Flame kernel generation and propagation in turbulent partially premixed hydrocarbon jet
Mansour, Mohy S.
2014-04-23
Flame development, propagation, stability, combustion efficiency, pollution formation, and overall system efficiency are affected by the early stage of flame generation defined as flame kernel. Studying the effects of turbulence and chemistry on the flame kernel propagation is the main aim of this work for natural gas (NG) and liquid petroleum gas (LPG). In addition the minimum ignition laser energy (MILE) has been investigated for both fuels. Moreover, the flame stability maps for both fuels are also investigated and analyzed. The flame kernels are generated using Nd:YAG pulsed laser and propagated in a partially premixed turbulent jet. The flow field is measured using 2-D PIV technique. Five cases have been selected for each fuel covering different values of Reynolds number within a range of 6100-14400, at a mean equivalence ratio of 2 and a certain level of partial premixing. The MILE increases by increasing the equivalence ratio. Near stoichiometric the energy density is independent on the jet velocity while in rich conditions it increases by increasing the jet velocity. The stability curves show four distinct regions as lifted, attached, blowout, and a fourth region either an attached flame if ignition occurs near the nozzle or lifted if ignition occurs downstream. LPG flames are more stable than NG flames. This is consistent with the higher values of the laminar flame speed of LPG. The flame kernel propagation speed is affected by both turbulence and chemistry. However, at low turbulence level chemistry effects are more pronounced while at high turbulence level the turbulence becomes dominant. LPG flame kernels propagate faster than those for NG flame. In addition, flame kernel extinguished faster in LPG fuel as compared to NG fuel. The propagation speed is likely to be consistent with the local mean equivalence ratio and its corresponding laminar flame speed. Copyright © Taylor & Francis Group, LLC.
NUMERICAL SIMULATION OF THE GROWTH OF NANOPARTICLES IN A FLAME CVD PROCESS
Institute of Scientific and Technical Information of China (English)
Lixi Wang; Si Chen; Hongyong Xie
2004-01-01
The growth of titania nanoparticles in a flame CVD process has been simulated by computational fluid dynamics, based on the change rate of particle number density due to their collisions calculated from an integral collision kernel. The assumptions made on constant particle volume density nv (nd3), constant density of particle surface area ns (nd2), and constant entity nd2.5 in coagulation process have been examined. Comparisons have been made on particle size distribution between measurement results and predictions from present model of particle growth and Kruis model of particle dynamics for titania nanoparticles synthesized by the flame CVD process. Effects of operational parameters such as O2 mole fraction and particle number density on mean particle size and size distribution have been discussed.
Growth of Y-shaped Carbon Nanofibers from Ethanol Flames
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Cheng Jin
2008-01-01
Full Text Available Abstract Y-shaped carbon nanofibers as a multi-branched carbon nanostructure have potential applications in electronic devices. In this article, we report that several types of Y-shaped carbon nanofibers are obtained from ethanol flames. These Y-shaped carbon nanofibers have different morphologies. According to our experimental results, the growth mechanism of Y-shaped carbon nanofibers has been discussed and a possible growth model of Y-shaped carbon nanofibers has been proposed.
INTEGRAL COLLISION KERNEL FOR THE GROWTH OF AEROSOL PARTICLES
Institute of Scientific and Technical Information of China (English)
Hongyong Xie
2005-01-01
Integral collision kernel is elucidated using experimental results for titania, silica and alumina nanoparticles synthesized by FCVD process, and titania submicron particles synthesized in a tube furnace reactor. The integral collision kernel was obtained from a particle number balance equation by the integration of collision rates from the kinetic theory of dilute gases for the free-molecule regime, from the Smoluchowski theory for the continuum regime, and by a semi-empirical interpolation for the transition regime between the two limiting regimes. Comparisons have been made on particle size and the integral collision kernel, showing that the predicted integral collision kernel agreed well with the experimental results in Knudsen number range from about 1.5 to 20.
Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K
2015-05-01
We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template.
Askari, Omid; Beretta, Gian Paolo; Eisazadeh-Far, Kian; Metghalchi, Hameed
2016-07-01
Thermodynamic properties of hydrocarbon/air plasma mixtures at ultra-high temperatures must be precisely calculated due to important influence on the flame kernel formation and propagation in combusting flows and spark discharge applications. A new algorithm based on the complete chemical equilibrium assumption is developed to calculate the ultra-high temperature plasma composition and thermodynamic properties, including enthalpy, entropy, Gibbs free energy, specific heat at constant pressure, specific heat ratio, speed of sound, mean molar mass, and degree of ionization. The method is applied to compute the thermodynamic properties of H2/air and CH4/air plasma mixtures for different temperatures (1000-100 000 K), different pressures (10-6-100 atm), and different fuel/air equivalence ratios within flammability limit. In calculating the individual thermodynamic properties of the atomic species needed to compute the complete equilibrium composition, the Debye-Huckel cutoff criterion has been used for terminating the series expression of the electronic partition function so as to capture the reduction of the ionization potential due to pressure and the intense connection between the electronic partition function and the thermodynamic properties of the atomic species and the number of energy levels taken into account. Partition functions have been calculated using tabulated data for available atomic energy levels. The Rydberg and Ritz extrapolation and interpolation laws have been used for energy levels which are not observed. The calculated plasma properties are then presented as functions of temperature, pressure and equivalence ratio, in terms of a new set of thermodynamically self-consistent correlations that are shown to provide very accurate fits suitable for efficient use in CFD simulations. Comparisons with existing data for air plasma show excellent agreement.
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.
Probing the dynamics of nanoparticle growth in a flame using synchrotron radiation.
Beaucage, Gregory; Kammler, Hendrik K; Mueller, Roger; Strobel, Reto; Agashe, Nikhil; Pratsinis, Sotiris E; Narayanan, Theyencheri
2004-06-01
Flame synthesis is one of the most versatile and promising technologies for large-scale production of nanoscale materials. Pyrolysis has recently been shown to be a useful route for the production of single-walled nanotubes, quantum dots and a wide variety of nanostructured ceramic oxides for catalysis and electrochemical applications. An understanding of the mechanisms of nanostructural growth in flames has been hampered by a lack of direct observations of particle growth, owing to high temperatures (2,000 K), rapid kinetics (submillisecond scale), dilute growth conditions (10(-6) volume fraction) and optical emission of synthetic flames. Here we report the first successful in situ study of nanoparticle growth in a flame using synchrotron X-ray scattering. The results indicate that simple growth models, first derived for colloidal synthesis, can be used to facilitate our understanding of flame synthesis. Further, the results indicate the feasibility of studies of nanometre-scale aerosols of toxicological and environmental concern.
P. Aarumugam; P. Saravana Bhavan; T. Muralisankar; N. Manickam; V. Srinevasan; S. Radhakrishnan
2013-01-01
The growth promoting potential of fruits wastes, mango seed kernel, banana peel and papaya peel on the freshwater prawn, Macrobrachium rosenbergii post larvae (PL) was evaluated. Basal diet equated to 35% protein was prepared by using soybean meal, groundnut oilcake, horse gram and wheat flour. Each fruit waste powder was separately incorporated with basal diet at a proportion of 10%. Sunflower oil was used as lipid source. Egg albumin and tapioca flour were used as binding agents. Vitamin B-...
Hayashi, J.; Nakatsuka, N.; Morimoto, I.; Akamatsu, F.
2017-02-01
The lean combustion is one of the key techniques for the advanced internal combustion systems due to the requirement of the higher thermal efficiency. Since the successful ignition must be guaranteed even in the lean combustion, advanced ignition systems have been developed in this decade. Laser ignition is one of the advanced ignition systems which have the profits of the flexibility in the position and the timing of ignition. To develop this ignition system for the actual combustion system, it is required to reveal the underlying physics of the laser ignition. Particularly, the time evolution of high temperature region formed by laser induced breakdown should be discussed. In this study, therefore, the time evolution of the high temperature region formed by the laser induced breakdown and the development of flame kernel were observed by using high-speed imaging. The ignition trials of methane/air lean premixed mixture were carried out in the constant volume combustion vessel to obtain minimum laser pulse energy for ignition (MPE). Results showed that the light emission from plasma formed by laser induced breakdown remained at least in several tens nano-seconds. In addition, there were large differences between the breakdown threshold and the MPE, which meant that the breakdown threshold did not determine the minimum pulse energy for ignition.
A PAH growth mechanism and synergistic effect on PAH formation in counterflow diffusion flames
Wang, Yu
2013-09-01
A reaction mechanism having molecular growth up to benzene for hydrocarbon fuels with up to four carbon-atoms was extended to include the formation and growth of polycyclic aromatic hydrocarbons (PAHs) up to coronene (C24H12). The new mechanism was tested for ethylene premixed flames at low (20torr) and atmospheric pressures by comparing experimentally observed species concentrations with those of the computed ones for small chemical species and PAHs. As compared to several existing mechanisms in the literature, the newly developed mechanism showed an appreciable improvement in the predicted profiles of PAHs. The new mechanism was also used to simulate PAH formation in counterflow diffusion flames of ethylene to study the effects of mixing propane and benzene in the fuel stream. In the ethylene-propane flames, existing experimental results showed a synergistic effect in PAH concentrations, i.e. PAH concentrations first increased and then decreased with increasing propane mixing. This PAH behavior was successfully captured by the new mechanism. The synergistic effect was predicted to be more pronounced for larger PAH molecules as compared to the smaller ones, which is in agreement with experimental observations. In the experimental study in which the fuel stream of ethylene-propane flames was doped with benzene, a synergistic effect was mitigated for benzene, but was observed for large PAHs. This effect was also predicted in the computed PAH profiles for these flames. To explain these responses of PAHs in the flames of mixture fuels, a pathway analysis has been conducted, which show that several resonantly stabilized species as well as C4H4 and H atom contribute to the enhanced synergistic behaviors of larger PAHs as compared to the small ones in the flames of mixture fuels. © 2013 The Combustion Institute.
Moore, S M; Stalder, K J; Beitz, D C; Stahl, C H; Fithian, W A; Bregendahl, K
2008-03-01
Corn kernel composition may affect its nutritive value and, thus, pig growth performance and carcass characteristics. The objective of this study was to determine the influence of the chemical and physical traits of corn kernels from different hybrids on the growth performance and carcass characteristics of pigs. A total of 288 crossbred pigs were grown in a 3-phase program from 21 kg of BW until slaughter at 113 kg of BW with 12 pens (4 pigs/pen) per dietary treatment. Target BW for each phase were 20 to 40 kg (grower 1), 40 to 80 kg (grower 2), and 80 to 120 kg (finisher). In each phase, diets were formulated to be marginally deficient in Lys, TSAA, Ca, Na, and nonphytate P to improve the likelihood of detecting differences in performance due to corn hybrid. Each of 6 corn hybrids represented a wide range of kernel chemical and physical traits and was substituted for corn in a common diet formulation on an equal weight basis to make the 6 dietary treatments. Physical and chemical composition of the kernels were analyzed and correlated with performance measures by multivariate ANOVA. Kernel density was correlated with i.m. fat (IMF) content in LM (r = -.35, P physical and chemical traits were statistically significant yet not large enough to base corn hybrid selection for feeding pigs on any single kernel chemical or physical trait.
Directory of Open Access Journals (Sweden)
Cuijuan Shi
2014-01-01
Full Text Available Fusarium graminearum is the main causal pathogen affecting small-grain cereals, and it produces deoxynivalenol, a kind of mycotoxin, which displays a wide range of toxic effects in human and animals. Bacterial strains isolated from peanut shells were investigated for their activities against F. graminearum by dual-culture plate and tip-culture assays. Among them, twenty strains exhibited potent inhibition to the growth of F. graminearum, and the inhibition rates ranged from 41.41% to 54.55% in dual-culture plate assay and 92.70% to 100% in tip-culture assay. Furthermore, eighteen strains reduced the production of deoxynivalenol by 16.69% to 90.30% in the wheat kernels assay. Finally, the strains with the strongest inhibitory activity were identified by morphological, physiological, biochemical methods and also 16S rDNA and gyrA gene analysis as Bacillus amyloliquefaciens. The current study highlights the potential application of antagonistic microorganisms and their metabolites in the prevention of fungal growth and mycotoxin production in wheat kernels. As a biological strategy, it might avoid safety problems and nutrition loss which always caused by physical and chemical strategies.
Damköhler number effects on soot formation and growth in turbulent nonpremixed flames
Attili, Antonio
2015-01-01
The effect of Damköhler number on turbulent nonpremixed sooting flames is investigated via large scale direct numerical simulation in three-dimensional n-heptane/air jet flames at a jet Reynolds number of 15,000 and at three different Damköhler numbers. A reduced chemical mechanism, which includes the soot precursor naphthalene, and a high-order method of moments are employed. At the highest Damköhler number, local extinction is negligible, while flames holes are observed in the two lowest Damköhler number cases. Compared to temperature and other species controlled by fuel oxidation chemistry, naphthalene is found to be affected more significantly by the Damköhler number. Consequently, the overall soot mass fraction decreases by more than one order of magnitude for a fourfold decrease of the Damköhler number. On the contrary, the overall number density of soot particles is approximately the same, but its distribution in mixture fraction space is different in the three cases. The total soot mass growth rate is found to be proportional to the Damköhler number. In the two lowest Da number cases, soot leakage across the flame is observed. Leveraging Lagrangian statistics, it is concluded that soot leakage is due to patches of soot that cross the stoichiometric surface through flame holes. These results show the leading order effects of turbulent mixing in controlling the dynamics of soot in turbulent flames. © 2014 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
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P. Aarumugam
2013-06-01
Full Text Available The growth promoting potential of fruits wastes, mango seed kernel, banana peel and papaya peel on the freshwater prawn, Macrobrachium rosenbergii post larvae (PL was evaluated. Basal diet equated to 35% protein was prepared by using soybean meal, groundnut oilcake, horse gram and wheat flour. Each fruit waste powder was separately incorporated with basal diet at a proportion of 10%. Sunflower oil was used as lipid source. Egg albumin and tapioca flour were used as binding agents. Vitamin B-complex with Vitamin-C was also mixed. Feed without any fruit waste was served as control. M. rosenbergii PL (length: 1.2-1.4 cm; weight: 0.09- 0.13 g was fed with these feeds for a period of 90 days. Significant improvements in the nutritional indices (survival rate, weight gain, biomass index, specific growth rate and condition factor, concentrations of biochemical constituents (total protein, carbohydrate and lipid, levels of non-enzymatic antioxidants (vitamin-C and E, content of minerals (Na+ and K+, activities of digestive enzymes (protease, amylase and lipase, and profiles of essential amino acids and fatty acids were recorded in fruits wastes incorporated feeds fed PL when compared with control (P< 0.003 – 0.878. The overall results indicated the fact that mango seed kernel incorporated feed was produced the best performance, followed by better performance of banana peel and good performance of papaya peel. These fruits wastes incorporated feeds enhance digestive enzymes activities and act as appetizer, which in turn enhances food utilization and ultimately yielded better survival and growth of M. rosenbergii PL. Therefore, these fruits wastes have considerable potentials in sustainable development of Macrobrachium culture.
Defective Kernel 1 (DEK1) is required for three-dimensional growth in Physcomitrella patens.
Perroud, Pierre-François; Demko, Viktor; Johansen, Wenche; Wilson, Robert C; Olsen, Odd-Arne; Quatrano, Ralph S
2014-08-01
Orientation of cell division is critical for plant morphogenesis. This is evident in the formation and function of meristems and for morphogenetic transitions. Mosses undergo such transitions: from two-dimensional tip-growing filaments (protonema) to the generation of three-dimensional leaf-like structures (gametophores). The Defective Kernel 1 (DEK1) protein plays a key role in the perception of and/or response to positional cues that specify the formation and function of the epidermal layer in developing seeds of flowering plants. The moss Physcomitrella patens contains the highly conserved DEK1 gene. Using efficient gene targeting, we generated a precise PpDEK1 deletion (∆dek1), which resulted in normal filamentous growth of protonema. Two distinct mutant phenotypes were observed: an excess of buds on the protonema, and abnormal cell divisions in the emerging buds resulting in developmental arrest and the absence of three-dimensional growth. Overexpression of a complete PpDEK1 cDNA, or the calpain domain of PpDEK1 alone, successfully complements both phenotypes. These results in P. patens demonstrate the morphogenetic importance of the DEK1 protein in the control of oriented cell divisions. As it is not for protonema, it will allow dissection of the structure/function relationships of the different domains of DEK1 using gene targeting in null mutant background.
Flame structure of methane inverse diffusion flame
Elbaz, Ayman M.
2014-07-01
This paper presents high speed images of OH-PLIF at 10. kHz simultaneously with 2D PIV (particle image velocimetry) measurements collected along the entire length of an inverse diffusion flame with circumferentially arranged methane fuel jets. For a fixed fuel flow rate, the central air jet Re was varied, leading to four air to fuel velocity ratios, namely Vr = 20.7, 29, 37.4 and 49.8. A double flame structure could be observed composed of a lower fuel entrainment region and an upper mixing and intense combustion region. The entrainment region was enveloped by an early OH layer, and then merged through a very thin OH neck to an annular OH layer located at the shear layer of the air jet. The two branches of this annular OH layer broaden as they moved downstream and eventfully merged together. Three types of events were observed common to all flames: breaks, closures and growing kernels. In upstream regions of the flames, the breaks were counterbalanced by flame closures. These breaks in OH signal were found to occur at locations where locally high velocity flows were impinging on the flame. As the Vr increased to 37.4, the OH layers became discontinuous over the downstream region of the flame, and these regions of low or no OH moved upstream. With further increases in Vr, these OH pockets act as flame kernels, growing as they moved downstream, and became the main mechanism for flame re-ignition. Along the flame length, the direction of the two dimensional principle compressive strain rate axis exhibited a preferred orientation of approximately 45° with respect to the flow direction. Moreover, the OH zones were associated with elongated regions of high vorticity. © 2013 Elsevier Inc.
Effect of various levels of date palm kernel on growth performance of broilers
Tareen, Muhammad Hamza; Wagan, Rani; Siyal, Farman Ali; Babazadeh, Daryoush; Bhutto, Zohaib Ahmed; Arain, Muhammad Asif; Saeed, Muhammad
2017-01-01
Aim: The aim of this study was the assessment of various levels of date palm kernel (DPK) on the growth performance of broilers. Materials and Methods: A 250-day-old broiler chicks were randomly selected and categorized into five groups (50 chicks/group) contained A (control), B, C, D and E fed with 0%, 1%, 2%, 3% and 4% levels of DPK in balanced ration, respectively, for 6 weeks. Feed and water intake were recorded daily in the morning and evening. The data for feed intake, water intake, live body weight, and feed conversion ratio (FCR) were recorded from all birds regularly. The carcass weight and percentage obtained via six slaughtered birds were randomly selected from each group. Finally, economic aspects of the rations evaluated. Results: The most feed intakes of broilers were recorded in Group A (3915.1 g) that was significantly higher than Groups D and E. The highest water intake was in Group E (9067.78 ml) that was significantly higher than Group A and control group. Live body weight was highest in Group E (979.85 g) than Groups B, C, and control group. The best growth weights were determined significantly in Groups D (1921.96 g) and E (1935.95 g). The lowest FCRs were indicated significantly in Groups D (1.97 g/g) and E (1.92 g/g) than Groups B and A. The highest carcass weights were recorded in Groups D (1214.01 g) and E (1230.88 g) that were significantly more than other groups. Dressing percentages in Groups D (61.76%) and E (62.17%) were higher than other groups (pprofits (Rs.) in Groups A, B, C, D and E were indicated 27.01, 32.77, 36.78, 43.47 and 44.51 per broiler, respectively. Conclusion: It was concluded that the high levels of DPK (3-4%) significantly decreased broiler feed intake and increased water intake, live body weight, growth weight, carcass weight, dressing percentage, net profit per bird and also had positive effects on growth of broilers. PMID:28344407
Effect of various levels of date palm kernel on growth performance of broilers
Directory of Open Access Journals (Sweden)
Muhammad Hamza Tareen
2017-02-01
Full Text Available Aim: The aim of this study was the assessment of various levels of date palm kernel (DPK on the growth performance of broilers. Materials and Methods: A 250-day-old broiler chicks were randomly selected and categorized into five groups (50 chicks/group contained A (control, B, C, D and E fed with 0%, 1%, 2%, 3% and 4% levels of DPK in balanced ration, respectively, for 6 weeks. Feed and water intake were recorded daily in the morning and evening. The data for feed intake, water intake, live body weight, and feed conversion ratio (FCR were recorded from all birds regularly. The carcass weight and percentage obtained via six slaughtered birds were randomly selected from each group. Finally, economic aspects of the rations evaluated. Results: The most feed intakes of broilers were recorded in Group A (3915.1 g that was significantly higher than Groups D and E. The highest water intake was in Group E (9067.78 ml that was significantly higher than Group A and control group. Live body weight was highest in Group E (979.85 g than Groups B, C, and control group. The best growth weights were determined significantly in Groups D (1921.96 g and E (1935.95 g. The lowest FCRs were indicated significantly in Groups D (1.97 g/g and E (1.92 g/g than Groups B and A. The highest carcass weights were recorded in Groups D (1214.01 g and E (1230.88 g that were significantly more than other groups. Dressing percentages in Groups D (61.76% and E (62.17% were higher than other groups (p<0.05. The net profits (Rs. in Groups A, B, C, D and E were indicated 27.01, 32.77, 36.78, 43.47 and 44.51 per broiler, respectively. Conclusion: It was concluded that the high levels of DPK (3-4% significantly decreased broiler feed intake and increased water intake, live body weight, growth weight, carcass weight, dressing percentage, net profit per bird and also had positive effects on growth of broilers.
Scalable flame synthesis of SiO2 nanowires: dynamics of growth.
Tricoli, Antonio; Righettoni, Marco; Krumeich, Frank; Stark, Wendelin J; Pratsinis, Sotiris E
2010-11-19
Silica nanowire arrays were grown directly onto plain glass substrates by scalable flame spray pyrolysis of organometallic solutions (hexamethyldisiloxane or tetraethyl orthosilicate). The silicon dioxide films consisted of a network of interwoven nanowires from a few to several hundred nanometres long (depending on the process conditions) and about 20 nm in diameter, as determined by scanning electron microscopy. These films were formed rapidly (within 10-20 s) at high growth rates (ca 11-30 nm s(-1)) by chemical vapour deposition (surface growth) at ambient conditions on the glass substrate as determined by thermophoretic sampling of the flame aerosol and microscopy. In contrast, on high purity quartz nearly no nanowires were grown while on steel substrates porous SiO(2) films were formed. Functionalization with perfluorooctyl triethoxysilane converted the nanowire surface from super-hydrophilic to hydrophobic. Additionally, their hermetic coating by thin carbon layers was demonstrated also revealing their potential as substrates for synthesis of other functional 1D composite structures. This approach is a significant step towards large scale synthesis of SiO(2) nanowires facilitating their utilization in several applications.
Regularization in kernel learning
Mendelson, Shahar; 10.1214/09-AOS728
2010-01-01
Under mild assumptions on the kernel, we obtain the best known error rates in a regularized learning scenario taking place in the corresponding reproducing kernel Hilbert space (RKHS). The main novelty in the analysis is a proof that one can use a regularization term that grows significantly slower than the standard quadratic growth in the RKHS norm.
Zhao, Xiaoyang; T'ien, James S.; Ferkul, Paul V.; Olson, Sandra L.
2015-01-01
As a part of the NASA BASS and BASS-II experimental projects aboard the International Space Station, flame growth, spread and extinction over a composite cotton-fiberglass fabric blend (referred to as the SIBAL fabric) were studied in low-speed concurrent forced flows. The tests were conducted in a small flow duct within the Microgravity Science Glovebox. The fuel samples measured 1.2 and 2.2 cm wide and 10 cm long. Ambient oxygen was varied from 21% down to 16% and flow speed from 40 cm/s down to 1 cm/s. A small flame resulted at low flow, enabling us to observe the entire history of flame development including ignition, flame growth, steady spread (in some cases) and decay at the end of the sample. In addition, by decreasing flow velocity during some of the tests, low-speed flame quenching extinction limits were found as a function of oxygen percentage. The quenching speeds were found to be between 1 and 5 cm/s with higher speed in lower oxygen atmosphere. The shape of the quenching boundary supports the prediction by earlier theoretical models. These long duration microgravity experiments provide a rare opportunity for solid fuel combustion since microgravity time in ground-based facilities is generally not sufficient. This is the first time that a low-speed quenching boundary in concurrent spread is determined in a clean and unambiguous manner.
Gamma irradiation of peanut kernel to control mold growth and to diminish aflatoxin contamination
Y.-Y. Chiou, R.
1996-09-01
Peanut kernel inoculated with Aspergillus parasiticus conidia were gamma irradiated with 0, 2.5, 5.0 and 10 kGy using Co60. Levels higher than 2.5 kGy were effective in retarding the outgrowth of A. parasiticus and reducing the population of natural mold contaminants. However, complete elimination of these molds was not achieved even at the dose of 10 kGy. After 4 wk incubation of the inoculated kernels in a humidified condition, aflatoxins produced by the surviving A. parasiticus were 69.12, 2.42, 57.36 and 22.28 μ/g, corresponding to the original irradiation levels. Peroxide content of peanut oils prepared from the irradiated peanuts increased with increased irradiation dosage. After storage, at each irradiation level, peroxide content in peanuts stored at -14°C was lower than that in peanuts stored at an ambient temperature. TBA values and CDHP contents of the oil increased with increased irradiation dosage and changed slightly after storage. However, fatty acid contents of the peanut oil varied in a limited range as affected by the irradiation dosage and storage temperature. The SDS-PAGE protein pattern of peanuts revealed no noticeable variation of protein subunits resulting from irradiation and storage.
Directory of Open Access Journals (Sweden)
P. Aarumugam
2013-06-01
Full Text Available The growth promoting potential of fruits wastes, mango seed kernel, banana peel and papaya peel on the freshwater prawn, Macrobrachium rosenbergii post larvae (PL was evaluated. Basal diet equated to 35% protein was prepared by using soybean meal, groundnut oilcake, horse gram and wheat flour. Each fruit waste powder was separately incorporated with basal diet at a proportion of 10%. Sunflower oil was used as lipid source. Egg albumin and tapioca flour were used as binding agents. Vitamin B-complex with Vitamin-C was also mixed. Feed without any fruit waste was served as control. M. rosenbergii PL (length: 1.2-1.4 cm; weight: 0.09- 0.13 g was fed with these feeds for a period of 90 days. Significant improvements in the nutritional indices (survival rate, weight gain, biomass index, specific growth rate and condition factor, concentrations of biochemical constituents (total protein, carbohydrate and lipid, levels of non-enzymatic antioxidants (vitamin-C and E, content of minerals (Na+ and K+, activities of digestive enzymes (protease, amylase and lipase, and profiles of essential amino acids and fatty acids were recorded in fruits wastes incorporated feeds fed PL when compared with control (P< 0.003 – 0.878. The overall results indicated the fact that mango seed kernel incorporated feed was produced the best performance, followed by better performance of banana peel and good performance of papaya peel. These fruits wastes incorporated feeds enhance digestive enzymes activities and act as appetizer, which in turn enhances food utilization and ultimately yielded better survival and growth of M. rosenbergii PL. Therefore, these fruits wastes have considerable potentials in sustainable development of Macrobrachium culture.
Ferruz, Elena; Loran, Susana; Herrera, Marta; Gimenez, Isabel; Bervis, Noemi; Barcena, Carmen; Carramiñana, Juan Jose; Juan, Teresa; Herrera, Antonio; Ariño, Agustin
2016-10-01
The possible role of natural phenolic compounds in inhibiting fungal growth and toxin production has been of recent interest as an alternative strategy to the use of chemical fungicides for the maintenance of food safety. Fusarium is a worldwide fungal genus mainly associated with cereal crops. The most important Fusarium mycotoxins are trichothecenes, zearalenone, and fumonisins. This study was conducted to evaluate the potential of four natural phenolic acids (caffeic, ferulic, p-coumaric, and chlorogenic) for the control of mycelial growth and mycotoxin production by six toxigenic species of Fusarium . The addition of phenolic acids to corn meal agar had a marked inhibitory effect on the radial growth of all Fusarium species at levels of 2.5 to 10 mM in a dose-response pattern, causing total inhibition (100%) in all species except F. sporotrichioides and F. langsethiae . However, the effects of phenolic acids on mycotoxin production in maize kernels were less evident than the effects on growth. The fungal species differed in their responses to the phenolic acid treatments, and significant reductions in toxin concentrations were observed only for T-2 and HT-2 (90% reduction) and zearalenone (48 to 77% reduction). These results provide data that could be used for developing pre- and postharvest strategies for controlling Fusarium infection and subsequent toxin production in cereal grains.
Formation, growth, and transport of soot in a three-dimensional turbulent non-premixed jet flame
Attili, Antonio
2014-07-01
The formation, growth, and transport of soot is investigated via large scale numerical simulation in a three-dimensional turbulent non-premixed n-heptane/air jet flame at a jet Reynolds number of 15,000. For the first time, a detailed chemical mechanism, which includes the soot precursor naphthalene and a high-order method of moments are employed in a three-dimensional simulation of a turbulent sooting flame. The results are used to discuss the interaction of turbulence, chemistry, and the formation of soot. Compared to temperature and other species controlled by oxidation chemistry, naphthalene is found to be affected more significantly by the scalar dissipation rate. While the mixture fraction and temperature fields show fairly smooth spatial and temporal variations, the sensitivity of naphthalene to turbulent mixing causes large inhomogeneities in the precursor fields, which in turn generate even stronger intermittency in the soot fields. A strong correlation is apparent between soot number density and the concentration of naphthalene. On the contrary, while soot mass fraction is usually large where naphthalene is present, pockets of fluid with large soot mass are also frequent in regions with very low naphthalene mass fraction values. From the analysis of Lagrangian statistics, it is shown that soot nucleates and grows mainly in a layer close to the flame and spreads on the rich side of the flame due to the fluctuating mixing field, resulting in more than half of the total soot mass being located at mixture fractions larger than 0.6. Only a small fraction of soot is transported towards the flame and is completely oxidized in the vicinity of the stoichiometric surface. These results show the leading order effects of turbulent mixing in controlling the dynamics of soot in turbulent flames. Finally, given the difficulties in obtaining quantitative data in experiments of turbulent sooting flames, this simulation provides valuable data to guide the development of
Kandianis, Catherine B; Michenfelder, Abigail S; Simmons, Susan J; Grusak, Michael A; Stapleton, Ann E
2013-01-01
The improvement of grain nutrient profiles for essential minerals and vitamins through breeding strategies is a target important for agricultural regions where nutrient poor crops like maize contribute a large proportion of the daily caloric intake. Kernel iron concentration in maize exhibits a broad range. However, the magnitude of genotype by environment (GxE) effects on this trait reduces the efficacy and predictability of selection programs, particularly when challenged with abiotic stress such as water and nitrogen limitations. Selection has also been limited by an inverse correlation between kernel iron concentration and the yield component of kernel size in target environments. Using 25 maize inbred lines for which extensive genome sequence data is publicly available, we evaluated the response of kernel iron density and kernel mass to water and nitrogen limitation in a managed field stress experiment using a factorial design. To further understand GxE interactions we used partition analysis to characterize response of kernel iron and weight to abiotic stressors among all genotypes, and observed two patterns: one characterized by higher kernel iron concentrations in control over stress conditions, and another with higher kernel iron concentration under drought and combined stress conditions. Breeding efforts for this nutritional trait could exploit these complementary responses through combinations of favorable allelic variation from these already well-characterized genetic stocks.
Mark A. Dietenberger
2010-01-01
Effective mitigation of external fires on structures can be achieved flexibly, economically, and aesthetically by (1) preventing large-area ignition on structures by avoiding close proximity of burning vegetation; and (2) stopping flame travel from firebrands landing on combustible building objects. Using bench-scale and mid-scale fire tests to obtain flammability...
Presumed PDF Modeling of Early Flame Propagation in Moderate to Intense Turbulence Environments
Carmen, Christina; Feikema, Douglas A.
2003-01-01
The present paper describes the results obtained from a one-dimensional time dependent numerical technique that simulates early flame propagation in a moderate to intense turbulent environment. Attention is focused on the development of a spark-ignited, premixed, lean methane/air mixture with the unsteady spherical flame propagating in homogeneous and isotropic turbulence. A Monte-Carlo particle tracking method, based upon the method of fractional steps, is utilized to simulate the phenomena represented by a probability density function (PDF) transport equation. Gaussian distributions of fluctuating velocity and fuel concentration are prescribed. Attention is focused on three primary parameters that influence the initial flame kernel growth: the detailed ignition system characteristics, the mixture composition, and the nature of the flow field. The computational results of moderate and intense isotropic turbulence suggests that flames within the distributed reaction zone are not as vulnerable, as traditionally believed, to the adverse effects of increased turbulence intensity. It is also shown that the magnitude of the flame front thickness significantly impacts the turbulent consumption flame speed. Flame conditions studied have fuel equivalence ratio s in the range phi = 0.6 to 0.9 at standard temperature and pressure.
2014-01-01
In this study, the effect of xylanase and cellulase supplementation in palm kernel meal (PKM) based diet on growth performance, volatile fatty acids (VFAs) and the caecal bacterial populations of broiler chickens were investigated. Seventy five day old male Cobb broiler chicks were randomly allocated to three dietary treatment groups receiving T1 (20% PKM-based diet without enzyme), T2 (20% PKM-based diet with xylanase) and T3 (20% PKM-based diet with cellulase). Each enzyme was supplemented ...
Kong, Lizhuo; Tu, Kunkun; Guan, Hao; Wang, Xiaoqing
2017-06-01
Zinc oxide (ZnO) nanorod arrays were successfully assembled on the wood surface in situ via a two-step process consisting of formation of ZnO seeds and subsequent crystal growth under hydrothermal conditions at a low temperature. The morphology and crystalline structure of the formed ZnO nanorods were studied by field-emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD). Highly dense and uniform arrays of ZnO nanorods with well-defined hexagonal facets were generated on the wood surface by tuning the concentration of the ZnO growth solution during the hydrothermal treatment. Accelerated weathering tests indicated that the assembled ZnO nanorod arrays were highly protective against UV radiation and greatly enhanced the photostability of the coated wood. Meanwhile, the ZnO nanorod-coated wood can withstand continuous exposure to flame with only minor smoldering in contrast with the pristine wood catching fire easily and burning rapidly. Moreover, when further modified with low-surface-energy stearic acid, the ZnO nanorod decorated wood surface can be transformed into a superhydrophobic surface, with a water contact angle (CA) of ∼154°. Such ZnO nanorod-modified woods with enhanced photostability, flame retardancy and water repellency offer an interesting alternative to conventional wood preservation strategies, highlighting their potential applications in some novel wood products.
Athanassiou, Christos G; Opit, George P; Throne, James E
2010-06-01
Differences in stored-product psocid progeny production as a function of commodity type, percentage of cracked kernels, and wheat class were examined using laboratory bioassays. Population growth of Liposcelis bostrychophila Badonnel, Liposcelis decolor (Pearman), Liposcelis paeta Pearman, and Liposcelis entomophila (Enderlein) (Psocoptera: Liposcelididae) was highest on sorghum Sorghum bicolor (L.) Moench, followed by wheat, Triticum aestivum L., and rice, Oryza sativa L., whereas progeny production was negligible on wheat germ. In a second experiment that did not include L. entomophila, population growth was examined on wheat containing 0, 1, 5, 10, 20, 50, and 100% cracked kernels. Progeny production did not increase as cracked kernel content increased. Instead, progeny production peaked at 20% for L. bostrychophila adults and nymphs, at 10% for L. decolor, and at 50% for L. paeta adults; no further increases were noted beyond these levels of cracked wheat content. In a third experiment that did not include L. entomophila, progeny production was examined on eight classes of wheat: hard red winter, hard red spring, soft white winter, soft white spring, soft club, durum, soft red winter, and hard white. Overall, progeny production was higher on durum wheat than on the other classes. The results indicate that there are considerable variations in psocid population growth among the different commodities tested, and this information may be used to predict the degree to which stored commodities are susceptible to psocid infestation.
Experimental characterization of methane inverse diffusion flame
Elbaz, Ayman M.
2014-06-26
This article presents 10-kHz images of OH-PLIF simultaneously with 2-D PIV measurements in an inverse methane diffusion flame. Under a constant fuel flow rate, the central air jet Re was varied, leading to air to fuel velocity ratio, Vr, to vary from 8.3 to 66.5. Starting from Vr = 20.7, the flame is commonly characterized by three distinct zones. The length of the lower fuel entrainment region is inversely proportional to Vr. The flames investigated resemble a string shear layer confining this zone, and converging into the second distinct region, the flame neck zone. The third region is the rest of the flame, which spreads in a jet-like manner. The inverse diffusion flames exhibit varying degrees of partial premixing, depending upon on the velocity ratio Vr, and this region of partial premixing evolves into a well-mixed reaction zone along the flame centerline. The OH distribution correlated with the changes in the mean characteristics of the flow through reduction in the local Reynolds number due to heat release. The existence of a flame suppresses or laminarizes the turbulence at early axial locations and promotes fluctuations at the flame tip for flames with Vr < 49.8. In addition, the flame jet width can be correlated to the OH distribution. In upstream regions of the flames, the breaks in OH are counterbalanced by flame closures and are governed by edge flame propagation. These local extinctions were found to occur at locations where large flow structures were impinging on the flame and are associated with a locally higher strain rate or correlated to the local high strain rates at the flame hole edges without this flow impinging. Another contributor to re-ignition was found to be growing flame kernels. As the flames approach global blow-off, these kernels become the main mechanism for re-ignition further downstream of the flames. At low Vr, laminarization within the early regions of the flame provides an effective shield, preventing the jet flow from
Directory of Open Access Journals (Sweden)
Niwat MUANGKEOW
2013-04-01
Full Text Available The objective of the current study was to investigate the effect of palm kernel meal (PKM and Aspergillus wentii TISTR 3075 fermented PKM at various levels on growth performance and nutrient digestibility of broiler chickens. Four hundred and thirty-two day old Ross-308 broiler chicks were used in a 2 × 4 factorial in completely randomized design with one control. Two kinds of PKM (unfermented and A. wentii fermented PKM in broiler rations were used, each at 10, 20, 30 and 40 %. Increasing level of PKM or A. wentii fermented PKM higher than 20 % significantly decreased feed intake and average weight gain also decreased, while feed efficiency declined. Feed intake of growing broilers during 0 to 21 d of age fed with PKM decreased linearly followed by a quadratic response during the finishing period (22 to 42 d of age while those broilers fed with A. wentii fermented PKM exhibited a quadratic response throughout the 42 d feeding trial. Data show that feed intake and average weight gain response when fed with PKM decreased linearly while when fed with A. wentii fermented PKM it was quadratic and then slowly decreased. The poor performance of the birds fed PKM or A. wentii fermented PKM at high levels might be due to the higher in crude fiber content and the lower nitrogen retention. In the growing period PKM or A. wentii fermented PKM no more than 20 % of the broiler ration should be used while in the finishing period PKM up to 30 % is effective.
Directory of Open Access Journals (Sweden)
Nesseim, TDT.
2017-01-01
Full Text Available Jatropha curcas is a tropical plant belonging to the Euphorbiaceae family whose cultivation has been largely promoted in recent years for the production of biofuels. The kernel of the seed contains approximately 55% lipid in dry matter and the meal obtained could be an exceptional source of proteins for family poultry farming, after treatments to remove toxic and anti-nutritional compounds. The ingestion and the growth performance of J. curcas kernel meal (JKM, obtained after partial physico-chemical de-oiling combined or not with heating was evaluated in broiler chickens and chicks. Sixty unsexed broiler chickens, 30 day-old, divided into three groups as well as twenty broiler chicks, 1 day-old, divided into two groups were used in two experiments. In experiment 1, jatropha kernel was de-oiled and incorporated into a control fattening feed at 40 and 80g/kg (diets 4JKM1 and 8JM1. In experiment 2, jatropha kernel meal obtained in experiment 1 was heat treated and incorporated into a growing diet at 80g/kg (diet 8JKM2. Daily dietary intakes as well as weight gain of the animals were affected by the incorporation of jatropha kernel meal in the ration. In experiment 1, average daily feed intake (ADFI1 of 139.2, 55.2 and 23.4g/day/animal and also average daily weight gain (ADWG1 of 61.9, 18.5 and -7.7g/animal were obtained respectively for the groups fed with diets 0JKM1, 4JKM1 and 8JKM1. In experiment 2, Average daily feed intake (ADFI2 of 18.7 and 3.1g/day/animal and also average daily weight gain (ADWG2 of 7.1 and 1.9g/animal were obtained respectively for the groups fed with diets 0JKM2 and 8JKM2. In both experiment, feed conversion ratio (FCR was also affected by the dietary treatments and the overall mortality rate showed an increase according to levels of jatropha kernel meal in diet.
Mishra, Yogendra K.; Gröttrup, Jorit; Smazna, Daria; Hölken, Iris; Hoppe, Mathias; Sindushree, Sindushree; Kaps, Sören; Lupan, Oleg; Seidel, Jan; Monteiro, Teresa; Tiginyanu, Ion M.; Kienle, Lorenz; Ronning, Carsten; Schulte, Karl; Fiedler, Bodo; Adelung, Rainer
2017-06-01
The recent flame based growth strategy offers a simple and versatile fabrication of various (one, two, and three-dimensional) nano- and microstructures from different metal oxides (ZnO, SnO2, Fe2O3, etc.) in a desired manner.[1] ZnO structures ranging from nanoscales wires to macroscopic and highly porous 3D interconnected tetrapod networks have been successfully synthesized, characterized and utilized for various applications. The ZnO micro- and nanoneedles grown at walls in silicon trenches showed excellent whispering gallery mode resonances and photocatalytic properties.[2] Using the same strategy, large polycrystalline micro- and nanostructured ZnO platelets can be grown with grains interconnected together via grain boundaries and these grain boundaries exhibit a higher conductivity as compared to individual grains.[3] This flame transport synthesis (FTS) approach offers the growth of a large amount of ZnO tetrapods which have shown interesting applications because of their 3D spatial shape and micro-and nanoscale size, for example, interconnected tetrapods based devices for UV-detection and gas sensing.[4-5] Because of their complex 3D shape, ZnO tetrapods can be used as efficient filler particles for designing self-reporting,[6] and other interesting composites. The nanostructured materials exhibit an important role with respect to advanced biomedical applications as grown ZnO structures have shown strong potentials for antiviral applications.[7] Being mechanically strong and micro-and nanoscale in dimensions, these ZnO tetrapods can be easily doped with other elements or hybridized with various nanoparticles in form of hybrid ZnO tetrapods which are suitable for various multifunctional applications, for example, these hybrid tetrapods showed improved gas sensing properties.[8] The sacrificial nature of ZnO allows the for growth of new tetrapods and 3D network materials for various advanced applications, for example, highly porous and ultra light carbon based
Hanft, J M; Jones, R J
1986-06-01
Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.
Energy Technology Data Exchange (ETDEWEB)
Kang, K.T.; Hwang, J.Y.; Chung, S.H. [Seoul National Univ. (Korea, Republic of). Dept. of Mechanical Engineering; Lee, W. [Dankook Univ., Seoul (Korea, Republic of). Dept. of Mechanical Engineering
1997-04-01
Soot zone structures of counterflow and co-flow diffusion flames have been studied experimentally using the soot extinction-scattering, polycyclic aromatic hydrocarbon fluorescence, and laser Doppler velocimetry measurements. The counterflow flame has been numerically modelled with detailed chemistry. Results show that two different categories of sooting flame structures can be classified depending on the relative transport of soot particles to flames. These are the soot formation-oxidation flame and the soot formation flame. The soot formation-oxidation flame characteristics are observed in counterflow flames when located on the fuel side and in normal co-flow flames. In this case, soot particles are transported toward the high temperature region or the flame and experience soot inception, coagulation-growth, and oxidation. The soot formation flame characteristics are observed in counterflow flames when located on the oxidizer side and in inverse co-flow flames. In this case, soot particles are transported away from the flame without experiencing oxidation and finally leak through the stagnation plane in counterflow flames or leave the flame in inverse co-flow flames. Sooting limit measurements in both flames also substantiate the two different sooting flame structures and their characteristics.
DEFF Research Database (Denmark)
Ranjitkar, Samir; Engberg, Ricarda Greuel
2016-01-01
% and 30% in maize-based diets. Broilers were orally inoculated with 2 × 105 log cfu/ml C. jejuni on day 14. Four birds from each pen were randomly selected and killed by cervical dislocation on days 3, 6, 9, 14 and 21 post infection and intestinal contents from ileum, caeca and rectum as well as liver......An infection trial and a production trial over 35 days were conducted in parallel to study the influence of feeding crimped kernel maize silage (CKMS) on the intestinal Campylobacter jejuni colonization and broiler performance, respectively. The CKMS was used at dietary inclusion levels of 15...... supplemented with 15% CKMS was comparable with the control maize-based feed, whereas addition of 30% CKMS reduced broiler body weight (P
Mbunwen, Ndofor-Foleng Harriet; Ngongeh, Lucas Atehmengo; Okolie, Peter Nzeribe; Okoli, Emeka Linus
2015-08-01
One hundred fifty Anak and 120 Nigerian heavy local ecotype (NHLE) chickens were used to study the effects of feeding graded levels of mango seed kernel meal (MKM) replacing maize diet on growth traits and haematological parameters. A 2 × 5 factorial arrangement was employed: two breeds and five diets. The birds were randomly allocated to five finisher diets formulated such that MKM replaced maize at 0, 10, 20, 30 and 40% (T1, T2, T3, T4 and T5) inclusion levels, respectively. The effect of breed and dietary treatments on growth performance and blood characteristics were determined. The results showed a significant (P 0.05) when the breeds and treatments were compared. It was concluded that inclusion of dietary MKM below 30% could replace maize in the diets of Anak and NHLE growing chickens without adverse effect on growth performance and blood constituents. This work suggests that genetic differences exist in growth traits of these breeds of chickens. This advantage could be useful in breed improvement programmes and better feeding managements of the NHLE and Anak chickens.
Torres, Leticia; Orazio, Carl E.; Peterman, Paul H.; Patino, Reynaldo
2013-01-01
Little is known about the effects of brominated flame retardants in teleosts and some of the information currently available is inconsistent. This study examined effects of dietary exposure to 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) on thyroid condition, body mass and size, and gonadal development of zebrafish. Pubertal, 49-day-old (posthatch) fish were fed diets without BDE-47 (control) or with 1, 5 or 25 μg/g BDE-47/diet. Treatments were conducted in triplicate 30-L tanks each containing 50 zebrafish, and 15 fish per treatment (5 per tank) were sampled at days 40, 80 and 120 of exposure. Measurements were taken of body mass, standard length, head depth and head length. Sex (at 40–120 days of exposure), germ cell stage (at 40 days) and thyroid condition (at 120 days; follicular cell height, colloid depletion, angiogenesis) were histologically determined. Whole-body BDE-47 levels at study completion were within the high end of levels reported in environmentally exposed (wild) fishes. Analysis of variance was used to determine differences among treatments at each sampling time. No effects were observed on thyroid condition or germ cell stage in either sex. Reduced head length was observed in females exposed to BDE-47 at 80 days but not at 40 or 120 days. In males, no apparent effects of BDE-47 were observed at 40 and 80 days, but fish exposed to 25 μg/g had lower body mass at 120 days compared to control fish. These observations suggest that BDE-47 at environmentally relevant whole-body concentrations does not affect thyroid condition or pubertal development of zebrafish but does affect growth during the juvenile-to-adult transition, especially in males.
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...... analysis, looking at the class of subsampled realised kernels and we derive the limit theory for this class of estimators. We find that subsampling is highly advantageous for estimators based on discontinuous kernels, such as the truncated kernel. For kinked kernels, such as the Bartlett kernel, we show...... 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...
Earth Data Analysis Center, University of New Mexico — Flame length was modeled using FlamMap, an interagency fire behavior mapping and analysis program that computes potential fire behavior characteristics. The tool...
Trajectory, Development, and Temperature of Spark Kernels Exiting into Quiescent Air (Preprint)
2012-04-01
measurements of the Hencken burner flames. Jay Gore is the academic advisor for the corresponding author. His tutelage is gratefully acknowledged...165-184. 6Au, S., Haley , R., Smy, P., “The Influence of the Igniter-Induced Blast Wave Upon the Initial Volume and Expansion of the Flame Kernel
Ranjitkar, Samir; Engberg, Ricarda Margarete
2016-01-01
An infection trial and a production trial over 35 days were conducted in parallel to study the influence of feeding crimped kernel maize silage (CKMS) on the intestinal Campylobacter jejuni colonization and broiler performance, respectively. The CKMS was used at dietary inclusion levels of 15% and 30% in maize-based diets. Broilers were orally inoculated with 2 × 10(5) log cfu/ml C. jejuni on day 14. Four birds from each pen were randomly selected and killed by cervical dislocation on days 3, 6, 9, 14 and 21 post infection and intestinal contents from ileum, caeca and rectum as well as liver samples were taken. Body weight and feed consumption of broilers were registered on days 13, 22 and 35. On day 35, litter dry matter (DM) was measured and the condition of the foot pads was evaluated. There was no significant effect of CKMS on the colonization of C. jejuni. Body weight of the broilers supplemented with 15% CKMS was comparable with the control maize-based feed, whereas addition of 30% CKMS reduced broiler body weight (P < 0.001). However, DM intake and feed conversion ratio were the same in all three dietary treatments. Furthermore, the foot pad condition of broilers significantly improved with the inclusion of CKMS on broiler diets as a result of a higher DM content in the litter material. It is concluded that CKMS did not influence intestinal Campylobacter colonization, but improved the foot pad health of broilers.
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...
2008-08-01
Berg et al., 1984] has been used in a machine learning context by Cuturi and Vert [2005]. Definition 26 Let (X ,+) be a semigroup .2 A function ϕ : X...R is called pd (in the semigroup sense) if k : X × X → R, defined as k(x, y) = ϕ(x + y), is a pd kernel. Likewise, ϕ is called nd if k is a nd...kernel. Accordingly, these are called semigroup kernels. 7.3 Jensen-Shannon and Tsallis kernels The basic result that allows deriving pd kernels based on
Approximate kernel competitive learning.
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.
Flames in vortices & tulip-flame inversion
Dold, J. W.
This article summarises two areas of research regarding the propagation of flames in flows which involve significant fluid-dynamical motion [1]-[3]. The major difference between the two is that in the first study the fluid motion is present before the arrival of any flame and remains unaffected by the flame [1, 2] while, in the second study it is the flame that is responsible for all of the fluid dynamical effects [3]. It is currently very difficult to study flame-motion in which the medium is both highly disturbed before the arrival of a flame and is further influenced by the passage of the flame.
The Growth Analysis in the Kernel Filling Process of K-Type Hybrid 901 and Its Parent Wheat
Institute of Scientific and Technical Information of China (English)
GONG Yue-hua; LIU Ying-zhou; GAO Jun-feng
2005-01-01
Using Matlab software, the grain filling process of hybrid wheat 901 and its parents was fitted by Richards equation W = A/(1 +Be-kt in order to study the characteristics of grain filling of the hybrid. The active grain growth period of the hybrid was 6 d longer than that of Shaan 229, and its final grain weight (43.7 g/1000 grains) was higher than that of Shaan229 (36.3 g/1 000 grains). N values of 901 and R205 were both less than 1, and their grain growth was faster in the early filling stage, while slower in the middle-late stage. N value of Shaan 229 was ＞1, and its growth was slower in the early stage and faster in the middle stage. The period of early stage of 901 was shorter and of middle-late stage was longer. The situation of Shaan 229 was totally reversed. For parents, the father plant R205 was similar to hybrid wheat 901, whereas its mother plant K3314A similar to Shaan 229. It has been found that Richards equation was more suitable for fitting the grain filling process of wheat than Logistic equation.
Kumar, V; Akinleye, A O; Makkar, H P S; Angulo-Escalante, M A; Becker, K
2012-02-01
Jatropha platyphylla is available on the pacific coast from Sinaloa to Michoacán including the Nayarit and Jalisco states in Mexico. The seeds of J. platyphylla are rich in oil and protein, and the kernel meal (JPKM) prepared after oil extraction contains 70-75% crude protein (CP). Contents of essential amino acids (except lysine) are higher in JPKM than in soybean meal (SBM). Phorbol-esters, the main toxin present in most Jatropha species is absent in J. platyphylla. Heat-treated JPKM (H-JPKM) was evaluated as a protein supplement in tilapia feed and compared with that of SBM and fish meal (FM). Nile tilapia (Oreochromis niloticus L.) fingerlings (15 fish; av. body mass 13.9 ± 0.17 g) were randomly distributed in three groups with five replicates each. A 12-week experiment was conducted in a respirometer system to evaluate the growth performance, nutrient utilization and energy budget. Nile tilapia fingerlings were fed three iso-nitrogenous diets (36% CP): Control containing FM, and Jatropha and Soybean diets in which 62.5% of FM protein was replaced by H-JPKM and SBM respectively. The growth performance, feed conversion ratio, protein efficiency ratio, apparent lipid conversion and energy retention did not differ significantly among the three groups. Higher protein productive value was observed in plant protein fed groups. Average metabolic rate, energy expenditure per g protein fed and retained in the body did not differ significantly among the three groups. Conclusively, Nile tilapia fed plant protein (heated JPKM and SBM) and FM protein-based diets exhibited equal average metabolic rate which indicate that JPKM can be used as a protein source in aqua feed.
Optimized Kernel Entropy Components.
Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau
2016-02-25
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.
Isolation of bacterial endophytes from germinated maize kernels.
Rijavec, Tomaz; Lapanje, Ales; Dermastia, Marina; Rupnik, Maja
2007-06-01
The germination of surface-sterilized maize kernels under aseptic conditions proved to be a suitable method for isolation of kernel-associated bacterial endophytes. Bacterial strains identified by partial 16S rRNA gene sequencing as Pantoea sp., Microbacterium sp., Frigoribacterium sp., Bacillus sp., Paenibacillus sp., and Sphingomonas sp. were isolated from kernels of 4 different maize cultivars. Genus Pantoea was associated with a specific maize cultivar. The kernels of this cultivar were often overgrown with the fungus Lecanicillium aphanocladii; however, those exhibiting Pantoea growth were never colonized with it. Furthermore, the isolated bacterium strain inhibited fungal growth in vitro.
The initial development of a tulip flame
Energy Technology Data Exchange (ETDEWEB)
Matalon, M.; Mcgreevy, J.L. [Northwestern Univ., Evanston, IL (United States)
1994-12-31
The initial development of a ``tulip flame``, often observed during flame propagation in closed tubes, is attributed to a combustion instability. The roles of hydrodynamic and of the diffusional-thermal processes on the onset of instability are investigated through a linear stability analysis in which the growth or decay of small disturbances, superimposed on an otherwise smooth and planar flame front, are followed. A range of the Markstein parameter, related to the mixture composition through an appropriately defined Lewis number, has been identified where a tulip flame could be observed. For a given value of the Markstein parameter within this range, a critical wavelength is identified as the most unstable mode. This wavelength is directly related to the minimal aspect ratio of the tube where a tulip flame could be observed. The time of onset of instability is identified as the time when the most unstable disturbance, associated with the critical wavelength, grows at a faster rate than the flame front itself and exceeds a certain threshold. This occurs after the flame has propagated a certain distance down the tube: a value which has been explicitly determined in terms of the relevant parameters. Experimental records on the tulip flame phenomenon support the finding of the analysis. That is, the tulip flame forms after the flame has traveled half the tube`s length, it does not form in short tubes, and its formation depends on the mixture composition and on the initial pressure in the tube.
Stabilization of a premixed methane-air flame with a high repetition nanosecond laser-induced plasma
Yu, Yang; Li, Xiaohui; An, Xiaokang; Yu, Xin; Fan, Rongwei; Chen, Deying; Sun, Rui
2017-07-01
Laser-induced plasma ignition has been applied in various combustion systems, however, work on flame stabilization with repetitive laser-induced plasma (LIP) is rather limited. In this paper, stabilization of a premixed methane-air flame with a high repetition nanosecond LIP is reported. The plasma energy coupling and the temporal evolution of the flame kernels generated by the LIPs are investigated with different laser repetition rates, i.e., 1 Hz, 100 Hz and 250 Hz, respectively. The plasma energy coupling is not affected in the air flow and in the premixed methane-air flow with the applied laser repetition rates. Continuous combustion flame stabilization has been achieved with LIPs of 100 Hz and 250 Hz, in terms of catch-up and merging of the consecutive flame kernels. The flame kernel formed by the last LIP does not affect the evolution of the newly formed flame kernel by the next LIP. The catch-up distance, defined as the distance from the LIP initiation site to the flame kernel catch-up position, is estimated for different laser repetition rates based on the temporal evolution of the flame kernels. A higher laser repetition rate will lead to a shorter catch-up distance which is beneficial for flame stabilization. The up limit for the laser repetition rate to realize effective flame stabilization is determined from the critical inter-pulse delay defined from the onset of the LIP to the return of the initially contraflow propagating lower front to the LIP initiation site. The up limit is 377 Hz under the flow conditions of this work (equivalence ratio of 1, flow speed of 2 m/s, and Reynolds number of 1316).
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`.
Kernel Affine Projection Algorithms
Directory of Open Access Journals (Sweden)
José C. Príncipe
2008-05-01
Full Text Available The combination of the famed kernel trick and affine projection algorithms (APAs yields powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up study of the recently introduced kernel least-mean-square algorithm (KLMS. KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance. More interestingly, it provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares (KRLS, and regularization networks. Therefore, many insights can be gained into the basic relations among them and the tradeoff between computation complexity and performance. Several simulations illustrate its wide applicability.
Kernel Affine Projection Algorithms
Liu, Weifeng; Príncipe, José C.
2008-12-01
The combination of the famed kernel trick and affine projection algorithms (APAs) yields powerful nonlinear extensions, named collectively here, KAPA. This paper is a follow-up study of the recently introduced kernel least-mean-square algorithm (KLMS). KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance. More interestingly, it provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares (KRLS), and regularization networks. Therefore, many insights can be gained into the basic relations among them and the tradeoff between computation complexity and performance. Several simulations illustrate its wide applicability.
Impact of flame-wall interaction on premixed flame dynamics and transfer function characteristics
Kedia, K.S.
2011-01-01
In this paper, we numerically investigate the response of a perforated-plate stabilized laminar methane-air premixed flame to imposed inlet velocity perturbations. A flame model using detailed chemical kinetics mechanism is applied and heat exchange between the burner plate and the gas mixture is incorporated. Linear transfer functions, for low mean inlet velocity oscillations, are analyzed for different equivalence ratio, mean inlet velocity, plate thermal conductivity and distance between adjacent holes. The oscillations of the heat exchange rate at the top of the burner surface plays a critical role in driving the growth of the perturbations over a wide range of conditions, including resonance. The flame response to the perturbations at its base takes the form of consumption speed oscillations in this region. Flame stand-off distance increases/decreases when the flame-wall interaction strengthens/weakens, impacting the overall dynamics of the heat release. The convective lag between the perturbations and the flame base response govern the phase of heat release rate oscillations. There is an additional convective lag between the perturbations at the flame base and the flame tip which has a weaker impact on the heat release rate oscillations. At higher frequencies, the flame-wall interaction is weaker and the heat release oscillations are driven by the flame area oscillations. The response of the flame to higher amplitude oscillations are used to gain further insight into the mechanisms. © 2010 Published by Elsevier Inc. on behalf of The Combustion Institute. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Okada, Katsuyuki; Komatsu, Shojiro; Ishigaki, Takamasa; Matsumoto, Seiichiro; Moriyoshi, Yusuke (National Inst. for Research in Inorganic Materials, Tsukuba, Ibaraki (Japan))
1992-02-01
When diamond particles deposited on a molybdenum substrate in a C{sub 2}H{sub -}O{sub 2} combustion-flame were kept for one year in the ambient atmosphere at room temperature, spontaneous whisker growth from an interlayer of Mo{sub 2}C beneath the diamond particles took place. The whiskers were clarified by electron probe micro-analysis (EPMA) and transmission electron microscopy (TEM) in a polycrystal composed of MoO{sub 2}, MoOC, and Mo{sub 2}C. The growth mechanism of them is discussed from two different points of view as follows: One is that the oxidation of an interlayer of Mo{sub 2}C beneath a diamond particle effectively reduces the surface free energy between the interlayer and diamond particle; consequently, the whisker can grow by using a screw dislocation. The other is that the internal stress existing between a diamond particle and an Mo{sub 2}C interlayer provides a very reactive zone where the growth of whisker takes place through the oxidation of Mo{sub 2}C. (orig.).
Directory of Open Access Journals (Sweden)
R. Lakshmi
2014-06-01
Full Text Available A kernel $J$ of a digraph $D$ is an independent set of vertices of $D$ such that for every vertex $w,in,V(D,setminus,J$ there exists an arc from $w$ to a vertex in $J.$ In this paper, among other results, a characterization of $2$-regular circulant digraph having a kernel is obtained. This characterization is a partial solution to the following problem: Characterize circulant digraphs which have kernels; it appeared in the book {it Digraphs - theory, algorithms and applications}, Second Edition, Springer-Verlag, 2009, by J. Bang-Jensen and G. Gutin.
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
Locally linear approximation for Kernel methods : the Railway Kernel
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 capability of the pr...
Kroah-Hartman, Greg
2009-01-01
Linux Kernel in a Nutshell covers the entire range of kernel tasks, starting with downloading the source and making sure that the kernel is in sync with the versions of the tools you need. In addition to configuration and installation steps, the book offers reference material and discussions of related topics such as control of kernel options at runtime.
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
Mixture Density Mercer Kernels
National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...
Johno, Hisashi; Nakamoto, Kazunori; Saigo, Tatsuhiko
2015-01-01
Kernel Bayes' rule has been proposed as a nonparametric kernel-based method to realize Bayesian inference in reproducing kernel Hilbert spaces. However, we demonstrate both theoretically and experimentally that the prediction result by kernel Bayes' rule is in some cases unnatural. We consider that this phenomenon is in part due to the fact that the assumptions in kernel Bayes' rule do not hold in general.
Linearized Kernel Dictionary Learning
Golts, Alona; Elad, Michael
2016-06-01
In this paper we present a new approach of incorporating kernels into dictionary learning. The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an improvement in classification performance, with relation to its linear counterpart K-SVD. However, this algorithm requires the storage and handling of a very large kernel matrix, which leads to high computational cost, while also limiting its use to setups with small number of training examples. We address these problems by combining two ideas: first we approximate the kernel matrix using a cleverly sampled subset of its columns using the Nystr\\"{o}m method; secondly, as we wish to avoid using this matrix altogether, we decompose it by SVD to form new "virtual samples," on which any linear dictionary learning can be employed. Our method, termed "Linearized Kernel Dictionary Learning" (LKDL) can be seamlessly applied as a pre-processing stage on top of any efficient off-the-shelf dictionary learning scheme, effectively "kernelizing" it. We demonstrate the effectiveness of our method on several tasks of both supervised and unsupervised classification and show the efficiency of the proposed scheme, its easy integration and performance boosting properties.
Directory of Open Access Journals (Sweden)
Christoph Siewert
2014-09-01
Full Text Available This study deals with the comparison of numerically and experimentally determined collision kernels of water drops in air turbulence. The numerical and experimental setups are matched as closely as possible. However, due to the individual numerical and experimental restrictions, it could not be avoided that the turbulent kinetic energy dissipation rate of the measurement and the simulations differ. Direct numerical simulations (DNS are performed resulting in a very large database concerning geometric collision kernels with 1470 individual entries. Based on this database a fit function for the turbulent enhancement of the collision kernel is developed. In the experiments, the collision rates of large drops (radius >7.5μm$> 7.5\\,\\text{\\textmu{}m}$ are measured. These collision rates are compared with the developed fit, evaluated at the measurement conditions. Since the total collision rates match well for all occurring dissipation rates the distribution information of the fit could be used to enhance the statistical reliability and for the first time an experimental collision kernel could be constructed. In addition to the collision rates, the drop size distributions at three consecutive streamwise positions are measured. The drop size distributions contain mainly small drops (radius <7.5μm$< 7.5\\,\\text{\\textmu{}m}$. The measured evolution of the drop size distribution is confronted with model calculations based on the newly derived fit of the collision kernel. It turns out that the observed fast evolution of the drop size distribution can only be modeled if the collision kernel for small drops is drastically increased. A physical argument for this amplification is missing since for such small drops, neither DNSs nor experiments have been performed. For large drops, for which a good agreement of the collision rates was found in the DNS and the experiment, the time for the evolution of the spectrum in the wind tunnel is too short to draw
Contingent kernel density estimation.
Directory of Open Access Journals (Sweden)
Scott Fortmann-Roe
Full Text Available Kernel density estimation is a widely used method for estimating a distribution based on a sample of points drawn from that distribution. Generally, in practice some form of error contaminates the sample of observed points. Such error can be the result of imprecise measurements or observation bias. Often this error is negligible and may be disregarded in analysis. In cases where the error is non-negligible, estimation methods should be adjusted to reduce resulting bias. Several modifications of kernel density estimation have been developed to address specific forms of errors. One form of error that has not yet been addressed is the case where observations are nominally placed at the centers of areas from which the points are assumed to have been drawn, where these areas are of varying sizes. In this scenario, the bias arises because the size of the error can vary among points and some subset of points can be known to have smaller error than another subset or the form of the error may change among points. This paper proposes a "contingent kernel density estimation" technique to address this form of error. This new technique adjusts the standard kernel on a point-by-point basis in an adaptive response to changing structure and magnitude of error. In this paper, equations for our contingent kernel technique are derived, the technique is validated using numerical simulations, and an example using the geographic locations of social networking users is worked to demonstrate the utility of the method.
Multidimensional kernel estimation
Milosevic, Vukasin
2015-01-01
Kernel estimation is one of the non-parametric methods used for estimation of probability density function. Its first ROOT implementation, as part of RooFit package, has one major issue, its evaluation time is extremely slow making in almost unusable. The goal of this project was to create a new class (TKNDTree) which will follow the original idea of kernel estimation, greatly improve the evaluation time (using the TKTree class for storing the data and creating different user-controlled modes of evaluation) and add the interpolation option, for 2D case, with the help of the new Delaunnay2D class.
for palm kernel oil extraction
African Journals Online (AJOL)
user
OEE), ... designed (CRD) experimental approach with 4 factor levels and 2 replications was used to determine the effect of kernel .... palm kernels in either a continuous or batch mode ... are fed through the hopper; the screw conveys, crushes,.
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...
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...
Adaptive metric kernel regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
2000-01-01
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...
Adaptive Metric Kernel Regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
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...
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...
Multiple Kernel Point Set Registration.
Nguyen, Thanh Minh; Wu, Q M Jonathan
2016-06-01
The finite Gaussian mixture model with kernel correlation is a flexible tool that has recently received attention for point set registration. While there are many algorithms for point set registration presented in the literature, an important issue arising from these studies concerns the mapping of data with nonlinear relationships and the ability to select a suitable kernel. Kernel selection is crucial for effective point set registration. We focus here on multiple kernel point set registration. We make several contributions in this paper. First, each observation is modeled using the Student's t-distribution, which is heavily tailed and more robust than the Gaussian distribution. Second, by automatically adjusting the kernel weights, the proposed method allows us to prune the ineffective kernels. This makes the choice of kernels less crucial. After parameter learning, the kernel saliencies of the irrelevant kernels go to zero. Thus, the choice of kernels is less crucial and it is easy to include other kinds of kernels. Finally, we show empirically that our model outperforms state-of-the-art methods recently proposed in the literature.
Dietrich, D. L.; Ross, H. D.; Tien, J. S.
1995-01-01
The candle flame in both normal and microgravity is non-propagating. In microgravity, however, the candle flame is also non-convective where (excepting Stefan flow) pure diffusion is the only transport mode. It also shares many characteristics with another classical problem, that of isolated droplet combustion. Given their qualitatively similar flame shapes and the required heat feedback to condensed-phase fuels, the gas-phase flow and temperature fields should be relatively similar for a droplet and a candle in reduced gravity. Unless the droplet diameter is maintained somehow through non-intrusive replenishment of fuel, the quasi-steady burning characteristics of a droplet can be maintained for only a few seconds. In contrast, the candle flame in microgravity may achieve a nearly steady state over a much longer time and is therefore ideal for examining a number of combustion-related phenomena. In this paper, we examine candle flame behavior in both short-duration and long-duration, quiescent, microgravity environments. Interest in this type of flame, especially 'candle flames in weightlessness', is demonstrated by very frequent public inquiries. The question is usually posed as 'will a candle flame burn in zero gravity', or, 'will a candle burn indefinitely (or steadily) in zero gravity in a large volume of quiescent air'. Intuitive speculation suggests to some that, in the absence of buoyancy, the accumulation of products in the vicinity of the flame will cause flame extinction. The classical theory for droplet combustion with its spherically-shaped diffusion flame, however, shows that steady combustion is possible in the absence of buoyancy if the chemical kinetics are fast enough. Previous experimental studies of candle flames in reduced and microgravity environments showed the flame could survive for at least 5 seconds, but did not reach a steady state in the available test time.
Dynamics of bluff-body-stabilized lean premixed syngas flames in a meso-scale channel
Lee, Bok Jik
2016-07-15
Direct numerical simulations are conducted to investigate the dynamics of lean premixed syngas flames stabilized by a bluff-body in a meso-scale channel at near blow-off conditions, in order to provide fundamental insights into the physical mechanisms responsible for the critical phenomena. Flames in a two-dimensional meso-scale channel with a square flame holder are adopted as the model configuration, and a syngas mixture at an equivalence ratio of 0.5 with the CO:H ratio of 1 is considered. As the inlet velocity is increased, the initially stable steady flames undergo a transition to an unsteady mode of regular asymmetric fluctuation. When the inlet velocity is further increased, the flame is eventually blown off. Between the regular fluctuation mode and blow-off limit, there exists a narrow range of the inlet velocity where the flames exhibit periodic local extinction and recovery. Approaching further to the blow-off limit, the recovery mode fails to occur but the flame survives as a short kernel attached to the base of the bluff-body, until it is completely extinguished as the attached flames are gradually shrunk towards the bluff-body. The results are systematically compared with the hydrogen flame results reported in our earlier study. Examination of the characteristic time scales of relevant processes provided understanding of key mechanisms responsible for the observed differences, thereby allowing improved description of the local extinction and re-ignition dynamics that are critical to flame stabilization.
Haskin, Henry H. (Inventor); Vasquez, Peter (Inventor)
2013-01-01
A flame holder system includes a modified torch body and a ceramic flame holder. Catch pin(s) are coupled to and extend radially out from the torch body. The ceramic flame holder has groove(s) formed in its inner wall that correspond in number and positioning to the catch pin(s). Each groove starts at one end of the flame holder and can be shaped to define at least two 90.degree.turns. Each groove is sized to receive one catch pin therein when the flame holder is fitted over the end of the torch body. The flame holder is then manipulated until the catch pin(s) butt up against the end of the groove(s).
Directory of Open Access Journals (Sweden)
Rohit Kulkarni
2012-01-01
Full Text Available The potential of a progress variable formulation for predicting autoignition and subsequent kernel development in a nonpremixed jet flame is explored in the LES (Large Eddy Simulation context. The chemistry is tabulated as a function of mixture fraction and a composite progress variable, which is defined as a combination of an intermediate and a product species. Transport equations are solved for mixture fraction and progress variable. The filtered mean source term for the progress variable is closed using a probability density function of presumed shape for the mixture fraction. Subgrid fluctuations of the progress variable conditioned on the mixture fraction are neglected. A diluted hydrogen jet issuing into a turbulent coflow of preheated air is chosen as a test case. The model predicts ignition lengths and subsequent kernel growth in good agreement with experiment without any adjustment of model parameters. The autoignition length predicted by the model depends noticeably on the chemical mechanism which the tabulated chemistry is based on. Compared to models using detailed chemistry, significant reduction in computational costs can be realized with the progress variable formulation.
Institute of Scientific and Technical Information of China (English)
郑洪建; 董树亭; 王空军; 胡昌浩; 张吉旺; 郭玉秋
2001-01-01
通过播期、覆膜调控，研究了不同生态条件下不同类型品种的生长发育，重点研究生态因素对玉米花后子粒发育的影响。试验主要结果如下：高温少光条件影响子粒灌浆，表现在灌浆期持续时间短、灌浆速率相对较低。晚熟品种灌浆期长而灌浆速率相对较低，早熟品种灌浆期短而灌浆速率相对较高，是正常年份两类品种都能取得高产的原因。子粒体积变化与干重变化趋势一致。适宜生态条件下，玉米穗粒性状变异系数小，果穗发育整齐一致。掖单13穗长较大，易于形成大果穗，高产潜力大，但高温少光条件下，穗粒性状变异系数大，果穗不整齐，产量低。高温少光条件下，子粒呼吸速率明显降低，高值持续时间短；同时CTK含量较低。ABA含量变化规律性不强，子粒生长受多种内源物质协调调控。%Through sowing date and plastic film,the effect of ecological factors on the growth of maize seed after bloom was studied.The results were as follows:The effect of high temperature and defficent light on maize seed filling leads to short duration of seed filling and low speed of seed filling.Late varieties have a long filling period and a low filling speed while early varieties have a short filling period and a high filling speed,so two type variety both can reach high yield in normal year.The kernel volume has the same trendline of change with dry matter of kernel.Maize ear is orderly at fitting ecological condition.Y13 can form big ear easily and have big potential of high yield;but the value for coefficient of variation of maize ear and seed is big,the ear is not orderly and the yield is low in the condition of high temperature and deficient light?In stress condition,the respiration rate of kernel decrease and the duration of high value become short and the content of CTK are low relatively.The law of the ABA change is not obviously.The growth of kernel
Oxyhydrogen burner for low-temperature flame fusion
Ueltzen, M.; Brüggenkamp, T.; Franke, M.; Altenburg, H.
1993-04-01
An oxyhydrogen burner as described in this article enables the growth of crystals by Verneuil's technique at temperatures of about 1000 °C. The powder fed to the crystal passes along a low-temperature pathway through the flame, so that evaporation of volatile components is prevented. Low-temperature flame fusion of superconducting Y-Ba-cuprate is reported.
Testing Monotonicity of Pricing Kernels
Timofeev, Roman
2007-01-01
In this master thesis a mechanism to test mononicity of empirical pricing kernels (EPK) is presented. By testing monotonicity of pricing kernel we can determine whether utility function is concave or not. Strictly decreasing pricing kernel corresponds to concave utility function while non-decreasing EPK means that utility function contains some non-concave regions. Risk averse behavior is usually described by concave utility function and considered to be a cornerstone of classical behavioral ...
7 CFR 51.1415 - Inedible kernels.
2010-01-01
... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or...
7 CFR 981.8 - Inedible kernel.
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,...
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....
7 CFR 981.408 - Inedible kernel.
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...
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....
Institute of Scientific and Technical Information of China (English)
2008-01-01
Modern science plays a crucial role in lighting the Olympic flame on the world’s highest mountain when the world saw live telecasts of the Olympic flame burning onthe top of Mount Qomolangma(Mount Everest) at 9:17 on the morning of May 8, few realized the years of work and high level of technology that had
Kernel Phase and Kernel Amplitude in Fizeau Imaging
Pope, Benjamin J S
2016-01-01
Kernel phase interferometry is an approach to high angular resolution imaging which enhances the performance of speckle imaging with adaptive optics. Kernel phases are self-calibrating observables that generalize the idea of closure phases from non-redundant arrays to telescopes with arbitrarily shaped pupils, by considering a matrix-based approximation to the diffraction problem. In this paper I discuss the recent history of kernel phase, in particular in the matrix-based study of sparse arrays, and propose an analogous generalization of the closure amplitude to kernel amplitudes. This new approach can self-calibrate throughput and scintillation errors in optical imaging, which extends the power of kernel phase-like methods to symmetric targets where amplitude and not phase calibration can be a significant limitation, and will enable further developments in high angular resolution astronomy.
El-Asrag, Hossam A.
2011-01-01
Direct simulation of all the length and time scales relevant to practical combustion processes is computationally prohibitive. When combustion processes are driven by reaction and transport phenomena occurring at the unresolved scales of a numerical simulation, one must introduce a dynamic subgrid model that accounts for the multiscale nature of the problem using information available on a resolvable grid. Here, we discuss a model that captures unsteady flow-flame interactions- including extinction, re-ignition, and history effects-via embedded simulations at the subgrid level. The model efficiently accounts for subgrid flame structure and incorporates detailed chemistry and transport, allowing more accurate prediction of the stretch effect and the heat release. In this chapter we first review the work done in the past thirty years to develop the flame embedding concept. Next we present a formulation for the same concept that is compatible with Large Eddy Simulation in the flamelet regimes. The unsteady flame embedding approach (UFE) treats the flame as an ensemble of locally one-dimensional flames, similar to the flamelet approach. However, a set of elemental one-dimensional flames is used to describe the turbulent flame structure directly at the subgrid level. The calculations employ a one-dimensional unsteady flame model that incorporates unsteady strain rate, curvature, and mixture boundary conditions imposed by the resolved scales. The model is used for closure of the subgrid terms in the context of large eddy simulation. Direct numerical simulation (DNS) data from a flame-vortex interaction problem is used for comparison. © Springer Science+Business Media B.V. 2011.
A Thermodynamic Model for Argon Plasma Kernel Formation
Directory of Open Access Journals (Sweden)
James Keck
2010-11-01
Full Text Available Plasma kernel formation of argon is studied experimentally and theoretically. The experiments have been performed in a constant volume cylindrical vessel located in a shadowgraph system. The experiments have been done in constant pressure. The energy of plasma is supplied by an ignition system through two electrodes located in the vessel. The experiments have been done with two different spark energies to study the effect of input energy on kernel growth and its properties. A thermodynamic model employing mass and energy balance was developed to predict the experimental data. The agreement between experiments and model prediction is very good. The effect of various parameters such as initial temperature, initial radius of the kernel, and the radiation energy loss have been investigated and it has been concluded that initial condition is very important on formation and expansion of the kernel.
Viability Kernel for Ecosystem Management Models
Anaya, Eladio Ocana; Oliveros--Ramos, Ricardo; Tam, Jorge
2009-01-01
We consider sustainable management issues formulated within the framework of control theory. The problem is one of controlling a discrete--time dynamical system (e.g. population model) in the presence of state and control constraints, representing conflicting economic and ecological issues for instance. The viability kernel is known to play a basic role for the analysis of such problems and the design of viable control feedbacks, but its computation is not an easy task in general. We study the viability of nonlinear generic ecosystem models under preservation and production constraints. Under simple conditions on the growth rates at the boundary constraints, we provide an explicit description of the viability kernel. A numerical illustration is given for the hake--anchovy couple in the Peruvian upwelling ecosystem.
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...
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...
Graph kernels between point clouds
Bach, Francis
2007-01-01
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and practical constraints associated with point clouds in computer vision and graphics. In this paper, we present extensions of graph kernels for point clouds, which allow to use kernel methods for such ob jects as shapes, line drawings, or any three-dimensional point clouds. In order to design rich and numerically efficient kernels with as few free parameters as possible, we use kernels between covariance matrices and their factorizations on graphical models. We derive polynomial time dynamic programming recursions and present applications to recognition of handwritten digits and Chinese characters from few training examples.
Kernel Generalized Noise Clustering Algorithm
Institute of Scientific and Technical Information of China (English)
WU Xiao-hong; ZHOU Jian-jiang
2007-01-01
To deal with the nonlinear separable problem, the generalized noise clustering (GNC) algorithm is extended to a kernel generalized noise clustering (KGNC) model. Different from the fuzzy c-means (FCM) model and the GNC model which are based on Euclidean distance, the presented model is based on kernel-induced distance by using kernel method. By kernel method the input data are nonlinearly and implicitly mapped into a high-dimensional feature space, where the nonlinear pattern appears linear and the GNC algorithm is performed. It is unnecessary to calculate in high-dimensional feature space because the kernel function can do itjust in input space. The effectiveness of the proposed algorithm is verified by experiments on three data sets. It is concluded that the KGNC algorithm has better clustering accuracy than FCM and GNC in clustering data sets containing noisy data.
Bruemmer, David J.
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.
Nowicki, Dimitri; Siegelmann, Hava
2010-06-11
This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.
Directory of Open Access Journals (Sweden)
Dimitri Nowicki
Full Text Available This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces.
Mixture Density Mercer Kernels: A Method to Learn Kernels
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...
Institute of Scientific and Technical Information of China (English)
2008-01-01
Deaf-mute Jiang Xintian lights a small cauldron in the hands of wheelchairbound fencer Jin Jing at the Paralympic Flame Lighting Ceremony in Beijing’s symbolic Temple of Heaven on August 28. For nine days until September 6, when the 13th Paralympics opens in Beijing, a total of 850 torchbearers would relay the Paralympic flame along two routes through 11 Chinese provinces,
Aromatics oxidation and soot formation in flames
Energy Technology Data Exchange (ETDEWEB)
Howard, J.B.; Pope, C.J.; Shandross, R.A.; Yadav, T.
1993-04-01
This project is concerned with the kinetics and mechanisms of aromatics oxidation and soot and fullerenes formation in flames. The scope includes detailed measurements of profiles of stable and radical species concentrations in low-pressure one-dimensional premixed flames. Intermediate species identifications and mole fractions, fluxes, and net reaction rates calculated from the measured profiles are used to test postulated reaction mechanisms. Particular objectives are to identify, and to confirm or determine rate constants for, the main benzene oxidation reactions in flames, and to characterize soot and fullerenes and their formation mechanisms and kinetics. Stable and radical species profiles in the aromatics oxidation study are measured using molecular beam sampling with on-line mass spectrometry. The rate of soot formation measured by conventional optical techniques is found to support the hypotheses that particle inception occurs through reactive coagulation of high molecular weight PAH in competition with destruction by OHattack, and that the subsequent growth of the soot mass occurs through addition reactions of PAH and C[sub 2]H[sub 2] with the soot particles. During the first year of this reporting period, fullerenes C[sub 60] and C[sub 70] in substantial quantities were found in the flames being studied. The fullerenes were recovered, purified and spectroscopically identified. The yields of C[sub 60] and C[sub 70] were then determined over ranges of conditions in low-pressure premixed flames of benzene and oxygen.
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,...
(Pre)kernel catchers for cooperative games
Chang, Chih; Driessen, Theo
1995-01-01
The paper provides a new (pre)kernel catcher in that the relevant set always contains the (pre)kernel. This new (pre)kernel catcher gives rise to a better lower bound ɛ*** such that the kernel is included in strong ɛ-cores for all real numbers ɛ not smaller than the relevant bound ɛ***.
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....
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...
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The methods for computing the kemel consistency-based diagnoses and the kernel abductive diagnoses are only suited for the situation where part of the fault behavioral modes of the components are known. The characterization of the kernel model-based diagnosis based on the general causal theory is proposed, which can break through the limitation of the above methods when all behavioral modes of each component are known. Using this method, when observation subsets deduced logically are respectively assigned to the empty or the whole observation set, the kernel consistency-based diagnoses and the kernel abductive diagnoses can deal with all situations. The direct relationship between this diagnostic procedure and the prime implicants/implicates is proved, thus linking theoretical result with implementation.
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....
Kernel Rootkits Implement and Detection
Institute of Scientific and Technical Information of China (English)
LI Xianghe; ZHANG Liancheng; LI Shuo
2006-01-01
Rootkits, which unnoticeably reside in your computer, stealthily carry on remote control and software eavesdropping, are a great threat to network and computer security. It' time to acquaint ourselves with their implement and detection. This article pays more attention to kernel rootkits, because they are more difficult to compose and to be identified than useland rootkits. The latest technologies used to write and detect kernel rootkits, along with their advantages and disadvantages, are present in this article.
Energy Technology Data Exchange (ETDEWEB)
Wang, Yingde, E-mail: wyd502@163.com [Science and Technology on Advanced Ceramic Fibers and Composites Laboratory, National University of Defense Technology, Changsha PR 410073 (China); Wang, Bing [Science and Technology on Advanced Ceramic Fibers and Composites Laboratory, National University of Defense Technology, Changsha PR 410073 (China); Lei, Yongpeng, E-mail: lypkd@163.com [College of Basic Education, National University of Defense Technology, Changsha PR 410073 (China); Wu, Nan; Han, Cheng; Gou, Yanzi [Science and Technology on Advanced Ceramic Fibers and Composites Laboratory, National University of Defense Technology, Changsha PR 410073 (China); Fang, Dong [College of Materials Science and Engineering, Wuhan Textile University, Wuhan PR 430074 (China)
2015-04-30
Highlights: • SnO{sub 2} nanoparticle chains/SiC fibers were in situ prepared by sol–gel-flame method. • The composite fibers with hierarchical structure formed a flexible mat. • The flexible mats showed superior electrical and optical properties. • Such composite fibers mat can be easily scalable synthesized. - Abstract: SnO{sub 2} nanoparticle chains (SNPCs) were controllably in situ grown on the electrospun SiC ultrathin fibers (SUFs) by a scalable sol–gel-flame method to form a flexible mat. While bulk SnO{sub 2} was obtained by relatively slow pyrolysis in conventional horizontal tube furnace. The effect of process parameters on the microstructure and morphology of SNPCs/SUFs mats was discussed. I–V characteristics of the SNPCs/SUFs mats revealed a nonlinear curve, indicating the formation of Schottky-type junctions. The composite fibers mats also exhibited broad and strong emission bands between 400 and 650 nm. This may be attributed to the existence of a large amount of oxygen vacancies and defects in SNPCs caused by the fast pyrolysis process. Such composite fibers mats may have great potentials in high-temperature gas sensors, light-emitting diodes and lithium-ion storages, etc.
Eaves, Nick A.; Zhang, Qingan; Liu, Fengshan; Guo, Hongsheng; Dworkin, Seth B.; Thomson, Murray J.
2016-10-01
Mitigation of soot emissions from combustion devices is a global concern. For example, recent EURO 6 regulations for vehicles have placed stringent limits on soot emissions. In order to allow design engineers to achieve the goal of reduced soot emissions, they must have the tools to so. Due to the complex nature of soot formation, which includes growth and oxidation, detailed numerical models are required to gain fundamental insights into the mechanisms of soot formation. A detailed description of the CoFlame FORTRAN code which models sooting laminar coflow diffusion flames is given. The code solves axial and radial velocity, temperature, species conservation, and soot aggregate and primary particle number density equations. The sectional particle dynamics model includes nucleation, PAH condensation and HACA surface growth, surface oxidation, coagulation, fragmentation, particle diffusion, and thermophoresis. The code utilizes a distributed memory parallelization scheme with strip-domain decomposition. The public release of the CoFlame code, which has been refined in terms of coding structure, to the research community accompanies this paper. CoFlame is validated against experimental data for reattachment length in an axi-symmetric pipe with a sudden expansion, and ethylene-air and methane-air diffusion flames for multiple soot morphological parameters and gas-phase species. Finally, the parallel performance and computational costs of the code is investigated.
Uniqueness Result in the Cauchy Dirichlet Problem via Mehler Kernel
Dhungana, Bishnu P.
2014-09-01
Using the Mehler kernel, a uniqueness theorem in the Cauchy Dirichlet problem for the Hermite heat equation with homogeneous Dirichlet boundary conditions on a class P of bounded functions U( x, t) with certain growth on U x ( x, t) is established.
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...
An Approximate Approach to Automatic Kernel Selection.
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.
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...
Moor, Peter J.; Heuvelman, A.; Verleur, R.
2010-01-01
In this explorative study, flaming on YouTube was studied using surveys of YouTube users. Flaming is defined as displaying hostility by insulting, swearing or using otherwise offensive language. Three general conclusions were drawn. First, although many users said that they themselves do not flame,
Moor, Peter J.; Heuvelman, Ard; Verleur, Ria
2010-01-01
In this explorative study, flaming on YouTube was studied using surveys of YouTube users. Flaming is defined as displaying hostility by insulting, swearing or using otherwise offensive language. Three general conclusions were drawn. First, although many users said that they themselves do not flame,
Probing flame chemistry with MBMS, theory, and modeling
Energy Technology Data Exchange (ETDEWEB)
Westmoreland, P.R. [Univ. of Massachusetts, Amherst (United States)
1993-12-01
The objective is to establish kinetics of combustion and molecular-weight growth in C{sub 3} hydrocarbon flames as part of an ongoing study of flame chemistry. Specific reactions being studied are (1) the growth reactions of C{sub 3}H{sub 5} and C{sub 3}H{sub 3} with themselves and with unsaturated hydrocarbons and (2) the oxidation reactions of O and OH with C{sub 3}`s. This approach combines molecular-beam mass spectrometry (MBMS) experiments on low-pressure flat flames; theoretical predictions of rate constants by thermochemical kinetics, Bimolecular Quantum-RRK, RRKM, and master-equation theory; and whole-flame modeling using full mechanisms of elementary reactions.
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.
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...
Kernel learning algorithms for face recognition
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
NEAR-BLOWOFF DYNAMICS OF BLUFF-BODY-STABILIZED PREMIXED HYDROGEN/AIR FLAMES IN A NARROW CHANNEL
Lee, Bok Jik
2015-06-07
The flame stability is known to be significantly enhanced when the flame is attached to a bluff-body. The main interest of this study is on the stability of the flame in a meso-scale channel, considering applications such as combustion-based micro power generators. We investigate the dynamics of lean premixed hydrogen/air flames stabilized behind a square box in a two-dimensional meso-scale channel with high-fidelity numerical simulations. Characteristics of both non-reacting flows and reacting flows over the bluff-body are studied for a range of the mean inflow velocity. The flame stability in reacting flows is investigated by ramping up the mean inflow velocity step by step. As the inlet velocity is increased, the initially stable steady flames undergo a transition to an unsteady mode of regular asymmetric fluctuation. When the inlet velocity is further increased, the flame is eventually blown off. Between the regular fluctuation mode and blowoff limit, there exists a narrow range of the inlet velocity where the flames exhibit periodic local extinction and recovery. Approaching further to blowoff limit, the local extinction and recovery becomes highly transient and a failure of recovery leads blowoff and extinction of the flame kernel.
Flame Stretch Analysis in Diffusion Flames with Inert Gas
Institute of Scientific and Technical Information of China (English)
Ay Su; Ying-Chieh Liu
2001-01-01
Experimental investigations of impinging flame with fuel mixed with non-reaction gas were conducted.According to the observations of combustion test and temperature measurement, the non-reaction gas might dilute the local concentration of fuel in the diffusion process. The shape of the flame was symmetrical due to the flame stretch force. Results show that the conical flame might be de-structured by the addition of inert gas in pure methane fuel. The impinging flame became shorter and bluer as nitrogen was added to the fuel. The conditions of N2/CH4 equal to 1/2 and 1/1 show a wider plane in the YZ plane. The effect of inert gas overcomes the flame stretch and destroys the symmetrical column flame as well as the cold flow. Nitrogen addition also enhances the diffusion rate and combustion efficiency.
Propagation Limits of High Pressure Cool Flames
Ju, Yiguang
2016-11-01
The flame speeds and propagation limits of premixed cool flames at elevated pressures with radiative heat loss are numerically modelled using dimethyl ether mixtures. The primary focus is paid on the effects of pressure, mixture dilution, flame size, and heat loss on cool flame propagation. The results showed that cool flames exist on both fuel lean and fuel rich sides and thus dramatically extend the lean and rich flammability limits. There exist three different flame regimes, hot flame, cool flame, and double flame. A new flame flammability diagram including both cool flames and hot flames is obtained at elevated pressure. The results show that pressure significantly changes cool flame propagation. It is found that the increases of pressure affects the propagation speeds of lean and rich cool flames differently due to the negative temperature coefficient effect. On the lean side, the increase of pressure accelerates the cool flame chemistry and shifts the transition limit of cool flame to hot flame to lower equivalence ratio. At lower pressure, there is an extinction transition from hot flame to cool flame. However, there exists a critical pressure above which the cool flame to hot flame transition limit merges with the lean flammability limit of the hot flame, resulting in a direct transition from hot flame to cool flame. On the other hand, the increase of dilution reduces the heat release of hot flame and promotes cool flame formation. Moreover, it is shown that a smaller flame size and a higher heat loss also extend the cool flame transition limit and promote cool flame formation.
Experimental study of the inverse diffusion flame using high repetition rate OH/acetone PLIF and PIV
Elbaz, Ayman M.
2015-10-29
Most previous work on inverse diffusion flames (IDFs) has focused on laminar IDF emissions and the soot formation characteristics. Here, we investigate the characteristics and structure of methane IDFs using high speed planar laser-induced fluorescence (PLIF) images of OH, particle image velocimetry (PIV), and acetone PLIF imaging for non-reacting cases. First, the flame appearance was investigated with fixed methane loading (mass flux) but with varying airflow rates, yielding a central air jet Reynolds number (Re) of 1,000 to 6,000 (when blow-off occurs). Next, it was investigated a fixed central air jet Re of 4500, but with varied methane mass flux such that the global equivalence ratio spanned 0.5 to 4. It was observed that at Re smaller than 2000, the inner air jet promotes the establishment of an inverse diffusion flame surrounded by a normal diffusion flame. However, when the Re was increased to 2500, two distinct zones became apparent in the flame, a lower entrainment zone and an upper mixing and combustion zone. 10 kHz OH-PLIF images, and 2D PIV allow the identification of the fate and spatial flame structure. Many flame features were identified and further analyzed using simple but effective image processing methods, where three types of structure in all the flames investigated here: flame holes or breaks; closures; and growing kernels. Insights about the rate of evolution of these features, the dynamics of local extinction, and the sequence of events that lead to re-ignition are reported here. In the lower entrainment zone, the occurrence of the flame break events is counterbalanced by closure events, and the edge propagation appears to control the rate at which the flame holes and closures propagate. The rate of propagation of holes was found to be statistically faster than the rate of closure. As the flames approach blow-off, flame kernels become the main mechanism for flame re-ignition further downstream. The simultaneous OH-PLIF/Stereo PIV
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....
Congruence Kernels of Orthoimplication Algebras
Directory of Open Access Journals (Sweden)
I. Chajda
2007-10-01
Full Text Available Abstracting from certain properties of the implication operation in Boolean algebras leads to so-called orthoimplication algebras. These are in a natural one-to-one correspondence with families of compatible orthomodular lattices. It is proved that congruence kernels of orthoimplication algebras are in a natural one-to-one correspondence with families of compatible p-filters on the corresponding orthomodular lattices. Finally, it is proved that the lattice of all congruence kernels of an orthoimplication algebra is relatively pseudocomplemented and a simple description of the relative pseudocomplement is given.
Landis, Arthur M.; Davies, Malonne I.; Landis, Linda
2009-01-01
Cleaning erasers are used to support methanol-fueled flame tests. This safe demonstration technique requires only small quantities of materials, provides clean colors for up to 45 seconds, and can be used in the classroom or the auditorium. (Contains 1 note.)
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...
Bergman kernel on generalized exceptional Hua domain
Institute of Scientific and Technical Information of China (English)
YIN; weipng(殷慰萍); ZHAO; zhengang(赵振刚)
2002-01-01
We have computed the Bergman kernel functions explicitly for two types of generalized exceptional Hua domains, and also studied the asymptotic behavior of the Bergman kernel function of exceptional Hua domain near boundary points, based on Appell's multivariable hypergeometric function.
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....
Random Feature Maps for Dot Product Kernels
Kar, Purushottam; Karnick, Harish
2012-01-01
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explic...
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
Directory of Open Access Journals (Sweden)
Tarn Duong
2007-09-01
Full Text Available Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.
Theoretical and Numerical Investigation of Radiative Extinction of Diffusion Flames
Ray, Anjan
1996-01-01
The influence of soot radiation on diffusion flames was investigated using both analytical and numerical techniques. Soot generated in diffusion flames dominate the flame radiation over gaseous combustion products and can significantly lower the temperature of the flame. In low gravity situations there can be significant accumulation of soot and combustion products in the vicinity of the primary reaction zone owing to the absence of any convective buoyant flow. Such situations may result in substantial suppression of chemical activities in a flame, and the possibility of a radiative extinction may also be anticipated. The purpose of this work was to not only investigate the possibility of radiative extinction of a diffusion flame but also to qualitatively and quantitatively analyze the influence of soot radiation on a diffusion flame. In this study, first a hypothetical radiative loss profile of the form of a sech(sup 2) was assumed to influence a pure diffusion flame. It was observed that the reaction zone can, under certain circumstances, move through the radiative loss zone and locate itself on the fuel side of the loss zone contrary to our initial postulate. On increasing the intensity and/or width of the loss zone it was possible to extinguish the flame, and extinction plots were generated. In the presence of a convective flow, however, the movement of the temperature and reaction rate peaks indicated that the flame behavior is more complicated compared to a pure diffusional flame. A comprehensive model of soot formation, oxidation and radiation was used in a more involved analysis. The soot model of Syed, Stewart and Moss was used for soot nucleation and growth and the model of Nagle and Strickland-Constable was used for soot oxidation. The soot radiation was considered in the optically thin limit. An analysis of the flame structure revealed that the radiative loss term is countered both by the reaction term and the diffusion term. The essential balance for
On the Diamond Bessel Heat Kernel
Directory of Open Access Journals (Sweden)
Wanchak Satsanit
2011-01-01
Full Text Available We study the heat equation in n dimensional by Diamond Bessel operator. We find the solution by method of convolution and Fourier transform in distribution theory and also obtain an interesting kernel related to the spectrum and the kernel which is called Bessel heat kernel.
Local Observed-Score Kernel Equating
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…
Computations of Bergman Kernels on Hua Domains
Institute of Scientific and Technical Information of China (English)
殷慰萍; 王安; 赵振刚; 赵晓霞; 管冰辛
2001-01-01
@@The Bergman kernel function plays an important ro1e in several complex variables.There exists the Bergman kernel function on any bounded domain in Cn. But we can get the Bergman kernel functions in explicit formulas for a few types of domains only,for example:the bounded homogeneous domains and the egg domain in some cases.
Veto-Consensus Multiple Kernel Learning
Y. Zhou; N. Hu; C.J. Spanos
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 propose
Accelerating the Original Profile Kernel.
Directory of Open Access Journals (Sweden)
Tobias Hamp
Full Text Available One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.
Adaptive wiener image restoration kernel
Yuan, Ding
2007-06-05
A method and device for restoration of electro-optical image data using an adaptive Wiener filter begins with constructing imaging system Optical Transfer Function, and the Fourier Transformations of the noise and the image. A spatial representation of the imaged object is restored by spatial convolution of the image using a Wiener restoration 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.
Salt stress reduces kernel number of corn by inhibiting plasma membrane H(+)-ATPase activity.
Jung, Stephan; Hütsch, Birgit W; Schubert, Sven
2017-04-01
Salt stress affects yield formation of corn (Zea mays L.) at various physiological levels resulting in an overall grain yield decrease. In this study we investigated how salt stress affects kernel development of two corn cultivars (cvs. Pioneer 3906 and Fabregas) at and shortly after pollination. In an earlier study, we found an accumulation of hexoses in the kernel tissue. Therefore, it was hypothesized that hexose uptake into developing endosperm and embryo might be inhibited. Hexoses are transported into the developing endosperm by carriers localized in the plasma membrane (PM). The transport is driven by the pH gradient which is built up by the PM H(+)-ATPase. It was investigated whether the PM H(+)-ATPase activity in developing corn kernels was inhibited by salt stress, which would cause a lower pH gradient resulting in impaired hexose import and finally in kernel abortion. Corn grown under control and salt stress conditions was harvested 0 and 2 days after pollination (DAP). Under salt stress sucrose and hexose concentrations in kernel tissue were higher 0 and 2 DAP. Kernel PM H(+)-ATPase activity was not affected at 0 DAP, but it was reduced at 2 DAP. This is in agreement with the finding, that kernel growth and thus kernel setting was not affected in the salt stress treatment at pollination, but it was reduced 2 days later. It is concluded that inhibition of PM H(+)-ATPase under salt stress impaired the energization of hexose transporters into the cells, resulting in lower kernel growth and finally in kernel abortion.
Random Feature Maps for Dot Product Kernels
Kar, Purushottam
2012-01-01
Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explicit low dimensional Euclidean spaces in which the native dot product provides an approximation to the dot product kernel with high confidence.
Thompson, C. M.; Smith, J. G., Jr.; Connell, J. W.; Hergenrother, P. M.; Lyon, R. E.
2004-01-01
As part of a program to develop fire resistant exterior composite structures for future subsonic commercial aircraft, flame retardant epoxy resins are under investigation. Epoxies and their curing agents (aromatic diamines) containing phosphorus were synthesized and used to prepare epoxy formulations. Phosphorus was incorporated within the backbone of the epoxy resin and not used as an additive. The resulting cured epoxies were characterized by thermogravimetric analysis, propane torch test, elemental analysis and microscale combustion calorimetry. Several formulations showed excellent flame retardation with phosphorous contents as low as 1.5% by weight. The fracture toughness of plaques of several cured formulations was determined on single-edge notched bend specimens. The chemistry and properties of these new epoxy formulations are discussed.
Wintzer, Niki E.; Guberman, David E.
2015-01-01
Antimony is a brittle, silvery-white semimetal that conducts heat poorly. The chemical compound antimony trioxide (Sb2O3) is widely used in plastics, rubbers, paints, and textiles, including industrial safety suits and some children’s clothing, to make them resistant to the spread of flames. Also, sodium antimonate (NaSbO3) is used during manufacturing of high-quality glass, which is found in cellular phones.
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....
Speech Enhancement Using Kernel and Normalized Kernel Affine Projection Algorithm
Directory of Open Access Journals (Sweden)
Bolimera Ravi
2013-08-01
Full Text Available The goal of this paper is to investigate the speech signal enhancement using Kernel Affine ProjectionAlgorithm (KAPA and Normalized KAPA. The removal of background noise is very important in manyapplications like speech recognition, telephone conversations, hearing aids, forensic, etc. Kernel adaptivefilters shown good performance for removal of noise. If the evaluation of background noise is more slowlythan the speech, i.e., noise signal is more stationary than the speech, we can easily estimate the noiseduring the pauses in speech. Otherwise it is more difficult to estimate the noise which results indegradation of speech. In order to improve the quality and intelligibility of speech, unlike time andfrequency domains, we can process the signal in new domain like Reproducing Kernel Hilbert Space(RKHS for high dimensional to yield more powerful nonlinear extensions. For experiments, we have usedthe database of noisy speech corpus (NOIZEUS. From the results, we observed the removal noise in RKHShas great performance in signal to noise ratio values in comparison with conventional adaptive filters.
Dynamics of unconfined spherical flames
Leblanc, Louis; Dennis, Kadeem; Zhe,; Liang,; Radulescu, Matei I
2012-01-01
Using the soap bubble technique, we visualize the dynamics of unconfined hydrogen-air flames using high speed schlieren video. We show that for sufficiently weak mixtures, i.e., low flame speeds, buoyancy effects become important. Flame balls of a critical dimension begin to rise. The experiments are found in very good agreement with the scaling laws proposed by Zingale and Dursi. We report the results in a fluid dynamics video.
Self Induced Buoyant Blow Off in Upward Flame Spread on Thin Solid Fuels
Johnston, Michael C.; T'ien, James S.; Muff, Derek E.; Olson, Sandra L.; Ferkul, Paul V.
2013-01-01
Upward flame spread experiments were conducted on a thin fabric cloth consisting of 75% cotton and 25% fiberglass. The sample is sandwiched symmetrically with stainless steel plates with the exposed width varying between 2 to 8.8 cm from test to test and >1.5m tall. The bottom edge was ignited resulting in a symmetric two sided flame. For the narrower samples (. 5cm), two sided flame growth would proceed until reaching some limiting value (15-30 cm depending on sample width). Fluctuation or instability of the flame base on one side would initially become visible and then the flame base would retreat downstream and cause extinguishment on one side. Detailed examination of the still images shows that the fuel continues to vaporize from the extinguished side due to the thermally thin nature of the fuel. But, due to the remaining inert fiberglass mesh, which acts as a flashback arrestor, the extinguished side was not able to be reignited by the remaining flame. The remaining flame would then shrink in length due to the reduced heat transfer to the solid to a shorter length. The one-sided flame will spread stably with a constant speed and a constant flame length to the end of the sample. A constant length flame implies that the pyrolysis front and the burnt out fronts move at the same speed. For the wider samples (. 7cm), no one-sided extinction is observed. Two-sided flames spread all the way to the top of the sample. For these wider widths, the flames are still growing and have not reached their limiting length if it exists. Care was taken to minimize the amount of non-symmetries in the experimental configuration. Repeated tests show that blow-off can occur on either side of the sample. The flame growth is observed to be very symmetric during the growth phase and grew to significant length (>10cm) before extinction of the flame on one side. Our proposed explanation of this unusual phenomenon (i.e. stronger two ]sided flame cannot exist but weaker one-sided flame can
Nonlinear Deep Kernel Learning for Image Annotation.
Jiu, Mingyuan; Sahbi, Hichem
2017-02-08
Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.
Nonlinear projection trick in kernel methods: an alternative to the kernel trick.
Kwak, Nojun
2013-12-01
In kernel methods such as kernel principal component analysis (PCA) and support vector machines, the so called kernel trick is used to avoid direct calculations in a high (virtually infinite) dimensional kernel space. In this brief, based on the fact that the effective dimensionality of a kernel space is less than the number of training samples, we propose an alternative to the kernel trick that explicitly maps the input data into a reduced dimensional kernel space. This is easily obtained by the eigenvalue decomposition of the kernel matrix. The proposed method is named as the nonlinear projection trick in contrast to the kernel trick. With this technique, the applicability of the kernel methods is widened to arbitrary algorithms that do not use the dot product. The equivalence between the kernel trick and the nonlinear projection trick is shown for several conventional kernel methods. In addition, we extend PCA-L1, which uses L1-norm instead of L2-norm (or dot product), into a kernel version and show the effectiveness of the proposed approach.
Solid Propellant Flame Spectroscopy
1988-08-01
400 jm to reach the maximum flame temperature, a distance that can be reduced by replacing the HTPB binder with a polyester or CMDB binder. The...the dark zone for propellants similar to HIX2 is 2-2.5 mm at 1.8 MPa (18 atm, 265 psia) (Ref. 22,187). In contrast, the dark zone for HMX CMDB ...propellants eliminates the dark zone is not surprising, since TMETN is a nitrate ester as was the double-base matrix of Kubota’s HMX CMDB propellant. A
Yu, Haibo; Gao, Qinfeng; Dong, Shuanglin; Hou, Yiran; Wen, Bin
2016-08-01
The present study was conducted to determine the change of digestive physiology in sea cucumber Apostichopus japonicus (Selenka) induced by corn kernels meal and soybean meal in diets. Four experimental diets were tested, in which Sargassum thunbergii was proportionally replaced by the mixture of corn kernels meal and soybean meal. The growth performance, body composition and intestinal digestive enzyme activities in A. japonicus fed these 4 diets were examined. Results showed that the sea cucumber exhibited the maximum growth rate when 20% of S. thunbergii in the diet was replaced by corn kernels meal and soybean meal, while 40% of S. thunbergii in the diet can be replaced by the mixture of corn kernels meal and soybean meal without adversely affecting growth performance of A. japonicus. The activities of intestinal trypsin and amylase in A. japonicus can be significantly altered by corn kernels meal and soybean meal in diets. Trypsin activity in the intestine of A. japonicus significantly increased in the treatment groups compared to the control, suggesting that the supplement of corn kernels meal and soybean meal in the diets might increase the intestinal trypsin activity of A. japonicus. However, amylase activity in the intestine of A. japonicus remarkably decreased with the increasing replacement level of S. thunbergii by the mixture of corn kernels meal and soybean meal, suggesting that supplement of corn kernels meal and soybean meal in the diets might decrease the intestinal amylase activity of A. japonicus.
Dynamics and structure of stretched flames
Energy Technology Data Exchange (ETDEWEB)
Law, C.K. [Princeton Univ., NJ (United States)
1993-12-01
This program aims to gain fundamental understanding on the structure, geometry, and dynamics of laminar premixed flames, and relate these understanding to the practical issues of flame extinction and stabilization. The underlying fundamental interest here is the recent recognition that the response of premixed flames can be profoundly affected by flame stretch, as manifested by flow nonuniformity, flame curvature, and flame/flow unsteadiness. As such, many of the existing understanding on the behavior of premixed flames need to be qualitatively revised. The research program consists of three major thrusts: (1) detailed experimental and computational mapping of the structure of aerodynamically-strained planar flames, with emphasis on the effects of heat loss, nonequidiffusion, and finite residence time on the flame thickness, extent of incomplete reaction, and the state of extinction. (2) Analytical study of the geometry and dynamics of stretch-affected wrinkled flame sheets in simple configurations, as exemplified by the Bunsen flame and the spatially-periodic flame, with emphasis on the effects of nonlinear stretch, the phenomena of flame cusping, smoothing, and tip opening, and their implications on the structure and burning rate of turbulent flames. (3) Stabilization and blowoff of two-dimensional inverted premixed and stabilization and determining the criteria governing flame blowoff. The research is synergistically conducted through the use of laser-based diagnostics, computational simulation of the flame structure with detailed chemistry and transport, and mathematical analysis of the flame dynamics.
Theory of reproducing kernels and applications
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...
Filters, reproducing kernel, and adaptive meshfree method
You, Y.; Chen, J.-S.; Lu, H.
Reproducing kernel, with its intrinsic feature of moving averaging, can be utilized as a low-pass filter with scale decomposition capability. The discrete convolution of two nth order reproducing kernels with arbitrary support size in each kernel results in a filtered reproducing kernel function that has the same reproducing order. This property is utilized to separate the numerical solution into an unfiltered lower order portion and a filtered higher order portion. As such, the corresponding high-pass filter of this reproducing kernel filter can be used to identify the locations of high gradient, and consequently serves as an operator for error indication in meshfree analysis. In conjunction with the naturally conforming property of the reproducing kernel approximation, a meshfree adaptivity method is also proposed.
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....
Tame Kernels of Pure Cubic Fields
Institute of Scientific and Technical Information of China (English)
Xiao Yun CHENG
2012-01-01
In this paper,we study the p-rank of the tame kernels of pure cubic fields.In particular,we prove that for a fixed positive integer m,there exist infinitely many pure cubic fields whose 3-rank of the tame kernel equal to m.As an application,we determine the 3-rank of their tame kernels for some special pure cubic fields.
Kernel Factor Analysis Algorithm with Varimax
Institute of Scientific and Technical Information of China (English)
Xia Guoen; Jin Weidong; Zhang Gexiang
2006-01-01
Kernal factor analysis (KFA) with varimax was proposed by using Mercer kernel function which can map the data in the original space to a high-dimensional feature space, and was compared with the kernel principle component analysis (KPCA). The results show that the best error rate in handwritten digit recognition by kernel factor analysis with varimax (4.2%) was superior to KPCA (4.4%). The KFA with varimax could more accurately image handwritten digit recognition.
Convergence of barycentric coordinates to barycentric kernels
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.
Efficient classification for additive kernel SVMs.
Maji, Subhransu; Berg, Alexander C; Malik, Jitendra
2013-01-01
We show that a class of nonlinear kernel SVMs admits approximate classifiers with runtime and memory complexity that is independent of the number of support vectors. This class of kernels, which we refer to as additive kernels, includes widely used kernels for histogram-based image comparison like intersection and chi-squared kernels. Additive kernel SVMs can offer significant improvements in accuracy over linear SVMs on a wide variety of tasks while having the same runtime, making them practical for large-scale recognition or real-time detection tasks. We present experiments on a variety of datasets, including the INRIA person, Daimler-Chrysler pedestrians, UIUC Cars, Caltech-101, MNIST, and USPS digits, to demonstrate the effectiveness of our method for efficient evaluation of SVMs with additive kernels. Since its introduction, our method has become integral to various state-of-the-art systems for PASCAL VOC object detection/image classification, ImageNet Challenge, TRECVID, etc. The techniques we propose can also be applied to settings where evaluation of weighted additive kernels is required, which include kernelized versions of PCA, LDA, regression, k-means, as well as speeding up the inner loop of SVM classifier training algorithms.
Molecular hydrodynamics from memory kernels
Lesnicki, Dominika; Carof, Antoine; Rotenberg, Benjamin
2016-01-01
The memory kernel for a tagged particle in a fluid, computed from molecular dynamics simulations, decays algebraically as $t^{-3/2}$. We show how the hydrodynamic Basset-Boussinesq force naturally emerges from this long-time tail and generalize the concept of hydrodynamic added mass. This mass term is negative in the present case of a molecular solute, at odds with incompressible hydrodynamics predictions. We finally discuss the various contributions to the friction, the associated time scales and the cross-over between the molecular and hydrodynamic regimes upon increasing the solute radius.
Hilbertian kernels and spline functions
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.
Subwoofer and nanotube butterfly acoustic flame extinction
Aliev, Ali E.; Mayo, Nathanael K.; Baughman, Ray H.; Mills, Brent T.; Habtour, Ed
2017-07-01
Nonchemical flame control using acoustic waves from a subwoofer and a lightweight carbon nanotube thermoacoustic projector was demonstrated. The intent was to manipulate flame intensity, direction and propagation. The mechanisms of flame suppression using low frequency acoustic waves were discussed. Laminar flame control and extinction were achieved using a thermoacoustic ‘butterfly’ projector based on freestanding carbon nanotube sheets.
Recent Advances in Flame Tomographyt
Institute of Scientific and Technical Information of China (English)
闫勇; 邱天; 卢钢; M.M.Hossain; G.Gilabert; 刘石
2012-01-01
To reduce greenhouse gas emissions from fossil fuel fired power plants,a range of new combustion technologies are being developed or refined,including oxy-fuel combustion,co-firing biomass with coal and fluidized bed combustion.Flame characteristics under such combustion conditions are expected to be different from those in normal air fired combustion processes.Quantified flame characteristics such as temperature distribution,oscillation frequency,and ignition volume play an important part in the optimized design and operation of the environmentally friendly power generation systems.However,it is challenging to obtain such flame characteristics particularly through a three-dimensional and non-intrusive means.Various tomography methods have been proposed to visualize and characterize flames,including passive optical tomography,laser based tomography,and electrical tomography.This paper identifies the challenges in flame tomography and reviews existing techniques for the quantitative characterization of flames.Future trends in flame tomography for industrial applications are discussed.
Turbulence in laminar premixed V-flames
Institute of Scientific and Technical Information of China (English)
ZHANG; Xiaoqian(张孝谦); LEI; Yu(雷宇); WANG; Baorui(王宝瑞); WANG; Yue(王岳); WEI; Minggang(韦明罡)
2003-01-01
Strong velocity fluctuations had been found in the laminar premixed V-flames. These velocity fluctuations are closely related to the chemical reaction. But the effects of the upstream combustible mixture velocity on the velocity fluctuations inside the flame are quite weak. The probability distribution function (PDF) of the velocity in the centre region of the flame appears "flat top" shaped. By analyzing the experiment results the flame-flow interactions are found to affect the flame not only at large scale in the flow field but also at small scale inside the flame. These effects will give rise to flame generated small scale turbulences.
Premixed flame propagation in vertical tubes
Kazakov, Kirill A
2015-01-01
Analytical treatment of premixed flame propagation in vertical tubes with smooth walls is given. Using the on-shell flame description, equations describing quasi-steady flame with a small but finite front thickness are obtained and solved numerically. It is found that near the limits of inflammability, solutions describing upward flame propagation come in pairs having close propagation speeds, and that the effect of gravity is to reverse the burnt gas velocity profile generated by the flame. On the basis of these results, a theory of partial flame propagation driven by the gravitational field is developed. A complete explanation is given of the intricate observed behavior of limit flames, including dependence of the inflammability range on the size of the combustion domain, the large distances of partial flame propagation, and the progression of flame extinction. The role of the finite front-thickness effects is discussed in detail. Also, various mechanisms governing flame acceleration in smooth tubes are ide...
Differentiable Kernels in Generalized Matrix Learning Vector Quantization
Kästner, M.; Nebel, D.; Riedel, M.; Biehl, M.; Villmann, T.
2013-01-01
In the present paper we investigate the application of differentiable kernel for generalized matrix learning vector quantization as an alternative kernel-based classifier, which additionally provides classification dependent data visualization. We show that the concept of differentiable kernels allo
Kernel current source density method.
Potworowski, Jan; Jakuczun, Wit; Lȩski, Szymon; Wójcik, Daniel
2012-02-01
Local field potentials (LFP), the low-frequency part of extracellular electrical recordings, are a measure of the neural activity reflecting dendritic processing of synaptic inputs to neuronal populations. To localize synaptic dynamics, it is convenient, whenever possible, to estimate the density of transmembrane current sources (CSD) generating the LFP. In this work, we propose a new framework, the kernel current source density method (kCSD), for nonparametric estimation of CSD from LFP recorded from arbitrarily distributed electrodes using kernel methods. We test specific implementations of this framework on model data measured with one-, two-, and three-dimensional multielectrode setups. We compare these methods with the traditional approach through numerical approximation of the Laplacian and with the recently developed inverse current source density methods (iCSD). We show that iCSD is a special case of kCSD. The proposed method opens up new experimental possibilities for CSD analysis from existing or new recordings on arbitrarily distributed electrodes (not necessarily on a grid), which can be obtained in extracellular recordings of single unit activity with multiple electrodes.
Filtering algorithms using shiftable kernels
Chaudhury, Kunal Narayan
2011-01-01
It was recently demonstrated in [4][arxiv:1105.4204] that the non-linear bilateral filter \\cite{Tomasi} can be efficiently implemented using an O(1) or constant-time algorithm. At the heart of this algorithm was the idea of approximating the Gaussian range kernel of the bilateral filter using trigonometric functions. In this letter, we explain how the idea in [4] can be extended to few other linear and non-linear filters [18,21,2]. While some of these filters have received a lot of attention in recent years, they are known to be computationally intensive. To extend the idea in \\cite{Chaudhury2011}, we identify a central property of trigonometric functions, called shiftability, that allows us to exploit the redundancy inherent in the filtering operations. In particular, using shiftable kernels, we show how certain complex filtering can be reduced to simply that of computing the moving sum of a stack of images. Each image in the stack is obtained through an elementary pointwise transform of the input image. Thi...
Quantifying acoustic damping using flame chemiluminescence
Boujo, E.; Denisov, A.; Schuermans, B.; Noiray, N.
2016-12-01
Thermoacoustic instabilities in gas turbines and aeroengine combustors falls within the category of complex systems. They can be described phenomenologically using nonlinear stochastic differential equations, which constitute the grounds for output-only model-based system identification. It has been shown recently that one can extract the governing parameters of the instabilities, namely the linear growth rate and the nonlinear component of the thermoacoustic feedback, using dynamic pressure time series only. This is highly relevant for practical systems, which cannot be actively controlled due to a lack of cost-effective actuators. The thermoacoustic stability is given by the linear growth rate, which results from the combination of the acoustic damping and the coherent feedback from the flame. In this paper, it is shown that it is possible to quantify the acoustic damping of the system, and thus to separate its contribution to the linear growth rate from the one of the flame. This is achieved by post-processing in a simple way simultaneously acquired chemiluminescence and acoustic pressure data. It provides an additional approach to further unravel from observed time series the key mechanisms governing the system dynamics. This straightforward method is illustrated here using experimental data from a combustion chamber operated at several linearly stable and unstable operating conditions.
Detoxification of Jatropha curcas kernel cake by a novel Streptomyces fimicarius strain.
Wang, Xing-Hong; Ou, Lingcheng; Fu, Liang-Liang; Zheng, Shui; Lou, Ji-Dong; Gomes-Laranjo, José; Li, Jiao; Zhang, Changhe
2013-09-15
A huge amount of kernel cake, which contains a variety of toxins including phorbol esters (tumor promoters), is projected to be generated yearly in the near future by the Jatropha biodiesel industry. We showed that the kernel cake strongly inhibited plant seed germination and root growth and was highly toxic to carp fingerlings, even though phorbol esters were undetectable by HPLC. Therefore it must be detoxified before disposal to the environment. A mathematic model was established to estimate the general toxicity of the kernel cake by determining the survival time of carp fingerling. A new strain (Streptomyces fimicarius YUCM 310038) capable of degrading the total toxicity by more than 97% in a 9-day solid state fermentation was screened out from 578 strains including 198 known strains and 380 strains isolated from air and soil. The kernel cake fermented by YUCM 310038 was nontoxic to plants and carp fingerlings and significantly promoted tobacco plant growth, indicating its potential to transform the toxic kernel cake to bio-safe animal feed or organic fertilizer to remove the environmental concern and to reduce the cost of the Jatropha biodiesel industry. Microbial strain profile essential for the kernel cake detoxification was discussed.
Electrical Aspects of Impinging Flames
Chien, Yu-Chien
This dissertation examines the use of electric fields as one mechanism for controlling combustion as flames are partially extinguished when impinging on nearby surfaces. Electrical aspects of flames, specifically, the production of chemi-ions in hydrocarbon flames and the use of convective flows driven by these ions, have been investigated in a wide range of applications in prior work but despite this fairly comprehensive effort to study electrical aspects of combustion, relatively little research has focused on electrical phenomena near flame extinguishment, nor for flames near impingement surfaces. Electrical impinging flames have complex properties under global influences of ion-driven winds and flow field disturbances from the impingement surface. Challenges of measurements when an electric field is applied in the system have limited an understanding of changes to the flame behavior and species concentrations caused by the field. This research initially characterizes the ability of high voltage power supplies to respond on sufficiently short time scales to permit real time electrical flame actuation. The study then characterizes the influence of an electric field on the impinging flame shape, ion current and flow field of the thermal plume associated with the flame. The more significant further examinations can be separated into two parts: 1) the potential for using electric fields to control the release of carbon monoxide (CO) from surface-impinging flames, and 2) an investigation of controlling electrically the heat transfer to a plate on which the flame impinges. Carbon monoxide (CO) results from the incomplete oxidation of hydrocarbon fuels and, while CO can be desirable in some syngas processes, it is usually a dangerous emission from forest fires, gas heaters, gas stoves, or furnaces where insufficient oxygen in the core reaction does not fully oxidize the fuel to carbon dioxide and water. Determining how carbon monoxide is released and how heat transfer
Memory Kernel in the Expertise of Chess Players
Schaigorodsky, Ana L; Billoni, Orlando V
2015-01-01
In this work we investigate a mechanism for the emergence of long-range time correlations observed in a chronologically ordered database of chess games. We analyze a modified Yule-Simon preferential growth process proposed by Cattuto et al., which includes memory effects by means of a probabilistic kernel. According to the Hurst exponent of different constructed time series from the record of games, artificially generated databases from the model exhibit similar long-range correlations. In addition, the inter-event time frequency distribution is well reproduced by the model for realistic parameter values. In particular, we find the inter-event time distribution properties to be correlated with the expertise of the chess players through the memory kernel extension. Our work provides new information about the strategies implemented by players with different levels of expertise, showing an interesting example of how popularities and long-range correlations build together during a collective learning process.
Kernel parameter dependence in spatial factor analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
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...
Improving the Bandwidth Selection in Kernel Equating
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…
Ranking Support Vector Machine with Kernel Approximation.
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.
Generalized Derivative Based Kernelized Learning Vector Quantization
Schleif, Frank-Michael; Villmann, Thomas; Hammer, Barbara; Schneider, Petra; Biehl, Michael; Fyfe, Colin; Tino, Peter; Charles, Darryl; Garcia-Osoro, Cesar; Yin, Hujun
2010-01-01
We derive a novel derivative based version of kernelized Generalized Learning Vector Quantization (KGLVQ) as an effective, easy to interpret, prototype based and kernelized classifier. It is called D-KGLVQ and we provide generalization error bounds, experimental results on real world data, showing t
PALM KERNEL SHELL AS AGGREGATE FOR LIGHT
African Journals Online (AJOL)
of cement, sand, gravel andpalm kernel shells respectively gave the highest compressive strength of ... Keywords: Aggregate, Cement, Concrete, Sand, Palm Kernel Shell. ... delivered to the jOb Slte in a plastic ... structures, breakwaters, piers and docks .... related to cement content at a .... sheet and the summary is shown.
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...
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate its better robustness to the complex and nonlinear variations of real face images, such as illumination, facial expression, scale and pose variations, experiments are carried out on the Olivetti Research Laboratory, Yale and self-built face databases. The results indicate that in contrast to kernel principal component analysis and kernel linear discriminant analysis, the method can achieve lower (7%) error rate using only a very small set of features. Furthermore, a new corrected kernel model is proposed to improve the recognition performance. Experimental results confirm its superiority (1% in terms of recognition rate) to other polynomial kernel models.
Parameter-Free Spectral Kernel Learning
Mao, Qi
2012-01-01
Due to the growing ubiquity of unlabeled data, learning with unlabeled data is attracting increasing attention in machine learning. In this paper, we propose a novel semi-supervised kernel learning method which can seamlessly combine manifold structure of unlabeled data and Regularized Least-Squares (RLS) to learn a new kernel. Interestingly, the new kernel matrix can be obtained analytically with the use of spectral decomposition of graph Laplacian matrix. Hence, the proposed algorithm does not require any numerical optimization solvers. Moreover, by maximizing kernel target alignment on labeled data, we can also learn model parameters automatically with a closed-form solution. For a given graph Laplacian matrix, our proposed method does not need to tune any model parameter including the tradeoff parameter in RLS and the balance parameter for unlabeled data. Extensive experiments on ten benchmark datasets show that our proposed two-stage parameter-free spectral kernel learning algorithm can obtain comparable...
Soot Formation in Laminar Acetylene/Air Diffusion Flames at Atmospheric Pressure. Appendix J
Xu, F.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)
2001-01-01
The flame structure and soot-formation (soot nucleation and growth) properties of axisymmetric laminar coflowing jet diffusion flames were studied experimentally. Test conditions involved acetylene-nitrogen jets burning in coflowing air at atmospheric pressure. Measurements were limited to the axes of the flames and included soot concentrations, soot temperatures, soot structure, major gas species concentrations, radical species (H, OH, and O) concentrations, and gas velocities. The results show that as distance increases along the axes of the flames, detectable soot formation begins when significant H concentrations are present, and ends when acetylene concentrations become small. Species potentially associated with soot oxidation--O2, CO2, H2O, O, and OH-are present throughout the soot-formation region so that soot formation and oxidation proceed at the same time. Strong rates of soot growth compared to soot nucleation early in the soot-formation process, combined with increased rates of soot nucleation and oxidation as soot formation proceeds, causes primary soot particle diameters to reach a maximum relatively early in the soot-formation process. Aggregation of primary soot particles proceeds, however, until the final stages of soot oxidation. Present measurements of soot growth (corrected for soot oxidation) in laminar diffusion flames were consistent with earlier measurements of soot growth in laminar premixed flames and exhibited encouraging agreement with existing hydrogen-abstraction/carbon-addition (HACA) soot growth mechanisms in the literature that were developed based on measurements within laminar premixed flames. Measured primary soot particle nucleation rates in the present laminar diffusion flames also were consistent with corresponding rates measured in laminar premixed flames and yielded a crude correlation in terms of acetylene and H concentrations and the temperature.
Soot Formation in Laminar Acetylene/Air Diffusion Flames at Atmospheric Pressure. Appendix H
Xu, F.; Faeth, G. M.; Yuan, Z.-G. (Technical Monitor); Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)
2001-01-01
The flame structure and soot-formation (soot nucleation and growth) properties of axisymmetric laminar coflowing jet diffusion flames were studied experimentally. Test conditions involved acetylene-nitrogen jets burning in coflowing air at atmospheric pressure. Measurements were limited to the axes of the flames and included soot concentrations, soot temperatures, soot structure, major gas species concentrations, radical species (H, OH, and O) concentrations, and gas velocities. The results show that as distance increases along the axes of the flames, detectable soot formation begins when significant H concentrations are present, and ends when acetylene concentrations become small. Species potentially associated with soot oxidation-O2, CO2, H2O, O, and OH-are present throughout the soot-formation region so that soot formation and oxidation proceed at the same time. Strong rates of soot growth compared to soot nucleation early in the soot-formation process, combined with increased rates of soot nucleation and oxidation as soot formation proceeds, causes primary soot particle diameters to reach a maximum relatively early in the soot-formation process. Aggregation of primary soot particles proceeds, however, until the final stages of soot oxidation. Present measurements of soot growth (corrected for soot oxidation) in laminar diffusion flames were consistent with earlier measurements of soot growth in laminar premixed flames and exhibited encouraging agreement with existing hydrogen-abstraction/carbon-addition (HACA) soot growth mechanisms in the literature that were developed based on measurements within laminar premixed flames. Measured primary soot particle nucleation rates in the present laminar diffusion flames also were consistent with corresponding rates measured in laminar premixed flames and yielded a crude correlation in terms of acetylene and H concentrations and the temperature.
Soot Formation in Laminar Acetylene/Air Diffusion Flames at Atmospheric Pressure. Appendix C
Xu, F.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)
2000-01-01
The flame structure and soot-formation (soot nucleation and growth) properties of axisymmetric laminar coflowing jet diffusion flames were studied experimentally. Test conditions involved acetylene-nitrogen jets burning in coflowing air at atmospheric pressure. Measurements were limited to the axes of the flames and included soot concentrations, soot temperatures, soot structure, major gas species concentrations, radical species (H, OH, and O) concentrations, and gas velocities. The results show that as distance increases along the axes of the flames, detectable soot formation begins when significant H concentrations are present, and ends when acetylene concentrations become small. Species potentially associated with soot oxidation-O2, CO2, H2O, O, and OH-are present throughout the soot-formation region so that soot formation and oxidation proceed at the same time. Strong rates of soot growth compared to soot nucleation early in the soot-formation process, combined with increased rates of soot nucleation and oxidation as soot formation proceeds, causes primary soot particle diameters to reach a maximum relatively early in the soot-formation process. Aggregation of primary soot particles proceeds, however, until the final stages of soot oxidation. Present measurements of soot growth (corrected for soot oxidation) in laminar diffusion flames were consistent with earlier measurements of soot growth in laminar premixed flames and exhibited encouraging agreement with existing hydrogen-abstraction/carbon-addition (HACA) soot growth mechanisms in the literature that were developed based on measurements within laminar premixed flames. Measured primary soot particle nucleation rates in the present laminar diffusion flames also were consistent with corresponding rates measured in laminar premixed flames and yielded a crude correlation in terms of acetylene and H concentrations and the temperature.
Role of flame generated flow in the formation of tulip flame
Energy Technology Data Exchange (ETDEWEB)
Jeung, I.S.; Cho, K.K.; Jeong, K.S.
1989-01-01
The role of flame generated flow during the laminar 'tulip' flame formation in a long rectangular combustion vessel was examined by laser Doppler velocimeter measurement, high speed schlieren photographic flame visualization, and combustion vessel pressure measurement. Results of these investigations showed the transition of convex-shaped flame to concave-shaped tulip flame and interactions between the flame shape and flame generated flow in a confined geometry, and gave physical understanding of flow field formation of tulip flame. 15 references.
Directory of Open Access Journals (Sweden)
Petcharat, V. and
2004-09-01
Full Text Available The objective of this study was to determine the optimum rate of oil palm kernel meal, for an abalone mushroom (Pleurotus cystidiosus cultivation. Different concentrations of oil palm kernel meal (5- 20% were added to pararubber sawdust and used to grow the abalone mushroom in plastic bags. Growth rate of the mycelia, number of days from watering to harvesting and yield were compared to those on 94% sawdust + 5% rice bran + 1% Ca(OH2. The results showed that 10% oil palm kernel meal was the optimum concentration for abalone mushroom cultivation. Yield on 950 g/bag of 89% sawdust + 10% oil palm kernel meal + 1% Ca(OH2 was 202.12 g/bag (B.E. = 60.79% during 120 days of havesting time. Addition of higher concentration of oil palm kernel meal (15-20% did not increase yield of the basidiocarps.
Kim, Hun; Woloshuk, C P
2008-06-01
Fumonisin B1 (FB(1)) biosynthesis is repressed in cultures containing ammonium as the nitrogen source and when grown on blister kernels, the earliest stages of kernel development. In this study AREA, a regulator of nitrogen metabolism, was disrupted in Fusarium verticilliodes. The mutant (DeltaareA) grew poorly on mature maize kernels, but grew similar to wild type (WT) with the addition of ammonium phosphate. FB(1) was not produced by DeltaareA under any condition or by the WT with added ammonium phosphate. Constitutive expression of AREA (strain AREA-CE) rescued the growth and FB(1) defects in DeltaareA. Growth of WT, DeltaareA, and AREA-CE on blister-stage kernels was similar. After 7 days of growth, none of the strains produced FB(1) and the pH of the kernel tissues was 8.0. Addition of amylopectin to the blister kernels resulted in a pH near 6.6 and FB(1) production by WT and AREA-CE. The results support the hypothesis that FB(1) biosynthesis is regulated by AREA. Also the failure to produce FB(1) in blister kernels is due to high pH conditions generated because of an unfavorable carbon/nitrogen environment.
Soot Aerosol Properties in Laminar Soot-Emitting Microgravity Nonpremixed Flames
Konsur, Bogdan; Megaridis, Constantine M.; Griffin, Devon W.
1999-01-01
The 0-g flame soot measurements reported in previous studies are extended by adding new 0-g data for different fuel flow rates and burner diameters. The new flame conditions allow more conclusive comparisons regarding the effect of characteristic flow residence times on soot field structure, the influence of fuel preheat on fuel pyrolysis rates near the flame centerline, and the premature cessation of soot growth along the soot annulus in 0-g when the fuel is preheated. The paper also reports on the implementation of thermophoretic soot sampling in a specific 0-g flame featuring burner exit velocities typical of buoyant flames and presents quantitative data on the radial variation of soot microstructure at a fixed height above the burner mouth.
Heat-kernel approach for scattering
Li, Wen-Du
2015-01-01
An approach for solving scattering problems, based on two quantum field theory methods, the heat kernel method and the scattering spectral method, is constructed. This approach has a special advantage: it is not only one single approach; it is indeed a set of approaches for solving scattering problems. Concretely, we build a bridge between a scattering problem and the heat kernel method, so that each method of calculating heat kernels can be converted into a method of solving a scattering problem. As applications, we construct two approaches for solving scattering problems based on two heat-kernel expansions: the Seeley-DeWitt expansion and the covariant perturbation theory. In order to apply the heat kernel method to scattering problems, we also calculate two off-diagonal heat-kernel expansions in the frames of the Seeley-DeWitt expansion and the covariant perturbation theory, respectively. Moreover, as an alternative application of the relation between heat kernels and partial-wave phase shifts presented in...
Ideal regularization for learning kernels from labels.
Pan, Binbin; Lai, Jianhuang; Shen, Lixin
2014-08-01
In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently.
Mechanistic aspects of ionic reactions in flames
DEFF Research Database (Denmark)
Egsgaard, H.; Carlsen, L.
1993-01-01
Some fundamentals of the ion chemistry of flames are summarized. Mechanistic aspects of ionic reactions in flames have been studied using a VG PlasmaQuad, the ICP-system being substituted by a simple quartz burner. Simple hydrocarbon flames as well as sulfur-containing flames have been investigated....... The simple hydrocarbon flames are dominated by a series of hydrocarbonic ions and, to a minor extent, protonated oxo-compounds. The introduction of sulfur to the flames leads to significant changes in the ion composition, as sulfur-containing species become dominant. The ability of the technique to study...
Kernel score statistic for dependent data.
Malzahn, Dörthe; Friedrichs, Stefanie; Rosenberger, Albert; Bickeböller, Heike
2014-01-01
The kernel score statistic is a global covariance component test over a set of genetic markers. It provides a flexible modeling framework and does not collapse marker information. We generalize the kernel score statistic to allow for familial dependencies and to adjust for random confounder effects. With this extension, we adjust our analysis of real and simulated baseline systolic blood pressure for polygenic familial background. We find that the kernel score test gains appreciably in power through the use of sequencing compared to tag-single-nucleotide polymorphisms for very rare single nucleotide polymorphisms with <1% minor allele frequency.
Kernel-based Maximum Entropy Clustering
Institute of Scientific and Technical Information of China (English)
JIANG Wei; QU Jiao; LI Benxi
2007-01-01
With the development of Support Vector Machine (SVM),the "kernel method" has been studied in a general way.In this paper,we present a novel Kernel-based Maximum Entropy Clustering algorithm (KMEC).By using mercer kernel functions,the proposed algorithm is firstly map the data from their original space to high dimensional space where the data are expected to be more separable,then perform MEC clustering in the feature space.The experimental results show that the proposed method has better performance in the non-hyperspherical and complex data structure.
Kernel adaptive filtering a comprehensive introduction
Liu, Weifeng; Haykin, Simon
2010-01-01
Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, O
Multiple Operator-valued Kernel Learning
Kadri, Hachem; Bach, Francis; Preux, Philippe
2012-01-01
This paper addresses the problem of learning a finite linear combination of operator-valued kernels. We study this problem in the case of kernel ridge regression for functional responses with a lr-norm constraint on the combination coefficients. We propose a multiple operator-valued kernel learning algorithm based on solving a system of linear operator equations by using a block coordinate descent procedure. We experimentally validate our approach on a functional regression task in the context of finger movement prediction in Brain-Computer Interface (BCI).
Polynomial Kernelizations for $\\MINF_1$ and $\\MNP$
Kratsch, Stefan
2009-01-01
The relation of constant-factor approximability to fixed-parameter tractability and kernelization is a long-standing open question. We prove that two large classes of constant-factor approximable problems, namely $\\MINF_1$ and $\\MNP$, including the well-known subclass $\\MSNP$, admit polynomial kernelizations for their natural decision versions. This extends results of Cai and Chen (JCSS 1997), stating that the standard parameterizations of problems in $\\MSNP$ and $\\MINF_1$ are fixed-parameter tractable, and complements recent research on problems that do not admit polynomial kernelizations (Bodlaender et al. ICALP 2008).
Approximating W projection as a separable kernel
Merry, Bruce
2015-01-01
W projection is a commonly-used approach to allow interferometric imaging to be accelerated by Fast Fourier Transforms (FFTs), but it can require a huge amount of storage for convolution kernels. The kernels are not separable, but we show that they can be closely approximated by separable kernels. The error scales with the fourth power of the field of view, and so is small enough to be ignored at mid to high frequencies. We also show that hybrid imaging algorithms combining W projection with ...
Approximating W projection as a separable kernel
Merry, Bruce
2016-02-01
W projection is a commonly used approach to allow interferometric imaging to be accelerated by fast Fourier transforms, but it can require a huge amount of storage for convolution kernels. The kernels are not separable, but we show that they can be closely approximated by separable kernels. The error scales with the fourth power of the field of view, and so is small enough to be ignored at mid- to high frequencies. We also show that hybrid imaging algorithms combining W projection with either faceting, snapshotting, or W stacking allow the error to be made arbitrarily small, making the approximation suitable even for high-resolution wide-field instruments.
Extension of Wirtinger's Calculus in Reproducing Kernel Hilbert Spaces and the Complex Kernel LMS
Bouboulis, Pantelis
2010-01-01
Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. The primary mathematical tool employed in these methods is the notion of the Reproducing Kernel Hilbert Space. However, so far, the emphasis has been on batch techniques. It is only recently, that online techniques have been considered in the context of adaptive signal processing tasks. Moreover, these efforts have only been focussed on and real valued data sequences. To the best of our knowledge, no kernel-based strategy has been developed, so far, that is able to deal with complex valued signals. In this paper, we present a general framework to attack the problem of adaptive filtering of complex signals, using either real reproducing kernels, taking advantage of a technique called \\textit{complexification} of real RKHSs, or complex reproducing kernels, highlighting the use of the complex gaussian kernel. In order to derive gradients of operators that need to be defined on the associat...
Kernel map compression for speeding the execution of kernel-based methods.
Arif, Omar; Vela, Patricio A
2011-06-01
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machines. Unfortunately, after learning, the computational complexity of execution through a kernel is of the order of the size of the training set, which is quite large for many applications. This paper proposes a two-step procedure for arriving at a compact and computationally efficient execution procedure. After learning in the kernel space, the proposed extension exploits the universal approximation capabilities of generalized radial basis function neural networks to efficiently approximate and replace the projections onto the empirical kernel map used during execution. Sample applications demonstrate significant compression of the kernel representation with graceful performance loss.
Research on flame retardation of wool fibers
Energy Technology Data Exchange (ETDEWEB)
Enomoto, Ichiro; Ametani, Kazuo; Sawai, Takeshi (Tokyo Metropolitan Isotope Research Center (Japan))
1990-01-01
Flame retardant, vinyl phosphonate oligomer, was uniformly impregnated in wool fibers, and by irradiating low energy electron beam or cobalt-60 gamma ray, the flame retardation of fabrics was attempted, as the results, the following knowledges were obtained. At the rate of sticking of flame retardant lower than that in cotton fabrics, sufficient flame retarding property can be given. The flame retarding property withstands 30 times of washing. The lowering of strength due to the processing hardly arose. For the flame retardation, gamma-ray was more effective than electron beam. Since the accidents of burning clothes have occurred frequently, their flame retardation has been demanded. So far the flame retardation of cotton fabrics has been advanced, but this time the research on the flame retardation of wool fabrics was carried out by the same method. The experimental method is explained. As for the performance of the processed fabrics, the rate of sticking of the flame retardant, the efficiency of utilization, the flame retarding property, the endurance in washing and the tensile and tearing strength were examined. As the oxygen index was higher, the flame retarding property was higher, and in the case of the index being more than 27, the flame retarding property is sufficient, that is, the rate of sticking of 6% in serge and 5% in muslin. (K.I.).
The Linux kernel as flexible product-line architecture
Jonge, M. de
2002-01-01
The 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 component they real
7 CFR 51.2296 - Three-fourths half kernel.
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...
7 CFR 981.401 - Adjusted kernel weight.
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...
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...
7 CFR 51.1403 - Kernel color classification.
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...
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.
Relative n-widths of periodic convolution classes with NCVD-kernel and B-kernel
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
In this paper,we consider the relative n-widths of two kinds of periodic convolution classes,Kp(K) and Bp(G),whose convolution kernels are NCVD-kernel K and B-kernel G. The asymptotic estimations of Kn(Kp(K),Kp(K))q and Kn(Bp(G),Bp(G))q are obtained for p=1 and ∞,1≤ q≤∞.
Reproducing Kernel for D2(Ω, ρ) and Metric Induced by Reproducing Kernel
Institute of Scientific and Technical Information of China (English)
ZHAO Zhen Gang
2009-01-01
An important property of the reproducing kernel of D2(Ω, ρ) is obtained and the reproducing kernels for D2(Ω, ρ) are calculated when Ω = Bn × Bn and ρ are some special functions. A reproducing kernel is used to construct a semi-positive definite matrix and a distance function defined on Ω×Ω. An inequality is obtained about the distance function and the pseudodistance induced by the matrix.
Chung, Yong Ho
2013-03-01
This study of nitrogen-diluted non-premixed counterflow flames with finite burner diameters investigates the important role of the outer-edge flame on flame extinction through experimental and numerical analyses. It explores flame stability diagrams mapping the flame extinction response of nitrogen-diluted non-premixed counterflow flames to varying global strain rates in terms of burner diameter, burner gap, and velocity ratio. A critical nitrogen mole fraction exists beyond which the flame cannot be sustained; the critical nitrogen mole fraction versus global strain rate curves have C-shapes for various burner diameters, burner gaps, and velocity ratios. At sufficiently high strain-rate flames, these curves collapse into one curve; therefore, the flames follow the one-dimensional flame response of a typical diffusion flame. Low strain-rate flames are significantly affected by radial conductive heat loss, and therefore flame length. Three flame extinction modes are identified: flame extinction through shrinkage of the outer-edge flame with or without oscillations at the outer-edge flame prior to the extinction, and flame extinction through a flame hole at the flame center. The extinction modes are significantly affected by the behavior of the outer-edge flame. Detailed explanations are provided based on the measured flame-surface temperature and numerical evaluation of the fractional contribution of each term in the energy equation. Radial conductive heat loss at the flame edge to ambience is the main mechanism of extinction through shrinkage of the outer-edge flame in low strain-rate flames. Reduction of the burner diameter can extend the flame extinction mode by shrinking the outer-edge flame in higher strain-rate flames. © 2012 Elsevier Ltd. All rights reserved.
Enhancement of turbulent flame speed of V-shaped flames in fractal-grid-generated turbulence
Verbeek, A.A.; Willems, P.A.; Stoffels, G.G.M.; Geurts, B.J.; Meer, van der T.H.
2016-01-01
A variety of fractal grids is used to investigate how fractal-grid-generated turbulence affects the turbulent flame speed for premixed flames. The grids are placed inside a rectangular duct and a V-shaped flame is stabilized downstream of the duct, using a metal wire. This flame is characterized usi
33 CFR 154.822 - Detonation arresters, flame arresters, and flame screens.
2010-07-01
... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Detonation arresters, flame arresters, and flame screens. 154.822 Section 154.822 Navigation and Navigable Waters COAST GUARD... BULK Vapor Control Systems § 154.822 Detonation arresters, flame arresters, and flame screens. (a)...
Discriminant Kernel Assignment for Image Coding.
Deng, Yue; Zhao, Yanyu; Ren, Zhiquan; Kong, Youyong; Bao, Feng; Dai, Qionghai
2017-06-01
This paper proposes discriminant kernel assignment (DKA) in the bag-of-features framework for image representation. DKA slightly modifies existing kernel assignment to learn width-variant Gaussian kernel functions to perform discriminant local feature assignment. When directly applying gradient-descent method to solve DKA, the optimization may contain multiple time-consuming reassignment implementations in iterations. Accordingly, we introduce a more practical way to locally linearize the DKA objective and the difficult task is cast as a sequence of easier ones. Since DKA only focuses on the feature assignment part, it seamlessly collaborates with other discriminative learning approaches, e.g., discriminant dictionary learning or multiple kernel learning, for even better performances. Experimental evaluations on multiple benchmark datasets verify that DKA outperforms other image assignment approaches and exhibits significant efficiency in feature coding.
Multiple Kernel Spectral Regression for Dimensionality Reduction
Directory of Open Access Journals (Sweden)
Bing Liu
2013-01-01
Full Text Available Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL into SR for dimensionality reduction. The proposed approach (termed MKL-SR seeks an embedding function in the Reproducing Kernel Hilbert Space (RKHS induced by the multiple base kernels. An MKL-SR algorithm is proposed to improve the performance of kernel-based SR (KSR further. Furthermore, the proposed MKL-SR algorithm can be performed in the supervised, unsupervised, and semi-supervised situation. Experimental results on supervised classification and semi-supervised classification demonstrate the effectiveness and efficiency of our algorithm.
Quantum kernel applications in medicinal chemistry.
Huang, Lulu; Massa, Lou
2012-07-01
Progress in the quantum mechanics of biological molecules is being driven by computational advances. The notion of quantum kernels can be introduced to simplify the formalism of quantum mechanics, making it especially suitable for parallel computation of very large biological molecules. The essential idea is to mathematically break large biological molecules into smaller kernels that are calculationally tractable, and then to represent the full molecule by a summation over the kernels. The accuracy of the kernel energy method (KEM) is shown by systematic application to a great variety of molecular types found in biology. These include peptides, proteins, DNA and RNA. Examples are given that explore the KEM across a variety of chemical models, and to the outer limits of energy accuracy and molecular size. KEM represents an advance in quantum biology applicable to problems in medicine and drug design.
Kernel method-based fuzzy clustering algorithm
Institute of Scientific and Technical Information of China (English)
Wu Zhongdong; Gao Xinbo; Xie Weixin; Yu Jianping
2005-01-01
The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.
Kernel representations for behaviors over finite rings
Kuijper, M.; Pinto, R.; Polderman, J.W.; Yamamoto, Y.
2006-01-01
In this paper we consider dynamical systems finite rings. The rings that we study are the integers modulo a power of a given prime. We study the theory of representations for such systems, in particular kernel representations.
Ensemble Approach to Building Mercer Kernels
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...
Convolution kernels for multi-wavelength imaging
National Research Council Canada - National Science Library
Boucaud, Alexandre; Bocchio, Marco; Abergel, Alain; Orieux, François; Dole, Hervé; Hadj-Youcef, Mohamed Amine
2016-01-01
.... Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been...
Difference image analysis: Automatic kernel design using information criteria
Bramich, D M; Alsubai, K A; Bachelet, E; Mislis, D; Parley, N
2015-01-01
We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially-invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularisation. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unreg...
Asymptotic analysis of outwardly propagating spherical flames
Institute of Scientific and Technical Information of China (English)
Yun-Chao Wu; Zheng Chen
2012-01-01
Asymptotic analysis is conducted for outwardly propagating spherical flames with large activation energy.The spherical flame structure consists of the preheat zone,reaction zone,and equilibrium zone.Analytical solutions are separately obtained in these three zones and then asymptotically matched.In the asymptotic analysis,we derive a correlation describing the spherical flame temperature and propagation speed changing with the flame radius.This correlation is compared with previous results derived in the limit of infinite value of activation energy.Based on this correlation,the properties of spherical flame propagation are investigated and the effects of Lewis number on spherical flame propagation speed and extinction stretch rate are assessed.Moreover,the accuracy and performance of different models used in the spherical flame method are examined.It is found that in order to get accurate laminar flame speed and Markstein length,non-linear models should be used.
Flame Retardants Used in Flexible Polyurethane Foam
The partnership project on flame retardants in furniture seeks to update the health and environmental profiles of flame-retardant chemicals that meet fire safety standards for upholstered consumer products with polyurethane foam
Preparing UO2 kernels by gelcasting
Institute of Scientific and Technical Information of China (English)
GUO Wenli; LIANG Tongxiang; ZHAO Xingyu; HAO Shaochang; LI Chengliang
2009-01-01
A process named gel-casting has been developed for the production of dense UO2 kernels for the high-ten-temperature gas-cooled reactor. Compared with the sol-gel process, the green microspheres can be got by dispersing the U3O8 slurry in gelcasting process, which means that gelcasting is a more facilitative process with less waste in fabricating UO2 kernels. The heat treatment.
The Bergman kernel functions on Hua domains
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
We get the Bergman kernel functions in explicit formulas on four types of Hua domain.There are two key steps: First, we give the holomorphic automorphism groups of four types of Hua domain; second, we introduce the concept of semi-Reinhardt domain and give their complete orthonormal systems. Based on these two aspects we obtain the Bergman kernel function in explicit formulas on Hua domains.
Fractal Weyl law for Linux Kernel Architecture
Ermann, L; Shepelyansky, D L
2010-01-01
We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be $\
Varying kernel density estimation on ℝ+
Mnatsakanov, Robert; Sarkisian, Khachatur
2015-01-01
In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction. PMID:26740729
Adaptively Learning the Crowd Kernel
Tamuz, Omer; Belongie, Serge; Shamir, Ohad; Kalai, Adam Tauman
2011-01-01
We introduce an algorithm that, given n objects, learns a similarity matrix over all n^2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen triplet-based relative-similarity queries. Each query has the form "is object 'a' more similar to 'b' or to 'c'?" and is chosen to be maximally informative given the preceding responses. The output is an embedding of the objects into Euclidean space (like MDS); we refer to this as the "crowd kernel." The runtime (empirically observed to be linear) and cost (about $0.15 per object) of the algorithm are small enough to permit its application to databases of thousands of objects. The distance matrix provided by the algorithm allows for the development of an intuitive and powerful sequential, interactive search algorithm which we demonstrate for a variety of visual stimuli. We present quantitative results that demonstrate the benefit in cost and time of our approach compared to a nonadaptive approach. We also show the ability of our appr...
Evaluating the Gradient of the Thin Wire Kernel
Wilton, Donald R.; Champagne, Nathan J.
2008-01-01
Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.
On the Inclusion Relation of Reproducing Kernel Hilbert Spaces
Zhang, Haizhang; Zhao, Liang
2011-01-01
To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are established. A full table of inclusion relations among widely-used translation invariant kernels is given. Concrete examples for Hilbert-Schmidt kernels are presented as well. We also discuss the preservation of such a relation under various operations of ...
Firefighters and flame retardant activism.
Cordner, Alissa; Rodgers, Kathryn M; Brown, Phil; Morello-Frosch, Rachel
2015-02-01
In the past decade, exposure to flame retardant chemicals has become a pressing health concern and widely discussed topic of public safety for firefighters in the United States. Working through local, state, and national unions and independent health and advocacy organizations, firefighters have made important contributions to efforts to restrict the use of certain flame retardants. Firefighters are key members in advocacy coalitions dedicated to developing new environmental health regulations and reforming flammability standards to reflect the best available fire science. Their involvement has been motivated by substantiated health concerns and critiques of deceptive lobbying practices by the chemical industry. Drawing on observations and interviews with firefighters, fire safety experts, and other involved stakeholders, this article describes why firefighters are increasingly concerned about their exposure to flame retardant chemicals in consumer products, and analyzes their involvement in state and national environmental health coalitions.
Droplet and Supercritical Flame Dynamics in Propulsion
2010-03-26
In order to study the stability of a lifted jet flame by nozzle-generated vortexes, we have developed a chemical explosive mode analysis ( CEMA ) to...runaway can consequently be distinguished. CEMA of the lifted flame shows the existence of two premixed flame fronts, which are difficult to detect
Premixed flame propagation in vertical tubes
Kazakov, Kirill A.
2016-04-01
Analytical treatment of the premixed flame propagation in vertical tubes with smooth walls is given. Using the on-shell flame description, equations for a quasi-steady flame with a small but finite front thickness are obtained and solved numerically. It is found that near the limits of inflammability, solutions describing upward flame propagation come in pairs having close propagation speeds and that the effect of gravity is to reverse the burnt gas velocity profile generated by the flame. On the basis of these results, a theory of partial flame propagation driven by a strong gravitational field is developed. A complete explanation is given of the intricate observed behavior of limit flames, including dependence of the inflammability range on the size of the combustion domain, the large distances of partial flame propagation, and the progression of flame extinction. The role of the finite front-thickness effects is discussed in detail. Also, various mechanisms governing flame acceleration in smooth tubes are identified. Acceleration of methane-air flames in open tubes is shown to be a combined effect of the hydrostatic pressure difference produced by the ambient cold air and the difference of dynamic gas pressure at the tube ends. On the other hand, a strong spontaneous acceleration of the fast methane-oxygen flames at the initial stage of their evolution in open-closed tubes is conditioned by metastability of the quasi-steady propagation regimes. An extensive comparison of the obtained results with the experimental data is made.
30 CFR 14.20 - Flame resistance.
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Flame resistance. 14.20 Section 14.20 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF... § 14.20 Flame resistance. Conveyor belts for use in underground coal mines must be flame-resistant...
Acoustic power measurements of oscillating flames
Valk, M.
1981-01-01
The acoustic power of an oscillating flame is measured. A turbulent premixed propane/air flame is situated near a pressure antinode of a standing wave in a laboratory combustion chamber. This standing wave is generated by a piston. The fluctuating heat release of the flame will supply acoustic power
Hysteresis and transition in swirling nonpremixed flames
Tummers, M.J.; Hübner, A.W.; Veen, van E.H.; Hanjalic, K.; Meer, van der Th.H.
2009-01-01
Strongly swirling nonpremixed flames are known to exhibit a hysteresis when transiting from an attached long, sooty, yellow flame to a short lifted blue flame, and vice versa. The upward transition (by increasing the air and fuel flow rates) corresponds to a vortex breakdown, i.e. an abrupt change f
Acoustic power measurements of oscillating flames
Valk, M.
1981-01-01
The acoustic power of an oscillating flame is measured. A turbulent premixed propane/air flame is situated near a pressure antinode of a standing wave in a laboratory combustion chamber. This standing wave is generated by a piston. The fluctuating heat release of the flame will supply acoustic power
Environmental Considerations for Flame Resistant Textiles
Virtually all common textiles will ignite and burn. There are mandatory and voluntary cigarette and open-flame ignition regulations to address unreasonable fire risks associated with textile products that require them to be treated with and/or contain flame retardant chemicals to make them flame res...
Laser-induced incandescence of titania nanoparticles synthesized in a flame
Cignoli, F.; Bellomunno, C.; Maffi, S.; Zizak, G.
2009-09-01
Laser induced incandescence experiments were carried out in a flame reactor during titania nanoparticle synthesis. The structure of the reactor employed allowed for a rather smooth particle growth along the flame axis, with limited mixing of different size particles. Particle incandescence was excited by the 4th harmonic of a Nd:YAG laser. The radiation emitted from the particles was recorded in time and checked by spectral analysis. Results were compared with measurements from transmission electron microscopy of samples taken at the same locations probed by incandescence. This was done covering a portion of the flame length within which a particle size growth of a factor of about four was detected . The incandescence decay time was found to increase monotonically with particle size. The attainment of a process control tool in nanoparticle flame synthesis appears to be realistic.
Cars Spectroscopy of Propellant Flames
1983-11-01
Harris, K. Aron, and J. Fendell "N2 and 00 Vibrational CARS and H2 Rotational CARS Spectroscopy of CHI/N20 Flames," Proceedings of the Nineteenth...JANNAF Combustion Meeting, CIIA Publication No. 366, 1982, p 123. 21. K. Aron, L. E. Harris, and J. Fendell , "N and CO Vibrational CARS and H2 Rotational...9 6 5 . p 3 8 4 . . . . . 23. J. Fendell , L. E, Harris, and K. Aron, "Theoretical Calculation of 11 CARS S-Branches for Propellant Flames
Simulations and experiments on the ignition probability in turbulent premixed bluff-body flames
Sitte, Michael Philip; Bach, Ellen; Kariuki, James; Bauer, Hans-Jörg; Mastorakos, Epaminondas
2016-05-01
The ignition characteristics of a premixed bluff-body burner under lean conditions were investigated experimentally and numerically with a physical model focusing on ignition probability. Visualisation of the flame with a 5 kHz OH* chemiluminescence camera confirmed that successful ignitions were those associated with the movement of the kernel upstream, consistent with previous work on non-premixed systems. Performing many separate ignition trials at the same spark position and flow conditions resulted in a quantification of the ignition probability Pign, which was found to decrease with increasing distance downstream of the bluff body and a decrease in equivalence ratio. Flows corresponding to flames close to the blow-off limit could not be ignited, although such flames were stable if reached from a richer already ignited condition. A detailed comparison with the local Karlovitz number and the mean velocity showed that regions of high Pign are associated with low Ka and negative bulk velocity (i.e. towards the bluff body), although a direct correlation was not possible. A modelling effort that takes convection and localised flame quenching into account by tracking stochastic virtual flame particles, previously validated for non-premixed and spray ignition, was used to estimate the ignition probability. The applicability of this approach to premixed flows was first evaluated by investigating the model's flame propagation mechanism in a uniform turbulence field, which showed that the model reproduces the bending behaviour of the ST-versus-u‧ curve. Then ignition simulations of the bluff-body burner were carried out. The ignition probability map was computed and it was found that the model reproduces all main trends found in the experimental study.
Institute of Scientific and Technical Information of China (English)
无
2012-01-01
In this paper,we consider the reaction diffusion equations with strong generic delay kernel and non-local effect,which models the microbial growth in a flow reactor.The existence of traveling waves is established for this model.More precisely,using the geometric singular perturbation theory,we show that traveling wave solutions exist provided that the delay is sufficiently small with the strong generic delay kernel.
Energy Technology Data Exchange (ETDEWEB)
Krisman, Alexander; Hawkes, Evatt Robert.; Talei, Mohsen; Bhagatwala, Ankit; Chen, Jacqueline H.
2016-11-11
In diesel engines, combustion is initiated by a two-staged autoignition that includes both low- and high-temperature chemistry. The location and timing of both stages of autoignition are important parameters that influence the development and stabilisation of the flame. In this study, a two-dimensional direct numerical simulation (DNS) is conducted to provide a fully resolved description of ignition at diesel engine-relevant conditions. The DNS is performed at a pressure of 40 atmospheres and at an ambient temperature of 900 K using dimethyl ether (DME) as the fuel, with a 30 species reduced chemical mechanism. At these conditions, similar to diesel fuel, DME exhibits two-stage ignition. The focus of this study is on the behaviour of the low-temperature chemistry (LTC) and the way in which it influences the high-temperature ignition. The results show that the LTC develops as a “spotty” first-stage autoignition in lean regions which transitions to a diffusively supported cool-flame and then propagates up the local mixture fraction gradient towards richer regions. The cool-flame speed is much faster than can be attributed to spatial gradients in first-stage ignition delay time in homogeneous reactors. The cool-flame causes a shortening of the second-stage ignition delay times compared to a homogeneous reactor and the shortening becomes more pronounced at richer mixtures. Multiple high-temperature ignition kernels are observed over a range of rich mixtures that are much richer than the homogeneous most reactive mixture and most kernels form much earlier than suggested by the homogeneous ignition delay time of the corresponding local mixture. Altogether, the results suggest that LTC can strongly influence both the timing and location in composition space of the high-temperature ignition.
Single pass kernel -means clustering method
Indian Academy of Sciences (India)
T Hitendra Sarma; P Viswanath; B Eswara Reddy
2013-06-01
In unsupervised classiﬁcation, kernel -means clustering method has been shown to perform better than conventional -means clustering method in identifying non-isotropic clusters in a data set. The space and time requirements of this method are $O(n^2)$, where is the data set size. Because of this quadratic time complexity, the kernel -means method is not applicable to work with large data sets. The paper proposes a simple and faster version of the kernel -means clustering method, called single pass kernel k-means clustering method. The proposed method works as follows. First, a random sample $\\mathcal{S}$ is selected from the data set $\\mathcal{D}$. A partition $\\Pi_{\\mathcal{S}}$ is obtained by applying the conventional kernel -means method on the random sample $\\mathcal{S}$. The novelty of the paper is, for each cluster in $\\Pi_{\\mathcal{S}}$, the exact cluster center in the input space is obtained using the gradient descent approach. Finally, each unsampled pattern is assigned to its closest exact cluster center to get a partition of the entire data set. The proposed method needs to scan the data set only once and it is much faster than the conventional kernel -means method. The time complexity of this method is $O(s^2+t+nk)$ where is the size of the random sample $\\mathcal{S}$, is the number of clusters required, and is the time taken by the gradient descent method (to ﬁnd exact cluster centers). The space complexity of the method is $O(s^2)$. The proposed method can be easily implemented and is suitable for large data sets, like those in data mining applications. Experimental results show that, with a small loss of quality, the proposed method can signiﬁcantly reduce the time taken than the conventional kernel -means clustering method. The proposed method is also compared with other recent similar methods.
Kernel-Based Reconstruction of Graph Signals
Romero, Daniel; Ma, Meng; Giannakis, Georgios B.
2017-02-01
A number of applications in engineering, social sciences, physics, and biology involve inference over networks. In this context, graph signals are widely encountered as descriptors of vertex attributes or features in graph-structured data. Estimating such signals in all vertices given noisy observations of their values on a subset of vertices has been extensively analyzed in the literature of signal processing on graphs (SPoG). This paper advocates kernel regression as a framework generalizing popular SPoG modeling and reconstruction and expanding their capabilities. Formulating signal reconstruction as a regression task on reproducing kernel Hilbert spaces of graph signals permeates benefits from statistical learning, offers fresh insights, and allows for estimators to leverage richer forms of prior information than existing alternatives. A number of SPoG notions such as bandlimitedness, graph filters, and the graph Fourier transform are naturally accommodated in the kernel framework. Additionally, this paper capitalizes on the so-called representer theorem to devise simpler versions of existing Thikhonov regularized estimators, and offers a novel probabilistic interpretation of kernel methods on graphs based on graphical models. Motivated by the challenges of selecting the bandwidth parameter in SPoG estimators or the kernel map in kernel-based methods, the present paper further proposes two multi-kernel approaches with complementary strengths. Whereas the first enables estimation of the unknown bandwidth of bandlimited signals, the second allows for efficient graph filter selection. Numerical tests with synthetic as well as real data demonstrate the merits of the proposed methods relative to state-of-the-art alternatives.
Thermal and chemical influences on the soot mass growth
Energy Technology Data Exchange (ETDEWEB)
Bachmann, M.; Wiese, W.; Homann, K.H. [Technische Hochschule Darmstadt (Germany). Inst. fuer Physikalische Chemie
1994-12-31
Charged soot particles in the mass range between 2 {center_dot} 10{sup 3} and 3 {center_dot} 10{sup 4} u were analyzed by a Wien filter mass spectrometer. Several gases were injected into sooting premixed low-pressure flames. The results show that molecular oxygen does not oxidize young soot particles of the mass range studied. High intensities of the injection gas flow cause a high amount of PAH-ions. Under these conditions, more PAHs are formed than in undisturbed flames. Two flames could be stabilized simultaneously on a burner consisting of two sintered plates. The particle, mass growth in these flames is due to surface growth. From the mass distributions at different distances from the burner, the mass growth rate constants could be estimated. These constants are proportional to the particles surface area. Lean flames next to a sooting flame cause a lower amount of soot in the sooting flame. Flames with low temperatures decrease the mass growth rate. The changes in the growth rate constants can be explained by the different temperatures in the flames. Hydrogen/oxygen flames beside sooting flames cause a slower mass growth. The results show that high concentrations of H atoms do not increase the surface growth rate.
Direct numerical simulations of type Ia supernovae flames I: The landau-darrieus instability
Energy Technology Data Exchange (ETDEWEB)
Bell, J.B.; Day, M.S.; Rendleman, C.A.; Woosley, S.E.; Zingale, M.
2003-11-24
Planar flames are intrinsically unstable in open domains due to the thermal expansion across the burning front--the Landau-Darrieus instability. This instability leads to wrinkling and growth of the flame surface, and corresponding acceleration of the flame, until it is stabilized by cusp formation. We look at the Landau-Darrieus in stability for C/O thermonuclear flames at conditions relevant to the late stages of a Type Ia supernova explosion. Two-dimensional direct numerical simulations of both single-mode and multi-mode perturbations using a low Mach number hydrodynamics code are presented. We show the effect of the instability on the flame speed as a function of both the density and domain size, demonstrate the existence of the small scale cutoff to the growth of the instability, and look for the proposed breakdown of the non-linear stabilization at low densities. The effects of curvature on the flame as quantified through measurements of the growth rate and computation of the corresponding Markstein number. While accelerations of a few percent are observed, they are too small to have any direct outcome on the supernova explosion.
Direct Numerical Simulations of Type Ia Supernovae Flames I: The Landau-Darrieus Instability
Bell, J B; Rendleman, C A; Woosley, S E; Zingale, M A
2004-01-01
Planar flames are intrinsically unstable in open domains due to the thermal expansion across the burning front--the Landau-Darrieus instability. This instability leads to wrinkling and growth of the flame surface, and corresponding acceleration of the flame, until it is stabilized by cusp formation. We look at the Landau-Darrieus instability for C/O thermonuclear flames at conditions relevant to the late stages of a Type Ia supernova explosion. Two-dimensional direct numerical simulations of both single-mode and multi-mode perturbations using a low Mach number hydrodynamics code are presented. We show the effect of the instability on the flame speed as a function of both the density and domain size, demonstrate the existence of the small scale cutoff to the growth of the instability, and look for the proposed breakdown of the non-linear stabilization at low densities. The effects of curvature on the flame as quantified through measurements of the growth rate and computation of the corresponding Markstein numb...
A new Mercer sigmoid kernel for clinical data classification.
Carrington, André M; Fieguth, Paul W; Chen, Helen H
2014-01-01
In classification with Support Vector Machines, only Mercer kernels, i.e. valid kernels, such as the Gaussian RBF kernel, are widely accepted and thus suitable for clinical data. Practitioners would also like to use the sigmoid kernel, a non-Mercer kernel, but its range of validity is difficult to determine, and even within range its validity is in dispute. Despite these shortcomings the sigmoid kernel is used by some, and two kernels in the literature attempt to emulate and improve upon it. We propose the first Mercer sigmoid kernel, that is therefore trustworthy for the classification of clinical data. We show the similarity between the Mercer sigmoid kernel and the sigmoid kernel and, in the process, identify a normalization technique that improves the classification accuracy of the latter. The Mercer sigmoid kernel achieves the best mean accuracy on three clinical data sets, detecting melanoma in skin lesions better than the most popular kernels; while with non-clinical data sets it has no significant difference in median accuracy as compared with the Gaussian RBF kernel. It consistently classifies some points correctly that the Gaussian RBF kernel does not and vice versa.
Imaging Invisible Flames Without Additives
Weiland, Karen J.
1996-01-01
Image intensifiers, video cameras, and image-data-processing computers used to study combustion. Possible to view and analyze methane, hydrogen, and other flames dim or invisible to human eye and difficult to image by use of conventional photographic and video cameras.
Olympic Flame Burning In Athens
Institute of Scientific and Technical Information of China (English)
2004-01-01
<正>At 6:00pm March 25 (Beijing time), 2004 Athens Olympic flame was lit in Greece’s ancient sanctuary, indicating that the torch relay started.The torch relay, established at the Berlin Games in 1936, will for the first time visit all five continents
The VLT FLAMES Tarantula Survey
Evans, C.; Taylor, W.; Sana, H.; Hénault-Brunet, V.; Bagnoli, T.; Bastian, N.; Bestenlehner, J.; Bonanos, A.; Bressert, E.; Brott, I.; Campbell, M.; Cantiello, M.; Carraro, G.; Clark, S.; Costa, E.; Crowther, P.; de Koter, A.; de Mink, S.; Doran, E.; Dufton, P.; Dunstall, P.; Garcia, M.; Gieles, M.; Gräfener, G.; Herrero, A.; Howarth, I.; Izzard, R.; Köhler, K.; Langer, N.; Lennon, D.; Maíz Apellániz, J.; Markova, N.; Najarro, P.; Puls, J.; Ramirez, O.; Sabín-Sanjulián, C.; Simón-Díaz, S.; Smartt, S.; Stroud, V.; van Loon, J.; Vink, J.S.; Walborn, N.
2011-01-01
We introduce the VLT FLAMES Tarantula Survey, an ESO Large Programme from which we have obtained optical spectroscopy of over 800 massive stars in the spectacular 30 Doradus region of the Large Magellanic Cloud. A key feature is the use of multi-epoch observations to provide strong constraints on
Flame monitoring enhances burner management
Energy Technology Data Exchange (ETDEWEB)
Flynn, T.; Bailey, R.; Fuller, T.; Daw, S.; Finney, C.; Stallings, J. [Babcock & Wilcox Research Center (USA)
2003-02-01
A new burner monitoring and diagnostic system called Flame Doctor offers users a more precise and discriminating understanding of burner conditions. Alpha testing on Unit 4 at AmerenUE's Meramec power plant in St. Louis, MO, USA and Beta testing is underway at plants owned by Dynegy and Allegheny Energy. 6 refs., 3 figs.
Enhancements of Impinging Flame by Pulsation
Institute of Scientific and Technical Information of China (English)
AySu; Ying－ChiehLiu
2000-01-01
Experimental investigations on the pulsating jet-impinging diffusion flame were executed.A soleoid valve was aligned upstream of the jet orifice and the methane fuel was controlled in open-closed cycles from 0 Hz to 20Hz.Results show that the open-closed cycles,indeed increase the fluctuations of the methane fuel obviously.The evolutions of pulsating flame therefore develop faster than the continuous impinging flame.The optimized pulating frequencies are near 9 to 11 hz from the Re=170 to 283.The temperature differences between that under optimized pulsating rate and full open condition(no pulsation)are ranging from 100 to 150 degree.The pulsating effect is more singnificant at low Reynolds number.The cross section of continuous impinging flame behaves as elliptic shape with axial ratio equals to 2/3.The tip of the impinging flame obviously crosses at 42mm above the impinging point.ecause of the phenomenon of pulsation flame,the flame sheet or flame front may not be identified clearly in the averaged temperature contours.Results shows that the averaged end-contour of pulsation flame rears at 38mm above the impinging point.By observation and experiment,the pulsating flame behaves more stable and efficient than the continuous impinging flame.
Turbulent Oxygen Flames in Type Ia Supernovae
Aspden, A J; Woosley, S E; 10.1088/0004-637X/730/2/144
2011-01-01
In previous studies, we examined turbulence-flame interactions in carbon-burning thermonuclear flames in Type Ia supernovae. In this study, we consider turbulence-flame interactions in the trailing oxygen flames. The two aims of the paper are to examine the response of the inductive oxygen flame to intense levels of turbulence, and to explore the possibility of transition to detonation in the oxygen flame. Scaling arguments analogous to the carbon flames are presented and then compared against three-dimensional simulations for a range of Damk\\"ohler numbers ($\\Da_{16}$) at a fixed Karlovitz number. The simulations suggest that turbulence does not significantly affect the oxygen flame when $\\Da_{16}1$, turbulence enhances heat transfer and drives the propagation of a flame that is {\\em narrower} than the corresponding inductive flame would be. Furthermore, burning under these conditions appears to occur as part of a combined carbon-oxygen turbulent flame with complex compound structure. The simulations do not ...
Sooting limit of a double diffusion flame
Energy Technology Data Exchange (ETDEWEB)
Kitano, Michio; Kobayashi, Hideaki; Nishiki, Nobuhiko (Tohoku Univ., Faculty of Engineering, Sendai, Japan Sony Corp., Tokyo (Japan))
1989-07-25
The soot exhaust from the flame of pot type burner for the domestic heating use was basically studied. Inside a fuel (secondary) diffusion flame in air atmosphere, which was an ordinary diffusion flame, an air (primary) diffusion flame in fuel atmosphere, which was reverse in relation between them, was formed by using propane fuel. For the sooting limit of that double diffusion flame, the effect of primary air ratio, distance between primary and secondary flames, thermal condition on wall surface and flow stretch being investigated by use of three different types of burner, the double diffusion flame method was studied in effectiveness on the soot exhaust and known to heighten the control against it, which heightening however depended in degree upon the locative relation between both the flames. The control was more heightened with a more lengthening in the secondary flame. Because the sooting limit is governed by the secondary flame temperature, the establishment of condition so as to heighten the flame temperature is necessary for the effective control against the soot exhaust. 11 refs., 11 figs.
Flame Reconstruction Using Synthetic Aperture Imaging
Murray, Preston; Tree, Dale; Truscott, Tadd
2011-01-01
Flames can be formed by burning methane (CH4). When oxygen is scarce, carbon particles nucleate into solid particles called soot. These particles emit photons, making the flame yellow. Later, methane is pre-mixed with air forming a blue flame; burning more efficiently, providing less soot and light. Imaging flames and knowing their temperature are vital to maximizing efficiency and validating numerical models. Most temperature probes disrupt the flame and create differences leading to an inaccurate measurement of the flame temperature. We seek to image the flame in three dimensions using synthetic aperture imaging. This technique has already successfully measured velocity fields of a vortex ring [1]. Synthetic aperture imaging is a technique that views one scene from multiple cameras set at different angles, allowing some cameras to view objects that are obscured by others. As the resulting images are overlapped different depths of the scene come into and out of focus, known as focal planes, similar to tomogr...
Flex-flame burner and combustion method
Soupos, Vasilios; Zelepouga, Serguei; Rue, David M.; Abbasi, Hamid A.
2010-08-24
A combustion method and apparatus which produce a hybrid flame for heating metals and metal alloys, which hybrid flame has the characteristic of having an oxidant-lean portion proximate the metal or metal alloy and having an oxidant-rich portion disposed above the oxidant lean portion. This hybrid flame is produced by introducing fuel and primary combustion oxidant into the furnace chamber containing the metal or metal alloy in a substoichiometric ratio to produce a fuel-rich flame and by introducing a secondary combustion oxidant into the furnace chamber above the fuel-rich flame in a manner whereby mixing of the secondary combustion oxidant with the fuel-rich flame is delayed for a portion of the length of the flame.
Starch Accumulation and Enzyme Activities Associated with Starch Synthesis in Maize Kernels
Institute of Scientific and Technical Information of China (English)
ZHANG Hai-yan; DONG Shu-ting; GAO Rong-qi; SUN Qing-quan
2007-01-01
The filling rate and the starch accumulation in developing maize kernel were analyzed. The changes of enzyme activities associated with sucrose metabolism and starch biosynthesis were investigated. The purpose is to discuss the enzymatic mechanisms responsible for starch synthesis. Two types of maize cultivars (Zea mays), high starch maize (Feiyu 3) and normal maize (Yuyu 22), were grown in a corn field. The factors involved in starch synthesis were performed during the growth period. The kernel filling rate, the sucrose content, the starch accumulating rates and the activities of SS (sucrose synthase), GBSS (granule-bound starch synthase), SBE (starch branching enzyme) of Feiyu 3, which has high starch content, were significantly higher than those of Yuyu 22, which has low starch content, after 10 DAP (days after pollination).Correlation analysis indicated that ADPGPPase (ADP-glucose pyrophosphorylase) and DBE (starch debranching enzyme)were not correlated with the starch accumulating rates and the kernel filling rate, but the SS activity at the middle and late period were highly significantly correlated with the starch accumulating rates and the kernel filling rate. The GBSS activity was highly significantly correlated with the amylose accumulating rate, but not correlated with the kernel filling rate. The SBE activity was highly significantly correlated with the amylopectin accumulating rate and the kernel filling rate. It was not ADPGPPase and DBE, but SS was the rate-limiting factor of starch biosynthesis in developing maize kernels. GBSS had an important effect on amylose accumulation, and SBE had a significant effect on amylopectin accumulation.
Pattern Classification of Signals Using Fisher Kernels
Directory of Open Access Journals (Sweden)
Yashodhan Athavale
2012-01-01
Full Text Available The intention of this study is to gauge the performance of Fisher kernels for dimension simplification and classification of time-series signals. Our research work has indicated that Fisher kernels have shown substantial improvement in signal classification by enabling clearer pattern visualization in three-dimensional space. In this paper, we will exhibit the performance of Fisher kernels for two domains: financial and biomedical. The financial domain study involves identifying the possibility of collapse or survival of a company trading in the stock market. For assessing the fate of each company, we have collected financial time-series composed of weekly closing stock prices in a common time frame, using Thomson Datastream software. The biomedical domain study involves knee signals collected using the vibration arthrometry technique. This study uses the severity of cartilage degeneration for classifying normal and abnormal knee joints. In both studies, we apply Fisher Kernels incorporated with a Gaussian mixture model (GMM for dimension transformation into feature space, which is created as a three-dimensional plot for visualization and for further classification using support vector machines. From our experiments we observe that Fisher Kernel usage fits really well for both kinds of signals, with low classification error rates.
Analog forecasting with dynamics-adapted kernels
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.
The discrete regime of flame propagation
Tang, Francois-David; Goroshin, Samuel; Higgins, Andrew
The propagation of laminar dust flames in iron dust clouds was studied in a low-gravity envi-ronment on-board a parabolic flight aircraft. The elimination of buoyancy-induced convection and particle settling permitted measurements of fundamental combustion parameters such as the burning velocity and the flame quenching distance over a wide range of particle sizes and in different gaseous mixtures. The discrete regime of flame propagation was observed by substitut-ing nitrogen present in air with xenon, an inert gas with a significantly lower heat conductivity. Flame propagation in the discrete regime is controlled by the heat transfer between neighbor-ing particles, rather than by the particle burning rate used by traditional continuum models of heterogeneous flames. The propagation mechanism of discrete flames depends on the spa-tial distribution of particles, and thus such flames are strongly influenced by local fluctuations in the fuel concentration. Constant pressure laminar dust flames were observed inside 70 cm long, 5 cm diameter Pyrex tubes. Equally-spaced plate assemblies forming rectangular chan-nels were placed inside each tube to determine the quenching distance defined as the minimum channel width through which a flame can successfully propagate. High-speed video cameras were used to measure the flame speed and a fiber optic spectrometer was used to measure the flame temperature. Experimental results were compared with predictions obtained from a numerical model of a three-dimensional flame developed to capture both the discrete nature and the random distribution of particles in the flame. Though good qualitative agreement was obtained between model predictions and experimental observations, residual g-jitters and the short reduced-gravity periods prevented further investigations of propagation limits in the dis-crete regime. The full exploration of the discrete flame phenomenon would require high-quality, long duration reduced gravity environment
Uranakara, Harshavardhana A.
2015-11-21
Interactions of turbulence, molecular transport, and energy transport, coupled with chemistry play a crucial role in the evolution of flame surface geometry, propagation, annihilation, and local extinction/re-ignition characteristics of intensely turbulent premixed flames. This study seeks to understand how these interactions affect flame surface annihilation of lean hydrogen–air premixed turbulent flames. Direct numerical simulations (DNSs) are conducted at different parametric conditions with a detailed reaction mechanism and transport properties for hydrogen–air flames. Flame particle tracking (FPT) technique is used to follow specific flame surface segments. An analytical expression for the local displacement flame speed (Sd) of a temperature isosurface is considered, and the contributions of transport, chemistry, and kinematics on the displacement flame speed at different turbulence-flame interaction conditions are identified. In general, the displacement flame speed for the flame particles is found to increase with time for all conditions considered. This is because, eventually all flame surfaces and their resident flame particles approach annihilation by reactant island formation at the end of stretching and folding processes induced by turbulence. Statistics of principal curvature evolving in time, obtained using FPT, suggest that these islands are ellipsoidal on average enclosing fresh reactants. Further examinations show that the increase in Sd is caused by the increased negative curvature of the flame surface and eventual homogenization of temperature gradients as these reactant islands shrink due to flame propagation and turbulent mixing. Finally, the evolution of the normalized, averaged, displacement flame speed vs. stretch Karlovitz number are found to collapse on a narrow band, suggesting that a unified description of flame speed dependence on stretch rate may be possible in the Lagrangian description.
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...
OS X and iOS Kernel Programming
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
Soot Formation in Laminar Premixed Ethylene/Air Flames at Atmospheric Pressure. Appendix G
Xu, F.; Sunderland, P. B.; Faeth, G. M.; Urban, D. L. (Technical Monitor)
2001-01-01
Soot formation was studied within laminar premixed ethylene/air flames (C/O ratios of 0.78-0.98) stabilized on a flat-flame burner operating at atmospheric pressure. Measurements included soot volume fractions by both laser extinction and gravimetric methods, temperatures by multiline emission, soot structure by thermophoretic sampling and transmission electron microscopy, major gas species concentrations by sampling and gas chromatography, concentrations of condensable hydrocarbons by gravimetric sampling. and velocities by laser velocimetry. These data were used to find soot surface growth rates and primary soot particle nucleation rates along the axes of the flames. Present measurements of soot surface growth rates were correlated successfully by predictions based on typical hydrogen-abstraction/carbon-addition (HACA) mechanisms of Frenklach and co-workers and Colket and Hall. These results suavest that reduced soot surface growth rates with increasing residence time seen in the present and other similar flames were mainly caused by reduced rates of surface activation due to reduced H atom concentrations as temperatures decrease as a result of radiative heat losses. Primary soot particle nucleation rates exhibited variations with temperature and acetylene concentrations that were similar to recent observations for diffusion flames; however, nucleation rates in the premixed flames were significantly lower than in, the diffusion flames for reasons that still must be explained. Finally, predictions of yields of major gas species based on mechanisms from both Frenklach and co-workers and Leung and Lindstedt were in good agreement with present measurements and suggest that H atom concentrations (relevant to HACA mechanisms) approximate estimates based on local thermodynamic equilibrium in the present flames.
Using the Meeting Graph Framework to Minimise Kernel Loop Unrolling for Scheduled Loops
Bachir, Mounira; Gregg, David; Touati, Sid-Ahmed-Ali
This paper improves our previous research effort [1] by providing an efficient method for kernel loop unrolling minimisation in the case of already scheduled loops, where circular lifetime intervals are known. When loops are software pipelined, the number of values simultaneously alive becomes exactly known giving better opportunities for kernel loop unrolling. Furthermore, fixing circular lifetime intervals allows us to reduce the algorithmic complexity of our method compared to [1] by computing a new research space for minimal kernel loop unrolling. The meeting graph (MG) is one of the [3] frameworks proposed in the literature which models loop unrolling and register allocation together in a common formal framework for software pipelined loops. Although MG significantly improves loop register allocation, the computed loop unrolling may lead to unpractical code growth.
The scalar field kernel in cosmological spaces
Energy Technology Data Exchange (ETDEWEB)
Koksma, Jurjen F; Prokopec, Tomislav [Institute for Theoretical Physics (ITP) and Spinoza Institute, Utrecht University, Postbus 80195, 3508 TD Utrecht (Netherlands); Rigopoulos, Gerasimos I [Helsinki Institute of Physics, University of Helsinki, PO Box 64, FIN-00014 (Finland)], E-mail: J.F.Koksma@phys.uu.nl, E-mail: T.Prokopec@phys.uu.nl, E-mail: gerasimos.rigopoulos@helsinki.fi
2008-06-21
We construct the quantum-mechanical evolution operator in the functional Schroedinger picture-the kernel-for a scalar field in spatially homogeneous FLRW spacetimes when the field is (a) free and (b) coupled to a spacetime-dependent source term. The essential element in the construction is the causal propagator, linked to the commutator of two Heisenberg picture scalar fields. We show that the kernels can be expressed solely in terms of the causal propagator and derivatives of the causal propagator. Furthermore, we show that our kernel reveals the standard light cone structure in FLRW spacetimes. We finally apply the result to Minkowski spacetime, to de Sitter spacetime and calculate the forward time evolution of the vacuum in a general FLRW spacetime.
Robust Visual Tracking via Fuzzy Kernel Representation
Directory of Open Access Journals (Sweden)
Zhiqiang Wen
2013-05-01
Full Text Available A robust visual kernel tracking approach is presented for solving the problem of existing background pixels in object model. At first, after definition of fuzzy set on image is given, a fuzzy factor is embedded into object model to form the fuzzy kernel representation. Secondly, a fuzzy membership functions are generated by center-surround approach and log likelihood ratio of feature distributions. Thirdly, details about fuzzy kernel tracking algorithm is provided. After that, methods of parameter selection and performance evaluation for tracking algorithm are proposed. At last, a mass of experimental results are done to show our method can reduce the influence of the incomplete representation of object model via integrating both color features and background features.
Fractal Weyl law for Linux Kernel architecture
Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.
2011-01-01
We study the properties of spectrum and eigenstates of the Google matrix of a directed network formed by the procedure calls in the Linux Kernel. Our results obtained for various versions of the Linux Kernel show that the spectrum is characterized by the fractal Weyl law established recently for systems of quantum chaotic scattering and the Perron-Frobenius operators of dynamical maps. The fractal Weyl exponent is found to be ν ≈ 0.65 that corresponds to the fractal dimension of the network d ≈ 1.3. An independent computation of the fractal dimension by the cluster growing method, generalized for directed networks, gives a close value d ≈ 1.4. The eigenmodes of the Google matrix of Linux Kernel are localized on certain principal nodes. We argue that the fractal Weyl law should be generic for directed networks with the fractal dimension d < 2.
Optoacoustic inversion via Volterra kernel reconstruction
Melchert, O; Roth, B
2016-01-01
In this letter we address the numeric inversion of optoacoustic signals to initial stress profiles. Therefore we put under scrutiny the optoacoustic kernel reconstruction problem in the paraxial approximation of the underlying wave-equation. We apply a Fourier-series expansion of the optoacoustic Volterra kernel and obtain the respective expansion coefficients for a given "apparative" setup by performing a gauge procedure using synthetic input data. The resulting effective kernel is subsequently used to solve the optoacoustic source reconstruction problem for general signals. We verify the validity of the proposed inversion protocol for synthetic signals and explore the feasibility of our approach to also account for the diffraction transformation of signals beyond the paraxial approximation.
Tile-Compressed FITS Kernel for IRAF
Seaman, R.
2011-07-01
The Flexible Image Transport System (FITS) is a ubiquitously supported standard of the astronomical community. Similarly, the Image Reduction and Analysis Facility (IRAF), developed by the National Optical Astronomy Observatory, is a widely used astronomical data reduction package. IRAF supplies compatibility with FITS format data through numerous tools and interfaces. The most integrated of these is IRAF's FITS image kernel that provides access to FITS from any IRAF task that uses the basic IMIO interface. The original FITS kernel is a complex interface of purpose-built procedures that presents growing maintenance issues and lacks recent FITS innovations. A new FITS kernel is being developed at NOAO that is layered on the CFITSIO library from the NASA Goddard Space Flight Center. The simplified interface will minimize maintenance headaches as well as add important new features such as support for the FITS tile-compressed (fpack) format.
Institute of Scientific and Technical Information of China (English)
GUO; Zhe; LOU; Chun; LIU; ZhengDong; ZHOU; HuaiChun
2013-01-01
Based on a detailed chemical mechanism, impacts of combustion characteristics and flame structure on soot formation in opposed-flow diffusion ethylene flames was studied with different stoichiometric mixture fractions in O2/N2and O2/CO2atmospheres. The results showed the followings. 1) In both atmospheres, with the increase of stoichiometric mixture fraction, the flame structure changed significantly. The stagnation plane shifted toward the oxidizer side. Furthermore, there were less C2H2 but more O and OH to occur in the soot inception zone, therefore the amount of soot in the flame decreased. 2) Compared withN2, CO2had a suppression effect on soot formation, which was mainly due to thermal and direct chemical interaction effects of CO2. This is because the specific heat capacity of CO2is higher than that of N2, which will cause the flame temperature to drop,and mole fractions of C2H2, H, O, OH and main PAHs to decrease. Soot oxidation played a dominant role, while soot surface growth was attributed to the secondary position. Meanwhile, when CO2 abounded in the flame, OH concentration was increased through the backward reaction of CO+OH=CO2+H, and this would be conducive to the oxidation of soot precursor and incipient soot particles. In addition, the results of maximum particle density indicated the thermal effect of CO2on soot for-mation is more important than the direct chemical interaction effect.
A kernel-based approach for biomedical named entity recognition.
Patra, Rakesh; Saha, Sujan Kumar
2013-01-01
Support vector machine (SVM) is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER). The performance of the SVM classifier largely depends on the appropriateness of the kernel function. In the last few years a number of task-specific kernel functions have been proposed and used in various text processing tasks, for example, string kernel, graph kernel, tree kernel and so on. So far very few efforts have been devoted to the development of NER task specific kernel. In the literature we found that the tree kernel has been used in NER task only for entity boundary detection or reannotation. The conventional tree kernel is unable to execute the complete NER task on its own. In this paper we have proposed a kernel function, motivated by the tree kernel, which is able to perform the complete NER task. To examine the effectiveness of the proposed kernel, we have applied the kernel function on the openly available JNLPBA 2004 data. Our kernel executes the complete NER task and achieves reasonable accuracy.
Numerical simulation of tulip flame dynamics
Energy Technology Data Exchange (ETDEWEB)
Cloutman, L.D.
1991-11-30
A finite difference reactive flow hydrodynamics program based on the full Navier-Stokes equations was used to simulate the combustion process in a homogeneous-charge, constant-volume combustion bomb in which an oddly shaped flame, known as a ``tulip flame`` in the literature, occurred. The ``tulip flame`` was readily reproduced in the numerical simulations, producing good agreement with the experimental flame shapes and positions at various times. The calculations provide sufficient detail about the dynamics of the experiment to provide some insight into the physical mechanisms responsible for the peculiar flame shape. Several factors seem to contribute to the tulip formation. The most important process is the baroclinic production of vorticity by the flame front, and this rate of production appears to be dramatically increased by the nonaxial flow generated when the initial semicircular flame front burns out along the sides of the chamber. The vorticity produces a pair of vortices behind the flame that advects the flame into the tulip shape. Boundary layer effects contribute to the details of the flame shape next to the walls of the chamber, but are otherwise not important. 24 refs.
Numerical simulation of tulip flame dynamics
Energy Technology Data Exchange (ETDEWEB)
Cloutman, L.D.
1991-11-30
A finite difference reactive flow hydrodynamics program based on the full Navier-Stokes equations was used to simulate the combustion process in a homogeneous-charge, constant-volume combustion bomb in which an oddly shaped flame, known as a tulip flame'' in the literature, occurred. The tulip flame'' was readily reproduced in the numerical simulations, producing good agreement with the experimental flame shapes and positions at various times. The calculations provide sufficient detail about the dynamics of the experiment to provide some insight into the physical mechanisms responsible for the peculiar flame shape. Several factors seem to contribute to the tulip formation. The most important process is the baroclinic production of vorticity by the flame front, and this rate of production appears to be dramatically increased by the nonaxial flow generated when the initial semicircular flame front burns out along the sides of the chamber. The vorticity produces a pair of vortices behind the flame that advects the flame into the tulip shape. Boundary layer effects contribute to the details of the flame shape next to the walls of the chamber, but are otherwise not important. 24 refs.
Full Waveform Inversion Using Waveform Sensitivity Kernels
Schumacher, Florian; Friederich, Wolfgang
2013-04-01
We present a full waveform inversion concept for applications ranging from seismological to enineering contexts, in which the steps of forward simulation, computation of sensitivity kernels, and the actual inversion are kept separate of each other. We derive waveform sensitivity kernels from Born scattering theory, which for unit material perturbations are identical to the Born integrand for the considered path between source and receiver. The evaluation of such a kernel requires the calculation of Green functions and their strains for single forces at the receiver position, as well as displacement fields and strains originating at the seismic source. We compute these quantities in the frequency domain using the 3D spectral element code SPECFEM3D (Tromp, Komatitsch and Liu, 2008) and the 1D semi-analytical code GEMINI (Friederich and Dalkolmo, 1995) in both, Cartesian and spherical framework. We developed and implemented the modularized software package ASKI (Analysis of Sensitivity and Kernel Inversion) to compute waveform sensitivity kernels from wavefields generated by any of the above methods (support for more methods is planned), where some examples will be shown. As the kernels can be computed independently from any data values, this approach allows to do a sensitivity and resolution analysis first without inverting any data. In the context of active seismic experiments, this property may be used to investigate optimal acquisition geometry and expectable resolution before actually collecting any data, assuming the background model is known sufficiently well. The actual inversion step then, can be repeated at relatively low costs with different (sub)sets of data, adding different smoothing conditions. Using the sensitivity kernels, we expect the waveform inversion to have better convergence properties compared with strategies that use gradients of a misfit function. Also the propagation of the forward wavefield and the backward propagation from the receiver
Inverse of the String Theory KLT Kernel
Mizera, Sebastian
2016-01-01
The field theory Kawai-Lewellen-Tye (KLT) kernel, which relates scattering amplitudes of gravitons and gluons, turns out to be the inverse of a matrix whose components are bi-adjoint scalar partial amplitudes. In this note we propose an analogous construction for the string theory KLT kernel. We present simple diagrammatic rules for the computation of the $\\alpha'$-corrected bi-adjoint scalar amplitudes that are exact in $\\alpha'$. We find compact expressions in terms of graphs, where the standard Feynman propagators $1/p^2$ are replaced by either $1/\\sin (\\pi \\alpha' p^2)$ or $1/\\tan (\\pi \\alpha' p^2)$, which is determined by a recursive procedure.
Reduced multiple empirical kernel learning machine.
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
Volatile compound formation during argan kernel roasting.
El Monfalouti, Hanae; Charrouf, Zoubida; Giordano, Manuela; Guillaume, Dominique; Kartah, Badreddine; Harhar, Hicham; Gharby, Saïd; Denhez, Clément; Zeppa, Giuseppe
2013-01-01
Virgin edible argan oil is prepared by cold-pressing argan kernels previously roasted at 110 degrees C for up to 25 minutes. The concentration of 40 volatile compounds in virgin edible argan oil was determined as a function of argan kernel roasting time. Most of the volatile compounds begin to be formed after 15 to 25 minutes of roasting. This suggests that a strictly controlled roasting time should allow the modulation of argan oil taste and thus satisfy different types of consumers. This could be of major importance considering the present booming use of edible argan oil.
Learning Rates for -Regularized Kernel Classifiers
Directory of Open Access Journals (Sweden)
Hongzhi Tong
2013-01-01
Full Text Available We consider a family of classification algorithms generated from a regularization kernel scheme associated with -regularizer and convex loss function. Our main purpose is to provide an explicit convergence rate for the excess misclassification error of the produced classifiers. The error decomposition includes approximation error, hypothesis error, and sample error. We apply some novel techniques to estimate the hypothesis error and sample error. Learning rates are eventually derived under some assumptions on the kernel, the input space, the marginal distribution, and the approximation error.
Face Recognition Using Kernel Discriminant Analysis
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Linear Discrimiant Analysis (LDA) has demonstrated their success in face recognition. But LDA is difficult to handle the high nonlinear problems, such as changes of large viewpoint and illumination in face recognition. In order to overcome these problems, we investigate Kernel Discriminant Analysis (KDA) for face recognition. This approach adopts the kernel functions to replace the dot products of nonlinear mapping in the high dimensional feature space, and then the nonlinear problem can be solved in the input space conveniently without explicit mapping. Two face databases are used to test KDA approach. The results show that our approach outperforms the conventional PCA(Eigenface) and LDA(Fisherface) approaches.
Directory of Open Access Journals (Sweden)
Chao Huang
2014-01-01
Full Text Available Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA and grey relational analysis (GRA. Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM in China shows that the proposed approach has good performance.
Mechanical weed control on small-size dry bean and its response to cross-flaming
Energy Technology Data Exchange (ETDEWEB)
Martelloni, L.; Frasconi, C.; Fontanelli, M.; Raffaelli, M.; Peruzzi, A.
2016-11-01
Dry bean (Phaseolus vulgaris L.) can be a profitable crop for farmers; however controlling weeds effectively without a decrease in yield remains a problem. An example where mechanical weed control is difficult to conduct is dry bean ‘Toscanello’, which is a small sized high-income niche product growing low to the ground. Concerning intra-row weed control, also flame weeding could be an opportunity but the dry bean heat tolerance needs to be studied. The aims of this research were to study the weed control efficacy of a spring-tine harrow and an inter-row cultivator in this bean variety, and to test the tolerance of dry bean cultivated under weed-free conditions to cross-flaming applied with different liquefied petroleum gas (LPG) doses. Flame weeding was applied at BBCH 13 and BBCH 14 bean growth stages by pairs of burners producing direct double flame acting into the intra-row space, with bean plants placed in the middle. The results suggest that the spring-tine harrow used two times at BBCH 13 and 14, respectively, lead to a yield similar to that of the weedy control. The inter-row cultivator could be an opportunity for small-sized dry bean crops producers, enabling them to obtain a similar yield compared to the hand-weeded control. Concerning the bean tolerance to cross-flaming the results showed that bean flamed at BBCH 13 stage had little tolerance to cross-flaming. Bean flamed at BBCH 14 stage was tolerant until an LPG dose of 39 kg/ha, giving yield responses similar to those observed in the non-flamed control. (Author)
Regularization techniques for PSF-matching kernels - I. Choice of kernel basis
Becker, A. C.; Homrighausen, D.; Connolly, A. J.; Genovese, C. R.; Owen, R.; Bickerton, S. J.; Lupton, R. H.
2012-09-01
We review current methods for building point spread function (PSF)-matching kernels for the purposes of image subtraction or co-addition. Such methods use a linear decomposition of the kernel on a series of basis functions. The correct choice of these basis functions is fundamental to the efficiency and effectiveness of the matching - the chosen bases should represent the underlying signal using a reasonably small number of shapes, and/or have a minimum number of user-adjustable tuning parameters. We examine methods whose bases comprise multiple Gauss-Hermite polynomials, as well as a form-free basis composed of delta-functions. Kernels derived from delta-functions are unsurprisingly shown to be more expressive; they are able to take more general shapes and perform better in situations where sum-of-Gaussian methods are known to fail. However, due to its many degrees of freedom (the maximum number allowed by the kernel size) this basis tends to overfit the problem and yields noisy kernels having large variance. We introduce a new technique to regularize these delta-function kernel solutions, which bridges the gap between the generality of delta-function kernels and the compactness of sum-of-Gaussian kernels. Through this regularization we are able to create general kernel solutions that represent the intrinsic shape of the PSF-matching kernel with only one degree of freedom, the strength of the regularization λ. The role of λ is effectively to exchange variance in the resulting difference image with variance in the kernel itself. We examine considerations in choosing the value of λ, including statistical risk estimators and the ability of the solution to predict solutions for adjacent areas. Both of these suggest moderate strengths of λ between 0.1 and 1.0, although this optimization is likely data set dependent. This model allows for flexible representations of the convolution kernel that have significant predictive ability and will prove useful in implementing
Kernel methods and minimum contrast estimators for empirical deconvolution
Delaigle, Aurore
2010-01-01
We survey classical kernel methods for providing nonparametric solutions to problems involving measurement error. In particular we outline kernel-based methodology in this setting, and discuss its basic properties. Then we point to close connections that exist between kernel methods and much newer approaches based on minimum contrast techniques. The connections are through use of the sinc kernel for kernel-based inference. This `infinite order' kernel is not often used explicitly for kernel-based deconvolution, although it has received attention in more conventional problems where measurement error is not an issue. We show that in a comparison between kernel methods for density deconvolution, and their counterparts based on minimum contrast, the two approaches give identical results on a grid which becomes increasingly fine as the bandwidth decreases. In consequence, the main numerical differences between these two techniques are arguably the result of different approaches to choosing smoothing parameters.
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...
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...
HEAT KERNEL AND HARDY'S THEOREM FOR JACOBI TRANSFORM
Institute of Scientific and Technical Information of China (English)
T. KAWAZOE; LIU JIANMING(刘建明)
2003-01-01
In this paper, the authors obtain sharp upper and lower bounds for the heat kernel associatedwith Jacobi transform, and get some analogues of Hardy's Theorem for Jacobi transform byusing the sharp estimate of the heat kernel.
Numerical Investigation of Soot Formation in Non-premixed Flames
Abdelgadir, Ahmed Gamaleldin
2017-05-01
Soot is a carbon particulate formed as a result of the combustion of fossil fuels. Due to the health hazard posed by the carbon particulate, government agencies have applied strict regulations to control soot emissions from road vehicles, airplanes, and industrial plants. Thus, understanding soot formation and evolution is critical. Practical combustion devices operate at high pressure and in the turbulent regime. Elevated pressures and turbulence on soot formation significantly and fundamental understanding of these complex interactions is still poor. In this study, the effects of pressure and turbulence on soot formation and growth are investigated numerically. As the first step, the evolution of the particle size distribution function (PSDF) and soot particles morphology are investigated in turbulent non-premixed flames. A Direct Simulation Monte Carlo (DSMC) code is developed and used. The stochastic reactor describes the evolution of soot in fluid parcels following Lagrangian trajectories in a turbulent flow field. The trajectories are sampled from a Direct Numerical Simulation (DNS) of an n-heptane turbulent non-premixed flame. Although individual trajectories display strong bimodality as in laminar flames, the ensemble-average PSDF possesses only one mode and a broad tail, which implies significant polydispersity induced by turbulence. Secondly, the effect of the flow and mixing fields on soot formation at atmospheric and elevated pressures is investigated in coflow laminar diffusion flames. The experimental observation and the numerical prediction of the spatial distribution are in good agreement. Based on the common scaling methodology of the flames (keeping the Reynolds number constant), the scalar dissipation rate decreases as pressure increases, promoting the formation of PAH species and soot. The decrease of the scalar dissipation rate significantly contributes to soot formation occurring closer to the nozzle and outward on the flames wings as pressure
Gustin, Jeffery L; Jackson, Sean; Williams, Chekeria; Patel, Anokhee; Armstrong, Paul; Peter, Gary F; Settles, A Mark
2013-11-20
Maize kernel density affects milling quality of the grain. Kernel density of bulk samples can be predicted by near-infrared reflectance (NIR) spectroscopy, but no accurate method to measure individual kernel density has been reported. This study demonstrates that individual kernel density and volume are accurately measured using X-ray microcomputed tomography (μCT). Kernel density was significantly correlated with kernel volume, air space within the kernel, and protein content. Embryo density and volume did not influence overall kernel density. Partial least-squares (PLS) regression of μCT traits with single-kernel NIR spectra gave stable predictive models for kernel density (R(2) = 0.78, SEP = 0.034 g/cm(3)) and volume (R(2) = 0.86, SEP = 2.88 cm(3)). Density and volume predictions were accurate for data collected over 10 months based on kernel weights calculated from predicted density and volume (R(2) = 0.83, SEP = 24.78 mg). Kernel density was significantly correlated with bulk test weight (r = 0.80), suggesting that selection of dense kernels can translate to improved agronomic performance.
Flame Propagation Through Concentration Gradient
Institute of Scientific and Technical Information of China (English)
JunyaIINO; MitsuakiTANABE; 等
2000-01-01
The experiment was carried out in homogeneous propane-air mixture and in several concentration gradient of mixture.Igniter is put on the upper side of the combustion chamber,In concentration gradient experiment.ixture was ignited from lean side.An experimental study was conducted in a combustion chamber.The combustion chamber has glass windows for optical measurements at any side.For the measurement of distribution of fuel concentration,infraed absorption method using 3.39μm He-Ne laser was used,and for the observation of proagating flams,Schlieren method was employed.As a measurment result of flame propagation velocity and flammable limit,for a mixture of an identical local equivalence ratio.flame propagation velocity in concentration gradient is faster than that in homogeneous mixture,and rich flammable limit in concentration gradient shows a tendency to be higher than that in homogeneous mixture.
The Interaction of High-Speed Turbulence with Flames: Global Properties and Internal Flame Structure
Poludnenko, Alexei Y; 10.1016/j.combustflame.2009.11.018
2011-01-01
We study the dynamics and properties of a turbulent flame, formed in the presence of subsonic, high-speed, homogeneous, isotropic Kolmogorov-type turbulence in an unconfined system. Direct numerical simulations are performed with Athena-RFX, a massively parallel, fully compressible, high-order, dimensionally unsplit, reactive-flow code. A simplified reaction-diffusion model represents a stoichiometric H2-air mixture. The system being modeled represents turbulent combustion with the Damkohler number Da = 0.05 and with the turbulent velocity at the energy injection scale 30 times larger than the laminar flame speed. The simulations show that flame interaction with high-speed turbulence forms a steadily propagating turbulent flame with a flame brush width approximately twice the energy injection scale and a speed four times the laminar flame speed. A method for reconstructing the internal flame structure is described and used to show that the turbulent flame consists of tightly folded flamelets. The reaction zon...
Kernel Partial Least Squares for Nonlinear Regression and Discrimination
Rosipal, Roman; Clancy, Daniel (Technical Monitor)
2002-01-01
This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.
Mitigation of artifacts in rtm with migration kernel decomposition
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.
Sparse Event Modeling with Hierarchical Bayesian Kernel Methods
2016-01-05
the kernel function which depends on the application and the model user. This research uses the most popular kernel function, the radial basis...an important role in the nation’s economy. Unfortunately, the system’s reliability is declining due to the aging components of the network [Grier...kernel function. Gaussian Bayesian kernel models became very popular recently and were extended and applied to a number of classification problems. An
Heat and mass transfer in flames
Faeth, G. M.
1986-01-01
Heat- and mass-transfer processes in turbulent diffusion flames are discussed, considering turbulent mixing and the structure of single-phase flames, drop processes in spray flames, and nonluminous and luminous flame radiation. Interactions between turbulence and other phenomena are emphasized, concentrating on past work of the author and his associates. The conserved-scalar formalism, along with the laminar-flamelet approximation, is shown to provide reasonable estimates of the structure of gas flames, with modest levels of empiricism. Extending this approach to spray flames has highlighted the importance of drop/turbulence interactions; e.g., turbulent dispersion of drops, modification of turbulence by drops, etc. Stochastic methods being developed to treat these phenomena are yielding encouraging results.
Institute of Scientific and Technical Information of China (English)
Jinling Li; Suyuan Yu
2003-01-01
A laminar premixed Propane/Air flame with a fuel equivalence ratio of 2.1 was employed for analysis of soot particles. Zeroth-order Iognormal distributions (ZOLD) were used in the analysis of experimental distribution phenomena at different residence times during soot formation in the flame. Rayleigh's theory and Mie's scattering theory were combined with agglomerate analysis using scattering and extinction data to determine the following soot characteristics: agglomerate parameters, volumetric fractions, mass flow rates and surface growth rate. Soot density measurements were carried out to determine density variations at different stages of growth. The measured results show that metric fraction and mass flow rate indicate that the surface growth rate of soot particles exceeds the oxidation rates in the flame studied. The data obtained in this work would be used to study soot oxidation rate under flaming condition.
An Extended Ockham Algebra with Endomorphism Kernel Property
Institute of Scientific and Technical Information of China (English)
Jie FANG
2007-01-01
An algebraic structure (∮) is said to have the endomorphism kernel property if every congruence on (∮) , other than the universal congruence, is the kernel of an endomorphism on (∮) .Inthis paper, we consider the EKP (that is, endomorphism kernel property) for an extended Ockham algebra (∮) . In particular, we describe the structure of the finite symmetric extended de Morgan algebras having EKP.
End-use quality of soft kernel durum wheat
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...
7 CFR 981.61 - Redetermination of kernel weight.
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...
Multiple spectral kernel learning and a gaussian complexity computation.
Reyhani, Nima
2013-07-01
Multiple kernel learning (MKL) partially solves the kernel selection problem in support vector machines and similar classifiers by minimizing the empirical risk over a subset of the linear combination of given kernel matrices. For large sample sets, the size of the kernel matrices becomes a numerical issue. In many cases, the kernel matrix is of low-efficient rank. However, the low-rank property is not efficiently utilized in MKL algorithms. Here, we suggest multiple spectral kernel learning that efficiently uses the low-rank property by finding a kernel matrix from a set of Gram matrices of a few eigenvectors from all given kernel matrices, called a spectral kernel set. We provide a new bound for the gaussian complexity of the proposed kernel set, which depends on both the geometry of the kernel set and the number of Gram matrices. This characterization of the complexity implies that in an MKL setting, adding more kernels may not monotonically increase the complexity, while previous bounds show otherwise.
A Fast and Simple Graph Kernel for RDF
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
7 CFR 981.60 - Determination of kernel weight.
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...
21 CFR 176.350 - Tamarind seed kernel powder.
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...
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...
Stable Kernel Representations as Nonlinear Left Coprime Factorizations
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
Kernel Temporal Differences for Neural Decoding
Directory of Open Access Journals (Sweden)
Jihye Bae
2015-01-01
Full Text Available 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.
Bergman kernel and complex singularity exponent
Institute of Scientific and Technical Information of China (English)
LEE; HanJin
2009-01-01
We give a precise estimate of the Bergman kernel for the model domain defined by Ω F={(z,w) ∈ C n+1:Im w |F (z)| 2 > 0},where F=(f 1,...,f m) is a holomorphic map from C n to C m,in terms of the complex singularity exponent of F.
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...
Analytic properties of the Virasoro modular kernel
Nemkov, Nikita
2016-01-01
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.
A Cubic Kernel for Feedback Vertex Set
Bodlaender, H.L.
2006-01-01
The FEEDBACK VERTEX SET problem on unweighted, undirected graphs is considered. Improving upon a result by Burrage et al. [7], we show that this problem has a kernel with O(κ3) vertices, i.e., there is a polynomial time algorithm, that given a graph G and an integer κ, finds a graph G' and integer
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.)
Hyperbolic L2-modules with Reproducing Kernels
Institute of Scientific and Technical Information of China (English)
David EELPODE; Frank SOMMEN
2006-01-01
Abstract In this paper, the Dirac operator on the Klein model for the hyperbolic space is considered. A function space containing L2-functions on the sphere Sm-1 in (R)m, which are boundary values of solutions for this operator, is defined, and it is proved that this gives rise to a Hilbert module with a reproducing kernel.
Protein Structure Prediction Using String Kernels
2006-03-03
Prediction using String Kernels 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER...consists of 4352 sequences from SCOP version 1.53 extracted from the Astral database, grouped into families and superfamilies. The dataset is processed
Bergman kernel and complex singularity exponent
Institute of Scientific and Technical Information of China (English)
CHEN BoYong; LEE HanJin
2009-01-01
We give a precise estimate of the Bergman kernel for the model domain defined by Ω_F = {(z,w) ∈ C~(n+1) : Imw - |F(z)|~2 > 0},where F = (f_1,... ,f_m) is a holomorphic map from C~n to C~m,in terms of the complex singularity exponent of F.
Symbol recognition with kernel density matching.
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.
Developing Linux kernel space device driver
Institute of Scientific and Technical Information of China (English)
Zheng Wei; Wang Qinruo; Wu Naiyou
2003-01-01
This thesis introduces how to develop kernel level device drivers on Linux platform in detail. On the basis of comparing proc file system with dev file system, we choose PCI devices and USB devices as instances to introduce the method of writing device drivers for character devices by using these two file systems.
Heat Kernel Renormalization on Manifolds with Boundary
Albert, Benjamin I.
2016-01-01
In the monograph Renormalization and Effective Field Theory, Costello gave an inductive position space renormalization procedure for constructing an effective field theory that is based on heat kernel regularization of the propagator. In this paper, we extend Costello's renormalization procedure to a class of manifolds with boundary. In addition, we reorganize the presentation of the preexisting material, filling in details and strengthening the results.
Convolution kernels for multi-wavelength imaging
Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.
2016-12-01
Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher
Covariant derivative expansion of the heat kernel
Energy Technology Data Exchange (ETDEWEB)
Salcedo, L.L. [Universidad de Granada, Departamento de Fisica Moderna, Granada (Spain)
2004-11-01
Using the technique of labeled operators, compact explicit expressions are given for all traced heat kernel coefficients containing zero, two, four and six covariant derivatives, and for diagonal coefficients with zero, two and four derivatives. The results apply to boundaryless flat space-times and arbitrary non-Abelian scalar and gauge background fields. (orig.)
Flame Suppression Agent, System and Uses
Parrish, Clyde F. (Inventor)
2013-01-01
Aqueous droplets encapsulated in a flame retardant polymer are useful in suppressing combustion. Upon exposure to a flame, the encapsulated aqueous droplets rupture and vaporize, removing heat and displacing oxygen to retard the combustion process. The polymer encapsulant, through decomposition, may further add free radicals to the combustion atmosphere, thereby further retarding the combustion process. The encapsulated aqueous droplets may be used as a replacement to halon, water mist and dry powder flame suppression systems.
Comparative Analysis of Flame Characteristics of Castor Oil and ...
African Journals Online (AJOL)
Flame Retardants Used in Polyurethane Foam Systems. Polycarp .O. Ikeh ... such as ignition time, flame propagation rate, after glow, char rate, add-on and glow time. These properties .... hours before the flame test to ensure complete curing.
Pole solutions for flame front propagation
Kupervasser, Oleg
2015-01-01
This book deals with solving mathematically the unsteady flame propagation equations. New original mathematical methods for solving complex non-linear equations and investigating their properties are presented. Pole solutions for flame front propagation are developed. Premixed flames and filtration combustion have remarkable properties: the complex nonlinear integro-differential equations for these problems have exact analytical solutions described by the motion of poles in a complex plane. Instead of complex equations, a finite set of ordinary differential equations is applied. These solutions help to investigate analytically and numerically properties of the flame front propagation equations.
A Kernel Approach to Multi-Task Learning with Task-Specific Kernels
Institute of Scientific and Technical Information of China (English)
Wei Wu; Hang Li; Yun-Hua Hu; Rong Jin
2012-01-01
Several kernel-based methods for multi-task learning have been proposed,which leverage relations among tasks as regularization to enhance the overall learning accuracies.These methods assume that the tasks share the same kernel,which could limit their applications because in practice different tasks may need different kernels.The main challenge of introducing multiple kernels into multiple tasks is that models from different reproducing kernel Hilbert spaces (RKHSs) are not comparable,making it difficult to exploit relations among tasks.This paper addresses the challenge by formalizing the problem in the square integrable space (SIS).Specially,it proposes a kernel-based method which makes use of a regularization term defined in SIS to represent task relations.We prove a new representer theorem for the proposed approach in SIS.We further derive a practical method for solving the learning problem and conduct consistency analysis of the method.We discuss the relationship between our method and an existing method.We also give an SVM (support vector machine)-based implementation of our method for multi-label classification.Experiments on an artificial example and two real-world datasets show that the proposed method performs better than the existing method.
Kernel based orthogonalization for change detection in hyperspectral images
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
Kernel versions of principal component analysis (PCA) and minimum noise fraction (MNF) analysis are applied to change detection in hyperspectral image (HyMap) data. The kernel versions are based on so-called Q-mode analysis in which the data enter into the analysis via inner products in the Gram...... the kernel function and then performing a linear analysis in that space. An example shows the successful application of (kernel PCA and) kernel MNF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, in Southern Germany. In the change detection...
Geodesic exponential kernels: When Curvature and Linearity Conflict
DEFF Research Database (Denmark)
Feragen, Aase; Lauze, François; Hauberg, Søren
2015-01-01
We consider kernel methods on general geodesic metric spaces and provide both negative and positive results. First we show that the common Gaussian kernel can only be generalized to a positive definite kernel on a geodesic metric space if the space is flat. As a result, for data on a Riemannian...... Laplacian kernel can be generalized while retaining positive definiteness. This implies that geodesic Laplacian kernels can be generalized to some curved spaces, including spheres and hyperbolic spaces. Our theoretical results are verified empirically....
The pre-image problem in kernel methods.
Kwok, James Tin-yau; Tsang, Ivor Wai-hung
2004-11-01
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.
Generalization Performance of Regularized Ranking With Multiscale Kernels.
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.
Flame dynamics of a meso-scale heat recirculating combustor
Energy Technology Data Exchange (ETDEWEB)
Vijayan, V.; Gupta, A.K. [Department of Mechanical Engineering, University of Maryland, College Park, MD 20742 (United States)
2010-12-15
The dynamics of premixed propane-air flame in a meso-scale ceramic combustor has been examined here. The flame characteristics in the combustor were examined by measuring the acoustic emissions and preheat temperatures together with high-speed cinematography. For the small-scale combustor, the volume to surface area ratio is small and hence the walls have significant effect on the global flame structure, flame location and flame dynamics. In addition to the flame-wall thermal coupling there is a coupling between flame and acoustics in the case of confined flames. Flame-wall thermal interactions lead to low frequency flame fluctuations ({proportional_to}100 Hz) depending upon the thermal response of the wall. However, the flame-acoustic interactions can result in a wide range of flame fluctuations ranging from few hundred Hz to few kHz. Wall temperature distribution is one of the factors that control the amount of reactant preheating which in turn effects the location of flame stabilization. Acoustic emission signals and high-speed flame imaging confirmed that for the present case flame-acoustic interactions have more significant effect on flame dynamics. Based on the acoustic emissions, five different flame regimes have been identified; whistling/harmonic mode, rich instability mode, lean instability mode, silent mode and pulsating flame mode. (author)
Unsteady planar diffusion flames: Ignition, travel, burnout
Fendell, F.; Wu, F.
1995-01-01
In microgravity, a thin planar diffusion flame is created and thenceforth travels so that the flame is situated at all times at an interface at which the hydrogen and oxygen meet in stoichiometric proportion. If the initial amount of hydrogen is deficient relative to the initial amount of oxygen, then the planar flame will travel further and further into the half volume initially containing hydrogen, until the hydrogen is (virtually) fully depleted. Of course, when the amount of residual hydrogen becomes small, the diffusion flame is neither vigorous nor thin; in practice, the flame is extinguished before the hydrogen is fully depleted, owing to the finite rate of the actual chemical-kinetic mechanism. The rate of travel of the hydrogen-air diffusion flame is much slower than the rate of laminar flame propagation through a hydrogen-air mixture. This slow travel facilitates diagnostic detection of the flame position as a function of time, but the slow travel also means that the time to burnout (extinction) probably far exceeds the testing time (typically, a few seconds) available in earth-sited facilities for microgravity-environment experiments. We undertake an analysis to predict (1) the position and temperature of the diffusion flame as a function of time, (2) the time at which extinction of the diffusion flame occurs, and (3) the thickness of quench layers formed on side walls (i.e., on lateral boundaries, with normal vectors parallel to the diffusion-flame plane), and whether, prior to extinction, water vapor formed by burning will condense on these cold walls.
Tulip flames: changes in shape of premixed flames propagating in closed tubes
Dunn-Rankin, D.; Sawyer, R. F.
The experimental results that are the subject of this communication provide high-speed schlieren images of the closed-tube flame shape that has come to be known as the tulip flame. The schlieren images, along with in-chamber pressure records, help demonstrate the effects of chamber length, equivalence ratio, and igniter geometry on formation of the tulip flame. The pressure/time records show distinct features which correlate with flame shape changes during the transition to tulip. The measurements indicate that the basic tulip flame formation is a robust phenomenon that depends on little except the overall geometry of the combustion vessel.
Aromatics Oxidation and Soot Formation in Flames
Energy Technology Data Exchange (ETDEWEB)
Howard, J. B.; Richter, H.
2005-03-29
This project is concerned with the kinetics and mechanisms of aromatics oxidation and the growth process to polycyclic aromatic hydrocarbons (PAH) of increasing size, soot and fullerenes formation in flames. The overall objective of the experimental aromatics oxidation work is to extend the set of available data by measuring concentration profiles for decomposition intermediates such as phenyl, cyclopentadienyl, phenoxy or indenyl radicals which could not be measured with molecular-beam mass spectrometry to permit further refinement and testing of benzene oxidation mechanisms. The focus includes PAH radicals which are thought to play a major role in the soot formation process while their concentrations are in many cases too low to permit measurement with conventional mass spectrometry. The radical species measurements are used in critical testing and improvement of a kinetic model describing benzene oxidation and PAH growth. Thermodynamic property data of selected species are determined computationally, for instance using density functional theory (DFT). Potential energy surfaces are explored in order to identify additional reaction pathways. The ultimate goal is to understand the conversion of high molecular weight compounds to nascent soot particles, to assess the roles of planar and curved PAH and relationships between soot and fullerenes formation. The specific aims are to characterize both the high molecular weight compounds involved in the nucleation of soot particles and the structure of soot including internal nanoscale features indicative of contributions of planar and/or curved PAH to particle inception.
Aromatics Oxidation and Soot Formation in Flames
Energy Technology Data Exchange (ETDEWEB)
Howard, J. B.; Richter, H.
2005-03-29
This project is concerned with the kinetics and mechanisms of aromatics oxidation and the growth process to polycyclic aromatic hydrocarbons (PAH) of increasing size, soot and fullerenes formation in flames. The overall objective of the experimental aromatics oxidation work is to extend the set of available data by measuring concentration profiles for decomposition intermediates such as phenyl, cyclopentadienyl, phenoxy or indenyl radicals which could not be measured with molecular-beam mass spectrometry to permit further refinement and testing of benzene oxidation mechanisms. The focus includes PAH radicals which are thought to play a major role in the soot formation process while their concentrations are in many cases too low to permit measurement with conventional mass spectrometry. The radical species measurements are used in critical testing and improvement of a kinetic model describing benzene oxidation and PAH growth. Thermodynamic property data of selected species are determined computationally, for instance using density functional theory (DFT). Potential energy surfaces are explored in order to identify additional reaction pathways. The ultimate goal is to understand the conversion of high molecular weight compounds to nascent soot particles, to assess the roles of planar and curved PAH and relationships between soot and fullerenes formation. The specific aims are to characterize both the high molecular weight compounds involved in the nucleation of soot particles and the structure of soot including internal nanoscale features indicative of contributions of planar and/or curved PAH to particle inception.
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...... models to kernel learning, and means for restoring the generalizability in both kernel Principal Component Analysis and the Support Vector Machine are proposed. Viability is proved on a wide range of benchmark machine learning data sets....... as innerproducts in the model formulation. This dissertation presents research on improving the performance of standard kernel methods like kernel Principal Component Analysis and the Support Vector Machine. Moreover, the goal of the thesis has been two-fold. The first part focuses on the use of kernel Principal...
Efficient $\\chi ^{2}$ Kernel Linearization via Random Feature Maps.
Yuan, Xiao-Tong; Wang, Zhenzhen; Deng, Jiankang; Liu, Qingshan
2016-11-01
Explicit feature mapping is an appealing way to linearize additive kernels, such as χ(2) kernel for training large-scale support vector machines (SVMs). Although accurate in approximation, feature mapping could pose computational challenges in high-dimensional settings as it expands the original features to a higher dimensional space. To handle this issue in the context of χ(2) kernel SVMs learning, we introduce a simple yet efficient method to approximately linearize χ(2) kernel through random feature maps. The main idea is to use sparse random projection to reduce the dimensionality of feature maps while preserving their approximation capability to the original kernel. We provide approximation error bound for the proposed method. Furthermore, we extend our method to χ(2) multiple kernel SVMs learning. Extensive experiments on large-scale image classification tasks confirm that the proposed approach is able to significantly speed up the training process of the χ(2) kernel SVMs at almost no cost of testing accuracy.
Multiple Kernel Learning in Fisher Discriminant Analysis for Face Recognition
Directory of Open Access Journals (Sweden)
Xiao-Zhang Liu
2013-02-01
Full Text Available Recent applications and developments based on support vector machines (SVMs have shown that using multiple kernels instead of a single one can enhance classifier performance. However, there are few reports on performance of the kernel‐based Fisher discriminant analysis (kernel‐based FDA method with multiple kernels. This paper proposes a multiple kernel construction method for kernel‐based FDA. The constructed kernel is a linear combination of several base kernels with a constraint on their weights. By maximizing the margin maximization criterion (MMC, we present an iterative scheme for weight optimization. The experiments on the FERET and CMU PIE face databases show that, our multiple kernel Fisher discriminant analysis (MKFD achieves high recognition performance, compared with single‐kernel‐based FDA. The experiments also show that the constructed kernel relaxes parameter selection for kernel‐based FDA to some extent.
Institute of Scientific and Technical Information of China (English)
陈珊珊; 蒋勇; 邱榕; 安江涛
2012-01-01
A numerical study on premixed methane/ethylene/air flames with various ethylene fractions and equivalence ratios was conducted at room temperature and atmospheric pressure. The effects of ethylene addition on laminar burning velocity, flame structure and flame stability under the condition of lean burning were investigated. The results show that the laminar burning velocity increases with ethylene fraction, especially at a large equivalence ratio. More ethylene addition gives rise to higher concentrations of H, O and OH radicals in the flame, which significantly promotes chemical reactions, and a linear correlation exists between the laminar burning velocity and the maximum H + OH concentration in the reaction zone. With the increase of ethylene fraction, the adiabatic flame temperature is raised, while the inner layer temperature becomes lower, contributing to the enhancement of combustion. Markstein length and Markstein number, representative of the flame stability, increase as more ethylene is added, indicating the tendency of flame stability to improve with ethylene addition.
On the transition from a highly turbulent curved flame into a tulip flame
Energy Technology Data Exchange (ETDEWEB)
Kratzel, T.; Pantow, E.; Fischer, M. [German Aerospace Research Establishment, Stuttgart (Germany). Institute of Technical Thermodynamics
1998-12-31
Experimental and numerical investigations of premixed flame propagation behaviour associated with vortex interactions due to planar pressure waves crossing a curved flame front have been carried out. The resulting ``tulip flame`` formation in such a closed tube has been studied by Schlieren visualization. The ``tulip flame`` phenomenon was observed only closed tubes, while cellular flame fronts appeared in half-open tubes. A physical model has been developed and implemented in a discrete vortex method combined with a flame tracking algorithm. The numerical method has been applied to model and understand the processes that cause the flame to change from a curved to a tulip shape. The results of the simulation are in good agreement with the experimental observations. (author)
A Novel Framework for Learning Geometry-Aware Kernels.
Pan, Binbin; Chen, Wen-Sheng; Xu, Chen; Chen, Bo
2016-05-01
The data from real world usually have nonlinear geometric structure, which are often assumed to lie on or close to a low-dimensional manifold in a high-dimensional space. How to detect this nonlinear geometric structure of the data is important for the learning algorithms. Recently, there has been a surge of interest in utilizing kernels to exploit the manifold structure of the data. Such kernels are called geometry-aware kernels and are widely used in the machine learning algorithms. The performance of these algorithms critically relies on the choice of the geometry-aware kernels. Intuitively, a good geometry-aware kernel should utilize additional information other than the geometric information. In many applications, it is required to compute the out-of-sample data directly. However, most of the geometry-aware kernel methods are restricted to the available data given beforehand, with no straightforward extension for out-of-sample data. In this paper, we propose a framework for more general geometry-aware kernel learning. The proposed framework integrates multiple sources of information and enables us to develop flexible and effective kernel matrices. Then, we theoretically show how the learned kernel matrices are extended to the corresponding kernel functions, in which the out-of-sample data can be computed directly. Under our framework, a novel family of geometry-aware kernels is developed. Especially, some existing geometry-aware kernels can be viewed as instances of our framework. The performance of the kernels is evaluated on dimensionality reduction, classification, and clustering tasks. The empirical results show that our kernels significantly improve the performance.
Kernel Density Estimation, Kernel Methods, and Fast Learning in Large Data Sets.
Wang, Shitong; Wang, Jun; Chung, Fu-lai
2014-01-01
Kernel methods such as the standard support vector machine and support vector regression trainings take O(N(3)) time and O(N(2)) space complexities in their naïve implementations, where N is the training set size. It is thus computationally infeasible in applying them to large data sets, and a replacement of the naive method for finding the quadratic programming (QP) solutions is highly desirable. By observing that many kernel methods can be linked up with kernel density estimate (KDE) which can be efficiently implemented by some approximation techniques, a new learning method called fast KDE (FastKDE) is proposed to scale up kernel methods. It is based on establishing a connection between KDE and the QP problems formulated for kernel methods using an entropy-based integrated-squared-error criterion. As a result, FastKDE approximation methods can be applied to solve these QP problems. In this paper, the latest advance in fast data reduction via KDE is exploited. With just a simple sampling strategy, the resulted FastKDE method can be used to scale up various kernel methods with a theoretical guarantee that their performance does not degrade a lot. It has a time complexity of O(m(3)) where m is the number of the data points sampled from the training set. Experiments on different benchmarking data sets demonstrate that the proposed method has comparable performance with the state-of-art method and it is effective for a wide range of kernel methods to achieve fast learning in large data sets.
Monitoring Atmospheric Transmission with FLAME
Zimmer, Peter C.; McGraw, J. T.; Zirzow, D. C.; Koppa, M.; Buttler-Pena, K.
2014-01-01
Calibration of ground-based observations in the optical and near-infrared requires precise and accurate understanding of atmospheric transmission, at least as precise and accurate as that required for the spectral energy distributions of science targets. Traditionally this has used the Langley extrapolation method, observing targets and calibrators over a range of airmass and extrapolating to zero airmass by assuming a plane-parallel homogeneous atmosphere. The technique we present uses direct measurements of the atmosphere to derive the transmission along the line of sight to science targets at a few well-chosen wavelengths. The Facility Lidar Atmospheric Monitor of Extinction (FLAME) is a 0.5m diameter three Nd:YAG wavelength (355nm, 532nm & 1064nm) elastic backscatter lidar system. Laser pulses are transmitted into the atmosphere in the direction of the science target. Photons scattered back toward the receiver by molecules, aerosols and clouds are collected and time-gated so that the backscatter intensity is measured as a function of range to the scattering volume. The system is housed in a mobile calibration lab, which also contains auxiliary instrumentation to provide a NIST traceable calibration of the transmitted laser power and receiver efficiency. FLAME was designed to create a million photons per minute signal from the middle stratosphere, where the atmosphere is relatively calm and dominated by molecules of the well-mixed atmosphere (O2 & N2). Routine radiosonde measurements of the density at these altitudes constrain the scattering efficiency in this region and, combined with calibration of the transmitter and receiver, the only remaining unknown quantity is the two-way transmission to the stratosphere. These measurements can inform atmospheric transmission models to better understand the complex and ever-changing observatory radiative transfer environment. FLAME is currently under active development and we present some of our ongoing measurements.
Physical and Chemical Processing in Flames
2013-08-12
than the classical Troe formula, and the development of a Chemical Explosive Mode Analysis ( CEMA ) computation algorithm that allows on-the-fly...6-311++G(d,p) method. 3. Flame Stabilization and Chemical Explosive Mode Analysis ( CEMA ) Flame stabilization is essential in the understanding of
Development of PIV for Microgravity Diffusion Flames
Greenberg, Paul S.; Wernet, Mark P.; Yanis, William; Urban, David L.; Sunderland, Peter B.
2003-01-01
Results are presented from the application of Particle Image Velocimetry(PIV) to the overfire region of a laminar gas jet diffusion flame in normal gravity. A methane flame burning in air at 0.98 bar was considered. The apparatus demonstrated here is packaged in a drop rig designed for use in the 2.2 second drop tower.
Chemical processes in the HNF flame
Ermolin, N.E.; Zarko, V.E.; Keizers, H.L.J.
2006-01-01
Results of modeling the HNF flame structure are presented. From an analysis of literature data on the thermal decomposition and combustion of HNF, it is concluded that the dissociative vaporization of HNF proceeds via the route HNFliq → (N2H4)g + (HC(NO 2)3)g. The flame structure is modeled using a
Flaming in CMC: Prometheus' Fire or Inferno's?
Abrams, Zsuzsanna Ittzes
2003-01-01
Reports on a descriptive study with 75 intermediate college learners of German participating in two sessions of synchronous computer mediated communication during the course of a semester that investigated students' flaming behavior--aggressive interpersonal language and rude behavior. Shows that not only is flaming a very infrequent occurrence,…
Flame retardant cotton barrier nonwovens for mattresses
According to regulation CPSC 16 CFR 1633, every new residential mattress sold in the United States since July 2007 must resist ignition by open flame. An environmentally benign “green”, inexpensive way to meet this regulation is to use a low-cost flame retardant (FR) barrier fabric. In this study, a...
Flame retardant cotton based highloft nonwovens
Flame retardancy has been a serious bottleneck to develop cotton blended very high specific volume bulky High loft fabrics. Alternately, newer approach to produce flame retardant cotton blended High loft fabrics must be employed that retain soft feel characteristics desirable of furnishings. Hence, ...
Flaming in CMC: Prometheus' Fire or Inferno's?
Abrams, Zsuzsanna Ittzes
2003-01-01
Reports on a descriptive study with 75 intermediate college learners of German participating in two sessions of synchronous computer mediated communication during the course of a semester that investigated students' flaming behavior--aggressive interpersonal language and rude behavior. Shows that not only is flaming a very infrequent occurrence,…
Physical and Chemical Processes in Turbulent Flames
2015-06-23
DISTRIBUTION A: Distribution approved for public release. AF Office Of Scientific Research (AFOSR)/ RTE Arlington, Virginia 22203 Air Force Research...two-year subject program, conducted through tight coupling between experiment, theory and computation, and reported in high impact journal articles ...The thrust for this program constitutes of three major areas of turbulent combustion: (1) Flame surface statistics , (2) Flame-turbulence interaction
Simulations of flame generated particles
Patterson, Robert
2016-01-05
The nonlinear structure of the equations describing the evolution of a population of coagulating particles in a flame make the use of stochastic particle methods attractive for numerical purposes. I will present an analysis of the stochastic fluctuations inherent in these numerical methods leading to an efficient sampling technique for steady-state problems. I will also give some examples where stochastic particle methods have been used to explore the effect of uncertain parameters in soot formation models. In conclusion I will try to indicate some of the issues in optimising these methods for the study of uncertain model parameters.
Numerical modeling of turbulent combustion and flame spread
Energy Technology Data Exchange (ETDEWEB)
Yan Zhenghua
1999-01-01
Theoretical models have been developed to address several important aspects of numerical modeling of turbulent combustion and flame spread. The developed models include a pyrolysis model for charring and non-charring solid materials, a fast narrow band radiation property evaluation model (FASTNB) and a turbulence model for buoyant flow and flame. In the pyrolysis model, a completely new algorithm has been proposed, where a moving dual mesh concept was developed and implemented. With this new concept, it provides proper spatial resolution for both temperature and density and automatically considers the regression of the surface of the non-charring solid material during its pyrolysis. It is simple, very efficient and applicable to both charring and non-charring materials. FASTNB speeds up significantly the evaluation of narrow band spectral radiation properties and thus provides a potential of applying narrow band model in numerical simulations of practical turbulent combustion. The turbulence model was developed to improve the consideration of buoyancy effect on turbulence and turbulent transport. It was found to be simple, promising and numerically stable. It has been tested against both plane and axisymmetric thermal plumes and an axisymmetric buoyant diffusion flame. When compared with the widely used standard buoyancy-modified {kappa} - {epsilon} model, it gives significant improvement on numerical results. These developed models have been fully incorporated into CFD (Computational Fluid Dynamics) code and coupled with other CFD sub-models, including the DT (Discrete Transfer) radiation model, EDC (Eddy Dissipation Concept) combustion model, flamelet combustion model, various soot models and transpired wall function. Comprehensive numerical simulations have been carried out to study soot formation and oxidation in turbulent buoyant diffusion flames, flame heat transfer and flame spread in fires. The gas temperature and velocity, soot volume fraction, wall
Defective Kernel Mutants of Maize II. Morphological and Embryo Culture Studies.
Sheridan, W F; Neuffer, M G
1980-08-01
This report presents the initial results of our study of the immature kernel stage of 150 defective kernel maize mutants. They are single gene, recessive mutants that map throughout the genome, defective in both endosperm and embryo development and, for the most part, lethal (Neuffer and Sheridan 1980). All can be distinguished on immature ears, and 85% of them reveal a mutant phenotype within 11 to 17 days post-pollination. Most have immature kernels that are smaller and lighter in color than their normal counterparts. Forty of the mutants suffer from their defects early in kernel development and are blocked in embryogenesis before their primordia differentiate, or, if primordia are formed, they are unable to germinate when cultured as immature embryos or tested at maturity; a few begin embryo degeneration prior to the time that mutant kernels became visually distinguishable. The others express the associated lesion later in kernel development and form at least one leaf primordium by the time kernels are distinguishable and will germinate when cultured or tested at maturity. In most cases, on a fresh weight basis, the mutants have embryos that are more severely defective than the endosperm; their embryos usually are no more than one-half to two-thirds the size, and lag behind by one or two developmental stages. in comparison with embryos in normal kernels from the same ear. One hundred and two mutants were examined by culturing embryos on basal and enriched media; 21 simply enlarged or completely failed to grow on any of the media tested; and 81 produced shoots and roots on at least one medium. Many grew equally well on basal and enriched media; 16 grew at a faster rate on basal medium and 23 displayed a superior growth on enriched medium. Among the latter group, 10 may be auxotrophs. One of these mutants and another mutant isolated by E. H. Coe are proline-requiring mutants, allelic to pro-1. Considering their diversity of expression as evidenced by their
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.
Learning Potential Energy Landscapes using Graph Kernels
Ferré, G; Barros, K
2016-01-01
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. We show on a standard benchmark that our Graph Approximated Energy (GRAPE) method is competitive with state of the art kernel m...
A kernel version of spatial factor analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2009-01-01
of PCA and related techniques. An interesting dilemma in reduction of dimensionality of data is the desire to obtain simplicity for better understanding, visualization and interpretation of the data on the one hand, and the desire to retain sufficient detail for adequate representation on the other hand......Based on work by Pearson in 1901, Hotelling in 1933 introduced principal component analysis (PCA). PCA is often used for general feature generation and linear orthogonalization or compression by dimensionality reduction of correlated multivariate data, see Jolliffe for a comprehensive description...... 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...
Quark-hadron duality: pinched kernel approch
Dominguez, C A; Schilcher, K; Spiesberger, H
2016-01-01
Hadronic spectral functions measured by the ALEPH collaboration in the vector and axial-vector channels are used to study potential quark-hadron duality violations (DV). This is done entirely in the framework of pinched kernel finite energy sum rules (FESR), i.e. in a model independent fashion. The kinematical range of the ALEPH data is effectively extended up to $s = 10\\; {\\mbox{GeV}^2}$ by using an appropriate kernel, and assuming that in this region the spectral functions are given by perturbative QCD. Support for this assumption is obtained by using $e^+ e^-$ annihilation data in the vector channel. Results in both channels show a good saturation of the pinched FESR, without further need of explicit models of DV.
Analog Forecasting with Dynamics-Adapted Kernels
Zhao, Zhizhen
2014-01-01
Analog forecasting is a non-parametric 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 state-space reconstruction for dynamical systems and kernel methods developed in harmonic analysis and machine learning. The first improvement is to augment the dimension of the initial data using Takens' delay-coordinate maps to recover information in the initial data lost through partial observations. Then, instead of using Euclidean distances between the states, weighted ensembles of analogs are constructed according to similarity kernels in delay-coordinate space, featuring an explicit dependence on the dynamical vector field generating the data. The eigenvalues and eigenfunctions ...
Edge Diffusion Flame Propagation and Stabilization Studied
Takahashi, Fumiaki; Katta, Viswanath R.
2004-01-01
In most practical combustion systems or fires, fuel and air are initially unmixed, thus forming diffusion flames. As a result of flame-surface interactions, the diffusion flame often forms an edge, which may attach to burner walls, spread over condensed fuel surfaces, jump to another location through the fuel-air mixture formed, or extinguish by destabilization (blowoff). Flame holding in combustors is necessary to achieve design performance and safe operation of the system. Fires aboard spacecraft behave differently from those on Earth because of the absence of buoyancy in microgravity. This ongoing in-house flame-stability research at the NASA Glenn Research Center is important in spacecraft fire safety and Earth-bound combustion systems.
Interaction Between Flames and Electric Fields Studied
Yuan, Zeng-Guang; Hegde, Uday
2003-01-01
The interaction between flames and electric fields has long been an interesting research subject that has theoretical importance as well as practical significance. Many of the reactions in a flame follow an ionic pathway: that is, positive and negative ions are formed during the intermediate steps of the reaction. When an external electric field is applied, the ions move according to the electric force (the Coulomb force) exerted on them. The motion of the ions modifies the chemistry because the reacting species are altered, it changes the velocity field of the flame, and it alters the electric field distribution. As a result, the flame will change its shape and location to meet all thermal, chemical, and electrical constraints. In normal gravity, the strong buoyant effect often makes the flame multidimensional and, thus, hinders the detailed study of the problem.
Searching and Indexing Genomic Databases via Kernelization
Directory of Open Access Journals (Sweden)
Travis eGagie
2015-02-01
Full Text Available The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.
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). Th......). The MAF projection exploits the fact that interesting phenomena in images typically exhibit spatial autocorrelation. The analysis is based on nearinfrared hyperspectral images of maize grains demonstrating the superiority of the kernelbased MAF method....
Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?
Indian Academy of Sciences (India)
Fa Cui; Anming Ding; Jun Li; Chunhua Zhao; Xingfeng Li; Deshun Feng; Xiuqin Wang; Lin Wang; Jurong Gao; Honggang Wang
2011-12-01
Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F8:9 recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.
Inertial particles in a turbulent premixed Bunsen flame
Energy Technology Data Exchange (ETDEWEB)
Battista, F.; Picano, F.; Casciola, C.M. [Sapienza Univ., Rome (Italy). Dipt. di Meccanica e Aeronautica; Troiani, G. [ENEA C.R. Casaccia, Rome (Italy)
2012-07-01
Many fields of engineering and physics are characterized by reacting flows seeded with particles of different inertia and dimensions, e.g. solid-propellant rockets, reciprocating engines where carbon particles form due to combustion, vulcano eruptions. Particles are also used as velocity transducers in Particle Image Velocimetry (PIV) of turbulent flames. The effects of combustion on inertial particle dynamics is still poorly understood, despite its relevance for its effects on particle collisions and coalescence, phenomena which have a large influence in soot formation and growth. As a matter of fact, the flame front induces abrupt accelerations of the fluid in a very thin region which particles follow with different lags depending on their inertia. This phenomenon has a large impact on the particle spatial arrangement. The issuing clustering is here analyzed by a DNS of Bunsen turbulent flame coupled with particle Lagrangian tracking with the aim of evaluating the effect of inertia on particle spatial localization in combustion applications. The Eulerian algorith is based on Low-Mach number expansion of Navier-Stokes equations that allow arbitrary density variations neglecting acoustics waves. (orig.)
Absolute Orientation Based on Distance Kernel Functions
Directory of Open Access Journals (Sweden)
Yanbiao Sun
2016-03-01
Full Text Available The classical absolute orientation method is capable of transforming tie points (TPs from a local coordinate system to a global (geodetic coordinate system. The method is based only on a unique set of similarity transformation parameters estimated by minimizing the total difference between all ground control points (GCPs and the fitted points. Nevertheless, it often yields a transformation with poor accuracy, especially in large-scale study cases. To address this problem, this study proposes a novel absolute orientation method based on distance kernel functions, in which various sets of similarity transformation parameters instead of only one set are calculated. When estimating the similarity transformation parameters for TPs using the iterative solution of a non-linear least squares problem, we assigned larger weighting matrices for the GCPs for which the distances from the point are short. The weighting matrices can be evaluated using the distance kernel function as a function of the distances between the GCPs and the TPs. Furthermore, we used the exponential function and the Gaussian function to describe distance kernel functions in this study. To validate and verify the proposed method, six synthetic and two real datasets were tested. The accuracy was significantly improved by the proposed method when compared to the classical method, although a higher computational complexity is experienced.
Physicochemical Properties of Palm Kernel Oil
Directory of Open Access Journals (Sweden)
Amira P. Olaniyi
2014-09-01
Full Text Available Physicochemical analyses were carried out on palm kernel oil (Adin and the following results were obtained: Saponification value; 280.5±56.1 mgKOH/g, acid value; 2.7±0.3 mg KOH/g, Free Fatty Acid (FFA; 1.35±0.15 KOH/g, ester value; 277.8±56.4 mgKOH/g, peroxide value; 14.3±0.8 mEq/kg; iodine value; 15.86±4.02 mgKOH/g, Specific Gravity (S.G value; 0.904, refractive index; 1.412 and inorganic materials; 1.05%. Its odour and colour were heavy burnt smell and burnt brown, respectively. These values were compared with those obtained for groundnut and coconut oils. It was found that the physico-chemical properties of palm kernel oil are comparable to those of groundnut and coconut oils except for the peroxide value (i.e., 14.3±0.8 mEq which was not detectable in groundnut and coconut oils. Also the odour of both groundnut and coconut oils were pleasant while that of the palm kernel oil was not as pleasant (i.e., heavy burnt smell.
Convolution kernels for multi-wavelength imaging
Boucaud, Alexandre; Abergel, Alain; Orieux, François; Dole, Hervé; Hadj-Youcef, Mohamed Amine
2016-01-01
Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as PSF, that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assumin...
A Fast Reduced Kernel Extreme Learning Machine.
Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua
2016-04-01
In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred.
Kernel methods for phenotyping complex plant architecture.
Kawamura, Koji; Hibrand-Saint Oyant, Laurence; Foucher, Fabrice; Thouroude, Tatiana; Loustau, Sébastien
2014-02-07
The Quantitative Trait Loci (QTL) mapping of plant architecture is a critical step for understanding the genetic determinism of plant architecture. Previous studies adopted simple measurements, such as plant-height, stem-diameter and branching-intensity for QTL mapping of plant architecture. Many of these quantitative traits were generally correlated to each other, which give rise to statistical problem in the detection of QTL. We aim to test the applicability of kernel methods to phenotyping inflorescence architecture and its QTL mapping. We first test Kernel Principal Component Analysis (KPCA) and Support Vector Machines (SVM) over an artificial dataset of simulated inflorescences with different types of flower distribution, which is coded as a sequence of flower-number per node along a shoot. The ability of discriminating the different inflorescence types by SVM and KPCA is illustrated. We then apply the KPCA representation to the real dataset of rose inflorescence shoots (n=1460) obtained from a 98 F1 hybrid mapping population. We find kernel principal components with high heritability (>0.7), and the QTL analysis identifies a new QTL, which was not detected by a trait-by-trait analysis of simple architectural measurements. The main tools developed in this paper could be use to tackle the general problem of QTL mapping of complex (sequences, 3D structure, graphs) phenotypic traits.
Cool Sooting Flames of Hydrocarbons
Institute of Scientific and Technical Information of China (English)
Z.A. MANSUROV
2001-01-01
This paper presents the study of polycyclic aromatic hydrocarbons (PAH) and paramagnetism of soot particles sampled from cool sooting flames of methane and propane in a separately-heated two-sectional reactor under atmospheric pressure at the reactor temperatures of 670-1170 K. The temperature profiles of the flames were studied. The sampling was carried out with a quartz sampler and the samples were frozen with liquid nitrogen. A number of polyaromatic hydrocarbons such as pyrene, fluoranthene, coronene, anthanthrene, 1,12-benzperylene,were identified by spectroscopic methods in the extract of soot. The processes of soot formation at methaneoxygen mixture combustion in the electric field with applied potential changed from 0 to 2,2 kV at different polarity of electrodes have been investigated. It has been stated that at the electrical field application, an increase in soot particle sizes and soot yield occurs; besides, at the application of the field, speeding up the positively charged particles, the interplanar distance decreases. On the basis of investigation of soot particles paramagnetism, it was shown that initially soot particles have high carcinogetic activity and pollute the environment owing to a rapid decrease of the number of these radical centers. The reduction of the radical concentration is connected with radical recombination on soot.
Laguerre Kernels –Based SVM for Image Classification
Directory of Open Access Journals (Sweden)
Ashraf Afifi
2014-01-01
Full Text Available Support vector machines (SVMs have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient properties that other methods hardly provide. However the performance of SVMs is very sensitive to how the kernel function is selected, the challenge is to choose the kernel function for accurate data classification. In this paper, we introduce a set of new kernel functions derived from the generalized Laguerre polynomials. The proposed kernels could improve the classification accuracy of SVMs for both linear and nonlinear data sets. The proposed kernel functions satisfy Mercer’s condition and orthogonally properties which are important and useful in some applications when the support vector number is needed as in feature selection. The performance of the generalized Laguerre kernels is evaluated in comparison with the existing kernels. It was found that the choice of the kernel function, and the values of the parameters for that kernel are critical for a given amount of data. The proposed kernels give good classification accuracy in nearly all the data sets, especially those of high dimensions.
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.
Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.
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.
Image quality of mixed convolution kernel in thoracic computed tomography.
Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar
2016-11-01
The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.
Al-Noman, Saeed M.
2016-06-01
Autoignition characteristics of pre-vaporized iso-octane, primary reference fuels, gasolines, and dimethyl ether (DME) have been investigated experimentally in a coflow with elevated temperature of air. With the coflow air at relatively low initial temperatures below autoignition temperature Tauto, an external ignition source was required to stabilize the flame. Non-autoignited lifted flames had tribrachial edge structures and their liftoff heights correlated well with the jet velocity scaled by the stoichiometric laminar burning velocity, indicating the importance of the edge propagation speed on flame stabilization balanced with local flow velocity. At high initial temperatures over Tauto, the autoignited flames were stabilized without requiring an external ignition source. The autoignited lifted flames exhibited either tribrachial edge structures or Mild combustion behaviors depending on the level of fuel dilution. For the iso-octane and n-heptane fuels, two distinct transition behaviors were observed in the autoignition regime from a nozzle-attached flame to a lifted tribrachial-edge flame and then a sudden transition to lifted Mild combustion as the jet velocity increased at a certain fuel dilution level. The liftoff data of the autoignited flames with tribrachial edges were analyzed based on calculated ignition delay times for the pre-vaporized fuels. Analysis of the experimental data suggested that ignition delay time may be much less sensitive to initial temperature under atmospheric pressure conditions as compared with predictions. For the gasoline fuels for advanced combustion engines (FACEs), and primary reference fuels (PRFs), autoignited liftoff data were correlated with Research Octane Number and Cetane Number. For the DME fuel, planar laser-induced fluorescence (PLIF) of formaldehyde (CH2O) and CH* chemiluminescence were visualized qualitatively. In the autoignition regime for both tribrachial structure and mild combustion, formaldehyde were found
Flame Structure and Emissions of Strongly-Pulsed Turbulent Diffusion Flames with Swirl
Liao, Ying-Hao
This work studies the turbulent flame structure, the reaction-zone structure and the exhaust emissions of strongly-pulsed, non-premixed flames with co-flow swirl. The fuel injection is controlled by strongly-pulsing the fuel flow by a fast-response solenoid valve such that the fuel flow is completely shut off between pulses. This control strategy allows the fuel injection to be controlled over a wide range of operating conditions, allowing the flame structure to range from isolated fully-modulated puffs to interacting puffs to steady flames. The swirl level is controlled by varying the ratio of the volumetric flow rate of the tangential air to that of the axial air. For strongly-pulsed flames, both with and without swirl, the flame geometry is strongly impacted by the injection time. Flames appear to exhibit compact, puff-like structures for short injection times, while elongated flames, similar in behaviors to steady flames, occur for long injection times. The flames with swirl are found to be shorter for the same fuel injection conditions. The separation/interaction level between flame puffs in these flames is essentially governed by the jet-off time. The separation between flame puffs decreases as swirl is imposed, consistent with the decrease in flame puff celerity due to swirl. The decreased flame length and flame puff celerity are consistent with an increased rate of air entrainment due to swirl. The highest levels of CO emissions are generally found for compact, isolated flame puffs, consistent with the rapid quenching due to rapid dilution with excess air. The imposition of swirl generally results in a decrease in CO levels, suggesting more rapid and complete fuel/air mixing by imposing swirl in the co-flow stream. The levels of NO emissions for most cases are generally below the steady-flame value. The NO levels become comparable to the steady-flame value for sufficiently short jet-off time. The swirled co-flow air can, in some cases, increase the NO
Scaling of turbulent flame speed for expanding flames with Markstein diffusion considerations.
Chaudhuri, Swetaprovo; Wu, Fujia; Law, Chung K
2013-09-01
In this paper we clarify the role of Markstein diffusivity, which is the product of the planar laminar flame speed and the Markstein length, on the turbulent flame speed and its scaling, based on experimental measurements on constant-pressure expanding turbulent flames. Turbulent flame propagation data are presented for premixed flames of mixtures of hydrogen, methane, ethylene, n-butane, and dimethyl ether with air, in near-isotropic turbulence in a dual-chamber, fan-stirred vessel. For each individual fuel-air mixture presented in this work and the recently published iso-octane data from Leeds, normalized turbulent flame speed data of individual fuel-air mixtures approximately follow a Re_{T,f}^{0.5} scaling, for which the average radius is the length scale and thermal diffusivity is the transport property of the turbulence Reynolds number. At a given Re_{T,f}^{}, it is experimentally observed that the normalized turbulent flame speed decreases with increasing Markstein number, which could be explained by considering Markstein diffusivity as the leading dissipation mechanism for the large wave number flame surface fluctuations. Consequently, by replacing thermal diffusivity with the Markstein diffusivity in the turbulence Reynolds number definition above, it is found that normalized turbulent flame speeds could be scaled by Re_{T,M}^{0.5} irrespective of the fuel, equivalence ratio, pressure, and turbulence intensity for positive Markstein number flames.
Directory of Open Access Journals (Sweden)
Muzhir Shaban Al-Ani
2011-05-01
Full Text Available Detecting faces across multiple views is more challenging than in a frontal view. To address this problem,an efficient approach is presented in this paper using a kernel machine based approach for learning suchnonlinear mappings to provide effective view-based representation for multi-view face detection. In thispaper Kernel Principal Component Analysis (KPCA is used to project data into the view-subspaces thencomputed as view-based features. Multi-view face detection is performed by classifying each input imageinto face or non-face class, by using a two class Kernel Support Vector Classifier (KSVC. Experimentalresults demonstrate successful face detection over a wide range of facial variation in color, illuminationconditions, position, scale, orientation, 3D pose, and expression in images from several photo collections.
Lee, Yi-Hsuan; von Davier, Alina A.
2008-01-01
The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…
Laminar Soot Processes Experiment Shedding Light on Flame Radiation
Urban, David L.
1998-01-01
The Laminar Soot Processes (LSP) experiment investigated soot processes in nonturbulent, round gas jet diffusion flames in still air. The soot processes within these flames are relevant to practical combustion in aircraft propulsion systems, diesel engines, and furnaces. However, for the LSP experiment, the flames were slowed and spread out to allow measurements that are not tractable for practical, Earth-bound flames.
Flaming: More than a Necessary Evil for Academic Mailing Lists?
Wang, Hongjie
1996-01-01
States that although Internet "gurus" advocate that users refrain from "flaming," in fact, flaming permeates the Internet. Explores the nature of flaming in its characteristics and forms as seen in academic discussion groups. Argues that flaming educates the ignorant, tames the uncouth, and promotes effective communication. (PA)
Merino-Aceituno, Sara
2016-12-01
The isotropic 4-wave kinetic equation is considered in its weak formulation using model (simplified) homogeneous kernels. Existence and uniqueness of solutions is proven in a particular setting where the kernels have a rate of growth at most linear. We also consider finite stochastic particle systems undergoing instantaneous coagulation-fragmentation phenomena and give conditions in which this system approximates the solution of the equation (mean-field limit).
Kernels for Vector-Valued Functions: a Review
Alvarez, Mauricio A; Lawrence, Neil D
2011-01-01
Kernel methods are among the most popular techniques in machine learning. From a frequentist/discriminative perspective they play a central role in regularization theory as they provide a natural choice for the hypotheses space and the regularization functional through the notion of reproducing kernel Hilbert spaces. From a Bayesian/generative perspective they are the key in the context of Gaussian processes, where the kernel function is also known as the covariance function. Traditionally, kernel methods have been used in supervised learning problem with scalar outputs and indeed there has been a considerable amount of work devoted to designing and learning kernels. More recently there has been an increasing interest in methods that deal with multiple outputs, motivated partly by frameworks like multitask learning. In this paper, we review different methods to design or learn valid kernel functions for multiple outputs, paying particular attention to the connection between probabilistic and functional method...
The dilution effect on the extinction of wall diffusion flame
Directory of Open Access Journals (Sweden)
Ghiti Nadjib
2014-12-01
Full Text Available The dynamic process of the interaction between a turbulent jet diffusion methane flame and a lateral wall was experimentally studied. The evolution of the flame temperature field with the Nitrogen dilution of the methane jet flame was examined. The interaction between the diffusion flame and the lateral wall was investigated for different distance between the wall and the central axes of the jet flame. The dilution is found to play the central role in the flame extinction process. The flame response as the lateral wall approaches from infinity and the increasing of the dilution rate make the flame extinction more rapid than the flame without dilution, when the nitrogen dilution rate increase the flame temperature decrease.
Structure of a poly(ethylene) opposed flow diffusion flame
Energy Technology Data Exchange (ETDEWEB)
Pitz, W.J.; Brown, N.J.; Sawyer, R.F.
1980-08-01
Structural measurements were obtained and compared with other investigations of diffusion flames. Departures from the commonly assumed collapsed flame model of laminar diffusion flames were observed in terms of excessive CO concentrations and oxygen penetration into the fuel side of the flame. An upper bound on the importance of oxygen diffusion to the fuel surface and subsequent surface oxidation was placed at 20% of the energy required for fuel pyrolysis, with the remainder of the energy being delivered to the surface from the flame through heat transfer processes. As the oxygen concentration in the oxidizer flow was decreased and extinction conditions approached, the CO/CO/sub 2/ ratio at the flame increased slightly, the oxygen concentration at the luminous flame zone decreased, the flame stand-off distance decreased, and the flame temperature decreased. Radial similarity in the composition and temperature profiles was established experimentally which confirms predictions and greatly simplifies the modeling of the opposed flow diffusion flame.
FRACTIONAL INTEGRALS WITH VARIABLE KERNELS ON HARDY SPACES
Institute of Scientific and Technical Information of China (English)
ZhangPu; DingYong
2003-01-01
The fractional integral operators with variable kernels are discussed.It is proved that if the kernel satisfies the Dini-condition,then the fractional integral operators with variable kernels are bounded from Hp(Rn) into Lq(Rn) when 0
Approximating and learning by Lipschitz kernel on the sphere
Institute of Scientific and Technical Information of China (English)
CAO Fei-long; WANG Chang-miao
2014-01-01
This paper investigates some approximation properties and learning rates of Lips-chitz kernel on the sphere. A perfect convergence rate on the shifts of Lipschitz kernel on the sphere, which is faster than O(n-1/2), is obtained, where n is the number of parameters needed in the approximation. By means of the approximation, a learning rate of regularized least square algorithm with the Lipschitz kernel on the sphere is also deduced.
Kernel based visual tracking with scale invariant features
Institute of Scientific and Technical Information of China (English)
Risheng Han; Zhongliang Jing; Yuanxiang Li
2008-01-01
The kernel based tracking has two disadvantages:the tracking window size cannot be adjusted efficiently,and the kernel based color distribution may not have enough ability to discriminate object from clutter background.FDr boosting up the feature's discriminating ability,both scale invariant features and kernel based color distribution features are used as descriptors of tracked object.The proposed algorithm can keep tracking object of varying scales even when the surrounding background is similar to the object's appearance.
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....
Aromatics oxidation and soot formation in flames
Energy Technology Data Exchange (ETDEWEB)
Howard, J.B.; Pope, C.J.; Shandross, R.A.; Yadav, T. [Massachusetts Institute of Technology, Cambridge (United States)
1993-12-01
This project is concerned with the kinetics and mechanisms of aromatics oxidation and soot and fullerenes formation in flames. The scope includes detailed measurements of profiles of stable and radical species concentrations in low-pressure one-dimensional premixed flames. Intermediate species identifications and mole fractions, fluxes, and net reaction rates calculated from the measured profiles are used to test postulated reaction mechanisms. Particular objectives are to identify and to determine or confirm rate constants for the main benzene oxidation reactions in flames, and to characterize fullerenes and their formation mechanisms and kinetics.
Systems and methods for controlling flame instability
Cha, Min Suk
2016-07-21
A system (62) for controlling flame instability comprising: a nozzle (66) coupled to a fuel supply line (70), an insulation housing (74) coupled to the nozzle, a combustor (78) coupled to the nozzle via the insulation housing, where the combustor is grounded (80), a pressure sensor (82) coupled to the combustor and configured to detect pressure in the combustor, and an instability controlling assembly coupled to the pressure sensor and to an alternating current power supply (86), where, the instability controlling assembly can control flame instability of a flame in the system based on pressure detected by the pressure sensor.
Novel Flame-Based Synthesis of Nanowires for Multifunctional Application
2015-05-13
laser-based diagnostics for in-situ Raman characterization of as- synthesized nanomaterials, (iv) flame synthesis of graphene , (v) flame synthesis of...laser- based diagnostics for in-situ Raman characterization of as-synthesized nanomaterials, (iv) flame synthesis of graphene , (v) flame synthesis of...Stephen D. Tse, Manish Chhowalla, Bernard H. Kear. Role of substrate, temperature, and hydrogen on the flame synthesis of graphene films, Proceedings
Acoustically Forced Coaxial Hydrogen / Liquid Oxygen Jet Flames
2016-05-15
visualized for both reacting and nonreacting cases. The jet flame was studied unforced, without acoustics , and forced, with transverse acoustic waves in...liquid rocket injector flames react to acoustic waves . In this study, a representative coaxial gaseous hydrogen / liquid oxygen (LOX) jet flame is...hydrogen / liquid oxygen (LOX) jet flame is visualized for both reacting and nonreacting cases. The jet flame was studied unforced, without acoustics , and
Energy Technology Data Exchange (ETDEWEB)
Kopp-Vaughan, Kristin M.; Tuttle, Steven G.; Renfro, Michael W. [Department of Mechanical Engineering, University of Connecticut, 191 Auditorium Rd, U-3139, Storrs, CT 06269 (United States); King, Galen B. [School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)
2009-10-15
An open-open organ pipe burner (Rijke tube) with a bluff-body ring was used to create a self-excited, acoustically-driven, premixed methane-air conical flame, with equivalence ratios ranging from 0.85 to 1.05. The feed tube velocities corresponded to Re = 1780-4450. Coupled oscillations in pressure, velocity, and heat release from the flame are naturally encouraged at resonant frequencies in the Rijke tube combustor. This coupling creates sustainable self-excited oscillations in flame front area and shape. The period of the oscillations occur at the resonant frequency of the combustion chamber when the flame is placed {proportional_to}1/4 of the distance from the bottom of the tube. In this investigation, the shape of these acoustically-driven flames is measured by employing both OH planar laser-induced fluorescence (PLIF) and chemiluminescence imaging and the images are correlated to simultaneously measured pressure in the combustor. Past research on acoustically perturbed flames has focused on qualitative flame area and heat release relationships under imposed velocity perturbations at imposed frequencies. This study reports quantitative empirical fits with respect to pressure or phase angle in a self-generated pressure oscillation. The OH-PLIF images were single temporal shots and the chemiluminescence images were phase averaged on chip, such that 15 exposures were used to create one image. Thus, both measurements were time resolved during the flame oscillation. Phase-resolved area and heat release variations throughout the pressure oscillation were computed. A relation between flame area and the phase angle before the pressure maximum was derived for all flames in order to quantitatively show that the Rayleigh criterion was satisfied in the combustor. Qualitative trends in oscillating flame area were found with respect to feed tube flow rates. A logarithmic relation was found between the RMS pressure and both the normalized average area and heat release rate
Direct numerical simulations of non-premixed ethylene-air flames: Local flame extinction criterion
Lecoustre, Vivien R.
2014-11-01
Direct Numerical Simulations (DNS) of ethylene/air diffusion flame extinctions in decaying two-dimensional turbulence were performed. A Damköhler-number-based flame extinction criterion as provided by classical large activation energy asymptotic (AEA) theory is assessed for its validity in predicting flame extinction and compared to one based on Chemical Explosive Mode Analysis (CEMA) of the detailed chemistry. The DNS code solves compressible flow conservation equations using high order finite difference and explicit time integration schemes. The ethylene/air chemistry is simulated with a reduced mechanism that is generated based on the directed relation graph (DRG) based methods along with stiffness removal. The numerical configuration is an ethylene fuel strip embedded in ambient air and exposed to a prescribed decaying turbulent flow field. The emphasis of this study is on the several flame extinction events observed in contrived parametric simulations. A modified viscosity and changing pressure (MVCP) scheme was adopted in order to artificially manipulate the probability of flame extinction. Using MVCP, pressure was changed from the baseline case of 1 atm to 0.1 and 10 atm. In the high pressure MVCP case, the simulated flame is extinction-free, whereas in the low pressure MVCP case, the simulated flame features frequent extinction events and is close to global extinction. Results show that, despite its relative simplicity and provided that the global flame activation temperature is correctly calibrated, the AEA-based flame extinction criterion can accurately predict the simulated flame extinction events. It is also found that the AEA-based criterion provides predictions of flame extinction that are consistent with those provided by a CEMA-based criterion. This study supports the validity of a simple Damköhler-number-based criterion to predict flame extinction in engineering-level CFD models. © 2014 The Combustion Institute.
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....
Reproducing wavelet kernel method in nonlinear system identification
Institute of Scientific and Technical Information of China (English)
WEN Xiang-jun; XU Xiao-ming; CAI Yun-ze
2008-01-01
By combining the wavelet decomposition with kernel method, a practical approach of universal multi-scale wavelet kernels constructed in reproducing kernel Hilbert space (RKHS) is discussed, and an identifica-tion scheme using wavelet support vector machines ( WSVM ) estimator is proposed for nonlinear dynamic sys-tems. The good approximating properties of wavelet kernel function enhance the generalization ability of the pro-posed method, and the comparison of some numerical experimental results between the novel approach and some existing methods is encouraging.
Influence of wheat kernel physical properties on the pulverizing process.
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.
A Kernel-based Account of Bibliometric Measures
Ito, Takahiko; Shimbo, Masashi; Kudo, Taku; Matsumoto, Yuji
The application of kernel methods to citation analysis is explored. We show that a family of kernels on graphs provides a unified perspective on the three bibliometric measures that have been discussed independently: relatedness between documents, global importance of individual documents, and importance of documents relative to one or more (root) documents (relative importance). The framework provided by the kernels establishes relative importance as an intermediate between relatedness and global importance, in which the degree of `relativity,' or the bias between relatedness and importance, is naturally controlled by a parameter characterizing individual kernels in the family.
WAVELET KERNEL SUPPORT VECTOR MACHINES FOR SPARSE APPROXIMATION
Institute of Scientific and Technical Information of China (English)
Tong Yubing; Yang Dongkai; Zhang Qishan
2006-01-01
Wavelet, a powerful tool for signal processing, can be used to approximate the target function. For enhancing the sparse property of wavelet approximation, a new algorithm was proposed by using wavelet kernel Support Vector Machines (SVM), which can converge to minimum error with better sparsity. Here, wavelet functions would be firstly used to construct the admitted kernel for SVM according to Mercy theory; then new SVM with this kernel can be used to approximate the target funciton with better sparsity than wavelet approxiamtion itself. The results obtained by our simulation experiment show the feasibility and validity of wavelet kernel support vector machines.
Convolution kernel design and efficient algorithm for sampling density correction.
Johnson, Kenneth O; Pipe, James G
2009-02-01
Sampling density compensation is an important step in non-cartesian image reconstruction. One of the common techniques to determine weights that compensate for differences in sampling density involves a convolution. A new convolution kernel is designed for sampling density attempting to minimize the error in a fully reconstructed image. The resulting weights obtained using this new kernel are compared with various previous methods, showing a reduction in reconstruction error. A computationally efficient algorithm is also presented that facilitates the calculation of the convolution of finite kernels. Both the kernel and the algorithm are extended to 3D. Copyright 2009 Wiley-Liss, Inc.
High pressure flame system for pollution studies with results for methane-air diffusion flames
Miller, I. M.; Maahs, H. G.
1977-01-01
A high pressure flame system was designed and constructed for studying nitrogen oxide formation in fuel air combustion. Its advantages and limitations were demonstrated by tests with a confined laminar methane air diffusion flame over the pressure range from 1 to 50 atm. The methane issued from a 3.06 mm diameter port concentrically into a stream of air contained within a 20.5 mm diameter chimney. As the combustion pressure is increased, the flame changes in shape from wide and convex to slender and concave, and there is a marked increase in the amount of luminous carbon. The height of the flame changes only moderately with pressure.
Flame and solution syntheses of high-dimensional homo- and hetero-structured nanomaterials
Dong, Zhizhong
Tungsten-oxide and molybdenum-oxide nanostructures are fabricated directly from the surfaces of metal substrates using counter-flow diffusion-flame synthesis method, which allows for correlation of morphologies with local conditions. Computational simulations aid in tailoring the flame structure with respect to chemical species and temperature. Furthermore, methane flames are compared with hydrogen flames, which only have H2O (and no CO2) as product species. The temperature profiles of the methane and hydrogen flames are strategically matched in order to compare the effect of chemical species produced by the flame which serve as reactants for nanostructure growth. Single-crystalline, well-vertically-aligned, and dense WO2.9 nanowires (diameters of 20-50 nm, lengths of >10 microm) are obtained at a gas-phase temperature of 1720 K, where the CO2 route is presumed to seed the growth of nanowires at the nucleation stage, with subsequent vapor-solid growth. Similarly, single-crystalline, vertically-aligned, and dense MoO 2 nanoplates (thicknesses of 60-80 nm, widths of 200-450 nm, lengths of 1-2 microm) are obtained at 1720 K. Nanoheterostructures are fabricated by decorating/coating the above flame-synthesized tungsten-oxide nanowires with other materials using an aqueous solution synthesis method. With WO 2.9 nanowires serving as the scaffold, sequential growth of hexagonal ZnO nanoplates, Zn2SnO4 nanocubes, and SnO2 nanoparticles are attained for different Zn2+:Sn2+ concentration ratios. High-resolution transmission electron microscopy (HRTEM) of the interfaces at the nanoheterojunctions show atomically abrupt interfaces for ZnO/WO2.9 and Zn2SnO4/WO2.9, despite lattice mismatches. Separately, co-axial nanoheterostructures are fabricated using ionic-liquid solutions, where single-crystal nanoscale Al layer are electrodeposited on the surfaces of the above flame-synthesized WO2.9 nanowires. These tungsten-oxide/aluminum coaxial nanowire arrays constitute thermite
Computational Fluid-Particle Dynamics for the Flame Synthesis of Alumina Particles
DEFF Research Database (Denmark)
Johannessen, Tue; Pratsinis, Sotirie E.; Livbjerg, Hans
2000-01-01
A mathematical model for the dynamics of particle growth during synthesis of ultra fine particles in diffusion flames is presented. The model includes the kinetics of particle coalescence and coagulation, and when combined with a calculation of the temperature, velocity and gas composition...... distribution in the flame, the effuent aerosol characteristics are calculated. The model is validated by comparison with an experimental study of the synthesis of alumina particles by combustion of Al-tri-sec-butoxide. Two parameters of the coalescence kinetics are estimated by regression of the model...
Simulation and analysis of the soot particle size distribution in a turbulent nonpremixed flame
Lucchesi, Marco
2017-02-05
A modeling framework based on Direct Simulation Monte Carlo (DSMC) is employed to simulate the evolution of the soot particle size distribution in turbulent sooting flames. The stochastic reactor describes the evolution of soot in fluid parcels following Lagrangian trajectories in a turbulent flow field. The trajectories are sampled from a Direct Numerical Simulation (DNS) of a n-heptane turbulent nonpremixed flame. The DSMC method is validated against experimentally measured size distributions in laminar premixed flames and found to reproduce quantitatively the experimental results, including the appearance of the second mode at large aggregate sizes and the presence of a trough at mobility diameters in the range 3–8 nm. The model is then applied to the simulation of soot formation and growth in simplified configurations featuring a constant concentration of soot precursors and the evolution of the size distribution in time is found to depend on the intensity of the nucleation rate. Higher nucleation rates lead to a higher peak in number density and to the size distribution attaining its second mode sooner. The ensemble-averaged PSDF in the turbulent flame is computed from individual samples of the PSDF from large sets of Lagrangian trajectories. This statistical measure is equivalent to time-averaged, scanning mobility particle size (SMPS) measurements in turbulent flames. Although individual trajectories display strong bimodality as in laminar flames, the ensemble-average PSDF possesses only one mode and a long, broad tail, which implies significant polydispersity induced by turbulence. Our results agree very well with SMPS measurements available in the literature. Conditioning on key features of the trajectory, such as mixture fraction or radial locations does not reduce the scatter in the size distributions and the ensemble-averaged PSDF remains broad. The results highlight and explain the important role of turbulence in broadening the size distribution of
42 Variability Bugs in the Linux Kernel
DEFF Research Database (Denmark)
Abal, Iago; Brabrand, Claus; Wasowski, Andrzej
2014-01-01
Feature-sensitive verification pursues effective analysis of the exponentially many variants of a program family. However, researchers lack examples of concrete bugs induced by variability, occurring in real large-scale systems. Such a collection of bugs is a requirement for goal-oriented research......, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 42 variability bugs collected from bug-fixing commits to the Linux kernel repository. We analyze each of the bugs, and record the results in a database. In addition, we...
40 Variability Bugs in the Linux Kernel
DEFF Research Database (Denmark)
Abal Rivas, Iago; Brabrand, Claus; Wasowski, Andrzej
2014-01-01
is a requirement for goal-oriented research, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 40 variability bugs collected from bug-fixing commits to the Linux kernel repository. We investigate each of the 40 bugs, recording......Feature-sensitive verification is a recent field that pursues the effective analysis of the exponential number of variants of a program family. Today researchers lack examples of concrete bugs induced by variability, and occurring in real large-scale software. Such a collection of bugs...
Application of RBAC Model in System Kernel
Directory of Open Access Journals (Sweden)
Guan Keqing
2012-11-01
Full Text Available In the process of development of some technologies about Ubiquitous computing, the application of embedded intelligent devices is booming. Meanwhile, information security will face more serious threats than before. To improve the security of information terminal’s operation system, this paper analyzed the threats to system’s information security which comes from the abnormal operation by processes, and applied RBAC model into the safety management mechanism of operation system’s kernel. We built an access control model of system’s process, and proposed an implement framework. And the methods of implementation of the model for operation systems were illustrated.
SVM multiuser detection based on heuristic kernel
Institute of Scientific and Technical Information of China (English)
Yang Tao; Hu Bo
2007-01-01
A support vector machine (SVM) based multiuser detection (MUD) scheme in code-division multiple-access (CDMA) system is proposed. In this scheme, the equivalent support vector (SV) is obtained through a kernel sparsity approximation algorithm, which avoids the conventional costly quadratic programming (QP) procedure in SVM. Besides, the coefficient of the SV is attained through the solution to a generalized eigenproblem. Simulation results show that the proposed scheme has almost the same bit error rate (BER) as the standard SVM and is better than minimum mean square error (MMSE) scheme. Meanwhile, it has a low computation complexity.
Characterization of Flour from Avocado Seed Kernel
Macey A. Mahawan; Ma. Francia N. Tenorio; Jaycel A. Gomez; Rosenda A. Bronce
2015-01-01
The study focused on the Characterization of Flour from Avocado Seed Kernel. Based on the findings of the study the percentages of crude protein, crude fiber, crude fat, total carbohydrates, ash and moisture were 7.75, 4.91, 0.71, 74.65, 2.83 and 14.05 respectively. On the other hand the falling number was 495 seconds while gluten was below the detection limit of the method used. Moreover, the sensory evaluation in terms of color, texture and aroma in 0% proportion of Avocado seed flour was m...
Fixed kernel regression for voltammogram feature extraction
Acevedo Rodriguez, F. J.; López-Sastre, R. J.; Gil-Jiménez, P.; Ruiz-Reyes, N.; Maldonado Bascón, S.
2009-12-01
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.
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...
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...
Effect of Dimethyl Ether Mixing on Soot Size Distribution in Premixed Ethylene Flame
Li, Zepeng
2016-04-21
As a byproduct of incomplete combustion, soot attracts increasing attentions as extensive researches exploring serious health and environmental effects from soot particles. Soot emission reduction requires a comprehensive understanding of the mechanism for polycyclic aromatic hydrocarbons and of soot formation and aging processes. Therefore, advanced experimental techniques and numerical simulations have been conducted to investigate this procedure. In order to investigate the effects of dimethyl ether (DME) mixing on soot particle size distribution functions (PSDFs), DME was mixed in premixed ethylene/oxygen/argon at flames at the equivalence ratio of 2.0 with a range of mixing ratio from 0% to 30% of the total carbon fed. Two series of atmospheric pressure flames were tested in which cold gas velocity was varied to obtain different flame temperatures. The evolution of PSDFs along the centerline of the flame was determined by burner stabilized stagnation probe and scanning mobility particle sizer (SMPS) techniques, yielding the PSDFs for various separation distances above the burner surface. Meanwhile, the flame temperature profiles were carefully measured by a thermocouple and the comparison to that of simulated laminar premixed burner-stabilized stagnation flame was satisfactory. Additionally, to understand the chemical role of DME mixing in soot properties, characterization measurements were conducted on soot samples using thermo-gravimetric analysis (TGA) and elemental analysis (EA). Results of the evolution of PSDFs and soot volume fraction showed that adding DME into ethylene flame could reduce soot yield significantly. The addition of DME led to the decrease of both the soot nucleation rate and the particle mass growth rate. To explain the possible mechanism for the observation, numerical simulations were performed. Although DME addition resulted in the slight increase of methyl radicals from pyrolysis, the decrease in acetylene and propargyl radicals
Theory of DDT in unconfined flames
Khokhlov, A M; Wheeler, J C; Wheeler, J Craig
1996-01-01
This paper outlines a theoretical approach for predicting the onset of detonation in unconfined turbulent flames which is relevant both to problems of terrestrial combustion and to thermonuclear burning in Type Ia supernovae. Two basic assumuptions are made: 1) the gradient mechanism is the inherent mechanism that leads to DDT in unconfined conditions, and 2) the sole mechanism for preparing the gradient in induction time is by turbulent mixing and local flame quenching. The criterion for DDT is derived in terms of the one-dimensional detonation wave thickness, the laminar flame speed, and the laminar flame thickness in the reactive gas. This approach gives a lower-bound criterion for DDT for conditions where shock preheating, wall effects, and interactions with obstacles are absent. Regions in parameter space where unconfined DDT can and cannot occur are determined. A subsequent paper will address these issues specifically in the astrophysical context.
A Century of Sapphire Crystal Growth
2004-05-17
Crystal growth storage cabinet from Frémy’s lab.5,6 Flame Fusion and the Verneuil Process In 1885 rubies selling for $1000-2500...1891: Working with his student, M. Pacquier, Verneuil had developed most of what we now call Verneuil flame-fusion crystal growth . Verneuil ... Verneuil ) Crystal Growth Nassau, Gems Made by Man 11 • 1892: Verneuil eliminated crystal cracking by making contact area between ruby crystal
Institute of Scientific and Technical Information of China (English)
Kane
2003-01-01
Flaming Pear是个一直给我留下深刻印象的软件开发公司。我以前评论过很多这个公司的插件，每一次都是不错的经历。同样的优良传统同样体现在Flaming Pear的新品Creative Pack1.0
Abdelgadir, Ahmed
2015-03-30
A set of coflow diffusion flames are simulated to study the formation, growth, and oxidation of soot in flames of diluted hydrocarbon fuels, with focus on the effects of pressure. Firstly, we assess the ability of a high performance CFD solver, coupled with detailed transport and kinetic models, to reproduce experimental measurements of a series of ethylene-air coflow flames. Detailed finite rate chemistry describing the formation of Polycyclic Aromatic Hydro-carbons is used. Soot is modeled with a moment method and the resulting moment transport equations are solved with a Lagrangian numerical scheme. Numerical and experimental results are compared for various pressures. Finally, a sensitivity study is performed assessing the effect of the boundary conditions and kinetic mechanisms on the flame structure and stabilization properties.
Kernel learning at the first level of inference.
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.
Dynamics of flow-soot interaction in wrinkled non-premixed ethylene-air flames
Arias, Paul G.; Lecoustre, Vivien R.; Roy, Somesh; Luo, Zhaoyu; Haworth, Daniel C.; Lu, Tianfeng; Trouvé, Arnaud; Im, Hong G.
2015-09-01
A two-dimensional simulation of a non-premixed ethylene-air flame was conducted by employing a detailed gas-phase reaction mechanism considering polycyclic aromatic hydrocarbons, an aerosol-dynamics-based soot model using a method of moments with interpolative closure, and a grey gas and soot radiation model using the discrete transfer method. Interaction of the sooting flame with a prescribed decaying random velocity field was investigated, with a primary interest in the effects of velocity fluctuations on the flame structure and the associated soot formation process for a fuel-strip configuration and a composition with mature soot growth. The temporally evolving simulation revealed a multi-layered soot formation process within the flame, at a level of detail not properly described by previous studies based on simplified soot models utilizing acetylene or naphthalene precursors for initial soot inception. The overall effect of the flame topology on the soot formation was found to be consistent with previous experimental studies, while a unique behaviour of localised strong oxidation was also noted. The imposed velocity fluctuations led to an increase of the scalar dissipation rate in the sooting zone, causing a net suppression in the soot production rate. Considering the complex structure of the soot formation layer, the effects of the imposed fluctuations vary depending on the individual soot reactions. For the conditions under study, the soot oxidation reaction was identified as the most sensitive to the fluctuations and was mainly responsible for the local suppression of the net soot production.
Aromatics oxidation and soot formation in flames. Progress report, August 15, 1990--August 14, 1993
Energy Technology Data Exchange (ETDEWEB)
Howard, J.B.; Pope, C.J.; Shandross, R.A.; Yadav, T.
1993-04-01
This project is concerned with the kinetics and mechanisms of aromatics oxidation and soot and fullerenes formation in flames. The scope includes detailed measurements of profiles of stable and radical species concentrations in low-pressure one-dimensional premixed flames. Intermediate species identifications and mole fractions, fluxes, and net reaction rates calculated from the measured profiles are used to test postulated reaction mechanisms. Particular objectives are to identify, and to confirm or determine rate constants for, the main benzene oxidation reactions in flames, and to characterize soot and fullerenes and their formation mechanisms and kinetics. Stable and radical species profiles in the aromatics oxidation study are measured using molecular beam sampling with on-line mass spectrometry. The rate of soot formation measured by conventional optical techniques is found to support the hypotheses that particle inception occurs through reactive coagulation of high molecular weight PAH in competition with destruction by OHattack, and that the subsequent growth of the soot mass occurs through addition reactions of PAH and C{sub 2}H{sub 2} with the soot particles. During the first year of this reporting period, fullerenes C{sub 60} and C{sub 70} in substantial quantities were found in the flames being studied. The fullerenes were recovered, purified and spectroscopically identified. The yields of C{sub 60} and C{sub 70} were then determined over ranges of conditions in low-pressure premixed flames of benzene and oxygen.
Soot Formation in Laminar Premixed Methane/Oxygen Flames at Atmospheric Pressure
Xu, F.; Lin, K.-C.; Faeth, G. M.
1998-01-01
Flame structure and soot formation were studied within soot-containing laminar premixed mc1hane/oxygen flames at atmospheric pressure. The following measurements were made: soot volume fractions by laser extinction, soot temperatures by multiline emission, gas temperatures (where soot was absent) by corrected fine-wire thermocouples, soot structure by thermophoretic sampling and transmission electron microscope (TEM), major gas species concentrations by sampling and gas chromatography, and gas velocities by laser velocimetry. Present measurements of gas species concentrations were in reasonably good agreement with earlier measurements due to Ramer et al. as well as predictions based on the detailed mechanisms of Frenklach and co-workers and Leung and Lindstedt: the predictions also suggest that H atom concentrations are in local thermodynamic equilibrium throughout the soot formation region. Using this information, it was found that measured soot surface growth rates could be correlated successfully by predictions based on the hydrogen-abstraction/carbon-addition (HACA) mechanisms of both Frenklach and co-workers and Colket and Hall, extending an earlier assessment of these mechanisms for premixed ethylene/air flames to conditions having larger H/C ratios and acetylene concentrations. Measured primary soot particle nucleation rates were somewhat lower than the earlier observations for laminar premixed ethylene/air flames and were significantly lower than corresponding rates in laminar diffusion flames. for reasons that still must be explained.
Soot Formation in Laminar Premixed Methane/Oxygen Flames at Atmospheric Pressure. Appendix H
Xu, F.; Lin, K.-C.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)
2001-01-01
Flame structure and soot formation were studied within soot-containing laminar premixed methanefoxygen flames at atmospheric pressure. The following measurements were made: soot volume fractions by laser extinction, soot temperatures by multiline emission, gas temperatures (where soot was absent) by corrected fine-wire thermocouples, soot structure by thermophoretic sampling and transmission electron microscope (TEM), major gas species concentrations by sampling and gas chromatography, and gas velocities by laser velocimetry. Present measurements of gas species concentrations were in reasonably good agreement with earlier measurements due to Ramer et al. as well as predictions based on the detailed mechanisms of Frenklach and co-workers and Leung and Lindstedt; the predictions also suggest that H atom concentrations are in local thermodynamic equilibrium throughout the soot formation region. Using this information, it was found that measured soot surface growth rates could be correlated successfully by predictions based on the hydrogenabstraction/carbon-addition (HACA) mechanisms of both Frenklach and co-workers and Colket and Hall, extending an earlier assessment of these mechanisms for premixed ethylene/air flames to conditions having larger H/C ratios and acetylene concentrations. Measured primary soot particle nucleation rates were somewhat lower than the earlier observations for laminar premixed ethylene/air flames and were significantly lower than corresponding rates in laminar diffusion flames, for reasons that still must be explained.
NO concentration imaging in turbulent nonpremixed flames
Energy Technology Data Exchange (ETDEWEB)
Schefer, R.W. [Sandia National Laboratories, Livermore, CA (United States)
1993-12-01
The importance of NO as a pollutant species is well known. An understanding of the formation characteristics of NO in turbulent hydrocarbon flames is important to both the desired reduction of pollutant emissions and the validation of proposed models for turbulent reacting flows. Of particular interest is the relationship between NO formation and the local flame zone, in which the fuel is oxidized and primary heat release occurs. Planar imaging of NO provides the multipoint statistics needed to relate NO formation to the both the flame zone and the local turbulence characteristics. Planar imaging of NO has been demonstrated in turbulent flames where NO was seeded into the flow at high concentrations (2000 ppm) to determine the gas temperature distribution. The NO concentrations in these experiments were significantly higher than those expected in typical hydrocarbon-air flames, which require a much lower detectability limit for NO measurements. An imaging technique based on laser-induced fluorescence with sufficient sensitivity to study the NO formation mechanism in the stabilization region of turbulent lifted-jet methane flames.
Synthesis of Nano-Particles in Flames
DEFF Research Database (Denmark)
Johannessen, Tue
The scope of this work is to investigate the synthesis of aluminum oxide particles in flames from the combustion of an aluminum alkoxide precursor.A general introduction to particles formation in the gas phase is presented with emphasis on the mechanisms that control the particle morphology after...... for the analysis of particle formation in flames. Good results for a wide range of operating conditions were obtained. Therefore, the method should be useful as a tool for the optimization and/or design of flame processes for particle production.......The scope of this work is to investigate the synthesis of aluminum oxide particles in flames from the combustion of an aluminum alkoxide precursor.A general introduction to particles formation in the gas phase is presented with emphasis on the mechanisms that control the particle morphology after...... flame burner and a premixed burner with a precursor jet. The experimental setups and results are shown and discussed in detail. Alumina powder with specific surface area between 45 m2/g and 190 m2/g was obtained.Temperature and flow fields of the flame processes are analysed by numerical simulations...
Conical quarl swirl stabilized non-premixed flames: flame and flow field interaction
Elbaz, Ayman M.
2017-09-19
The flame-flow field interaction is studied in non-premixed methane swirl flames stabilized in quartz quarl via simultaneous measurements of the flow field using a stereo PIV and OH-PLIF at 5 KHz repetition rate. Under the same swirl intensity, two flames with different fuel jet velocity were investigated. The time-averaged flow field shows a unique flow pattern at the quarl exit, where two recirculation vortices are formed; a strong recirculation zone formed far from the quarl exit and a larger recirculation zone extending inside the quarl. However, the instantaneous images show that, the flow pattern near the quarl exit plays a vital role in the spatial location and structure of the reaction zone. In the low fuel jet velocity flame, a pair of vortical structures, located precisely at the corners of the quarl exit, cause the flame to roll up into the central region of low speed flow, where the flame sheet then tracks the axial velocity fluctuations. The vorticity field reveals a vortical structure surrounding the reaction zones, which reside on a layer of low compressive strain adjacent to that vortical structure. In the high fuel jet velocity flame, initially a laminar flame sheet resides at the inner shear layer of the main jet, along the interface between incoming fresh gas and high temperature recirculating gas. Further downstream, vortex breakdown alters the flame sheet path toward the central flame region. The lower reaction zones show good correlation to the regions of maximum vorticity and track the regions of low compressive strain associated with the inner shear layer of the jet flow. In both flames the reactions zones conform the passage of the large structure while remaining inside the low speed regions or at the inner shear layer.
Generalized Langevin equation with tempered memory kernel
Liemert, André; Sandev, Trifce; Kantz, Holger
2017-01-01
We study a generalized Langevin equation for a free particle in presence of a truncated power-law and Mittag-Leffler memory kernel. It is shown that in presence of truncation, the particle from subdiffusive behavior in the short time limit, turns to normal diffusion in the long time limit. The case of harmonic oscillator is considered as well, and the relaxation functions and the normalized displacement correlation function are represented in an exact form. By considering external time-dependent periodic force we obtain resonant behavior even in case of a free particle due to the influence of the environment on the particle movement. Additionally, the double-peak phenomenon in the imaginary part of the complex susceptibility is observed. It is obtained that the truncation parameter has a huge influence on the behavior of these quantities, and it is shown how the truncation parameter changes the critical frequencies. The normalized displacement correlation function for a fractional generalized Langevin equation is investigated as well. All the results are exact and given in terms of the three parameter Mittag-Leffler function and the Prabhakar generalized integral operator, which in the kernel contains a three parameter Mittag-Leffler function. Such kind of truncated Langevin equation motion can be of high relevance for the description of lateral diffusion of lipids and proteins in cell membranes.
Pareto-path multitask multiple kernel learning.
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.
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.
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.
Preparation of Flame Retardant Modified with Titanate for Asphalt Binder
Directory of Open Access Journals (Sweden)
Bo Li
2014-01-01
Full Text Available Improving the compatibility between flame retardant and asphalt is a difficult task due to the complex nature of the materials. This study explores a low dosage compound flame retardant and seeks to improve the compatibility between flame retardants and asphalt. An orthogonal experiment was designed taking magnesium hydroxide, ammonium polyphosphate, and melamine as factors. The oil absorption and activation index were tested to determine the effect of titanate on the flame retardant additive. The pavement performance test was conducted to evaluate the effect of the flame retardant additive. Oxygen index test was conducted to confirm the effect of flame retardant on flame ability of asphalt binder. The results of this study showed that the new composite flame retardant is more effective in improving the compatibility between flame retardant and asphalt and reducing the limiting oxygen index of asphalt binder tested in this study.
Gene discovery for improvement of kernel quality-related traits in maize
Directory of Open Access Journals (Sweden)
Motto M.
2010-01-01
Full Text Available Developing maize plants with improved kernel quality traits involves the ability to use existing genetic variation and to identify and manipulate commercially important genes. This will open avenues for designing novel variation in grain composition and will provide the basis for the development of the next generation of specialty maize. This paper provides an overview of current knowledge on the identification and exploitation of genes affecting the composition, development, and structure of the maize kernel with particular emphasis on pathways relevant to endosperm growth and development, differentiation of starch-filled cells, and biosynthesis of starches, storage proteins, lipids, and carotenoids. The potential that the new technologies of cell and molecular biology will provide for the creation of new variation in the future are also indicated and discussed.
Energy Technology Data Exchange (ETDEWEB)
Kearney, Sean P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guildenbecher, Daniel Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Winters, Caroline [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Farias, Paul Abraham [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grasser, Thomas W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hewson, John C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-09-01
We present a detailed set of measurements from a piloted, sooting, turbulent C _{2} H _{4 }- fueled diffusion flame. Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (CARS) is used to monitor temperature and oxygen, while laser-induced incandescence (LII) is applied for imaging of the soot volume fraction in the challenging jet-flame environment at Reynolds number, Re = 20,000. Single-laser shot results are used to map the mean and rms statistics, as well as probability densities. LII data from the soot-growth region of the flame are used to benchmark the soot source term for one-dimensional turbulence (ODT) modeling of this turbulent flame. The ODT code is then used to predict temperature and oxygen fluctuations higher in the soot oxidation region higher in the flame.
Scheduler Activations on BSD: Sharing Thread Management Between Kernel and Application
Small, Christopher A.; Seltzer, Margo I.
1995-01-01
There are two commonly used thread models: kernel level threads and user level threads. Kernel level threads suffer from the cost of frequent user-kernel domain crossings and fixed kernel scheduling priorities. User level threads are not integrated with the kernel, blocking all threads whenever one thread is blocked. The Scheduler Activations model, proposed by Anderson et al. [ANDE91], combines kernel CPU al location decisions with application control over thread scheduling. This paper discu...
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...
THE COLLOCATION METHODS FOR SINGULAR INTEGRAL EQUATIONS WITH CAUCHY KERNELS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
This paper applies the singular integral operators,singular quadrature operators and discretization matrices associated withsingular integral equations with Cauchy kernels, which are established in [1],to give a unified framework for various collocation methods of numericalsolutions of singular integral equations with Cauchy kernels. Under theframework, the coincidence of the direct quadrature method and the indirectquadrature method is very simple and obvious.
Extracting Feature Model Changes from the Linux Kernel Using FMDiff
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 ex
KERNEL IDEALS AND CONGRUENCES ON MS-ALGEBRAS
Institute of Scientific and Technical Information of China (English)
Luo Congwen; Zeng Yanlu
2006-01-01
In this article, the authors describe the largest congruence induced by a kernel ideal of an MS-algebra and characterize those MS-algebras on which all the congruences are in a one-to-one correspondence with the kernel ideals.
Integral Transform Methods: A Critical Review of Various Kernels
Orlandini, Giuseppina; Turro, Francesco
2017-03-01
Some general remarks about integral transform approaches to response functions are made. Their advantage for calculating cross sections at energies in the continuum is stressed. In particular we discuss the class of kernels that allow calculations of the transform by matrix diagonalization. A particular set of such kernels, namely the wavelets, is tested in a model study.
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.
Integrating the Gradient of the Thin Wire Kernel
Champagne, Nathan J.; Wilton, Donald R.
2008-01-01
A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form
ON APPROXIMATION BY SPHERICAL REPRODUCING KERNEL HILBERT SPACES
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The spherical approximation between two nested reproducing kernels Hilbert spaces generated from different smooth kernels is investigated. It is shown that the functions of a space can be approximated by that of the subspace with better smoothness. Furthermore, the upper bound of approximation error is given.
End-use quality of soft kernel durum wheat
Kernel texture is a major determinant of end-use quality of wheat. Durum wheat is known for its very hard texture, which influences how it is milled and for what products it is well suited. We developed soft kernel durum wheat lines via Ph1b-mediated homoeologous recombination with Dr. Leonard Joppa...
Optimal Bandwidth Selection in Observed-Score Kernel Equating
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…
Comparison of Kernel Equating and Item Response Theory Equating Methods
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…
Integral transform methods: a critical review of various kernels
Orlandini, Giuseppina
2016-01-01
Some general remarks about integral transform approaches to response functions are made. Their advantage for calculating cross sections at energies in the continuum is stressed. In particular we discuss the class of kernels that allow calculations of the transform by matrix diagonalization. A particular set of such kernels, namely the wavelets, is tested in a model study.
Indigenous Methods in Preserving Bush Mango Kernels in Cameroon
Directory of Open Access Journals (Sweden)
Zac Tchoundjeu
2005-01-01
Full Text Available Traditional practices for preserving Irvingia wombolu and Irvingia gabonensis (bush mango kernels were assessed in a survey covering twelve villages (Dongo, Bouno, Gribi [East], Elig-Nkouma, Nkom I, Ngoumou [Centre], Bidjap, Nko’ovos, Ondodo [South], Besong-Abang, Ossing and Kembong [Southwest], in the humid lowland forest zone of Cameroon. All the interviewed households that own trees of species were found to preserve kernels in periods of abundance, excluding Elig-Nkouma (87.5%. Eighty nine and 85% did so in periods of scarcity for I. wombolu and I. gabonensis respectively. Seventeen and twenty-nine kernel preservation practices were recorded for I. wombolu and I. gabonensis respectively. Most were based on continuous heating of the kernels or kernel by-products (cakes. The most commonly involved keeping the sun-dried kernels in a plastic bag on a bamboo rack hung above the fireplace in the kitchen. A 78% of interviews households reported preserving I. wombolu kernels for less than one year while 22% preserved it for more than one year with 1.9% for two years, the normal length of the off-season period for trees in the wild. Cakes wrapped with leaves and kept on a bamboo rack hung over the fireplace were reported by households in the East and South provinces to store Irvingia gabonensis longer (more than one year. Further studies on the utilization of heat for preserving and canning bush mango kernels are recommended.
THE HEAT KERNEL ON THE CAYLEY HEISENBERG GROUP
Institute of Scientific and Technical Information of China (English)
Luan Jingwen; Zhu Fuliu
2005-01-01
The authors obtain an explicit expression of the heat kernel for the Cayley Heisenberg group of order n by using the stochastic integral method of Gaveau. Apart from the standard Heisenberg group and the quaternionic Heisenberg group, this is the only nilpotent Lie group on which an explicit formula for the heat kernel has been obtained.
Oven-drying reduces ruminal starch degradation in maize kernels
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 (consist
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...
Efficient Kernel-based 2DPCA for Smile Stages Recognition
Directory of Open Access Journals (Sweden)
Fitri Damayanti
2012-03-01
Full Text Available Recently, an approach called two-dimensional principal component analysis (2DPCA has been proposed for smile stages representation and recognition. The essence of 2DPCA is that it computes the eigenvectors of the so-called image covariance matrix without matrix-to-vector conversion so the size of the image covariance matrix are much smaller, easier to evaluate covariance matrix, computation cost is reduced and the performance is also improved than traditional PCA. In an effort to improve and perfect the performance of smile stages recognition, in this paper, we propose efficient Kernel based 2DPCA concepts. The Kernelization of 2DPCA can be benefit to develop the nonlinear structures in the input data. This paper discusses comparison of standard Kernel based 2DPCA and efficient Kernel based 2DPCA for smile stages recognition. The results of experiments show that Kernel based 2DPCA achieve better performance in comparison with the other approaches. While the use of efficient Kernel based 2DPCA can speed up the training procedure of standard Kernel based 2DPCA thus the algorithm can achieve much more computational efficiency and remarkably save the memory consuming compared to the standard Kernel based 2DPCA.
Kernel maximum autocorrelation factor and minimum noise fraction transformations
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2010-01-01
) dimensional feature space via the kernel function and then performing a linear analysis in that space. Three examples show the very successful application of kernel MAF/MNF analysis to 1) change detection in DLR 3K camera data recorded 0.7 seconds apart over a busy motorway, 2) change detection...
Oven-drying reduces ruminal starch degradation in maize kernels
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
Lp-boundedness of flag kernels on homogeneous groups
Glowacki, Pawel
2010-01-01
We prove that the flag kernel singular integral operators of Nagel-Ricci-Stein on a homogeneous group are bounded on the Lp spaces. The gradation associated with the kernels is the natural gradation of the underlying Lie algebra. Our main tools are the Littlewood-Paley theory and a symbolic calculus combined in the spirit of Duoandikoetxea and Rubio de Francia.
Extracting Feature Model Changes from the Linux Kernel Using FMDiff
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
Gaussian kernel operators on white noise functional spaces
Institute of Scientific and Technical Information of China (English)
骆顺龙; 严加安
2000-01-01
The Gaussian kernel operators on white noise functional spaces, including second quantization, Fourier-Mehler transform, scaling, renormalization, etc. are studied by means of symbol calculus, and characterized by the intertwining relations with annihilation and creation operators. The infinitesimal generators of the Gaussian kernel operators are second order white noise operators of which the number operator and the Gross Laplacian are particular examples.
Evolutionary optimization of kernel weights improves protein complex comembership prediction.
Hulsman, Marc; Reinders, Marcel J T; de Ridder, Dick
2009-01-01
In recent years, more and more high-throughput data sources useful for protein complex prediction have become available (e.g., gene sequence, mRNA expression, and interactions). The integration of these different data sources can be challenging. Recently, it has been recognized that kernel-based classifiers are well suited for this task. However, the different kernels (data sources) are often combined using equal weights. Although several methods have been developed to optimize kernel weights, no large-scale example of an improvement in classifier performance has been shown yet. In this work, we employ an evolutionary algorithm to determine weights for a larger set of kernels by optimizing a criterion based on the area under the ROC curve. We show that setting the right kernel weights can indeed improve performance. We compare this to the existing kernel weight optimization methods (i.e., (regularized) optimization of the SVM criterion or aligning the kernel with an ideal kernel) and find that these do not result in a significant performance improvement and can even cause a decrease in performance. Results also show that an expert approach of assigning high weights to features with high individual performance is not necessarily the best strategy.
Visualization of nonlinear kernel models in neuroimaging by sensitivity maps
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Lund, Torben Ellegaard
2011-01-01
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......, and conclude that the sensitivity map is a versatile and computationally efficient tool for visualization of nonlinear kernel models in neuroimaging....
Autoignition and flame stabilisation processes in turbulent non-premixed hot coflow flames
Oldenhof , E.
2012-01-01
This dissertation examines stabilisation processes in turbulent non-premixed jet flames, created by injecting gaseous fuel into a co-flowing stream of hot, low-oxygen combustion products. Being able to predict whether and how a flame achieves stable and reliable combustion is a matter of great pract
On the dynamics of flame edges in diffusion-flame/vortex interactions
Energy Technology Data Exchange (ETDEWEB)
Hermanns, Miguel; Linan, Amable [Departamento de Motopropulsion y Termofluidodinamica, Universidad Politecnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid (Spain); Vera, Marcos [Area de Mecanica de Fluidos, Universidad Carlos III de Madrid, 28911 Leganes (Spain)
2007-04-15
We analyze the local flame extinction and reignition of a counterflow diffusion flame perturbed by a laminar vortex ring. Local flame extinction leads to the appearance of flame edges separating the burning and extinguished regions of the distorted mixing layer. The dynamics of these edges is modeled based on previous numerical results, with heat release effects fully taken into account, which provide the propagation velocity of triple and edge flames in terms of the upstream unperturbed value of the scalar dissipation. The temporal evolution of the mixing layer is determined using the classical mixture fraction approach, with both unsteady and curvature effects taken into account. Although variable density effects play an important role in exothermic reacting mixing layers, in this paper the description of the mixing layer is carried out using the constant density approximation, leading to a simplified analytical description of the flow field. The mathematical model reveals the relevant nondimensional parameters governing diffusion-flame/vortex interactions and provides the parameter range for the more relevant regime of local flame extinction followed by reignition via flame edges. Despite the simplicity of the model, the results show very good agreement with previously published experimental results. (author)
Methane Formation by Flame-Generated Hydrogen Atoms in the Flame Ionization Detector
DEFF Research Database (Denmark)
Holm, Torkil; Madsen, Jørgen Øgaard
1996-01-01
The precombustion degradation of organic compounds in the flame ionization detector has been studied (1) by heating the additives in hydrogen in a quartz capillary and analyzing the reaction products by GC and (2) by following the degradation of the additives in a hydrogen flame, by means of a th...
Modeling Candle Flame Behavior In Variable Gravity
Alsairafi, A.; Tien, J. S.; Lee, S. T.; Dietrich, D. L.; Ross, H. D.
2003-01-01
The burning of a candle, as typical non-propagating diffusion flame, has been used by a number of researchers to study the effects of electric fields on flame, spontaneous flame oscillation and flickering phenomena, and flame extinction. In normal gravity, the heat released from combustion creates buoyant convection that draws oxygen into the flame. The strength of the buoyant flow depends on the gravitational level and it is expected that the flame shape, size and candle burning rate will vary with gravity. Experimentally, there exist studies of candle burning in enhanced gravity (i.e. higher than normal earth gravity, g(sub e)), and in microgravity in drop towers and space-based facilities. There are, however, no reported experimental data on candle burning in partial gravity (g model of the candle flame, buoyant forces were neglected. The treatment of momentum equation was simplified using a potential flow approximation. Although the predicted flame characteristics agreed well with the experimental results, the model cannot be extended to cases with buoyant flows. In addition, because of the use of potential flow, no-slip boundary condition is not satisfied on the wick surface. So there is some uncertainty on the accuracy of the predicted flow field. In the present modeling effort, the full Navier-Stokes momentum equations with body force term is included. This enables us to study the effect of gravity on candle flames (with zero gravity as the limiting case). In addition, we consider radiation effects in more detail by solving the radiation transfer equation. In the previous study, flame radiation is treated as a simple loss term in the energy equation. Emphasis of the present model is on the gas-phase processes. Therefore, the detailed heat and mass transfer phenomena inside the porous wick are not treated. Instead, it is assumed that a thin layer of liquid fuel coated the entire wick surface during the burning process. This is the limiting case that the mass
On the formation and early evolution of soot in turbulent nonpremixed flames
Bisetti, Fabrizio
2012-01-01
A Direct Numerical Simulation (DNS) of soot formation in an n-heptane/air turbulent nonpremixed flame has been performed to investigate unsteady strain effects on soot growth and transport. For the first time in a DNS of turbulent combustion, Polycyclic Aromatic Hydrocarbons (PAH) are included via a validated, reduced chemical mechanism. A novel statistical representation of soot aggregates based on the Hybrid Method of Moments is used [M.E. Mueller, G. Blanquart, H. Pitsch, Combust. Flame 156 (2009) 1143-1155], which allows for an accurate state-of-the-art description of soot number density, volume fraction, and morphology of the aggregates. In agreement with previous experimental studies in laminar flames, Damköhler number effects are found to be significant for PAH. Soot nucleation and growth from PAH are locally inhibited by high scalar dissipation rate, thus providing a possible explanation for the experimentally observed reduction of soot yields at increasing levels of mixing in turbulent sooting flames. Furthermore, our data indicate that soot growth models that rely on smaller hydrocarbon species such as acetylene as a proxy for large PAH molecules ignore or misrepresent the effects of turbulent mixing and hydrodynamic strain on soot formation due to differences in the species Damköhler number. Upon formation on the rich side of the flame, soot is displaced relative to curved mixture fraction iso-surfaces due to differential diffusion effects between soot and the gas-phase. Soot traveling towards the flame is oxidized, and aggregates displaced away from the flame grow primarily by condensation of PAH on the particle surface. In contrast to previous DNS studies based on simplified soot and chemistry models, surface reactions are found to contribute barely to the growth of soot, for nucleation and condensation processes occurring in the fuel stream are responsible for the most of soot mass generation. Furthermore, the morphology of the soot aggregates is
Higher Order Kernels and Locally Affine LDDMM Registration
Sommer, Stefan; Darkner, Sune; Pennec, Xavier
2011-01-01
To achieve sparse description that allows intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. We accomplish this by introducing higher order kernels in the LDDMM registration framework. The kernels allow local description of affine transformations and subsequent compact description of non-translational movement and of the entire non-rigid deformation. This is obtained with a representation that contains directly interpretable information from both mathematical and modeling perspectives. We develop the mathematical construction behind the higher order kernels, we show the implications for sparse image registration and deformation description, and we provide examples of how the capacity of the kernels enables registration with a very low number of parameters. The capacity and interpretability of the kernels lead to natural modeling of articulated movement, and th...
Hypothesis testing using pairwise distances and associated kernels
Sejdinovic, Dino; Sriperumbudur, Bharath; Fukumizu, Kenji
2012-01-01
We provide a unifying framework linking two classes of statistics used in two-sample and independence testing: on the one hand, the energy distances and distance covariances from the statistics literature; on the other, distances between embeddings of distributions to reproducing kernel Hilbert spaces (RKHS), as established in machine learning. The equivalence holds when energy distances are computed with semimetrics of negative type, in which case a kernel may be defined such that the RKHS distance between distributions corresponds exactly to the energy distance. We determine the class of probability distributions for which kernels induced by semimetrics are characteristic (that is, for which embeddings of the distributions to an RKHS are injective). Finally, we investigate the performance of this family of kernels in two-sample and independence tests: we show in particular that the energy distance most commonly employed in statistics is just one member of a parametric family of kernels, and that other choic...
An iterative modified kernel based on training data
Institute of Scientific and Technical Information of China (English)
Zhi-xiang ZHOU; Feng-qing HAN
2009-01-01
To improve performance of a support vector regression, a new method for a modified kernel function is proposed. In this method, information of all samples is included in the kernel function with conformal mapping. Thus the kernel function is data-dependent. With a random initial parameter, the kernel function is modified re-peatedly until a satisfactory result is achieved. Compared with the conventional model, the improved approach does not need to select parameters of the kernel function. Sim-ulation is carried out for the one-dimension continuous function and a case of strong earthquakes. The results show that the improved approach has better learning ability and forecasting precision than the traditional model. With the increase of the iteration number, the figure of merit decreases and converges. The speed of convergence depends on the parameters used in the algorithm.
Nonlinear Statistical Process Monitoring and Fault Detection Using Kernel ICA
Institute of Scientific and Technical Information of China (English)
ZHANG Xi; YAN Wei-wu; ZHAO Xu; SHAO Hui-he
2007-01-01
A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis (ICA) is proposed. The kernel ICA method is a two-phase algorithm: whitened kernel principal component (KPCA) plus ICA. KPCA spheres data and makes the data structure become as linearly separable as possible by virtue of an implicit nonlinear mapping determined by kernel. ICA seeks the projection directions in the KPCA whitened space, making the distribution of the projected data as non-gaussian as possible. The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed process monitoring method based on kernel ICA can effectively capture the nonlinear relationship in process variables. Its performance significantly outperforms monitoring method based on ICA or KPCA.
Anatomically-aided PET reconstruction using the kernel method
Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi
2016-09-01
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.
OSKI: A Library of Automatically Tuned Sparse Matrix Kernels
Energy Technology Data Exchange (ETDEWEB)
Vuduc, R; Demmel, J W; Yelick, K A
2005-07-19
The Optimized Sparse Kernel Interface (OSKI) is a collection of low-level primitives that provide automatically tuned computational kernels on sparse matrices, for use by solver libraries and applications. These kernels include sparse matrix-vector multiply and sparse triangular solve, among others. The primary aim of this interface is to hide the complex decision-making process needed to tune the performance of a kernel implementation for a particular user's sparse matrix and machine, while also exposing the steps and potentially non-trivial costs of tuning at run-time. This paper provides an overview of OSKI, which is based on our research on automatically tuned sparse kernels for modern cache-based superscalar machines.
OSKI: A library of automatically tuned sparse matrix kernels
Vuduc, Richard; Demmel, James W.; Yelick, Katherine A.
2005-01-01
The Optimized Sparse Kernel Interface (OSKI) is a collection of low-level primitives that provide automatically tuned computational kernels on sparse matrices, for use by solver libraries and applications. These kernels include sparse matrix-vector multiply and sparse triangular solve, among others. The primary aim of this interface is to hide the complex decisionmaking process needed to tune the performance of a kernel implementation for a particular user's sparse matrix and machine, while also exposing the steps and potentially non-trivial costs of tuning at run-time. This paper provides an overview of OSKI, which is based on our research on automatically tuned sparse kernels for modern cache-based superscalar machines.
CRKSPH - A Conservative Reproducing Kernel Smoothed Particle Hydrodynamics Scheme
Frontiere, Nicholas; Owen, J Michael
2016-01-01
We present a formulation of smoothed particle hydrodynamics (SPH) that employs a first-order consistent reproducing kernel function, exactly interpolating linear fields with particle tracers. Previous formulations using reproducing kernel (RK) interpolation have had difficulties maintaining conservation of momentum due to the fact the RK kernels are not, in general, spatially symmetric. Here, we utilize a reformulation of the fluid equations such that mass, momentum, and energy are all manifestly conserved without any assumption about kernel symmetries. Additionally, by exploiting the increased accuracy of the RK method's gradient, we formulate a simple limiter for the artificial viscosity that reduces the excess diffusion normally incurred by the ordinary SPH artificial viscosity. Collectively, we call our suite of modifications to the traditional SPH scheme Conservative Reproducing Kernel SPH, or CRKSPH. CRKSPH retains the benefits of traditional SPH methods (such as preserving Galilean invariance and manif...
A novel extended kernel recursive least squares algorithm.
Zhu, Pingping; Chen, Badong; Príncipe, José C
2012-08-01
In this paper, a novel extended kernel recursive least squares algorithm is proposed combining the kernel recursive least squares algorithm and the Kalman filter or its extensions to estimate or predict signals. Unlike the extended kernel recursive least squares (Ex-KRLS) algorithm proposed by Liu, the state model of our algorithm is still constructed in the original state space and the hidden state is estimated using the Kalman filter. The measurement model used in hidden state estimation is learned by the kernel recursive least squares algorithm (KRLS) in reproducing kernel Hilbert space (RKHS). The novel algorithm has more flexible state and noise models. We apply this algorithm to vehicle tracking and the nonlinear Rayleigh fading channel tracking, and compare the tracking performances with other existing algorithms.
Virtual screening with support vector machines and structure kernels
Mahé, Pierre
2007-01-01
Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classification or regression, and provide a flexible and computationally efficient framework to include relevant information and prior knowledge about the data and problems to be handled. In particular, with kernel methods molecules do not need to be represented and stored explicitly as vectors or fingerprints, but only to be compared to each other through a comparison function technically called a kernel. While classical kernels can be used to compare vector or fingerprint representations of molecules, completely new kernels were developed in the recent years to directly compare the 2D or 3D structures of molecules, without the need for an explicit vectorization step through the extraction of molecular descriptors. While still in their infancy, these approaches have already demonstrated their relevance on several toxicity prediction and s...
3-D waveform tomography sensitivity kernels for anisotropic media
Djebbi, R.
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.
Turbulence-flame interactions in DNS of a laboratory high Karlovitz premixed turbulent jet flame
Wang, Haiou; Hawkes, Evatt R.; Chen, Jacqueline H.
2016-09-01
In the present work, direct numerical simulation (DNS) of a laboratory premixed turbulent jet flame was performed to study turbulence-flame interactions. The turbulent flame features moderate Reynolds number and high Karlovitz number (Ka). The orientations of the flame normal vector n, the vorticity vector ω and the principal strain rate eigenvectors ei are examined. The in-plane and out-of-plane angles are introduced to quantify the vector orientations, which also measure the flame geometry and the vortical structures. A general observation is that the distributions of these angles are more isotropic downstream as the flame and the flow become more developed. The out-of-plane angle of the flame normal vector, β, is a key parameter in developing the correction of 2D measurements to estimate the corresponding 3D quantities. The DNS results show that the correction factor is unity at the inlet and approaches its theoretical value of an isotropic distribution downstream. The alignment characteristics of n, ω and ei, which reflect the interactions of turbulence and flame, are also studied. Similar to a passive scalar gradient in non-reacting flows, the flame normal has a tendency to align with the most compressive strain rate, e3, in the flame, indicating that turbulence contributes to the production of scalar gradient. The vorticity dynamics are examined via the vortex stretching term, which was found to be the predominant source of vorticity generation balanced by dissipation, in the enstrophy transport equation. It is found that although the vorticity preferentially aligns with the intermediate strain rate, e2, the contribution of the most extensive strain rate, e1, to vortex stretching is comparable with that of the intermediate strain rate, e2. This is because the eigenvalue of the most extensive strain rate, λ1, is always large and positive. It is confirmed that the vorticity vector is preferentially positioned along the flame tangential plane, contributing
Structure of Flame Balls at Low Lewis-Number
Weiland, Karen J.; Ronney, Paul
1998-01-01
The Structure of Flame Balls at Low Lewis-Number (SOFBALL) experiment explored the behavior of a newly discovered flame phenomena called "flame balls." These spherical, stable, stationary flame structures, observed only in microgravity, provide a unique opportunity to study the interactions of the two most important processes necessary for combustion (chemical reaction and heat and mass transport) in the simplest possible configuration. The previously unobtainable experimental data provided a comparison with models of flame stability and flame propagation limits that are crucial both in assessing fire safety and in designing efficient, clean-burning combustion engines.
Flame Quenching Dynamics of High Velocity Flames in Rectangular Cross-section Channels
Mahuthannan, Ariff Magdoom
2017-01-05
Understanding flame quenching for different conditions is necessary to develop safety devices like flame arrestors. In practical applications, the speed of a deflagration in the lab-fixed reference frame will be a strong function of the geometry through which the deflagration propagates. This study reports on the effect of the flame speed, at the entrance of a quenching section, on the quenching distance. A 2D rectangular channel joining two main spherical vessels is considered for studying this effect. Two different velocity regimes are investigated and referred to as configurations A, and B. For configuration A, the velocity of the flame is 20 m/s, while it is about 100 m/s for configuration B. Methane-air stoichiometric mixtures at 1 bar and 298 K are used. Simultaneous dynamic pressure measurements along with schlieren imaging are used to analyze the quenching of the flame. Risk assessment of re-ignition is also reported and analyzed.
Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.
Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan
2016-11-01
In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects.
Engineering Flame Retardant Biodegradable Nanocomposites
He, Shan; Yang, Kai; Guo, Yichen; Zhang, Linxi; Pack, Seongchan; Davis, Rachel; Lewin, Menahem; Ade, Harald; Korach, Chad; Kashiwagi, Takashi; Rafailovich, Miriam
2013-03-01
Cellulose-based PLA/PBAT polymer blends can potentially be a promising class of biodegradable nanocomposites. Adding cellulose fiber reinforcement can improve mechanical properties of biodegradable plastics, but homogeneously dispersing hydrophilic cellulose in the hydrophobic polymer matrix poses a significant challenge. We here show that resorcinol diphenyl phosphates (RDP) can be used to modify the surface energy, not only reducing phase separation between two polymer kinds but also allowing the cellulose particles and the Halloysite clay to be easily dispersed within polymer matrices to achieve synergy effect using melt blending. Here in this study we describe the use of cellulose fiber and Halloysite clay, coated with RDP surfactant, in producing the flame retardant polymer blends of PBAT(Ecoflex) and PLA which can pass the stringent UL-94 V0 test. We also utilized FTIR, SEM and AFM nanoindentation to elucidate the role RDP plays in improving the compatibility of biodegradable polymers, and to determine structure property of chars that resulted in composites that could have optimized mechanical and thermal properties. Supported by Garcia Polymer Center and NSF Foundation.
A, a Brominated Flame Retardant
Directory of Open Access Journals (Sweden)
Tomomi Takeshita
2013-01-01
Full Text Available Tetrabromobisphenol A (TBBPA, a brominated flame retardant, has been found to exacerbate pneumonia in respiratory syncytial virus- (RSV- infected mice. We examined the effect of Brazilian propolis (AF-08 on the exacerbation of RSV infection by TBBPA exposure in mice. Mice were fed a powdered diet mixed with 1% TBBPA alone, 0.02% AF-08 alone, or 1% TBBPA and 0.02% AF-08 for four weeks and then intranasally infected with RSV. TBBPA exposure increased the pulmonary virus titer and level of IFN-γ, a representative marker of pneumonia due to RSV infection, in the lungs of infected mice without toxicity. AF-08 was significantly effective in reducing the virus titers and IFN-γ level increased by TBBPA exposure. Also, AF-08 significantly reduced proinflammatory cytokine (TNF-α and IL-6 levels in the lungs of RSV-infected mice with TBBPA exposure, but Th2 cytokine (IL-4 and IL-10 levels were not evidently increased. Neither TBBPA exposure nor AF-08 treatment affected the anti-RSV antibody production in RSV-infected mice. In flow cytometry analysis, AF-08 seemed to be effective in reducing the ratio of pulmonary CD8a+ cells in RSV-infected mice with TBBPA exposure. TBBPA and AF-08 did not exhibit anti-RSV activity in vitro. Thus, AF-08 probably ameliorated pneumonia exacerbated by TBBPA exposure in RSV-infected mice by limiting excess cellular immune responses.
Pope, Benjamin; Hinkley, Sasha; Ireland, Michael J; Greenbaum, Alexandra; Latyshev, Alexey; Monnier, John D; Martinache, Frantz
2015-01-01
At present, the principal limitation on the resolution and contrast of astronomical imaging instruments comes from aberrations in the optical path, which may be imposed by the Earth's turbulent atmosphere or by variations in the alignment and shape of the telescope optics. These errors can be corrected physically, with active and adaptive optics, and in post-processing of the resulting image. A recently-developed adaptive optics post-processing technique, called kernel phase interferometry, uses linear combinations of phases that are self-calibrating with respect to small errors, with the goal of constructing observables that are robust against the residual optical aberrations in otherwise well-corrected imaging systems. Here we present a direct comparison between kernel phase and the more established competing techniques, aperture masking interferometry, point spread function (PSF) fitting and bispectral analysis. We resolve the alpha Ophiuchi binary system near periastron, using the Palomar 200-Inch Telesco...
Sooting turbulent jet flame: characterization and quantitative soot measurements
Köhler, M.; Geigle, K. P.; Meier, W.; Crosland, B. M.; Thomson, K. A.; Smallwood, G. J.
2011-08-01
Computational fluid dynamics (CFD) modelers require high-quality experimental data sets for validation of their numerical tools. Preferred features for numerical simulations of a sooting, turbulent test case flame are simplicity (no pilot flame), well-defined boundary conditions, and sufficient soot production. This paper proposes a non-premixed C2H4/air turbulent jet flame to fill this role and presents an extensive database for soot model validation. The sooting turbulent jet flame has a total visible flame length of approximately 400 mm and a fuel-jet Reynolds number of 10,000. The flame has a measured lift-off height of 26 mm which acts as a sensitive marker for CFD model validation, while this novel compiled experimental database of soot properties, temperature and velocity maps are useful for the validation of kinetic soot models and numerical flame simulations. Due to the relatively simple burner design which produces a flame with sufficient soot concentration while meeting modelers' needs with respect to boundary conditions and flame specifications as well as the present lack of a sooting "standard flame", this flame is suggested as a new reference turbulent sooting flame. The flame characterization presented here involved a variety of optical diagnostics including quantitative 2D laser-induced incandescence (2D-LII), shifted-vibrational coherent anti-Stokes Raman spectroscopy (SV-CARS), and particle image velocimetry (PIV). Producing an accurate and comprehensive characterization of a transient sooting flame was challenging and required optimization of these diagnostics. In this respect, we present the first simultaneous, instantaneous PIV, and LII measurements in a heavily sooting flame environment. Simultaneous soot and flow field measurements can provide new insights into the interaction between a turbulent vortex and flame chemistry, especially since soot structures in turbulent flames are known to be small and often treated in a statistical manner.
Institute of Scientific and Technical Information of China (English)
李玉玲; 王勇; 郭平峰; 伍国红; 骆强伟
2015-01-01
以火焰无核自交胚珠为试材，研究了红光、蓝光、白光及暗处理对胚发育、胚萌发及试管苗生长发育的影响。结果表明：3种光质处理对胚发育均有一定促进作用，但与对照未达到显著性水平。在胚萌发阶段，红光对胚萌发有明显的促进作用。在试管苗发育成苗阶段，以蓝光处理的试管苗最为矮壮，红光下葡萄胚挽救苗试管苗节间最长，发育最高，叶绿素含量最低；各处理试管苗继代后移栽成活率均可达到90%以上。%The open pollination ovules from flame Seedless were used to investigate the effect of diffierent light quality on the proportion of embryo development and germination ,and test-tube plantlets growth and development in vitro, including red light, blue light, white light and dark condition. The results showed that three lights had positive effect on embryo during ovule development, but did not significantly; Red light could promote obsively embryo germination; the plantlets were the most stocky under blue light. Red light was favorable to the longitudinal growth of the test-tube Plantlets, Chlorophyll content were the lowest. Each treatment plantlets transplant survival rate could reach 90%.
Heat kernel method and its applications
Avramidi, Ivan G
2015-01-01
The heart of the book is the development of a short-time asymptotic expansion for the heat kernel. This is explained in detail and explicit examples of some advanced calculations are given. In addition some advanced methods and extensions, including path integrals, jump diffusion and others are presented. The book consists of four parts: Analysis, Geometry, Perturbations and Applications. The first part shortly reviews of some background material and gives an introduction to PDEs. The second part is devoted to a short introduction to various aspects of differential geometry that will be needed later. The third part and heart of the book presents a systematic development of effective methods for various approximation schemes for parabolic differential equations. The last part is devoted to applications in financial mathematics, in particular, stochastic differential equations. Although this book is intended for advanced undergraduate or beginning graduate students in, it should also provide a useful reference ...
Image Processing Variations with Analytic Kernels
Garnett, John B; Vese, Luminita A
2012-01-01
Let $f\\in L^1(\\R^d)$ be real. The Rudin-Osher-Fatemi model is to minimize $\\|u\\|_{\\dot{BV}}+\\lambda\\|f-u\\|_{L^2}^2$, in which one thinks of $f$ as a given image, $\\lambda > 0$ as a "tuning parameter", $u$ as an optimal "cartoon" approximation to $f$, and $f-u$ as "noise" or "texture". Here we study variations of the R-O-F model having the form $\\inf_u\\{\\|u\\|_{\\dot{BV}}+\\lambda \\|K*(f-u)\\|_{L^p}^q\\}$ where $K$ is a real analytic kernel such as a Gaussian. For these functionals we characterize the minimizers $u$ and establish several of their properties, including especially their smoothness properties. In particular we prove that on any open set on which $u \\in W^{1,1}$ and $\
The Dynamical Kernel Scheduler - Part 1
Adelmann, Andreas; Suter, Andreas
2015-01-01
Emerging processor architectures such as GPUs and Intel MICs provide a huge performance potential for high performance computing. However developing software using these hardware accelerators introduces additional challenges for the developer such as exposing additional parallelism, dealing with different hardware designs and using multiple development frameworks in order to use devices from different vendors. The Dynamic Kernel Scheduler (DKS) is being developed in order to provide a software layer between host application and different hardware accelerators. DKS handles the communication between the host and device, schedules task execution, and provides a library of built-in algorithms. Algorithms available in the DKS library will be written in CUDA, OpenCL and OpenMP. Depending on the available hardware, the DKS can select the appropriate implementation of the algorithm. The first DKS version was created using CUDA for the Nvidia GPUs and OpenMP for Intel MIC. DKS was further integrated in OPAL (Object-or...
Online Learning of Noisy Data with Kernels
Cesa-Bianchi, Nicolò; Shamir, Ohad
2010-01-01
We study online learning when individual instances are corrupted by random noise. We assume the noise distribution is unknown, and may change over time with no restriction other than having zero mean and bounded variance. Our technique relies on a family of unbiased estimators for non-linear functions, which may be of independent interest. We show that a variant of online gradient descent can learn functions in any dot-product (e.g., polynomial) or Gaussian kernel space with any analytic convex loss function. Our variant uses randomized estimates that need to query a random number of noisy copies of each instance, where with high probability this number is upper bounded by a constant. Allowing such multiple queries cannot be avoided: Indeed, we show that online learning is in general impossible when only one noisy copy of each instance can be accessed.
Index-free Heat Kernel Coefficients
De van Ven, A E M
1998-01-01
Using index-free notation, we present the diagonal values of the first five heat kernel coefficients associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient appears here for the first time. For a flat space with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as required for the fourth coefficient. These results are obtained by directly solving the relevant recursion relations, working in Fock-Schwinger gauge and Riemann normal coordinates. Our procedure is thus noncovariant, but we show that for any coefficient the `gauged' respectively `curved' version is found from the corresponding `non-gauged' respectively `flat' coefficient by making some simple covariant substitutions. These substitutions being understood, the coefficients retain their `flat' form and size. In this sense the fift...
Kernel density estimation using graphical processing unit
Sunarko, Su'ud, Zaki
2015-09-01
Kernel density estimation for particles distributed over a 2-dimensional space is calculated using a single graphical processing unit (GTX 660Ti GPU) and CUDA-C language. Parallel calculations are done for particles having bivariate normal distribution and by assigning calculations for equally-spaced node points to each scalar processor in the GPU. The number of particles, blocks and threads are varied to identify favorable configuration. Comparisons are obtained by performing the same calculation using 1, 2 and 4 processors on a 3.0 GHz CPU using MPICH 2.0 routines. Speedups attained with the GPU are in the range of 88 to 349 times compared the multiprocessor CPU. Blocks of 128 threads are found to be the optimum configuration for this case.
Learning RoboCup-Keepaway with Kernels
Jung, Tobias
2012-01-01
We apply kernel-based methods to solve the difficult reinforcement learning problem of 3vs2 keepaway in RoboCup simulated soccer. Key challenges in keepaway are the high-dimensionality of the state space (rendering conventional discretization-based function approximation like tilecoding infeasible), the stochasticity due to noise and multiple learning agents needing to cooperate (meaning that the exact dynamics of the environment are unknown) and real-time learning (meaning that an efficient online implementation is required). We employ the general framework of approximate policy iteration with least-squares-based policy evaluation. As underlying function approximator we consider the family of regularization networks with subset of regressors approximation. The core of our proposed solution is an efficient recursive implementation with automatic supervised selection of relevant basis functions. Simulation results indicate that the behavior learned through our approach clearly outperforms the best results obta...
Heat kernel measures on random surfaces
Klevtsov, Semyon
2015-01-01
The heat kernel on the symmetric space of positive definite Hermitian matrices is used to endow the spaces of Bergman metrics of degree k on a Riemann surface M with a family of probability measures depending on a choice of the background metric. Under a certain matrix-metric correspondence, each positive definite Hermitian matrix corresponds to a Kahler metric on M. The one and two point functions of the random metric are calculated in a variety of limits as k and t tend to infinity. In the limit when the time t goes to infinity the fluctuations of the random metric around the background metric are the same as the fluctuations of random zeros of holomorphic sections. This is due to the fact that the random zeros form the boundary of the space of Bergman metrics.
Pattern Programmable Kernel Filter for Bot Detection
Directory of Open Access Journals (Sweden)
Kritika Govind
2012-05-01
Full Text Available Bots earn their unique name as they perform a wide variety of automated task. These tasks include stealing sensitive\tuser\tinformation. Detection of bots using solutions such as behavioral\tcorrelation of\tflow\trecords,\tgroup activity\tin DNS traffic, observing\tthe periodic repeatability in\tcommunication, etc., lead to monitoring\tthe network traffic\tand\tthen\tclassifying them as Bot or normal traffic.\tOther solutions for\tBot detection\tinclude kernel level key stroke verification, system call initialization,\tIP black listing, etc. In the first\ttwo solutions\tthere is no assurance\tthat\tthe\tpacket carrying user information is prevented from being sent to the attacker and the latter suffers from the problem of\tIP spoofing. This motivated\tus to think\tof a solution that would\tfilter\tout\tthe malicious\tpackets\tbefore being\tput onto\tthe network. To come out with such a\tsolution,\ta real time\tbot\tattack\twas\tgenerated with SpyEye Exploit kit and traffic\tcharacteristics were analyzed. The analysis revealed the existence\tof a unique repeated communication\tbetween\tthe Zombie machine\tand\tthe botmaster. This motivated us to propose, a Pattern\tProgrammable Kernel\tFilter (PPKF\tfor filtering out the malicious\tpackets generated by bots.\tPPKF was developed\tusing the\twindows\tfiltering platform (WFP filter engine.\tPPKF was programmed to\tfilter\tout\tthe\tpackets\twith\tunique pattern which were observed\tfrom\tthe\tbot\tattack experiments. Further\tPPKF was found\tto completely suppress the\tflow\tof packets having the programmed uniqueness in them thus preventing the functioning of bots in terms of user information being sent to the Botmaster.
Launch Pad Flame Trench Refractory Materials
Calle, Luz M.; Hintze, Paul E.; Parlier, Christopher R.; Bucherl, Cori; Sampson, Jeffrey W.; Curran, Jerome P.; Kolody, Mark; Perusich, Steve; Whitten, Mary
2010-01-01
The launch complexes at NASA's John F. Kennedy Space Center (KSC) are critical support facilities for the successful launch of space-based vehicles. These facilities include a flame trench that bisects the pad at ground level. This trench includes a flame deflector system that consists of an inverted, V-shaped steel structure covered with a high temperature concrete material five inches thick that extends across the center of the flame trench. One side of the "V11 receives and deflects the flames from the orbiter main engines; the opposite side deflects the flames from the solid rocket boosters. There are also two movable deflectors at the top of the trench to provide additional protection to shuttle hardware from the solid rocket booster flames. These facilities are over 40 years old and are experiencing constant deterioration from launch heat/blast effects and environmental exposure. The refractory material currently used in launch pad flame deflectors has become susceptible to failure, resulting in large sections of the material breaking away from the steel base structure and creating high-speed projectiles during launch. These projectiles jeopardize the safety of the launch complex, crew, and vehicle. Post launch inspections have revealed that the number and frequency of repairs, as well as the area and size of the damage, is increasing with the number of launches. The Space Shuttle Program has accepted the extensive ground processing costs for post launch repair of damaged areas and investigations of future launch related failures for the remainder of the program. There currently are no long term solutions available for Constellation Program ground operations to address the poor performance and subsequent failures of the refractory materials. Over the last three years, significant liberation of refractory material in the flame trench and fire bricks along the adjacent trench walls following Space Shuttle launches have resulted in extensive investigations of
Associative morphological memories based on variations of the kernel and dual kernel methods.
Sussner, Peter
2003-01-01
Morphological associative memories (MAMs) belong to the class of morphological neural networks. The recording scheme used in the original MAM models is similar to the correlation recording recipe. Recording is achieved by means of a maximum (MXY model) or minimum (WXY model) of outer products. Notable features of autoassociative morphological memories (AMMs) include optimal absolute storage capacity and one-step convergence. Heteroassociative morphological memories (HMMs) do not have these properties and are not very well understood. The fixed points of AMMs can be characterized exactly in terms of the original patterns. Unfortunately, AMM fixed points include a large number of spurious memories. In this paper, we combine the MXX model and variations of the kernel method to produce new autoassociative and heteroassociative memories. We also introduce a dual kernel method. A new, dual model is given by a combination of the WXX model and a variation of the dual kernel method. The new MAM models exhibit better error correction capabilities than MXX and WXX and a reduced number of spurious memories which can be easily described in terms of the fundamental memories.
Chaotic radiation/turbulence interactions in flames
Energy Technology Data Exchange (ETDEWEB)
Menguec, M.P.; McDonough, J.M.
1998-11-01
In this paper, the authors present a review of their recent efforts to model chaotic radiation-turbulence interactions in flames. The main focus is to characterize soot volume fraction fluctuations in turbulent diffusion flames, as they strongly contribute to these interaction. The approach is based on the hypothesis that the fluctuations of properties in turbulent flames are deterministic in nature, rather than random. The authors first discuss the theoretical details and then they briefly outline the experiments conducted to measure the scattered light signals from fluctuating soot particles along the axis of an ethylene-air diffusion flame. They compare the power spectra and time series obtained from experiments against the ad-hoc and rigorous models derived using a series of logistic maps. These logistic maps can be used in simulation of the fluctuations in these type of flames, without extensive computational effort or sacrifice of physical detail. Availability of accurate models of these kinds allows investigation of radiation-turbulence interactions at a more fundamental level than it was previously possible.
Second Law Analysis of Diffusion Flames
Directory of Open Access Journals (Sweden)
Yalcin Gogus
2001-03-01
Full Text Available The objective of this paper is to investigate the sources of volumetric irreversibilities in both laminar and turbulent diffusion flames. The theoretical background of analysis relies on the local exergy transport equation, which allows the microscopic formulation of the well-known Gouy-Stodola theorem. For laminar reacting flows, the volumetric entropy generation rate expression includes the viscous, thermal, diffusion and chemical components. Their expressions show that the corresponding irreversibilities are uncoupled if the combustion process occurs at constant pressure. The numerical simulation of a methane-air combustion process shows that the thermal, chemical and diffusive irreversibilities represent, in order of enumeration, the predominant irreversibilities in the laminar diffusion reacting flows. In the case of turbulent diffusion flames, the viscous, thermal, diffusion and chemical mean components have to be expressed in accordance with the combustion model. Two combustion models are used: the multi-species approach based on the eddy-break formulation of mean reaction rate, and the assumed probability density function for a conserved scalar that relies on the flame sheet model. For a diffusion methane-air jet flame, the distribution of mean irreversibility components is presented. Taking into account the technical importance of diffusion flames, the analysis could serve to improve the combustion geometry and the flow condition.
Distributed Flames in Type Ia Supernovae
Aspden, A J; Woosley, S E; 10.1088/0004-637X/710/2/1654
2011-01-01
In the distributed burning regime, turbulence disrupts the internal structure of the flame, and so the idea of laminar burning propagated by conduction is no longer valid. The nature of the burning depends on the turbulent Damkohler number (Da), which steadily declines from much greater than one to less that one as the density decreases to a few 10^6 g/cc. Scaling arguments predict that the turbulent flame speed s, normalized by the turbulent intensity u, follows s/u=Da^1/2 for Da1, and that localized excursions to as much as five times u can occur. The lambda-flame speed and width can be predicted based on the turbulence in the star and the turbulent nuclear burning time scale of the fuel. We propose a practical method for measuring these based on the scaling relations and small-scale computationally-inexpensive simulations. This suggests that a simple turbulent flame model can be easily constructed suitable for large-scale distributed supernovae flames.