronous machines (SM) is presented. The optimization is aimed at high power SM suitable for direct driven wind turbines applications. The optimization process was applied to a general radial flux machine with a peak air gap flux density of ~3T...... is suitable for which coil segment is presented. Thus, the performed study gives valuable input for the coil design of HTS machines ensuring optimal usage of HTS tapes....

vSphere virtual machine management

CERN Document Server

Fitzhugh, Rebecca

2014-01-01

This book follows a step-by-step tutorial approach with some real-world scenarios that vSphere businesses will be required to overcome every day. This book also discusses creating and configuring virtual machines and also covers monitoring virtual machine performance and resource allocation options. This book is for VMware administrators who want to build their knowledge of virtual machine administration and configuration. It's assumed that you have some experience with virtualization administration and vSphere.

Technology of magnetic abrasive finishing in machining of difficult-to-machine alloy complex surface

Directory of Open Access Journals (Sweden)

Fujian MA

2016-10-01

Full Text Available The technology of magnetic abrasive finishing is one of the important finishing technologies. Combining with low-frequency vibration and ultrasonic vibration, it can attain higher precision, quality and efficiency. The characteristics and the related current research of magnetic abrasive finishing, vibration assisted magnetic abrasive finishing and ultrasonic assisted magnetic abrasive finishing are introduced. According to the characteristics of the difficult-to-machine alloy's complex surface, the important problems for further study are presented to realize the finishing of complex surface with the technology of magnetic abrasive finishing, such as increasing the machining efficiency by enhancing the magnetic flux density of machining gap and compounding of magnetic energy and others, establishing of the control function during machining and the process planning method for magnetic abrasive finishing of complex surface under the space geometry restraint of complex surface on magnetic pole, etc.

The Button Sew Machine. Module 12.

Science.gov (United States)

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

This module on the button sew machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the button sew machine. These components are provided: an introduction, direction, an objective, learning activities, student information, a student self-check, and a…

The Zig Zag Machine. Module 14.

Science.gov (United States)

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

This module on the zig zag machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the zig zag machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and a…

The Bar Tack Machine. Module 16.

Science.gov (United States)

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

This module on the bar tack machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the bar tack machine. These components are provided: an introduction, directions, an objective, learning activities, student information, a student self-check, and a…

Machine function based control code algebras

NARCIS (Netherlands)

Bergstra, J.A.

Machine functions have been introduced by Earley and Sturgis in [6] in order to provide a mathematical foundation of the use of the T-diagrams proposed by Bratman in [5]. Machine functions describe the operation of a machine at a very abstract level. A theory of hardware and software based on

New Applications of Learning Machines

DEFF Research Database (Denmark)

Larsen, Jan

* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection......* Machine learning framework for sound search * Genre classification * Music separation * MIMO channel estimation and symbol detection...

Marketing and vending machine; Marketing to jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Onzo, N. [Waseda University, Tokyo (Japan)

1999-08-10

Vending machines in Japan have made original progress and have developed into big business. Annual sales by vending machines are 6 trillion 700 billion yen, which exceeds 6 trillion 100 billion yen sales by convenience stores. Research on vending machines may have advanced on the technical side but almost none on the marketing. In a vending machine that made an appearance in 1980 with the feature of a lottery, the winning probability was approximately one in fifty. In addition to a simple vending function, these machines have a promotion function. Some other machines have an electrical display of a commercial for products inside the machine for the purpose of attracting attention of passersby. This is an advertising function of the machines. In other words, one vending machine is capable of various marketing functions. This precisely means the subjects are numerous in the marketing research on vending machines. In contrast to the present century in which technical innovations have been made for vending machines, the coming 21st century may turn out to be the one in which marketing innovations are the mainstream for them. (NEDO)

High pressure water jet mining machine

Science.gov (United States)

Barker, Clark R.

1981-05-05

A high pressure water jet mining machine for the longwall mining of coal is described. The machine is generally in the shape of a plowshare and is advanced in the direction in which the coal is cut. The machine has mounted thereon a plurality of nozzle modules each containing a high pressure water jet nozzle disposed to oscillate in a particular plane. The nozzle modules are oriented to cut in vertical and horizontal planes on the leading edge of the machine and the coal so cut is cleaved off by the wedge-shaped body.

The cognitive approach to conscious machines

CERN Document Server

Haikonen, Pentti O

2003-01-01

Could a machine have an immaterial mind? The author argues that true conscious machines can be built, but rejects artificial intelligence and classical neural networks in favour of the emulation of the cognitive processes of the brain-the flow of inner speech, inner imagery and emotions. This results in a non-numeric meaning-processing machine with distributed information representation and system reactions. It is argued that this machine would be conscious; it would be aware of its own existence and its mental content and perceive this as immaterial. Novel views on consciousness and the mind-

Study of Tool Wear Mechanisms and Mathematical Modeling of Flank Wear During Machining of Ti Alloy (Ti6Al4V)

Science.gov (United States)

Chetan; Narasimhulu, A.; Ghosh, S.; Rao, P. V.

2015-07-01

Machinability of titanium is poor due to its low thermal conductivity and high chemical affinity. Lower thermal conductivity of titanium alloy is undesirable on the part of cutting tool causing extensive tool wear. The main task of this work is to predict the various wear mechanisms involved during machining of Ti alloy (Ti6Al4V) and to formulate an analytical mathematical tool wear model for the same. It has been found from various experiments that adhesive and diffusion wear are the dominating wear during machining of Ti alloy with PVD coated tungsten carbide tool. It is also clear from the experiments that the tool wear increases with the increase in cutting parameters like speed, feed and depth of cut. The wear model was validated by carrying out dry machining of Ti alloy at suitable cutting conditions. It has been found that the wear model is able to predict the flank wear suitably under gentle cutting conditions.

DESIGN OF GRASS BRIQUETTE MACHINE

African Journals Online (AJOL)

user

E-mail addresses: 1 mike.ajieh@gmail.com, 2 dracigboanugo@yahoo.com, ... machine design was considered for processing biomass of grass origin. The machine operations include pulverization, compaction and extrusion of the briquettes.

Surface mining machines problems of maintenance and modernization

CERN Document Server

Rusiński, Eugeniusz; Moczko, Przemysław; Pietrusiak, Damian

2017-01-01

This unique volume imparts practical information on the operation, maintenance, and modernization of heavy performance machines such as lignite mine machines, bucket wheel excavators, and spreaders. Problems of large scale machines (mega machines) are highly specific and not well recognized in the common mechanical engineering environment. Prof. Rusiński and his co-authors identify solutions that increase the durability of these machines as well as discuss methods of failure analysis and technical condition assessment procedures. "Surface Mining Machines: Problems in Maintenance and Modernization" stands as a much-needed guidebook for engineers facing the particular challenges of heavy performance machines and offers a distinct and interesting demonstration of scale-up issues for researchers and scientists from across the fields of machine design and mechanical engineering.

Power training using pneumatic machines vs. plate-loaded machines to improve muscle power in older adults.

Science.gov (United States)

Balachandran, Anoop T; Gandia, Kristine; Jacobs, Kevin A; Streiner, David L; Eltoukhy, Moataz; Signorile, Joseph F

2017-11-01

Power training has been shown to be more effective than conventional resistance training for improving physical function in older adults; however, most trials have used pneumatic machines during training. Considering that the general public typically has access to plate-loaded machines, the effectiveness and safety of power training using plate-loaded machines compared to pneumatic machines is an important consideration. The purpose of this investigation was to compare the effects of high-velocity training using pneumatic machines (Pn) versus standard plate-loaded machines (PL). Independently-living older adults, 60years or older were randomized into two groups: pneumatic machine (Pn, n=19) and plate-loaded machine (PL, n=17). After 12weeks of high-velocity training twice per week, groups were analyzed using an intention-to-treat approach. Primary outcomes were lower body power measured using a linear transducer and upper body power using medicine ball throw. Secondary outcomes included lower and upper body muscle muscle strength, the Physical Performance Battery (PPB), gallon jug test, the timed up-and-go test, and self-reported function using the Patient Reported Outcomes Measurement Information System (PROMIS) and an online video questionnaire. Outcome assessors were blinded to group membership. Lower body power significantly improved in both groups (Pn: 19%, PL: 31%), with no significant difference between the groups (Cohen's d=0.4, 95% CI (-1.1, 0.3)). Upper body power significantly improved only in the PL group, but showed no significant difference between the groups (Pn: 3%, PL: 6%). For balance, there was a significant difference between the groups favoring the Pn group (d=0.7, 95% CI (0.1, 1.4)); however, there were no statistically significant differences between groups for PPB, gallon jug transfer, muscle muscle strength, timed up-and-go or self-reported function. No serious adverse events were reported in either of the groups. Pneumatic and plate

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2014-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Virtual machining considering dimensional, geometrical and tool deflection errors in three-axis CNC milling machines

OpenAIRE

Soori, Mohsen; Arezoo, Behrooz; Habibi, Mohsen

2016-01-01

Virtual manufacturing systems can provide useful means for products to be manufactured without the need of physical testing on the shop floor. As a result, the time and cost of part production can be decreased. There are different error sources in machine tools such as tool deflection, geometrical deviations of moving axis and thermal distortions of machine tool structures. Some of these errors can be decreased by controlling the machining process and environmental parameters. However other e...

Functional Correspondence between Evaluators and Abstract Machines

DEFF Research Database (Denmark)

Ager, Mads Stig; Biernacki, Dariusz; Danvy, Olivier

2003-01-01

We bridge the gap between functional evaluators and abstract machines for the λ-calculus, using closure conversion, transformation into continuation-passing style, and defunctionalization.We illustrate this approach by deriving Krivine's abstract machine from an ordinary call-by-name evaluator...... and by deriving an ordinary call-by-value evaluator from Felleisen et al.'s CEK machine. The first derivation is strikingly simpler than what can be found in the literature. The second one is new. Together, they show that Krivine's abstract machine and the CEK machine correspond to the call-by-name and call...

Machine learning in healthcare informatics

CERN Document Server

Acharya, U; Dua, Prerna

2014-01-01

The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: Machines, Machineries and Perpetual Motion

Directory of Open Access Journals (Sweden)

Raffaele Pisano

2015-05-01

Full Text Available This paper is the second part of our recent paper ‘Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: How Science and Technique Work’ (Pisano & Bussotti 2014a. In the first paper—which discussed some aspects of the relations between science and technology from Antiquity to the Renaissance—we highlighted the differences between the Aristotelian/Euclidean tradition and the Archimedean tradition. We also pointed out the way in which the two traditions were perceived around the Renaissance. The Archimedean tradition is connected with machines: its relationship with science and construction of machines should be made clear. It is enough to think that Archimedes mainly dealt with three machines: lever, pulley and screw (and a correlated principle of mechanical advantage. As underlined in the first part, our thesis is that many machines were constructed by people who ignored theory, even though, in other cases, the knowledge of the Archimedean tradition was a precious help in order to build machines. Hence, an a priori idea as to the relations between the Archimedean tradition and construction of machines cannot exist. In this second part we offer some examples of functioning machines constructed by people who ignored any physical theory, whereas, in other cases, the ignorance of some principles—such as the impossibility of a perpetuum mobile—induced the attempt to construct impossible machines. What is very interesting is that these machines did not function, of course, as a perpetuum mobile, but anyway had their functioning and were useful for certain aims, although they were constructed on an idea which is completely wrong from a theoretical point of view. We mainly focus on the Renaissance and early modern period, but we also provide examples of machines built before and after this period. We have followed a chronological order in both parts, starting from the analysis of the situation in

Surface Inspection Machine Infrared (SIMIR). Final CRADA report

Energy Technology Data Exchange (ETDEWEB)

Powell, G.L. [Lockheed Martin Energy Systems, Inc., Oak Ridge, TN (United States); Neu, J.T.; Beecroft, M. [Surface Optics Corp., San Diego, CA (United States)

1997-02-28

This Cooperative Research and Development Agreement was a one year effort to make the surface inspection machine based on diffuse reflectance infrared spectroscopy (Surface Inspection Machine-Infrared, SIMIR), being developed by Surface Optics Corporation, perform to its highest potential as a practical, portable surface inspection machine. The design function of the SIMIR is to inspect metal surfaces for cleanliness (stains). The system is also capable of evaluating graphite-resin systems for cure and heat damage, and for measuring the effects of moisture exposure on lithium hydride, corrosion on uranium metal, and the constituents of and contamination on wood, paper, and fabrics. Over the period of the CRADA, extensive experience with the use of the SIMIR for surface cleanliness measurements have been achieved through collaborations with NASA and the Army. The SIMIR was made available to the AMTEX CRADA for Finish on Yarn where it made a very significant contribution. The SIMIR was the foundation of a Forest Products CRADA that was developed over the time interval of this CRADA. Surface Optics Corporation and the SIMIR have been introduced to the chemical spectroscopy on-line analysis market and have made staffing additions and arrangements for international marketing of the SIMIR as an on-line surface inspection device. LMES has been introduced to a wide range of aerospace applications, the research and fabrication skills of Surface Optics Corporation, has gained extensive experience in the areas of surface cleanliness from collaborations with NASA and the Army, and an extensive introduction to the textile and forest products industries. The SIMIR, marketed as the SOC-400, has filled an important new technology need in the DOE-DP Enhanced Surveillance Program with instruments delivered to or on order by LMES, LANL, LLNL, and Pantex, where extensive collaborations are underway to implement and improve this technology.

Surface Inspection Machine Infrared (SIMIR). Final CRADA report

International Nuclear Information System (INIS)

Powell, G.L.; Neu, J.T.; Beecroft, M.

1997-01-01

This Cooperative Research and Development Agreement was a one year effort to make the surface inspection machine based on diffuse reflectance infrared spectroscopy (Surface Inspection Machine-Infrared, SIMIR), being developed by Surface Optics Corporation, perform to its highest potential as a practical, portable surface inspection machine. The design function of the SIMIR is to inspect metal surfaces for cleanliness (stains). The system is also capable of evaluating graphite-resin systems for cure and heat damage, and for measuring the effects of moisture exposure on lithium hydride, corrosion on uranium metal, and the constituents of and contamination on wood, paper, and fabrics. Over the period of the CRADA, extensive experience with the use of the SIMIR for surface cleanliness measurements have been achieved through collaborations with NASA and the Army. The SIMIR was made available to the AMTEX CRADA for Finish on Yarn where it made a very significant contribution. The SIMIR was the foundation of a Forest Products CRADA that was developed over the time interval of this CRADA. Surface Optics Corporation and the SIMIR have been introduced to the chemical spectroscopy on-line analysis market and have made staffing additions and arrangements for international marketing of the SIMIR as an on-line surface inspection device. LMES has been introduced to a wide range of aerospace applications, the research and fabrication skills of Surface Optics Corporation, has gained extensive experience in the areas of surface cleanliness from collaborations with NASA and the Army, and an extensive introduction to the textile and forest products industries. The SIMIR, marketed as the SOC-400, has filled an important new technology need in the DOE-DP Enhanced Surveillance Program with instruments delivered to or on order by LMES, LANL, LLNL, and Pantex, where extensive collaborations are underway to implement and improve this technology

QCD machines - present and future

International Nuclear Information System (INIS)

Christ, N.H.

1991-01-01

The present status of the currently working and nearly working dedicated QCD machines is reviewed and proposals for future machines are discussed with particular emphasis on the QCD Teraflop Project in the US. (orig.)

Metal release from coffee machines and electric kettles.

Science.gov (United States)

Müller, Frederic D; Hackethal, Christin; Schmidt, Roman; Kappenstein, Oliver; Pfaff, Karla; Luch, Andreas

2015-01-01

The release of elemental ions from 8 coffee machines and 11 electric kettles into food simulants was investigated. Three different types of coffee machines were tested: portafilter espresso machines, pod machines and capsule machines. All machines were tested subsequently on 3 days before and on 3 days after decalcification. Decalcification of the machines was performed with agents according to procedures as specified in the respective manufacturer's manuals. The electric kettles showed only a low release of the elements analysed. For the coffee machines decreasing concentrations of elements were found from the first to the last sample taken in the course of 1 day. Metal release on consecutive days showed a decreasing trend as well. After decalcification a large increase in the amounts of elements released was encountered. In addition, the different machine types investigated clearly differed in their extent of element release. By far the highest leaching, both quantitatively and qualitatively, was found for the portafilter machines. With these products releases of Pb, Ni, Mn, Cr and Zn were in the range and beyond the release limits as proposed by the Council of Europe. Therefore, a careful rinsing routine, especially after decalcification, is recommended for these machines. The comparably lower extent of release of one particular portafilter machine demonstrates that metal release at levels above the threshold that triggers health concerns are technically avoidable.

Modularity Design Approach for Preventive Machine Maintenance

Science.gov (United States)

Ernawati, D.; Pudji, E.; Ngatilah, Y.; Handoyo, R.

2018-01-01

In a company, machine maintenance system will be very influential in production process activity. The company should have a scheduled engine maintenance system that does not require high costs when repairing and replacing machine parts. Modularity Design method is able to provide solutions to the engine maintenance scheduling system and can prevent fatal damage to the engine components. It can minimize the cost of repair and replacement of these machine components.The paper provides a solution to machine maintenance problems. The paper is also completed with case study of milling machines. That case studies can give us a real description about impact implementation of modularity design to prevent fatal damage to components and minimize the cost of repair and replacement of components of the machine.

Machine learning with R

CERN Document Server

Lantz, Brett

2015-01-01

Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

Human Machine Learning Symbiosis

Science.gov (United States)

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…

Human-Machine Communication

International Nuclear Information System (INIS)

Farbrot, J.E.; Nihlwing, Ch.; Svengren, H.

2005-01-01

New requirements for enhanced safety and design changes in process systems often leads to a step-wise installation of new information and control equipment in the control room of older nuclear power plants, where nowadays modern digital I and C solutions with screen-based human-machine interfaces (HMI) most often are introduced. Human factors (HF) expertise is then required to assist in specifying a unified, integrated HMI, where the entire integration of information is addressed to ensure an optimal and effective interplay between human (operators) and machine (process). Following a controlled design process is the best insurance for ending up with good solutions. This paper addresses the approach taken when introducing modern human-machine communication in the Oskarshamn 1 NPP, the results, and the lessons learned from this work with high operator involvement seen from an HF point of view. Examples of possibilities modern technology might offer for the operators are also addressed. (orig.)

Behind the machines

CERN Multimedia

Laëtitia Pedroso

2010-01-01

One of the first things we think about when someone mentions physics is the machines. But behind the machines, there are the men and women who design, build and operate them. In an exhibition at the Thinktank planetarium’s art gallery in Birmingham (UK), Claudia Marcelloni and her husband Neal Hartman—she is a photographer and Outreach Officer for ATLAS, while he is an engineer working on the ATLAS pixel detector—explore the human side of scientists.   The exhibition at the Thinktank Planetarium art gallery, Birmingham (UK). It all began two years ago with the publication of Exploring the mystery of matter, a book about ATLAS. “A Norwegian physicist friend, Heidi Sandaker, saw my photographs and suggested that I display them in a museum. I thought this was an interesting idea, except that the photos consisted entirely of depictions of machinery, with human beings completely absent. For me, showing the people who are behind the machines and the fascination ...

Gram staining with an automatic machine.

Science.gov (United States)

Felek, S; Arslan, A

1999-01-01

This study was undertaken to develop a new Gram-staining machine controlled by a micro-controller and to investigate the quality of slides that were stained in the machine. The machine was designed and produced by the authors. It uses standard 220 V AC. Staining, washing, and drying periods are controlled by a timer built in the micro-controller. A software was made that contains a certain algorithm and time intervals for the staining mode. One-hundred and forty smears were prepared from Escherichia coli, Staphylococcus aureus, Neisseria sp., blood culture, trypticase soy broth, direct pus and sputum smears for comparison studies. Half of the slides in each group were stained with the machine, the other half by hand and then examined by four different microbiologists. Machine-stained slides had a higher clarity and less debris than the hand-stained slides (p stained slides, some Gram-positive organisms showed poor Gram-positive staining features (p Gram staining with the automatic machine increases the staining quality and helps to decrease the work load in a busy diagnostic laboratory.

Addressing uncertainty in atomistic machine learning

DEFF Research Database (Denmark)

Peterson, Andrew A.; Christensen, Rune; Khorshidi, Alireza

2017-01-01

Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility of the predi......Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility...... of the predictions. In this perspective, we address the types of errors that might arise in atomistic machine learning, the unique aspects of atomistic simulations that make machine-learning challenging, and highlight how uncertainty analysis can be used to assess the validity of machine-learning predictions. We...... suggest this will allow researchers to more fully use machine learning for the routine acceleration of large, high-accuracy, or extended-time simulations. In our demonstrations, we use a bootstrap ensemble of neural network-based calculators, and show that the width of the ensemble can provide an estimate...

Diamond machining of micro-optical components and structures

Science.gov (United States)

Gläbe, Ralf; Riemer, Oltmann

2010-05-01

Diamond machining originates from the 1950s to 1970s in the USA. This technology was originally designed for machining of metal optics at macroscopic dimensions with so far unreached tolerances. During the following decades the machine tools, the monocrystalline diamond cutting tools, the workpiece materials and the machining processes advanced to even higher precision and flexibility. For this reason also the fabrication of small functional components like micro optics at a large spectrum of geometries became technologically and economically feasible. Today, several kinds of fast tool machining and multi axis machining operations can be applied for diamond machining of micro optical components as well as diffractive optical elements. These parts can either be machined directly as single or individual component or as mold insert for mass production by plastic replication. Examples are multi lens arrays, micro mirror arrays and fiber coupling lenses. This paper will give an overview about the potentials and limits of the current diamond machining technology with respect to micro optical components.

Machining of Fibre Reinforced Plastic Composite Materials

Science.gov (United States)

2018-01-01

Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented. PMID:29562635

Machining of Fibre Reinforced Plastic Composite Materials

Directory of Open Access Journals (Sweden)

Alessandra Caggiano

2018-03-01

Full Text Available Fibre reinforced plastic composite materials are difficult to machine because of the anisotropy and inhomogeneity characterizing their microstructure and the abrasiveness of their reinforcement components. During machining, very rapid cutting tool wear development is experienced, and surface integrity damage is often produced in the machined parts. An accurate selection of the proper tool and machining conditions is therefore required, taking into account that the phenomena responsible for material removal in cutting of fibre reinforced plastic composite materials are fundamentally different from those of conventional metals and their alloys. To date, composite materials are increasingly used in several manufacturing sectors, such as the aerospace and automotive industry, and several research efforts have been spent to improve their machining processes. In the present review, the key issues that are concerning the machining of fibre reinforced plastic composite materials are discussed with reference to the main recent research works in the field, while considering both conventional and unconventional machining processes and reporting the more recent research achievements. For the different machining processes, the main results characterizing the recent research works and the trends for process developments are presented.

Controlling the Adhesion of Superhydrophobic Surfaces Using Electrolyte Jet Machining Techniques

Science.gov (United States)

Yang, Xiaolong; Liu, Xin; Lu, Yao; Zhou, Shining; Gao, Mingqian; Song, Jinlong; Xu, Wenji

2016-01-01

Patterns with controllable adhesion on superhydrophobic areas have various biomedical and chemical applications. Electrolyte jet machining technique (EJM), an electrochemical machining method, was firstly exploited in constructing dimples with various profiles on the superhydrophobic Al alloy surface using different processing parameters. Sliding angles of water droplets on those dimples firstly increased and then stabilized at a certain value with the increase of the processing time or the applied voltages of the EJM, indicating that surfaces with different adhesion force could be obtained by regulating the processing parameters. The contact angle hysteresis and the adhesion force that restricts the droplet from sliding off were investigated through experiments. The results show that the adhesion force could be well described using the classical Furmidge equation. On account of this controllable adhesion force, water droplets could either be firmly pinned to the surface, forming various patterns or slide off at designed tilting angles at specified positions on a superhydrophobic surface. Such dimples on superhydrophopbic surfaces can be applied in water harvesting, biochemical analysis and lab-on-chip devices. PMID:27046771

Superconducting magnetic systems and electrical machines

International Nuclear Information System (INIS)

Glebov, I.A.

1975-01-01

The use of superconductors for magnets and electrical machines attracts close attention of designers and scientists. A description is given of an ongoing research program to create superconductive magnetic systems, commutator motors, homopolar machines, topological generators and turbogenerators with superconductive field windings. All the machines are tentative experimental models and serve as a basis for further developments

Advanced Machining Toolpath for Low Distortion

Science.gov (United States)

2017-02-28

Advanced Machining Toolpath for Low Distortion FINAL STATUS REPORT Prepared by Brian Becker R&D Technology Manager Third Wave Systems, Inc... Machining Toolpath for Low Distortion December 2016 Contract No.: W911W6-16-P-0044 2 Table of Contents 1.0 EXECUTIVE SUMMARY...2 2.1 Task 1: Collect Details of Machining Lab to Support

Mini lathe machine converted to CNC

Directory of Open Access Journals (Sweden)

Alexandru Morar

2012-06-01

Full Text Available This paper presents the adaptation of a mechanical mini-lathing machine to a computerized numerical control (CNC lathing machine. This machine is composed of a ASIST mini-lathe and a two-degrees-of-freedom XZ stage designed specifically for this application. The whole system is controlled from a PC using adequate CNC control software.

Magnetic field-assisted electrochemical discharge machining

International Nuclear Information System (INIS)

Cheng, Chih-Ping; Mai, Chao-Chuang; Wu, Kun-Ling; Hsu, Yu-Shan; Yan, Biing-Hwa

2010-01-01

Electrochemical discharge machining (ECDM) is an effective unconventional method for micromachining in non-conducting materials, such as glass, quartz and some ceramics. However, since the spark discharge performance becomes unpredictable as the machining depth increases, it is hard to achieve precision geometry and efficient machining rate in ECDM drilling. One of the main factors for this is the lack of sufficient electrolyte flow in the narrow gap between the tool and the workpiece. In this study a magnetohydrodynamic (MHD) convection, which enhances electrolyte circulation has been applied to the ECDM process in order to upgrade the machining accuracy and efficiency. During electrolysis in the presence of a magnetic field, the Lorenz force induces the charged ions to form a MHD convection. The MHD convection then forces the electrolyte into movement, thus enhancing circulation of electrolyte. Experimental results show that the MHD convection induced by the magnetic field can effectively enhance electrolyte circulation in the micro-hole, which contributes to higher machining efficiency. Micro-holes in glass with a depth of 450 µm are drilled in less than 20 s. At the same time, better electrolyte circulation can prevent deterioration of gas film quality with increasing machining depth, while ensuring stable electrochemical discharge. The improvement in the entrance diameter thus achieved was 23.8% while that in machining time reached 57.4%. The magnetic field-assisted approach proposed in the research does not require changes in the machining setup or electrolyte but has proved to achieve significant enhancement in both accuracy and efficiency of ECDM.

Chemical Entity Recognition and Resolution to ChEBI

Science.gov (United States)

Grego, Tiago; Pesquita, Catia; Bastos, Hugo P.; Couto, Francisco M.

2012-01-01

Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an annotated corpus, this task can be addressed. We developed a machine-learning-based method for chemical entity recognition and a lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based method. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for the entity recognition task, 2–5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks. PMID:25937941

Structural dynamics of turbo-machines

CERN Document Server

Rangwala, AS

2009-01-01

The book presents a detailed and comprehensive treatment of structural vibration evaluation of turbo-machines. Starting with the fundamentals of the theory of vibration as related to various aspects of rotating machines, the dynamic analysis procedures of a broad spectrum of turbo-machines is covered. An in-depth procedure for analyzing the torsional and flexural oscillations of the components and of the rotor-bearing system is presented. The latest trends in design and analysis are presented, chief among them: Blade and coupled disk-blade mod

Sixth international conference on electrical machines and drives

International Nuclear Information System (INIS)

1993-01-01

This volume contains 111 papers presented at the Sixth International Conference on Electrical Machines and Drives. The topics covered include: miniature and micro motors; induction motors; DC machines; reluctance motors; condition monitoring; synchronous machines and drives; induction machines; induction generators; simulation; design; and operating experience; linear machines; noise and vibration; special machines. Separate abstracts have been prepared for a paper on linear step motors for control rod drives and for a paper on a motor drive for gas filtration in gas-cooled reactors. (UK)

Man - Machine Communication

CERN Document Server

Petersen, Peter; Nielsen, Henning

1984-01-01

This report describes a Man-to-Machine Communication module which together with a STAC can take care of all operator inputs from the touch-screen, tracker balls and mechanical buttons. The MMC module can also contain a G64 card which could be a GPIB driver but many other G64 cards could be used. The soft-ware services the input devices and makes the results accessible from the CAMAC bus. NODAL functions for the Man Machine Communication is implemented in the STAC and in the ICC.

Application of Machine Learning Techniques in Aquaculture

OpenAIRE

Rahman, Akhlaqur; Tasnim, Sumaira

2014-01-01

In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.

Machinability of IPS Empress 2 framework ceramic.

Science.gov (United States)

Schmidt, C; Weigl, P

2000-01-01

Using ceramic materials for an automatic production of ceramic dentures by CAD/CAM is a challenge, because many technological, medical, and optical demands must be considered. The IPS Empress 2 framework ceramic meets most of them. This study shows the possibilities for machining this ceramic with economical parameters. The long life-time requirement for ceramic dentures requires a ductile machined surface to avoid the well-known subsurface damages of brittle materials caused by machining. Slow and rapid damage propagation begins at break outs and cracks, and limits life-time significantly. Therefore, ductile machined surfaces are an important demand for machine dental ceramics. The machining tests were performed with various parameters such as tool grain size and feed speed. Denture ceramics were machined by jig grinding on a 5-axis CNC milling machine (Maho HGF 500) with a high-speed spindle up to 120,000 rpm. The results of the wear test indicate low tool wear. With one tool, you can machine eight occlusal surfaces including roughing and finishing. One occlusal surface takes about 60 min machining time. Recommended parameters for roughing are middle diamond grain size (D107), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 1000 mm/min, depth of cut a(e) = 0.06 mm, width of contact a(p) = 0.8 mm, and for finishing ultra fine diamond grain size (D46), cutting speed v(c) = 4.7 m/s, feed speed v(ft) = 100 mm/min, depth of cut a(e) = 0.02 mm, width of contact a(p) = 0.8 mm. The results of the machining tests give a reference for using IPS Empress(R) 2 framework ceramic in CAD/CAM systems. Copyright 2000 John Wiley & Sons, Inc.

Nano Mechanical Machining Using AFM Probe

Science.gov (United States)

Mostofa, Md. Golam

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

High speed operation of permanent magnet machines

Science.gov (United States)

El-Refaie, Ayman M.

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

Remote filter handling machine for Sizewell B

International Nuclear Information System (INIS)

Barker, D.

1993-01-01

Two Filter Handling machines (FHM) have been supplied to Nuclear Electric plc for use at Sizewell B Power Station. These machines have been designed and built following ALARP principles with the functional objective being to remove radioactive filter cartridges from a filter housing and replace them with clean filter cartridges. Operation of the machine is achieved by the prompt of each distinct task via an industrial computer or the prompt of a full cycle using the automatic mode. The design of the machine features many aspects demonstrating ALARP while keeping the machine simple, robust and easy to maintain. (author)

EXPERIMENTAL EVALUATION OF WEDM MACHINED SURFACE WAVINESS

Directory of Open Access Journals (Sweden)

Katerina Mouralova

2016-10-01

Full Text Available Wire Electrical Discharge Machining (WEDM an unconventional machining technology which has become indispensable in many industries. The typical morphology of a surface machined using the electrical discharge technology is characterized with a large number of craters caused by electro-spark discharges produced during the machining process. The study deals with an evaluation of the machine parameter setting on the profile parameters of surface waviness on samples made of two metal materials Al 99.5 and Ti-6Al-4V. Attention was also paid to an evaluation of the surface morphology using 3D colour filtered and non-filtered images.

Machinability of experimental Ti-Ag alloys.

Science.gov (United States)

Kikuchi, Masafumi; Takahashi, Masatoshi; Okuno, Osamu

2008-03-01

This study investigated the machinability of experimental Ti-Ag alloys (5, 10, 20, and 30 mass% Ag) as a new dental titanium alloy candidate for CAD/CAM use. The alloys were slotted with a vertical milling machine and carbide square end mills under two cutting conditions. Machinability was evaluated through cutting force using a three-component force transducer fixed on the table of the milling machine. The horizontal cutting force of the Ti-Ag alloys tended to decrease as the concentration of silver increased. Values of the component of the horizontal cutting force perpendicular to the feed direction for Ti-20% Ag and Ti-30% Ag were more than 20% lower than those for titanium under both cutting conditions. Alloying with silver significantly improved the machinability of titanium in terms of cutting force under the present cutting conditions.

Machine learning for adaptive many-core machines a practical approach

CERN Document Server

Lopes, Noel

2015-01-01

The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind.

Gaussian processes for machine learning.

Science.gov (United States)

Seeger, Matthias

2004-04-01

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.

Addressing Machining Issues for the Intermetallic Compound 60-NITINOL

Science.gov (United States)

Stanford, Malcolm K.; Wozniak, Walter A.; McCue, Terry R.

2012-01-01

60-NITINOL (60 wt.% Ni - 40 wt.% Ti) is being studied as a material for advanced aerospace components. Frequent wire breakage during electrical-discharge machining of this material was investigated. The studied material was fabricated from hot isostatically pressed 60-NITINOL powder obtained through a commercial source. Bulk chemical analysis of the material showed that the composition was nominal but had relatively high levels of certain impurities, including Al and O. It was later determined that Al2O3 particles had contaminated the material during the hot isostatic pressing procedure and that these particles were the most likely cause of the wire breakage. The results of this investigation highlight the importance of material cleanliness to its further implementation.

Mechanical design of walking machines.

Science.gov (United States)

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

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

A nucleonic weighing machine

International Nuclear Information System (INIS)

Anon.

1978-01-01

The design and operation of a nucleonic weighing machine fabricated for continuous weighing of material over conveyor belt are described. The machine uses a 40 mCi cesium-137 line source and a 10 litre capacity ionization chamber. It is easy to maintain as there are no moving parts. It can also be easily removed and reinstalled. (M.G.B.)

Chatter and machine tools

CERN Document Server

Stone, Brian

2014-01-01

Focussing on occurrences of unstable vibrations, or Chatter, in machine tools, this book gives important insights into how to eliminate chatter with associated improvements in product quality, surface finish and tool wear. Covering a wide range of machining processes, including turning, drilling, milling and grinding, the author uses his research expertise and practical knowledge of vibration problems to provide solutions supported by experimental evidence of their effectiveness. In addition, this book contains links to supplementary animation programs that help readers to visualise the ideas detailed in the text. Advancing knowledge in chatter avoidance and suggesting areas for new innovations, Chatter and Machine Tools serves as a handbook for those desiring to achieve significant reductions in noise, longer tool and grinding wheel life and improved product finish.

GPK heading machine

Energy Technology Data Exchange (ETDEWEB)

Krmasek, J.; Novosad, K.

1981-01-01

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

Philips high tension generator (x-ray machine) testing for baby ebm (electron beam machine) project

International Nuclear Information System (INIS)

Norman Awalludin; Leo Kwee Wah; Abu Bakar Mhd Ghazali

2005-01-01

This paper describes the test of the HT system (from X-ray machine) for usage of the mini EBM (Electron Beam Machine). It consists the procedures of the installation, the safety procedures when deals with HT, modification of the system for testing purpose and the technique/method for testing the HT system. As a result, the voltage for the HT system and the electron gun (filament) current can be measured. Based on the results, suitability of the machine for baby EBM could be confirmed. (Author)

First neutrons from new machine

International Nuclear Information System (INIS)

Gray, D.A.

1985-01-01

Nimrod, the last weak focusing proton machine to be built, provided its first 7 GeV proton beam in 1963 and provided the research fuel for several generations of UK particle physicists. With the decision to build the SNS, the task was to transform the existing facility into a high repetition rate, high intensity machine furnishing the protons to bombard a neutron production target. As well as equipment from Nimrod, the SNS synchrotron also makes use of components from the old NINA electron machine at Daresbury, closed down in 1977. (orig./HSI).

Learning with Support Vector Machines

CERN Document Server

Campbell, Colin

2010-01-01

Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such a

Machine Learning an algorithmic perspective

CERN Document Server

Marsland, Stephen

2009-01-01

Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement le

Machine tool evaluation

International Nuclear Information System (INIS)

Lunsford, B.E.

1976-01-01

Continued improvement in numerical control (NC) units and the mechanical components used in the construction of today's machine tools, necessitate the use of more precise instrumentation to calibrate and determine the capabilities of these systems. It is now necessary to calibrate most tape-control lathes to a tool-path positioning accuracy of +-300 microinches in the full slide travel and, on some special turning and boring machines, a capability of +-100 microinches must be achieved. The use of a laser interferometer to determine tool-path capabilities is described

Electrical machines diagnosis

CERN Document Server

Trigeassou, Jean-Claude

2013-01-01

Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

The great chemical residue detection debate: dog versus machine

Science.gov (United States)

Tripp, Alan C.; Walker, James C.

2003-09-01

Many engineering groups desire to construct instrumentation to replace dog-handler teams in identifying and localizing chemical mixtures. This goal requires performance specifications for an "artificial dog-handler team". Progress toward generating such specifications from laboratory tests of dog-handler teams has been made recently at the Sensory Research Institute, and the method employed is amenable to the measurement of tasks representative of the decision-making that must go on when such teams solve problems in actual (and therefore informationally messy) situations. As progressively more quantitative data are obtained on progressively more complex odor tasks, the boundary conditions of dog-handler performance will be understood in great detail. From experiments leading to this knowledge, one ca develop, as we do in this paper, a taxonomy of test conditions that contain various subsets of the variables encountered in "real world settings". These tests provide the basis for the rigorous testing that will provide an improved basis for deciding when biological sensing approaches (e.g. dog-handler teams) are best and when "artificial noses" are most valuable.

Managing virtual machines with Vac and Vcycle

Science.gov (United States)

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.

Charging machine

International Nuclear Information System (INIS)

Medlin, J.B.

1976-01-01

A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine. 3 claims, 11 drawing figures

Improvement of automatic fish feeder machine design

Science.gov (United States)

Chui Wei, How; Salleh, S. M.; Ezree, Abdullah Mohd; Zaman, I.; Hatta, M. H.; Zain, B. A. Md; Mahzan, S.; Rahman, M. N. A.; Mahmud, W. A. W.

2017-10-01

Nation Plan of action for management of fishing is target to achieve an efficient, equitable and transparent management of fishing capacity in marine capture fisheries by 2018. However, several factors influence the fishery production and efficiency of marine system such as automatic fish feeder machine could be taken in consideration. Two latest fish feeder machines have been chosen as the reference for this study. Based on the observation, it has found that the both machine was made with heavy structure, low water and temperature resistance materials. This research’s objective is to develop the automatic feeder machine to increase the efficiency of fish feeding. The experiment has conducted to testing the new design of machine. The new machine with maximum storage of 5 kg and functioning with two DC motors. This machine able to distribute 500 grams of pellets within 90 seconds and longest distance of 4.7 meter. The higher speed could reduce time needed and increase the distance as well. The minimum speed range for both motor is 110 and 120 with same full speed range of 255.

Machine Readable Passports & The Visa Waiver Programme

CERN Multimedia

2003-01-01

From 1 October 2003, all passengers intending to enter the USA on the Visa Waiver Programme (VWP) will be required to present a machine-readable passport (MRP). Passengers travelling to the USA with a non-machine readable passport will require a valid US entry visa. Applying for a US visa is a lengthy process, which can take several weeks or even months. Therefore it is strongly recommended that: • All Visa Waiver nationals who hold a non-machine readable passport should obtain a MRP before their next visit to the USA. • Children travelling on a parent's passport (be it machine readable or non-machine readable) cannot benefit from the Visa Waiver Programme and should obtain their own MRP prior to travelling to the USA or request a visa. What is a Machine Readable Passport (MRP)? A MRP has the holders' personal details, e.g. name, date of birth, nationality and their passport number contained in two lines of text at the base of the photo page. This text may be read by machine. These 2 lines ...

Program Design Report of the CNC Machine Tool(II)

International Nuclear Information System (INIS)

Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H.

2007-06-01

The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

Program Design Report of the CNC Machine Tool(II)

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H

2007-06-15

The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology.

Program Design Report of the CNC Machine Tool(III)

International Nuclear Information System (INIS)

Kim, Jong Kiun; Youm, K. U.; Kim, K. S.; Lee, I. B.; Yoon, K. B.; Lee, C. K.; Youm, J. H.

2008-08-01

The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

Program Design Report of the CNC Machine Tool (I)

International Nuclear Information System (INIS)

Kim, Jong Kiun; Youm, K. U.; Kim, K. S.

2006-08-01

The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

Program Design Report of the CNC Machine Tool(IV)

International Nuclear Information System (INIS)

Youm, Ki Un; Lee, I. B.; Youm, J. H.

2009-09-01

The application of CNC machine tool being widely expanded according to variety of machine work method and rapid promotion of machine tool, cutting tool, for high speed efficient machine work. In order to conduct of the project of manufacture and maintenance of laboratory equipment, production design and machine work technology are continually developed, especially the application of CNC machine tool is very important for the improvement of productivity, quality and clearing up a manpower shortage. We publish technical report which it includes CNC machine tool program and drawing, it contributes to the systematic development of CNC program design and machine work technology

Diamond turning on advanced machine tool prototypes

International Nuclear Information System (INIS)

Arnold, J.B.; Steger, P.J.

1975-01-01

Specular-quality metal mirrors are being machined for use in laser optical systems. The fabrication process incorporates special quality diamond tools and specially constructed turning machines. The machines are controlled by advanced control techniques and are housed in an environmentally controlled laboratory to insure ultimate machine stability and positional accuracy. The materials from which these mirrors are primarily produced are the softer face-center-cubic structure metals, such as gold, silver, copper, and aluminum. Mirror manufacturing by the single-point diamond machining process is in an early stage of development, but it is anticipated that this method will become the most economical way for producing high-quality metal mirrors. (U.S.)