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Sample records for research kernel spark

  1. A Experimental Study of the Growth of Laser Spark and Electric Spark Ignited Flame Kernels.

    Science.gov (United States)

    Ho, Chi Ming

    1995-01-01

    Better ignition sources are constantly in demand for enhancing the spark ignition in practical applications such as automotive and liquid rocket engines. In response to this practical challenge, the present experimental study was conducted with the major objective to obtain a better understanding on how spark formation and hence spark characteristics affect the flame kernel growth. Two laser sparks and one electric spark were studied in air, propane-air, propane -air-nitrogen, methane-air, and methane-oxygen mixtures that were initially at ambient pressure and temperature. The growth of the kernels was monitored by imaging the kernels with shadowgraph systems, and by imaging the planar laser -induced fluorescence of the hydroxyl radicals inside the kernels. Characteristic dimensions and kernel structures were obtained from these images. Since different energy transfer mechanisms are involved in the formation of a laser spark as compared to that of an electric spark; a laser spark is insensitive to changes in mixture ratio and mixture type, while an electric spark is sensitive to changes in both. The detailed structures of the kernels in air and propane-air mixtures primarily depend on the spark characteristics. But the combustion heat released rapidly in methane-oxygen mixtures significantly modifies the kernel structure. Uneven spark energy distribution causes remarkably asymmetric kernel structure. The breakdown energy of a spark creates a blast wave that shows good agreement with the numerical point blast solution, and a succeeding complex spark-induced flow that agrees reasonably well with a simple puff model. The transient growth rates of the propane-air, propane-air -nitrogen, and methane-air flame kernels can be interpreted in terms of spark effects, flame stretch, and preferential diffusion. For a given mixture, a spark with higher breakdown energy produces a greater and longer-lasting enhancing effect on the kernel growth rate. By comparing the growth

  2. Experimental investigation and phenomenological model development of flame kernel growth rate in a gasoline fuelled spark ignition engine

    International Nuclear Information System (INIS)

    Salvi, B.L.; Subramanian, K.A.

    2015-01-01

    Highlights: • Experimental measurement of the flame kernel growth rate (FKGR) in SI engine. • FKGR is the highest at MBT timing as compared with retarded and advanced timings. • FKGR decreases with increase in engine speed. • FKGR is correlated with equivalence ratio, charge density, in-cylinder pressure and engine speed. - Abstract: As flame kernel growth plays a major role in combustion of premixed-charge in spark ignition engines for higher energy efficiency and less emission, the experimental study was carried out on a single cylinder spark ignition research engine for measurement of flame kernel growth rate (FKGR) using spark plug fibre optics probe (VisioFlame sensor). The FKGR was measured on the engine at different power output with varied spark ignition timings and different engine speeds. The experimental results indicate that the FKGR was the highest with the maximum brake torque (MBT) spark timing and it decreases with increase in the engine speed. The FKGR at engine speed of 1000 RPM was the highest of 1.81 m/s with MBT timing (20° bTDC) as compared to 1.6 m/s (15° bTDC), 1.67 m/s (25° bTDC), and 1.61 m/s (30° bTDC) with retarded and advanced timing. In addition to this, a phenomenological model was developed for calculation of FKGR. It was observed from the model that FKGR is function of equivalence ratio, engine speed, in-cylinder pressure and charge density. The experimental results and methodology emerged from this study would be useful for optimization of engine parameters using the FKGR and also further development of model for alternative fuels

  3. Research of Performance Linux Kernel File Systems

    Directory of Open Access Journals (Sweden)

    Andrey Vladimirovich Ostroukh

    2015-10-01

    Full Text Available The article describes the most common Linux Kernel File Systems. The research was carried out on a personal computer, the characteristics of which are written in the article. The study was performed on a typical workstation running GNU/Linux with below characteristics. On a personal computer for measuring the file performance, has been installed the necessary software. Based on the results, conclusions and proposed recommendations for use of file systems. Identified and recommended by the best ways to store data.

  4. The relative effects of fuel concentration, residual-gas fraction, gas motion, spark energy and heat losses to the electrodes on flame-kernel development in a lean-burn spark ignition engine

    Energy Technology Data Exchange (ETDEWEB)

    Aleiferis, P.G.; Taylor, A.M.K.P. [Imperial College of Science, Technology and Medicine, London (United Kingdom). Dept. of Mechanical Engineering; Ishii, K. [Honda International Technical School, Saitama (Japan); Urata, Y. [Honda R and D Co., Ltd., Tochigi (Japan). Tochigi R and D Centre

    2004-04-01

    The potential of lean combustion for the reduction in exhaust emissions and fuel consumption in spark ignition engines has long been established. However, the operating range of lean-burn spark ignition engines is limited by the level of cyclic variability in the early-flame development stage that typically corresponds to the 0-5 per cent mass fraction burned duration. In the current study, the cyclic variations in early flame development were investigated in an optical stratified-charge spark ignition engine at conditions close to stoichiometry [air-to-fuel ratio (A/F) = 15] and to the lean limit of stable operation (A/F = 22). Flame images were acquired through either a pentroof window ('tumble plane' of view) or the piston crown ('swirl plane' of view) and these were processed to calculate the intra-cycle flame-kernel radius evolution. In order to quantify the relative effects of local fuel concentration, gas motion, spark-energy release and heat losses to the electrodes on the flame-kernel growth rate, a zero-dimensional flame-kernel growth model, in conjunction with a one-dimensional spark ignition model, was employed. Comparison of the calculated flame-radius evolutions with the experimental data suggested that a variation in A/F around the spark plug of {delta}(A/F) {approx} 4 or, in terms of equivalence ratio {phi}, a variation in {delta}{phi} {approx} 0.15 at most was large enough to account for 100 per cent of the observed cyclic variability in flame-kernel radius. A variation in the residual-gas fraction of about 20 per cent around the mean was found to account for up to 30 per cent of the variability in flame-kernel radius at the timing of 5 per cent mass fraction burned. The individual effect of 20 per cent variations in the 'mean' in-cylinder velocity at the spark plug at ignition timing was found to account for no more than 20 per cent of the measured cyclic variability in flame kernel radius. An individual effect of

  5. The Flux OSKit: A Substrate for Kernel and Language Research

    Science.gov (United States)

    1997-10-01

    unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 tions. Our own microkernel -based OS, Fluke [17], puts almost all of the OSKit to use...kernels distance the language from the hardware; even microkernels and other extensible kernels enforce some default policy which often conflicts with a...be particu- larly useful in these research projects. 6.1.1 The Fluke OS In 1996 we developed an entirely new microkernel - based system called Fluke

  6. Research on spark discharge of floating roof tank shunt

    International Nuclear Information System (INIS)

    Bi, Xiaolei; Liu, Quanzhen; Liu, Baoquan; Gao, Xin; Hu, Haiyan; Liu, Juan

    2013-01-01

    In order to quantitatively analyze the spark discharge risk of floating roof tank shunts, the breakdown voltage of shunt has been calculated by Townsend theory, the shunt spark discharge experiment is carried out by using 1.2/50 μs impulse voltage wave, and the relationship between breakdown voltage of shunt spark discharge and air gap is analyzed. It has been indicated by theoretical analysis and experimental study that the small gap is more easily cause spark discharge than the big gap when the contact between shunt and tank shell is poor. When air gap distance is equal to 0.1 cm, average breakdown voltage is 5280 V. When the air gap distance is less than 0.3 cm, experiment data agree well with Townsend theory. Therefore, in the condition of small gap, Townsend theory can be used to calculated breakdown voltage of shunt. Finally, based on the above conclusions, improvements for avoiding the spark discharge risk of shunt of floating roof tanks have been proposed.

  7. Research on retailer data clustering algorithm based on Spark

    Science.gov (United States)

    Huang, Qiuman; Zhou, Feng

    2017-03-01

    Big data analysis is a hot topic in the IT field now. Spark is a high-reliability and high-performance distributed parallel computing framework for big data sets. K-means algorithm is one of the classical partition methods in clustering algorithm. In this paper, we study the k-means clustering algorithm on Spark. Firstly, the principle of the algorithm is analyzed, and then the clustering analysis is carried out on the supermarket customers through the experiment to find out the different shopping patterns. At the same time, this paper proposes the parallelization of k-means algorithm and the distributed computing framework of Spark, and gives the concrete design scheme and implementation scheme. This paper uses the two-year sales data of a supermarket to validate the proposed clustering algorithm and achieve the goal of subdividing customers, and then analyze the clustering results to help enterprises to take different marketing strategies for different customer groups to improve sales performance.

  8. TORCH Computational Reference Kernels - A Testbed for Computer Science Research

    Energy Technology Data Exchange (ETDEWEB)

    Kaiser, Alex; Williams, Samuel Webb; Madduri, Kamesh; Ibrahim, Khaled; Bailey, David H.; Demmel, James W.; Strohmaier, Erich

    2010-12-02

    For decades, computer scientists have sought guidance on how to evolve architectures, languages, and programming models in order to improve application performance, efficiency, and productivity. Unfortunately, without overarching advice about future directions in these areas, individual guidance is inferred from the existing software/hardware ecosystem, and each discipline often conducts their research independently assuming all other technologies remain fixed. In today's rapidly evolving world of on-chip parallelism, isolated and iterative improvements to performance may miss superior solutions in the same way gradient descent optimization techniques may get stuck in local minima. To combat this, we present TORCH: A Testbed for Optimization ResearCH. These computational reference kernels define the core problems of interest in scientific computing without mandating a specific language, algorithm, programming model, or implementation. To compliment the kernel (problem) definitions, we provide a set of algorithmically-expressed verification tests that can be used to verify a hardware/software co-designed solution produces an acceptable answer. Finally, to provide some illumination as to how researchers have implemented solutions to these problems in the past, we provide a set of reference implementations in C and MATLAB.

  9. Research on personalized recommendation algorithm based on spark

    Science.gov (United States)

    Li, Zeng; Liu, Yu

    2018-04-01

    With the increasing amount of data in the past years, the traditional recommendation algorithm has been unable to meet people's needs. Therefore, how to better recommend their products to users of interest, become the opportunities and challenges of the era of big data development. At present, each platform enterprise has its own recommendation algorithm, but how to make efficient and accurate push information is still an urgent problem for personalized recommendation system. In this paper, a hybrid algorithm based on user collaborative filtering and content-based recommendation algorithm is proposed on Spark to improve the efficiency and accuracy of recommendation by weighted processing. The experiment shows that the recommendation under this scheme is more efficient and accurate.

  10. Accelerators: Sparking Innovation and Transdisciplinary Team Science in Disparities Research

    Directory of Open Access Journals (Sweden)

    Carol R. Horowitz

    2017-02-01

    Full Text Available Development and implementation of effective, sustainable, and scalable interventions that advance equity could be propelled by innovative and inclusive partnerships. Readied catalytic frameworks that foster communication, collaboration, a shared vision, and transformative translational research across scientific and non-scientific divides are needed to foster rapid generation of novel solutions to address and ultimately eliminate disparities. To achieve this, we transformed and expanded a community-academic board into a translational science board with members from public, academic and private sectors. Rooted in team science, diverse board experts formed topic-specific “accelerators”, tasked with collaborating to rapidly generate new ideas, questions, approaches, and projects comprising patients, advocates, clinicians, researchers, funders, public health and industry leaders. We began with four accelerators—digital health, big data, genomics and environmental health—and were rapidly able to respond to funding opportunities, transform new ideas into clinical and community programs, generate new, accessible, actionable data, and more efficiently and effectively conduct research. This innovative model has the power to maximize research quality and efficiency, improve patient care and engagement, optimize data democratization and dissemination among target populations, contribute to policy, and lead to systems changes needed to address the root causes of disparities.

  11. Accelerators: Sparking Innovation and Transdisciplinary Team Science in Disparities Research

    Science.gov (United States)

    Horowitz, Carol R.; Shameer, Khader; Gabrilove, Janice; Atreja, Ashish; Shepard, Peggy; Goytia, Crispin N.; Smith, Geoffrey W.; Dudley, Joel; Manning, Rachel; Bickell, Nina A.; Galvez, Maida P.

    2017-01-01

    Development and implementation of effective, sustainable, and scalable interventions that advance equity could be propelled by innovative and inclusive partnerships. Readied catalytic frameworks that foster communication, collaboration, a shared vision, and transformative translational research across scientific and non-scientific divides are needed to foster rapid generation of novel solutions to address and ultimately eliminate disparities. To achieve this, we transformed and expanded a community-academic board into a translational science board with members from public, academic and private sectors. Rooted in team science, diverse board experts formed topic-specific “accelerators”, tasked with collaborating to rapidly generate new ideas, questions, approaches, and projects comprising patients, advocates, clinicians, researchers, funders, public health and industry leaders. We began with four accelerators—digital health, big data, genomics and environmental health—and were rapidly able to respond to funding opportunities, transform new ideas into clinical and community programs, generate new, accessible, actionable data, and more efficiently and effectively conduct research. This innovative model has the power to maximize research quality and efficiency, improve patient care and engagement, optimize data democratization and dissemination among target populations, contribute to policy, and lead to systems changes needed to address the root causes of disparities. PMID:28241508

  12. Plotting a Course to Spark Scholastic Journalism Research.

    Science.gov (United States)

    Peterson, Jane Willoughby

    1991-01-01

    Discusses a survey of members of the Secondary Education Division of the Association for Education in Journalism and Mass Communication. Explains that respondents ranked certification and preparation of journalism teachers and advisers and the legal and ethical issues of the student press as the most important research topics. (SG)

  13. Research on offense and defense technology for iOS kernel security mechanism

    Science.gov (United States)

    Chu, Sijun; Wu, Hao

    2018-04-01

    iOS is a strong and widely used mobile device system. It's annual profits make up about 90% of the total profits of all mobile phone brands. Though it is famous for its security, there have been many attacks on the iOS operating system, such as the Trident apt attack in 2016. So it is important to research the iOS security mechanism and understand its weaknesses and put forward targeted protection and security check framework. By studying these attacks and previous jailbreak tools, we can see that an attacker could only run a ROP code and gain kernel read and write permissions based on the ROP after exploiting kernel and user layer vulnerabilities. However, the iOS operating system is still protected by the code signing mechanism, the sandbox mechanism, and the not-writable mechanism of the system's disk area. This is far from the steady, long-lasting control that attackers expect. Before iOS 9, breaking these security mechanisms was usually done by modifying the kernel's important data structures and security mechanism code logic. However, after iOS 9, the kernel integrity protection mechanism was added to the 64-bit operating system and none of the previous methods were adapted to the new versions of iOS [1]. But this does not mean that attackers can not break through. Therefore, based on the analysis of the vulnerability of KPP security mechanism, this paper implements two possible breakthrough methods for kernel security mechanism for iOS9 and iOS10. Meanwhile, we propose a defense method based on kernel integrity detection and sensitive API call detection to defense breakthrough method mentioned above. And we make experiments to prove that this method can prevent and detect attack attempts or invaders effectively and timely.

  14. Spark Channels

    Energy Technology Data Exchange (ETDEWEB)

    Haydon, S. C. [Department of Physics, University of New England, Armidale, NSW (Australia)

    1968-04-15

    A brief summary is given of the principal methods used for initiating spark channels and the various highly time-resolved techniques developed recently for studies with nanosecond resolution. The importance of the percentage overvoltage in determining the early history and subsequent development of the various phases of the growth of the spark channel is discussed. An account is then given of the recent photographic, oscillographic and spectroscopic investigations of spark channels initiated by co-axial cable discharges of spark gaps at low [{approx} 1%] overvoltages. The phenomena observed in the development of the immediate post-breakdown phase, the diffuse glow structure, the growth of the luminous filament and the final formation of the spark channel in hydrogen are described. A brief account is also given of the salient features emerging from corresponding studies of highly overvolted spark gaps in which the spark channel develops from single avalanche conditions. The essential differences between the two types of channel formation are summarized and possible explanations of the general features are indicated. (author)

  15. Research on a Novel Kernel Based Grey Prediction Model and Its Applications

    Directory of Open Access Journals (Sweden)

    Xin Ma

    2016-01-01

    Full Text Available The discrete grey prediction models have attracted considerable interest of research due to its effectiveness to improve the modelling accuracy of the traditional grey prediction models. The autoregressive GM(1,1 model, abbreviated as ARGM(1,1, is a novel discrete grey model which is easy to use and accurate in prediction of approximate nonhomogeneous exponential time series. However, the ARGM(1,1 is essentially a linear model; thus, its applicability is still limited. In this paper a novel kernel based ARGM(1,1 model is proposed, abbreviated as KARGM(1,1. The KARGM(1,1 has a nonlinear function which can be expressed by a kernel function using the kernel method, and its modelling procedures are presented in details. Two case studies of predicting the monthly gas well production are carried out with the real world production data. The results of KARGM(1,1 model are compared to the existing discrete univariate grey prediction models, including ARGM(1,1, NDGM(1,1,k, DGM(1,1, and NGBMOP, and it is shown that the KARGM(1,1 outperforms the other four models.

  16. The SPARK Tool to prioritise questions for systematic reviews in health policy and systems research: development and initial validation.

    Science.gov (United States)

    Akl, Elie A; Fadlallah, Racha; Ghandour, Lilian; Kdouh, Ola; Langlois, Etienne; Lavis, John N; Schünemann, Holger; El-Jardali, Fadi

    2017-09-04

    Groups or institutions funding or conducting systematic reviews in health policy and systems research (HPSR) should prioritise topics according to the needs of policymakers and stakeholders. The aim of this study was to develop and validate a tool to prioritise questions for systematic reviews in HPSR. We developed the tool following a four-step approach consisting of (1) the definition of the purpose and scope of tool, (2) item generation and reduction, (3) testing for content and face validity, (4) and pilot testing of the tool. The research team involved international experts in HPSR, systematic review methodology and tool development, led by the Center for Systematic Reviews on Health Policy and Systems Research (SPARK). We followed an inclusive approach in determining the final selection of items to allow customisation to the user's needs. The purpose of the SPARK tool was to prioritise questions in HPSR in order to address them in systematic reviews. In the item generation and reduction phase, an extensive literature search yielded 40 relevant articles, which were reviewed by the research team to create a preliminary list of 19 candidate items for inclusion in the tool. As part of testing for content and face validity, input from international experts led to the refining, changing, merging and addition of new items, and to organisation of the tool into two modules. Following pilot testing, we finalised the tool, with 22 items organised in two modules - the first module including 13 items to be rated by policymakers and stakeholders, and the second including 9 items to be rated by systematic review teams. Users can customise the tool to their needs, by omitting items that may not be applicable to their settings. We also developed a user manual that provides guidance on how to use the SPARK tool, along with signaling questions. We have developed and conducted initial validation of the SPARK tool to prioritise questions for systematic reviews in HPSR, along with

  17. Organizing for ontological change: The kernel of an AIDS research infrastructure

    Science.gov (United States)

    Polk, Jessica Beth

    2015-01-01

    Is it possible to prepare and plan for emergent and changing objects of research? Members of the Multicenter AIDS Cohort Study have been investigating AIDS for over 30 years, and in that time, the disease has been repeatedly transformed. Over the years and across many changes, members have continued to study HIV disease while in the process regenerating an adaptable research organization. The key to sustaining this technoscientific flexibility has been what we call the kernel of a research infrastructure: ongoing efforts to maintain the availability of resources and services that may be brought to bear in the investigation of new objects. In the case of the Multicenter AIDS Cohort Study, these resources are as follows: specimens and data, calibrated instruments, heterogeneous experts, and participating cohorts of gay and bisexual men. We track three ontological transformations, examining how members prepared for and responded to changes: the discovery of a novel retroviral agent (HIV), the ability to test for that agent, and the transition of the disease from fatal to chronic through pharmaceutical intervention. Respectively, we call the work, ‘technologies’, and techniques of adapting to these changes, ‘repurposing’, ‘elaborating’, and ‘extending the kernel’. PMID:26477206

  18. Nursing research across a large health care system: sparking nurses' clinical inquiry.

    Science.gov (United States)

    Wolf, Ilene Sue; Paoletti, Cathy; Du, Hongyan

    2012-01-01

    In our journey to achieve Magnet designation, we sought to increase staff nurses' research participation and teach them about the research process by conducting a corporate-wide study, a blind taste test, using potato chips. To compare 3 varieties of the same-brand potato chips for overall preference and perception of healthiness. We hypothesized that the potato chip the nurses liked the best would not be the chip they perceived as the healthiest. For this institutional review board-approved study, nurses were recruited via (1) randomly selected units and (2) a convenience sample during cafeteria lunch hours. After informed consent was obtained, nurses rated each potato chip in a blinded manner, based on appearance, crispiness, flavor, saltiness, and greasiness. They indicated which potato chip they perceived to be the healthiest and which they preferred overall, and they completed an anonymous demographic questionnaire. A total of 263 nurses participated, with 78% being staff nurses. Regular (full fat) was most preferred (37.6%), whereas fat free was least preferred (16%) and also considered the healthiest (45.2%) (P free chip as the healthiest, proving our hypothesis that the preferred chip would not be considered the healthiest. This study was easy, feasible, and helped promote systemwide nursing research.

  19. Research of combustion in older generation spark-ignition engines in the condition of use leaded and unleaded petrol

    Directory of Open Access Journals (Sweden)

    Bulatović Željko M.

    2014-01-01

    Full Text Available This paper analyzes the potential problems in the exploitation of the older generation of spark-ignition engines with higher octane number of petrol (unleaded petrol BMB 95 than required (leaded petrol MB 86. Within the experimental tests on two different engines (STEYR-PUCH model 712 and GAZ 41 by applying piezoelectric pressure sensors integrated with the engine spark plugs, acceleration sensors (accelerometers and special electronic block connected with distributor, show that the cumulative first and second theoretical phase of combustion when petrol of higher octane number (BMB 95 is used lasts slightly longer than when the low-octane petrol MB 86 is used. For new petrol (BMB 95 higher optimal angles of pre-ignition have been determined by which better performances of the engine are achieved without a danger of the combustion with detonation (also called knocking.

  20. Fastdata processing with Spark

    CERN Document Server

    Karau, Holden

    2013-01-01

    This book will be a basic, step-by-step tutorial, which will help readers take advantage of all that Spark has to offer.Fastdata Processing with Spark is for software developers who want to learn how to write distributed programs with Spark. It will help developers who have had problems that were too much to be dealt with on a single computer. No previous experience with distributed programming is necessary. This book assumes knowledge of either Java, Scala, or Python.

  1. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  2. Optical spark chamber

    CERN Multimedia

    CERN PhotoLab

    1971-01-01

    An optical spark chamber developed for use in the Omega spectrometer. On the left the supporting frame is exceptionally thin to allow low momentum particles to escape and be detected outside the magnetic field.

  3. Research of performance on a spark ignition engine fueled by alcohol–gasoline blends using artificial neural networks

    International Nuclear Information System (INIS)

    Kapusuz, Murat; Ozcan, Hakan; Yamin, Jehad Ahmad

    2015-01-01

    In this paper, we investigate various alcohol–unleaded gasoline mixtures that can be used with no modifications in a spark-ignition engine. The mixtures consisted of 5%, 10% and 15% ethanol, methanol together and separately. Based on the recommendations of the Jordanian Petroleum Company (JoPetrol), total alcohol content should not exceed 15–20% owing to safety and ignition hazards. Optimizations for the use of alcohol were made for the maximum torque, maximum power and minimum specific fuel consumption values. For torque 0.9906, for brake power 0.997, and for brake specific fuel consumption 0.9312 regression values for tests have been obtained from models generated by the neural network. According to the modeling and optimizations, use of fuel mixture containing 11% methanol–1% ethanol for performance, and fuel mixture containing 2% methanol for BSFC were found to have better results. Moreover, the paper demonstrates that ANN (Artificial Neural Network) can be used successfully as an alternative type of modeling technique for internal combustion engines. - Highlights: • ANN model was developed and verified. • Effects of alcohol–gasoline blends on performance of a SI engine are fairly simulated. • Effects of alcohol–gasoline blends on performance of a SI engine are optimized.

  4. Testing Infrastructure for Operating System Kernel Development

    DEFF Research Database (Denmark)

    Walter, Maxwell; Karlsson, Sven

    2014-01-01

    Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....

  5. SparkRS - Spark for Remote Sensing, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation is Spark-RS, an open source software project that enables GPU-accelerated remote sensing workflows in an Apache Spark distributed computing...

  6. Numerical study of the ignition behavior of a post-discharge kernel injected into a turbulent stratified cross-flow

    Science.gov (United States)

    Jaravel, Thomas; Labahn, Jeffrey; Ihme, Matthias

    2017-11-01

    The reliable initiation of flame ignition by high-energy spark kernels is critical for the operability of aviation gas turbines. The evolution of a spark kernel ejected by an igniter into a turbulent stratified environment is investigated using detailed numerical simulations with complex chemistry. At early times post ejection, comparisons of simulation results with high-speed Schlieren data show that the initial trajectory of the kernel is well reproduced, with a significant amount of air entrainment from the surrounding flow that is induced by the kernel ejection. After transiting in a non-flammable mixture, the kernel reaches a second stream of flammable methane-air mixture, where the successful of the kernel ignition was found to depend on the local flow state and operating conditions. By performing parametric studies, the probability of kernel ignition was identified, and compared with experimental observations. The ignition behavior is characterized by analyzing the local chemical structure, and its stochastic variability is also investigated.

  7. Ignition of turbulent swirling n-heptane spray flames using single and multiple sparks

    Energy Technology Data Exchange (ETDEWEB)

    Marchionea, T.; Ahmeda, S.F.; Mastorakos, E. [Department of Engineering, University of Cambridge (United Kingdom)

    2009-01-15

    This paper examines ignition processes of an n-heptane spray in a flow typical of a liquid-fuelled burner. The spray is created by a hollow-cone pressure atomiser placed in the centre of a bluff body, around which swirling air induces a strong recirculation zone. Ignition was achieved by single small sparks of short duration (2 mm; 0.5 ms), located at various places inside the flow so as to identify the most ignitable regions, or larger sparks of longer duration (5 mm; 8 ms) repeated at 100 Hz, located close to the combustion chamber enclosure so as to mimic the placement and characteristics of a gas turbine combustor surface igniter. The air and droplet velocities, the droplet diameter, and the total (i.e. liquid plus vapour) equivalence ratio were measured in inert flow by phase Doppler anemometry and sampling respectively. Fast camera imaging suggested that successful ignition events were associated with flamelets that propagated back towards the spray nozzle. Measurements of ignition probability with the single spark showed that localised ignition inside the spray is more likely to result in successful flame establishment when the spark is located in a region of negative velocity, relatively small droplet Sauter mean diameter, and mean equivalence ratio within the flammability limits. Ignition with the single spark was not possible at the location where the multiple spark experiments were performed. For those, the multiple spark sequence lasted approximately 1 to 5 s. It was found that a long spark sequence increases the ignition efficiency, which reached a maximum of 100% at the axial distance where the recirculation zone had maximum width. Ignition was not feasible with the spark downstream of about two burner diameters. Visualisation showed that small flame kernels emanate very often from the spark, which can be stretched as far as 20 mm from the electrodes by the turbulent velocity fluctuations. These kernels survive very little time. Successful overall

  8. Sparking Connections: Toward Better Linkages Between Research and Human Health Policy — An Example with Multiwalled Carbon Nanotubes

    Science.gov (United States)

    Risk assessment and subsequent risk management of environmental contaminants can benefit from early collaboration among researchers, risk assessors and risk managers. The benefits of collaboration in research planning are particularly evident in light of 1) increasing calls to ex...

  9. Laser ignition - Spark plug development and application in reciprocating engines

    Science.gov (United States)

    Pavel, Nicolaie; Bärwinkel, Mark; Heinz, Peter; Brüggemann, Dieter; Dearden, Geoff; Croitoru, Gabriela; Grigore, Oana Valeria

    2018-03-01

    Combustion is one of the most dominant energy conversion processes used in all areas of human life, but global concerns over exhaust gas pollution and greenhouse gas emission have stimulated further development of the process. Lean combustion and exhaust gas recirculation are approaches to improve the efficiency and to reduce pollutant emissions; however, such measures impede reliable ignition when applied to conventional ignition systems. Therefore, alternative ignition systems are a focus of scientific research. Amongst others, laser induced ignition seems an attractive method to improve the combustion process. In comparison with conventional ignition by electric spark plugs, laser ignition offers a number of potential benefits. Those most often discussed are: no quenching of the combustion flame kernel; the ability to deliver (laser) energy to any location of interest in the combustion chamber; the possibility of delivering the beam simultaneously to different positions, and the temporal control of ignition. If these advantages can be exploited in practice, the engine efficiency may be improved and reliable operation at lean air-fuel mixtures can be achieved, making feasible savings in fuel consumption and reduction in emission of exhaust gasses. Therefore, laser ignition can enable important new approaches to address global concerns about the environmental impact of continued use of reciprocating engines in vehicles and power plants, with the aim of diminishing pollutant levels in the atmosphere. The technology can also support increased use of electrification in powered transport, through its application to ignition of hybrid (electric-gas) engines, and the efficient combustion of advanced fuels. In this work, we review the progress made over the last years in laser ignition research, in particular that aimed towards realizing laser sources (or laser spark plugs) with dimensions and properties suitable for operating directly on an engine. The main envisaged

  10. Research of some operating parameters and the emissions level variation in a spark ignited engine through on-board investigation methods in different loading conditions

    Science.gov (United States)

    Iosif, Ferenti; Baldean, Doru Laurean

    2014-06-01

    The present paper shows research made on a spark ignited engine with port fuel injection in different operation conditions in order to improve the comprehension about the cold start sequence, acceleration when changing the gear ratios, quality of combustion process and also any measures to be taken for pollutant reduction in such cases. The engineering endeavor encompasses the pollutants investigation during the operation time of gasoline supplied engine with four inline cylinders in different conditions. The temperature and any other parameters were measured with specific sensors installed on the engine or in the exhaust pipes. All the data collected has been evaluated using electronic investigation systems and highly developed equipment. In this manner it has enabled the outline of the idea of how pollutants of engine vary in different operating conditions. Air quality in the everyday environment is very important for the human health, and thus the ambient air quality has a well-known importance in the European pollution standards and legislation. The high level of attention directed to the pollution problem in the European lifestyle is a driving force for all kinds of studies in the field of the reduction of engine emission.

  11. Acquisition of Mechanically Assisted Spark Plasma Sintering System for Advanced Research and Education on Functionally Graded Hybrid Materials

    Science.gov (United States)

    2012-03-14

    Institute. The proposed effort offers a multidisciplinary research program to achieve the topic goals by coupling thermal- acoustic - mechanical flight...optional optical pyrometer .  Single port for standard (mechanical vacuum pump) and high vacuum system. POWER SUPPLY  10,000 amp, 10 VDC pulsed...Amperage TEMPERATURE CONTROL SYSTEM  Ten (10) Type K and five (5) Type C thermocouples with protective flexible sheaths.  Optical Pyrometer

  12. Formation of small sparks

    International Nuclear Information System (INIS)

    Barreto, E.; Jurenka, H.; Reynolds, S.I.

    1977-01-01

    The formation of a small incendiary spark at atmospheric pressure is identified with the transition from a weakly to a strongly ionized plasma. It is shown that initial gaseous ionization produced by avalanches and/or streamers always creates a high-temperature ideal electron gas that can shield the applied voltage difference and reduce ionization in the volume of the gas. The electron gas is collision dominated but able to maintain its high temperature, for times long compared to discharge events, through long-range Coulomb forces. In fact, electrons in the weakly ionized plasma constitute a collisionless independent fluid with a thermodynamic state that can be affected directly by field or density changes. Accordingly, with metal electrodes, cathode spot emission is always associated with the transition to a strongly ionized plasma. Neutral heating can be accomplished in two different ways. Effective dispersal of the electrons from the cathode leads to electron heating dominated by diffusion effects. Conversely, a fast rate of emission or rapid field changes can produce nonlinear wave propagation. It is shown that solitary waves are possible, and it is suggested that some spark transitions are associated with shock waves in the collisionless electron gas. In either the diffuse or nonlinear regime, neutral gas heating is controlled by collisions of ions with isotropic thermal electrons. This interaction is always subsequent to changes in state of the electron gas population. The basic results obtained should apply to all sparks

  13. Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

    OpenAIRE

    Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

    2016-01-01

    To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...

  14. Approximate kernel competitive learning.

    Science.gov (United States)

    Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

    2015-03-01

    Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Experimental study of plume induced by nanosecond repetitively pulsed spark microdischarges in air at atmospheric pressure

    Science.gov (United States)

    Orriere, Thomas; Benard, Nicolas; Moreau, Eric; Pai, David

    2016-09-01

    Nanosecond repetitively pulsed (NRP) spark discharges have been widely studied due to their high chemical reactivity, low gas temperature, and high ionization efficiency. They are useful in many research areas: nanomaterials synthesis, combustion, and aerodynamic flow control. In all of these fields, particular attention has been devoted to chemical species transport and/or hydrodynamic and thermal effects for applications. The aim of this study is to generate an electro-thermal plume by combining an NRP spark microdischarge in a pin-to-pin configuration with a third DC-biased electrode placed a few centimeters away. First, electrical characterization and optical emission spectroscopy were performed to reveal important plasma processes. Second, particle image velocimetry was combined with schlieren photography to investigate the main characteristics of the generated flow. Heating processes are measured by using the N2(C ->B) (0,2) and (1,3) vibrational bands, and effects due to the confinement of the discharge are described. Moreover, the presence of atomic ions N+ and O+ is discussed. Finally, the electro-thermal plume structure is characterized by a flow velocity around 1.8 m.s-1, and the thermal kernel has a spheroidal shape.

  16. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

    SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model, is able to model the rate of occurrence of... kernel methods made use of: (i) the Bayesian property of improving predictive accuracy as data are dynamically obtained, and (ii) the kernel function

  17. DNS of spark ignition and edge flame propagation in turbulent droplet-laden mixing layers

    Energy Technology Data Exchange (ETDEWEB)

    Neophytou, A.; Mastorakos, E.; Cant, R.S. [Hopkinson Laboratory, Department of Engineering, University of Cambridge (United Kingdom)

    2010-06-15

    A parametric study of forced ignition at the mixing layer between air and air carrying fine monosized fuel droplets is done through one-step chemistry direct numerical simulations to determine the influence of the size and volatility of the droplets, the spark location, the droplet-air mixing layer initial thickness and the turbulence intensity on the ignition success and the subsequent flame propagation. The propagation is analyzed in terms of edge flame displacement speed, which has not been studied before for turbulent edge spray flames. Spark ignition successfully resulted in a tribrachial flame if enough fuel vapour was available at the spark location, which occurred when the local droplet number density was high. Ignition was achieved even when the spark was offset from the spray, on the air side, due to the diffusion of heat from the spark, provided droplets evaporated rapidly. Large kernels were obtained by sparking close to the spray, since fuel was more readily available. At long times after the spark, for all flames studied, the probability density function of the displacement speed was wide, with a mean value in the range 0.55-0.75S{sub L}, with S{sub L} the laminar burning velocity of a stoichiometric gaseous premixed flame. This value is close to the mean displacement speed in turbulent edge flames with gaseous fuel. The displacement speed was negatively correlated with curvature. The detrimental effect of curvature was attenuated with a large initial kernel and by increasing the thickness of the mixing layer. The mixing layer was thicker when evaporation was slow and the turbulence intensity higher. However, high turbulence intensity also distorted the kernel which could lead to high values of curvature. The edge flame reaction component increased when the maximum temperature coincided with the stoichiometric contour. The results are consistent with the limited available experimental evidence and provide insights into the processes associated with

  18. Modelling Spark Integration in Science Classroom

    Directory of Open Access Journals (Sweden)

    Marie Paz E. Morales

    2014-02-01

    Full Text Available The study critically explored how a PASCO-designed technology (SPARK ScienceLearning System is meaningfully integrated into the teaching of selected topics in Earth and Environmental Science. It highlights on modelling the effectiveness of using the SPARK Learning System as a primary tool in learning science that leads to learning and achievement of the students. Data and observation gathered and correlation of the ability of the technology to develop high intrinsic motivation to student achievement were used to design framework on how to meaningfully integrate SPARK ScienceLearning System in teaching Earth and Environmental Science. Research instruments used in this study were adopted from standardized questionnaires available from literature. Achievement test and evaluation form were developed and validated for the purpose of deducing data needed for the study. Interviews were done to delve into the deeper thoughts and emotions of the respondents. Data from the interviews served to validate all numerical data culled from this study. Cross-case analysis of the data was done to reveal some recurring themes, problems and benefits derived by the students in using the SPARK Science Learning System to further establish its effectiveness in the curriculum as a forerunner to the shift towards the 21st Century Learning.

  19. Fast data processing with Spark

    CERN Document Server

    Sankar, Krishna

    2015-01-01

    Fast Data Processing with Spark - Second Edition is for software developers who want to learn how to write distributed programs with Spark. It will help developers who have had problems that were too big to be dealt with on a single computer. No previous experience with distributed programming is necessary. This book assumes knowledge of either Java, Scala, or Python.

  20. Tool grinding and spark testing

    Science.gov (United States)

    Widener, Edward L.

    1993-01-01

    The objectives were the following: (1) to revive the neglected art of metal-sparking; (2) to promote quality-assurance in the workplace; (3) to avoid spark-ignited explosions of dusts or volatiles; (4) to facilitate the salvage of scrap metals; and (5) to summarize important references.

  1. Primary Science Interview: Science Sparks

    Science.gov (United States)

    Bianchi, Lynne

    2016-01-01

    In this "Primary Science" interview, Lynne Bianchi talks with Emma Vanstone about "Science Sparks," which is a website full of creative, fun, and exciting science activity ideas for children of primary-school age. "Science Sparks" started with the aim of inspiring more parents to do science at home with their…

  2. Modelling of spark to ignition transition in gas mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Akram, M.

    1996-10-01

    This thesis pertains to the models for studying sparking in chemically inert gases. The processes taking place in a spark to flame transition can be segregated into physical and chemical processes, and this study is focused on physical processes. The plasma is regarded as a single-substance material. One and two-dimensional models are developed. The transfer of electrical energy into thermal energy of the gas and its redistribution in space and time along with the evolution of a plasma kernel is studied in the time domain ranging from 10 ns to 40 micros. In the case of ultra-fast sparks, the propagation of the shock and its reflection from a rigid wall is presented. The influence of electrode shape and the gap size on the flow structure development is found to be a dominating factor. It is observed that the flow structure that has developed in the early stage more or less prevails at later stages and strongly influences the shape and evolution of the hot kernel. The electrode geometry and configuration are responsible for the development of the flow structure. The strength of the vortices generated in the flow field is influenced by the power input to the gap and their location of emergence is dictated by the electrode shape and configuration. The heat transfer after 2 micros in the case of ultra-fast sparks is dominated by convection and diffusion. The strong mixing produced by hydrodynamic effects and the electrode geometry give the indication that the magnetic pinch effect might be negligible. Finally, a model for a multicomponent gas mixture is presented. The chemical kinetics mechanism for dissociation and ionization is introduced. 56 refs

  3. Optimized Kernel Entropy Components.

    Science.gov (United States)

    Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

    2017-06-01

    This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

  4. Subsampling Realised Kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our...... that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled...

  5. Enhancement of flame development by microwave-assisted spark ignition in constant volume combustion chamber

    KAUST Repository

    Wolk, Benjamin

    2013-07-01

    The enhancement of laminar flame development using microwave-assisted spark ignition has been investigated for methane-air mixtures at a range of initial pressures and equivalence ratios in a 1.45. l constant volume combustion chamber. Microwave enhancement was evaluated on the basis of several parameters including flame development time (FDT) (time for 0-10% of total net heat release), flame rise time (FRT) (time for 10-90% of total net heat release), total net heat release, flame kernel growth rate, flame kernel size, and ignitability limit extension. Compared to a capacitive discharge spark, microwave-assisted spark ignition extended the lean and rich ignition limits at all pressures investigated (1.08-7.22. bar). The addition of microwaves to a capacitive discharge spark reduced FDT and increased the flame kernel size for all equivalence ratios tested and resulted in increases in the spatial flame speed for sufficiently lean flames. Flame enhancement is believed to be caused by (1) a non-thermal chemical kinetic enhancement from energy deposition to free electrons in the flame front and (2) induced flame wrinkling from excitation of flame (plasma) instability. The enhancement of flame development by microwaves diminishes as the initial pressure of the mixture increases, with negligible flame enhancement observed above 3. bar. © 2013 The Combustion Institute.

  6. Iterative software kernels

    Energy Technology Data Exchange (ETDEWEB)

    Duff, I.

    1994-12-31

    This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.

  7. Ultra Fast, High Rep Rate, High Voltage Spark Gap Pulser

    Science.gov (United States)

    1995-07-01

    current rise time. The spark gap was designed to have a coaxial geometry reducing its inductance. Provisions were made to pass flowing gas between the...ULTRA FAST, HIGH REP RATE, HIGH VOLTAGE SPARK GAP PULSER Robert A. Pastore Jr., Lawrence E. Kingsley, Kevin Fonda, Erik Lenzing Electrophysics and...Modeling Branch AMSRL-PS-EA Tel.: (908)-532-0271 FAX: (908)-542-3348 U.S. Army Research Laboratory Physical Sciences Directorate Ft. Monmouth

  8. An Evaluation of Kernel Equating: Parallel Equating with Classical Methods in the SAT Subject Tests[TM] Program. Research Report. ETS RR-09-06

    Science.gov (United States)

    Grant, Mary C.; Zhang, Lilly; Damiano, Michele

    2009-01-01

    This study investigated kernel equating methods by comparing these methods to operational equatings for two tests in the SAT Subject Tests[TM] program. GENASYS (ETS, 2007) was used for all equating methods and scaled score kernel equating results were compared to Tucker, Levine observed score, chained linear, and chained equipercentile equating…

  9. Classification With Truncated Distance Kernel.

    Science.gov (United States)

    Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

    2018-05-01

    This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

  10. A spectroscopy study of gasoline partially premixed compression ignition spark assisted combustion

    International Nuclear Information System (INIS)

    Pastor, J.V.; García-Oliver, J.M.; García, A.; Micó, C.; Durrett, R.

    2013-01-01

    Highlights: ► PPC combustion combined with spark assistance and gasoline fuel on a CI engine. ► Chemiluminescence of different chemical species describes the progress of combustion reaction. ► Spectra of a novel combustion mode under SACI conditions is described. ► UV–Visible spectrometry, high speed imaging and pressure diagnostic were employed for analysis. - Abstract: Nowadays many research efforts are focused on the study and development of new combustion modes, mainly based on the use of locally lean air–fuel mixtures. This characteristic, combined with exhaust gas recirculation, provides low combustion temperatures that reduces pollutant formation and increases efficiency. However these combustion concepts have some drawbacks, related to combustion phasing control, which must be overcome. In this way, the use of a spark plug has shown to be a good solution to improve phasing control in combination with lean low temperature combustion. Its performance is well reported on bibliography, however phenomena involving the combustion process are not completely described. The aim of the present work is to develop a detailed description of the spark assisted compression ignition mode by means of application of UV–Visible spectrometry, in order to improve insight on the combustion process. Tests have been performed in an optical engine by means of broadband radiation imaging and emission spectrometry. The engine hardware is typical of a compression ignition passenger car application. Gasoline was used as the fuel due to its low reactivity. Combining broadband luminosity images with pressure-derived heat-release rate and UV–Visible spectra, it was possible to identify different stages of the combustion reaction. After the spark discharge, a first flame kernel appears and starts growing as a premixed flame front, characterized by a low and constant heat-release rate in combination with the presence of remarkable OH radical radiation. Heat release increases

  11. Kernels for structured data

    CERN Document Server

    Gärtner, Thomas

    2009-01-01

    This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by

  12. Locally linear approximation for Kernel methods : the Railway Kernel

    OpenAIRE

    Muñoz, Alberto; González, Javier

    2008-01-01

    In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...

  13. Data-variant kernel analysis

    CERN Document Server

    Motai, Yuichi

    2015-01-01

    Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include

  14. Digital signal processing with kernel methods

    CERN Document Server

    Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

    2018-01-01

    A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

  15. Are Crab nanoshots Schwinger sparks?

    Energy Technology Data Exchange (ETDEWEB)

    Stebbins, Albert [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Yoo, Hojin [Univ. of Wisconsin, Madison, WI (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)

    2015-05-21

    The highest brightness temperature ever observed are from "nanoshots" from the Crab pulsar which we argue could be the signature of bursts of vacuum e± pair production. If so this would be the first time the astronomical Schwinger effect has been observed. These "Schwinger sparks" would be an intermittent but extremely powerful, ~103 L, 10 PeV e± accelerator in the heart of the Crab. These nanosecond duration sparks are generated in a volume less than 1 m3 and the existence of such sparks has implications for the small scale structure of the magnetic field of young pulsars such as the Crab. As a result, this mechanism may also play a role in producing other enigmatic bright short radio transients such as fast radio bursts.

  16. On flame kernel formation and propagation in premixed gases

    Energy Technology Data Exchange (ETDEWEB)

    Eisazadeh-Far, Kian; Metghalchi, Hameed [Northeastern University, Mechanical and Industrial Engineering Department, Boston, MA 02115 (United States); Parsinejad, Farzan [Chevron Oronite Company LLC, Richmond, CA 94801 (United States); Keck, James C. [Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)

    2010-12-15

    Flame kernel formation and propagation in premixed gases have been studied experimentally and theoretically. The experiments have been carried out at constant pressure and temperature in a constant volume vessel located in a high speed shadowgraph system. The formation and propagation of the hot plasma kernel has been simulated for inert gas mixtures using a thermodynamic model. The effects of various parameters including the discharge energy, radiation losses, initial temperature and initial volume of the plasma have been studied in detail. The experiments have been extended to flame kernel formation and propagation of methane/air mixtures. The effect of energy terms including spark energy, chemical energy and energy losses on flame kernel formation and propagation have been investigated. The inputs for this model are the initial conditions of the mixture and experimental data for flame radii. It is concluded that these are the most important parameters effecting plasma kernel growth. The results of laminar burning speeds have been compared with previously published results and are in good agreement. (author)

  17. Bright Sparks of Our Future!

    Science.gov (United States)

    Riordan, Naoimh

    2016-04-01

    My name is Naoimh Riordan and I am the Vice Principal of Rockboro Primary School in Cork City, South of Ireland. I am a full time class primary teacher and I teach 4th class, my students are aged between 9-10 years. My passion for education has developed over the years and grown towards STEM (Science, Technology, Engineering and Mathematics) subjects. I believe these subjects are the way forward for our future. My passion and beliefs are driven by the unique after school programme that I have developed. It is titled "Sparks" coming from the term Bright Sparks. "Sparks" is an after school programme with a difference where the STEM subjects are concentrated on through lessons such as Science, Veterinary Science Computer Animation /Coding, Eco engineering, Robotics, Magical Maths, Chess and Creative Writing. All these subjects are taught through activity based learning and are one-hour long each week for a ten-week term. "Sparks" is fully inclusive and non-selective which gives all students of any level of ability an opportunity to engage into these subjects. "Sparks" is open to all primary students in County Cork. The "Sparks" after school programme is taught by tutors from the different Universities and Colleges in Cork City. It works very well because the tutor brings their knowledge, skills and specialised equipment from their respective universities and in turn the tutor gains invaluable teaching practise, can trial a pilot programme in a chosen STEM subject and gain an insight into what works in the physical classroom.

  18. Development of a SPARK Training Dataset

    International Nuclear Information System (INIS)

    Sayre, Amanda M.; Olson, Jarrod R.

    2015-01-01

    In its first five years, the National Nuclear Security Administration's (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK's intended analysis capability. The analysis demonstration sought to answer

  19. Spark channel propagation in a microbubble liquid

    Energy Technology Data Exchange (ETDEWEB)

    Panov, V. A.; Vasilyak, L. M., E-mail: vasilyak@ihed.ras.ru; Vetchinin, S. P.; Pecherkin, V. Ya.; Son, E. E. [Russian Academy of Sciences, Joint Institute for High Temperatures (Russian Federation)

    2016-11-15

    Experimental study on the development of the spark channel from the anode needle under pulsed electrical breakdown of isopropyl alcohol solution in water with air microbubbles has been performed. The presence of the microbubbles increases the velocity of the spark channel propagation and increases the current in the discharge gap circuit. The observed rate of spark channel propagation in microbubble liquid ranges from 4 to 12 m/s, indicating the thermal mechanism of the spark channel development in a microbubble liquid.

  20. Pressure dependence of the spark constant

    Energy Technology Data Exchange (ETDEWEB)

    Hess, H; Radtke, R; Deparade, W [Akademie der Wissenschaften der DDR, Berlin. Zentralinstitut fuer Elektronenphysik

    1978-02-21

    The author's theory on the development of LTE plasmas in low-inductance spark discharges has proved to be a useful tool in predicting the electric behaviour of such sparks. Their earlier experimental work was restricted to only one initial pressure, and in this paper they extend the examined pressure range to obtain some general conclusions on the pressure dependence of the spark behaviour.

  1. Realized kernels in practice

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger

    2009-01-01

    and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...

  2. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  3. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  4. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

    We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

  5. Development of a SPARK Training Dataset

    Energy Technology Data Exchange (ETDEWEB)

    Sayre, Amanda M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Olson, Jarrod R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-01

    In its first five years, the National Nuclear Security Administration’s (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK’s intended analysis capability. The analysis demonstration sought to answer the

  6. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  7. Kernel bundle EPDiff

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads

    2011-01-01

    In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space...

  8. Kernel structures for Clouds

    Science.gov (United States)

    Spafford, Eugene H.; Mckendry, Martin S.

    1986-01-01

    An overview of the internal structure of the Clouds kernel was presented. An indication of how these structures will interact in the prototype Clouds implementation is given. Many specific details have yet to be determined and await experimentation with an actual working system.

  9. Fiber coupled optical spark delivery system

    Science.gov (United States)

    Yalin, Azer; Willson, Bryan; Defoort, Morgan

    2008-08-12

    A spark delivery system for generating a spark using a laser beam is provided, the spark delivery system including a laser light source and a laser delivery assembly. The laser delivery assembly includes a hollow fiber and a launch assembly comprising launch focusing optics to input the laser beam in the hollow fiber. In addition, the laser delivery assembly includes exit focusing optics that demagnify an exit beam of laser light from the hollow fiber, thereby increasing the intensity of the laser beam and creating a spark. In accordance with embodiments of the present invention, the assembly may be used to create a spark in a combustion engine. In accordance with other embodiments of the present invention, a method of using the spark delivery system is provided. In addition, a method of choosing an appropriate fiber for creating a spark using a laser beam is also presented.

  10. Construction of Chained True Score Equipercentile Equatings under the Kernel Equating (KE) Framework and Their Relationship to Levine True Score Equating. Research Report. ETS RR-09-24

    Science.gov (United States)

    Chen, Haiwen; Holland, Paul

    2009-01-01

    In this paper, we develop a new chained equipercentile equating procedure for the nonequivalent groups with anchor test (NEAT) design under the assumptions of the classical test theory model. This new equating is named chained true score equipercentile equating. We also apply the kernel equating framework to this equating design, resulting in a…

  11. Viscosity kernel of molecular fluids

    DEFF Research Database (Denmark)

    Puscasu, Ruslan; Todd, Billy; Daivis, Peter

    2010-01-01

    , temperature, and chain length dependencies of the reciprocal and real-space viscosity kernels are presented. We find that the density has a major effect on the shape of the kernel. The temperature range and chain lengths considered here have by contrast less impact on the overall normalized shape. Functional...... forms that fit the wave-vector-dependent kernel data over a large density and wave-vector range have also been tested. Finally, a structural normalization of the kernels in physical space is considered. Overall, the real-space viscosity kernel has a width of roughly 3–6 atomic diameters, which means...

  12. Preliminary investigation into the simulation of a laser-induced plasma by means of a floating object in a spark gap

    CSIR Research Space (South Africa)

    West, NJ

    2007-08-01

    Full Text Available In this research, an orthogonally laser-triggered spark gap is investigated. The laser beam is directed in the region of a 30mm spark gap at 90 degrees to the gap and focused on the axis. The influence of plasma position within the spark gap...

  13. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

    We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to b...

  14. Steerability of Hermite Kernel

    Czech Academy of Sciences Publication Activity Database

    Yang, Bo; Flusser, Jan; Suk, Tomáš

    2013-01-01

    Roč. 27, č. 4 (2013), 1354006-1-1354006-25 ISSN 0218-0014 R&D Projects: GA ČR GAP103/11/1552 Institutional support: RVO:67985556 Keywords : Hermite polynomials * Hermite kernel * steerability * adaptive filtering Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.558, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/yang-0394387. pdf

  15. Sample preparations for spark source mass spectrography

    International Nuclear Information System (INIS)

    Catlett, C.W.; Rollins, M.B.; Griffin, E.B.; Dorsey, J.G.

    1977-10-01

    Methods have been developed for the preparation of various materials for spark source mass spectrography. The essential features of these preparations (all which can provide adequate precision in a cost-effective manner) consist in obtaining spark-stable electrode sample pieces, a common matrix, a reduction of anomolous effects in the spark, the incorporation of a suitable internal standard for plate response normalization, and a reduction in time

  16. The pressure dependence of the spark constant

    International Nuclear Information System (INIS)

    Hess, H.; Radtke, R.; Deparade, W.

    1978-01-01

    The author's theory on the development of LTE plasmas in low-inductance spark discharges has proved to be a useful tool in predicting the electric behaviour of such sparks. Their earlier experimental work was restricted to only one initial pressure, and in this paper they extend the examined pressure range to obtain some general conclusions on the pressure dependence of the spark behaviour. (author)

  17. New spark test device for material characterization

    CERN Document Server

    Kildemo, Morten

    2004-01-01

    An automated spark test system based on combining field emission and spark measurements, exploiting a discharging capacitor is investigated. In particular, the remaining charge on the capacitor is analytically solved assuming the field emitted current to follow the Fowler Nordheim expression. The latter allows for field emission measurements from pA to A currents, and spark detection by complete discharge of the capacitor. The measurement theory and experiments on Cu and W are discussed.

  18. Kernel Machine SNP-set Testing under Multiple Candidate Kernels

    Science.gov (United States)

    Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

    2013-01-01

    Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

  19. SparkText: Biomedical Text Mining on Big Data Framework

    Science.gov (United States)

    He, Karen Y.; Wang, Kai

    2016-01-01

    Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

  20. SparkText: Biomedical Text Mining on Big Data Framework.

    Directory of Open Access Journals (Sweden)

    Zhan Ye

    Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

  1. SparkText: Biomedical Text Mining on Big Data Framework.

    Science.gov (United States)

    Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

    Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

  2. The definition of kernel Oz

    OpenAIRE

    Smolka, Gert

    1994-01-01

    Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...

  3. 7 CFR 981.7 - Edible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

  4. 7 CFR 981.408 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

  5. 7 CFR 981.8 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

  6. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  7. Experimental Investigation of Augmented Spark Ignition of a LO2/LCH4 Reaction Control Engine at Altitude Conditions

    Science.gov (United States)

    Kleinhenz, Julie; Sarmiento, Charles; Marshall, William

    2012-01-01

    The use of nontoxic propellants in future exploration vehicles would enable safer, more cost-effective mission scenarios. One promising green alternative to existing hypergols is liquid methane (LCH4) with liquid oxygen (LO2). A 100 lbf LO2/LCH4 engine was developed under the NASA Propulsion and Cryogenic Advanced Development project and tested at the NASA Glenn Research Center Altitude Combustion Stand in a low pressure environment. High ignition energy is a perceived drawback of this propellant combination; so this ignition margin test program examined ignition performance versus delivered spark energy. Sensitivity of ignition to spark timing and repetition rate was also explored. Three different exciter units were used with the engine s augmented (torch) igniter. Captured waveforms indicated spark behavior in hot fire conditions was inconsistent compared to the well-behaved dry sparks. This suggests that rising pressure and flow rate increase spark impedance and may at some point compromise an exciter s ability to complete each spark. The reduced spark energies of such quenched deliveries resulted in more erratic ignitions, decreasing ignition probability. The timing of the sparks relative to the pressure/flow conditions also impacted the probability of ignition. Sparks occurring early in the flow could trigger ignition with energies as low as 1 to 6 mJ, though multiple, similarly timed sparks of 55 to 75 mJ were required for reliable ignition. Delayed spark application and reduced spark repetition rate both correlated with late and occasional failed ignitions. An optimum time interval for spark application and ignition therefore coincides with propellant introduction to the igniter.

  8. Programmable spark counter of tracks

    International Nuclear Information System (INIS)

    Denisov, A.E.; Nikolaev, V.A.; Vorobjev, I.B.

    2005-01-01

    For the purpose, a new set-the programmable all-automatic spark counter AIST-4-has been developed and manufactured. Compared to our previous automated spark counter ISTRA, which was operated by the integrated fixed program, the new set is operated completely by a personal computer. The mechanism for pressing and pulling the aluminized foil is put into action by a step motor operated by a microcontroller. The step motor turns an axle. The axle has two eccentrics. One of them moves a pressing plate up and down. The second eccentric moves the aluminized foil by steps of ∼15mm after the end of each pulse counting. One turnover of the axle corresponds to one pulse count cycle. The step motor, the high-voltage block and the pulse count block are operated by the microcontroller PIC 16C84 (Microstar). The set can be operated either manually by keys on the front panel or by a PC using dialogue windows for radon or neutron measurements (for counting of alpha or fission fragment tracks). A number of algorithms are developed: the general procedures, the automatic stopping of the pulse counting, the calibration curve, determination of the count characteristics and elimination of the short circuit in a track

  9. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  10. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

    2006-01-01

    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

  11. Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

    Science.gov (United States)

    Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

    2018-02-13

    Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. INFLUENCE OF ELECTRIC SPARK ON HARDNESS OF CARBON STEEL

    Directory of Open Access Journals (Sweden)

    I. O. Vakulenko

    2014-03-01

    Full Text Available Purpose. The purpose of work is an estimation of influence of an electric spark treatment on the state of mouldable superficial coverage of carbon steel. Methodology. The steel of fragment of railway wheel rim served as material for research with chemical composition 0.65% С, 0.67% Mn, 0.3% Si, 0.027% P, 0.028% S. Structural researches were conducted with the use of light microscopy and methods of quantitative metallography. The structural state of the probed steel corresponded to the state after hot plastic deformation. The analysis of hardness distribution in the micro volumes of cathode metal was carried out with the use of microhardness tester of type of PMT-3. An electric spark treatment of carbon steel surface was executed with the use of equipment type of EFI-25M. Findings. After electric spark treatment of specimen surface from carbon steel the forming of multi-layered coverage was observed. The analysis of microstructure found out the existence of high-quality distinctions in the internal structure of coverage metal, depending on the probed area. The results obtained in the process are confirmed by the well-known theses, that forming of superficial coverage according to technology of electric spark is determined by the terms of transfer and crystallization of metal. The gradient of structures on the coverage thickness largely depends on development of structural transformation processes similar to the thermal character influence. Originality. As a result of electric spark treatment on the condition of identical metal of anode and cathode, the first formed layer of coverage corresponds to the monophase state according to external signs. In the volume of coverage metal, the appearance of carbide phase particles is accompanied by the decrease of microhardness values. Practical value. Forming of multi-layered superficial coverage during electric spark treatment is accompanied by the origin of structure gradient on a thickness. The effect

  13. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

    Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch

    2015-01-01

    This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

  14. Spark gap produced plasma diagnostics

    International Nuclear Information System (INIS)

    Chang, H.Y.

    1990-01-01

    A Spark Gap (Applied voltage : 2-8KV, Capacitor : 4 Micro F. Dia of the tube : 1 inch, Electrode distance : .3 ∼.5 inch) was made to generate a small size dynamic plasma. To measure the plasma density and temperature as a function of time and position, we installed and have been installing four detection systems - Mach-Zehnder type Interferometer for the plasma refractivity, Expansion speed detector using two He-Ne laser beams, Image Processing using Lens and A Optical-Fiber Array for Pointwise Radiation Sensing, Faraday Rotation of a Optical Fiber to measure the azimuthal component of B-field generated by the plasma drift. These systems was used for the wire explosion diagnostics, and can be used for the Laser driven plasma also

  15. Spark-safe power source

    Energy Technology Data Exchange (ETDEWEB)

    Mester, I M; Konushkin, N A; Nevozinskiy, A K; Rubinshteyn, B Sh; Serov, V I; Vasnev, M A

    1981-01-01

    A shortcoming of the known power sources is their low reliability. The purpose of the invention is to improve the reliability of the device. This is achieved because the spark-safe power source is equipped with a by-passing transistor and potentiometer, and also a generator of control interruptions in the circuit, an I-element, first separating transformer, control block, second separating transformer whose secondary winding has a relay winding whose contacts are connected to the load circuit are connected in series. The generator of control separations of the circuit is connected to the base of the by-passing transistor and to the power source outlet, the potentiometer is connected in series to the main thyristor. The middle point of the potentiometer is connected to the second inlet of the I-element.

  16. Damping Resonant Current in a Spark-Gap Trigger Circuit to Reduce Noise

    Science.gov (United States)

    2009-06-01

    DAMPING RESONANT CURRENT IN A SPARK- GAP TRIGGER CIRCUIT TO REDUCE NOISE E. L. Ruden Air Force Research Laboratory, Directed Energy Directorate, AFRL...REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Damping Resonant Current In A Spark- Gap Trigger Circuit To Reduce Noise 5a...thereby triggering 2 after delay 0, is 1. Each of the two rail- gaps (represented by 2) is trig- gered to close after the spark- gap (1) in the

  17. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID

    2009-11-17

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

  18. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Ling-Yu Duan

    2010-01-01

    Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  19. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Tian Yonghong

    2010-01-01

    Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  20. GeoSpark SQL: An Effective Framework Enabling Spatial Queries on Spark

    Directory of Open Access Journals (Sweden)

    Zhou Huang

    2017-09-01

    Full Text Available In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial database (e.g., PostgreSQL with PostGIS and Oracle Spatial cannot adapt well to the needs of large-scale spatial query processing. Spark is an emerging outstanding distributed computing framework in the Hadoop ecosystem. This paper aims to address the increasingly large-scale spatial query-processing requirement in the era of big data, and proposes an effective framework GeoSpark SQL, which enables spatial queries on Spark. On the one hand, GeoSpark SQL provides a convenient SQL interface; on the other hand, GeoSpark SQL achieves both efficient storage management and high-performance parallel computing through integrating Hive and Spark. In this study, the following key issues are discussed and addressed: (1 storage management methods under the GeoSpark SQL framework, (2 the spatial operator implementation approach in the Spark environment, and (3 spatial query optimization methods under Spark. Experimental evaluation is also performed and the results show that GeoSpark SQL is able to achieve real-time query processing. It should be noted that Spark is not a panacea. It is observed that the traditional spatial database PostGIS/PostgreSQL performs better than GeoSpark SQL in some query scenarios, especially for the spatial queries with high selectivity, such as the point query and the window query. In general, GeoSpark SQL performs better when dealing with compute-intensive spatial queries such as the kNN query and the spatial join query.

  1. Mixture Density Mercer Kernels: A Method to Learn Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...

  2. 7 CFR 981.9 - Kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

  3. 7 CFR 51.2295 - Half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

  4. Bubbles, sparks, and the postwar laboratory

    International Nuclear Information System (INIS)

    Galison, P.

    1989-01-01

    The development and use of bubble chambers and spark chambers in the 1950s form the main thrust of this article, the bubble chamber as an example of ''image-producing'' instruments and the spark chamber as a ''logic'' device. Work on a cloud chamber by Glaser led to the development of the bubble chamber detector using liquid hydrogen, which was later linked to a computer for accurate automatic track analysis. It made possible demonstrations of the existence of a particle or interaction. Spark chambers were easier to build and so soon became common, various types being developed across the world. The development of spark chambers originated in the need for timing devices for the Manhattan Project, but work on their design occurred in a number of units worldwide. (UK)

  5. SPARK: Adapting Keyword Query to Semantic Search

    Science.gov (United States)

    Zhou, Qi; Wang, Chong; Xiong, Miao; Wang, Haofen; Yu, Yong

    Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named 'SPARK' has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.

  6. Experimental study of a spark-gap

    International Nuclear Information System (INIS)

    Bruzzone, H.; Moreno, C.; Vieytes, R.

    1990-01-01

    Some experimental results concerning to the resistance of an atmospheric pressure spark-gap, operating in the self breakdown regime are presented. The influence of the energy discharging through the gap on this resistance is discussed. (Author)

  7. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  8. kernel oil by lipolytic organisms

    African Journals Online (AJOL)

    USER

    2010-08-02

    Aug 2, 2010 ... Rancidity of extracted cashew oil was observed with cashew kernel stored at 70, 80 and 90% .... method of American Oil Chemist Society AOCS (1978) using glacial ..... changes occur and volatile products are formed that are.

  9. Electro-spark deposition technology

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, R.N. [Pacific Northwest National Lab., Richland, WA (United States)

    1997-12-01

    Electro-Spark Deposition (ESD) is a micro-welding process that uses short duration, high-current electrical pulses to deposit or alloy a consumable electrode material onto a metallic substrate. The ESD process was developed to produce coatings for use in severe environments where most other coatings fail. Because of the exceptional damage resistance of these coatings, and the versatility of the process to apply a wide variety of alloys, intermetallics, and cermets to metal surfaces, the ESD process has been designated critical to the life and economy of the advanced fossil energy systems as the higher temperatures and corrosive environments exceed the limits of known structural materials to accommodate the service conditions. Developments include producing iron aluminide-based coatings with triple the corrosion resistance of the best previous Fe{sub 3}Al coatings, coatings with refractory metal diffusion barriers and multi layer coatings for achieving functionally gradient properties between the substrate and the surface. A new development is the demonstration of advanced aluminide-based ESD coatings for erosion and wear applications. One of the most significant breakthroughs to occur in the last dozen years is the discovery of a process regime that yields an order of magnitude increase in deposition rates and achievable coating thicknesses. Achieving this regime has required the development of advanced ESD electronic capabilities. Development is now focused on further improvements in deposition rates, system reliability when operating at process extremes, and economic competitiveness.

  10. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  11. Notes on the gamma kernel

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.

    The density function of the gamma distribution is used as shift kernel in Brownian semistationary processes modelling the timewise behaviour of the velocity in turbulent regimes. This report presents exact and asymptotic properties of the second order structure function under such a model......, and relates these to results of von Karmann and Horwath. But first it is shown that the gamma kernel is interpretable as a Green’s function....

  12. Efficiency improvement of a spark-ignition engine at full load conditions using exhaust gas recirculation and variable geometry turbocharger – Numerical study

    International Nuclear Information System (INIS)

    Sjerić, Momir; Taritaš, Ivan; Tomić, Rudolf; Blažić, Mislav; Kozarac, Darko; Lulić, Zoran

    2016-01-01

    Highlights: • A cylinder model was calibrated according to experimental results. • A full cycle simulation model of turbocharged spark-ignition engine was made. • Engine performance with high pressure exhaust gas recirculation was studied. • Cooled exhaust gas recirculation lowers exhaust temperature and knock occurrence. • Leaner mixtures enable fuel consumption improvement of up to 11.2%. - Abstract: The numerical analysis of performance of a four cylinder highly boosted spark-ignition engine at full load is described in this paper, with the research focused on introducing high pressure exhaust gas recirculation for control of engine limiting factors such as knock, turbine inlet temperature and cyclic variability. For this analysis the cycle-simulation model which includes modeling of the entire engine flow path, early flame kernel growth, mixture stratification, turbulent combustion, in-cylinder turbulence, knock and cyclic variability was applied. The cylinder sub-models such as ignition, turbulence and combustion were validated by using the experimental results of a naturally aspirated multi cylinder spark-ignition engine. The high load operation, which served as a benchmark value, was obtained by a standard procedure used in calibration of engines, i.e. operation with fuel enrichment and without exhaust gas recirculation. By introducing exhaust gas recirculation and by optimizing other engine operating parameters, the influence of exhaust gas recirculation on engine performance is obtained. The optimum operating parameters, such as spark advance, intake pressure, air to fuel ratio, were found to meet the imposed requirements in terms of fuel consumption, knock occurrence, exhaust gas temperature and variation of indicated mean effective pressure. By comparing the results of the base point with the results that used exhaust gas recirculation the improvement in fuel consumption of 8.7%, 11.2% and 1.5% at engine speeds of 2000 rpm, 3500 rpm and 5000

  13. Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

    OpenAIRE

    Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

    2017-01-01

    Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...

  14. Scattering profiles of sparks and combustibility of filter against hot sparks

    International Nuclear Information System (INIS)

    Asazuma, Shinichiro; Okada, Takashi; Kashiro, Kashio

    2004-01-01

    The glove-box dismantling facility in the Plutonium Fuel Production Facility is developed to dismantle after-service glove-boxes with remote-controlled devices such as an arm-type manipulator. An abrasive wheel cutter, which is used to size reduce the gloveboxes, generates sparks during operation. This dispersing spark was a problem from the fire prevention point of view. A suitable spark control measures for this operation were required. We developed panels to minimize spark dispersion, shields to prevent the income of sparks to the pre-filter, and incombustible pre-filters. The equipment was tested and effectiveness was confirmed. This report provides the results of these tests. (author)

  15. Kernel versions of some orthogonal transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...

  16. An Approximate Approach to Automatic Kernel Selection.

    Science.gov (United States)

    Ding, Lizhong; Liao, Shizhong

    2016-02-02

    Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

  17. Model Selection in Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels......, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. We interpret the latter two kernels in terms of their smoothing properties, and we relate the tuning parameters associated to all these kernels to smoothness measures of the prediction function and to the signal-to-noise ratio. Based...... on these interpretations, we provide guidelines for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study confirms the practical usefulness of these rules of thumb. Finally, the flexible and smooth functional forms provided by the Gaussian and Sinc kernels makes them widely...

  18. Study of ignition in a high compression ratio SI (spark ignition) methanol engine using LES (large eddy simulation) with detailed chemical kinetics

    International Nuclear Information System (INIS)

    Zhen, Xudong; Wang, Yang

    2013-01-01

    Methanol has been recently used as an alternative to conventional fuels for internal combustion engines in order to satisfy some environmental and economical concerns. In this paper, the ignition in a high compression ratio SI (spark ignition) methanol engine was studied by using LES (large eddy simulation) with detailed chemical kinetics. A 21-species, 84-reaction methanol mechanism was adopted to simulate the auto-ignition process of the methanol/air mixture. The MIT (minimum ignition temperature) and MIE (minimum ignition energy) are two important properties for designing safety standards and understanding the ignition process of combustible mixtures. The effects of the flame kernel size, flame kernel temperature and equivalence ratio were also examined on MIT, MIE and IDP (ignition delay period). The methanol mechanism was validated by experimental test. The simulated results showed that the flame kernel size, temperature and energy dramatically affected the values of the MIT, MIE and IDP for a methanol/air mixture, the value of the ignition delay period was not only related to the flame kernel energy, but also to the flame kernel temperature. - Highlights: • We used LES (large eddy simulation) coupled with detailed chemical kinetics to simulate methanol ignition. • The flame kernel size and temperature affected the minimum ignition temperature. • The flame kernel temperature and energy affected the ignition delay period. • The equivalence ratio of methanol–air mixture affected the ignition delay period

  19. Integral equations with contrasting kernels

    Directory of Open Access Journals (Sweden)

    Theodore Burton

    2008-01-01

    Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.

  20. Laser spark distribution and ignition system

    Science.gov (United States)

    Woodruff, Steven [Morgantown, WV; McIntyre, Dustin L [Morgantown, WV

    2008-09-02

    A laser spark distribution and ignition system that reduces the high power optical requirements for use in a laser ignition and distribution system allowing for the use of optical fibers for delivering the low peak energy pumping pulses to a laser amplifier or laser oscillator. An optical distributor distributes and delivers optical pumping energy from an optical pumping source to multiple combustion chambers incorporating laser oscillators or laser amplifiers for inducing a laser spark within a combustion chamber. The optical distributor preferably includes a single rotating mirror or lens which deflects the optical pumping energy from the axis of rotation and into a plurality of distinct optical fibers each connected to a respective laser media or amplifier coupled to an associated combustion chamber. The laser spark generators preferably produce a high peak power laser spark, from a single low power pulse. The laser spark distribution and ignition system has application in natural gas fueled reciprocating engines, turbine combustors, explosives and laser induced breakdown spectroscopy diagnostic sensors.

  1. Model selection for Gaussian kernel PCA denoising

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Hansen, Lars Kai

    2012-01-01

    We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

  2. RTOS kernel in portable electrocardiograph

    Science.gov (United States)

    Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.

    2011-12-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  3. RTOS kernel in portable electrocardiograph

    International Nuclear Information System (INIS)

    Centeno, C A; Voos, J A; Riva, G G; Zerbini, C; Gonzalez, E A

    2011-01-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  4. Spark - a modern approach for distributed analytics

    CERN Multimedia

    CERN. Geneva; Kothuri, Prasanth

    2016-01-01

    The Hadoop ecosystem is the leading opensource platform for distributed storing and processing big data. It is a very popular system for implementing data warehouses and data lakes. Spark has also emerged to be one of the leading engines for data analytics. The Hadoop platform is available at CERN as a central service provided by the IT department. By attending the session, a participant will acquire knowledge of the essential concepts need to benefit from the parallel data processing offered by Spark framework. The session is structured around practical examples and tutorials. Main topics: Architecture overview - work distribution, concepts of a worker and a driver Computing concepts of transformations and actions Data processing APIs - RDD, DataFrame, and SparkSQL

  5. Using SPARK as a Solver for Modelica

    Energy Technology Data Exchange (ETDEWEB)

    Wetter, Michael; Wetter, Michael; Haves, Philip; Moshier, Michael A.; Sowell, Edward F.

    2008-06-30

    Modelica is an object-oriented acausal modeling language that is well positioned to become a de-facto standard for expressing models of complex physical systems. To simulate a model expressed in Modelica, it needs to be translated into executable code. For generating run-time efficient code, such a translation needs to employ algebraic formula manipulations. As the SPARK solver has been shown to be competitive for generating such code but currently cannot be used with the Modelica language, we report in this paper how SPARK's symbolic and numerical algorithms can be implemented in OpenModelica, an open-source implementation of a Modelica modeling and simulation environment. We also report benchmark results that show that for our air flow network simulation benchmark, the SPARK solver is competitive with Dymola, which is believed to provide the best solver for Modelica.

  6. High performance Spark best practices for scaling and optimizing Apache Spark

    CERN Document Server

    Karau, Holden

    2017-01-01

    Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources. Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing. With this book, you’ll explore: How Spark SQL’s new interfaces improve performance over SQL’s RDD data structure The choice between data joins in Core Spark and Spark SQL Techniques for getting the most out of standard RDD transformations How to work around performance issues i...

  7. Semi-Supervised Kernel PCA

    DEFF Research Database (Denmark)

    Walder, Christian; Henao, Ricardo; Mørup, Morten

    We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least...... squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets....

  8. Chaotic combustion in spark ignition engines

    International Nuclear Information System (INIS)

    Wendeker, Miroslaw; Czarnigowski, Jacek; Litak, Grzegorz; Szabelski, Kazimierz

    2003-01-01

    We analyse the combustion process in a spark ignition engine using the experimental data of an internal pressure during the combustion process and show that the system can be driven to chaotic behaviour. Our conclusion is based on the observation of unperiodicity in the time series, suitable stroboscopic maps and a complex structure of a reconstructed strange attractor. This analysis can explain that in some circumstances the level of noise in spark ignition engines increases considerably due to nonlinear dynamics of a combustion process

  9. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

    Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...

  10. The suppression of destructive sparks in parallel plate proportional counters

    Energy Technology Data Exchange (ETDEWEB)

    Cockshott, R.A.; Mason, I.M.

    1984-02-01

    The authors find that high energy background events produce localised sparks in parallel plate counters when operated in the proportional mode. These sparks increase dead-time and lead to degradation ranging from electrode damage to spurious pulsing and continuous breakdown. The problem is particularly serious in low energy photon detectors for X-ray astronomy which are required to have lifetimes of several years in the high radiation environment of space. For the parallel plate imaging detector developed for the European X-ray Observatory Satellite (EXOSAT) they investigate quantitatively the spark thresholds, spark rates and degradation processes. They discuss the spark mechanism, pointing out differences from the situation in spark chambers and counters. They show that the time profile of the sparks allows them to devise a spark suppression system which reduces the degradation rate by a factor of ''200.

  11. Multiple Kernel Learning with Data Augmentation

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au...University, Australia Editors: Robert J. Durrant and Kee-Eung Kim Abstract The motivations of multiple kernel learning (MKL) approach are to increase... kernel expres- siveness capacity and to avoid the expensive grid search over a wide spectrum of kernels . A large amount of work has been proposed to

  12. A kernel version of multivariate alteration detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2013-01-01

    Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....

  13. A novel adaptive kernel method with kernel centers determined by a support vector regression approach

    NARCIS (Netherlands)

    Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

    2012-01-01

    The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an

  14. Spark discharge and flame inception analysis through spectroscopy in a DISI engine fuelled with gasoline and butanol

    Science.gov (United States)

    Irimescu, A.; Merola, S. S.

    2017-10-01

    Extensive application of downsizing, as well as the application of alternative combustion control with respect to well established stoichiometric operation, have determined a continuous increase in the energy that is delivered to the working fluid in order to achieve stable and repeatable ignition. Apart from the complexity of fluid-arc interactions, the extreme thermodynamic conditions of this initial combustion stage make its characterization difficult, both through experimental and numerical techniques. Within this context, the present investigation looks at the analysis of spark discharge and flame kernel formation, through the application of UV-visible spectroscopy. Characterization of the energy transfer from the spark plug’s electrodes to the air-fuel mixture was achieved by the evaluation of vibrational and rotational temperatures during ignition, for stoichiometric and lean fuelling of a direct injection spark ignition engine. Optical accessibility was ensured from below the combustion chamber through an elongated piston design, that allowed the central region of the cylinder to be investigated. Fuel effects were evaluated for gasoline and n-butanol; roughly the same load was investigated in throttled and wide-open throttle conditions for both fuels. A brief thermodynamic analysis confirmed that significant gains in efficiency can be obtained with lean fuelling, mainly due to the reduction of pumping losses. Minimal effect of fuel type was observed, while mixture strength was found to have a stronger influence on calculated temperature values, especially during the initial stage of ignition. In-cylinder pressure was found to directly determine emission intensity during ignition, but the vibrational and rotational temperatures featured reduced dependence on this parameter. As expected, at the end of kernel formation, temperature values converged towards those typically found for adiabatic flames. The results show that indeed only a relatively small part

  15. Complex use of cottonseed kernels

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova, A I

    1977-01-01

    A review with 41 references is made on the manufacture of oil, protein, and other products from cottonseed, the effects of gossypol on protein yield and quality and technology of gossypol removal. A process eliminating thermal treatment of the kernels and permitting the production of oil, proteins, phytin, gossypol, sugar, sterols, phosphatides, tocopherols, and residual shells and baggase is described.

  16. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  17. GRIM : Leveraging GPUs for Kernel integrity monitoring

    NARCIS (Netherlands)

    Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris

    2016-01-01

    Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious

  18. Paramecium: An Extensible Object-Based Kernel

    NARCIS (Netherlands)

    van Doorn, L.; Homburg, P.; Tanenbaum, A.S.

    1995-01-01

    In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection

  19. Local Observed-Score Kernel Equating

    Science.gov (United States)

    Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

    2014-01-01

    Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

  20. Veto-Consensus Multiple Kernel Learning

    NARCIS (Netherlands)

    Zhou, Y.; Hu, N.; Spanos, C.J.

    2016-01-01

    We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The

  1. Generation of Nanoparticles by Spark Discharge

    NARCIS (Netherlands)

    Salman Tabrizi, N.

    2009-01-01

    Spark discharge is a method for producing nanoparticles from conductive materials. Besides the general advantages of nanoparticle synthesis in the gas phase, the method offers additional advantages like simplicity, compactness and versatility. The synthesis process is continuous and is performed at

  2. Ambient fields generated by a laser spark

    Czech Academy of Sciences Publication Activity Database

    Rohlena, Karel; Mašek, Martin

    2016-01-01

    Roč. 61, č. 2 (2016), s. 119-124 ISSN 0029-5922 R&D Projects: GA MŠk(CZ) LD14089; GA MŠk(CZ) LG13031 Institutional support: RVO:68378271 Keywords : laser spark * radiation chemistry * field generation Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 0.760, year: 2016

  3. Electro-spark machining of cadmium antimonide

    International Nuclear Information System (INIS)

    Ivanovskij, V.N.; Stepakhina, K.A.

    1975-01-01

    Experimental data on electrical erosion of the semiconductor material (cadmium antimonide) alloyed with tellurium are given. The potentialisies and expediency of using the electric-spark method of cutting cadmium antimonide ingots with the resistivity of 1 ohm is discussed. Cutting has been carried out in distilled water and in the air

  4. Funding fears spark Italian protests

    CERN Multimedia

    Abbott, A

    2001-01-01

    150 Italian scientists took part in a symbolic funeral in Milan for Italian research. Scientists are worried that the new government will reduce support for basic research. Rumours that budgets will be cut are being confirmed and last week the government rejected the 3-year plan of the National Research Council, which had proposed an expansion of staff (1/2 page).

  5. Efficiency calibration of solid track spark auto counter

    International Nuclear Information System (INIS)

    Wang Mei; Wen Zhongwei; Lin Jufang; Liu Rong; Jiang Li; Lu Xinxin; Zhu Tonghua

    2008-01-01

    The factors influencing detection efficiency of solid track spark auto counter were analyzed, and the best etch condition and parameters of charge were also reconfirmed. With small plate fission ionization chamber, the efficiency of solid track spark auto counter at various experiment assemblies was re-calibrated. The efficiency of solid track spark auto counter at various experimental conditions was obtained. (authors)

  6. Genetic, Genomic, and Breeding Approaches to Further Explore Kernel Composition Traits and Grain Yield in Maize

    Science.gov (United States)

    Da Silva, Helena Sofia Pereira

    2009-01-01

    Maize ("Zea mays L.") is a model species well suited for the dissection of complex traits which are often of commercial value. The purpose of this research was to gain a deeper understanding of the genetic control of maize kernel composition traits starch, protein, and oil concentration, and also kernel weight and grain yield. Germplasm with…

  7. An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

    Directory of Open Access Journals (Sweden)

    Senyue Zhang

    2016-01-01

    Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.

  8. DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters

    OpenAIRE

    Kim, Hanjoo; Park, Jaehong; Jang, Jaehee; Yoon, Sungroh

    2016-01-01

    The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operation...

  9. Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

    Science.gov (United States)

    Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

    2018-05-01

    With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Wigner functions defined with Laplace transform kernels.

    Science.gov (United States)

    Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

    2011-10-24

    We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

  11. Development And Testing Of Biogas-Petrol Blend As An Alternative Fuel For Spark Ignition Engine

    Directory of Open Access Journals (Sweden)

    Awogbemi

    2015-08-01

    Full Text Available Abstract This research is on the development and testing of a biogas-petrol blend to run a spark ignition engine. A2080 ratio biogaspetrol blend was developed as an alternative fuel for spark ignition engine test bed. Petrol and biogas-petrol blend were comparatively tested on the test bed to determine the effectiveness of the fuels. The results of the tests showed that biogas petrol blend generated higher torque brake power indicated power brake thermal efficiency and brake mean effective pressure but lower fuel consumption and exhaust temperature than petrol. The research concluded that a spark ignition engine powered by biogas-petrol blend was found to be economical consumed less fuel and contributes to sanitation and production of fertilizer.

  12. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

    Widiharih, T.; Mukid, M. A.; Mustafid

    2018-05-01

    Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

  13. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  14. Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

    Science.gov (United States)

    Wei, Wei; Jia, Qingxuan

    2016-01-01

    Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

  15. Experimental investigations of argon spark gap recovery times by developing a high voltage double pulse generator.

    Science.gov (United States)

    Reddy, C S; Patel, A S; Naresh, P; Sharma, Archana; Mittal, K C

    2014-06-01

    The voltage recovery in a spark gap for repetitive switching has been a long research interest. A two-pulse technique is used to determine the voltage recovery times of gas spark gap switch with argon gas. First pulse is applied to the spark gap to over-volt the gap and initiate the breakdown and second pulse is used to determine the recovery voltage of the gap. A pulse transformer based double pulse generator capable of generating 40 kV peak pulses with rise time of 300 ns and 1.5 μs FWHM and with a delay of 10 μs-1 s was developed. A matrix transformer topology is used to get fast rise times by reducing L(l)C(d) product in the circuit. Recovery Experiments have been conducted for 2 mm, 3 mm, and 4 mm gap length with 0-2 bars pressure for argon gas. Electrodes of a sparkgap chamber are of rogowsky profile type, made up of stainless steel material, and thickness of 15 mm are used in the recovery study. The variation in the distance and pressure effects the recovery rate of the spark gap. An intermediate plateu is observed in the spark gap recovery curves. Recovery time decreases with increase in pressure and shorter gaps in length are recovering faster than longer gaps.

  16. On Convergence of Kernel Density Estimates in Particle Filtering

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2016-01-01

    Roč. 52, č. 5 (2016), s. 735-756 ISSN 0023-5954 Grant - others:GA ČR(CZ) GA16-03708S; SVV(CZ) 260334/2016 Institutional support: RVO:67985807 Keywords : Fourier analysis * kernel methods * particle filter Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.379, year: 2016

  17. Fractional quantum integral operator with general kernels and applications

    Science.gov (United States)

    Babakhani, Azizollah; Neamaty, Abdolali; Yadollahzadeh, Milad; Agahi, Hamzeh

    In this paper, we first introduce the concept of fractional quantum integral with general kernels, which generalizes several types of fractional integrals known from the literature. Then we give more general versions of some integral inequalities for this operator, thus generalizing some previous results obtained by many researchers.2,8,25,29,30,36

  18. Validation of Born Traveltime Kernels

    Science.gov (United States)

    Baig, A. M.; Dahlen, F. A.; Hung, S.

    2001-12-01

    Most inversions for Earth structure using seismic traveltimes rely on linear ray theory to translate observed traveltime anomalies into seismic velocity anomalies distributed throughout the mantle. However, ray theory is not an appropriate tool to use when velocity anomalies have scale lengths less than the width of the Fresnel zone. In the presence of these structures, we need to turn to a scattering theory in order to adequately describe all of the features observed in the waveform. By coupling the Born approximation to ray theory, the first order dependence of heterogeneity on the cross-correlated traveltimes (described by the Fréchet derivative or, more colourfully, the banana-doughnut kernel) may be determined. To determine for what range of parameters these banana-doughnut kernels outperform linear ray theory, we generate several random media specified by their statistical properties, namely the RMS slowness perturbation and the scale length of the heterogeneity. Acoustic waves are numerically generated from a point source using a 3-D pseudo-spectral wave propagation code. These waves are then recorded at a variety of propagation distances from the source introducing a third parameter to the problem: the number of wavelengths traversed by the wave. When all of the heterogeneity has scale lengths larger than the width of the Fresnel zone, ray theory does as good a job at predicting the cross-correlated traveltime as the banana-doughnut kernels do. Below this limit, wavefront healing becomes a significant effect and ray theory ceases to be effective even though the kernels remain relatively accurate provided the heterogeneity is weak. The study of wave propagation in random media is of a more general interest and we will also show our measurements of the velocity shift and the variance of traveltime compare to various theoretical predictions in a given regime.

  19. RKRD: Runtime Kernel Rootkit Detection

    Science.gov (United States)

    Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.

    In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.

  20. Kernel Bayesian ART and ARTMAP.

    Science.gov (United States)

    Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan

    2018-02-01

    Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

    Science.gov (United States)

    2013-01-01

    Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

  2. OH PLIF measurement in a spark ignition engine with a tumble flow

    Science.gov (United States)

    Kumar, Siddhartha; Moronuki, Tatsuya; Shimura, Masayasu; Minamoto, Yuki; Yokomori, Takeshi; Tanahashi, Mamoru; Strategic Innovation Program (SIP) Team

    2017-11-01

    Under lean conditions, high compression ratio and strong tumble flow; cycle-to-cycle variations of combustion in spark ignition (SI) engines is prominent, therefore, relation between flame propagation characteristics and increase of pressure needs to be clarified. The present study is aimed at exploring the spatial and temporal development of the flame kernel using OH planar laser-induced fluorescence (OH PLIF) in an optical SI engine. Equivalence ratio is changed at a fixed indicated mean effective pressure of 400 kPa. From the measurements taken at different crank angle degrees (CAD) after ignition, characteristics of flame behavior were investigated considering temporal evolution of in-cylinder pressure, and factors causing cycle-to-cycle variations are discussed. In addition, the effects of tumble flow intensity on flame propagation behavior were also investigated. This work is supported by the Cross-ministerial Strategic Innovation Program (SIP), `Innovative Combustion Technology'.

  3. Structure and characteristics of functional powder composite materials obtained by spark plasma sintering

    Science.gov (United States)

    Oglezneva, S. A.; Kachenyuk, M. N.; Kulmeteva, V. B.; Ogleznev, N. B.

    2017-07-01

    The article describes the results of spark plasma sintering of ceramic materials based on titanium carbide, titanium carbosilicide, ceramic composite materials based on zirconium oxide, strengthened by carbon nanostructures and composite materials of electrotechnical purpose based on copper with addition of carbon structures and titanium carbosilicide. The research shows that the spark plasma sintering can achieve relative density of the material up to 98%. The effect of sintering temperature on the phase composition, density and porosity of the final product has been studied. It was found that with addition of carbon nanostructures the relative density and hardness decrease, but the fracture strength of ZrO2 increases up to times 2. The relative erosion resistance of the electrodes made of composite copper-based powder materials, obtained by spark plasma sintering during electroerosion treatment of tool steel exceeds that parameter of pure copper up to times 15.

  4. Welding of titanium and nickel alloy by combination of explosive welding and spark plasma sintering technologies

    Energy Technology Data Exchange (ETDEWEB)

    Malyutina, Yu. N., E-mail: iuliiamaliutina@gmail.com; Bataev, A. A., E-mail: bataev@adm.nstu.ru; Shevtsova, L. I., E-mail: edeliya2010@mail.ru [Novosibirsk State Technical University, Novosibirsk, 630073 (Russian Federation); Mali, V. I., E-mail: vmali@mail.ru; Anisimov, A. G., E-mail: anis@hydro.nsc.ru [Lavrentyev Institute of Hydrodynamics SB RAS, Novosibirsk, 630090 (Russian Federation)

    2015-10-27

    A possibility of titanium and nickel-based alloys composite materials formation using combination of explosive welding and spark plasma sintering technologies was demonstrated in the current research. An employment of interlayer consisting of copper and tantalum thin plates makes possible to eliminate a contact between metallurgical incompatible titanium and nickel that are susceptible to intermetallic compounds formation during their interaction. By the following spark plasma sintering process the bonding has been received between titanium and titanium alloy VT20 through the thin powder layer of pure titanium that is distinguished by low defectiveness and fine dispersive structure.

  5. Trace amount analysis using spark mass spectrometry

    International Nuclear Information System (INIS)

    Stefani, Rene

    1975-01-01

    Characteristics of spark mass spectrometers (ion source, properties of the ion beam, ion optics, and performance) and their use in qualitative and quantitative analysis are described. This technique is very interesting for the semi-quantitative analysis of trace amounts, down to 10 -8 atoms. Examples of applications such as the analysis of high purity materials and non-conducting mineral samples, and determination of carbon and gas trace amounts are presented. (50 references) [fr

  6. Neutron bursts from long laboratory sparks

    Science.gov (United States)

    Kochkin, P.; Lehtinen, N. G.; Montanya, J.; Van Deursen, A.; Ostgaard, N.

    2016-12-01

    Neutron emission in association with thunderstorms and lightning discharges was reported by different investigators from ground-based observation platforms. In both cases such emission is explained by photonuclear reaction, since high-energy gamma-rays in sufficient fluxes are routinely detected from both, lightning and thunderclouds. The required gamma-rays are presumably generated by high-energy electrons in Bremsstrahlung process after their acceleration via cold and/or relativistic runaway mechanisms. This phenomenon attracted moderate scientific attention until fast neutron bursts (up to 10 MeV) from long 1 MV laboratory sparks have been reported. Clearly, with such relatively low applied voltage the electrons are unable to accelerate to the energies required for photo/electro disintegration. Moreover, all known elementary neutron generation processes are not capable to explain this emission right away. We performed an independent laboratory experiment on long sparks with the aim to confirm or disprove the neutron emission from them. The experimental setup was assembled at High-Voltage Laboratory in Barcelona and contained a Marx generator in a cone-cone spark gap configuration. The applied voltage was as low as 800 kV and the gap distance was only 60 cm. Two ns-fast cameras were located near the gap capturing short-exposure images of the pre-breakdown phenomenon at the expected neutron generation time. A plastic scintillation detector sensitive to neutrons was covered in 11 cm of lead and placed near the spark gap. The detector was calibrated and showed good performance in neutron detection. Apart of it, voltage, currents through both electrodes, and three X-ray detectors were also monitored in sophisticated measuring system. We will give an overview of the previous experimental and theoretical work in this topic, and present the results of our new experimental campaign. The conclusions are based on good signal-to-noise ratio measurements and are

  7. SPARK Version 1.1 user manual

    International Nuclear Information System (INIS)

    Weissenburger, D.W.

    1988-01-01

    This manual describes the input required to use Version 1.1 of the SPARK computer code. SPARK 1.1 is a library of FORTRAN main programs and subprograms designed to calculate eddy currents on conducting surfaces where current flow is assumed zero in the direction normal to the surface. Surfaces are modeled with triangular and/or quadrilateral elements. Lorentz forces produced by the interaction of eddy currents with background magnetic fields can be output at element nodes in a form compatible with most structural analysis codes. In addition, magnetic fields due to eddy currents can be determined at points off the surface. Version 1.1 features eddy current streamline plotting with optional hidden-surface-removal graphics and topological enhancements that allow essentially any orientable surface to be modeled. SPARK also has extensive symmetry specification options. In order to make the manual as self-contained as possible, six appendices are included that present summaries of the symmetry options, topological options, coil options and code algorithms, with input and output examples. An edition of SPARK 1.1 is available on the Cray computers at the National Magnetic Fusion Energy Computer Center at Livermore, California. Another more generic edition is operational on the VAX computers at the Princeton Plasma Physics Laboratory and is available on magnetic tape by request. The generic edition requires either the GKS or PLOT10 graphics package and the IMSL or NAG mathematical package. Requests from outside the United States will be subject to applicable federal regulations regarding dissemination of computer programs. 22 refs

  8. SPARK Version 1. 1 user manual

    Energy Technology Data Exchange (ETDEWEB)

    Weissenburger, D.W.

    1988-01-01

    This manual describes the input required to use Version 1.1 of the SPARK computer code. SPARK 1.1 is a library of FORTRAN main programs and subprograms designed to calculate eddy currents on conducting surfaces where current flow is assumed zero in the direction normal to the surface. Surfaces are modeled with triangular and/or quadrilateral elements. Lorentz forces produced by the interaction of eddy currents with background magnetic fields can be output at element nodes in a form compatible with most structural analysis codes. In addition, magnetic fields due to eddy currents can be determined at points off the surface. Version 1.1 features eddy current streamline plotting with optional hidden-surface-removal graphics and topological enhancements that allow essentially any orientable surface to be modeled. SPARK also has extensive symmetry specification options. In order to make the manual as self-contained as possible, six appendices are included that present summaries of the symmetry options, topological options, coil options and code algorithms, with input and output examples. An edition of SPARK 1.1 is available on the Cray computers at the National Magnetic Fusion Energy Computer Center at Livermore, California. Another more generic edition is operational on the VAX computers at the Princeton Plasma Physics Laboratory and is available on magnetic tape by request. The generic edition requires either the GKS or PLOT10 graphics package and the IMSL or NAG mathematical package. Requests from outside the United States will be subject to applicable federal regulations regarding dissemination of computer programs. 22 refs.

  9. Spark plasma sintering of tantalum carbide

    International Nuclear Information System (INIS)

    Khaleghi, Evan; Lin, Yen-Shan; Meyers, Marc A.; Olevsky, Eugene A.

    2010-01-01

    A tantalum carbide powder was consolidated by spark plasma sintering. The specimens were processed under various temperature and pressure conditions and characterized in terms of relative density, grain size, rupture strength and hardness. The results are compared to hot pressing conducted under similar settings. It is shown that high densification is accompanied by substantial grain growth. Carbon nanotubes were added to mitigate grain growth; however, while increasing specimens' rupture strength and final density, they had little effect on grain growth.

  10. A survey of kernel-type estimators for copula and their applications

    Science.gov (United States)

    Sumarjaya, I. W.

    2017-10-01

    Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

  11. Theory of reproducing kernels and applications

    CERN Document Server

    Saitoh, Saburou

    2016-01-01

    This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...

  12. Turbulent spark-jet ignition in SI gas fuelled engine

    Directory of Open Access Journals (Sweden)

    Pielecha Ireneusz

    2017-01-01

    Full Text Available The article contains a thermodynamic analysis of a new combustion system that allows the combustion of stratified gas mixtures with mean air excess coefficient in the range 1.4-1.8. Spark ignition was used in the pre-chamber that has been mounted in the engine cylinder head and contained a rich mixture out of which a turbulent flow of ignited mixture is ejected. It allows spark-jet ignition and the turbulent combustion of the lean mixture in the main combustion chamber. This resulted in a two-stage combustion system for lean mixtures. The experimental study has been conducted using a single-cylinder test engine with a geometric compression ratio ε = 15.5 adapted for natural gas supply. The tests were performed at engine speed n = 2000 rpm under stationary engine load when the engine operating parameters and toxic compounds emissions have been recorded. Analysis of the results allowed to conclude that the evaluated combustion system offers large flexibility in the initiation of charge ignition through an appropriate control of the fuel quantities supplied into the pre-chamber and into the main combustion chamber. The research concluded with determining the charge ignition criterion for a suitably divided total fuel dose fed to the cylinder.

  13. Near wall combustion modeling in spark ignition engines. Part A: Flame–wall interaction

    International Nuclear Information System (INIS)

    Demesoukas, Sokratis; Caillol, Christian; Higelin, Pascal; Boiarciuc, Andrei; Floch, Alain

    2015-01-01

    Highlights: • A model for flame–wall interaction in addition to flame wrinkling by turbulence is proposed. • Two sparkplug positions and two lengths are used in a test engine for model validation. • Flame–wall interaction decreases the maximum values of cylinder pressure and heat release rates. • The impact of combustion chamber geometry is taken into account by the flame–wall interaction model. - Abstract: Research and design in the field of spark ignition engines seek to achieve high performance while conserving fuel economy and low pollutant emissions. For the evaluation of various engine configurations, numerical simulations are favored, since they are quick and less expensive than experiments. Various zero-dimensional combustion models are currently used. Both flame front reactions and post-flame processes contribute to the heat release rate. The first part of this study focuses on the role of the flame front on the heat release rate, by modeling the interaction of the flame front with the chamber wall. Post-flame reactions are dealt with in Part B of the study. The basic configurations of flame quenching in laminar flames are also applicable in turbulent flames, which is the case in spark ignition engines. A simplified geometric model of the combustion chamber was used to calculate the mean flame surface, the flame volume and the distribution of flame surface as a function of the distance from the wall. The flame–wall interaction took into account the geometry of the combustion chamber and of the flame, aerodynamic turbulence and the in-cylinder pressure and temperature conditions, through a phenomenological attenuation function of the wrinkling factor. A modified global wrinkling factor as a function of the mean surface distance distribution from the wall was calculated. The impact of flame–wall interaction was simulated for four configurations of the sparkplug position and length: centered and lateral position, and standard and projected

  14. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří

    2016-02-12

    We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

  15. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří ; Barton, Michael

    2016-01-01

    We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

  16. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

    region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....

  17. Partial Deconvolution with Inaccurate Blur Kernel.

    Science.gov (United States)

    Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

    2017-10-17

    Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

  18. SciDB versus Spark: A Preliminary Comparison Based on an Earth Science Use Case

    Science.gov (United States)

    Clune, T.; Kuo, K. S.; Doan, K.; Oloso, A.

    2015-12-01

    We compare two Big Data technologies, SciDB and Spark, for performance, usability, and extensibility, when applied to a representative Earth science use case. SciDB is a new-generation parallel distributed database management system (DBMS) based on the array data model that is capable of handling multidimensional arrays efficiently but requires lengthy data ingest prior to analysis, whereas Spark is a fast and general engine for large scale data processing that can immediately process raw data files and thereby avoid the ingest process. Once data have been ingested, SciDB is very efficient in database operations such as subsetting. Spark, on the other hand, provides greater flexibility by supporting a wide variety of high-level tools including DBMS's. For the performance aspect of this preliminary comparison, we configure Spark to operate directly on text or binary data files and thereby limit the need for additional tools. Arguably, a more appropriate comparison would involve exploring other configurations of Spark which exploit supported high-level tools, but that is beyond our current resources. To make the comparison as "fair" as possible, we export the arrays produced by SciDB into text files (or converting them to binary files) for the intake by Spark and thereby avoid any additional file processing penalties. The Earth science use case selected for this comparison is the identification and tracking of snowstorms in the NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) reanalysis data. The identification portion of the use case is to flag all grid cells of the MERRA high-resolution hourly data that satisfies our criteria for snowstorm, whereas the tracking portion connects flagged cells adjacent in time and space to form a snowstorm episode. We will report the results of our comparisons at this presentation.

  19. ClimateSpark: An In-memory Distributed Computing Framework for Big Climate Data Analytics

    Science.gov (United States)

    Hu, F.; Yang, C. P.; Duffy, D.; Schnase, J. L.; Li, Z.

    2016-12-01

    Massive array-based climate data is being generated from global surveillance systems and model simulations. They are widely used to analyze the environment problems, such as climate changes, natural hazards, and public health. However, knowing the underlying information from these big climate datasets is challenging due to both data- and computing- intensive issues in data processing and analyzing. To tackle the challenges, this paper proposes ClimateSpark, an in-memory distributed computing framework to support big climate data processing. In ClimateSpark, the spatiotemporal index is developed to enable Apache Spark to treat the array-based climate data (e.g. netCDF4, HDF4) as native formats, which are stored in Hadoop Distributed File System (HDFS) without any preprocessing. Based on the index, the spatiotemporal query services are provided to retrieve dataset according to a defined geospatial and temporal bounding box. The data subsets will be read out, and a data partition strategy will be applied to equally split the queried data to each computing node, and store them in memory as climateRDDs for processing. By leveraging Spark SQL and User Defined Function (UDFs), the climate data analysis operations can be conducted by the intuitive SQL language. ClimateSpark is evaluated by two use cases using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. One use case is to conduct the spatiotemporal query and visualize the subset results in animation; the other one is to compare different climate model outputs using Taylor-diagram service. Experimental results show that ClimateSpark can significantly accelerate data query and processing, and enable the complex analysis services served in the SQL-style fashion.

  20. Spark innovation through empathic design.

    Science.gov (United States)

    Leonard, D; Rayport, J F

    1997-01-01

    Companies are used to bringing in customers to participate in focus groups, usability laboratories, and market research surveys in order to help in the development of new products and services. And for improving products that customers know well, those tools are highly sophisticated. For example, knowledgeable customers are adept at identifying the specific scent of leather they expect in a luxury vehicle or at helping to tune the sound of a motorcycle engine to just the timbre that evokes feelings of power. But to go beyond improvements to the familiar, companies need to identify and meet needs that customers may not yet recognize. To accomplish that task, a set of techniques called empathic design can help. Rather than bring the customers to the company, empathic design calls for company representatives to watch customers using products and services in the context of their own environments. By doing so, managers can often identify unexpected uses for their products, just as the product manager of a cooking oil did when he observed a neighbor spraying the oil on the blades of a lawn mower to reduce grass buildup. They can also uncover problems that customers don't mention in surveys, as the president of Nissan Design did when he watched a couple struggling to remove the backseat of a competitor's minivan in order to transport a couch. The five-step process Dorothy Leonard and Jeffrey Rayport describe in detail is a relatively low-cost, low-risk way to identify customer needs, and it has the potential to redirect a company's existing technological capabilities toward entirely new businesses.

  1. Process for producing metal oxide kernels and kernels so obtained

    International Nuclear Information System (INIS)

    Lelievre, Bernard; Feugier, Andre.

    1974-01-01

    The process desbribed is for producing fissile or fertile metal oxide kernels used in the fabrication of fuels for high temperature nuclear reactors. This process consists in adding to an aqueous solution of at least one metallic salt, particularly actinide nitrates, at least one chemical compound capable of releasing ammonia, in dispersing drop by drop the solution thus obtained into a hot organic phase to gel the drops and transform them into solid particles. These particles are then washed, dried and treated to turn them into oxide kernels. The organic phase used for the gel reaction is formed of a mixture composed of two organic liquids, one acting as solvent and the other being a product capable of extracting the anions from the metallic salt of the drop at the time of gelling. Preferably an amine is used as product capable of extracting the anions. Additionally, an alcohol that causes a part dehydration of the drops can be employed as solvent, thus helping to increase the resistance of the particles [fr

  2. US Department of Energy - Office of FreedomCar and Vehicle Technologies and US Centers for Disease Control and Prevention - National Institute for Occupational Safety and Health Inter-Agency Agreement Research on "The Analysis of Genotoxic Activities of Exhaust Emissions from Mobile Natural Gas, Diesel, and Spark-Ignition Engines"

    Energy Technology Data Exchange (ETDEWEB)

    William E. Wallace

    2006-09-30

    The US Department of Energy-Office of Heavy Vehicle Technologies (now the DOE-Office of FreedomCar and Vehicle Technologies) signed an Interagency Agreement (IAA) with National Institute for Occupational Safety and Health (NIOSH), No.01-15 DOE, 9/4/01, for 'The analysis of genotoxic activities of exhaust emissions from mobile natural gas, diesel, and spark-ignition engines'; subsequently modified on 3/27/02 (DOE IAG No.01-15-02M1); subsequently modified 9/02/03 (IAA Mod No. 01-15-03M1), as 'The analysis of genotoxic activities of exhaust emissions from mobile internal combustion engines: identification of engine design and operational parameters controlling exhaust genotoxicity'. The DOE Award/Contract number was DE-AI26-01CH11089. The IAA ended 9/30/06. This is the final summary technical report of National Institute for Occupational Safety and Health research performed with the US Department of Energy-Office of FreedomCar and Vehicle Technologies under that IAA: (A) NIOSH participation was requested by the DOE to provide in vitro genotoxicity assays of the organic solvent extracts of exhaust emissions from a suite of in-use diesel or spark-ignition vehicles; (B) research also was directed to develop and apply genotoxicity assays to the particulate phase of diesel exhaust, exploiting the NIOSH finding of genotoxicity expression by diesel exhaust particulate matter dispersed into the primary components of the surfactant coating the surface of the deep lung; (C) from the surfactant-dispersed DPM genotoxicity findings, the need for direct collection of DPM aerosols into surfactant for bioassay was recognized, and design and developmental testing of such samplers was initiated.

  3. Big Data Analytics with Datalog Queries on Spark.

    Science.gov (United States)

    Shkapsky, Alexander; Yang, Mohan; Interlandi, Matteo; Chiu, Hsuan; Condie, Tyson; Zaniolo, Carlo

    2016-01-01

    There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics.

  4. Hilbertian kernels and spline functions

    CERN Document Server

    Atteia, M

    1992-01-01

    In this monograph, which is an extensive study of Hilbertian approximation, the emphasis is placed on spline functions theory. The origin of the book was an effort to show that spline theory parallels Hilbertian Kernel theory, not only for splines derived from minimization of a quadratic functional but more generally for splines considered as piecewise functions type. Being as far as possible self-contained, the book may be used as a reference, with information about developments in linear approximation, convex optimization, mechanics and partial differential equations.

  5. Comparison Algorithm Kernels on Support Vector Machine (SVM To Compare The Trend Curves with Curves Online Forex Trading

    Directory of Open Access Journals (Sweden)

    irfan abbas

    2017-01-01

    Full Text Available At this time, the players Forex Trading generally still use the data exchange in the form of a Forex Trading figures from different sources. Thus they only receive or know the data rate of a Forex Trading prevailing at the time just so difficult to analyze or predict exchange rate movements future. Forex players usually use the indicators to enable them to analyze and memperdiksi future value. Indicator is a decision making tool. Trading forex is trading currency of a country, the other country's currency. Trading took place globally between the financial centers of the world with the involvement of the world's major banks as the major transaction. Trading Forex offers profitable investment type with a small capital and high profit, with relatively small capital can earn profits doubled. This is due to the forex trading systems exist leverage which the invested capital will be doubled if the predicted results of buy / sell is accurate, but Trading Forex having high risk level, but by knowing the right time to trade (buy or sell, the losses can be avoided. Traders who invest in the foreign exchange market is expected to have the ability to analyze the circumstances and situations in predicting the difference in currency exchange rates. Forex price movements that form the pattern (curve up and down greatly assist traders in making decisions. The movement of the curve used as an indicator in the decision to purchase (buy or sell (sell. This study compares (Comparation type algorithm kernel on Support Vector Machine (SVM to predict the movement of the curve in live time trading forex using the data GBPUSD, 1H. Results of research on the study of the results and discussion can be concluded that the Kernel Dot, Kernel Multiquaric, Kernel Neural inappropriately used for data is non-linear in the case of data forex to follow the pattern of trend curves, because curves generated curved linear (straight and then to type of kernel is the closest curve

  6. Liquid-Arc/Spark-Excitation Atomic-Emission Spectroscopy

    Science.gov (United States)

    Schlagen, Kenneth J.

    1992-01-01

    Constituents of solutions identified in situ. Liquid-arc/spark-excitation atomic-emission spectroscopy (LAES) is experimental variant of atomic-emission spectroscopy in which electric arc or spark established in liquid and spectrum of light from arc or spark analyzed to identify chemical elements in liquid. Observations encourage development of LAES equipment for online monitoring of process streams in such industries as metal plating, electronics, and steel, and for online monitoring of streams affecting environment.

  7. Notes on a storage manager for the Clouds kernel

    Science.gov (United States)

    Pitts, David V.; Spafford, Eugene H.

    1986-01-01

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

  8. Hybrid employment recommendation algorithm based on Spark

    Science.gov (United States)

    Li, Zuoquan; Lin, Yubei; Zhang, Xingming

    2017-08-01

    Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

  9. Sparking investment in Ontario's power generation industry

    International Nuclear Information System (INIS)

    Allen, J.

    2004-01-01

    This paper discusses the business strategy needed to spark investment in Ontario's power generation industry. It examines the process of decision making and investing in an uncertain environment. The paper suggests that any strategy based on one view of the future courts trouble and that strategic flexibility can prepare for what cannot be predicted. Finally the paper suggests that Ontario needs to create a stable policy and regulatory environment that allows investors to fulfill reasonable expectations and investors need to place bets that provide the flexibility to respond quickly to changing market conditions

  10. Anticipating Change, Sparking Innovation: Framing the Future

    Science.gov (United States)

    Finnegan, John R.; Spencer, Harrison C.

    2015-01-01

    As the 100th anniversary of the 1915 Welch-Rose report approaches, the Association of Schools and Programs of Public Health (ASPPH) has been pursuing two initiatives to spark innovation in academic partnerships for enhancing population health: (1) Framing the Future: The Second 100 Years of Education for Public Health and (2) Reconnecting Public Health and Care Delivery to Improve the Health of Populations. We describe how ASPPH-member schools and programs accredited by the Council on Education for Public Health, along with their extraordinarily diverse array of partners, are working to improve education that better prepares health professionals to meet 21st-century population health needs. PMID:25706017

  11. Dense Medium Machine Processing Method for Palm Kernel/ Shell ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In ... machine processing method using dense medium, a separator, a shell collector and a kernel .... efficiency, ease of maintenance and uniformity of.

  12. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge; Schuster, Gerard T.

    2012-01-01

    The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently

  13. Ranking Support Vector Machine with Kernel Approximation

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2017-01-01

    Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  14. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  15. Sentiment classification with interpolated information diffusion kernels

    NARCIS (Netherlands)

    Raaijmakers, S.

    2007-01-01

    Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of

  16. Evolution kernel for the Dirac field

    International Nuclear Information System (INIS)

    Baaquie, B.E.

    1982-06-01

    The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)

  17. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  18. Improving the Bandwidth Selection in Kernel Equating

    Science.gov (United States)

    Andersson, Björn; von Davier, Alina A.

    2014-01-01

    We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

  19. Kernel Korner : The Linux keyboard driver

    NARCIS (Netherlands)

    Brouwer, A.E.

    1995-01-01

    Our Kernel Korner series continues with an article describing the Linux keyboard driver. This article is not for "Kernel Hackers" only--in fact, it will be most useful to those who wish to use their own keyboard to its fullest potential, and those who want to write programs to take advantage of the

  20. Metabolic network prediction through pairwise rational kernels.

    Science.gov (United States)

    Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

    2014-09-26

    Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

  1. Accuracy of approximations of solutions to Fredholm equations by kernel methods

    Czech Academy of Sciences Publication Activity Database

    Gnecco, G.; Kůrková, Věra; Sanguineti, M.

    2012-01-01

    Roč. 218, č. 14 (2012), s. 7481-7497 ISSN 0096-3003 R&D Projects: GA ČR GAP202/11/1368; GA MŠk OC10047 Grant - others:CNR-AV ČR(CZ-IT) Project 2010–2012 “Complexity of Neural -Network and Kernel Computational Models Institutional research plan: CEZ:AV0Z10300504 Keywords : approximate solutions to integral equations * radial and kernel-based networks * Gaussian kernels * model complexity * analysis of algorithms Subject RIV: IN - Informatics, Computer Science Impact factor: 1.349, year: 2012

  2. Silicon nanoparticles produced by spark discharge

    International Nuclear Information System (INIS)

    Vons, Vincent A.; Smet, Louis C. P. M. de; Munao, David; Evirgen, Alper; Kelder, Erik M.; Schmidt-Ott, Andreas

    2011-01-01

    On the example of silicon, the production of nanoparticles using spark discharge is shown to be feasible for semiconductors. The discharge circuit is modelled as a damped oscillator circuit. This analysis reveals that the electrode resistance should be kept low enough to limit energy loss by Joule heating and to enable effective nanoparticle production. The use of doped electrodes results in a thousand-fold increase in the mass production rate as compared to intrinsic silicon. Pure and oxidised uniformly sized silicon nanoparticles with a primary particle diameter of 3–5 nm are produced. It is shown that the colour of the particles can be used as a good indicator of the oxidation state. If oxygen and water are banned from the spark generation system by (a) gas purification, (b) outgassing and (c) by initially using the particles produced as getters, unoxidised Si particles are obtained. They exhibit pyrophoric behaviour. This continuous nanoparticle preparation method can be combined with other processing techniques, including surface functionalization or the immediate impaction of freshly prepared nanoparticles onto a substrate for applications in the field of batteries, hydrogen storage or sensors.

  3. Power source with spark-safe outlet

    Energy Technology Data Exchange (ETDEWEB)

    Tsesarenko, N P; Alekhin, A V

    1982-01-01

    The invention refers to the technique of electrical monitoring and control in systems operating in a spark-safe medium (for example, in coal mines). A more accurate area of application is mobile objects with autonomous source of electricity (mine diesel locomotives, battery electric locomotives etc.). The purpose of the invention is to simplify and to improve the reliability of the planned device, and also to expand the area of application for conditions when it is powered from an autonomous generator of direct voltage. This goal is achieved because the power source with spark-safe outlet (the source contains a thyristor of advance disconnection, connected by anode to the delimiting throttle, one outlet of which is connected to the capacitor included between the controlling electrode and the anode of the thyristor, and the capacitor is connected through the resistor parallel to the outlet clamps of the source, while the thyristor of emergency protection connected parallel to the inlet clamps of the power source) is additionally equipped with a current sensor, hercon, transistor key (included in series in the power circuit) and optron, whose emitter is connected parallel to the current sensor connected in series to the inlet of the power source, while the receiver of the optron is connected in a circuit for controlling the thyristor of emergency protection. Hercon is built into the core of the delimiting throttle and is connected to the circuit for controlling the transistor key.

  4. Bayesian Kernel Mixtures for Counts.

    Science.gov (United States)

    Canale, Antonio; Dunson, David B

    2011-12-01

    Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.

  5. Detector for recoil nuclei stopping in the spark chamber gas

    International Nuclear Information System (INIS)

    Aleksanyan, A.S.; Asatiani, T.L.; Ivanov, V.I.; Mkrtchyan, G.G.; Pikhtelev, R.N.

    1974-01-01

    A detector consisting of the combination of a drift and a wide gap spark chambers and designed to detect recoil nuclei stopping in the spark chamber gas is described. It is shown, that by using an appropriate discrimination the detector allows to detect reliably the recoil nuclei in the presence of intensive electron and γ-quanta beams

  6. Combustion and operating characteristics of spark-ignition engines

    Science.gov (United States)

    Heywood, J. B.; Keck, J. C.; Beretta, G. P.; Watts, P. A.

    1980-01-01

    The spark-ignition engine turbulent flame propagation process was investigated. Then, using a spark-ignition engine cycle simulation and combustion model, the impact of turbocharging and heat transfer variations or engine power, efficiency, and NO sub x emissions was examined.

  7. Dual Spark Plugs For Stratified-Charge Rotary Engine

    Science.gov (United States)

    Abraham, John; Bracco, Frediano V.

    1996-01-01

    Fuel efficiency of stratified-charge, rotary, internal-combustion engine increased by improved design featuring dual spark plugs. Second spark plug ignites fuel on upstream side of main fuel injector; enabling faster burning and more nearly complete utilization of fuel.

  8. Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

    Directory of Open Access Journals (Sweden)

    Zhengbin Liu

    2016-08-01

    Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.

  9. Straight-chain halocarbon forming fluids for TRISO fuel kernel production – Tests with yttria-stabilized zirconia microspheres

    Energy Technology Data Exchange (ETDEWEB)

    Baker, M.P. [Nuclear Science and Engineering Program, Metallurgical and Materials Engineering Department, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); King, J.C., E-mail: kingjc@mines.edu [Nuclear Science and Engineering Program, Metallurgical and Materials Engineering Department, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Gorman, B.P. [Metallurgical and Materials Engineering Department, Colorado Center for Advanced Ceramics, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Braley, J.C. [Nuclear Science and Engineering Program, Chemistry and Geochemistry Department, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States)

    2015-03-15

    Highlights: • YSZ TRISO kernels formed in three alternative, non-hazardous forming fluids. • Kernels characterized for size, shape, pore/grain size, density, and composition. • Bromotetradecane is suitable for further investigation with uranium-based precursor. - Abstract: Current methods of TRISO fuel kernel production in the United States use a sol–gel process with trichloroethylene (TCE) as the forming fluid. After contact with radioactive materials, the spent TCE becomes a mixed hazardous waste, and high costs are associated with its recycling or disposal. Reducing or eliminating this mixed waste stream would not only benefit the environment, but would also enhance the economics of kernel production. Previous research yielded three candidates for testing as alternatives to TCE: 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane. This study considers the production of yttria-stabilized zirconia (YSZ) kernels in silicone oil and the three chosen alternative formation fluids, with subsequent characterization of the produced kernels and used forming fluid. Kernels formed in silicone oil and bromotetradecane were comparable to those produced by previous kernel production efforts, while those produced in chlorooctadecane and iodododecane experienced gelation issues leading to poor kernel formation and geometry.

  10. Protection of neutral-beam accelerator electrodes from spark discharges

    International Nuclear Information System (INIS)

    Praeg, W.F.

    1977-01-01

    The high-voltage (HV) electrodes of neutral beam sources (NBS's) must be protected from occasional sparks to ground. Spark currents can be limited with special transformers and reactors which introduce time delays that are long enough to quench the spark or to disconnect the energy source. A saturated time delay transformer (STDT) connected in series with the HV power supply detects spark faults and limits the current supplied by the power supply and its capacitance to ground; it also initiates spark quenching. Nonsaturated, longitudinal reactors limit the discharge current supplied by the energy stored in the circuit capacitance of the NBS filament and arc power supplies long enough to discharge this capacitance into a resistor. The design principles of these protective circuits are presented

  11. Protection of neutral-beam-accelerator electrodes from spark discharges

    International Nuclear Information System (INIS)

    Praeg, W.F.

    1977-01-01

    The high-voltage (HV) electrodes of neutral beam sources (NBS's) must be protected from occasional sparks to ground. Spark currents can be limited with special transformers and reactors which introduce time delays that are long enough to quench the spark or to disconnect the energy source. A saturated time delay transformer (STDT) connected in series with the HV power supply detects spark faults and limits the current supplied by the power supply and its capacitance to ground; it also initiates spark quenching. Nonsaturated, longitudinal reactors limit the discharge current supplied by the energy stored in the circuit capacitance of the NBS filament and arc power supplies long enough to discharge this capacitance into a resistor. The design principles of these protective circuits are presented in this paper

  12. Protection of neutral-beam-accelerator electrodes from spark discharges

    International Nuclear Information System (INIS)

    Praeg, W.F.

    1978-01-01

    The high-voltage (HV) electrodes of neutral beam sources (NBS's) must be protected from occasional sparks to ground. Spark currents can be limited with special transformers and reactors which introduce time delays that are long enough to quench the spark or to disconnect the energy source. A saturated time delay transformer (STDT) connected in series with the HV power supply detects spark faults and limits the current supplied by the power supply and its capacitance to ground; it also initiates spark quenching. Nonsaturated, longitudinal reactors limit the discharge current supplied by the energy stored in the circuit capacitance of the NBS filament and arc power supplies long enough to discharge this capacitance into a resistor. The design principles of these protective circuits are presented in this paper

  13. Putting Priors in Mixture Density Mercer Kernels

    Science.gov (United States)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2004-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

  14. Anisotropic hydrodynamics with a scalar collisional kernel

    Science.gov (United States)

    Almaalol, Dekrayat; Strickland, Michael

    2018-04-01

    Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

  15. Contextual Weisfeiler-Lehman Graph Kernel For Malware Detection

    OpenAIRE

    Narayanan, Annamalai; Meng, Guozhu; Yang, Liu; Liu, Jinliang; Chen, Lihui

    2016-01-01

    In this paper, we propose a novel graph kernel specifically to address a challenging problem in the field of cyber-security, namely, malware detection. Previous research has revealed the following: (1) Graph representations of programs are ideally suited for malware detection as they are robust against several attacks, (2) Besides capturing topological neighbourhoods (i.e., structural information) from these graphs it is important to capture the context under which the neighbourhoods are reac...

  16. Learning with Generalization Capability by Kernel Methods of Bounded Complexity

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2005-01-01

    Roč. 21, č. 3 (2005), s. 350-367 ISSN 0885-064X R&D Projects: GA AV ČR 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : supervised learning * generalization * model complexity * kernel methods * minimization of regularized empirical errors * upper bounds on rates of approximate optimization Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2005

  17. Nonlinear control of a spark ignition engine

    Energy Technology Data Exchange (ETDEWEB)

    Bidan, P [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Boverie, S; Chaumerliac, V [Siemens AutomotiveSA, MIRGAS Laboratory, 31 - Toulouse (France)

    1994-12-31

    This paper describes the improvements which can be made to spark ignition engine by extensive use of automatic control. Particular emphasis is placed on fast transient phases produced by simultaneous action on the throttle and the electronic fuel injection device. The aim is to achieve better performance for the fuel/air ratio regulation system, thereby improving engine efficiency and exhaust emission during these transient phases. The authors begin by presenting an average dynamic model of the intake manifold validated on an engine test bench and goes on to develop a closed-loop system controlling average pressure in the intake manifold using the reference tracking model method. The air supply control system is combined with a predictor to compensate for delays in the injection procedure. The paper concludes with a comparison between the results obtained using simulation and those obtained experimentally from the engine. (author) 10 refs.

  18. Spark-safe mechanical fluctuation sensor

    Energy Technology Data Exchange (ETDEWEB)

    Retek, S; Galisz, T

    1979-04-20

    The subject of the invention is a mechanical fluctuation sensor in a spark-safe design for use at mines which are dangerous for gas, as an element of different systems for remote control information transfer. The patented sensor of mechanical fluctuations contains: magnetic-induction transformer characterized by the fact that its inert mass consists of a plane permanent magnet placed in the suspended state on springs between 2 coils, which together with their cores are rigidly fixed to the walls of the ferromagnetic vessels. The ends of the coil windings are interconnected, while the beginnings of the windings are lead out with connection to the outlet of the electronic amplifier with binary outlet signal. The electronic amplifier is placed between the transformer in the common ferromagnetic housing which is a screen for protection from the effect of external magnetic fields.

  19. Spark formation as a moving boundary process

    Science.gov (United States)

    Ebert, Ute

    2006-03-01

    The growth process of spark channels recently becomes accessible through complementary methods. First, I will review experiments with nanosecond photographic resolution and with fast and well defined power supplies that appropriately resolve the dynamics of electric breakdown [1]. Second, I will discuss the elementary physical processes as well as present computations of spark growth and branching with adaptive grid refinement [2]. These computations resolve three well separated scales of the process that emerge dynamically. Third, this scale separation motivates a hierarchy of models on different length scales. In particular, I will discuss a moving boundary approximation for the ionization fronts that generate the conducting channel. The resulting moving boundary problem shows strong similarities with classical viscous fingering. For viscous fingering, it is known that the simplest model forms unphysical cusps within finite time that are suppressed by a regularizing condition on the moving boundary. For ionization fronts, we derive a new condition on the moving boundary of mixed Dirichlet-Neumann type (φ=ɛnφ) that indeed regularizes all structures investigated so far. In particular, we present compact analytical solutions with regularization, both for uniformly translating shapes and for their linear perturbations [3]. These solutions are so simple that they may acquire a paradigmatic role in the future. Within linear perturbation theory, they explicitly show the convective stabilization of a curved front while planar fronts are linearly unstable against perturbations of arbitrary wave length. [1] T.M.P. Briels, E.M. van Veldhuizen, U. Ebert, TU Eindhoven. [2] C. Montijn, J. Wackers, W. Hundsdorfer, U. Ebert, CWI Amsterdam. [3] B. Meulenbroek, U. Ebert, L. Schäfer, Phys. Rev. Lett. 95, 195004 (2005).

  20. Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

    African Journals Online (AJOL)

    In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...

  1. NLO corrections to the Kernel of the BKP-equations

    Energy Technology Data Exchange (ETDEWEB)

    Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)

    2012-10-02

    We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.

  2. Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  3. Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  4. Kernel maximum autocorrelation factor and minimum noise fraction transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...

  5. 7 CFR 51.1441 - Half-kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

  6. 7 CFR 51.2296 - Three-fourths half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

  7. 7 CFR 981.401 - Adjusted kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Adjusted kernel weight. 981.401 Section 981.401... Administrative Rules and Regulations § 981.401 Adjusted kernel weight. (a) Definition. Adjusted kernel weight... kernels in excess of five percent; less shells, if applicable; less processing loss of one percent for...

  8. 7 CFR 51.1403 - Kernel color classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

  9. The Linux kernel as flexible product-line architecture

    NARCIS (Netherlands)

    M. de Jonge (Merijn)

    2002-01-01

    textabstractThe Linux kernel source tree is huge ($>$ 125 MB) and inflexible (because it is difficult to add new kernel components). We propose to make this architecture more flexible by assembling kernel source trees dynamically from individual kernel components. Users then, can select what

  10. Parsimonious Wavelet Kernel Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Wang Qin

    2015-11-01

    Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

  11. Ensemble Approach to Building Mercer Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive...

  12. Control Transfer in Operating System Kernels

    Science.gov (United States)

    1994-05-13

    microkernel system that runs less code in the kernel address space. To realize the performance benefit of allocating stacks in unmapped kseg0 memory, the...review how I modified the Mach 3.0 kernel to use continuations. Because of Mach’s message-passing microkernel structure, interprocess communication was...critical control transfer paths, deeply- nested call chains are undesirable in any case because of the function call overhead. 4.1.3 Microkernel Operating

  13. Uranium kernel formation via internal gelation

    International Nuclear Information System (INIS)

    Hunt, R.D.; Collins, J.L.

    2004-01-01

    In the 1970s and 1980s, U.S. Department of Energy (DOE) conducted numerous studies on the fabrication of nuclear fuel particles using the internal gelation process. These amorphous kernels were prone to flaking or breaking when gases tried to escape from the kernels during calcination and sintering. These earlier kernels would not meet today's proposed specifications for reactor fuel. In the interim, the internal gelation process has been used to create hydrous metal oxide microspheres for the treatment of nuclear waste. With the renewed interest in advanced nuclear fuel by the DOE, the lessons learned from the nuclear waste studies were recently applied to the fabrication of uranium kernels, which will become tri-isotropic (TRISO) fuel particles. These process improvements included equipment modifications, small changes to the feed formulations, and a new temperature profile for the calcination and sintering. The modifications to the laboratory-scale equipment and its operation as well as small changes to the feed composition increased the product yield from 60% to 80%-99%. The new kernels were substantially less glassy, and no evidence of flaking was found. Finally, key process parameters were identified, and their effects on the uranium microspheres and kernels are discussed. (orig.)

  14. Quantum tomography, phase-space observables and generalized Markov kernels

    International Nuclear Information System (INIS)

    Pellonpaeae, Juha-Pekka

    2009-01-01

    We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase-space observable with a regular kernel state. Illustrative examples are given in the cases of a 'Schroedinger cat' kernel state and the Cahill-Glauber s-parametrized distributions. Also we consider an example of a kernel state when the generalized Markov kernel cannot be constructed.

  15. Target fabrication using laser and spark erosion machining

    International Nuclear Information System (INIS)

    Clement, X.; Coudeville, A.; Eyharts, P.; Perrine, J.P.; Rouillard, R.

    1982-01-01

    Fabrication of laser fusion targets requires a number of special techniques. We have developed both laser and spark erosion machining to produce minute parts of complex targets. A high repetition rate YAG laser at double frequency is used to etch various materials. For example, marks or patterns are often necessary on structured or advanced targets. The laser is also used to thin down plastic coated stalks. A spark erosion system has proved to be a versatile tool and we describe current fabrication processes like cutting, drilling, and ultra precise machining. Spark erosion has interesting features for target fabrication: it is a highly controllable and reproducible technique as well as relatively inexpensive

  16. Penetuan Bilangan Iodin pada Hydrogenated Palm Kernel Oil (HPKO) dan Refined Bleached Deodorized Palm Kernel Oil (RBDPKO)

    OpenAIRE

    Sitompul, Monica Angelina

    2015-01-01

    Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...

  17. Local Kernel for Brains Classification in Schizophrenia

    Science.gov (United States)

    Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.

    In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.

  18. High pressure gas-filled cermet spark gaps

    International Nuclear Information System (INIS)

    Avilov, Eh.A.; Yur'ev, A.L.

    2000-01-01

    The results of modernization of the R-48 and R-49 spark gaps making it possible to improve their electrical characteristics are presented. The design is described and characteristics of gas-filled cermet spark gaps are presented. By the voltage rise time of 5-6 μs in the Marx generator scheme they provide for the pulse break-through voltage of 120 and 150 kV. By the voltage rise time of 0.5-1 μs the break-through voltage of these spark gaps may be increased up to 130 and 220 kV. The proper commutation time is equal to ≤ 0.5 ns. Practical recommendations relative to designing cermet spark gaps are given [ru

  19. Exploring the Performance of Spark for a Scientific Use Case

    Energy Technology Data Exchange (ETDEWEB)

    Sehrish, Saba [Fermilab; Kowalkowski, Jim [Fermilab; Paterno, Marc [Fermilab

    2016-01-01

    We present an evaluation of the performance of a Spark implementation of a classification algorithm in the domain of High Energy Physics (HEP). Spark is a general engine for in-memory, large-scale data processing, and is designed for applications where similar repeated analysis is performed on the same large data sets. Classification problems are one of the most common and critical data processing tasks across many domains. Many of these data processing tasks are both computation- and data-intensive, involving complex numerical computations employing extremely large data sets. We evaluated the performance of the Spark implementation on Cori, a NERSC resource, and compared the results to an untuned MPI implementation of the same algorithm. While the Spark implementation scaled well, it is not competitive in speed to our MPI implementation, even when using significantly greater computational resources.

  20. Benchmarking NWP Kernels on Multi- and Many-core Processors

    Science.gov (United States)

    Michalakes, J.; Vachharajani, M.

    2008-12-01

    Increased computing power for weather, climate, and atmospheric science has provided direct benefits for defense, agriculture, the economy, the environment, and public welfare and convenience. Today, very large clusters with many thousands of processors are allowing scientists to move forward with simulations of unprecedented size. But time-critical applications such as real-time forecasting or climate prediction need strong scaling: faster nodes and processors, not more of them. Moreover, the need for good cost- performance has never been greater, both in terms of performance per watt and per dollar. For these reasons, the new generations of multi- and many-core processors being mass produced for commercial IT and "graphical computing" (video games) are being scrutinized for their ability to exploit the abundant fine- grain parallelism in atmospheric models. We present results of our work to date identifying key computational kernels within the dynamics and physics of a large community NWP model, the Weather Research and Forecast (WRF) model. We benchmark and optimize these kernels on several different multi- and many-core processors. The goals are to (1) characterize and model performance of the kernels in terms of computational intensity, data parallelism, memory bandwidth pressure, memory footprint, etc. (2) enumerate and classify effective strategies for coding and optimizing for these new processors, (3) assess difficulties and opportunities for tool or higher-level language support, and (4) establish a continuing set of kernel benchmarks that can be used to measure and compare effectiveness of current and future designs of multi- and many-core processors for weather and climate applications.

  1. Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM

    Directory of Open Access Journals (Sweden)

    Chenchao Zhao

    2018-01-01

    Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.

  2. Radiofrequency spark chambers and delay line resonators

    International Nuclear Information System (INIS)

    Sayag, Jacques

    1971-01-01

    According to a suggestion of A. Kastler, a spark chamber was excited by an undamped radiofrequency pulse and tracks about 1 mm wide obtained; the result was interpreted by computation of the coefficients of electronic amplification and partial ambipolar diffusion. This work led us to the construction of a new fast triggering undamped wave-train generator of very high tension (patent taken out by the C.E.A. under the no.: EN 7 134 650 the 27.9.1971). Since this apparatus uses a resonant storage line, its design implied a precise knowledge of high impedance delay lines. The experimental radiofrequency spectra of the input impedance of opened or short-circuited lines were plotted completely and analysed by the circuits theory, new measuring methods were established, dispersion relations accurately checked and the equivalence of the formulas, within the third order, with theses of Debye's Dipolar Absorption demonstrated. General properties of Hilbert's transform were also investigated. From the experimental point of view, the electromagnetic energy storage process was extended to the case of a liquid nitrogen-immersed resonant delay line. The good behavior of the cryogenic experiment, where the main difficulty of icing was overcame by the construction of special electrodes, offers great promise for extrapolation to superconductivity. (author) [fr

  3. Sparks Will Fly: engineering creative script conflicts

    Science.gov (United States)

    Veale, Tony; Valitutti, Alessandro

    2017-10-01

    Scripts are often dismissed as the stuff of good movies and bad politics. They codify cultural experience so rigidly that they remove our freedom of choice and become the very antithesis of creativity. Yet, mental scripts have an important role to play in our understanding of creative behaviour, since a deliberate departure from an established script can produce results that are simultaneously novel and familiar, especially when others stick to the conventional script. Indeed, creative opportunities often arise at the overlapping boundaries of two scripts that antagonistically compete to mentally organise the same situation. This work explores the computational integration of competing scripts to generate creative friction in short texts that are surprising but meaningful. Our exploration considers conventional macro-scripts - ordered sequences of actions - and the less obvious micro-scripts that operate at even the lowest levels of language. For the former, we generate plots that squeeze two scripts into a single mini-narrative; for the latter, we generate ironic descriptions that use conflicting scripts to highlight the speaker's pragmatic insincerity. We show experimentally that verbal irony requires both kinds of scripts - macro and micro - to work together to reliably generate creative sparks from a speaker's subversive intent.

  4. Automatic spark counting of alpha-tracks in plastic foils

    International Nuclear Information System (INIS)

    Somogyi, G.; Medveczky, L.; Hunyadi, I.; Nyako, B.

    1976-01-01

    The possibility of alpha-track counting by jumping spark counter in cellulose acetate and polycarbonate nuclear track detectors was studied. A theoretical treatment is presented which predicts the optimum residual thickness of the etched foils in which completely through-etched tracks (i.e. holes) can be obtained for alpha-particles of various energies and angles of incidence. In agreement with the theoretical prediction it is shown that a successful spark counting of alpha-tracks can be performed even in polycarbonate foils. Some counting characteristics, such as counting efficiency vs particle energy at various etched foil thicknesses, surface spark density produced by electric breakdowns in unexposed foils vs foil thickness, etc. have been determined. Special attention was given to the spark counting of alpha-tracks entering thin detectors at right angle. The applicability of the spark counting technique is demonstrated in angular distribution measurements of the 27 Al(p,α 0 ) 24 Mg nuclear reaction at Ep = 1899 keV resonance energy. For this study 15 μm thick Makrofol-G foils and a jumping spark counter of improved construction were used. (orig.) [de

  5. Aflatoxin contamination of developing corn kernels.

    Science.gov (United States)

    Amer, M A

    2005-01-01

    Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

  6. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  7. Basic study of Eu.sup.2+./sup.-doped garnet ceramic scintillator produced by spark plasma sintering

    Czech Academy of Sciences Publication Activity Database

    Sugiyama, K.; Yanagida, T.; Fujimoto, Y.; Yokota, Y.; Ito, A.; Nikl, Martin; Goto, T.; Yoshikawa, A.

    2012-01-01

    Roč. 35, č. 2 (2012), s. 222-226 ISSN 0925-3467 R&D Projects: GA MŠk LH12150 Institutional research plan: CEZ:AV0Z10100521 Keywords : Eu 2+ 5d–4f transition * scintillator * spark plasma sintering Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.918, year: 2012

  8. OS X and iOS Kernel Programming

    CERN Document Server

    Halvorsen, Ole Henry

    2011-01-01

    OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i

  9. The Classification of Diabetes Mellitus Using Kernel k-means

    Science.gov (United States)

    Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

    2018-01-01

    Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

  10. Object classification and detection with context kernel descriptors

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2014-01-01

    Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

  11. Scattering profiles of sparks and combustibility of filter against hot sparks

    International Nuclear Information System (INIS)

    Tobita, Noriyuki; Okada, Takashi; Kashiro, Kashio

    2004-12-01

    An event that a pre-filter burned on fire took place in the glove box dismantlement facility of Plutonium Production Facility, on April 21, 2003. The direct cause of this event was considered to be sparks generated by an abrasive wheel cutter, some of which reached the pre-filter and eventually burned the pre-filter. Further investigation revealed that there exist other deficiencies those of which formed indirect causes of the event, i.e., the wheel cutter was used without protective cover and adequate shield against sparks was not installed during the operation. To prevent similar event in the future, following corrective actions were introduced. Wheel cutter will not be used without protective cover; Incombustible pre-filter will be used; Shield will be place at the front of the pre-filter. We have conducted series of experimental tests in order to evaluate and confirm the validity of these corrective actions as well as determine the cause of the fire. This report present the results of these tests. (author)

  12. Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

    Science.gov (United States)

    Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

    2017-12-15

    Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

  13. Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates

    International Nuclear Information System (INIS)

    Hanft, J.M.; Jones, R.J.

    1986-01-01

    This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose

  14. Fluidization calculation on nuclear fuel kernel coating

    International Nuclear Information System (INIS)

    Sukarsono; Wardaya; Indra-Suryawan

    1996-01-01

    The fluidization of nuclear fuel kernel coating was calculated. The bottom of the reactor was in the from of cone on top of the cone there was a cylinder, the diameter of the cylinder for fluidization was 2 cm and at the upper part of the cylinder was 3 cm. Fluidization took place in the cone and the first cylinder. The maximum and the minimum velocity of the gas of varied kernel diameter, the porosity and bed height of varied stream gas velocity were calculated. The calculation was done by basic program

  15. Reduced multiple empirical kernel learning machine.

    Science.gov (United States)

    Wang, Zhe; Lu, MingZhe; Gao, Daqi

    2015-02-01

    Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

  16. Social Interactions Sparked by Pictorial Warnings on Cigarette Packs

    Directory of Open Access Journals (Sweden)

    Marissa G. Hall

    2015-10-01

    Full Text Available The Message Impact Framework suggests that social interactions may offer smokers the opportunity to process pictorial warnings on cigarette packs more deeply. We aimed to describe adult smokers’ social interactions about pictorial cigarette pack warnings in two longitudinal pilot studies. In Pilot Study 1, 30 smokers used cigarette packs with one of nine pictorial warnings for two weeks. In Pilot Study 2, 46 smokers used cigarette packs with one of five pictorial warnings for four weeks. Nearly all smokers (97%/96% in Pilot Study 1/2 talked about the warnings with other people, with the most common people being friends (67%/87% and spouses/significant others (34%/42%. Pilot Study 2 found that 26% of smokers talked about the warnings with strangers. Discussions about the health effects of smoking and quitting smoking were more frequent during the first week of exposure to pictorial warnings than in the week prior to beginning the study (both p < 0.05. Pictorial warnings sparked social interactions about the warnings, the health effects of smoking, and quitting smoking, indicating that pictorial warnings may act as a social intervention reaching beyond the individual. Future research should examine social interactions as a potential mediator of the impact of pictorial warnings on smoking behavior.

  17. Consolidation of copper and aluminium powders by spark plasma sintering

    Science.gov (United States)

    Saiprasad, M.; Atchayakumar, R.; Thiruppathi, K.; Raghuraman, S.

    2016-09-01

    Processing in the powder metallurgy route has emerged as an economical process for the production of near net shaped components with a wide range of desired mechanical properties suitable for various applications of industrial needs. This research work was conducted with an objective of studying the improvisation of density and hardness of Copper-Aluminium alloy prepared by spark plasma sintering. Cu-Al alloy with a composition of 95% copper and 5% aluminium was prepared by SPS process. SPS is a low voltage, DC pulse current activated, pressure-assisted sintering, which enables sintering at lower temperatures and shorter durations. The combination offered by Cu-Al alloy of high strength and high corrosion resistance results their applications under a wide variety of conditions. The density and hardness of the prepared sample were measured by conducting appropriate tests. Apparently, the values of hardness and density of the specimen prepared by SPS seemed to be better than that of conventional sintering. The experimental procedure, testing methodologies and analysis are presented.

  18. Optimization of process parameters for spark plasma sintering of nano structured SAF 2205 composite

    Directory of Open Access Journals (Sweden)

    Samuel Ranti Oke

    2018-04-01

    Full Text Available This research optimized spark plasma sintering (SPS process parameters in terms of sintering temperature, holding time and heating rate for the development of a nano-structured duplex stainless steel (SAF 2205 grade reinforced with titanium nitride (TiN. The mixed powders were sintered using an automated spark plasma sintering machine (model HHPD-25, FCT GmbH, Germany. Characterization was performed using X-ray diffraction and scanning electron microscopy. Density and hardness of the composites were investigated. The XRD result showed the formation of FeN0.068. SEM/EDS revealed the presence of nano ranged particles of TiN segregated at the grain boundaries of the duplex matrix. A decrease in hardness and densification was observed when sintering temperature and heating rate were 1200 °C and 150 °C/min respectively. The optimum properties were obtained in composites sintered at 1150 °C for 15 min and 100 °C/min. The composite grades irrespective of the process parameters exhibited similar shrinkage behavior, which is characterized by three distinctive peaks, which is an indication of good densification phenomena. Keywords: Spark plasma sintering, Duplex stainless steel (SAF 2205, Titanium nitride (TiN, Microstructure, Density, Hardness

  19. Contribution to the study of 'Pseudo-spark' discharges applied to the realisation of latch devices

    International Nuclear Information System (INIS)

    Bauville, Gerard

    1994-01-01

    The objective of this research thesis is to study discharges growing from a hollow geometry of electrodes for pressures on the left side of the Paschen minimum. The study characterises the main conduction phase by experimentally determining the discharge voltage and current. Based on a numerical analysis, the author deduces some macroscopic characteristics such as voltage mean value, dissipated energy, with respect to the variation of various parameters such as gas pressure and nature, discharge duration, and electrode cavity geometries. After a first part on switches (technological applications, switches, pseudo-spark breakers), the author addresses the discharges (presentation of a 'pseudo-spark'-type discharge, involved physical mechanisms, methods of initiation of pseudo-spark discharges, triggering by a magnetic field pulse). The next part describes the test bench in a detailed way (electrodes, triggering system, electric configurations), and the last part reports the experimental study. It addresses the following issues: distribution of magnetic field lines, voltage drop, conjunction phase, discharge footprints on the surfaces, propagation rate, disjunction [fr

  20. Formation and properties of two-phase bulk metallic glasses by spark plasma sintering

    Energy Technology Data Exchange (ETDEWEB)

    Xie Guoqiang, E-mail: xiegq@imr.tohoku.ac.jp [Institute for Materials Research, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577 (Japan); Louzguine-Luzgin, D.V. [WPI Advanced Institute for Materials Research, Tohoku University, Sendai 980-8577 (Japan); Inoue, Akihisa [Institute for Materials Research, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577 (Japan); WPI Advanced Institute for Materials Research, Tohoku University, Sendai 980-8577 (Japan)

    2011-06-15

    Research highlights: > Two-phase bulk metallic glasses with high strength and good soft magnetic properties as well as satisfying large-size requirements were produced by spark plasma sintering. > Effects of sintering temperature on thermal stability, microstructure, mechanical and magnetic properties were investigated. > Densified samples were obtained by the spark plasma sintering at above 773 K. - Abstract: Using a mixture of the gas-atomized Ni{sub 52.5}Nb{sub 10}Zr{sub 15}Ti{sub 15}Pt{sub 7.5} and Fe{sub 73}Si{sub 7}B{sub 17}Nb{sub 3} glassy alloy powders, we produced the two-phase bulk metallic glass (BMG) with high strength and good soft magnetic properties as well as satisfying large-size requirements by the spark plasma sintering (SPS) process. Two kinds of glassy particulates were homogeneously dispersed each other. With an increase in sintering temperature, density of the produced samples increased, and densified samples were obtained by the SPS process at above 773 K. Good bonding state among the Ni- and Fe-based glassy particulates was achieved.

  1. Comparative Analysis of Kernel Methods for Statistical Shape Learning

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

    2006-01-01

    .... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

  2. Variable kernel density estimation in high-dimensional feature spaces

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2017-02-01

    Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...

  3. Influence of differently processed mango seed kernel meal on ...

    African Journals Online (AJOL)

    Influence of differently processed mango seed kernel meal on performance response of west African ... and TD( consisted spear grass and parboiled mango seed kernel meal with concentrate diet in a ratio of 35:30:35). ... HOW TO USE AJOL.

  4. On methods to increase the security of the Linux kernel

    International Nuclear Information System (INIS)

    Matvejchikov, I.V.

    2014-01-01

    Methods to increase the security of the Linux kernel for the implementation of imposed protection tools have been examined. The methods of incorporation into various subsystems of the kernel on the x86 architecture have been described [ru

  5. Linear and kernel methods for multi- and hypervariate change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    . Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...... formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution......, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...

  6. Kernel methods in orthogonalization of multi- and hypervariate data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis...... via inner products in the Gram matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings...... are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MAF analysis handle nonlinearities by implicitly transforming data into high (even infinite...

  7. Sparking protection for MFTF-B Neutral Beam Power Supplies

    International Nuclear Information System (INIS)

    Cummings, D.B.

    1983-01-01

    This paper describes the upgrade of MFTF-B Neutral Beam Power Supplies for sparking protection. High performance ion sources spark repeatedly so ion source power supplies must be insensitive to sparking. The hot deck houses the series tetrode, arc and filament supplies, and controls. Hot deck shielding has been upgraded and a continuous shield around the arc, filament, gradient grid, and control cables now extends from the hot deck, through the core snubber, to the source. The shield carries accelerating current and connects only to the source. Shielded source cables go through an outer duct which now connects to a ground plane under the hot deck. This hybrid transmission line is a low inductance path for sparks discharging the stray capacitance of the hot deck and isolation transformers, reducing coupling to building steel. Parallel DC current return cables inside the duct lower inductance to reduce inductive turn-off transients. MOVs to ground further limit surges in the remote power supply return. Single point grounding is at the source. No control or rectifier components have been damaged nor are there any known malfunctions due to sparking up to 80 kV output

  8. Spark counting technique with an aluminium oxide film

    International Nuclear Information System (INIS)

    Kawai, H.; Koga, T.; Morishima, H.; Niwa, T.; Nishiwaki, Y.

    1980-01-01

    Automatic spark counting of etch-pits on a polycarbonate film produced by nuclear fission fragments is now used for neutron monitoring in several countries. A method was developed using an aluminium oxide film instead of a polycarbonate as the neutron detector. Aluminium oxide films were prepared as follows: A cleaned aluminium plate as an anode and a nickel plate as a cathode were immersed in dilute sulfuric acid solution and electric current flowed between the electrodes at 12degC for 10-30 minutes. Electric current density was about 10 mA/cm 2 . The aluminium plate was then kept in boiling water for 10-30 minutes for sealing. The thickness of the aluminium oxide layer formed was about 1μm. The aluminium plate attached to a plate of suitable fissionable material, such as uranium or thorium, was irradiated with neutrons and set in a usual spark counter for fission track counting. One electrode was the aluminium plate and the other was an aluminized polyester sheet. Sparked pulses were counted with a usual scaler. The advantage of using spark counting with an aluminium oxide film for neutron monitoring is rapid measurement of neutron exposure, since chemical etching which is indispensable for spark counting with a polycarbonate detector film, is not needed. (H.K.)

  9. Sparking protection for MFTF-B neutral beam power supplies

    International Nuclear Information System (INIS)

    Cummings, D.B.

    1983-01-01

    This paper describes the upgrade of MFTF-B Neutral Beam Power Supplies for sparking protection. High performance ion sources spark repeatedly so ion source power supplies must be insensitive to sparking. The hot deck houses the series tetrode, arc and filament supplies, and controls. Hot deck shielding has been upgraded and a continuous shield around the arc, filament, gradient grid, and control cables now extends from the hot deck, through the core snubber, to the source. The shield carries accelerating current and connects only to the source. Shielded source cables go through an outer duct which now connects to a ground plane under the hot deck. This hybrid transmission line is a low inductance path for sparks discharging the stray capacitance of the hot deck and isolation transformers, reducing coupling to building steel. Parallel dc current return cables inside the duct lower inductance to reduce inductive turn-off transients. MOVs to ground further limit surges in the remote power supply return. Single point grounding is at the source. No control or rectifier components have been damaged nor are there any known malfunctions due to sparking up to 80 kV output

  10. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge

    2012-01-01

    The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

  11. Relationship between attenuation coefficients and dose-spread kernels

    International Nuclear Information System (INIS)

    Boyer, A.L.

    1988-01-01

    Dose-spread kernels can be used to calculate the dose distribution in a photon beam by convolving the kernel with the primary fluence distribution. The theoretical relationships between various types and components of dose-spread kernels relative to photon attenuation coefficients are explored. These relations can be valuable as checks on the conservation of energy by dose-spread kernels calculated by analytic or Monte Carlo methods

  12. Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

    International Nuclear Information System (INIS)

    Barnes, Charles; Richardson, Clay; Nagley, Scott; Hunn, John; Shaber, Eric

    2010-01-01

    Babcock and Wilcox (B and W) has been producing high quality uranium oxycarbide (UCO) kernels for Advanced Gas Reactor (AGR) fuel tests at the Idaho National Laboratory. In 2005, 350-(micro)m, 19.7% 235U-enriched UCO kernels were produced for the AGR-1 test fuel. Following coating of these kernels and forming the coated-particles into compacts, this fuel was irradiated in the Advanced Test Reactor (ATR) from December 2006 until November 2009. B and W produced 425-(micro)m, 14% enriched UCO kernels in 2008, and these kernels were used to produce fuel for the AGR-2 experiment that was inserted in ATR in 2010. B and W also produced 500-(micro)m, 9.6% enriched UO2 kernels for the AGR-2 experiments. Kernels of the same size and enrichment as AGR-1 were also produced for the AGR-3/4 experiment. In addition to fabricating enriched UCO and UO2 kernels, B and W has produced more than 100 kg of natural uranium UCO kernels which are being used in coating development tests. Successive lots of kernels have demonstrated consistent high quality and also allowed for fabrication process improvements. Improvements in kernel forming were made subsequent to AGR-1 kernel production. Following fabrication of AGR-2 kernels, incremental increases in sintering furnace charge size have been demonstrated. Recently small scale sintering tests using a small development furnace equipped with a residual gas analyzer (RGA) has increased understanding of how kernel sintering parameters affect sintered kernel properties. The steps taken to increase throughput and process knowledge have reduced kernel production costs. Studies have been performed of additional modifications toward the goal of increasing capacity of the current fabrication line to use for production of first core fuel for the Next Generation Nuclear Plant (NGNP) and providing a basis for the design of a full scale fuel fabrication facility.

  13. Consistent Estimation of Pricing Kernels from Noisy Price Data

    OpenAIRE

    Vladislav Kargin

    2003-01-01

    If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

  14. A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

    Directory of Open Access Journals (Sweden)

    Domonkos Tikk

    Full Text Available The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study

  15. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.

    2009-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  16. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.; Coecke, B.; Panangaden, P.; Selinger, P.

    2011-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  17. Symbol recognition with kernel density matching.

    Science.gov (United States)

    Zhang, Wan; Wenyin, Liu; Zhang, Kun

    2006-12-01

    We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach in various situations.

  18. Flexible Scheduling in Multimedia Kernels: An Overview

    NARCIS (Netherlands)

    Jansen, P.G.; Scholten, Johan; Laan, Rene; Chow, W.S.

    1999-01-01

    Current Hard Real-Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where we can make a considerable profit by a better and more

  19. Reproducing kernel Hilbert spaces of Gaussian priors

    NARCIS (Netherlands)

    Vaart, van der A.W.; Zanten, van J.H.; Clarke, B.; Ghosal, S.

    2008-01-01

    We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of posterior distributions based on Gaussian priors can be described

  20. A synthesis of empirical plant dispersal kernels

    Czech Academy of Sciences Publication Activity Database

    Bullock, J. M.; González, L. M.; Tamme, R.; Götzenberger, Lars; White, S. M.; Pärtel, M.; Hooftman, D. A. P.

    2017-01-01

    Roč. 105, č. 1 (2017), s. 6-19 ISSN 0022-0477 Institutional support: RVO:67985939 Keywords : dispersal kernel * dispersal mode * probability density function Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 5.813, year: 2016

  1. Analytic continuation of weighted Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 94, č. 6 (2010), s. 622-650 ISSN 0021-7824 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * analytic continuation * Toeplitz operator Subject RIV: BA - General Mathematics Impact factor: 1.450, year: 2010 http://www.sciencedirect.com/science/article/pii/S0021782410000942

  2. On convergence of kernel learning estimators

    NARCIS (Netherlands)

    Norkin, V.I.; Keyzer, M.A.

    2009-01-01

    The paper studies convex stochastic optimization problems in a reproducing kernel Hilbert space (RKHS). The objective (risk) functional depends on functions from this RKHS and takes the form of a mathematical expectation (integral) of a nonnegative integrand (loss function) over a probability

  3. Analytic properties of the Virasoro modular kernel

    Energy Technology Data Exchange (ETDEWEB)

    Nemkov, Nikita [Moscow Institute of Physics and Technology (MIPT), Dolgoprudny (Russian Federation); Institute for Theoretical and Experimental Physics (ITEP), Moscow (Russian Federation); National University of Science and Technology MISIS, The Laboratory of Superconducting metamaterials, Moscow (Russian Federation)

    2017-06-15

    On the space of generic conformal blocks the modular transformation of the underlying surface is realized as a linear integral transformation. We show that the analytic properties of conformal block implied by Zamolodchikov's formula are shared by the kernel of the modular transformation and illustrate this by explicit computation in the case of the one-point toric conformal block. (orig.)

  4. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  5. Kernel Temporal Differences for Neural Decoding

    Science.gov (United States)

    Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2015-01-01

    We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

  6. Scattering kernels and cross sections working group

    International Nuclear Information System (INIS)

    Russell, G.; MacFarlane, B.; Brun, T.

    1998-01-01

    Topics addressed by this working group are: (1) immediate needs of the cold-moderator community and how to fill them; (2) synthetic scattering kernels; (3) very simple synthetic scattering functions; (4) measurements of interest; and (5) general issues. Brief summaries are given for each of these topics

  7. Enhanced gluten properties in soft kernel durum wheat

    Science.gov (United States)

    Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

  8. Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...

    African Journals Online (AJOL)

    Estimated error of ± 0.18 and ± 0.2 are envisaged while applying the models for predicting palm kernel and sesame oil colours respectively. Keywords: Palm kernel, Sesame, Palm kernel, Oil Colour, Process Parameters, Model. Journal of Applied Science, Engineering and Technology Vol. 6 (1) 2006 pp. 34-38 ...

  9. Stable Kernel Representations as Nonlinear Left Coprime Factorizations

    NARCIS (Netherlands)

    Paice, A.D.B.; Schaft, A.J. van der

    1994-01-01

    A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

  10. 7 CFR 981.60 - Determination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which settlement...

  11. 21 CFR 176.350 - Tamarind seed kernel powder.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

  12. End-use quality of soft kernel durum wheat

    Science.gov (United States)

    Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

  13. Heat kernel analysis for Bessel operators on symmetric cones

    DEFF Research Database (Denmark)

    Möllers, Jan

    2014-01-01

    . The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...

  14. A Fast and Simple Graph Kernel for RDF

    NARCIS (Netherlands)

    de Vries, G.K.D.; de Rooij, S.

    2013-01-01

    In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster

  15. 7 CFR 981.61 - Redetermination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of almonds...

  16. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  17. Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

    Science.gov (United States)

    Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

    2016-09-13

    Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

  18. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Directory of Open Access Journals (Sweden)

    Lan Shu

    2008-07-01

    Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

  19. Osteoarthritis Severity Determination using Self Organizing Map Based Gabor Kernel

    Science.gov (United States)

    Anifah, L.; Purnomo, M. H.; Mengko, T. L. R.; Purnama, I. K. E.

    2018-02-01

    The number of osteoarthritis patients in Indonesia is enormous, so early action is needed in order for this disease to be handled. The aim of this paper to determine osteoarthritis severity based on x-ray image template based on gabor kernel. This research is divided into 3 stages, the first step is image processing that is using gabor kernel. The second stage is the learning stage, and the third stage is the testing phase. The image processing stage is by normalizing the image dimension to be template to 50 □ 200 image. Learning stage is done with parameters initial learning rate of 0.5 and the total number of iterations of 1000. The testing stage is performed using the weights generated at the learning stage. The testing phase has been done and the results were obtained. The result shows KL-Grade 0 has an accuracy of 36.21%, accuracy for KL-Grade 2 is 40,52%, while accuracy for KL-Grade 2 and KL-Grade 3 are 15,52%, and 25,86%. The implication of this research is expected that this research as decision support system for medical practitioners in determining KL-Grade on X-ray images of knee osteoarthritis.

  20. Measurements of Radon Concentration in Yemen Using Spark Counter

    International Nuclear Information System (INIS)

    Arafa, W.; Abou-Leila, M.; Hafiz, M.E.; Al-Glal, N.

    2011-01-01

    Spark counter has been designed and realized and the optimum applied voltage was found to be 600 V. Excellent consistent agreements was observed between counted number of tracks by spark counter and reading by optical microscope. Radon concentration in some houses in Sana'a and Hodeidah cities in Yemen had been performed using LR-115 SSNTD and spark counter system. The average radon concentration in both cities was far lower the alert value. The results showed that radon concentration in the metropolitan area Sana'a was higher than that in Hodeidah city. Also, it was observed that old residential houses had higher levels of radon concentrations have compared to newly built houses in the metropolitan area Sana'a

  1. A miniature spark counter for public communication and education

    International Nuclear Information System (INIS)

    Mao, C.H.; Weng, P.S.

    1987-01-01

    The fabrication of a miniature spark counter for public communication and education using naturally occurring radon as a radioactive source without involving any man-made radioactivity is described. The battery-powered miniature spark counter weighs 2.07 kg with a volume of 4.844 x 10/sup -4/ m/sup 3/. The circuitry consists of seven major components: timer, high-voltage power supply, attenuator, noninverting amplifier, low-pass filter, one-shot generator, and counter. Cellulose nitrate films irradiated with alpha particles from radon emanating from soil were etched and counted. The visible sparks during counting are rather heuristic, which can be used to demonstrate naturally occurring radioactivity in classrooms or showplaces

  2. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

    Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

    2018-01-25

    The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

  3. Analysis of Plant Breeding on Hadoop and Spark

    Directory of Open Access Journals (Sweden)

    Shuangxi Chen

    2016-01-01

    Full Text Available Analysis of crop breeding technology is one of the important means of computer-assisted breeding techniques which have huge data, high dimensions, and a lot of unstructured data. We propose a crop breeding data analysis platform on Spark. The platform consists of Hadoop distributed file system (HDFS and cluster based on memory iterative components. With this cluster, we achieve crop breeding large data analysis tasks in parallel through API provided by Spark. By experiments and tests of Indica and Japonica rice traits, plant breeding analysis platform can significantly improve the breeding of big data analysis speed, reducing the workload of concurrent programming.

  4. Vacuum spark breakdown model based on exploding metal wire phenomena

    International Nuclear Information System (INIS)

    Haaland, J.

    1984-06-01

    Spark source mass spectra (SSMS) indicates that ions are extracted from an expanding and decaying plasma. The intensity distribution shows no dependance on vaporization properties of individual elements which indicates explosive vapour formation. This seems further to be a requirement for bridging a vacuum gap. A model including plasma ejection from a superheated anode spot by a process similar to that of an exploding metal wire is proposed. The appearance of hot plasma points in low inductance vacuum sparks can then be explained as exploding micro particles ejected from a final central anode spot. The phenomenological model is compared with available experimental results from literature, but no extensive quantification is attempted

  5. A note on preserving the spark of a matrix

    Directory of Open Access Journals (Sweden)

    Marcin Skrzynski

    2015-05-01

    Full Text Available Let Mm× n(F be the vector space of all m× n matrices over a field F. In the case where m ≥ n, char (F ≠ 2 and F has at least five elements, we give a complete characterization of linear maps Φ : Mm× n(F → Mm× n(F such that spark(Φ (A = spark(A for any A ∈ Mm× n(F.

  6. Phase characterisation in spark plasma sintered TiPt alloy

    CSIR Research Space (South Africa)

    Chikosha, S

    2011-12-01

    Full Text Available stream_source_info chikosha_2011.pdf.txt stream_content_type text/plain stream_size 4354 Content-Encoding UTF-8 stream_name chikosha_2011.pdf.txt Content-Type text/plain; charset=UTF-8 PHASE CHARACTERISATION IN SPARK... to form “necks”  Radiant Joule heat and pressure drives “neck” growth and material transfer © CSIR 2006 www.csir.co.za Page 6 Objective  Produce TiPt alloy compacts by Spark plasma sintering (SPS) of equiatomic...

  7. Researches on Preliminary Chemical Reactions in Spark-Ignition Engines

    Science.gov (United States)

    1943-06-01

    compression type, without ignition, the resulting preliminary reactions being detectable and meas- urable thermometrically . Contents I. Influence of Preliminary...thoroughly insulated be- tween the carburettor and the engine, by aluminium foil and asbestos. -I -I " I" I ’I il i~ " !, I I 1𔃻I I’ ) To enable the

  8. RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE) DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

    OpenAIRE

    Božena Barić; Ivana Pajač Živković; Dinka Matošević; Milorad Šubić; Erzsébet Voigt; Miklós Tóth

    2015-01-01

    Walnut husk fly (WHF), Rhagoletis completa Cresson 1929 is an invasive species spreading quickly and damaging walnuts in Croatia and neighbouring countries. We researched distribution of this pest in the continental part of Croatia, flight dynamics in Međimurje County and its influence on quality of walnut kernels. CSALOMON®PALz traps were used for monitoring the spread and flight dynamics of R. completa. Weight and the protein content of kernels and the presence of mycotoxin contamination we...

  9. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... analysis all 126 spectral bands of the HyMap are included. Changes on the ground are most likely due to harvest having taken place between the two acquisitions and solar effects (both solar elevation and azimuth have changed). Both types of kernel analysis emphasize change and unlike kernel PCA, kernel MNF...

  10. A laser optical method for detecting corn kernel defects

    Energy Technology Data Exchange (ETDEWEB)

    Gunasekaran, S.; Paulsen, M. R.; Shove, G. C.

    1984-01-01

    An opto-electronic instrument was developed to examine individual corn kernels and detect various kernel defects according to reflectance differences. A low power helium-neon (He-Ne) laser (632.8 nm, red light) was used as the light source in the instrument. Reflectance from good and defective parts of corn kernel surfaces differed by approximately 40%. Broken, chipped, and starch-cracked kernels were detected with nearly 100% accuracy; while surface-split kernels were detected with about 80% accuracy. (author)

  11. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  12. Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

    Directory of Open Access Journals (Sweden)

    Mohammed D. ABDULMALIK

    2008-06-01

    Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.

  13. Difference between standard and quasi-conformal BFKL kernels

    International Nuclear Information System (INIS)

    Fadin, V.S.; Fiore, R.; Papa, A.

    2012-01-01

    As it was recently shown, the colour singlet BFKL kernel, taken in Möbius representation in the space of impact parameters, can be written in quasi-conformal shape, which is unbelievably simple compared with the conventional form of the BFKL kernel in momentum space. It was also proved that the total kernel is completely defined by its Möbius representation. In this paper we calculated the difference between standard and quasi-conformal BFKL kernels in momentum space and discovered that it is rather simple. Therefore we come to the conclusion that the simplicity of the quasi-conformal kernel is caused mainly by using the impact parameter space.

  14. The Visualization and Analysis of POI Features under Network Space Supported by Kernel Density Estimation

    Directory of Open Access Journals (Sweden)

    YU Wenhao

    2015-01-01

    Full Text Available The distribution pattern and the distribution density of urban facility POIs are of great significance in the fields of infrastructure planning and urban spatial analysis. The kernel density estimation, which has been usually utilized for expressing these spatial characteristics, is superior to other density estimation methods (such as Quadrat analysis, Voronoi-based method, for that the Kernel density estimation considers the regional impact based on the first law of geography. However, the traditional kernel density estimation is mainly based on the Euclidean space, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. Hence, this research proposed a computational model of network kernel density estimation, and the extension type of model in the case of adding constraints. This work also discussed the impacts of distance attenuation threshold and height extreme to the representation of kernel density. The large-scale actual data experiment for analyzing the different POIs' distribution patterns (random type, sparse type, regional-intensive type, linear-intensive type discusses the POI infrastructure in the city on the spatial distribution of characteristics, influence factors, and service functions.

  15. A Generalized Pyramid Matching Kernel for Human Action Recognition in Realistic Videos

    Directory of Open Access Journals (Sweden)

    Wenjun Zhang

    2013-10-01

    Full Text Available Human action recognition is an increasingly important research topic in the fields of video sensing, analysis and understanding. Caused by unconstrained sensing conditions, there exist large intra-class variations and inter-class ambiguities in realistic videos, which hinder the improvement of recognition performance for recent vision-based action recognition systems. In this paper, we propose a generalized pyramid matching kernel (GPMK for recognizing human actions in realistic videos, based on a multi-channel “bag of words” representation constructed from local spatial-temporal features of video clips. As an extension to the spatial-temporal pyramid matching (STPM kernel, the GPMK leverages heterogeneous visual cues in multiple feature descriptor types and spatial-temporal grid granularity levels, to build a valid similarity metric between two video clips for kernel-based classification. Instead of the predefined and fixed weights used in STPM, we present a simple, yet effective, method to compute adaptive channel weights of GPMK based on the kernel target alignment from training data. It incorporates prior knowledge and the data-driven information of different channels in a principled way. The experimental results on three challenging video datasets (i.e., Hollywood2, Youtube and HMDB51 validate the superiority of our GPMK w.r.t. the traditional STPM kernel for realistic human action recognition and outperform the state-of-the-art results in the literature.

  16. TOWARDS FINDING A NEW KERNELIZED FUZZY C-MEANS CLUSTERING ALGORITHM

    Directory of Open Access Journals (Sweden)

    Samarjit Das

    2014-04-01

    Full Text Available Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like the conventional Fuzzy C-Means clustering technique this technique also suffers from inconsistency in its performance due to the fact that here also the initial centroids are obtained based on the randomly initialized membership values of the objects. Our present work proposes a new method where we have applied the Subtractive clustering technique of Chiu as a preprocessor to Kernelized Fuzzy CMeans clustering technique. With this new method we have tried not only to remove the inconsistency of Kernelized Fuzzy C-Means clustering technique but also to deal with the situations where the number of clusters is not predetermined. We have also provided a comparison of our method with the Subtractive clustering technique of Chiu and Kernelized Fuzzy C-Means clustering technique using two validity measures namely Partition Coefficient and Clustering Entropy.

  17. Optimization of the acceptance of prebiotic beverage made from cashew nut kernels and passion fruit juice.

    Science.gov (United States)

    Rebouças, Marina Cabral; Rodrigues, Maria do Carmo Passos; Afonso, Marcos Rodrigues Amorim

    2014-07-01

    The aim of this research was to develop a prebiotic beverage from a hydrosoluble extract of broken cashew nut kernels and passion fruit juice using response surface methodology in order to optimize acceptance of its sensory attributes. A 2(2) central composite rotatable design was used, which produced 9 formulations, which were then evaluated using different concentrations of hydrosoluble cashew nut kernel, passion fruit juice, oligofructose, and 3% sugar. The use of response surface methodology to interpret the sensory data made it possible to obtain a formulation with satisfactory acceptance which met the criteria of bifidogenic action and use of hydrosoluble cashew nut kernels by using 14% oligofructose and 33% passion fruit juice. As a result of this study, it was possible to obtain a new functional prebiotic product, which combined the nutritional and functional properties of cashew nut kernels and oligofructose with the sensory properties of passion fruit juice in a beverage with satisfactory sensory acceptance. This new product emerges as a new alternative for the industrial processing of broken cashew nut kernels, which have very low market value, enabling this sector to increase its profits. © 2014 Institute of Food Technologists®

  18. Kernel-based whole-genome prediction of complex traits: a review.

    Science.gov (United States)

    Morota, Gota; Gianola, Daniel

    2014-01-01

    Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  19. Kernel-based whole-genome prediction of complex traits: a review

    Directory of Open Access Journals (Sweden)

    Gota eMorota

    2014-10-01

    Full Text Available Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways, thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  20. Effects of spark plug configuration on combustion and emission characteristics of a LPG fuelled lean burn SI engine

    Science.gov (United States)

    Ravi, K.; Khan, Manazir Ahmed; Pradeep Bhasker, J.; Porpatham, E.

    2017-11-01

    Introduction of technological innovation in automotive engines in reducing pollution and increasing efficiency have been under contemplation. Gaseous fuels have proved to be a promising way to reduce emissions in Spark Ignition (SI) engines. In particular, LPG settled to be a favourable fuel for SI engines because of their higher hydrogen to carbon ratio, octane rating and lower emissions. Wide ignition limits and efficient combustion characteristics make LPG suitable for lean burn operation. But lean combustion technology has certain drawbacks like poor flame propagation, cyclic variations etc. Based on copious research it was found that location, types and number of spark plug significantly influence in reducing cyclic variations. In this work the influence of single and dual spark plugs of conventional and surface discharge electrode type were analysed. Dual surface discharge electrode spark plug enhanced the brake thermal efficiency and greatly reduced the cyclic variations. The experimental results show that rate of heat release and pressure rise was more and combustion duration was shortened in this configuration. On the emissions front, the NOx emission has increased whereas HC and CO emissions were reduced under lean condition.

  1. Practice and Exploration of New Rural Construction in West Bank of Taiwan Strait Led by Spark Science and Technology

    OpenAIRE

    Li, Chaocan

    2013-01-01

    According to practice and exploration of spark program for 26 years in Quanzhou, the main model and their effects of new rural construction in west bank of Taiwan Strait led by spark science and technology were expounded. Six spark program systems were established, consisting of policy support guide, science and technology project lead, experts’ intelligence support, spark science and technology training, sci-tech information service and spark program demonstration. Five spark projects were...

  2. Research in organizational participation and cooperation

    DEFF Research Database (Denmark)

    Jeppesen, Hans Jeppe; Jønsson, Thomas; Rasmussen, Thomas

    2005-01-01

    This article discusses some different perspectives on organizational participation and presents conducted and ongoing research projects by the research unit SPARK at Department of Psychology, University of Aarhus.......This article discusses some different perspectives on organizational participation and presents conducted and ongoing research projects by the research unit SPARK at Department of Psychology, University of Aarhus....

  3. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling

    Directory of Open Access Journals (Sweden)

    Hyojin Lee

    2015-01-01

    Full Text Available Precipitation is the main factor that drives hydrologic modeling; therefore, missing precipitation data can cause malfunctions in hydrologic modeling. Although interpolation of missing precipitation data is recognized as an important research topic, only a few methods follow a regression approach. In this study, daily precipitation data were interpolated using five different kernel functions, namely, Epanechnikov, Quartic, Triweight, Tricube, and Cosine, to estimate missing precipitation data. This study also presents an assessment that compares estimation of missing precipitation data through Kth nearest neighborhood (KNN regression to the five different kernel estimations and their performance in simulating streamflow using the Soil Water Assessment Tool (SWAT hydrologic model. The results show that the kernel approaches provide higher quality interpolation of precipitation data compared with the KNN regression approach, in terms of both statistical data assessment and hydrologic modeling performance.

  4. Bioconversions of Palm Kernel Cake and Rice Bran Mixtures by Trichoderma viride Toward Nutritional Contents

    OpenAIRE

    Yana Sukaryana; Umi Atmomarsono; Vitus D. Yunianto; Ejeng Supriyatna

    2010-01-01

    The objective of the research is to examine the mixtures of palm kernel cake and rice bran of fermented by Trichoderma viride. Completely randomized design in factorial pattern 4 x 4 was used in this experiment. factor I is the doses of inoculums; D1 = 0%, D2 =  0,1% , D3 =  0,2%, D4 =  0,3%, and  complement factor II is mixtures of palm kernel cake and rice bran : T1=20:80% ; T2=40:60% ; T3=60:40% ; T4=80:20%. The treatment each of three replicate. Fermentation was conduc...

  5. Reproducing kernel method with Taylor expansion for linear Volterra integro-differential equations

    Directory of Open Access Journals (Sweden)

    Azizallah Alvandi

    2017-06-01

    Full Text Available This research aims of the present a new and single algorithm for linear integro-differential equations (LIDE. To apply the reproducing Hilbert kernel method, there is made an equivalent transformation by using Taylor series for solving LIDEs. Shown in series form is the analytical solution in the reproducing kernel space and the approximate solution $ u_{N} $ is constructed by truncating the series to $ N $ terms. It is easy to prove the convergence of $ u_{N} $ to the analytical solution. The numerical solutions from the proposed method indicate that this approach can be implemented easily which shows attractive features.

  6. Analysis of cyclic variations during mode switching between spark ignition and controlled auto-ignition combustion operations

    OpenAIRE

    Chen, T; Zhao, H; Xie, H; He, B

    2014-01-01

    © IMechE 2014. Controlled auto-ignition, also known as homogeneous charge compression ignition, has been the subject of extensive research because of their ability to provide simultaneous reductions in fuel consumption and NOx emissions from a gasoline engine. However, due to its limited operation range, switching between controlled auto-ignition and spark ignition combustion is needed to cover the complete operating range of a gasoline engine for passenger car applications. Previous research...

  7. Prediction of protein subcellular localization using support vector machine with the choice of proper kernel

    Directory of Open Access Journals (Sweden)

    Al Mehedi Hasan

    2017-07-01

    Full Text Available The prediction of subcellular locations of proteins can provide useful hints for revealing their functions as well as for understanding the mechanisms of some diseases and, finally, for developing novel drugs. As the number of newly discovered proteins has been growing exponentially, laboratory-based experiments to determine the location of an uncharacterized protein in a living cell have become both expensive and time-consuming. Consequently, to tackle these challenges, computational methods are being developed as an alternative to help biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging problem, particularly when query proteins may have multi-label characteristics, i.e. their simultaneous existence in more than one subcellular location, or if they move between two or more different subcellular locations as well. At this point, to get rid of this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM has been employed to provide potential solutions for problems connected with the prediction of protein subcellular localization. However, the practicability of SVM is affected by difficulties in selecting its appropriate kernel as well as in selecting the parameters of that selected kernel. The literature survey has shown that most researchers apply the radial basis function (RBF kernel to build a SVM based subcellular localization prediction system. Surprisingly, there are still many other kernel functions which have not yet been applied in the prediction of protein subcellular localization. However, the nature of this classification problem requires the application of different kernels for SVM to ensure an optimal result. From this viewpoint, this paper presents the work to apply different kernels for SVM in protein

  8. Learning a peptide-protein binding affinity predictor with kernel ridge regression

    Science.gov (United States)

    2013-01-01

    peptide-protein binding affinities. The proposed approach is flexible and can be applied to predict any quantitative biological activity. Moreover, generating reliable peptide-protein binding affinities will also improve system biology modelling of interaction pathways. Lastly, the method should be of value to a large segment of the research community with the potential to accelerate the discovery of peptide-based drugs and facilitate vaccine development. The proposed kernel is freely available at http://graal.ift.ulaval.ca/downloads/gs-kernel/. PMID:23497081

  9. Pseudo-spark switch (PSS) characteristics under different operation conditions

    Energy Technology Data Exchange (ETDEWEB)

    Hamad, B. H., E-mail: dr.bassmahussain@gmail.com; Ahmad, A. K., E-mail: ahmad.kamal@sc.nahrainuniv.edu.iq [College of Science, Al Nahrain University, Jadria, Baghdad (Iraq); Lateef, K. H., E-mail: kamalhlatif@yahoo.com [Ministry of Science and Technology, Jadria, Baghdad (Iraq)

    2016-08-15

    The present paper concentrates on the characteristics of the pseudospark switch (PSS) designed in a previous work. The special characteristics of PSS make it a replacement for other high voltage switches such as thyratrons and ordinary high-pressure spark gaps. PSS is characterized by short rise time and small jitter time. The pseudo park chamber consists of two hollow cylindrical electrodes made of a stainless steel material (type 306L) separated by an insulator. The insulator used in our design is a glazed ceramic 70 mm in diameter and 3.5 mm in thickness. A PSS with an anode voltage of 29.2 kV, and a current of 3.6 kA and 11 ns rise time was achieved and used successfully at a repetition rate of about 2.2 kHz. A simple trigger circuit designed, built, and used effectively reaching more than 1.56 kV trigger pulse which is sufficient to ignite the argon gas inside the cathode to cause a breakdown. A non-inductive dummy load is designed to be a new technique to find the accurate value of the PSS inductance. A jitter time of ±10 ns pulses is observed to occur in a reliable manner for more than 6 h of continuous operation. In this research, the important parameters of this switch like rise time, peak current, and anode voltage were studied at various values of charging capacitance. The lifetime of this system is depending on the kind of the electrode material and on the type of insulation material in the main gap of the pseudospark switch.

  10. Stopping particles in the Mont Blanc spark chamber telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Bergamasco, L; Bilokon, H; Piazzoli, B E; Mannocchi, G; Picchi, P [Consiglio Nazionale delle Ricerche, Turin (Italy). Lab. di Cosmo-Geofisica; Turin Univ. (Italy). Ist. di Fisica Generale)

    1982-02-01

    We present the final results on the ratio of stopping to traversing muons as measured by two spark chamber telescopes in the Mont Blanc Station, Italy, at 4300 hg/cm/sup 2/. The experimental results are in agreement with the theoretical values within the limits of the error.

  11. Evolution of Spark plasma using nitrogen laser shadowgraphy system

    International Nuclear Information System (INIS)

    Ishiekwene, G.C.

    1994-07-01

    A simple, low cost, home built high power nitrogen laser is used as the light source for a shadowgraphy system. A series of shadowgrams depicting the temporal growth of a spark plasma discharge is obtained. The results could be useful in plasma diagnostic studies. (author). 5 refs, 6 figs

  12. knock characteristics analysis of a supercharged spark ignition

    African Journals Online (AJOL)

    user

    The power output of a spark ignition engine could be improved by boosting the ... that the presence of aromatics was responsible for the better anti-knock ..... System, a Master's Thesis in the Institutionen för ... Maintenance and Reliability, Vol.

  13. SPARK RttT: Year One Fidelity and Implementation

    Science.gov (United States)

    Rochford, Joseph A.; O'Neill, Adrienne; Gelb, Adele; Ross, Kimberly

    2014-01-01

    Developed in 2003 by the Sisters of Charity Foundation of Canton with a grant from the Kellogg Foundation, "Supporting Partnerships to Assure Ready Kids" ("SPARK Ohio") is a family-centered kindergarten readiness program that works with families, schools, and the community. From its initial sites in Stark County, "SPARK…

  14. Towards constrained optimal control of spark-ignition engines

    NARCIS (Netherlands)

    Feru, E.; Luo, X.

    2015-01-01

    In this paper, the torque control problem for spark-ignition engines is considered. The objective is to provide good output torque tracking with minimum fuel consumption, while avoiding engine knock and misre. To this end, three control strategies are proposed: a feed-forward controller with

  15. Utilization of Alcohol Fuel in Spark Ignition and Diesel Engines.

    Science.gov (United States)

    Berndt, Don; Stengel, Ron

    These five units comprise a course intended to prepare and train students to conduct alcohol fuel utilization seminars in spark ignition and diesel engines. Introductory materials include objectives and a list of instructor requirements. The first four units cover these topics: ethanol as an alternative fuel (technical and economic advantages,…

  16. Material machining with pseudo-spark electron beams

    International Nuclear Information System (INIS)

    Benker, W.; Christiansen, J.; Frank, K.; Gundel, H.; Redel, T.; Stetter, M.

    1989-01-01

    The authors give a brief description of the production of pseudo-spark (low pressure gas discharge) electron beams. They illustrate the use of these electron beams for machining not only conducting, semiconducting and insulating materials, but also thin layers of such materials as high temperature superconducting ceramics

  17. Multi-spark discharge system for preparation of nutritious water

    Science.gov (United States)

    Nakaso, Tetsushi; Harigai, Toru; Kusumawan, Sholihatta Aziz; Shimomura, Tomoya; Tanimoto, Tsuyoshi; Suda, Yoshiyuki; Takikawa, Hirofumi

    2018-01-01

    The nitrogen compound concentration in water is increased by atmospheric-pressure plasma discharge treatment. A rod-to-water electrode discharge treatment system using plasma discharge has been developed by our group to obtain water with a high concentration of nitrogen compounds, and this plasma-treated water improves the growth of chrysanthemum roots. However, it is difficult to apply the system to the agriculture because the amount of treated water obtained by using the system too small. In this study, a multi-spark discharge system (MSDS) equipped multiple spark plugs is presented to obtain a large amount of plasma-treated water. The MSDS consisted of inexpensive parts in order to reduce the system introduction cost for agriculture. To suppress the temperature increase of the spark plugs, the 9 spark plugs were divided into 3 groups, which were discharged in order. The plasma-treated water with a NO3- concentration of 50 mg/L was prepared using the MSDS for 90 min, and the treatment efficiency was about 6 times higher than that of our previous system. It was confirmed that the NO2-, O3, and H2O2 concentrations in the water were also increased by treating the water using the MSDS.

  18. Saffman-Taylor streamers: Mutual finger interaction in spark formation

    NARCIS (Netherlands)

    Luque, A.; Brau, F.; Ebert, U.

    2008-01-01

    Bunches of streamers form the early stages of sparks and lightning but theory presently concentrates on single streamers or on coarse approximations of whole breakdown trees. Here a periodic array of interacting streamer discharges in a strong homogeneous electric field is studied in density or

  19. The physics of photoconductive spark gap switching : pushing the frontiers

    NARCIS (Netherlands)

    Hendriks, J.

    2006-01-01

    Photoconductive switching of an atmospheric, air-¯lled spark gap by a high-power fem- tosecond laser is a novel approach for switching high voltages into pulses with a very fast rise time (order ps) and almost no shot-to-shot time variation (jitter). Such a switch makes it possible to synchronize

  20. Simulation of muon transport through the aragats spark chamber calorimeter

    International Nuclear Information System (INIS)

    Asatiani, T.L.; Ter-Antonyan, S.V.

    1981-01-01

    The algorithm is presented of the program on simulation of muon transport through Aragats spark calorimeter. Statistic test method with account of fluctuations and angular distributions of cascade showers is used. The program is worked out on the Fortran algorithm language for EVM BESM-6 and is calibrated by experimental data of Aragats complex installation [ru

  1. Analytic scattering kernels for neutron thermalization studies

    International Nuclear Information System (INIS)

    Sears, V.F.

    1990-01-01

    Current plans call for the inclusion of a liquid hydrogen or deuterium cold source in the NRU replacement vessel. This report is part of an ongoing study of neutron thermalization in such a cold source. Here, we develop a simple analytical model for the scattering kernel of monatomic and diatomic liquids. We also present the results of extensive numerical calculations based on this model for liquid hydrogen, liquid deuterium, and mixtures of the two. These calculations demonstrate the dependence of the scattering kernel on the incident and scattered-neutron energies, the behavior near rotational thresholds, the dependence on the centre-of-mass pair correlations, the dependence on the ortho concentration, and the dependence on the deuterium concentration in H 2 /D 2 mixtures. The total scattering cross sections are also calculated and compared with available experimental results

  2. Quantized kernel least mean square algorithm.

    Science.gov (United States)

    Chen, Badong; Zhao, Songlin; Zhu, Pingping; Príncipe, José C

    2012-01-01

    In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea behind this method is to quantize and hence compress the input (or feature) space. Different from sparsification, the new approach uses the "redundant" data to update the coefficient of the closest center. In particular, a quantized kernel least mean square (QKLMS) algorithm is developed, which is based on a simple online vector quantization method. The analytical study of the mean square convergence has been carried out. The energy conservation relation for QKLMS is established, and on this basis we arrive at a sufficient condition for mean square convergence, and a lower and upper bound on the theoretical value of the steady-state excess mean square error. Static function estimation and short-term chaotic time-series prediction examples are presented to demonstrate the excellent performance.

  3. Kernel-based tests for joint independence

    DEFF Research Database (Denmark)

    Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard

    2018-01-01

    if the $d$ variables are jointly independent, as long as the kernel is characteristic. Based on an empirical estimate of dHSIC, we define three different non-parametric hypothesis tests: a permutation test, a bootstrap test and a test based on a Gamma approximation. We prove that the permutation test......We investigate the problem of testing whether $d$ random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two variable Hilbert-Schmidt independence criterion (HSIC) but allows for an arbitrary number of variables. We embed...... the $d$-dimensional joint distribution and the product of the marginals into a reproducing kernel Hilbert space and define the $d$-variable Hilbert-Schmidt independence criterion (dHSIC) as the squared distance between the embeddings. In the population case, the value of dHSIC is zero if and only...

  4. Wilson Dslash Kernel From Lattice QCD Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Joo, Balint [Jefferson Lab, Newport News, VA; Smelyanskiy, Mikhail [Parallel Computing Lab, Intel Corporation, California, USA; Kalamkar, Dhiraj D. [Parallel Computing Lab, Intel Corporation, India; Vaidyanathan, Karthikeyan [Parallel Computing Lab, Intel Corporation, India

    2015-07-01

    Lattice Quantum Chromodynamics (LQCD) is a numerical technique used for calculations in Theoretical Nuclear and High Energy Physics. LQCD is traditionally one of the first applications ported to many new high performance computing architectures and indeed LQCD practitioners have been known to design and build custom LQCD computers. Lattice QCD kernels are frequently used as benchmarks (e.g. 168.wupwise in the SPEC suite) and are generally well understood, and as such are ideal to illustrate several optimization techniques. In this chapter we will detail our work in optimizing the Wilson-Dslash kernels for Intel Xeon Phi, however, as we will show the technique gives excellent performance on regular Xeon Architecture as well.

  5. Theoretical investigation of a photoconductively switched high-voltage spark gap

    NARCIS (Netherlands)

    Broks, B.H.P.; Hendriks, J.; Brok, W.J.M.; Brussaard, G.J.H.; Mullen, van der J.J.A.M.

    2006-01-01

    In this contribution, a photoconductively switched high-voltage spark gap with an emphasis on theswitching behavior is modeled. It is known experimentally that not all of the voltage that is present at the input of the spark gap is switched, but rather a fraction of it drops across the spark gap.

  6. The Results of a Randomized Control Trial Evaluation of the SPARK Literacy Program

    Science.gov (United States)

    Jones, Curtis J.; Christian, Michael; Rice, Andrew

    2016-01-01

    The purpose of this report is to present the results of a two-year randomized control trial evaluation of the SPARK literacy program. SPARK is an early grade literacy program developed by Boys & Girls Clubs of Greater Milwaukee. In 2010, SPARK was awarded an Investing in Innovation (i3) Department of Education grant to further develop the…

  7. Replacement value of palm kernel meal for maize on growth, egg ...

    African Journals Online (AJOL)

    A research was conducted to evaluate the effect of replacing maize with palm kernel meal (PKM) in the diet on the performance of duck hens. Five treatment diets were formulated in which PKM replaced maize at 0, 25, 50, 75 and 100% using a completely randomized design in three replications. The study lasted 8 weeks ...

  8. Experiences implementing the MPI standard on Sandia`s lightweight kernels

    Energy Technology Data Exchange (ETDEWEB)

    Brightwell, R.; Greenberg, D.S.

    1997-10-01

    This technical report describes some lessons learned from implementing the Message Passing Interface (MPI) standard, and some proposed extentions to MPI, at Sandia. The implementations were developed using Sandia-developed lightweight kernels running on the Intel Paragon and Intel TeraFLOPS platforms. The motivations for this research are discussed, and a detailed analysis of several implementation issues is presented.

  9. A Kernel for Protein Secondary Structure Prediction

    OpenAIRE

    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01

    http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...

  10. Scalar contribution to the BFKL kernel

    International Nuclear Information System (INIS)

    Gerasimov, R. E.; Fadin, V. S.

    2010-01-01

    The contribution of scalar particles to the kernel of the Balitsky-Fadin-Kuraev-Lipatov (BFKL) equation is calculated. A great cancellation between the virtual and real parts of this contribution, analogous to the cancellation in the quark contribution in QCD, is observed. The reason of this cancellation is discovered. This reason has a common nature for particles with any spin. Understanding of this reason permits to obtain the total contribution without the complicated calculations, which are necessary for finding separate pieces.

  11. Weighted Bergman Kernels for Logarithmic Weights

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 6, č. 3 (2010), s. 781-813 ISSN 1558-8599 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * Toeplitz operator * logarithmic weight * pseudodifferential operator Subject RIV: BA - General Mathematics Impact factor: 0.462, year: 2010 http://www.intlpress.com/site/pub/pages/journals/items/pamq/content/vols/0006/0003/a008/

  12. Heat kernels and zeta functions on fractals

    International Nuclear Information System (INIS)

    Dunne, Gerald V

    2012-01-01

    On fractals, spectral functions such as heat kernels and zeta functions exhibit novel features, very different from their behaviour on regular smooth manifolds, and these can have important physical consequences for both classical and quantum physics in systems having fractal properties. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical in honour of Stuart Dowker's 75th birthday devoted to ‘Applications of zeta functions and other spectral functions in mathematics and physics’. (paper)

  13. Erosion on spark plug electrodes; Funkenerosion an Zuendkerzenelektroden

    Energy Technology Data Exchange (ETDEWEB)

    Rager, J.

    2006-07-01

    Durability of spark plugs is mainly determined by spark gap widening, caused by electrode wear. Knowledge about the erosion mechanisms of spark plug materials is of fundamental interest for the development of materials with a high resistance against electrode erosion. It is therefore crucial to identify those parameters which significantly influence the erosion behaviour of a material. In this work, a reliable and reproducible testing method is presented which produces and characterizes electrode wear under well-defined conditions and which is capable of altering parameters specifically. Endurance tests were carried out to study the dependence of the wear behaviour of pure nickel and platinum on the electrode temperature, gas, electrode gap, electrode diameter, atmospheric pressure, and partial pressure of oxygen. It was shown that erosion under nitrogen is negligible, irrespective of the material. This disproves all common mechanism discussed in the literature explaining material loss of spark plug electrodes. Based on this observation and the variation of the mentioned parameters a new erosion model was deduced. This relies on an oxidation of the electrode material and describes the erosion of nickel and platinum separately. For nickel, electrode wear is caused by the removal of an oxide layer by the spark. In the case of platinum, material loss occurs due to the plasma-assisted formation and subsequent evaporation of volatile oxides in the cathode spot. On the basis of this mechanism a new composite material was developed whose erosion resistance is superior to pure platinum. Oxidation resistant metal oxide particles were added to a platinum matrix, thus leading to a higher erosion resistance of the composite. However, this can be decreased by a side reaction, the separation of oxygen from the metal oxides, which effectively assists the oxidation of the matrix. This reaction can be suppressed by using highly stable oxides, characterized by a large negative Gibbs

  14. Exploiting graph kernels for high performance biomedical relation extraction.

    Science.gov (United States)

    Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

    2018-01-30

    Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

  15. Identification of Fusarium damaged wheat kernels using image analysis

    Directory of Open Access Journals (Sweden)

    Ondřej Jirsa

    2011-01-01

    Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.

  16. Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

    Science.gov (United States)

    Kwak, Nojun

    2016-05-20

    Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

  17. Kernel based subspace projection of near infrared hyperspectral images of maize kernels

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

    2009-01-01

    In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...

  18. Characterization of Brazilian mango kernel fat before and after gamma irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Aquino, Fabiana da Silva; Ramos, Clecio Souza, E-mail: fasiaquino@yahoo.com.br, E-mail: clecio@dcm.ufrpe.br [Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE (Brazil); Aquino, Katia Aparecida da Silva, E-mail: aquino@ufpe.br [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil)

    2013-07-01

    Mangifera indica Linn (family of Anacardiaceae) is a tree indigenous to India, whose both unripe and ripe fruits (mangoes) are widely used by the local population. After consumption or industrial processing of the fruits, considerable amounts of mango seeds are discarded as waste. The kernel inside the seed represents from 45% to 75% of the seed and about 20% of the whole fruit and lipid composition of mango seed kernels has attracted the attention of researches because of their unique physical and chemical characteristics. Our study showed that fat of the mango kernel obtained by Soxhlet extraction with hexane had a solid consistency at environmental temperature (27 deg C) because it is rich in saturated acid. The fat contents of the seed of Mangifera indica was calculated to 10% and are comparable to the ones for commercial vegetable oils like soybean (11-25%). One problem found in the storage of fast and oils is the attack by microorganisms and the sterilization process becomes necessary. Samples of kernel fat were irradiated with gamma radiation ({sup 60}Co) at room temperature and air atmosphere at 5 and 10 kGy (sterilization doses). The data of GC-MS analysis revealed the presence of four major fatty acids in the sample of mango kernel examined and that the chemical profile of the sample not altered after being irradiated. Moreover, analysis of Proton Nuclear Magnetic Resonance (NMR H{sup 1}) was used to obtain the mango kernel fat parameters before and after gamma irradiation. The data interpretation of RMN H{sup 1} indicated that there are significant differences in the acidity and saponification indexes of fat. However, it was found an increase of 14% in iodine index of fat after irradiation. This result means that some double bonds were formed on the irradiation process of the fat. (author)

  19. Characterization of Brazilian mango kernel fat before and after gamma irradiation

    International Nuclear Information System (INIS)

    Aquino, Fabiana da Silva; Ramos, Clecio Souza; Aquino, Katia Aparecida da Silva

    2013-01-01

    Mangifera indica Linn (family of Anacardiaceae) is a tree indigenous to India, whose both unripe and ripe fruits (mangoes) are widely used by the local population. After consumption or industrial processing of the fruits, considerable amounts of mango seeds are discarded as waste. The kernel inside the seed represents from 45% to 75% of the seed and about 20% of the whole fruit and lipid composition of mango seed kernels has attracted the attention of researches because of their unique physical and chemical characteristics. Our study showed that fat of the mango kernel obtained by Soxhlet extraction with hexane had a solid consistency at environmental temperature (27 deg C) because it is rich in saturated acid. The fat contents of the seed of Mangifera indica was calculated to 10% and are comparable to the ones for commercial vegetable oils like soybean (11-25%). One problem found in the storage of fast and oils is the attack by microorganisms and the sterilization process becomes necessary. Samples of kernel fat were irradiated with gamma radiation ( 60 Co) at room temperature and air atmosphere at 5 and 10 kGy (sterilization doses). The data of GC-MS analysis revealed the presence of four major fatty acids in the sample of mango kernel examined and that the chemical profile of the sample not altered after being irradiated. Moreover, analysis of Proton Nuclear Magnetic Resonance (NMR H 1 ) was used to obtain the mango kernel fat parameters before and after gamma irradiation. The data interpretation of RMN H 1 indicated that there are significant differences in the acidity and saponification indexes of fat. However, it was found an increase of 14% in iodine index of fat after irradiation. This result means that some double bonds were formed on the irradiation process of the fat. (author)

  20. LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

    Science.gov (United States)

    Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

    2018-05-07

    Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

  1. Kernel based eigenvalue-decomposition methods for analysing ham

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

    2010-01-01

    methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...... useful factor of PCA and kernel based PCA respectively in Figure 2. The factor of the kernel based PCA turned out to be able to segment the two types of meat and in general that factor is much more distinct, compared to the traditional factor. After the orthogonal transformation a simple thresholding...

  2. A Temperature Compensation Method for Piezo-Resistive Pressure Sensor Utilizing Chaotic Ions Motion Algorithm Optimized Hybrid Kernel LSSVM

    Directory of Open Access Journals (Sweden)

    Ji Li

    2016-10-01

    Full Text Available A piezo-resistive pressure sensor is made of silicon, the nature of which is considerably influenced by ambient temperature. The effect of temperature should be eliminated during the working period in expectation of linear output. To deal with this issue, an approach consists of a hybrid kernel Least Squares Support Vector Machine (LSSVM optimized by a chaotic ions motion algorithm presented. To achieve the learning and generalization for excellent performance, a hybrid kernel function, constructed by a local kernel as Radial Basis Function (RBF kernel, and a global kernel as polynomial kernel is incorporated into the Least Squares Support Vector Machine. The chaotic ions motion algorithm is introduced to find the best hyper-parameters of the Least Squares Support Vector Machine. The temperature data from a calibration experiment is conducted to validate the proposed method. With attention on algorithm robustness and engineering applications, the compensation result shows the proposed scheme outperforms other compared methods on several performance measures as maximum absolute relative error, minimum absolute relative error mean and variance of the averaged value on fifty runs. Furthermore, the proposed temperature compensation approach lays a foundation for more extensive research.

  3. A Temperature Compensation Method for Piezo-Resistive Pressure Sensor Utilizing Chaotic Ions Motion Algorithm Optimized Hybrid Kernel LSSVM.

    Science.gov (United States)

    Li, Ji; Hu, Guoqing; Zhou, Yonghong; Zou, Chong; Peng, Wei; Alam Sm, Jahangir

    2016-10-14

    A piezo-resistive pressure sensor is made of silicon, the nature of which is considerably influenced by ambient temperature. The effect of temperature should be eliminated during the working period in expectation of linear output. To deal with this issue, an approach consists of a hybrid kernel Least Squares Support Vector Machine (LSSVM) optimized by a chaotic ions motion algorithm presented. To achieve the learning and generalization for excellent performance, a hybrid kernel function, constructed by a local kernel as Radial Basis Function (RBF) kernel, and a global kernel as polynomial kernel is incorporated into the Least Squares Support Vector Machine. The chaotic ions motion algorithm is introduced to find the best hyper-parameters of the Least Squares Support Vector Machine. The temperature data from a calibration experiment is conducted to validate the proposed method. With attention on algorithm robustness and engineering applications, the compensation result shows the proposed scheme outperforms other compared methods on several performance measures as maximum absolute relative error, minimum absolute relative error mean and variance of the averaged value on fifty runs. Furthermore, the proposed temperature compensation approach lays a foundation for more extensive research.

  4. The collapsed cone algorithm for (192)Ir dosimetry using phantom-size adaptive multiple-scatter point kernels.

    Science.gov (United States)

    Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc

    2015-07-07

    The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient

  5. Classification of maize kernels using NIR hyperspectral imaging

    DEFF Research Database (Denmark)

    Williams, Paul; Kucheryavskiy, Sergey V.

    2016-01-01

    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

  6. Ideal gas scattering kernel for energy dependent cross-sections

    International Nuclear Information System (INIS)

    Rothenstein, W.; Dagan, R.

    1998-01-01

    A third, and final, paper on the calculation of the joint kernel for neutron scattering by an ideal gas in thermal agitation is presented, when the scattering cross-section is energy dependent. The kernel is a function of the neutron energy after scattering, and of the cosine of the scattering angle, as in the case of the ideal gas kernel for a constant bound atom scattering cross-section. The final expression is suitable for numerical calculations

  7. Embedded real-time operating system micro kernel design

    Science.gov (United States)

    Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

    2005-12-01

    Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

  8. An SVM model with hybrid kernels for hydrological time series

    Science.gov (United States)

    Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

    2017-12-01

    Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

  9. Influence of wheat kernel physical properties on the pulverizing process.

    Science.gov (United States)

    Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

    2014-10-01

    The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

  10. Dose point kernels for beta-emitting radioisotopes

    International Nuclear Information System (INIS)

    Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.

    1986-01-01

    Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables

  11. Hadamard Kernel SVM with applications for breast cancer outcome predictions.

    Science.gov (United States)

    Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

    2017-12-21

    Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

  12. Parameter optimization in the regularized kernel minimum noise fraction transformation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2012-01-01

    Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....

  13. Fundamental Studies of Ignition Process in Large Natural Gas Engines Using Laser Spark Ignition

    Energy Technology Data Exchange (ETDEWEB)

    Azer Yalin; Bryan Willson

    2008-06-30

    Past research has shown that laser ignition provides a potential means to reduce emissions and improve engine efficiency of gas-fired engines to meet longer-term DOE ARES (Advanced Reciprocating Engine Systems) targets. Despite the potential advantages of laser ignition, the technology is not seeing practical or commercial use. A major impediment in this regard has been the 'open-path' beam delivery used in much of the past research. This mode of delivery is not considered industrially practical owing to safety factors, as well as susceptibility to vibrations, thermal effects etc. The overall goal of our project has been to develop technologies and approaches for practical laser ignition systems. To this end, we are pursuing fiber optically coupled laser ignition system and multiplexing methods for multiple cylinder engine operation. This report summarizes our progress in this regard. A partial summary of our progress includes: development of a figure of merit to guide fiber selection, identification of hollow-core fibers as a potential means of fiber delivery, demonstration of bench-top sparking through hollow-core fibers, single-cylinder engine operation with fiber delivered laser ignition, demonstration of bench-top multiplexing, dual-cylinder engine operation via multiplexed fiber delivered laser ignition, and sparking with fiber lasers. To the best of our knowledge, each of these accomplishments was a first.

  14. THE EFFECT OF VARIABLE COMPRESSION RATIO ON FUEL CONSUMPTION IN SPARK IGNITION ENGINES

    Directory of Open Access Journals (Sweden)

    Yakup SEKMEN

    2002-02-01

    Full Text Available Due to lack of energy sources in the world, we are obliged to use our current energy sources in the most efficient way. Therefore, in the automotive industry, research works to manufacture more economic cars in terms of fuelconsumption and environmental friendly cars, at the same time satisfying the required performance have been intensively increasing. Some positive results have been obtained by the studies, aimed to change the compression ratio according to the operating conditions of engine. In spark ignition engines in order to improve the combustion efficiency, fuel economy and exhaust emission in the partial loads, the compression ratio must be increased; but, under the high load and low speed conditions to prevent probable knock and hard running compression ratio must be decreased slightly. In this paper, various research works on the variable compression ratio with spark ignition engines, the effects on fuel economy, power output and thermal efficiency have been investigated. According to the results of the experiments performed with engines having variable compression ratio under the partial and mid-load conditions, an increase in engine power, a decrease in fuel consumption, particularly in partial loads up to 30 percent of fuel economy, and also severe reductions of some exhaust emission values were determined.

  15. Analysis of Advanced Fuel Kernel Technology

    International Nuclear Information System (INIS)

    Oh, Seung Chul; Jeong, Kyung Chai; Kim, Yeon Ku; Kim, Young Min; Kim, Woong Ki; Lee, Young Woo; Cho, Moon Sung

    2010-03-01

    The reference fuel for prismatic reactor concepts is based on use of an LEU UCO TRISO fissile particle. This fuel form was selected in the early 1980s for large high-temperature gas-cooled reactor (HTGR) concepts using LEU, and the selection was reconfirmed for modular designs in the mid-1980s. Limited existing irradiation data on LEU UCO TRISO fuel indicate the need for a substantial improvement in performance with regard to in-pile gaseous fission product release. Existing accident testing data on LEU UCO TRISO fuel are extremely limited, but it is generally expected that performance would be similar to that of LEU UO 2 TRISO fuel if performance under irradiation were successfully improved. Initial HTGR fuel technology was based on carbide fuel forms. In the early 1980s, as HTGR technology was transitioning from high-enriched uranium (HEU) fuel to LEU fuel. An initial effort focused on LEU prismatic design for large HTGRs resulted in the selection of UCO kernels for the fissile particles and thorium oxide (ThO 2 ) for the fertile particles. The primary reason for selection of the UCO kernel over UO 2 was reduced CO pressure, allowing higher burnup for equivalent coating thicknesses and reduced potential for kernel migration, an important failure mechanism in earlier fuels. A subsequent assessment in the mid-1980s considering modular HTGR concepts again reached agreement on UCO for the fissile particle for a prismatic design. In the early 1990s, plant cost-reduction studies led to a decision to change the fertile material from thorium to natural uranium, primarily because of a lower long-term decay heat level for the natural uranium fissile particles. Ongoing economic optimization in combination with anticipated capabilities of the UCO particles resulted in peak fissile particle burnup projection of 26% FIMA in steam cycle and gas turbine concepts

  16. Magnetic field influence on substructure formed by electric spark treatment

    International Nuclear Information System (INIS)

    Reza Rahbari, G.; Ivanov, A.N.

    1996-01-01

    The substructure of surface layer (about 10 microns thick) has been studied by x-ray line broadening technique in the samples of plain carbon steel (0.45%C) after electric spark doping with and without magnetic field (MF). The applied spark pulse energy was 0.12 J and MF induction varied from 0 to 0.08 T. The electrode material was the same as that of the treated sample. It has been observed that the MF reduces the tensile residual surface stresses from 660 ± 15MPa (no MF) to 260 ± 15MPa (B=0.053 T). The analysis of x-ray line broadening has revealed only the existence of microstrains, which are dependent of the MF magnitude. The microstrains have been related to the randomly distributed dislocation with the density of about 3x10 sup 11 cm sup -2

  17. 100 kV reliable accurately-synchronized spark gap

    International Nuclear Information System (INIS)

    Bosamykin, V.S.; Gerasimov, A.I.; Zenkov, D.I.

    1987-01-01

    100 kV three-electrode spark gap filled with 40% SF 6 +60% N 2 mixture under the pressure of ∼ 1 MPa, which has spread Δt ≤ ± 5 ns of operating time delay in the range of 10 4 triggerings and commutation energy of 2.5 kJ, providing electric strength is 100%, is described; at 10 kJ Δt is less than ± 10 ns for 10 3 triggerings. Parallel connection of 16 groups, each consisting of 5 spark gaps with series connection, electric strength being 100%, in the pulse charging unit of Arkadiev-Marx generator being in operation for several years manifested their high efficiency; mutual group spread is ≤ ± 15 ns

  18. Striated filamentary sparks produced by a CO2 TEA laser

    International Nuclear Information System (INIS)

    Schmieder, R.W.

    1979-01-01

    Sparks in the form of long, thin filaments having quasi-periodic longitudinal light and dark regions (striations) in time-integrated images have been ovserved in various gases using a CO 2 TEA laser. Typically, a 50-mJ pulse will produce a filament 1 cm long and 130 μm in diameter, with more than 150 striations spaced 50 μm apart in atmospheric air. Each striation is associated with the formation of a plasma region by one pulse in train of pulses from the mode-locked laser, and the filament results from the formation of successive (nearly identical) region, each displaced from the previous one toward the laser. The possible use of these sparks as a light source in diagnostics is noted

  19. Large area spark counters with fine time and position resolution

    International Nuclear Information System (INIS)

    Ogawa, A.; Atwood, W.B.; Fujiwara, N.; Pestov, Yu.N.; Sugahara, R.

    1983-10-01

    Spark counters trace their history back over three decades but have been used in only a limited number of experiments. The key properties of these devices include their capability of precision timing (at the sub 100 ps level) and of measuring the position of the charged particle to high accuracy. At SLAC we have undertaken a program to develop these devices for use in high energy physics experiments involving large detectors. A spark counter of size 1.2 m x 0.1 m has been constructed and has been operating continuously in our test setup for several months. In this talk I will discuss some details of its construction and its properties as a particle detector. 14 references

  20. Learning Rotation for Kernel Correlation Filter

    KAUST Repository

    Hamdi, Abdullah

    2017-08-11

    Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.

  1. Fixed kernel regression for voltammogram feature extraction

    International Nuclear Information System (INIS)

    Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N

    2009-01-01

    Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals

  2. Reciprocity relation for multichannel coupling kernels

    International Nuclear Information System (INIS)

    Cotanch, S.R.; Satchler, G.R.

    1981-01-01

    Assuming time-reversal invariance of the many-body Hamiltonian, it is proven that the kernels in a general coupled-channels formulation are symmetric, to within a specified spin-dependent phase, under the interchange of channel labels and coordinates. The theorem is valid for both Hermitian and suitably chosen non-Hermitian Hamiltonians which contain complex effective interactions. While of direct practical consequence for nuclear rearrangement reactions, the reciprocity relation is also appropriate for other areas of physics which involve coupled-channels analysis

  3. Wheat kernel dimensions: how do they contribute to kernel weight at ...

    Indian Academy of Sciences (India)

    2011-12-02

    Dec 2, 2011 ... yield components, is greatly influenced by kernel dimensions. (KD), such as ..... six linkage gaps, and it covered 3010.70 cM of the whole genome with an ...... Ersoz E. et al. 2009 The Genetic architecture of maize flowering.

  4. Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

    DEFF Research Database (Denmark)

    Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.

    2013-01-01

    correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...

  5. CMS Analysis and Data Reduction with Apache Spark

    Energy Technology Data Exchange (ETDEWEB)

    Gutsche, Oliver [Fermilab; Canali, Luca [CERN; Cremer, Illia [Magnetic Corp., Waltham; Cremonesi, Matteo [Fermilab; Elmer, Peter [Princeton U.; Fisk, Ian [Flatiron Inst., New York; Girone, Maria [CERN; Jayatilaka, Bo [Fermilab; Kowalkowski, Jim [Fermilab; Khristenko, Viktor [CERN; Motesnitsalis, Evangelos [CERN; Pivarski, Jim [Princeton U.; Sehrish, Saba [Fermilab; Surdy, Kacper [CERN; Svyatkovskiy, Alexey [Princeton U.

    2017-10-31

    Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems for distributed data processing, collectively called "Big Data" technologies have emerged from industry and open source projects to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and tools, promising a fresh look at analysis of very large datasets that could potentially reduce the time-to-physics with increased interactivity. Moreover these new tools are typically actively developed by large communities, often profiting of industry resources, and under open source licensing. These factors result in a boost for adoption and maturity of the tools and for the communities supporting them, at the same time helping in reducing the cost of ownership for the end-users. In this talk, we are presenting studies of using Apache Spark for end user data analysis. We are studying the HEP analysis workflow separated into two thrusts: the reduction of centrally produced experiment datasets and the end-analysis up to the publication plot. Studying the first thrust, CMS is working together with CERN openlab and Intel on the CMS Big Data Reduction Facility. The goal is to reduce 1 PB of official CMS data to 1 TB of ntuple output for analysis. We are presenting the progress of this 2-year project with first results of scaling up Spark-based HEP analysis. Studying the second thrust, we are presenting studies on using Apache Spark for a CMS Dark Matter physics search, comparing Spark's feasibility, usability and performance to the ROOT-based analysis.

  6. Loits skandaalitses gaalal. Sparks Rabarockil. Pärimusmuusika Ait

    Index Scriptorium Estoniae

    2008-01-01

    Pärnu Kontserdimajas Eesti muusikaauhindade galal üle astunud rockansambel Loits röövis koostöös kultuskirjaniku Sven Kivisildnikuga aasta metal/punk-artisti auhinna, mis pidi minema industrial-metal-artistile Finish Me Off. Ameerika bänd Sparks 14. juunil Järvakandis Rabarockil. Viljandis Tasuja pst.6 avati Eesti Pärimusmuusika Keskuse uus kodu - Pärimusmuusika Ait

  7. effect of gasket of varying thickness on spark ignition engines

    African Journals Online (AJOL)

    DJFLEX

    In the study of Toyota, In-line, 4 cylinders, spark ignition engine using gaskets of varying thicknesses. (1.75mm, 3.5mm, 5.25mm, 7mm and 8.75mm) between the cylinder head and the engine block, the performance characteristics of the engine was investigated via the effect of engine speed on brake power, brake thermal ...

  8. High repetition rate burst-mode spark gap

    International Nuclear Information System (INIS)

    Faltens, A.; Reginato, L.; Hester, R.; Chesterman, A.; Cook, E.; Yokota, T.; Dexter, W.

    1978-01-01

    Results are presented on the design and testing of a pressurized gas blown spark gap switch capable of high repetition rates in a burst mode of operation. The switch parameters which have been achieved are as follows: 220-kV, 42-kA, a five pulse burst at 1-kHz, 12-ns risetime, 2-ns jitter at a pulse width of 50-ns

  9. Modeling of the Inductance of a Blumlein Circuit Spark Gap

    International Nuclear Information System (INIS)

    Aboites, V; Rendón, L; Hernández, A I; Valdés, E

    2015-01-01

    In this paper we present an analysis of the time-varying inductance in the spark gap of a Blumlein circuit. We assume several mathematical expressions to describe the inductance and compare theoretical and computational calculations with experimental results. The time-varying inductance is approximated by a constant, a straight line and two parables which differ in their concavity. This is the first time to our knowledge, in which the time-varying ignition inductance of a nitrogen laser is modeled

  10. SparkJet characterizations in quiescent and supersonic flowfields

    Science.gov (United States)

    Emerick, T.; Ali, M. Y.; Foster, C.; Alvi, F. S.; Popkin, S.

    2014-12-01

    The aerodynamic community has studied active flow control actuators for some time, and developments have led to a wide variety of devices with various features and operating mechanisms. The design requirements for a practical actuator used for active flow control include reliable operation, requisite frequency and amplitude modulation capabilities, and a reasonable lifespan while maintaining minimal cost and design complexity. An active flow control device called the SparkJet actuator has been developed for high-speed flight control and incorporates no mechanical/moving parts, zero net mass flux capabilities and the ability to tune the operating frequency and momentum throughput. This actuator utilizes electrical power to deliver high-momentum flow with a very fast response time. The SparkJet actuator was characterized on the benchtop using a laser-based microschlieren visualization technique and maximum blast wave and jet front velocities of ~400 and ~310 m/s were, respectively, measured in the flowfield. An increase in jet front velocity from 240 to 310 m/s during subatmospheric (60 kPa) testing reveals that the actuator may have greater control authority at lower ambient pressures, which correspond to high-altitude flight conditions for air vehicles. A SparkJet array was integrated into a flat plate and tested in a Mach 1.5 crossflow. Phase-conditioned shadowgraph results revealed a maximum flow deflection angle of 5° created by the SparkJet 275 µs after the actuator was triggered in single-shot mode. Burst mode operation of frequencies up to 700 Hz revealed similar results during wind tunnel testing. Following these tests, the actuator trigger mechanism was improved and the ability of the actuator to be discharged in burst mode at a frequency of 1 kHz was achieved.

  11. The time response function of spark counters and RPCs

    International Nuclear Information System (INIS)

    Gobbi, A.; Mangiarotti, A.

    2003-01-01

    The fluctuation theory for the avalanche growth with and without space charge effects is briefly summarized and compared to a broad field of applications. These include spark counters as well as timing and trigger RPCs operated in avalanche mode. A large domain in electrical field strength, pressure, gap size and gas mixture type is covered. A reasonable agreement with the experiment is observed, giving confidence on the validity of both assumptions and treatment of the theory

  12. Production of uranium-molybdenum particles by spark-erosion

    International Nuclear Information System (INIS)

    Cabanillas, E.D.; Lopez, M.; Pasqualini, E.E.; Cirilo Lombardo, D.J.

    2004-01-01

    With the spark-erosion method we have produced spheroidal particles of an uranium-molybdenum alloy using pure water as dielectric. The particles were characterized by optical metallography, scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction. Mostly spherical particles of UO 2 with a distinctive size distribution with peaks centered at 70 and 10 μm were obtained. The particles have central inclusions of U and Mo compounds

  13. Production of uranium-molybdenum particles by spark-erosion

    Energy Technology Data Exchange (ETDEWEB)

    Cabanillas, E.D. E-mail: cabanill@cnea.gov.ar; Lopez, M.; Pasqualini, E.E.; Cirilo Lombardo, D.J

    2004-01-01

    With the spark-erosion method we have produced spheroidal particles of an uranium-molybdenum alloy using pure water as dielectric. The particles were characterized by optical metallography, scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction. Mostly spherical particles of UO{sub 2} with a distinctive size distribution with peaks centered at 70 and 10 {mu}m were obtained. The particles have central inclusions of U and Mo compounds.

  14. Particular bi-fuel application of spark ignition engines

    Science.gov (United States)

    Raţiu, S.; Alexa, V.; Kiss, I.

    2016-02-01

    This paper presents a comparative test concerning the operation of a spark-ignition engine, make: Dacia 1300, model: 810.99, fuelled alternatively with gasoline and LPG (Liquefied Petroleum Gas). The tests carried out show, on the one hand, the maintenance of power and torque performances in both engine fuelling cases, for all the engine operation regimes, and, on the other hand, a considerable decrease in CO and HC emissions when using poor mixtures related to LPG fuelling.

  15. Gas temperature of capacitance spark discharge in air

    International Nuclear Information System (INIS)

    Ono, Ryo; Nifuku, Masaharu; Fujiwara, Shuzo; Horiguchi, Sadashige; Oda, Tetsuji

    2005-01-01

    Capacitance spark discharge has been widely used for studying the ignition of flammable gas caused by electrostatic discharge. In the present study, the gas temperature of capacitance spark discharge is measured. The gas temperature is an important factor in understanding the electrostatic ignition process because it influences the reaction rate of ignition. Spark discharge is generated in air with a pulse duration shorter than 100 ns. The discharge energy is set to 0.03-1 mJ. The rotational and vibrational temperatures of the N 2 molecule are measured using the emission spectrum of the N 2 second positive system. The rotational and vibrational temperatures are estimated to be 500 and 5000 K, respectively, which are independent of the discharge energy. This result indicates that most of the electron energy is consumed in the excitation of vibrational levels of molecules rather than the heating of the gas. The gas temperature after discharge is also measured by laser-induced fluorescence of OH radicals. It is shown that the gas temperature increases after discharge and reaches approximately 1000 K at 3 μs after discharge. Then the temperature decreases at a rate in the range of 8-35 K/μs depending on the discharge energy

  16. Spark igniter having precious metal ground electrode inserts

    International Nuclear Information System (INIS)

    Ryan, N.A.

    1988-01-01

    This patent describes an igniter comprising a shell of a shell metal alloy which is resistant to spark erosion and corrosion, the shell having a firing end which terminates at its lower end in an annular ring, an insulator sealed within the metal shell and having a central bore and a surface extending inwardly toward the bore from the annular ring, a center electrode sealed within the bore of the insulator and having a firing end which is in spark gap relation with the annular ring of the shell and so positioned that a spark discharge between the firing end and the annular ring occurs along the inwardly extending surface of the insulator, and a plurality of oxidation and erosion resistant inserts, each of the inserts comprising a body of a metal selected from the group consisting of iridium, osmium, ruthenium, rhodium, platinum, and tungsten or an alloy or a ductile alloy of one of the foregoing metals, each of the bodies being embedded within a matching opening which extends from the exterior of the shell through the annular ring, being bonded to the shell

  17. River water remediation using pulsed corona, pulsed spark or ozonation

    Energy Technology Data Exchange (ETDEWEB)

    Izdebski, T.; Dors, M. [Polish Academy of Sciences, Szewalski Inst. of Fluid Flow Machiney, Fiszera (Poland). Centre for Plasma and Laser Engineering; Mizeraczyk, J. [Polish Academy of Sciences, Szewalski Inst. of Fluid Flow Machiney, Fiszera (Poland). Centre for Plasma and Laser Engineering; Gdynia Maritime Univ., Morska (Poland). Dept. of Marine Electronics

    2010-07-01

    The most common reason for epidemic formation is the pollution of surface and drinking water by wastewater bacteria. Pathogenic microorganisms that form the largest part of this are fecal bacteria, such as escherichia coli (E. coli). Wastewater treatment plants reduce the amount of the fecal bacteria by 1-3 orders of magnitude, depending on the initial number of bacteria. There is a lack of data on waste and drinking water purification by the electrohydraulic discharges method, which causes the destruction and inactivation of viruses, yeast, and bacteria. This paper investigated river water cleaning from microorganisms using pulsed corona, spark discharge and ozonization. The paper discussed the experimental setup and results. It was concluded that ozonization is the most efficient method of water disinfection as compared with pulsed spark and pulsed corona discharges. The pulsed spark discharge in water was capable of killing all microorganism similarly to ozonization, but with much lower energy efficiency. The pulsed corona discharge was found to be the less effective method of water disinfection. 21 refs., 4 figs.

  18. Infrared small target detection with kernel Fukunaga Koontz transform

    Science.gov (United States)

    Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

    2007-09-01

    The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

  19. Sparking connections: An exploration of adolescent girls' relationships with science

    Science.gov (United States)

    Wheeler, Kathryn A.

    Despite progress in narrowing the gender gap, fewer women than men pursue science careers. Adolescence is a critical age when girls' science interest is sparked or smothered. Prior research provides data on who drops out of the "science pipeline" and when, but few studies examine why and how girls disconnect from science. This thesis is an in-depth exploratory study of adolescent girls' relationships with science based on a series of interviews with four middle-class Caucasian girls---two from public schools, two homeschooled. The girls' stones about their experiences with, feelings about, and perspectives on science, the science process, and their science learning environments are examined with a theoretical and analytic approach grounded in relational psychology. The potential link between girls' voices and their involvement in science is investigated. Results indicate that girls' relationships with science are multitiered. Science is engaging and familiar in the sense that girls are curious about the world, enjoy learning about scientific phenomena, and informally use science in their everyday fives. However, the girls in this study differentiated between the science they do and the field of science, which they view as a mostly male endeavor (often despite real life experiences to the contrary) that uses rather rigid methods to investigate questions of limited scope and interest. In essence, how these girls defined science defined their relationship with science: those with narrow conceptions of science felt distant from it. Adolescent girls' decreased involvement in science activities may be a relational act---a move away from a patriarchical process, pedagogy, and institution that does not resonate with their experiences, questions, and learning styles. Girls often feel like outsiders to science; they resist considering science careers when they have concerns that implicitly or explicitly, doing so would involve sacrificing their knowledge, creativity, or

  20. Kernel learning at the first level of inference.

    Science.gov (United States)

    Cawley, Gavin C; Talbot, Nicola L C

    2014-05-01

    Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Spirituality in business: Sparks from the Anvil

    Directory of Open Access Journals (Sweden)

    B. Mahadevan

    2013-06-01

    Full Text Available The economic crises in the recent past have led to a renewed interest in exploring the role of spirituality in business management. However there are several challenges in understanding what “spirituality” means in an operational sense of business management. This article first traces the research in the area of spirituality as applied to business and in the second part, reports on the beliefs of Suresh B. Hundre, Chairman and MD of Polyhydron Pvt. Ltd, Belgaum, India, as practised in Polyhydron, a company known for its ethical management, and where the concept of “Business Ashrama” integrates spirituality into business.

  2. The Kernel Estimation in Biosystems Engineering

    Directory of Open Access Journals (Sweden)

    Esperanza Ayuga Téllez

    2008-04-01

    Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

  3. Consistent Valuation across Curves Using Pricing Kernels

    Directory of Open Access Journals (Sweden)

    Andrea Macrina

    2018-03-01

    Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

  4. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

    Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

    Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

  5. Pareto-path multitask multiple kernel learning.

    Science.gov (United States)

    Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2015-01-01

    A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

  6. Formal truncations of connected kernel equations

    International Nuclear Information System (INIS)

    Dixon, R.M.

    1977-01-01

    The Connected Kernel Equations (CKE) of Alt, Grassberger and Sandhas (AGS); Kouri, Levin and Tobocman (KLT); and Bencze, Redish and Sloan (BRS) are compared against reaction theory criteria after formal channel space and/or operator truncations have been introduced. The Channel Coupling Class concept is used to study the structure of these CKE's. The related wave function formalism of Sandhas, of L'Huillier, Redish and Tandy and of Kouri, Krueger and Levin are also presented. New N-body connected kernel equations which are generalizations of the Lovelace three-body equations are derived. A method for systematically constructing fewer body models from the N-body BRS and generalized Lovelace (GL) equations is developed. The formally truncated AGS, BRS, KLT and GL equations are analyzed by employing the criteria of reciprocity and two-cluster unitarity. Reciprocity considerations suggest that formal truncations of BRS, KLT and GL equations can lead to reciprocity-violating results. This study suggests that atomic problems should employ three-cluster connected truncations and that the two-cluster connected truncations should be a useful starting point for nuclear systems

  7. Scientific Computing Kernels on the Cell Processor

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

    2007-04-04

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  8. Delimiting areas of endemism through kernel interpolation.

    Science.gov (United States)

    Oliveira, Ubirajara; Brescovit, Antonio D; Santos, Adalberto J

    2015-01-01

    We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  9. Delimiting areas of endemism through kernel interpolation.

    Directory of Open Access Journals (Sweden)

    Ubirajara Oliveira

    Full Text Available We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE, based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  10. Bioconversions of Palm Kernel Cake and Rice Bran Mixtures by Trichoderma viride Toward Nutritional Contents

    Directory of Open Access Journals (Sweden)

    Yana Sukaryana

    2010-12-01

    Full Text Available The objective of the research is to examine the mixtures of palm kernel cake and rice bran of fermented by Trichoderma viride. Completely randomized design in factorial pattern 4 x 4 was used in this experiment. factor I is the doses of inoculums; D1 = 0%, D2 =  0,1% , D3 =  0,2%, D4 =  0,3%, and  complement factor II is mixtures of palm kernel cake and rice bran : T1=20:80% ; T2=40:60% ; T3=60:40% ; T4=80:20%. The treatment each of three replicate. Fermentation was conducted at temperature 28 oC as long as 9 days. Determining the best of the mixtures be based on the crude protein increased and the crude fibre decreased. The results showed that the combination of product mix is the best fermentation inoculums doses 0.3% in mixture of palm kernel cake and rice bran ; 80%: 20%, which produces dry matter of 88,12%, crude protein 17.34%, ether extract 5,35%, crude fibre 23.67%, and ash 6.43%. When compared with a mixture of palm kernel cake and rice bran; 80%: 20% without of fermentation is crude protein increase 29.58% and crude fibre decreased 22.53%.

  11. A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.

    Science.gov (United States)

    Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei

    2016-05-09

    Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

  12. A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram

    Directory of Open Access Journals (Sweden)

    Chung Kit Wu

    2016-05-01

    Full Text Available Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG is a proven biosignal that accurately and simultaneously reflects human’s biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

  13. Biocompatibility assessment of spark plasma-sintered alumina-titanium cermets.

    Science.gov (United States)

    Guzman, Rodrigo; Fernandez-García, Elisa; Gutierrez-Gonzalez, Carlos F; Fernandez, Adolfo; Lopez-Lacomba, Jose Luis; Lopez-Esteban, Sonia

    2016-01-01

    Alumina-titanium materials (cermets) of enhanced mechanical properties have been lately developed. In this work, physical properties such as electrical conductivity and the crystalline phases in the bulk material are evaluated. As these new cermets manufactured by spark plasma sintering may have potential application for hard tissue replacements, their biocompatibility needs to be evaluated. Thus, this research aims to study the cytocompatibility of a novel alumina-titanium (25 vol. % Ti) cermet compared to its pure counterpart, the spark plasma sintered alumina. The influence of the particular surface properties (chemical composition, roughness and wettability) on the pre-osteoblastic cell response is also analyzed. The material electrical resistance revealed that this cermet may be machined to any shape by electroerosion. The investigated specimens had a slightly undulated topography, with a roughness pattern that had similar morphology in all orientations (isotropic roughness) and a sub-micrometric average roughness. Differences in skewness that implied valley-like structures in the cermet and predominance of peaks in alumina were found. The cermet presented a higher surface hydrophilicity than alumina. Any cytotoxicity risk associated with the new materials or with the innovative manufacturing methodology was rejected. Proliferation and early-differentiation stages of osteoblasts were statistically improved on the composite. Thus, our results suggest that this new multifunctional cermet could improve current alumina-based biomedical devices for applications such as hip joint replacements. © The Author(s) 2015.

  14. Effects of solution volume on hydrogen production by pulsed spark discharge in ethanol solution

    Energy Technology Data Exchange (ETDEWEB)

    Xin, Y. B.; Sun, B., E-mail: sunb88@dlmu.edu.cn; Zhu, X. M.; Yan, Z. Y.; Liu, H.; Liu, Y. J. [College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China)

    2016-07-15

    Hydrogen production from ethanol solution (ethanol/water) by pulsed spark discharge was optimized by varying the volume of ethanol solution (liquid volume). Hydrogen yield was initially increased and then decreased with the increase in solution volume, which achieved 1.5 l/min with a solution volume of 500 ml. The characteristics of pulsed spark discharge were studied in this work; the results showed that the intensity of peak current, the rate of current rise, and energy efficiency of hydrogen production can be changed by varying the volume of ethanol solution. Meanwhile, the mechanism analysis of hydrogen production was accomplished by monitoring the process of hydrogen production and the state of free radicals. The analysis showed that decreasing the retention time of gas production and properly increasing the volume of ethanol solution can enhance the hydrogen yield. Through this research, a high-yield and large-scale method of hydrogen production can be achieved, which is more suitable for industrial application.

  15. Development of laser-induced fluorescence for precombustion diagnostics in spark-ignition engines

    Energy Technology Data Exchange (ETDEWEB)

    Neij, H.

    1998-11-01

    Motivated by a desire to understand and optimize combustion in spark-ignition (SI) engines, laser techniques have been developed for measurement of fuel and residual gas, respectively, in the precombustion mixture of an operating SI engine. The primary objective was to obtain two-dimensional, quantitative data in the vicinity of the spark gap at the time of ignition. A laser-induced fluorescence (LIF) technique was developed for fuel visualization in engine environments. Since the fluorescence signal from any commercial gasoline fuel would be unknown to its origin, with an unpredictable dependence on collisional partners, pressure and temperature, a non-fluorescent base fuel - isooctane - was used. For LIF detection, a fluorescent species was added to the fuel. An additive not commonly used in this context - 3-pentanone - was chosen based on its suitable vaporization characteristics and fluorescent properties. The LIF technique was applied to an optically accessible research engine. By calibration, the fluorescence signal from the additive was converted to fuel-to-air equivalence ratio ({phi}). The accuracy and precision of the acquired data were assessed. A statistical evaluation revealed that the spatially averaged equivalence ratio around the spark plug had a significant impact on the combustion event. The strong correlation between these two quantities suggested that the early combustion was sensitive to large-scale inhomogeneities in the precombustion mixture. A similar LIF technique, using acetone as a fluorescent additive in methane, was applied to a combustion cell for ion current evaluation. The local equivalence ratio around the spark gap at the time of ignition was extracted from LIF data. Useful relations were identified between different ion current parameters and the local equivalence ratio, although the impact of the flow field, the fuel type, and the electrode geometry were identified as areas for future research. A novel fuel - dimethyl ether (DME

  16. Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  −  t SPARKS)

    International Nuclear Information System (INIS)

    Park, Suhyung; Park, Jaeseok

    2015-01-01

    Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  −  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  −  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  −  t SPARKS incorporates Kalman-smoother self-calibration in k  −  t space and sparse signal recovery in x  −   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  −  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  −  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors. (paper)

  17. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically

  18. Replacement Value of Palm Kernel Meal for Maize on Carcass ...

    African Journals Online (AJOL)

    This study was conducted to evaluate the effect of replacing maize with palm kernel meal on nutrient composition, fatty acid profile and sensory qualities of the meat of turkeys fed the dietary treatments. Six dietary treatments were formulated using palm kernel meal to replace maize at 0, 20, 40, 60, 80 and 100 percent.

  19. Effect of Palm Kernel Cake Replacement and Enzyme ...

    African Journals Online (AJOL)

    A feeding trial which lasted for twelve weeks was conducted to study the performance of finisher pigs fed five different levels of palm kernel cake replacement for maize (0%, 40%, 40%, 60%, 60%) in a maize-palm kernel cake based ration with or without enzyme supplementation. It was a completely randomized design ...

  20. Capturing option anomalies with a variance-dependent pricing kernel

    NARCIS (Netherlands)

    Christoffersen, P.; Heston, S.; Jacobs, K.

    2013-01-01

    We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

  1. Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan

    This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi...

  2. Commutators of Integral Operators with Variable Kernels on Hardy ...

    Indian Academy of Sciences (India)

    Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.

  3. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  4. Kernel Function Tuning for Single-Layer Neural Networks

    Czech Academy of Sciences Publication Activity Database

    Vidnerová, Petra; Neruda, Roman

    -, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/

  5. Geodesic exponential kernels: When Curvature and Linearity Conflict

    DEFF Research Database (Denmark)

    Feragen, Aase; Lauze, François; Hauberg, Søren

    2015-01-01

    manifold, the geodesic Gaussian kernel is only positive definite if the Riemannian manifold is Euclidean. This implies that any attempt to design geodesic Gaussian kernels on curved Riemannian manifolds is futile. However, we show that for spaces with conditionally negative definite distances the geodesic...

  6. Denoising by semi-supervised kernel PCA preimaging

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

    2014-01-01

    Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...

  7. Design and construction of palm kernel cracking and separation ...

    African Journals Online (AJOL)

    Design and construction of palm kernel cracking and separation machines. ... Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Design and construction of palm kernel cracking and separation machines. JO Nordiana, K ...

  8. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  9. Genetic relationship between plant growth, shoot and kernel sizes in ...

    African Journals Online (AJOL)

    Maize (Zea mays L.) ear vascular tissue transports nutrients that contribute to grain yield. To assess kernel heritabilities that govern ear development and plant growth, field studies were conducted to determine the combining abilities of parents that differed for kernel-size, grain-filling rates and shoot-size. Thirty two hybrids ...

  10. A relationship between Gel'fand-Levitan and Marchenko kernels

    International Nuclear Information System (INIS)

    Kirst, T.; Von Geramb, H.V.; Amos, K.A.

    1989-01-01

    An integral equation which relates the output kernels of the Gel'fand-Levitan and Marchenko inverse scattering equations is specified. Structural details of this integral equation are studied when the S-matrix is a rational function, and the output kernels are separable in terms of Bessel, Hankel and Jost solutions. 4 refs

  11. Boundary singularity of Poisson and harmonic Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2015-01-01

    Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170

  12. Oven-drying reduces ruminal starch degradation in maize kernels

    NARCIS (Netherlands)

    Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.

    2014-01-01

    The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels

  13. Real time kernel performance monitoring with SystemTap

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.

  14. Resolvent kernel for the Kohn Laplacian on Heisenberg groups

    Directory of Open Access Journals (Sweden)

    Neur Eddine Askour

    2002-07-01

    Full Text Available We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density. We conclude by obtaining the Green kernel for fractional powers of the Kohn Laplacian.

  15. Reproducing Kernels and Coherent States on Julia Sets

    Energy Technology Data Exchange (ETDEWEB)

    Thirulogasanthar, K., E-mail: santhar@cs.concordia.ca; Krzyzak, A. [Concordia University, Department of Computer Science and Software Engineering (Canada)], E-mail: krzyzak@cs.concordia.ca; Honnouvo, G. [Concordia University, Department of Mathematics and Statistics (Canada)], E-mail: g_honnouvo@yahoo.fr

    2007-11-15

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems.

  16. Reproducing Kernels and Coherent States on Julia Sets

    International Nuclear Information System (INIS)

    Thirulogasanthar, K.; Krzyzak, A.; Honnouvo, G.

    2007-01-01

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems

  17. A multi-scale kernel bundle for LDDMM

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard

    2011-01-01

    The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...

  18. Comparison of Kernel Equating and Item Response Theory Equating Methods

    Science.gov (United States)

    Meng, Yu

    2012-01-01

    The kernel method of test equating is a unified approach to test equating with some advantages over traditional equating methods. Therefore, it is important to evaluate in a comprehensive way the usefulness and appropriateness of the Kernel equating (KE) method, as well as its advantages and disadvantages compared with several popular item…

  19. An analysis of 1-D smoothed particle hydrodynamics kernels

    International Nuclear Information System (INIS)

    Fulk, D.A.; Quinn, D.W.

    1996-01-01

    In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

  20. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    Science.gov (United States)

    Häggström, Jenny; Wiberg, Marie

    2014-01-01

    The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

  1. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, Jeroen

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  2. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, J.

    2002-01-01

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  3. Spill sparks reform, leaves lasting scar

    International Nuclear Information System (INIS)

    Notthoff, A.

    1991-01-01

    Blackened shorelines, oil-soaked birds, and dying sea otters - images that riveted the Exxon Valdez oil spill on the public consciousness - also generated an outcry for action, Notthoff observes. No other spill caught the attention of the American public and prompted public-policy reform at the national, state, and local level like the Exxon Valdez, she says. Within two years of the accident, Congress had dusted off and passed oil-spill legislation that had been deadlocked for 10 years, and seven states had passed new oil-spill laws. The poor record of cleanup following the Exxon Valdez spill is due to the limits of technology, the physical conditions at the time of the accident, and a chronic inability to mobilize people and equipment under the chaotic circumstances that surround a major emergency, Notthoff says. In addition, there also was a failure to enforce existing response plans. Prevention is the best cure, and some of the new laws address this issue, she notes. They also tighten up requirements for response planning and encourage research into improved clean-up technology. What they fail to do Notthoff emphasizes, is seek to reduce tanker traffic by encouraging improved energy efficiency, conservation, and alternative energy technologies

  4. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi

    2014-01-01

    The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate this ambiguity between the different parameters. We use dynamic ray tracing to efficiently handle the expensive computational cost for 3-D anisotropic models. Ray tracing provides also the ray direction information necessary for conditioning the sensitivity kernels to handle anisotropy. The NMO velocity and η parameter kernels showed a maximum sensitivity for diving waves which results in a relevant choice of those parameters in wave equation tomography. The δ parameter kernel showed zero sensitivity; therefore it can serve as a secondary parameter to fit the amplitude in the acoustic anisotropic inversion. Considering the limited penetration depth of diving waves, migration velocity analysis based kernels are introduced to fix the depth ambiguity with reflections and compute sensitivity maps in the deeper parts of the model.

  5. Anatomically-aided PET reconstruction using the kernel method.

    Science.gov (United States)

    Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

    2016-09-21

    This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

  6. Open Problem: Kernel methods on manifolds and metric spaces

    DEFF Research Database (Denmark)

    Feragen, Aasa; Hauberg, Søren

    2016-01-01

    Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....

  7. Compactly Supported Basis Functions as Support Vector Kernels for Classification.

    Science.gov (United States)

    Wittek, Peter; Tan, Chew Lim

    2011-10-01

    Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.

  8. Sintering, consolidation, reaction and crystal growth by the spark plasma system (SPS)

    Energy Technology Data Exchange (ETDEWEB)

    Omori, M. [Tohoku Univ., Sendai (Japan). Inst. for Materials Research

    2000-08-15

    The graphite die set in spark plasma system (SPS) is heated by a pulse direct current. Weak plasma, discharge impact, electric field and electric current, which are based on this current, induce good effects on materials in the die. The surface films of aluminum and pure WC powders are ruptured by the spark plasma. Pure AlN powder is sintered without sintering additives in the electric field. The spark plasma leaves discharge patterns on insulators. Organic fibers are etched by the spark plasma. Thermosetting polyimide is consolidated by the spark plasma. Insoluble polymonomethylsilane is rearranged into the soluble one by the spark plasma. A single crystal of CoSb{sub 3} is grown from the compound powders in the electric field by slow heating. Coupled crystals of eutectic powder are connected with each other in the electric field. (orig.)

  9. Improved modeling of clinical data with kernel methods.

    Science.gov (United States)

    Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

    2012-02-01

    Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

  10. Intelligent Design of Metal Oxide Gas Sensor Arrays Using Reciprocal Kernel Support Vector Regression

    Science.gov (United States)

    Dougherty, Andrew W.

    Metal oxides are a staple of the sensor industry. The combination of their sensitivity to a number of gases, and the electrical nature of their sensing mechanism, make the particularly attractive in solid state devices. The high temperature stability of the ceramic material also make them ideal for detecting combustion byproducts where exhaust temperatures can be high. However, problems do exist with metal oxide sensors. They are not very selective as they all tend to be sensitive to a number of reduction and oxidation reactions on the oxide's surface. This makes sensors with large numbers of sensors interesting to study as a method for introducing orthogonality to the system. Also, the sensors tend to suffer from long term drift for a number of reasons. In this thesis I will develop a system for intelligently modeling metal oxide sensors and determining their suitability for use in large arrays designed to analyze exhaust gas streams. It will introduce prior knowledge of the metal oxide sensors' response mechanisms in order to produce a response function for each sensor from sparse training data. The system will use the same technique to model and remove any long term drift from the sensor response. It will also provide an efficient means for determining the orthogonality of the sensor to determine whether they are useful in gas sensing arrays. The system is based on least squares support vector regression using the reciprocal kernel. The reciprocal kernel is introduced along with a method of optimizing the free parameters of the reciprocal kernel support vector machine. The reciprocal kernel is shown to be simpler and to perform better than an earlier kernel, the modified reciprocal kernel. Least squares support vector regression is chosen as it uses all of the training points and an emphasis was placed throughout this research for extracting the maximum information from very sparse data. The reciprocal kernel is shown to be effective in modeling the sensor

  11. The Effects Foliar Application of Methanol at Different Growth Stages on Kernel Related Traits in Chickpea var. ILC 482

    Directory of Open Access Journals (Sweden)

    N. Naeimi,

    2013-12-01

    Full Text Available This research was conducted to evaluate the effects of foliar application of methanol on certain kernel related traits at different growth stages of pea var. ILC482 at the Research Station of Faculty of Agriculture in Islamic Azad University, Tabriz Branch in 2011. The study was conducted in split plot experiment based on Randomized Complete Block Design with three replications. Treatments were three levels methanol foliar application at different growth stages (vegetative, reproductive and foliar application at both two stages which considered as main factor, six levels of foliar application of methanol concentrations: (0 [control], 5, 10, 15, 20, 25, 30% as sub factor. Results showed that the interactions of methanol applications growth stages and its concentrations on grain number per plant, 100 kernel weight, grain yield, grain filing rate and harvest index were significantly different. Foliar application of methanol at reproductive stage decrease kernel related traits, but this application at both growth stages had positive effect on grain production and kernel related traits. This positive effect on number and 100 kernel weight were significant. The highest grain yield (2460 kg/ha was obtained by 20% concentration of methanol at both growth stages that increased grain yield above 13.5% compared to the control condition.

  12. RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

    Directory of Open Access Journals (Sweden)

    Božena Barić

    2015-06-01

    Full Text Available Walnut husk fly (WHF, Rhagoletis completa Cresson 1929 is an invasive species spreading quickly and damaging walnuts in Croatia and neighbouring countries. We researched distribution of this pest in the continental part of Croatia, flight dynamics in Međimurje County and its influence on quality of walnut kernels. CSALOMON®PALz traps were used for monitoring the spread and flight dynamics of R. completa. Weight and the protein content of kernels and the presence of mycotoxin contamination were measured. Walnut husk fly was found in six counties (Istria County: pest reconfirmation, Zagreb County, The City of Zagreb, Varaždin County, Međimurje County and Koprivnica-Križevci County. The presence of the fly was not confirmed on one site in Koprivnica-Križevci County (locality Ferdinandovac and in the eastern part of Croatia (Vukovar-Srijem County: Vinkovci locality. The flight dynamics showed rapid increase in number of adults only a year after the introduction into new area. The weight of infested kernels was 5.81% lower compared to not infested. Protein content was 14.04% in infested kernels and 17.31% in not infested kernels. There was no difference in mycotoxins levels. Additional researches on mycotoxin levels in stored nuts, ovipositional preferences of walnut husk fly and protection measures against this pest are suggested.

  13. Near-net shape manufacturing of miniature spur gears by wire spark erosion machining

    CERN Document Server

    Gupta, Kapil

    2016-01-01

    This work describes an experimental investigation with the aim to evaluate and establish wire spark erosion machining (WSEM) as a viable alternative for high quality miniature gear manufacturing. External spur type miniature brass (ASTM 858) gears with 12 teeth, 9.8 mm outside diameter and 5 mm face width were manufactured by WSEM. The research work was accomplished in four distinct experimental stages viz., preliminary, pilot, main and confirmation. The aim, scope and findings of each stage are progressively presented and discussed. In essence, the investigation found that it was possible to manufacture miniature gears to high quality by using WSEM. Gears up to DIN 5 quality with a good surface finish (1.2 µm average roughness) and satisfactory surface integrity were achieved. The results suggest that WSEM should be considered a viable alternative to conventional miniature gear manufacturing techniques and that in some instances it may even be superior. This work will prove useful to researchers and profess...

  14. A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

    Science.gov (United States)

    Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

    2015-09-01

    Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

  15. Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

    Science.gov (United States)

    Chen, Tianle; Zeng, Donglin

    2015-01-01

    Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

  16. A Comparative Study of Cycle Variability of Laser Plug Ignition vs Classical Spark Plug Ignition in Combustion Engines

    Science.gov (United States)

    Done, Bogdan

    2017-10-01

    Over the past 30 years numerous studies and laboratory experiments have researched the use of laser energy to ignite gas and fuel-air mixtures. The actual implementation of this laser application has still to be fully achieved in a commercial automotive application. Laser Plug Ignition as a replacement for Spark Plug Ignition in the internal combustion engines of automotive vehicles, offers several potential benefits such as extending lean burn capability, reducing the cyclic variability between combustion cycles and decreasing the total amount of ignition costs, and implicitly weight and energy requirements. The paper presents preliminary results of cycle variability study carried on a SI Engine equipped with laser Plug Ignition system. Versus classic ignition system, the use of the laser Plug Ignition system assures the reduction of the combustion process variability, reflected in the lower values of the coefficient of variability evaluated for indicated mean effective pressure, maximum pressure, maximum pressure angle and maximum pressure rise rate. The laser plug ignition system was mounted on an experimental spark ignition engine and tested at the regime of 90% load and 2800 rev/min, at dosage of λ=1.1. Compared to conventional spark plug, laser ignition assures the efficiency at lean dosage.

  17. Large-Eddy Simulations of Motored Flow and Combustion in a Homogeneous-Charge Spark-Ignition Engine

    Science.gov (United States)

    Shekhawat, Yajuvendra Singh

    Cycle-to-cycle variations (CCV) of flow and combustion in internal combustion engines (ICE) limit their fuel efficiency and emissions potential. Large-eddy simulation (LES) is the most practical simulation tool to understand the nature of these CCV. In this research, multi-cycle LES of a two-valve, four-stroke, spark-ignition optical engine has been performed for motored and fired operations. The LES mesh quality is assessed using a length scale resolution parameter and a energy resolution parameter. For the motored operation, two 50-consecutive-cycle LES with different turbulence models (Smagorinsky model and dynamic structure model) are compared with the experiment. The pressure comparison shows that the LES is able to capture the wave-dynamics in the intake and exhaust ports. The LES velocity fields are compared with particle-image velocimetry (PIV) measurements at three cutting planes. Based on the structure and magnitude indices, the dynamic structure model is somewhat better than the Smagorinsky model as far as the ensemble-averaged velocity fields are concerned. The CCV in the velocity fields is assessed by proper-orthogonal decomposition (POD). The POD analysis shows that LES is able to capture the level of CCV seen in the experiment. For the fired operation, two 60-cycle LES with different combustion models (thickened frame model and coherent frame model) are compared with experiment. The in-cylinder pressure and the apparent heat release rate comparison shows higher CCV for LES compared to the experiment, with the thickened frame model showing higher CCV than the coherent frame model. The correlation analysis for the LES using thickened frame model shows that the CCV in combustion/pressure is correlated with: the tumble at the intake valve closing, the resolved and subfilter-scale kinetic energy just before spark time, and the second POD mode (shear flow near spark gap) of the velocity fields just before spark time.

  18. Spark Ignition Characteristics of a L02/LCH4 Engine at Altitude Conditions

    Science.gov (United States)

    Kleinhenz, Julie; Sarmiento, Charles; Marshall, William

    2012-01-01

    The use of non-toxic propellants in future exploration vehicles would enable safer, more cost effective mission scenarios. One promising "green" alternative to existing hypergols is liquid methane/liquid oxygen. To demonstrate performance and prove feasibility of this propellant combination, a 100lbf LO2/LCH4 engine was developed and tested under the NASA Propulsion and Cryogenic Advanced Development (PCAD) project. Since high ignition energy is a perceived drawback of this propellant combination, a test program was performed to explore ignition performance and reliability versus delivered spark energy. The sensitivity of ignition to spark timing and repetition rate was also examined. Three different exciter units were used with the engine s augmented (torch) igniter. Propellant temperature was also varied within the liquid range. Captured waveforms indicated spark behavior in hot fire conditions was inconsistent compared to the well-behaved dry sparks (in quiescent, room air). The escalating pressure and flow environment increases spark impedance and may at some point compromise an exciter s ability to deliver a spark. Reduced spark energies of these sparks result in more erratic ignitions and adversely affect ignition probability. The timing of the sparks relative to the pressure/flow conditions also impacted the probability of ignition. Sparks occurring early in the flow could trigger ignition with energies as low as 1-6mJ, though multiple, similarly timed sparks of 55-75mJ were required for reliable ignition. An optimum time interval for spark application and ignition coincided with propellant introduction to the igniter and engine. Shifts of ignition timing were manifested by changes in the characteristics of the resulting ignition.

  19. Spark Ignition Characteristics of a LO2/LCH4 Engine at Altitude Conditions

    Science.gov (United States)

    Kleinhenz, Julie; Sarmiento, Charles; Marshall, William

    2012-01-01

    The use of non-toxic propellants in future exploration vehicles would enable safer, more cost effective mission scenarios. One promising "green" alternative to existing hypergols is liquid methane/liquid oxygen. To demonstrate performance and prove feasibility of this propellant combination, a 100lbf LO2/LCH4 engine was developed and tested under the NASA Propulsion and Cryogenic Advanced Development (PCAD) project. Since high ignition energy is a perceived drawback of this propellant combination, a test program was performed to explore ignition performance and reliability versus delivered spark energy. The sensitivity of ignition to spark timing and repetition rate was also examined. Three different exciter units were used with the engine's augmented (torch) igniter. Propellant temperature was also varied within the liquid range. Captured waveforms indicated spark behavior in hot fire conditions was inconsistent compared to the well-behaved dry sparks (in quiescent, room air). The escalating pressure and flow environment increases spark impedance and may at some point compromise an exciter.s ability to deliver a spark. Reduced spark energies of these sparks result in more erratic ignitions and adversely affect ignition probability. The timing of the sparks relative to the pressure/flow conditions also impacted the probability of ignition. Sparks occurring early in the flow could trigger ignition with energies as low as 1-6mJ, though multiple, similarly timed sparks of 55-75mJ were required for reliable ignition. An optimum time interval for spark application and ignition coincided with propellant introduction to the igniter and engine. Shifts of ignition timing were manifested by changes in the characteristics of the resulting ignition.

  20. Spark Ignition LPG for Hydrogen Gas Combustion the Reduction Furnace ME-11 Process

    International Nuclear Information System (INIS)

    Achmad Suntoro

    2007-01-01

    Reverse engineering method for automatic spark-ignition system of LPG to burn hydrogen gaseous in the reducing process of ME-11 furnace has been successfully implemented using local materials. A qualitative study to the initial behaviour of the LPG flame system has created an idea by modification to install an automatic spark-ignition of the LPG on the reducing furnace ME-11. The automatic spark-ignition system has been tested and proved working well. (author)

  1. Evaluation of Biosynthesis, Accumulation and Antioxidant Activityof Vitamin E in Sweet Corn (Zea mays L. during Kernel Development

    Directory of Open Access Journals (Sweden)

    Lihua Xie

    2017-12-01

    Full Text Available Sweet corn kernels were used in this research to study the dynamics of vitamin E, by evaluatingthe expression levels of genes involved in vitamin E synthesis, the accumulation of vitamin E, and the antioxidant activity during the different stage of kernel development. Results showed that expression levels of ZmHPT and ZmTC genes increased, whereas ZmTMT gene dramatically decreased during kernel development. The contents of all the types of vitamin E in sweet corn had a significant upward increase during kernel development, and reached the highest level at 30 days after pollination (DAP. Amongst the eight isomers of vitamin E, the content of γ-tocotrienol was the highest, and increased by 14.9 folds, followed by α-tocopherolwith an increase of 22 folds, and thecontents of isomers γ-tocopherol, α-tocotrienol, δ-tocopherol,δ-tocotrienol, and β-tocopherol were also followed during kernel development. The antioxidant activity of sweet corn during kernel development was increased, and was up to 101.8 ± 22.3 μmol of α-tocopherol equivlent/100 g in fresh weight (FW at 30 DAP. There was a positive correlation between vitamin E contents and antioxidant activity in sweet corn during the kernel development, and a negative correlation between the expressions of ZmTMT gene and vitamin E contents. These results revealed the relations amongst the content of vitamin E isomers and the gene expression, vitamin E accumulation, and antioxidant activity. The study can provide a harvesting strategy for vitamin E bio-fortification in sweet corn.

  2. Evaluation of Biosynthesis, Accumulation and Antioxidant Activityof Vitamin E in Sweet Corn (Zea mays L.) during Kernel Development.

    Science.gov (United States)

    Xie, Lihua; Yu, Yongtao; Mao, Jihua; Liu, Haiying; Hu, Jian Guang; Li, Tong; Guo, Xinbo; Liu, Rui Hai

    2017-12-20

    Sweet corn kernels were used in this research to study the dynamics of vitamin E, by evaluatingthe expression levels of genes involved in vitamin E synthesis, the accumulation of vitamin E, and the antioxidant activity during the different stage of kernel development. Results showed that expression levels of Zm HPT and Zm TC genes increased, whereas Zm TMT gene dramatically decreased during kernel development. The contents of all the types of vitamin E in sweet corn had a significant upward increase during kernel development, and reached the highest level at 30 days after pollination (DAP). Amongst the eight isomers of vitamin E, the content of γ-tocotrienol was the highest, and increased by 14.9 folds, followed by α-tocopherolwith an increase of 22 folds, and thecontents of isomers γ-tocopherol, α-tocotrienol, δ-tocopherol,δ-tocotrienol, and β-tocopherol were also followed during kernel development. The antioxidant activity of sweet corn during kernel development was increased, and was up to 101.8 ± 22.3 μmol of α-tocopherol equivlent/100 g in fresh weight (FW) at 30 DAP. There was a positive correlation between vitamin E contents and antioxidant activity in sweet corn during the kernel development, and a negative correlation between the expressions of Zm TMT gene and vitamin E contents. These results revealed the relations amongst the content of vitamin E isomers and the gene expression, vitamin E accumulation, and antioxidant activity. The study can provide a harvesting strategy for vitamin E bio-fortification in sweet corn.

  3. A method for manufacturing kernels of metallic oxides and the thus obtained kernels

    International Nuclear Information System (INIS)

    Lelievre Bernard; Feugier, Andre.

    1973-01-01

    A method is described for manufacturing fissile or fertile metal oxide kernels, consisting in adding at least a chemical compound capable of releasing ammonia to an aqueous solution of actinide nitrates dispersing the thus obtained solution dropwise in a hot organic phase so as to gelify the drops and transform them into solid particles, washing drying and treating said particles so as to transform them into oxide kernels. Such a method is characterized in that the organic phase used in the gel-forming reactions comprises a mixture of two organic liquids, one of which acts as a solvent, whereas the other is a product capable of extracting the metal-salt anions from the drops while the gel forming reaction is taking place. This can be applied to the so-called high temperature nuclear reactors [fr

  4. Measurements of some parameters of thermal sparks with respect to their ability to ignite aviation fuel/air mixtures

    Science.gov (United States)

    Haigh, S. J.; Hardwick, C. J.; Baldwin, R. E.

    1991-01-01

    A method used to generate thermal sparks for experimental purposes and methods by which parameters of the sparks, such as speed, size, and temperature, were measured are described. Values are given of the range of such parameters within these spark showers. Titanium sparks were used almost exclusively, since it is particles of this metal which are found to be ejected during simulation tests to carbon fiber composite (CFC) joints. Tests were then carried out in which titanium sparks and spark showers were injected into JP4/(AVTAG F40) mixtures with air. Single large sparks and dense showers of small sparks were found to be capable of causing ignition. Tests were then repeated using ethylene/air mixtures, which were found to be more easily ignited by thermal sparks than the JP4/ air mixtures.

  5. Learning molecular energies using localized graph kernels

    Science.gov (United States)

    Ferré, Grégoire; Haut, Terry; Barros, Kipton

    2017-03-01

    Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

  6. Development of Augmented Spark Impinging Igniter System for Methane Engines

    Science.gov (United States)

    Marshall, William M.; Osborne, Robin J.; Greene, Sandra E.

    2017-01-01

    The Lunar Cargo Transportation and Landing by Soft Touchdown (Lunar CATALYST) program is establishing multiple no-funds-exchanged Space Act Agreement (SAA) partnerships with U.S. private sector entities. The purpose of this program is to encourage the development of robotic lunar landers that can be integrated with U.S. commercial launch capabilities to deliver payloads to the lunar surface. NASA can share technology and expertise under the SAA for the benefit of the CATALYST partners. MSFC seeking to vacuum test Augmented Spark Impinging (ASI) igniter with methane and new exciter units to support CATALYST partners and NASA programs. ASI has previously been used/tested successfully at sea-level, with both O2/CH4 and O2/H2 propellants. Conventional ignition exciter systems historically experienced corona discharge issues in vacuum. Often utilized purging or atmospheric sealing on high voltage lead to remedy. Compact systems developed since PCAD could eliminate the high-voltage lead and directly couple the exciter to the spark igniter. MSFC developed Augmented Spark Impinging (ASI) igniter. Successfully used in several sea-level test programs. Plasma-assisted design. Portion of ox flow is used to generate hot plasma. Impinging flows downstream of plasma. Additional fuel flow down torch tube sleeve for cooling near stoichiometric torch flame. Testing done at NASA GRC Altitude Combustion Stand (ACS) facility 2000-lbf class facility with altitude simulation up to around 100,000 ft. (0.2 psia [10 Torr]) via nitrogen driven ejectors. Propellant conditioning systems can provide temperature control of LOX/CH4 up to test article.

  7. Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

    Science.gov (United States)

    Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

    2007-11-01

    Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

  8. Low temperature spark plasma sintering of YIG powders

    International Nuclear Information System (INIS)

    Fernandez-Garcia, L.; Suarez, M.; Menendez, J.L.

    2010-01-01

    A transition from a low to a high spin state in the magnetization saturation between 1000 and 1100 o C calcination temperature is observed in YIG powders prepared by oxides mixture. Spark plasma sintering of these powders between 900 and 950 o C leads to dense samples with minimal formation of YFeO 3 , opening the way to co-sintering of YIG with metals or metallic alloys. The optical properties depend on the sintering stage: low (high) density samples show poor (bulk) optical absorption.

  9. Spark gap overpressures in the transfer capacitor device

    International Nuclear Information System (INIS)

    Burkhardt, L.C.; Dike, R.S.

    1977-01-01

    A designer of spark gaps is often faced with two gas pressure problems, one static and one dynamic. The former is easy to obtain data on which to base intelligent design specifications; about the latter, less is known. It is the total internal pressure environment we have attempted to measure, in an un-time-resolved way, in order to give the designer some rationale in designing gaps of this category. We measure overpressures of approximately 400 PSI in a 13 cubic inch gap passing currents of approximately 200 kA

  10. Search for an optimum time response of spark counters

    International Nuclear Information System (INIS)

    Devismes, A.; Finck, Ch.; Kress, T.; Gobbi, A.; Eschke, J.; Herrmann, N.; Hildenbrand, K.D.; Koczon, P.; Petrovici, M.

    2002-01-01

    A spark counter of the type developed by Pestov has been tested with the aim of searching for an optimum time response function, changing voltage, content of noble and quencher gases, pressure and energy-loss. Replacing the usual argon by neon has brought an improvement of the resolution and a significant reduction of tails in the time response function. It has been proven that a counter as long as 90 cm can deliver, using neon gas mixture, a time resolution σ<60 ps with about 1% absolute tail and an efficiency of about 90%

  11. Compaction of lithium-silicate ceramics using spark plasma sintering

    Czech Academy of Sciences Publication Activity Database

    Kubatík, Tomáš František; Lukáč, František; Mušálek, Radek; Brožek, Vlastimil; Stehlíková, K.; Chráska, Tomáš

    2017-01-01

    Roč. 61, č. 1 (2017), s. 40-44 ISSN 0862-5468 R&D Projects: GA ČR GB14-36566G Institutional support: RVO:61389021 Keywords : Li2Si2O5 * Li2SiO3 * Spark plasma sintering (SPS) * Quantitative Rietveld refinement * X-ray diffraction (XRD) Subject RIV: JG - Metallurgy OBOR OECD: Materials engineering Impact factor: 0.439, year: 2016 http://www.ceramics-silikaty.cz/index.php?page=cs_detail_doi&id=789

  12. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  13. Multiple kernel boosting framework based on information measure for classification

    International Nuclear Information System (INIS)

    Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

    2016-01-01

    The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.

  14. Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

    Science.gov (United States)

    Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong

    2014-01-01

    Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.

  15. Deep Restricted Kernel Machines Using Conjugate Feature Duality.

    Science.gov (United States)

    Suykens, Johan A K

    2017-08-01

    The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

  16. Training Lp norm multiple kernel learning in the primal.

    Science.gov (United States)

    Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

    2013-10-01

    Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Fungal Distribution and Varieties Resistance to Kernel Discoloration in Korean Two-rowed Barley

    OpenAIRE

    Sang-Hyun Shin; Eun-Jo Seo; Jae-Seong Choi; JungKwan Lee; Jong-Chul Park; Chun-Sik Kang

    2013-01-01

    Barley kernel discoloration (KD) leads to substantial loss in value through downgrading and discounting of malting barley. The objective of this research is to investigate fungal distribution and varieties resistance to KD in Korean two-rowed barley. Several fungal organisms including Alternaria spp., Fusarium spp., Aspergillus spp., Epicoccum spp. and Rhizopus spp. were isolated from Korean two-rowed barley representing KD. The symptoms of KD were brown and black discolorations o...

  18. a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

    Science.gov (United States)

    Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

    2014-10-01

    In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

  19. 2-Methylfuran: A bio-derived octane booster for spark-ignition engines

    KAUST Repository

    Sarathy, Mani

    2018-04-02

    The efficiency of spark-ignition engines is limited by the phenomenon of knock, which is caused by auto-ignition of the fuel-air mixture ahead of the spark-initiated flame front. The resistance of a fuel to knock is quantified by its octane index; therefore, increasing the octane index of a spark-ignition engine fuel increases the efficiency of the respective engine. However, raising the octane index of gasoline increases the refining costs, as well as the energy consumption during production. The use of alternative fuels with synergistic blending effects presents an attractive option for improving octane index. In this work, the octane enhancing potential of 2-methylfuran (2-MF), a next-generation biofuel, has been examined and compared to other high-octane components (i.e., ethanol and toluene). A primary reference fuel with an octane index of 60 (PRF60) was chosen as the base fuel since it closely represents refinery naphtha streams, which are used as gasoline blend stocks. Initial screening of the fuels was done in an ignition quality tester (IQT). The PRF60/2-MF (80/20 v/v%) blend exhibited longer ignition delay times compared to PRF60/ethanol (80/20 v/v%) blend and PRF60/toluene (80/20 v/v%) blend, even though pure 2-MF is more reactive than both ethanol and toluene. The mixtures were also tested in a cooperative fuels research (CFR) engine under research octane number and motor octane number like conditions. The PRF60/2-MF blend again possesses a higher octane index than other blending components. A detailed chemical kinetic analysis was performed to understand the synergetic blending effect of 2-MF, using a well-validated PRF/2-MF kinetic model. Kinetic analysis revealed superior suppression of low-temperature chemistry with the addition of 2-MF. The results from simulations were further confirmed by homogeneous charge compression ignition engine experiments, which established its superior low-temperature heat release (LTHR) suppression compared to ethanol

  20. Gradient-based adaptation of general gaussian kernels.

    Science.gov (United States)

    Glasmachers, Tobias; Igel, Christian

    2005-10-01

    Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

  1. On weights which admit the reproducing kernel of Bergman type

    Directory of Open Access Journals (Sweden)

    Zbigniew Pasternak-Winiarski

    1992-01-01

    Full Text Available In this paper we consider (1 the weights of integration for which the reproducing kernel of the Bergman type can be defined, i.e., the admissible weights, and (2 the kernels defined by such weights. It is verified that the weighted Bergman kernel has the analogous properties as the classical one. We prove several sufficient conditions and necessary and sufficient conditions for a weight to be an admissible weight. We give also an example of a weight which is not of this class. As a positive example we consider the weight μ(z=(Imz2 defined on the unit disk in ℂ.

  2. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...

  3. Flour quality and kernel hardness connection in winter wheat

    Directory of Open Access Journals (Sweden)

    Szabó B. P.

    2016-12-01

    Full Text Available Kernel hardness is controlled by friabilin protein and it depends on the relation between protein matrix and starch granules. Friabilin is present in high concentration in soft grain varieties and in low concentration in hard grain varieties. The high gluten, hard wheat our generally contains about 12.0–13.0% crude protein under Mid-European conditions. The relationship between wheat protein content and kernel texture is usually positive and kernel texture influences the power consumption during milling. Hard-textured wheat grains require more grinding energy than soft-textured grains.

  4. Explicit signal to noise ratio in reproducing kernel Hilbert spaces

    DEFF Research Database (Denmark)

    Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo

    2011-01-01

    This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose...... an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...

  5. Effects of tetracaine on voltage-activated calcium sparks in frog intact skeletal muscle fibers.

    Science.gov (United States)

    Hollingworth, Stephen; Chandler, W Knox; Baylor, Stephen M

    2006-03-01

    The properties of Ca(2+) sparks in frog intact skeletal muscle fibers depolarized with 13 mM [K(+)] Ringer's are well described by a computational model with a Ca(2+) source flux of amplitude 2.5 pA (units of current) and duration 4.6 ms (18 degrees C; Model 2 of Baylor et al., 2002). This result, in combination with the values of single-channel Ca(2+) current reported for ryanodine receptors (RyRs) in bilayers under physiological ion conditions, 0.5 pA (Kettlun et al., 2003) to 2 pA (Tinker et al., 1993), suggests that 1-5 RyR Ca(2+) release channels open during a voltage-activated Ca(2+) spark in an intact fiber. To distinguish between one and greater than one channel per spark, sparks were measured in 8 mM [K(+)] Ringer's in the absence and presence of tetracaine, an inhibitor of RyR channel openings in bilayers. The most prominent effect of 75-100 microM tetracaine was an approximately sixfold reduction in spark frequency. The remaining sparks showed significant reductions in the mean values of peak amplitude, decay time constant, full duration at half maximum (FDHM), full width at half maximum (FWHM), and mass, but not in the mean value of rise time. Spark properties in tetracaine were simulated with an updated spark model that differed in minor ways from our previous model. The simulations show that (a) the properties of sparks in tetracaine are those expected if tetracaine reduces the number of active RyR Ca(2+) channels per spark, and (b) the single-channel Ca(2+) current of an RyR channel is normal voltage-activated sparks (i.e., in the absence of tetracaine) are produced by two or more active RyR Ca(2+) channels. The question of how the activation of multiple RyRs is coordinated is discussed.

  6. Advances in the electro-spark deposition coating process

    International Nuclear Information System (INIS)

    Johnson, R.N.; Sheldon, G.L.

    1986-04-01

    Electro-spark deposition (ESD) is a pulsed-arc micro-welding process using short-duration, high-current electrical pulses to deposit an electrode material on a metallic substrate. It is one of the few methods available by which a fused, metallurgically bonded coating can be applied with such a low total heat input that the bulk substrate material remains at or near ambient temperatures. The short duration of the electrical pulse allows an extremely rapid solidification of the deposited material and results in an exceptionally fine-grained, homogenous coating that approaches (and with some materials, actually is) an amorphous structure. This structure is believed to contribute to the good tribological and corrosion performance observed for hardsurfacing materials used in the demanding environments of high temperatures, liquid metals, and neutron irradiation. A brief historical review of the process is provided, followed by descriptions of the present state-of-the-art and of the performance and applications of electro-spark deposition coatings in liquid-metal-cooled nuclear reactors

  7. Observations of dense plasma formation in the vacuum spark

    International Nuclear Information System (INIS)

    Chuaqui, H.; Favre, M.; Wyndham, E.; Aliaga R, R.; Choi, P.; Dumitrescu-Zoita, C.

    1994-01-01

    A series of experimental observations have been performed on the dense plasma formations or Hot Spots generated in the Vacuum Spark. The plasma discharges are driven by a 1.5 Ohm, 120 ns line at currents up to 100 KA. The line may be used to deliver a rectangular current pulse when the line gap is used. Alternatively when the line gap is shorted, the Vacuum Spark itself switches the line. A Nd: Yag Laser, with an energy of 0.5 J in an 8 ns pulse, is used to pre ionizing the discharge. The formation of Hot Spots is studied under a range of different conditions. These include the pre ionizing conditions, as well as the Anode shape and the Anode Cathode separation. The optimization of these parameters permit very reproducible shot to shot behaviour. Of particular interest is the Hot Spot size dependence as a function of its temperature and of time. The use of a new variant on the Pin Hole Camera, the Slit Wire Camera provides a new method of measuring with precision the Hot Spot dimensions in different X-ray emission energy ranges. A quadruple hole Camera is used to measure the temperature of the Hot Spots. The temporal and spatial evolution of the X-ray emission is measured using using a Slit Wire, Scintillator, Fibre Optic, Photomultiplier array. The temporal emission of the X-rays is also observed using an array of PIN X-ray diodes. (author). 5 refs, 6 figs

  8. Exploratory studies on a passively triggered vacuum spark

    Energy Technology Data Exchange (ETDEWEB)

    Rout, R.K. [High Pressure Physics Division, Bhabha Atomic Research Centre, Mumbai (India)]. E-mail: rkrout@apsara.barc.ernet.in; Auluck, S.K.H.; Kulkarni, L.V. [High Pressure Physics Division, Bhabha Atomic Research Centre, Mumbai, India (India); Nagpal, J.S. [Radiation Standards and Instrumentation Division, Bhabha Atomic Research Centre, Mumbai (India)

    1999-12-07

    The results of an experimental investigation on a passively triggered vacuum spark device are presented. The diagnostics include the current, x-ray and optical emission measurements. The sharp dips in the current derivative signal indicate the occurrence of pinching at an early stage of the discharge (at current {approx} 5 kA). A well-confined plasma with a central hot region was recorded using a streak camera. The pinched plasma was observed to undergo kink-type oscillations with a time period of 10-15 ns. Repeated plasma fronts were seen to move from the anode to the cathode with an average velocity of {approx}5x10{sup 6} cm s{sup -1}. Soft x-ray emission having a radiation intensity of a few hundred mR per discharge was observed. The x-ray signals obtained using photodiodes showed multiple bursts. A soft x-ray pinhole camera recorded micro-pinches of {approx}100 {mu}m. The x-ray emitting regions were confined to the inter-electrode gap. The x-ray emission characteristics were influenced by the electrolytic resistance, which was connected across the spark gap to initiate discharge. (author)

  9. Exploratory studies on a passively triggered vacuum spark

    Science.gov (United States)

    Rout, R. K.; Auluck, S. K. H.; Nagpal, J. S.; Kulkarni, L. V.

    1999-12-01

    The results of an experimental investigation on a passively triggered vacuum spark device are presented. The diagnostics include the current, x-ray and optical emission measurements. The sharp dips in the current derivative signal indicate the occurrence of pinching at an early stage of the discharge (at current icons/Journals/Common/approx" ALT="approx" ALIGN="TOP"/>5 kA). A well-confined plasma with a central hot region was recorded using a streak camera. The pinched plasma was observed to undergo kink-type oscillations with a time period of 10-15 ns. Repeated plasma fronts were seen to move from the anode to the cathode with an average velocity of icons/Journals/Common/approx" ALT="approx" ALIGN="TOP"/>5 × 106 cm s-1. Soft x-ray emission having a radiation intensity of a few hundred mR per discharge was observed. The x-ray signals obtained using photodiodes showed multiple bursts. A soft x-ray pinhole camera recorded micro-pinches of icons/Journals/Common/approx" ALT="approx" ALIGN="TOP"/>100 µm. The x-ray emitting regions were confined to the inter-electrode gap. The x-ray emission characteristics were influenced by the electrolytic resistance, which was connected across the spark gap to initiate discharge.

  10. Influence of hydrox on spark ignition engine performance

    International Nuclear Information System (INIS)

    Naude, A.F.

    2003-01-01

    An experimental investigation was performed on the influence of the addition of small quantities of Hydrox (hydrogen and oxygen) as generated through electrolysis of water on the performance of a spark ignition engine. A Mazda 1600 cc fuel injected engine connected to a Superflow SF901 dynamometer system was used in this project. The engine was also equipped with a Unichip engine management system in order to enable changes in the spark timing and the amount of fuel injected. Hydrox was generated by an electrolysis process that could either be powered by the engine's alternator or from a separate power source. This hydrox gas produced from the electrolyzer was introduced into the engine's intake manifold and the influence of this was measured on the engine's performance, emissions and fuel consumption. For these tests a typical load condition as experienced for a light passenger car vehicle driven at 100 km/h on the open road was simulated. Typical results for the change in emissions with the hydrox introduction showed a significant reduction in hydrocarbons at lean air-fuel ratio operation of the engine. Additionally with the electrolysis process being driven by the engine a small improvement in fuel consumption was experienced. (author)

  11. Air spark-like plasma source for antimicrobial NOx generation

    International Nuclear Information System (INIS)

    Pavlovich, M J; Galleher, C; Curtis, B; Clark, D S; Graves, D B; Ono, T; Machala, Z

    2014-01-01

    We demonstrate and analyse the generation of nitrogen oxides and their antimicrobial efficacy using atmospheric air spark-like plasmas. Spark-like discharges in air in a 1 L confined volume are shown to generate NO x at an initial rate of about 1.5  ×  10 16 NO x molecules/J dissipated in the plasma. Such a discharge operating in this confined volume generates on the order of 6000 ppm NO x in 10 min. Around 90% of the NO x is in the form of NO 2 after several minutes of operation in the confined volume, suggesting that NO 2 is the dominant antimicrobial component. The strong antimicrobial action of the NO x mixture after several minutes of plasma operation is demonstrated by measuring rates of E. coli disinfection on surfaces and in water exposed to the NO x mixture. Some possible applications of plasma generation of NO x (perhaps followed by dissolution in water) include disinfection of surfaces, skin or wound antisepsis, and sterilization of medical instruments at or near room temperature. (paper)

  12. A new and efficient mechanism for spark ignition engines

    International Nuclear Information System (INIS)

    Shadloo, M.S.; Poultangari, R.; Abdollahzadeh Jamalabadi, M.Y.; Rashidi, M.M.

    2015-01-01

    Highlights: • A new slider–crank mechanism, with superior performance is presented. • Thermodynamic processes as well as vibration and internal forces have been modeled. • Comparison with the conventional four-stroke spark ignition engines is made. • Advantages and disadvantages of the proposed mechanism are discussed. - Abstract: In this paper a new symmetrical crank and slider mechanism is proposed and a zero dimensional model is utilized to study its combustion performance enhancement in a four-stroke spark ignition (SI) engine. The main features of this new mechanism are superior thermodynamic efficiency, lower internal frictions, and lower pollutants. Comparison is made between its performance and that of the conventional four-stroke SI engines. Presented mechanism is designed to provide better fuel consumption of internal combustion engines. These advantages over standard engine are achieved through synthesis of new mechanism. Numerical calculation have been performed for several cases of different mechanism parameters, compression ratio and engine speed. A comprehensive comparison between their thermodynamic processes as well as vibration and internal forces has been done. Calculated efficiency and power diagrams are plotted and compared with performance of a conventional SI engine. Advantages and disadvantages of the proposed mechanism are discussed in details

  13. Spark and HPC for High Energy Physics Data Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Sehrish, Saba; Kowalkowski, Jim; Paterno, Marc

    2017-05-01

    A full High Energy Physics (HEP) data analysis is divided into multiple data reduction phases. Processing within these phases is extremely time consuming, therefore intermediate results are stored in files held in mass storage systems and referenced as part of large datasets. This processing model limits what can be done with interactive data analytics. Growth in size and complexity of experimental datasets, along with emerging big data tools are beginning to cause changes to the traditional ways of doing data analyses. Use of big data tools for HEP analysis looks promising, mainly because extremely large HEP datasets can be represented and held in memory across a system, and accessed interactively by encoding an analysis using highlevel programming abstractions. The mainstream tools, however, are not designed for scientific computing or for exploiting the available HPC platform features. We use an example from the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) in Geneva, Switzerland. The LHC is the highest energy particle collider in the world. Our use case focuses on searching for new types of elementary particles explaining Dark Matter in the universe. We use HDF5 as our input data format, and Spark to implement the use case. We show the benefits and limitations of using Spark with HDF5 on Edison at NERSC.

  14. TRAINING TREE ADJOINING GRAMMARS WITH HUGE TEXT CORPUS USING SPARK MAP REDUCE

    Directory of Open Access Journals (Sweden)

    Vijay Krishna Menon

    2015-07-01

    Full Text Available Tree adjoining grammars (TAGs are mildly context sensitive formalisms used mainly in modelling natural languages. Usage and research on these psycho linguistic formalisms have been erratic in the past decade, due to its demanding construction and difficulty to parse. However, they represent promising future for formalism based NLP in multilingual scenarios. In this paper we demonstrate basic synchronous Tree adjoining grammar for English-Tamil language pair that can be used readily for machine translation. We have also developed a multithreaded chart parser that gives ambiguous deep structures and a par dependency structure known as TAG derivation. Furthermore we then focus on a model for training this TAG for each language using a large corpus of text through a map reduce frequency count model in spark and estimation of various probabilistic parameters for the grammar trees thereafter; these parameters can be used to perform statistical parsing on the trained grammar.

  15. Densification of silicon and zirconium carbides by a new process: spark plasma sintering

    International Nuclear Information System (INIS)

    Guillard, F.

    2006-12-01

    Materials research for suitable utilization in 4. generation nuclear plants needs new ways to densify testing components. Two carbides, silicon and zirconium carbide seems to be the most suitable choice due to their mechanical, thermal and neutron-transparency properties against next nuclear plant specifications. Nevertheless one main difficulty remains, which is densifying them even at high temperature. Spark Plasma Sintering a new metal-, ceramic- and composite-sintering process has been used to densify both SiC and ZrC. Understanding bases of mass transport mechanisms in SPS have been studied. Composites and interfaces have been processed and analyzed. This manuscript reports original results on SiC and ZrC ceramics sintered with commercial powder started, without additives. (author)

  16. Performance simulation of a spark ignited free-piston engine generator

    Energy Technology Data Exchange (ETDEWEB)

    Mikalsen, R.; Roskilly, A.P. [Sir Joseph Swan Institute for Energy Research, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU (United Kingdom)

    2008-10-15

    Free-piston engines are under investigation by a number of research groups worldwide due to potential fuel efficiency and engine emissions advantages. The free-piston engine generator, in which a linear electric generator is fixed to the mover to produce electric power, has been proposed as an alternative prime mover for hybrid-electric vehicles. This paper investigates the performance of a spark ignited free-piston engine generator and compares it to a conventional engine using a computational fluid dynamics simulation model. The particular operating characteristics of the free-piston engine were not found to give noticeable performance advantages, and it is concluded that the main potential of this technology lies in the simplicity and flexibility of the concept. (author)

  17. Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

    Science.gov (United States)

    Cid, Jaime A; von Davier, Alina A

    2015-05-01

    Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

  18. Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

    Science.gov (United States)

    Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

    Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

  19. Effect of surfactant and surfactant blends on pseudoternary phase diagram behavior of newly synthesized palm kernel oil esters

    Directory of Open Access Journals (Sweden)

    Mahdi ES

    2011-06-01

    used. The information gathered in this study is useful for researchers and manufacturers interested in using palm kernel oil esters in pharmaceutical and cosmetic preparation. The use of palm kernel oil esters can improve drug delivery and reduce the cost of cosmetics.Keywords: phase diagram, palm kernel oil esters, nonionic surfactants, microemulsions

  20. A Laser Spark Plug Ignition System for a Stationary Lean-Burn Natural Gas Reciprocating Engine

    Energy Technology Data Exchange (ETDEWEB)

    McIntyre, D. L. [West Virginia Univ., Morgantown, WV (United States)

    2007-05-01

    To meet the ignition system needs of large bore, high pressure, lean burn, natural gas engines a side pumped, passively Q-switched, Nd:YAG laser was developed and tested. The laser was designed to produce the optical intensities needed to initiate ignition in a lean burn, high compression engine. The laser and associated optics were designed with a passive Q-switch to eliminate the need for high voltage signaling and associated equipment. The laser was diode pumped to eliminate the need for high voltage flash lamps which have poor pumping efficiency. The independent and dependent parameters of the laser were identified and explored in specific combinations that produced consistent robust sparks in laboratory air. Prior research has shown that increasing gas pressure lowers the breakdown threshold for laser initiated ignition. The laser has an overall geometry of 57x57x152 mm with an output beam diameter of approximately 3 mm. The experimentation used a wide range of optical and electrical input parameters that when combined produced ignition in laboratory air. The results show a strong dependence of the output parameters on the output coupler reflectivity, Q-switch initial transmission, and gain media dopant concentration. As these three parameters were lowered the output performance of the laser increased leading to larger more brilliant sparks. The results show peak power levels of up to 3MW and peak focal intensities of up to 560 GW/cm2. Engine testing was performed on a Ricardo Proteus single cylinder research engine. The goal of the engine testing was to show that the test laser performs identically to the commercially available flashlamp pumped actively Q-switched laser used in previous laser ignition testing. The engine testing consisted of a comparison of the in-cylinder, and emissions behavior of the engine using each of the lasers as an ignition system. All engine parameters were kept as constant as possilbe while the equivalence ratio (fueling