Salt microspheres and potassium chloride usage for sodium reduction: Case study with sushi.

PubMed

Đorđević, Đani; Buchtová, Hana; Macharáčková, Blanka

2018-01-01

The aim of the study was to estimate possibilities of salt substitutes usage in the preparation of two sushi types (nigiri and maki) prepared with different seafood (salmon: Salmo salar, tuna: Thunnus albacares, and shrimp: Pleoticus muelleri). Potassium chloride (Mary samples), Soda-Lo (hollowed microsphere of regular salt crystals), and regular salt (sodium chloride) were used in the experiment. Sushi samples (n = 1960) were evaluated by 40 trained panelists who noticed that maki shrimp samples prepared with Mary salt had higher bitterness (21.48 ± 28.01) in comparison with 2% sodium chloride (7.91 ± 8.80). The saltiness was lower in nigiri tuna prepared with Mary (49.59 ± 17.47) than 2% sodium chloride (61.11 ± 15.75). The study clearly showed the possibility of lowering sodium content in sushi meal with the usage of salt substitutes, with emphasis that Soda-Lo should be considered as a better option due to the retention of sensory properties in sushi samples prepared with this salt substitute.

Tora no Maki III. Lessons for Teaching about Contemporary Japan.

ERIC Educational Resources Information Center

National Council for the Social Studies, Washington, DC.

The elements of Japan, including history, geography, economics, civics, and cultural studies, are in this collection of original lesson plans. The lessons are meant to provide original content about Japan to augment and supplement an existing unit of study and evoke a spirit of inquiry and introspection. The 24 lessons are as follows: (1)…

Upper critical and irreversibility fields in Ni- and Co-doped pnictide bulk superconductors

NASA Astrophysics Data System (ADS)

Nikolo, Martin; Singleton, John; Solenov, Dmitry; Jiang, Jianyi; Weiss, Jeremy; Hellstrom, Eric

2018-05-01

A comprehensive study of upper critical and irreversibility magnetic fields in Ba(Fe0.95Ni0.05)2As2 (large grain and small grain samples), Ba(Fe0.94Ni0.06)2As2, Ba(Fe0.92Co0.08)2As2, and Ba(Fe0.92Co0.09)2As2 polycrystalline bulk pnictide superconductors was made in pulsed fields of up to 65 T. The full magnetic field-temperature (H-T) phase diagrams, starting at 1.5 K, were measured. The higher temperature, upper critical field Hc2 data are well described by the one-band Werthamer, Helfand, and Hohenberg (WHH) model. At low temperatures, the experimental data depart from the fitted WHH curves, suggesting an emergence of a new phase that could be attributed to the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state. The large values of the Maki fitting parameter α indicate that the Zeeman pair breaking dominates over the orbital pair breaking and spin-paramagnetic pair-breaking effect is significant in these materials. Possible multi-band structure of these materials is lumped into effective parameters of the single-band model. Table of measured physical parameters allows us to compare these pnictide superconductors for different Co- and Ni- doping levels and granularity.

Observation of Electron Neutrino Appearance in a Muon Neutrino Beam

NASA Astrophysics Data System (ADS)

Abe, K.; Adam, J.; Aihara, H.; Akiri, T.; Andreopoulos, C.; Aoki, S.; Ariga, A.; Ariga, T.; Assylbekov, S.; Autiero, D.; Barbi, M.; Barker, G. J.; Barr, G.; Bass, M.; Batkiewicz, M.; Bay, F.; Bentham, S. W.; Berardi, V.; Berger, B. E.; Berkman, S.; Bertram, I.; Bhadra, S.; Blaszczyk, F. d. M.; Blondel, A.; Bojechko, C.; Bordoni, S.; Boyd, S. B.; Brailsford, D.; Bravar, A.; Bronner, C.; Buchanan, N.; Calland, R. G.; Caravaca Rodríguez, J.; Cartwright, S. L.; Castillo, R.; Catanesi, M. G.; Cervera, A.; Cherdack, D.; Christodoulou, G.; Clifton, A.; Coleman, J.; Coleman, S. J.; Collazuol, G.; Connolly, K.; Cremonesi, L.; Dabrowska, A.; Danko, I.; Das, R.; Davis, S.; de Perio, P.; De Rosa, G.; Dealtry, T.; Dennis, S. R.; Densham, C.; Di Lodovico, F.; Di Luise, S.; Drapier, O.; Duboyski, T.; Duffy, K.; Dufour, F.; Dumarchez, J.; Dytman, S.; Dziewiecki, M.; Emery, S.; Ereditato, A.; Escudero, L.; Finch, A. J.; Floetotto, L.; Friend, M.; Fujii, Y.; Fukuda, Y.; Furmanski, A. P.; Galymov, V.; Gaudin, A.; Giffin, S.; Giganti, C.; Gilje, K.; Goeldi, D.; Golan, T.; Gomez-Cadenas, J. J.; Gonin, M.; Grant, N.; Gudin, D.; Hadley, D. R.; Haesler, A.; Haigh, M. D.; Hamilton, P.; Hansen, D.; Hara, T.; Hartz, M.; Hasegawa, T.; Hastings, N. C.; Hayato, Y.; Hearty, C.; Helmer, R. L.; Hierholzer, M.; Hignight, J.; Hillairet, A.; Himmel, A.; Hiraki, T.; Hirota, S.; Holeczek, J.; Horikawa, S.; Huang, K.; Ichikawa, A. K.; Ieki, K.; Ieva, M.; Ikeda, M.; Imber, J.; Insler, J.; Irvine, T. J.; Ishida, T.; Ishii, T.; Ives, S. J.; Iyogi, K.; Izmaylov, A.; Jacob, A.; Jamieson, B.; Johnson, R. A.; Jo, J. H.; Jonsson, P.; Jung, C. K.; Kaboth, A. C.; Kajita, T.; Kakuno, H.; Kameda, J.; Kanazawa, Y.; Karlen, D.; Karpikov, I.; Kearns, E.; Khabibullin, M.; Khotjantsev, A.; Kielczewska, D.; Kikawa, T.; Kilinski, A.; Kim, J.; Kisiel, J.; Kitching, P.; Kobayashi, T.; Koch, L.; Kolaceke, A.; Konaka, A.; Kormos, L. L.; Korzenev, A.; Koseki, K.; Koshio, Y.; Kreslo, I.; Kropp, W.; Kubo, H.; Kudenko, Y.; Kumaratunga, S.; Kurjata, R.; Kutter, T.; Lagoda, J.; Laihem, K.; Lamont, I.; Laveder, M.; Lawe, M.; Lazos, M.; Lee, K. P.; Licciardi, C.; Lindner, T.; Lister, C.; Litchfield, R. P.; Longhin, A.; Ludovici, L.; Macaire, M.; Magaletti, L.; Mahn, K.; Malek, M.; Manly, S.; Marino, A. D.; Marteau, J.; Martin, J. F.; Maruyama, T.; Marzec, J.; Mathie, E. L.; Matveev, V.; Mavrokoridis, K.; Mazzucato, E.; McCarthy, M.; McCauley, N.; McFarland, K. S.; McGrew, C.; Metelko, C.; Mezzetto, M.; Mijakowski, P.; Miller, C. A.; Minamino, A.; Mineev, O.; Mine, S.; Missert, A.; Miura, M.; Monfregola, L.; Moriyama, S.; Mueller, Th. A.; Murakami, A.; Murdoch, M.; Murphy, S.; Myslik, J.; Nagasaki, T.; Nakadaira, T.; Nakahata, M.; Nakai, T.; Nakamura, K.; Nakayama, S.; Nakaya, T.; Nakayoshi, K.; Naples, D.; Nielsen, C.; Nirkko, M.; Nishikawa, K.; Nishimura, Y.; O'Keeffe, H. M.; Ohta, R.; Okumura, K.; Okusawa, T.; Oryszczak, W.; Oser, S. M.; Owen, R. A.; Oyama, Y.; Palladino, V.; Paolone, V.; Payne, D.; Pearce, G. F.; Perevozchikov, O.; Perkin, J. D.; Petrov, Y.; Pickard, L. J.; Pinzon Guerra, E. S.; Pistillo, C.; Plonski, P.; Poplawska, E.; Popov, B.; Posiadala, M.; Poutissou, J.-M.; Poutissou, R.; Przewlocki, P.; Quilain, B.; Radicioni, E.; Ratoff, P. N.; Ravonel, M.; Rayner, M. A. M.; Redij, A.; Reeves, M.; Reinherz-Aronis, E.; Retiere, F.; Robert, A.; Rodrigues, P. A.; Rojas, P.; Rondio, E.; Roth, S.; Rubbia, A.; Ruterbories, D.; Sacco, R.; Sakashita, K.; Sánchez, F.; Sato, F.; Scantamburlo, E.; Scholberg, K.; Schwehr, J.; Scott, M.; Seiya, Y.; Sekiguchi, T.; Sekiya, H.; Sgalaberna, D.; Shiozawa, M.; Short, S.; Shustrov, Y.; Sinclair, P.; Smith, B.; Smith, R. J.; Smy, M.; Sobczyk, J. T.; Sobel, H.; Sorel, M.; Southwell, L.; Stamoulis, P.; Steinmann, J.; Still, B.; Suda, Y.; Suzuki, A.; Suzuki, K.; Suzuki, S. Y.; Suzuki, Y.; Szeglowski, T.; Tacik, R.; Tada, M.; Takahashi, S.; Takeda, A.; Takeuchi, Y.; Tanaka, H. K.; Tanaka, H. A.; Tanaka, M. M.; Terhorst, D.; Terri, R.; Thompson, L. F.; Thorley, A.; Tobayama, S.; Toki, W.; Tomura, T.; Totsuka, Y.; Touramanis, C.; Tsukamoto, T.; Tzanov, M.; Uchida, Y.; Ueno, K.; Vacheret, A.; Vagins, M.; Vasseur, G.; Wachala, T.; Waldron, A. V.; Walter, C. W.; Wark, D.; Wascko, M. O.; Weber, A.; Wendell, R.; Wilkes, R. J.; Wilking, M. J.; Wilkinson, C.; Williamson, Z.; Wilson, J. R.; Wilson, R. J.; Wongjirad, T.; Yamada, Y.; Yamamoto, K.; Yanagisawa, C.; Yen, S.; Yershov, N.; Yokoyama, M.; Yuan, T.; Zalewska, A.; Zalipska, J.; Zambelli, L.; Zaremba, K.; Ziembicki, M.; Zimmerman, E. D.; Zito, M.; Żmuda, J.; T2K Collaboration

2014-02-01

The T2K experiment has observed electron neutrino appearance in a muon neutrino beam produced 295 km from the Super-Kamiokande detector with a peak energy of 0.6 GeV. A total of 28 electron neutrino events were detected with an energy distribution consistent with an appearance signal, corresponding to a significance of 7.3σ when compared to 4.92±0.55 expected background events. In the Pontecorvo-Maki-Nakagawa-Sakata mixing model, the electron neutrino appearance signal depends on several parameters including three mixing angles θ12, θ23, θ13, a mass difference Δm322 and a CP violating phase δCP. In this neutrino oscillation scenario, assuming |Δm322|=2.4×10-3 eV2, sin2θ23=0.5, and Δm322>0 (Δm322<0), a best-fit value of sin22θ13=0.140-0.032+0.038 (0.170-0.037+0.045) is obtained at δCP=0. When combining the result with the current best knowledge of oscillation parameters including the world average value of θ13 from reactor experiments, some values of δCP are disfavored at the 90% C.L.

Neutrino and C P -even Higgs boson masses in a nonuniversal U (1 )' extension

NASA Astrophysics Data System (ADS)

Mantilla, S. F.; Martinez, R.; Ochoa, F.

2017-05-01

We propose a new anomaly-free and family nonuniversal U (1 )' extension of the standard model with the addition of two scalar singlets and a new scalar doublet. The quark sector is extended by adding three exotic quark singlets, while the lepton sector includes two exotic charged lepton singlets, three right-handed neutrinos, and three sterile Majorana leptons to obtain the fermionic mass spectrum of the standard model. The lepton sector also reproduces the elements of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix and the squared-mass differences data from neutrino oscillation experiments. Also, analytical relations of the PMNS matrix are derived via the inverse seesaw mechanism, and numerical predictions of the parameters in both normal and inverse order scheme for the mass of the phenomenological neutrinos are obtained. We employed a simple seesawlike method to obtain analytical mass eigenstates of the C P -even 3 ×3 mass matrix of the scalar sector.

Measuring and Analyzing Cognitive Skills at the Platoon Level

DTIC Science & Technology

1990-03-01

s~jt tnheted ofe cursJsfe n h ai fcma fiinv 1fie trea’,; .)f ult\\ u01 this rsearch r t detrmed whics ariismot inunTes de cisoe makie abilites...admiinister the test to a group of Non -Comnmissioned Officers from Fort Ord. California. The test is 2iven once at the beginning of the Basic Non ...C. MTHOPOLEM............................................3 11. TEST DESIGN AND SCORING SYSTEM...........................5 A. TEST SCENARIO

Perceptual Organization, Figure-Ground, Attention and Saliency

DTIC Science & Technology

1991-08-01

hole is inside it, in one sense, whereas the dough is inside it in another. But the region occupied by the donut for the most part includes both...current assumption of which type of region is figure does not play any role in the processing. Rather, we have shown several examples where the...Landau 1984], [Jolicoeur 1985], [Palmer 1985], [Corballis and Cullen 86], [ Maki 1986], [Jolicoeur, Snow and Murray 1987], [Parsons and Shimojo 1987

Quantum oscillations and upper critical magnetic field of the iron-based superconductor FeSe

NASA Astrophysics Data System (ADS)

Audouard, Alain; Duc, Fabienne; Drigo, Loïc; Toulemonde, Pierre; Karlsson, Sandra; Strobel, Pierre; Sulpice, André

2015-01-01

Shubnikov-de Haas (SdH) oscillations and upper critical magnetic field (Hc2) of the iron-based superconductor FeSe (Tc = 8.6 \\text{K}) have been studied by tunnel diode oscillator-based measurements in magnetic fields of up to 55 T and temperatures down to 1.6 K. Several Fourier components enter the SdH oscillations spectrum with frequencies definitely smaller than predicted by band structure calculations indicating band renormalization and reconstruction of the Fermi surface at low temperature, in line with previous ARPES data. The Werthamer-Helfand-Hohenberg model accounts for the temperature dependence of (Hc2) for magnetic field applied both parallel (\\textbf{H} \\| ab) and perpendicular (\\textbf{H} \\| c) to the iron conducting plane, suggesting that one band mainly controls the superconducting properties in magnetic fields despite the multiband nature of the Fermi surface. Whereas Pauli pair breaking is negligible for \\textbf{H} \\| c , a Pauli paramagnetic contribution is evidenced for \\textbf{H} \\| ab with Maki parameter α = 2.1 , corresponding to Pauli field HP = 36.5 \\text{T} .

National Program for Inspection of Non-Federal Dams. Goodall-Sanford Dam (ME-00185), Mousam River Basin, Sanford, Maine. Phase I Inspection Report.

DTIC Science & Technology

1979-06-01

CONCRETE FACE (1//8 SILL 280 WATE DOWNSTREAM CHANNEL L275 BEDROCK SECTION B L #MA?~ki. ’ROGNAM CISPECTON OF PeON r 9 9 MOUSAM RIVER MAINE .- 20799 - 19...0DOWNSTREAM * CHANNEL -*.:’. BEDROCK27 SECTION C WOOLiA4 PROGAM OF looSPEC-OmN o moF.ol4’C~~a6 GOODALL DAM X - SECTION MOUSAM RIVER MAINE 20799 -19. S

Neutrino oscillations: The rise of the PMNS paradigm

NASA Astrophysics Data System (ADS)

Giganti, C.; Lavignac, S.; Zito, M.

2018-01-01

Since the discovery of neutrino oscillations, the experimental progress in the last two decades has been very fast, with the precision measurements of the neutrino squared-mass differences and of the mixing angles, including the last unknown mixing angle θ13. Today a very large set of oscillation results obtained with a variety of experimental configurations and techniques can be interpreted in the framework of three active massive neutrinos, whose mass and flavour eigenstates are related by a 3 × 3 unitary mixing matrix, the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix, parametrized by three mixing angles θ12, θ23, θ13 and a CP-violating phase δCP. The additional parameters governing neutrino oscillations are the squared-mass differences Δ mji2 = mj2 - mi2, where mi is the mass of the ith neutrino mass eigenstate. This review covers the rise of the PMNS three-neutrino mixing paradigm and the current status of the experimental determination of its parameters. The next years will continue to see a rich program of experimental endeavour coming to fruition and addressing the three missing pieces of the puzzle, namely the determination of the octant and precise value of the mixing angle θ23, the unveiling of the neutrino mass ordering (whether m1

iLab 20M: A Large-scale Controlled Object Dataset to Investigate Deep Learning

DTIC Science & Technology

2016-07-01

and train) and anno - tate them with rotation labels. Alexnet is fine tuned on the training set. We set the learning rate for all the layers to 0.001...Azizpour, A. Razavian, J . Sullivan, A. Maki, and S. Carls- son. From generic to specific deep representations for visual recognition. In CVPR...113–120. IEEE, 2014. 2 [5] J . Bromley, J . W. Bentz, L. Bottou, I. Guyon, Y. LeCun, C. Moore, E. Säckinger, and R. Shah. Signature verifica- tion using

Scoping Summary Report, Los Angeles AFB, California. Air Force Base Closure and Realignment Environmental Impact Analysis Process Support

DTIC Science & Technology

1990-07-01

Mexico 87123 Dayton, Ohio 45402 * Richard A. Lampson Butch Maki Hydro Conduit Corp. Congressman Bill Richardson - 4801 Yucatan N.E. 548 Agua Fria...some chile con queso; however, that would be too much, and I think that might be considered a bribe. The Mayor asked me to convey his regrets. He’s tied...that God sends you here. Also, the small momento that Loretta is giving you, which is our state symbol, has a chile on it; and that’s to remind you

Ground Target Modeling and Validation Conference (10th) Held in Houghton, Michigan, on 17-19 August 1999

DTIC Science & Technology

1999-08-01

electrically small or only have a greater size in one dimension will not have a significant impact on the total RCS. At 1000 MHz, the components on the model ...7^/43- L"^y 16 % 6 ^Ly Cc>v y to-*^ r*r+r g,^\\oS^ Proceedings ? Tenth Annual Ground Target Modeling and Validation Conference August 1999...of the Tenth Annual Ground Target Modeling and Validation Conference (Unclassified) \\2. PERSONAL AUTHOR(S) William R Reynolds and Tracy T. Maki 13a

AGR-1 Compact 1-3-1 Post-Irradiation Examination Results

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

Demkowicz, Paul Andrew

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program was established to perform the requisite research and development on tristructural isotropic (TRISO) coated particle fuel to support deployment of a high-temperature gas-cooled reactor (HTGR). The work continues as part of the Advanced Reactor Technologies (ART) TRISO Fuel program. The overarching program goal is to provide a baseline fuel qualification data set to support licensing and operation of an HTGR. To achieve these goals, the program includes the elements of fuel fabrication, irradiation, post-irradiation examination (PIE) and safety testing, fuel performance modeling, and fission product transport (INL 2015). A seriesmore » of fuel irradiation experiments is being planned and conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). These experiments will provide data on fuel performance under irradiation, support fuel process development, qualify the fuel for normal operating conditions, provide irradiated fuel for safety testing, and support the development of fuel performance and fission product transport models. The first of these irradiation tests, designated AGR-1, began in the ATR in December 2006 and ended in November 2009. This experiment was conducted primarily to act as a shakedown test of the multicapsule test train design and provide early data on fuel performance for use in fuel fabrication process development. It also provided samples for post-irradiation safety testing, where fission product retention of the fuel at high temperatures will be experimentally measured. The capsule design and details of the AGR-1 experiment have been presented previously (Grover, Petti, and Maki 2010, Maki 2009).« less

International Conference on Crystal Growth (10th) (ICCG-10) Held in San Diego, California on August 16 - 21, 1992

DTIC Science & Technology

1992-08-21

Synthetic Crystals. China82 The Growth of LaMgA],,O,,:Nd Large Crystals with High Quality B16 G, Wu. X Ma.* J. Xu. X Zhang and Y. Shen Crystal Growth and...Stolchlometry Problems of ZnSe for High Power Laser Y. ShIralshl Optical Components Kimura Metamelt Project. Japan E~ Kjause.* A. Moseal and H. Harmnn...Maki- Shanghai Institute of Ceramics. China Yokohama City University. Japa 023 CS Growth of High -CluaI~ty TI:A1202 Crystals for Solid-State Lase In

Possibility of relationship between the yellow sand and the foot-and-mouth disease in Miyazaki Prefecture, Japan in March 2010 by using MODIS images

NASA Astrophysics Data System (ADS)

Kato, Yoshinobu

2014-11-01

In Miyazaki Prefecture, Japan, the O-type foot-and-mouth disease (FMD) appeared and spread from March to July, 2010. The first infected livestock by FMD virus was detected on March 26, 2010 at Tsuno Town in Miyazaki Prefecture. The O-type FMD was found on March 14 at the suburb of Lanzhou City in Gansu, and on March 25, 2010 in Shanxi, China. The duration of FMD virus incubation is 2 to 8 days. Maki et al. (2011, 2012) presumed the cause of the first FMD in Miyazaki as follows: The yellow sand adhered with FMD virus was transported from Gansu to Miyazaki by global westerly winds. In this paper, we investigate whether the yellow sand generated in Gansu flew to Miyazaki in March, 2010 by using MODIS data of Terra and Aqua satellites. True-color mosaic images, AVI mosaic images and T11 mosaic images from China to Japan are made and examined. The aerosol vapor index (AVI) is defined as AVI=T12-T11, where T12 and T11 are the brightness temperatures at 12μm and 11μm wavelength, respectively. The AVI can detect the dust and sandstorms (DSS, i.e., yellow sands) in satellite images both at daytime and night. AVI values are classified into six levels from 0 to 5. From AVI images, DSS existed in the vicinity of Lanzhou on March 19, and in the south area of Shanxi on March 20, and in the vicinity of Tsuno Town on March 21. If Maki et al. are right, the cause of the first FMD in Miyazaki in March 2010 is that DSS generated in Gansu on March 19 flew to Miyazaki on March 21.

Quantum oscillations in vortex-liquids

NASA Astrophysics Data System (ADS)

Banerjee, Sumilan; Zhang, Shizhong; Randeria, Mohit

2012-02-01

Motivated by observations of quantum oscillations in underdoped cuprates [1], we examine the electronic density of states (DOS) in a vortex-liquid state, where long-range phase coherence is destroyed by an external magnetic field H but the local pairing amplitude survives. We note that this regime is distinct from that studied in most of the recent theories, which have focused on either a Fermi liquid with a competing order parameter or on a d-wave vortex lattice. The cuprate experiments are very likely in a resistive vortex-liquid state. We generalize the s-wave analysis of Maki and Stephen [2] to d-wave pairing and examine various regimes of the chemical potential, gap and field. We find that the (1/H) oscillations of the DOS at the chemical potential in a d-wave vortex-liquid are much more robust, i.e., have a reduced damping, compared to the s-wave case. We critically investigate the conventional wisdom relating the observed frequency to the area of an underlying Fermi surface. We also show that the oscillations in the DOS cross over to a √H behavior in the low field limit, in agreement with the recent specific heat measurements. [1] L. Taillefer, J. Phys. Cond. Mat. 21, 164212 (2009). [2] M. J. Stephen, Phys. Rev. B 45, 5481 (1992).

The upper critical field of filamentary Nb3Sn conductors

NASA Astrophysics Data System (ADS)

Godeke, A.; Jewell, M. C.; Fischer, C. M.; Squitieri, A. A.; Lee, P. J.; Larbalestier, D. C.

2005-05-01

We have examined the upper critical field of a large and representative set of present multifilamentary Nb3Sn wires and one bulk sample over a temperature range from 1.4 K up to the zero-field critical temperature. Since all present wires use a solid-state diffusion reaction to form the A15 layers, inhomogeneities with respect to Sn content are inevitable, in contrast to some previously studied homogeneous samples. Our study emphasizes the effects that these inevitable inhomogeneities have on the field-temperature phase boundary. The property inhomogeneities are extracted from field-dependent resistive transitions which we find broaden with increasing inhomogeneity. The upper 90%-99% of the transitions clearly separates alloyed and binary wires but a pure, Cu-free binary bulk sample also exhibits a zero-temperature critical field that is comparable to the ternary wires. The highest μ0Hc2 detected in the ternary wires are remarkably constant: The highest zero-temperature upper critical fields and zero-field critical temperatures fall within 29.5±0.3 and 17.8±0.3K, respectively, independent of the wire layout. The complete field-temperature phase boundary can be described very well with the relatively simple Maki-DeGennes model using a two-parameter fit, independent of composition, strain state, sample layout, or applied critical state criterion.

Theory of Semiconducting Superlattices and Microstructures

DTIC Science & Technology

1992-03-01

A)dee on ZnSc layer thic~ness V (number of ZnSe molecules thick) It is Ga ashallowit h do o nu io and s e x de trap (mak.i for N X 10 ZnSe/ZnO,$MnO...ZnSe (which can be easily doped n-type r but not p-type) and ZnTe (which can be doped 15 p-type): de ~ep levels that lie in the gap of ZnSe and btrap...1101 SX. Ren. 3.D. Dow and S. Klemmn. J. Appl. Vh’.-s. in press,search. the Army Research Office, and the De . 111) 3.D. Dow. Run-Di Hong. S, Klemm

Ice-Nucleating Bacteria

NASA Astrophysics Data System (ADS)

Obata, Hitoshi

Since the discovery of ice-nucleating bacteria in 1974 by Maki et al., a large number of studies on the biological characteristics, ice-nucleating substance, ice nucleation gene and frost damage etc. of the bacteria have been carried out. Ice-nucleating bacteria can cause the freezing of water at relatively warm temperature (-2.3°C). Tween 20 was good substrates for ice-nucleating activity of Pseudomonas fluorescens KUIN-1. Major fatty acids of Isolate (Pseudomonas fluorescens) W-11 grown at 30°C were palmitic, cis-9-hexadecenoic and cis-11-octadecenoic which amounted to 90% of the total fatty acids. Sequence analysis shows that an ice nucleation gene from Pseudomonas fluorescens is related to the gene of Pseudomonas syringae.

Superconducting Fluctuations above T c and pair breaking parameters of two dimensional Niobium Nitride Films

NASA Astrophysics Data System (ADS)

Shinozaki, B.; Ezaki, S.; Odou, T.; Makise, K.; Asano, T.

2018-03-01

Transport properties have been investigated for the epitaxial superconducting NbN thin films. We analysed the excess conductance σ’ ≡ σ(T) - σN by the sum of the Aslamazov-Larkin (AL) and Maki-Thompson (MT) terms for thermal fluctuations above T c, where the σN ≡1/R sq N is the normal state sheet conductance. We have found that the theoretical expression σ’theo (T) = σ’AL (T) + σ’MT (T,δ) can be well fitted to σ’exp (T) with use of the suitable value of the pair breaking parameter δ in the MT term relating to the inelastic scattering rate 1/τin(T) as δ = πħ/8k B Tτin. The rate 1/τin(T) given by the sum of 1/τfluc(T), 1/τe-e(T) and 1/τe-ph (T) is determined from the analysis of the magneto-conductance Δσ = σ(H) – σ(0) by the sum of AL, MT and the localization terms, where the first, second and third terms correspond to the rate due to the superconducting fluctuation effect, electron-electron and electron-phonon interactions, respectively. The R sq N dependence of δ is expressed by δ = δ0 + αR sq N, where the first term δ0 due to 1/τe-ph (T) and the second term due to the sum of 1/τfluc(T) and 1/τe-e(T). Although we obtained a reasonable value of Debye temperature ΘD ≈630 K from the δ0, the magnitude of the α is about 5 times larger than the theoretical value.

Lattice instability and enhancement of superconductivity in YB6

NASA Astrophysics Data System (ADS)

Sluchanko, N.; Glushkov, V.; Demishev, S.; Azarevich, A.; Anisimov, M.; Bogach, A.; Voronov, V.; Gavrilkin, S.; Mitsen, K.; Kuznetsov, A.; Sannikov, I.; Shitsevalova, N.; Filipov, V.; Kondrin, M.; Gabáni, S.; Flachbart, K.

2017-10-01

The superconducting and normal state characteristics of yttrium hexaboride (YB6) have been investigated for the single crystals with a transition temperatures Tc ranging between 4.2 K and 7.6 K. The extracted set of microscopic parameters [the coherence length ξ (0 )˜320 -340 Å , the penetration depth λ (0 )˜1100 -3250 Å and the mean free path of charge carriers l =11 -58 Å , the Ginzburg-Landau-Maki parameters κ1 ,2(0 ) ˜3.3 -9.5, and the superconducting gap Δ (0 )˜6.2 -14.8 K] confirms the type II superconductivity in "dirty limit" (ξ ≫l ) with a medium to strong electron-phonon interaction (the electron-phonon interaction constant λe -ph=0.32 -0.96 ) and s -type pairing of charge carriers in this compound [2 Δ (0 ) /kBTc≈3 -4]. The comparative analysis of charge transport (resistivity, Hall and Seebeck coefficients) and thermodynamic (heat capacity, magnetization) properties in the normal state in YB6 allowed to assume a transition into the cage-glass state at T*˜50 K with a static disorder in the arrangement of the Y3 + ions. We argue that the significant Tc variations in YB6 single crystals are determined by two main factors: (i) the superconductivity enhancement is related with the increase of the number of vacancies, both at yttrium and boron sites, leading to nonstoichiometric composition, which is accompanied by the enhancement of electron-phonon interaction in the hexaboride lattice; (ii) stronger Tc depression is observed in near stoichiometric and more dense crystals and it is induced by the development of bcc lattice instability producing strong distortion, disordering, and formation of defect complexes in the matrix of YB6.

Testing constrained sequential dominance models of neutrinos

NASA Astrophysics Data System (ADS)

Björkeroth, Fredrik; King, Stephen F.

2015-12-01

Constrained sequential dominance (CSD) is a natural framework for implementing the see-saw mechanism of neutrino masses which allows the mixing angles and phases to be accurately predicted in terms of relatively few input parameters. We analyze a class of CSD(n) models where, in the flavour basis, two right-handed neutrinos are dominantly responsible for the ‘atmospheric’ and ‘solar’ neutrino masses with Yukawa couplings to ({ν }e,{ν }μ ,{ν }τ ) proportional to (0,1,1) and (1,n,n-2), respectively, where n is a positive integer. These coupling patterns may arise in indirect family symmetry models based on A 4. With two right-handed neutrinos, using a χ 2 test, we find a good agreement with data for CSD(3) and CSD(4) where the entire Pontecorvo-Maki-Nakagawa-Sakata mixing matrix is controlled by a single phase η, which takes simple values, leading to accurate predictions for mixing angles and the magnitude of the oscillation phase | {δ }{CP}| . We carefully study the perturbing effect of a third ‘decoupled’ right-handed neutrino, leading to a bound on the lightest physical neutrino mass {m}1{{≲ }}1 meV for the viable cases, corresponding to a normal neutrino mass hierarchy. We also discuss a direct link between the oscillation phase {δ }{CP} and leptogenesis in CSD(n) due to the same see-saw phase η appearing in both the neutrino mass matrix and leptogenesis.

Quantum-Fluctuation Effects in the Transport Properties of Ultrathin Films of Disordered Superconductors above the Paramagnetic Limit

NASA Astrophysics Data System (ADS)

Khodas, M.; Levchenko, A.; Catelani, G.

2012-06-01

We study the transport in ultrathin disordered film near the quantum critical point induced by the Zeeman field. We calculate corrections to the normal state conductivity due to quantum pairing fluctuations. The fluctuation-induced transport is mediated by virtual rather than real quasiparticle excitations. We find that at zero temperature, where the corrections come from purely quantum fluctuations, the Aslamazov-Larkin paraconductivity term, the Maki-Thompson interference contribution, and the density of states effects are all of the same order. The total correction leads to the negative magnetoresistance. This result is in qualitative agreement with the recent transport observations in the parallel magnetic field of the homogeneously disordered amorphous films and superconducting two-dimensional electron gas realized at the oxide interfaces.

A comparison of student characteristics in traditional and Web-based college science courses

NASA Astrophysics Data System (ADS)

Andrikanich, Meghan

Distance learning options at colleges and universities are increasing dramatically (e.g. National Center for Educational Statistics [NCES], 1998; NCES, 2001). Web-based courses create an interesting learning environment for study (e.g., Dupin-Bryant, 2004; Maki & Maki, 2003). Because science is a topic that induces anxiety for many students (e.g., Brownlow, et al., 2000; Greenburg & Mallow, 1982), and test anxiety has been linked to reduced academic performance (e.g., Bruch, 1981; Spielberger, 1979), the intersection of course format, science, and test anxiety is an area in need of research. This study used an explanatory mixed method design. One hundred and seven web-based science students and 110 students enrolled in traditional courses completed a questionnaire regarding demographic and personal factors, the Reduced Reaction to Tests (RTT) (Benson & Bandalos, 1992) and the Locus of Control of Behavior Scale (Craig, Franklin, & Andrews, 1984). Ten students participated in a follow-up interview. Quantitative results found no significant difference between age, racial/ethnic background, student status (full-time or part-time), or degree program being pursued between traditional and web-based science courses. Significantly more females, more students employed full-time, and with an external locus of control enrolled in web-based courses. Students in traditional courses experienced more test anxiety due to test-irrelevant thoughts. Traditional students experienced more anxiety in traditional science courses, while nontraditional students experienced more anxiety in web-based science courses. Expected course grade and locus of control predicted test anxiety in traditional courses, and previous web experience, expected grade, and locus of control predicted test anxiety for web-based courses. Qualitative data indicated that students in both formats expressed opinions regarding course format, studying and test preparation methods, test-taking, communication with instructors in general, and specifically related to testing. Opinions indicated students prefer a comfortable course environment, whether that involves technology or not. Several recommendations can be made. A continued increase in the type and variety of web-based courses will allow students continued flexibility in course scheduling. Multiple-choice tests should be considered to reduce student anxiety. Instructors should strive towards creating comfortable classroom environments and communicate clearly with their students.

Minimal modification of tri-bimaximal neutrino mixing and leptonic CP violation

NASA Astrophysics Data System (ADS)

Kang, Sin Kyu

2017-12-01

We confront possible forms of the minimal modification of the tri-bimaximal (TBM) neutrino mixing matrix proposed by Kang and Kim (Phys. Rev. D 90, 077301 (2014)) with the latest global fit to neutrino data. One form among them is singled out by the current experimental results at 1σ confidence level (C.L.) The minimal modification of the TBM mixing matrix makes possible the prediction of Dirac-type CP phase in the Pontecorbo-Maki-Nakagawa-Sakata neutrino mixing matrix in terms of two neutrino mixing angles. By carrying out a numerical analysis based on the latest experimental results for neutrino mixing angles, we are able to present new results on the prediction of the Dirac-type CP phase. We also compare our results on CP violation with those from the current global fit at 1 σ C.L.

The exponential parameterization of the neutrino mixing matrix as an SU(3) group element and an account for new experimental data

NASA Astrophysics Data System (ADS)

Zhukovsky, K. V.

2017-09-01

The exponential form of the Pontecorvo-Maki-Nakagawa-Sakata mixing matrix for neutrinos is considered in the context of the fundamental representation of the SU(3) group. The logarithm of the mixing matrix is obtained. Based on the most recent experimental data on neutrino mixing, the exact values of the entries of the exponential matrix are calculated. The exact values for its real and imaginary parts are determined, respectively, in charge of the mixing without CP violation and of the pure CP violation effect. The hypothesis of complementarity for quarks and neutrinos is confirmed. The factorization of the exponential mixing matrix, which allows the separation of the mixing and of the CP violation itself in the form of the product of rotations around the real and imaginary axes, is demonstrated.

NASA DEVELOP students

NASA Image and Video Library

2008-07-08

NASA DEVELOP students at Stennis Space Center recently held a midterm review with George Crozier, who serves as a science adviser to the team. The team also was joined by Jamie Favors of the Mobile (Ala.) County Health Department DEVELOP Team; Cheri Miller, the team's NASA adviser; and Kenton Ross, a team science adviser. Students participating in the meeting included: Lauren Childs, Jason Jones, Maddie Brozen, Matt Batina, Jenn Frey, Angie Maki and Aaron Brooks. The primary purpose of the meeting was to update Crozier on the status of the team's work for the summer 2008 term and discuss plans for the fiscal year 2009 project proposal. This included discussion of a possible project to study the effects of hurricanes on the Florida panhandle. DEVELOP is a NASA-sponsored, student-led, student-run program focused on developing projects to help communities.

Effect of reduction in the density of states on fluctuation conductivity in Bi 2Sr 2CaCu 2O 8+ x single crystals

NASA Astrophysics Data System (ADS)

Chowdhury, P.; Bhatia, S. N.

1999-06-01

The in-plane ( ρab) and out-of-plane ( ρc) resistivities of BSCCO single crystals have been measured by six terminals technique. The ρab and ρc are well described by the fluctuation theory developed by Dorin et al. The main effect of these fluctuations is to cause a reduction in the quasi-particle density of states (DOS), leading to a negative contribution in the fluctuation conductivity Lawrence-Doniach (LD) and Maki-Thompson (MT) contributions. We have analyzed paraconductivity by adding this DOS contribution to LD and MT contributions. The analysis shows that approaches based on the conventional LD model alone cannot explain the paraconductivity along ab-plane and c-axis, even when the MT contribution is included.

Shoichi Sakata: His Life and Physics ---Collections of Materials in Sakata Memorial Archival Library---

NASA Astrophysics Data System (ADS)

Tanabashi, M.

Shoichi Sakata and his Nagoya School made a lot of important achievements at the predawn of the particle physics revolution. The ``two-meson'' theory (introduction of the second generation leptons), the ``C-meson theory'' (a theory which inspired Tomonaga's renormalization theory), the ``Sakata model'' (a precursor to the quark model), and the ``Maki-Nakagawa-Sakata'' theory on the neutrino mixings are among them. These outputs are now regarded as essential ingredients in modern particle physics. Sakata also took his leadership in setting up democratic administration system in his theoretical particle physics group (E-ken). It was this democratic atmosphere in which many excellent physicists were brought up as Sakata's diciples. In this talk, I introduce Sakata and his achievements in physics, showing various materials archived in the Sakata Memorial Archival Library (SMAL), an archival repository of primary material showing Sakata's activities. These SMAL documents vividly show Sakata's way of thinking in his approach to the new physics.

Fluctuation conductance and the Berezinskii-Kosterlitz-Thouless transition in two dimensional epitaxial NbTiN ultra-thin films

NASA Astrophysics Data System (ADS)

K, Makise; H, Terai; T, Yamashita; S, Miki; Z, Wang; Uzawa Y, Y.; S, Ezaki; T, Odou; B, Shinozaki

2012-12-01

We study on the electric transport properties of epitaxial NbTiN ultrathin films in a range from 2 to 8nm. The films with 4 nm thick shows superconductivity of which mean-field superconducting transition temperature is TC0 = 9.43 K The excess conductance due to superconducting fluctuations was measured at temperatures above TC0. The paraconductivity shows a two-dimensional like behaviour at close to TC0. Experimental results are in good agreement with the sum of Aslamazov - Larkin and Maki - Thompson term for superconducting fluctuation theory. Decreasing temperature below TC0, the current-voltage characteristic shows a crossover from linear to nonlinear behaviour. The exponent α of current-voltage relation, V ~ Iα showed universal jump at TCBKT = 9.33 K As results, we find that there is a consistency between the parametrization of the2D characteristics of fluctuation paraconductivity above TC0 and Berezinskii-Kosterlitz-Thouless type behaviour below TC0.

Superconducting fluctuations at arbitrary disorder strength

NASA Astrophysics Data System (ADS)

Stepanov, Nikolai A.; Skvortsov, Mikhail A.

2018-04-01

We study the effect of superconducting fluctuations on the conductivity of metals at arbitrary temperatures T and impurity scattering rates τ-1. Using the standard diagrammatic technique but in the Keldysh representation, we derive the general expression for the fluctuation correction to the dc conductivity applicable for any space dimensionality and analyze it in the case of the film geometry. We observe that the usual classification in terms of the Aslamazov-Larkin, Maki-Thompson, and density-of-states diagrams is to some extent artificial since these contributions produce similar terms, which partially cancel each other. In the diffusive limit, our results fully coincide with recent calculations in the Keldysh technique. In the ballistic limit near the transition, we demonstrate the absence of a divergent term (Tτ ) 2 attributed previously to the density-of-states contribution. In the ballistic limit far above the transition, the temperature-dependent part of the conductivity correction is shown to grow as T τ /ln(T /Tc) , where Tc is the critical temperature.

[Asymmetric confusability effect in recognition memory of cats pictures].

PubMed

Ando, M; Hakoda, Y

1999-06-01

Performance superiority of the addition of features in the stimuli over the deletion on recognition (asymmetric confusability effect) has been shown in previous studies (Pezdek, Maki, Valencia-Laver, Whetstone, Stoeckert, & Dougherty, 1988; Ando & Hakoda, 1998). We investigated the same effect by using a familiar living thing (cat) as a stimulus. Ten subjects were given a recognition task using pictures of cats with feature changes (additions, deletions, or no change). Results showed that the picture with deletions were easier to recognize than those with additions, which was opposite to the previous studies. Then, we examined the possibility that performance superiority of the deletions over the additions was mediated by the factor of impression. Another group of 18 subjects was asked to rate the impression scales consisting of a "typicality-reality factor", a "stability-balance factor", and a "grotesque-disgust factor". Results showed that there was a significant difference in impression ratings for each factor between the additions and the deletions, and that impression ratings predicted recognition performance well. It was concluded that performance superiority of the deletions over the additions was mediated by the factor of impression.

Leptonic CP phase determined by an equation involving PMNS matrix elements

NASA Astrophysics Data System (ADS)

Ke, Hong-Wei; Zhou, Jia-Hui; Li, Xue-Qian

2017-04-01

Several approximate equalities among the matrix elements of the Cabibbo-Kobayashi-Maskawa (CKM) and Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrices imply that hidden symmetries may exist and be common for both quark and neutrino sectors. The charge parity (CP) phase of the CKM matrix ({δ }{CKM}) is involved in these equalities and can be investigated when these equalities turn into several equations. As we substitute those experimentally measured values of the three mixing angles into the equations for quarks, it is noted that one of the equations which holds exactly has a solution {δ }{CKM}=({68.95}-1.15+1.15)^\\circ . That value accords with ({69.1}-3.85+2.02)^\\circ determined from available data. Generalizing the scenario to the lepton sector, the same equality determines the leptonic CP phase {δ }{PMNS} to be ({275.20}-1.15+1.15)^\\circ . Thus we predict the value of {δ }{PMNS} from the equation. So far there is no direct measurement on {δ }{PMNS}, but a recent analysis based on the neutrino oscillation data prefers a phase close to 270°.

Hexameric and pentameric complexes of the ExbBD energizer in the Ton system.

PubMed

Maki-Yonekura, Saori; Matsuoka, Rei; Yamashita, Yoshiki; Shimizu, Hirofumi; Tanaka, Maiko; Iwabuki, Fumie; Yonekura, Koji

2018-04-17

Gram-negative bacteria import essential nutrients such as iron and vitamin B 12 through outer membrane receptors. This process utilizes proton motive force harvested by the Ton system made up of three inner membrane proteins, ExbB, ExbD and TonB. ExbB and ExbD form the proton channel that energizes uptake through TonB. Recently, crystal structures suggest that the ExbB pentamer is the scaffold. Here, we present structures of hexameric complexes of ExbB and ExbD revealed by X-ray crystallography and single particle cryo-EM. Image analysis shows that hexameric and pentameric complexes coexist, with the proportion of hexamer increasing with pH. Channel current measurement and 2D crystallography support the existence and transition of the two oligomeric states in membranes. The hexameric complex consists of six ExbB subunits and three ExbD transmembrane helices enclosed within the central channel. We propose models for activation/inactivation associated with hexamer and pentamer formation and utilization of proton motive force. © 2018, Maki-Yonekura et al.

Manifestation of Nonuniversality of Lepton Interactions in Spontaneously Violated Mirror Symmetry

NASA Astrophysics Data System (ADS)

Dyatlov, I. T.

2018-03-01

Data from the LHCb experiments are indicative of a substantial distinction between the B → K (or K*) + e + e - and B → K (or K*) + μ + μ - branching ratios (April 2017). The branching ratio for the e+e- channel is substantially greater than that for the μ + μ - channel, whereas Standard Model (SM) calculations require that they be equal to each other. The above distinction may suggest the existence of a new interaction changing generations and discriminating between leptons that has couplings that are much greater than and are inverse in strength to the SM fermion couplings to the Higgs boson. Under conditions of spontaneously violated mirror symmetry, the coupling of SM particles to the second Higgs scalar that is inevitably present there and which is in principle heavy possesses precisely these properties. An inverse character of this coupling and its strength are not an additional hypothesis but a necessary condition for qualitatively reproducing, in addition, the observed charged-lepton mass hierarchy and the structure of weak lepton mixing—the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix. Within the mirror model being considered, all properties of the new interaction, including its inverse character, are due to the hierarchical character of the quark and charged-lepton mass spectrum.

Prediction on neutrino Dirac and Majorana phases and absolute mass scale from the CKM matrix

NASA Astrophysics Data System (ADS)

Haba, Naoyuki; Yamada, Toshifumi

2018-03-01

In the type-I seesaw model, the lepton-flavor-mixing matrix (Pontecorvo-Maki-Nakagawa-Sakata matrix) and the quark-flavor-mixing matrix [Cabibbo-Kobayashi-Maskawa (CKM) matrix] may be connected implicitly through a relation between the neutrino Dirac Yukawa coupling YD and the quark Yukawa couplings. In this paper, we study whether YD can satisfy—in the flavor basis where the charged lepton Yukawa and right-handed neutrino Majorana mass matrices are diagonal—the relation YD∝diag (yd,ys,yb)VCKMT or YD∝diag (yu,yc,yt)VCKM* without contradicting the current experimental data on quarks and neutrino oscillations. We search for sets of values of the neutrino Dirac C P phase δC P, Majorana phases α2 , α3 , and the lightest active neutrino mass that satisfy either of the above relations, with the normal or inverted hierarchy of neutrino masses. In performing the search, we consider renormalization group evolutions of the quark masses and CKM matrix and the propagation of their experimental errors along the evolutions. We find that only the former relation YD∝diag (yd,ys,yb)VCKMT with the normal neutrino mass hierarchy holds, based on which we make predictions for δC P, α2, α3, and the lightest active neutrino mass.

The development of a model of community garden benefits to wellbeing.

PubMed

Egli, Victoria; Oliver, Melody; Tautolo, El-Shadan

2016-06-01

Community gardens contribute to community wellbeing by influencing the nutritional and social environment. The aim of this research was to develop a model that communicates the many benefits of community garden participation as described in the academic literature, to a diverse audience of laypersons. This model is an example of effective knowledge translation because the information is able to be more than simply understood but also practically applied. From April to August 2015, a model depicting the many benefits of community garden participation was prepared based on a global, critical literature review. The wellbeing benefits from community garden participation have been grouped into factors influencing the nutritional health environment and factors influencing the social environment. The graphic chosen to form the basis of the model is a fractal tree of life. In October 2015, to test the models comprehension and to obtain stakeholder feedback this model was presented to a diverse group of community members, leaders and workers from the Tāmaki region of Auckland, New Zealand. The model we present here effectively and clearly translates knowledge obtained from the academic literature on the benefits to wellbeing from community garden participation into a tool that can be used, adapted and developed by community groups, government agencies and health promoters.

MARTIAN COLORS PROVIDE CLUES ABOUT MARTIAN WATER

NASA Technical Reports Server (NTRS)

2002-01-01

NASA Hubble Space Telescope images of Mars taken in visible and infrared light detail a rich geologic history and provide further evidence for water-bearing minerals on the planet's surface. LEFT This 'true-color' image of Mars shows the planet as it would look to human eyes. It is clearly more earth-toned than usually depicted in other astronomical images, including earlier Hubble pictures. The slightly bluer shade along the edges of the disk is due to atmospheric hazes and wispy water ice clouds (like cirrus clouds) in the early morning and late evening Martian sky. The yellowish-pink color of the northern polar cap indicates the presence of small iron-bearing dust particles. These particles are covering or are suspended in the air above the blue-white water ice and carbon dioxide ice, which make up the polar cap. Accurate colors are needed to determine the composition and mineralogy of Mars. This can tell how water has influenced the formation of rocks and minerals found on Mars today, as well as the distribution and abundance of ice and subsurface liquid water. Confirmation of the presence of certain oxidized (rusted) minerals (processed by heat or water action) would imply the possibility of different, perhaps much more Earth-like, past Martian climate periods. Because the smallest features visible in this image are only about 14 miles (22 km) across, Hubble can track small-scale variations in the distribution of minerals that do not follow global trends. The image was generated from three separate Wide Field and Planetary Camera 2 images acquired at wavelengths of 410, 502, and 673 nanometers, in March 1997. RIGHT A false-color picture taken in infrared light reveals features that cannot be seen in visible light. Hubble's unique infrared view pinpoints variations in the abundance and distribution of unknown water-bearing minerals on the planet. While it has been known for decades that small amounts of water-bearing minerals exist on the planet's surface, the reddish regions in this image indicate areas of enhanced concentrations of these as-yet-unidentified deposits. They are perhaps related to the water-rich history of this part of Mars. In particular, the large reddish region known as Mare Acidalium was the site of massive flooding early in Martian history. (NASA's Pathfinder spacecraft landed at the southern edge of this region in 1997.) This composite image was taken in July 1997 with Hubble's Near Infrared Camera and Multi-Object Spectrometer. Red corresponds to the strength of an absorption band detected near 1450 nanometers; green to the brightness of the surface in the near-infrared; and blue to topographic elevation, determined from Viking Orbiter data. Researchers: Jim Bell (Cornell University), Justin Maki (NASA Jet Propulsion Laboratory or JPL), and Mike Wolff (Space Sciences Institute), with acknowledgements to Robert Comstock (Central Washington University), Phil James (University of Toledo), and Dave Crisp (JPL) for image processing and acquisition assistance. Photo Credit: Jim Bell (Cornell University), Justin Maki (JPL), and Mike Wolff (Space Sciences Institute) and NASA

The impact of foreign direct investment on CO2 emissions in Turkey: new evidence from cointegration and bootstrap causality analysis.

PubMed

Koçak, Emrah; Şarkgüneşi, Aykut

2018-01-01

Pollution haven hypothesis (PHH), which is defined as foreign direct investment inducing a raising impact on the pollution level in the hosting country, is lately a subject of discussion in the field of economics. This study, within the scope of related discussion, aims to look into the potential impact of foreign direct investments on CO 2 emission in Turkey in 1974-2013 period using environmental Kuznets curve (EKC) model. For this purpose, Maki (Econ Model 29(5):2011-2015, 2012) structural break cointegration test, Stock and Watson (Econometrica 61:783-820, 1993) dynamic ordinary least square estimator (DOLS), and Hacker and Hatemi-J (J Econ Stud 39(2):144-160, 2012) bootstrap test for causality method are used. Research results indicate the existence of a long-term balance relationship between FDI, economic growth, energy usage, and CO 2 emission. As per this relationship, in Turkey, (1) the potential impact of FDI on CO 2 emission is positive. This result shows that PHH is valid in Turkey. (2) Moreover, this is not a one-way relationship; the changes in CO 2 emission also affect FDI entries. (3) The results also provide evidence for the existence of the EKC hypothesis in Turkey. Within the frame of related findings, the study concludes several polities and presents various suggestions.

3D photo mosaicing of Tagiri shallow vent field by an autonomous underwater vehicle (3rd report) - Mosaicing method based on navigation data and visual features -

NASA Astrophysics Data System (ADS)

Maki, Toshihiro; Ura, Tamaki; Singh, Hanumant; Sakamaki, Takashi

Large-area seafloor imaging will bring significant benefits to various fields such as academics, resource survey, marine development, security, and search-and-rescue. The authors have proposed a navigation method of an autonomous underwater vehicle for seafloor imaging, and verified its performance through mapping tubeworm colonies with the area of 3,000 square meters using the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan (Maki et al., 2008, 2009). This paper proposes a post-processing method to build a natural photo mosaic from a number of pictures taken by an underwater platform. The method firstly removes lens distortion, invariances of color and lighting from each image, and then ortho-rectification is performed based on camera pose and seafloor estimated by navigation data. The image alignment is based on both navigation data and visual characteristics, implemented as an expansion of the image based method (Pizarro et al., 2003). Using the two types of information realizes an image alignment that is consistent both globally and locally, as well as making the method applicable to data sets with little visual keys. The method was evaluated using a data set obtained by the AUV Tri-Dog 1 at the vent field in Sep. 2009. A seamless, uniformly illuminated photo mosaic covering the area of around 500 square meters was created from 391 pictures, which covers unique features of the field such as bacteria mats and tubeworm colonies.

New endoscopic classification of the cardiac orifice in esophageal achalasia: Champagne glass sign.

PubMed

Gomi, Kuniyo; Inoue, Haruhiro; Ikeda, Haruo; Bechara, Robert; Sato, Chiaki; Ito, Hiroaki; Onimaru, Manabu; Kitamura, Yohei; Suzuki, Michitaka; Nakamura, Jun; Hata, Yoshitaka; Maruyama, Shota; Sumi, Kazuya; Takahashi, Hiroshi

2016-09-01

Endoscopy, barium esophagram and manometry are used in the diagnosis of achalasia. In the case of early achalasia, characteristic endoscopic findings are difficult to recognize. As a result, the diagnosis of achalasia is often made several years after symptom onset. Therefore, we examined the endoscopic findings of the cardiac orifice in achalasia and propose a new classification. A total of 400 patients with spastic esophageal motility disorders who underwent peroral endoscopic myotomy (POEM) at our hospital between March 2014 and August 2015 were screened for this study. Champagne glass sign (CG) was defined as when the distal end of the lower esophageal sphincter relaxation failure (LESRF) was proximal to the squamocolumnar junction (SCJ) and the SCJ was dilated in the retroflex view. Specifically, CG-1 was defined as a distance from the SCJ to the lower end of LESRF of <1 cm, and CG-2 was defined as a distance ≥1 cm. CG-0 was seen in 73 patients (28.0%), whereas the CG sign was seen in 186 patients (71.3%), of whom 170 (65.1%) were CG-1 and 16 (6.1%) were CG-2. The CG sign is often observed in esophageal achalasia patients. CG-0 (equal to Maki-tsuki) was observed in 28.0% of achalasia patients only. Its absence with dilated SCJ cannot be used to rule out achalasia. Barium esophagram and manometry should be done if esophageal achalasia is strongly suspected. © 2016 Japan Gastroenterological Endoscopy Society.

Are central venous catheter tip cultures reliable after 6-day refrigeration?

PubMed

Bouza, Emilio; Guembe, Maria; Gómez, Haydee; Martín-Rabadán, Pablo; Rivera, Marisa; Alcalá, Luis

2009-07-01

Present guidelines recommend culturing only central venous catheter (CVC) tips from patients with suspected catheter-related bloodstream infection (CR-BSI). However, a high proportion of these suspicions are not confirmed. Moreover, CVC tip culture increases laboratory workload, and reports of colonization may be meaningless or misleading for the clinician. Our working hypothesis was that CVC tips should be refrigerated and cultured only in patients with positive blood cultures. We evaluated the effect of 6-day refrigeration of 215 CVC tips. We selected all the catheters with a significant count according to the Maki's roll-plate technique and randomly assigned them to 2 groups. In group A, the catheters were recultured after 24 h of refrigeration, and in group B, the catheters were recultured after 6 days more of refrigeration, so that the refrigeration time evaluated would be of 6 days. The yield of refrigerated CVC tips that grow significant colony counts of primary culture in group B was compared with the yield of refrigerated catheter tips in group A. The difference showed that 6-day refrigeration reduced the number of significant CVCs by 15.2%. Only 61 CVCs were obtained from patients with CR-BSI, and in most of them, blood cultures were already positive before CVC culture, so only 0.91% of the CR-BSI episodes would have been misdiagnosed as culture negative after refrigeration. Refrigeration of CVC tips sent for culture and culturing only those from patients with positive blood cultures reduce the workload in the microbiology laboratory without misdiagnosing CR-BSI.

Ancient acquisition of "alginate utilization loci" by human gut microbiota.

PubMed

Mathieu, Sophie; Touvrey-Loiodice, Mélanie; Poulet, Laurent; Drouillard, Sophie; Vincentelli, Renaud; Henrissat, Bernard; Skjåk-Bræk, Gudmund; Helbert, William

2018-05-23

In bacteria from the phylum Bacteroidetes, the genes coding for enzymes involved in polysaccharide degradation are often colocalized and coregulated in so-called "polysaccharide utilization loci" (PULs). PULs dedicated to the degradation of marine polysaccharides (e.g. laminaran, ulvan, alginate and porphyran) have been characterized in marine bacteria. Interestingly, the gut microbiome of Japanese individuals acquired, by lateral transfer from marine bacteria, the genes involved in the breakdown of porphyran, the cell wall polysaccharide of the red seaweed used in maki. Sequence similarity analyses predict that the human gut microbiome also encodes enzymes for the degradation of alginate, the main cell wall polysaccharide of brown algae. We undertook the functional characterization of diverse polysaccharide lyases from family PL17, frequently found in marine bacteria as well as those of human gut bacteria. We demonstrate here that this family is polyspecific. Our phylogenetic analysis of family PL17 reveals that all alginate lyases, which have all the same specificity and mode of action, cluster together in a very distinct subfamily. The alginate lyases found in human gut bacteria group together in a single clade which is rooted deeply in the PL17 tree. These enzymes were found in PULs containing PL6 enzymes, which also clustered together in the phylogenetic tree of PL6. Together, biochemical and bioinformatics analyses suggest that acquisition of this system appears ancient and, because only traces of two successful transfers were detected upon inspection of PL6 and PL17 families, the pace of acquisition of marine polysaccharide degradation system is probably very slow.

Superconducting fluctuations and characteristic time scales in amorphous WSi

NASA Astrophysics Data System (ADS)

Zhang, Xiaofu; Lita, Adriana E.; Sidorova, Mariia; Verma, Varun B.; Wang, Qiang; Nam, Sae Woo; Semenov, Alexei; Schilling, Andreas

2018-05-01

We study magnitudes and temperature dependencies of the electron-electron and electron-phonon interaction times which play the dominant role in the formation and relaxation of photon-induced hotspots in two-dimensional amorphous WSi films. The time constants are obtained through magnetoconductance measurements in a perpendicular magnetic field in the superconducting fluctuation regime and through time-resolved photoresponse to optical pulses. The excess magnetoconductivity is interpreted in terms of the weak-localization effect and superconducting fluctuations. Aslamazov-Larkin and Maki-Thompson superconducting fluctuations alone fail to reproduce the magnetic field dependence in the relatively high magnetic field range when the temperature is rather close to Tc because the suppression of the electronic density of states due to the formation of short-lifetime Cooper pairs needs to be considered. The time scale τi of inelastic scattering is ascribed to a combination of electron-electron (τe -e) and electron-phonon (τe -p h) interaction times, and a characteristic electron-fluctuation time (τe -f l) , which makes it possible to extract their magnitudes and temperature dependencies from the measured τi. The ratio of phonon-electron (τp h -e) and electron-phonon interaction times is obtained via measurements of the optical photoresponse of WSi microbridges. Relatively large τe -p h/τp h -e and τe -p h/τe -e ratios ensure that in WSi the photon energy is more efficiently confined in the electron subsystem than in other materials commonly used in the technology of superconducting nanowire single-photon detectors (SNSPDs). We discuss the impact of interaction times on the hotspot dynamics and compare relevant metrics of SNSPDs from different materials.

Transboundary transport of anthropogenic sulfur in PM2.5 at a coastal site in the Sea of Japan as studied by sulfur isotopic ratio measurement.

PubMed

Inomata, Yayoi; Ohizumi, Tsuyoshi; Take, Naoko; Sato, Keiichi; Nishikawa, Masataka

2016-05-15

Sulfur isotopic ratios (δ(34)S) in size separated aerosol particles (PM2.5 and coarse particles) were measured at Niigata-Maki facing the Sea of Japan. Non-sea salt δ(34)S (δ(34)Snss) in PM2.5 showed seasonal variations with relatively high values in winter (1.0-3.9‰ in spring, 2.8-4.5‰ in summer, 1.3-4.5‰ in autumn, 3.7-5.7‰ in winter). Taking into consideration air mass transport routes, δ(34)Snss in the air masses which originated in the Asian continent and were transported over the Sea of Japan to the monitoring sites were higher than those values for air masses which were transported over the Japanese islands after leaving the Asian continent for each season. Considering that the δ(34)Snss in sulfuric acid derived from domestic emissions in Japan are lower than those of δ(34)Snss in coal, the lower δ(34)Snss for the air mass transported over the Japanese islands suggest that sulfuric acid in PM2.5 modified the δ(34)Snss due to aerosol mixing with sulfuric acid in Japan. Material balance calculations suggested that the relative contribution of transboundary transport in winter was also higher than for other seasons (40-75% in spring, 51-63% in summer, 45-73% in autumn, and 53-81% in winter). In particular, the contribution to the air masses which were transported directly from the Asian continent was relatively large (75% in spring, 59% in autumn, 78% in winter) in comparison with that for the air masses which were transported over Japan. Copyright © 2016 Elsevier B.V. All rights reserved.

Restoration of Apollo Data by the NSSDC and the PDS Lunar Data Node

NASA Technical Reports Server (NTRS)

Williams, David R.; Hills, H. Kent; Lowman, Paul D.; Taylor, Patrick T.; Guinness, Edward A.

2011-01-01

The Lunar Data Node (LDN), under the auspices of the Geosciences Node of the Planetary Data System (PDS), is restoring Apollo data archived at the National Space Science Data Center. The Apollo data were arch ived on older media (7 -track tapes. microfilm, microfiche) and in ob solete digital formats, which limits use of the data. The LDN is maki ng these data accessible by restoring them to standard formats and archiving them through PDS. The restoration involves reading the older m edia, collecting supporting data (metadata), deciphering and understa nding the data, and organizing into a data set. The data undergo a pe er review before archive at PDS. We will give an update on last year' s work. We have scanned notebooks from Otto Berg, P.1. for the Lunar Ejecta and Meteorites Experiment. These notebooks contain information on the data and calibration coefficients which we hope to be able to use to restore the raw data into a usable archive. We have scanned Ap ollo 14 and 15 Dust Detector data from microfilm and are in the proce ss of archiving thc scans with PDS. We are also restoring raw dust de tector data from magnetic tape supplied by Yosio Nakamura (UT Austin) . Seiichi Nagihara (Texas Tech Univ.) and others in cooperation with NSSDC are recovering ARCSAV tapes (tapes containing raw data streams from all the ALSEP instruments). We will be preparing these data for archive with PDS. We are also in the process of recovering and archivi ng data not previously archived, from the Apollo 16 Gamma Ray Spectro meter and the Apollo 17 Infrared Spectrometer.

Character of cellulase activity in the guts of flagellate-free termites with different feeding habits.

PubMed

Li, Zhi-Qiang; Liu, Bing-Rong; Zeng, Wen-Hui; Xiao, Wei-Liang; Li, Qiu-Jian; Zhong, Jun-Hong

2013-01-01

Cellulose digestion in termites (Isoptera) is highly important for ecological reasons and applications in biofuel conversion. The speciose Termitidae family has lost flagellates in the hindgut and developed diverse feeding habits. To address the response of cellulase activity to the differentiation of feeding habits, a comparative study of the activity and distribution of composite cellulases, endo-β-1,4-glucanase, and β-glucosidase was performed in seven common flagellate-free termites with three feeding habits: the humus-feeding termites Sinocapritermes mushae (Oshima et Maki), Malaysiocapritermes zhangfengensis Zhu, Yang et Huang and Pericapritermes jiangtsekiangensis (Kemner); the fungus-growing termites Macrotermes barneyi Light and Odontotermes formosanus (Shiraki); and the wood-feeding termites Nasutitermes parvonasutus (Shiraki) and Havilanditermes orthonasus (Tsai et Chen). The results showed that in diverse feeding groups, the wood-feeding group had the highest total composite cellulase and endo-β-1,4-glucanase activities, while the fungus-growing group had the highest β-glucosidase activity. In terms of the distribution of cellulase activity in the alimentary canals, the cellulase activities in wood-feeding termites were concentrated in the midgut, but there was no significant difference between all gut segments in humus-feeding termites. As for the fungus-growing termites, the main site of composite cellulase activity was in the midgut. The endo-β-1,4-glucanase activity was restricted to the midgut, but the primary site of β-glucosidase activity was in the foregut and the midgut (Mac. barneyi). The functions of the gut segments apparently differentiated between feeding groups. The results suggest that the differentiation of feeding habits in flagellate-free termites was characterized by the distribution of cellulases in the gut rather than by variations in cellulase activity.

Character of Cellulase Activity in the Guts of Flagellate-Free Termites with Different Feeding Habits

PubMed Central

Li, Zhi-Qiang; Liu, Bing-Rong; Zeng, Wen-Hui; Xiao, Wei-Liang; Li, Qiu-Jian; Zhong, Jun-Hong

2013-01-01

Cellulose digestion in termites (Isoptera) is highly important for ecological reasons and applications in biofuel conversion. The speciose Termitidae family has lost flagellates in the hindgut and developed diverse feeding habits. To address the response of cellulase activity to the differentiation of feeding habits, a comparative study of the activity and distribution of composite cellulases, endo-β-1, 4-glucanase, and β-glucosidase was performed in seven common flagellate-free termites with three feeding habits: the humus-feeding termites Sinocapritermes mushae (Oshima et Maki), Malaysiocapritermes zhangfengensis Zhu, Yang et Huang and Pericapritermes jiangtsekiangensis (Kemner); the fungus-growing termites Macrotermes barneyi Light and Odontotermes formosanus (Shiraki); and the wood-feeding termites Nasutitermes parvonasutus (Shiraki) and Havilanditermes orthonasus (Tsai et Chen). The results showed that in diverse feeding groups, the wood-feeding group had the highest total composite cellulase and endo-β-1, 4-glucanase activities, while the fungus-growing group had the highest β-glucosidase activity. In terms of the distribution of cellulase activity in the alimentary canals, the cellulase activities in wood-feeding termites were concentrated in the midgut, but there was no significant difference between all gut segments in humus-feeding termites. As for the fungus-growing termites, the main site of composite cellulase activity was in the midgut. The endo-β-1, 4-glucanase activity was restricted to the midgut, but the primary site of β-glucosidase activity was in the foregut and the midgut (Mac. barneyi). The functions of the gut segments apparently differentiated between feeding groups. The results suggest that the differentiation of feeding habits in flagellate-free termites was characterized by the distribution of cellulases in the gut rather than by variations in cellulase activity. PMID:23895662

Study of types of some species of “Filaria” (Nematoda) parasites of small mammals described by von Linstow and Molin

PubMed Central

Guerrero, R.; Bain, O.

2011-01-01

Parasitic nematodes from the Berlin (ZMB) and Vienna (NMW) Museum collections referred to the genus Filaria Mueller, 1787 by von Linstow or Molin were studied. Three samples were in good condition and the specimens redescribed. Litomosa hepatica (von Linstow, 1897) n. comb., sample ZMB Vermes Entozoa 3368, from the megachiropteran Pteropus neohibernicus, Bismarck Archipelago, resembles L. maki Tibayrenc, Bain & Ramanchandran, 1979, from Pteropus vampyrus, in Malaysia, but the buccal capsule differs. Both species display particular morphological characters which differ from species of Litomosa parasitic in microchiropterans. The remaining material originates from Brazil. The spicule morphology of Litomosoides circularis (von Linstow, 1899) Chandler, 1931, sample ZMB Vermes Entozoa 1059 from Hesperomys spec. (= Holochilus brasiliensis), Porto Alegre, confirms that it belongs to the sigmodontis group; the microfilaria presents characters of the genus Litomosoides, e.g. body attenuated at both extremities and salient cephalic hook. Taxonomic discussions by others confirm that species of Litomosoides belonging to the sigmodontis group and described subsequently are distinct from L. circularis. Litomosoides serpicula (Molin, 1858) Guerrero, Martin, Gardner & Bain, 2002, is redescribed, sample NMW 6323 from the bat Phyllostoma spiculatum (= Sturnira lilium), Ypanema. It is very close to L. brasiliensis Almeida, 1936, type host Moytis sp., but distinguished by a single ring in the buccal capsule, rather than two, supporting previous conclusions that the taxon L. brasiliensis, as generally regarded, may represent a complex of species. Samples NMW 6322 and NMW 6324, from other bats and also identified by Molin (1858) as Filaria serpicula, contain unidentifiable fragments of Litomosoides incertae sedis. Filaria hyalina von Linstow, 1890, sample ZMB Vermes Entozoa Q 3905 from Sorex vulgaris (= Sorex araneus), is incertae sedis because it contains two unidentifiable posterior parts of male, which might be an acuarid, Stammerinema sp. Filaria vesperuginis von Linstow, 1885, sample ZMB Vermes Entozoa Q 3929, from the bat Vesperugo serotinus (= Eptesicus serotinus), contains encysted nematode larvae and is a nomen dubium. PMID:21678791

Effect of fluctuations on the NMR relaxation beyond the Abrikosov vortex state

DOE PAGES

Glatz, A.; Galda, A.; Varlamov, A. A.

2015-08-25

Here, the effect of fluctuations on the nuclear magnetic resonance (NMR) relaxation rate W = T –1 1 is studied in a complete phase diagram of a two-dimensional superconductor above the upper critical field line H c2(T). In the region of relatively high temperatures and low magnetic fields, the relaxation rate W is determined by two competing effects. The first one is its decrease in the result of suppression of the quasiparticle density of states (DOS) due to formation of fluctuation Cooper pairs (FCPs). The second one is a specific, purely quantum relaxation process of the Maki-Thompson (MT) type, whichmore » for low field leads to an increase of the relaxation rate. The latter describes particular fluctuation processes involving self-pairing of a single electron on self-intersecting trajectories of a size up to phase-breaking length ℓ Φ which becomes possible due to an electron spin-flip scattering event at a nucleus. As a result, different scenarios with either growth or decrease of the NMR relaxation rate are possible upon approaching the normal-metal–type-II superconductor transition. The character of fluctuations changes along the line H c2(T) from the thermal long-wavelength type in weak magnetic fields to the clusters of rotating FCPs in fields comparable to Hc2(0). We find that below the well-defined temperature T* 0 ≈ 0.6T c0, the MT process becomes ineffective even in the absence of intrinsic pair breaking. The small scale of the FCP rotations ξ xy in such high fields impedes formation of long (≲ℓ Φ) self-intersecting trajectories, causing the corresponding relaxation mechanism to lose its efficiency. This reduces the effect of superconducting fluctuations in the domain of high fields and low temperatures to just the suppression of quasiparticle DOS, analogous to the Abrikosov vortex phase below the H c2(T) line.« less

Upper critical fields and superconducting transition temperatures of some zirconium-base amorphous transition-metal alloys

NASA Astrophysics Data System (ADS)

Karkut, M. G.; Hake, R. R.

1983-08-01

Superconducting upper critical fields Hc2(T), transition temperatures Tc and normal-state electrical resistivities ρn have been measured in the amorphous transition-metal alloy series Zr1-xCox, Zr1-xNix, (Zr1-xTix)0.78Ni0.22, and (Zr1-xNbx)0.78Ni0.22. Structural integrity of these melt-spun alloys is indicated by x-ray, density, bend-ductility, normal-state electrical resistivity, superconducting transition width, and mixed-state flux-pinning measurements. The specimens display Tc=2.1-3.8 K, ρn=159-190 μΩ cm, and |(dHc2dT)Tc|=28-36 kG/K. These imply electron mean free paths l~2-6 Å, zero-temperature Ginzburg-Landau coherence distances ξG0~50-70 Å, penetration depths λG0~(7-10)×103 Å, and extremely high dirtiness parameters ξ0l~300-1300. All alloys display Hc2(T) curves with negative curvature and (with two exceptions) fair agreement with the standard dirty-limit theory of Werthamer, Helfand, Hohenberg, and Maki (WHHM) for physically reasonable values of spin-orbit-coupling induced, electron-spin-flip scattering time τso. This is in contrast to the anomalously elevated Hc2(T) behavior which is nearly linear in T that is observed by some, and the unphysically low-τso fits to WHHM theory obtained by others, for various amorphous alloys. Current ideas that such anomalies may be due to alloy inhomogeneity are supported by present results on two specimens for which relatively low-τso fits of Hc2(T) to WHHM theory are coupled with superconductive evidence for inhomogeneity: relatively broad transitions at Tc and Hc2 current-density-dependent transitions at Hc2 and (in one specimen) a J-dependent, high-H (>Hc2), resistive "beak effect." In the Zr1-xCox and Zr1-xNix series, Tc decreases linearly with x (and with unfilled-shell average electron-to-atom ratio < ea > in the range 5.05<=< ea ><=6.40 in fair agreement with previous results for these systems and contrary to the Tc vs < ea > behavior of both amorphous and crystalline transition-metal alloys formed between near neighbors in the Periodic Table. Upper-critical-field and normal-state electrical resistivity measurements suggest that the molar electronic specific-heat coefficient γm decreases with x in parallel with Tc in the Zr1-xCox and Zr1-xNix series. In the equal-< ea > (Zr1-xTix)0.78Ni0.22 system, Tc decreases with x; in the (Zr1-xNbx)0.78Ni0.22 system, Tc first increases and then decreases with x (hence with < ea >). These diverse < ea > dependencies of Tc appear consistent with the ultraviolet-photoemission-spectroscopy indicated split-band model of such amorphous transition-metal alloys and the associated idea that the alloying dependence of Tc cannot be described by general Tc vs < ea > rules.

Radio Wave Generation by a Collision or Contact between Various Materials

NASA Astrophysics Data System (ADS)

Takano, T.; Hanawa, R.; Saegusa, K.; Ikeda, H.

2014-12-01

In fracture of rock, radio wave emission was found experimentally [1]. This phenomenon could be used to detect a rock fracture during an earthquake or a volcanic activity [2]. The cause of the radio wave is expected to be micro-discharges, which are generated by an inhomogeneous potential distribution around micro-cracks. In order to better understand the phenomena and clarify the cause of radio wave emission, we carried out experiments to detect the emission in the cases of a collision or contact between various materials. We used receiving systems with great sensitivities and sufficient frequency bandwidths at 1 MHz-, 300 MHz-, 2 GHz-, and 18 GHz-bands. The specimen materials are as follows: Steel (2) Brass (3) Copper (4)Small coin (5)Celluloid. We obtained the following results: The signal was detected for the specimen of (1) to (4), but not for (5). The signal is composed of intermittent spikes which include waves with a frequency close to the center frequency of each frequency band. The power is strongest at the lower frequencies among all frequency bands. The more details will be given in the presentation. The origin of radio wave emission from the metal is supposed to be discharges between materials in these experiments. It is surprising that even a small coin can generate a significant amount of radio wave. Accordingly, it is inferred that all amount of charges are discharged through a conductive metal. On the other hand, celluloid did not generate radio wave, though the specimen was sufficiently charged by brushing. It is inferred that a quite localized charge was discharged but the remaining charges were blocked due to poor conductivity. Extending this hypothesis, large-scale contact should have occurred between broken fragments for the radio wave generation in the aforementioned rock fracture experiments. Turbulence of the fragments is a candidate for the explanation. [1] K. Maki et al., "An experimental study of microwave emission from compression failure of rocks" (in Japanese), Jour. of the Seismological Society of Japan, vol.58, no.4, pp.375-384, 2006.[2] T. Takano al., "Detection of microwave emission due to rock fracture as a new tool for geophysics: A field test at a volcano in Miyake Island, Japan", Journal of Applied Geophysics, 94, pp.1-14, 2013.

The distribution of atomic hydrogen and oxygen in the magnetosphere of Saturn

NASA Astrophysics Data System (ADS)

Melin, Henrik; Shemansky, Don E.; Liu, Xianming

2009-12-01

The intensity of H Ly α1216A˚ ( 2P- 1S) and OI 1304A˚ ( 2p33s3S-2p4P) is mapped in the magnetosphere of Saturn using the ultraviolet imaging spectrograph (UVIS) [Esposito, L.W., Barth, C.A., Colwell, J.E., Lawrence, G.M., McClintock, W.E., Stewart, A.I.F., Keller, H.U., Korth, A., Lauche, H., Festou, M.C., Lane, A.L., Hansen, C.J., Maki, J.N., West, R.A., Jahn, H., Reulke, R., Warlich, K., Shemansky, D.E., Yung, Y.L., 2004. The Cassini ultraviolet imaging spectrograph investigation. Space Science Reviews 115, 299-361] onboard Cassini. Spatial coverage is built up by stepping the slit sequentially across the system (system scan). Data are obtained at a large range of space-craft-Saturn distances. The observed atomic hydrogen distribution is very broad, extending beyond 40RS in the equatorial plane, with the intensity increasing with decreasing distances to Saturn. The distribution displays persistent local-time asymmetries, and is seen connecting continuously to the upper atmosphere of the planet at sub-solar latitudes located well outside of the equatorial (ring) plane. This is consistent with the source of the atomic hydrogen being located at the top of the atmosphere on the sun-lit side of the planet on the southern hemisphere. In addition there are a number of temporally persistent features in the intensity distribution, indicating a complex hydrogen energy distribution. The emission from OI 1304A˚ is generally distributed as a broad torus centered around ˜4RS although the position of the peak intensity can vary by as much as ±1RS. There is significant intensity present out to ±10RS. HST observations of hydroxyl (OH) are re-analyzed and display a distribution half as broad as that of oxygen, also centered at 4RS. The observed atomic oxygen distribution requires a sourcing of 1.3×1028atomss-1 against loss due to charge capture with the plasma. Using the ion partitioning of Schippers et al. [2008. Multi-instrument analysis of electron populations in Saturn's magnetosphere. Journal of Geophysical Research (Space Physics) 113 (A12) 7208-+] then recombination of H2O+ and H3O+ will account for about a quarter of the mass-loss in the inner magnetosphere, with charge capture of O+ accounting for the rest. The oxygen loss rate is seen to vary by 2×1027atomss-1 over periods of weeks.

Utility usage forecasting

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

Hosking, Jonathan R. M.; Natarajan, Ramesh

The computer creates a utility demand forecast model for weather parameters by receiving a plurality of utility parameter values, wherein each received utility parameter value corresponds to a weather parameter value. Determining that a range of weather parameter values lacks a sufficient amount of corresponding received utility parameter values. Determining one or more utility parameter values that corresponds to the range of weather parameter values. Creating a model which correlates the received and the determined utility parameter values with the corresponding weather parameters values.

Parameter screening: the use of a dummy parameter to identify non-influential parameters in a global sensitivity analysis

NASA Astrophysics Data System (ADS)

Khorashadi Zadeh, Farkhondeh; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2017-04-01

Parameter estimation is a major concern in hydrological modeling, which may limit the use of complex simulators with a large number of parameters. To support the selection of parameters to include in or exclude from the calibration process, Global Sensitivity Analysis (GSA) is widely applied in modeling practices. Based on the results of GSA, the influential and the non-influential parameters are identified (i.e. parameters screening). Nevertheless, the choice of the screening threshold below which parameters are considered non-influential is a critical issue, which has recently received more attention in GSA literature. In theory, the sensitivity index of a non-influential parameter has a value of zero. However, since numerical approximations, rather than analytical solutions, are utilized in GSA methods to calculate the sensitivity indices, small but non-zero indices may be obtained for the indices of non-influential parameters. In order to assess the threshold that identifies non-influential parameters in GSA methods, we propose to calculate the sensitivity index of a "dummy parameter". This dummy parameter has no influence on the model output, but will have a non-zero sensitivity index, representing the error due to the numerical approximation. Hence, the parameters whose indices are above the sensitivity index of the dummy parameter can be classified as influential, whereas the parameters whose indices are below this index are within the range of the numerical error and should be considered as non-influential. To demonstrated the effectiveness of the proposed "dummy parameter approach", 26 parameters of a Soil and Water Assessment Tool (SWAT) model are selected to be analyzed and screened, using the variance-based Sobol' and moment-independent PAWN methods. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. Moreover, the calculation does not even require additional model evaluations for the Sobol' method. A formal statistical test validates these parameter screening results. Based on the dummy parameter screening, 11 model parameters are identified as influential. Therefore, it can be denoted that the "dummy parameter approach" can facilitate the parameter screening process and provide guidance for GSA users to define a screening-threshold, with only limited additional resources. Key words: Parameter screening, Global sensitivity analysis, Dummy parameter, Variance-based method, Moment-independent method

Knowledge system and method for simulating chemical controlled release device performance

DOEpatents

Cowan, Christina E.; Van Voris, Peter; Streile, Gary P.; Cataldo, Dominic A.; Burton, Frederick G.

1991-01-01

A knowledge system for simulating the performance of a controlled release device is provided. The system includes an input device through which the user selectively inputs one or more data parameters. The data parameters comprise first parameters including device parameters, media parameters, active chemical parameters and device release rate; and second parameters including the minimum effective inhibition zone of the device and the effective lifetime of the device. The system also includes a judgemental knowledge base which includes logic for 1) determining at least one of the second parameters from the release rate and the first parameters and 2) determining at least one of the first parameters from the other of the first parameters and the second parameters. The system further includes a device for displaying the results of the determinations to the user.

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Generalized Grueneisen tensor from solid nonlinearity parameters

NASA Technical Reports Server (NTRS)

Cantrell, J. H., Jr.

1980-01-01

Anharmonic effects in solids are often described in terms of generalized Grueneisen parameters which measure the strain dependence of the lattice vibrational frequencies. The relationship between these parameters and the solid nonlinearity parameters measured directly in ultrasonic harmonic generation experiments is derived using an approach valid for normal-mode elastic wave propagation in any crystalline direction. The resulting generalized Grueneisen parameters are purely isentropic in contrast to the Brugger-Grueneisen parameters which are of a mixed thermodynamic state. Experimental data comparing the isentropic generalized Grueneisen parameters and the Brugger-Grueneisen parameters are presented.

Optimisation of shock absorber process parameters using failure mode and effect analysis and genetic algorithm

NASA Astrophysics Data System (ADS)

Mariajayaprakash, Arokiasamy; Senthilvelan, Thiyagarajan; Vivekananthan, Krishnapillai Ponnambal

2013-07-01

The various process parameters affecting the quality characteristics of the shock absorber during the process were identified using the Ishikawa diagram and by failure mode and effect analysis. The identified process parameters are welding process parameters (squeeze, heat control, wheel speed, and air pressure), damper sealing process parameters (load, hydraulic pressure, air pressure, and fixture height), washing process parameters (total alkalinity, temperature, pH value of rinsing water, and timing), and painting process parameters (flowability, coating thickness, pointage, and temperature). In this paper, the process parameters, namely, painting and washing process parameters, are optimized by Taguchi method. Though the defects are reasonably minimized by Taguchi method, in order to achieve zero defects during the processes, genetic algorithm technique is applied on the optimized parameters obtained by Taguchi method.

Stochastic control system parameter identifiability

NASA Technical Reports Server (NTRS)

Lee, C. H.; Herget, C. J.

1975-01-01

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters.

PubMed

Liang, Yuzhen; Torralba-Sanchez, Tifany L; Di Toro, Dominic M

2018-04-18

Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

The modified extended Hansen method to determine partial solubility parameters of drugs containing a single hydrogen bonding group and their sodium derivatives: benzoic acid/Na and ibuprofen/Na.

PubMed

Bustamante, P; Pena, M A; Barra, J

2000-01-20

Sodium salts are often used in drug formulation but their partial solubility parameters are not available. Sodium alters the physical properties of the drug and the knowledge of these parameters would help to predict adhesion properties that cannot be estimated using the solubility parameters of the parent acid. This work tests the applicability of the modified extended Hansen method to determine partial solubility parameters of sodium salts of acidic drugs containing a single hydrogen bonding group (ibuprofen, sodium ibuprofen, benzoic acid and sodium benzoate). The method uses a regression analysis of the logarithm of the experimental mole fraction solubility of the drug against the partial solubility parameters of the solvents, using models with three and four parameters. The solubility of the drugs was determined in a set of solvents representative of several chemical classes, ranging from low to high solubility parameter values. The best results were obtained with the four parameter model for the acidic drugs and with the three parameter model for the sodium derivatives. The four parameter model includes both a Lewis-acid and a Lewis-base term. Since the Lewis acid properties of the sodium derivatives are blocked by sodium, the three parameter model is recommended for these kind of compounds. Comparison of the parameters obtained shows that sodium greatly changes the polar parameters whereas the dispersion parameter is not much affected. Consequently the total solubility parameters of the salts are larger than for the parent acids in good agreement with the larger hydrophilicity expected from the introduction of sodium. The results indicate that the modified extended Hansen method can be applied to determine the partial solubility parameters of acidic drugs and their sodium salts.

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

Liu, Y.; Liu, Z.; Zhang, S.

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

Simultaneous Estimation of Microphysical Parameters and Atmospheric State Variables With Radar Data and Ensemble Square-root Kalman Filter

NASA Astrophysics Data System (ADS)

Tong, M.; Xue, M.

2006-12-01

An important source of model error for convective-scale data assimilation and prediction is microphysical parameterization. This study investigates the possibility of estimating up to five fundamental microphysical parameters, which are closely involved in the definition of drop size distribution of microphysical species in a commonly used single-moment ice microphysics scheme, using radar observations and the ensemble Kalman filter method. The five parameters include the intercept parameters for rain, snow and hail/graupel, and the bulk densities of hail/graupel and snow. Parameter sensitivity and identifiability are first examined. The ensemble square-root Kalman filter (EnSRF) is employed for simultaneous state and parameter estimation. OSS experiments are performed for a model-simulated supercell storm, in which the five microphysical parameters are estimated individually or in different combinations starting from different initial guesses. When error exists in only one of the microphysical parameters, the parameter can be successfully estimated without exception. The estimation of multiple parameters is found to be less robust, with end results of estimation being sensitive to the realization of the initial parameter perturbation. This is believed to be because of the reduced parameter identifiability and the existence of non-unique solutions. The results of state estimation are, however, always improved when simultaneous parameter estimation is performed, even when the estimated parameters values are not accurate.

Cognitive models of risky choice: parameter stability and predictive accuracy of prospect theory.

PubMed

Glöckner, Andreas; Pachur, Thorsten

2012-04-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are individual differences as measured by model parameters stable enough to improve the ability to predict behavior as compared to modeling without adjustable parameters? We examined this issue in cumulative prospect theory (CPT), arguably the most widely used framework to model decisions under risk. Specifically, we examined (a) the temporal stability of CPT's parameters; and (b) how well different implementations of CPT, varying in the number of adjustable parameters, predict individual choice relative to models with no adjustable parameters (such as CPT with fixed parameters, expected value theory, and various heuristics). We presented participants with risky choice problems and fitted CPT to each individual's choices in two separate sessions (which were 1 week apart). All parameters were correlated across time, in particular when using a simple implementation of CPT. CPT allowing for individual variability in parameter values predicted individual choice better than CPT with fixed parameters, expected value theory, and the heuristics. CPT's parameters thus seem to pick up stable individual differences that need to be considered when predicting risky choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of the IRT Parameter Invariance Property for the MCAT.

ERIC Educational Resources Information Center

Kelkar, Vinaya; Wightman, Linda F.; Luecht, Richard M.

The purpose of this study was to investigate the viability of the property of parameter invariance for the one-parameter (1P), two-parameter (2P), and three-parameter (3P) item response theory (IRT) models for the Medical College Admissions Tests (MCAT). Invariance of item parameters across different gender, ethnic, and language groups and the…

On Interpreting the Model Parameters for the Three Parameter Logistic Model

ERIC Educational Resources Information Center

Maris, Gunter; Bechger, Timo

2009-01-01

This paper addresses two problems relating to the interpretability of the model parameters in the three parameter logistic model. First, it is shown that if the values of the discrimination parameters are all the same, the remaining parameters are nonidentifiable in a nontrivial way that involves not only ability and item difficulty, but also the…

An improved state-parameter analysis of ecosystem models using data assimilation

USGS Publications Warehouse

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the simultaneous parameter estimation procedure significantly improves model predictions. Results also show that the SEnKF can dramatically reduce the variance in state variables stemming from the uncertainty of parameters and driving variables. The SEnKF is a robust and effective algorithm in evaluating and developing ecosystem models and in improving the understanding and quantification of carbon cycle parameters and processes. ?? 2008 Elsevier B.V.

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Classification of hydrological parameter sensitivity and evaluation of parameter transferability across 431 US MOPEX basins

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

Ren, Huiying; Hou, Zhangshuan; Huang, Maoyi

The Community Land Model (CLM) represents physical, chemical, and biological processes of the terrestrial ecosystems that interact with climate across a range of spatial and temporal scales. As CLM includes numerous sub-models and associated parameters, the high-dimensional parameter space presents a formidable challenge for quantifying uncertainty and improving Earth system predictions needed to assess environmental changes and risks. This study aims to evaluate the potential of transferring hydrologic model parameters in CLM through sensitivity analyses and classification across watersheds from the Model Parameter Estimation Experiment (MOPEX) in the United States. The sensitivity of CLM-simulated water and energy fluxes to hydrologicalmore » parameters across 431 MOPEX basins are first examined using an efficient stochastic sampling-based sensitivity analysis approach. Linear, interaction, and high-order nonlinear impacts are all identified via statistical tests and stepwise backward removal parameter screening. The basins are then classified accordingly to their parameter sensitivity patterns (internal attributes), as well as their hydrologic indices/attributes (external hydrologic factors) separately, using a Principal component analyses (PCA) and expectation-maximization (EM) –based clustering approach. Similarities and differences among the parameter sensitivity-based classification system (S-Class), the hydrologic indices-based classification (H-Class), and the Koppen climate classification systems (K-Class) are discussed. Within each S-class with similar parameter sensitivity characteristics, similar inversion modeling setups can be used for parameter calibration, and the parameters and their contribution or significance to water and energy cycling may also be more transferrable. This classification study provides guidance on identifiable parameters, and on parameterization and inverse model design for CLM but the methodology is applicable to other models. Inverting parameters at representative sites belonging to the same class can significantly reduce parameter calibration efforts.« less

A comparison between two powder compaction parameters of plasticity: the effective medium A parameter and the Heckel 1/K parameter.

PubMed

Mahmoodi, Foad; Klevan, Ingvild; Nordström, Josefina; Alderborn, Göran; Frenning, Göran

2013-09-10

The purpose of the research was to introduce a procedure to derive a powder compression parameter (EM A) representing particle yield stress using an effective medium equation and to compare the EM A parameter with the Heckel compression parameter (1/K). 16 pharmaceutical powders, including drugs and excipients, were compressed in a materials testing instrument and powder compression profiles were derived using the EM and Heckel equations. The compression profiles thus obtained could be sub-divided into regions among which one region was approximately linear and from this region, the compression parameters EM A and 1/K were calculated. A linear relationship between the EM A parameter and the 1/K parameter was obtained with a strong correlation. The slope of the plot was close to 1 (0.84) and the intercept of the plot was small in comparison to the range of parameter values obtained. The relationship between the theoretical EM A parameter and the 1/K parameter supports the interpretation of the empirical Heckel parameter as being a measure of yield stress. It is concluded that the combination of Heckel and EM equations represents a suitable procedure to derive a value of particle plasticity from powder compression data. Copyright © 2013 Elsevier B.V. All rights reserved.

The evolution of Zipf's law indicative of city development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2016-02-01

Zipf's law of city-size distributions can be expressed by three types of mathematical models: one-parameter form, two-parameter form, and three-parameter form. The one-parameter and one of the two-parameter models are familiar to urban scientists. However, the three-parameter model and another type of two-parameter model have not attracted attention. This paper is devoted to exploring the conditions and scopes of application of these Zipf models. By mathematical reasoning and empirical analysis, new discoveries are made as follows. First, if the size distribution of cities in a geographical region cannot be described with the one- or two-parameter model, maybe it can be characterized by the three-parameter model with a scaling factor and a scale-translational factor. Second, all these Zipf models can be unified by hierarchical scaling laws based on cascade structure. Third, the patterns of city-size distributions seem to evolve from three-parameter mode to two-parameter mode, and then to one-parameter mode. Four-year census data of Chinese cities are employed to verify the three-parameter Zipf's law and the corresponding hierarchical structure of rank-size distributions. This study is revealing for people to understand the scientific laws of social systems and the property of urban development.

System and method for motor parameter estimation

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

Luhrs, Bin; Yan, Ting

2014-03-18

A system and method for determining unknown values of certain motor parameters includes a motor input device connectable to an electric motor having associated therewith values for known motor parameters and an unknown value of at least one motor parameter. The motor input device includes a processing unit that receives a first input from the electric motor comprising values for the known motor parameters for the electric motor and receive a second input comprising motor data on a plurality of reference motors, including values for motor parameters corresponding to the known motor parameters of the electric motor and values formore » motor parameters corresponding to the at least one unknown motor parameter value of the electric motor. The processor determines the unknown value of the at least one motor parameter from the first input and the second input and determines a motor management strategy for the electric motor based thereon.« less

Dynamics of a neuron model in different two-dimensional parameter-spaces

NASA Astrophysics Data System (ADS)

Rech, Paulo C.

2011-03-01

We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.

Study the effect of chemical reaction and variable viscosity on free convection MHD radiating flow over an inclined plate bounded by porous medium

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

Ali, M., E-mail: ali.mehidi93@gmail.com; Department of Mathematics, Chittagong University of Engineering and Technology, Chittagong-4349; Alim, M. A., E-mail: maalim@math.buet.ac.bd

An analysis is performed to study the free convection heat and mass transfer flow of an electrically conducting incompressible viscous fluid about a semi-infinite inclined porous plate under the action of radiation, chemical reaction in presence of magnetic field with variable viscosity. The dimensionless governing equations are steady, two-dimensional coupled and non-linear ordinary differential equation. Nachtsgeim-Swigert shooting iteration technique along with Runge-Kutta integration scheme is used to solve the non-dimensional governing equations. The effects of magnetic parameter, viscosity parameter and chemical reaction parameter on velocity, temperature and concentration profiles are discussed numerically and shown graphically. Therefore, the results of velocitymore » profile decreases for increasing values of magnetic parameter and viscosity parameter but there is no effect for reaction parameter. The temperature profile decreases in presence of magnetic parameter, viscosity parameter and Prandtl number but increases for radiation parameter. Also, concentration profile decreases for the increasing values of magnetic parameter, viscosity parameter and reaction parameter. All numerical calculations are done with respect to salt water and fixed angle of inclination of the plate.« less

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process.

PubMed

Deng, Bo; Shi, Yaoyao; Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-31

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

PubMed Central

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Models for estimating photosynthesis parameters from in situ production profiles

NASA Astrophysics Data System (ADS)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of photosynthesis irradiance functions and parameters for modeling in situ production profiles. In light of the results obtained in this work we argue that the choice of the primary production model should reflect the available data and these models should be data driven regarding parameter estimation.

Hansen solubility parameters for polyethylene glycols by inverse gas chromatography.

PubMed

Adamska, Katarzyna; Voelkel, Adam

2006-11-03

Inverse gas chromatography (IGC) has been applied to determine solubility parameter and its components for nonionic surfactants--polyethylene glycols (PEG) of different molecular weight. Flory-Huggins interaction parameter (chi) and solubility parameter (delta(2)) were calculated according to DiPaola-Baranyi and Guillet method from experimentally collected retention data for the series of carefully selected test solutes. The Hansen's three-dimensional solubility parameters concept was applied to determine components (delta(d), delta(p), delta(h)) of corrected solubility parameter (delta(T)). The molecular weight and temperature of measurement influence the solubility parameter data, estimated from the slope, intercept and total solubility parameter. The solubility parameters calculated from the intercept are lower than those calculated from the slope. Temperature and structural dependences of the entopic factor (chi(S)) are presented and discussed.

Inverse gas chromatographic determination of solubility parameters of excipients.

PubMed

Adamska, Katarzyna; Voelkel, Adam

2005-11-04

The principle aim of this work was an application of inverse gas chromatography (IGC) for the estimation of solubility parameter for pharmaceutical excipients. The retention data of number of test solutes were used to calculate Flory-Huggins interaction parameter (chi1,2infinity) and than solubility parameter (delta2), corrected solubility parameter (deltaT) and its components (deltad, deltap, deltah) by using different procedures. The influence of different values of test solutes solubility parameter (delta1) over calculated values was estimated. The solubility parameter values obtained for all excipients from the slope, from Guillet and co-workers' procedure are higher than that obtained from components according Voelkel and Janas procedure. It was found that solubility parameter's value of the test solutes influences, but not significantly, values of solubility parameter of excipients.

Bayesian Parameter Estimation for Heavy-Duty Vehicles

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

Miller, Eric; Konan, Arnaud; Duran, Adam

2017-03-28

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

PubMed

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

FY2014 Parameters for Helions and Gold Ions in Booster, AGS, and RHIC

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

Gardner, C. J.

The nominal parameters for helions (helion is the bound state of two protons and one neutron, the nucleus of a helium-3 atom) and gold ions in Booster, AGS, and RHIC are given for the FY2014 running period. The parameters are found using various formulas to derive mass, helion anomalous g-factor, kinetic parameters, RF parameters, ring parameters, etc..

Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

NASA Astrophysics Data System (ADS)

Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

2018-05-01

The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced efficiency. Testing the parameter transferability using criteria of similar climate and flow characteristics at ungauged catchments and comparisons with predictions from a priori parameters are a novelty. The ultimate limitations of both approaches are recognized and recommendations are made for future research.

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

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

Buchheit, Thomas E.; Wilcox, Ian Zachary; Sandoval, Andrew J

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction andmore » portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.« less

On Markov parameters in system identification

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

1991-01-01

A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

USGS Publications Warehouse

Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

A note on some statistical properties of rise time parameters used in muon arrival time measurements

NASA Technical Reports Server (NTRS)

Vanderwalt, D. J.; Devilliers, E. J.

1985-01-01

Most investigations of the muon arrival time distribution in EAS during the past decade made use of parameters which can collectively be called rise time parameters. The rise time parameter T sub A/B is defined as the time taken for the integrated pulse from a detector to rise from A% to B% of its full amplitude. The use of these parameters are usually restricted to the determination of the radial dependence thereof. This radial dependence of the rise time parameters are usually taken as a signature of the particle interaction characteristics in the shower. As these parameters have a stochastic nature, it seems reasonable that one should also take notice of this aspect of the rise time parameters. A statistical approach to rise time parameters is presented.

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

Quantitative analysis of vascular parameters for micro-CT imaging of vascular networks with multi-resolution.

PubMed

Zhao, Fengjun; Liang, Jimin; Chen, Xueli; Liu, Junting; Chen, Dongmei; Yang, Xiang; Tian, Jie

2016-03-01

Previous studies showed that all the vascular parameters from both the morphological and topological parameters were affected with the altering of imaging resolutions. However, neither the sensitivity analysis of the vascular parameters at multiple resolutions nor the distinguishability estimation of vascular parameters from different data groups has been discussed. In this paper, we proposed a quantitative analysis method of vascular parameters for vascular networks of multi-resolution, by analyzing the sensitivity of vascular parameters at multiple resolutions and estimating the distinguishability of vascular parameters from different data groups. Combining the sensitivity and distinguishability, we designed a hybrid formulation to estimate the integrated performance of vascular parameters in a multi-resolution framework. Among the vascular parameters, degree of anisotropy and junction degree were two insensitive parameters that were nearly irrelevant with resolution degradation; vascular area, connectivity density, vascular length, vascular junction and segment number were five parameters that could better distinguish the vascular networks from different groups and abide by the ground truth. Vascular area, connectivity density, vascular length and segment number not only were insensitive to multi-resolution but could also better distinguish vascular networks from different groups, which provided guidance for the quantification of the vascular networks in multi-resolution frameworks.

Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system

USGS Publications Warehouse

Tiedeman, C.R.; Hill, M.C.; D'Agnese, F. A.; Faunt, C.C.

2003-01-01

Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new "value of improved information" (VOII) method presented here, which includes the effects of parameter correlation in addition to individual parameter uncertainty and prediction sensitivity. In this work, the PSS and VOII methods are demonstrated and evaluated using a model of the Death Valley regional groundwater flow system. The predictions of interest are advective transport paths originating at sites of past underground nuclear testing. Results show that for two paths evaluated the most important parameters include a subset of five or six of the 23 defined model parameters. Some of the parameters identified as most important are associated with flow system attributes that do not lie in the immediate vicinity of the paths. Results also indicate that the PSS and VOII methods can identify different important parameters. Because the methods emphasize somewhat different criteria for parameter importance, it is suggested that parameters identified by both methods be carefully considered in subsequent data collection efforts aimed at improving model predictions.

Practical identifiability analysis of a minimal cardiovascular system model.

PubMed

Pironet, Antoine; Docherty, Paul D; Dauby, Pierre C; Chase, J Geoffrey; Desaive, Thomas

2017-01-17

Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. Copyright © 2017. Published by Elsevier B.V.

Application of identified sensitive physical parameters in reducing the uncertainty of numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2016-04-01

An important source of uncertainty, which then causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. There are many physical parameters in numerical models in the atmospheric and oceanic sciences, and it would cost a great deal to reduce uncertainties in all physical parameters. Therefore, finding a subset of these parameters, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach. The results imply that nonlinear interactions among parameters play a key role in the uncertainty of numerical simulations in arid and semi-arid regions of China compared to those in northern, northeastern and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Sherborne Missile Fire Frequency with Unconstraint Parameters

NASA Astrophysics Data System (ADS)

Dong, Shaquan

2018-01-01

For the modeling problem of shipborne missile fire frequency, the fire frequency models with unconstant parameters were proposed, including maximum fire frequency models with unconstant parameters, and actual fire frequency models with unconstant parameters, which can be used to calculate the missile fire frequency with unconstant parameters.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

A Phenomenological Model for Circadian and Sleep Allostatic Modulation of Plasma Cortisol Concentration

DTIC Science & Technology

2012-09-25

amplitudes of the model’s produc- tion parameters (w, , s) and degradation parameters (kp, dc) because the estimates for all of these parameters... degradation parameters (kp, dc), because the estimates for all of these parameters are higher for group A than for group C. E1194 A MODEL OF...values of both production and degradation parameters (Table 3), but there is significant variability between subjects that is caused by underlying

A study of parameter identification

NASA Technical Reports Server (NTRS)

Herget, C. J.; Patterson, R. E., III

1978-01-01

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Dynamics in the Parameter Space of a Neuron Model

NASA Astrophysics Data System (ADS)

Paulo, C. Rech

2012-06-01

Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.

A practical iterative PID tuning method for mechanical systems using parameter chart

NASA Astrophysics Data System (ADS)

Kang, M.; Cheong, J.; Do, H. M.; Son, Y.; Niculescu, S.-I.

2017-10-01

In this paper, we propose a method of iterative proportional-integral-derivative parameter tuning for mechanical systems that possibly possess hidden mechanical resonances, using a parameter chart which visualises the closed-loop characteristics in a 2D parameter space. We employ a hypothetical assumption that the considered mechanical systems have their upper limit of the derivative feedback gain, from which the feasible region in the parameter chart becomes fairly reduced and thus the gain selection can be extremely simplified. Then, a two-directional parameter search is carried out within the feasible region in order to find the best set of parameters. Experimental results show the validity of the assumption used and the proposed parameter tuning method.

Some properties of a 5-parameter bivariate probability distribution

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.; Smith, O. E.

1983-01-01

A five-parameter bivariate gamma distribution having two shape parameters, two location parameters and a correlation parameter was developed. This more general bivariate gamma distribution reduces to the known four-parameter distribution. The five-parameter distribution gives a better fit to the gust data. The statistical properties of this general bivariate gamma distribution and a hypothesis test were investigated. Although these developments have come too late in the Shuttle program to be used directly as design criteria for ascent wind gust loads, the new wind gust model has helped to explain the wind profile conditions which cause large dynamic loads. Other potential applications of the newly developed five-parameter bivariate gamma distribution are in the areas of reliability theory, signal noise, and vibration mechanics.

Systems and methods for optimal power flow on a radial network

DOEpatents

Low, Steven H.; Peng, Qiuyu

2018-04-24

Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo

2017-08-01

This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.

An enhancement to the NA4 gear vibration diagnostic parameter

NASA Technical Reports Server (NTRS)

Decker, Harry J.; Handschuh, Robert F.; Zakrajsek, James J.

1994-01-01

A new vibration diagnostic parameter for health monitoring of gears, NA4*, is proposed and tested. A recently developed gear vibration diagnostic parameter NA4 outperformed other fault detection methods at indicating the start and initial progression of damage. However, in some cases, as the damage progressed, the sensitivity of the NA4 and FM4 parameters tended to decrease and no longer indicated damage. A new parameter, NA4* was developed by enhancing NA4 to improve the trending of the parameter. This allows for the indication of damage both at initiation and also as the damage progresses. The NA4* parameter was verified and compared to the NA4 and FM4 parameters using experimental data from single mesh spur and spiral bevel gear fatigue rigs. The primary failure mode for the test cases was naturally occurring tooth surface pitting. The NA4* parameter is shown to be a more robust indicator of damage.

Three-Dimensional Mixed Convection Flow of Viscoelastic Fluid with Thermal Radiation and Convective Conditions

PubMed Central

Hayat, Tasawar; Ashraf, Muhammad Bilal; Alsulami, Hamed H.; Alhuthali, Muhammad Shahab

2014-01-01

The objective of present research is to examine the thermal radiation effect in three-dimensional mixed convection flow of viscoelastic fluid. The boundary layer analysis has been discussed for flow by an exponentially stretching surface with convective conditions. The resulting partial differential equations are reduced into a system of nonlinear ordinary differential equations using appropriate transformations. The series solutions are developed through a modern technique known as the homotopy analysis method. The convergent expressions of velocity components and temperature are derived. The solutions obtained are dependent on seven sundry parameters including the viscoelastic parameter, mixed convection parameter, ratio parameter, temperature exponent, Prandtl number, Biot number and radiation parameter. A systematic study is performed to analyze the impacts of these influential parameters on the velocity and temperature, the skin friction coefficients and the local Nusselt number. It is observed that mixed convection parameter in momentum and thermal boundary layers has opposite role. Thermal boundary layer is found to decrease when ratio parameter, Prandtl number and temperature exponent are increased. Local Nusselt number is increasing function of viscoelastic parameter and Biot number. Radiation parameter on the Nusselt number has opposite effects when compared with viscoelastic parameter. PMID:24608594

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Efficient temporal and interlayer parameter prediction for weighted prediction in scalable high efficiency video coding

NASA Astrophysics Data System (ADS)

Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi

2017-01-01

Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.

Three-dimensional mixed convection flow of viscoelastic fluid with thermal radiation and convective conditions.

PubMed

Hayat, Tasawar; Ashraf, Muhammad Bilal; Alsulami, Hamed H; Alhuthali, Muhammad Shahab

2014-01-01

The objective of present research is to examine the thermal radiation effect in three-dimensional mixed convection flow of viscoelastic fluid. The boundary layer analysis has been discussed for flow by an exponentially stretching surface with convective conditions. The resulting partial differential equations are reduced into a system of nonlinear ordinary differential equations using appropriate transformations. The series solutions are developed through a modern technique known as the homotopy analysis method. The convergent expressions of velocity components and temperature are derived. The solutions obtained are dependent on seven sundry parameters including the viscoelastic parameter, mixed convection parameter, ratio parameter, temperature exponent, Prandtl number, Biot number and radiation parameter. A systematic study is performed to analyze the impacts of these influential parameters on the velocity and temperature, the skin friction coefficients and the local Nusselt number. It is observed that mixed convection parameter in momentum and thermal boundary layers has opposite role. Thermal boundary layer is found to decrease when ratio parameter, Prandtl number and temperature exponent are increased. Local Nusselt number is increasing function of viscoelastic parameter and Biot number. Radiation parameter on the Nusselt number has opposite effects when compared with viscoelastic parameter.

In vivo quantitative evaluation of vascular parameters for angiogenesis based on sparse principal component analysis and aggregated boosted trees

NASA Astrophysics Data System (ADS)

Zhao, Fengjun; Liu, Junting; Qu, Xiaochao; Xu, Xianhui; Chen, Xueli; Yang, Xiang; Cao, Feng; Liang, Jimin; Tian, Jie

2014-12-01

To solve the multicollinearity issue and unequal contribution of vascular parameters for the quantification of angiogenesis, we developed a quantification evaluation method of vascular parameters for angiogenesis based on in vivo micro-CT imaging of hindlimb ischemic model mice. Taking vascular volume as the ground truth parameter, nine vascular parameters were first assembled into sparse principal components (PCs) to reduce the multicolinearity issue. Aggregated boosted trees (ABTs) were then employed to analyze the importance of vascular parameters for the quantification of angiogenesis via the loadings of sparse PCs. The results demonstrated that vascular volume was mainly characterized by vascular area, vascular junction, connectivity density, segment number and vascular length, which indicated they were the key vascular parameters for the quantification of angiogenesis. The proposed quantitative evaluation method was compared with both the ABTs directly using the nine vascular parameters and Pearson correlation, which were consistent. In contrast to the ABTs directly using the vascular parameters, the proposed method can select all the key vascular parameters simultaneously, because all the key vascular parameters were assembled into the sparse PCs with the highest relative importance.

Bifurcation and Stability Analysis of the Equilibrium States in Thermodynamic Systems in a Small Vicinity of the Equilibrium Values of Parameters

NASA Astrophysics Data System (ADS)

Barsuk, Alexandr A.; Paladi, Florentin

2018-04-01

The dynamic behavior of thermodynamic system, described by one order parameter and one control parameter, in a small neighborhood of ordinary and bifurcation equilibrium values of the system parameters is studied. Using the general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, we performed an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behavior of the order parameter dependences on the control parameter (bifurcation diagrams). The peculiarities of the transition to an unstable state of the system are discussed, and the estimates of the transition time to the unstable state in the neighborhood of ordinary and bifurcation equilibrium values of parameters are given. The influence of an external field on the dynamic behavior of thermodynamic system is analyzed, and the peculiarities of the system dynamic behavior are discussed near the ordinary and bifurcation equilibrium values of parameters in the presence of external field. The dynamic process of magnetization of a ferromagnet is discussed by using the general methods of bifurcation and stability analysis presented in the paper.

Calibration parameters used to simulate streamflow from application of the Hydrologic Simulation Program-FORTRAN Model (HSPF) to mountainous basins containing coal mines in West Virginia

USGS Publications Warehouse

Atkins, John T.; Wiley, Jeffrey B.; Paybins, Katherine S.

2005-01-01

This report presents the Hydrologic Simulation Program-FORTRAN Model (HSPF) parameters for eight basins in the coal-mining region of West Virginia. The magnitude and characteristics of model parameters from this study will assist users of HSPF in simulating streamflow at other basins in the coal-mining region of West Virginia. The parameter for nominal capacity of the upper-zone storage, UZSN, increased from south to north. The increase in UZSN with the increase in basin latitude could be due to decreasing slopes, decreasing rockiness of the soils, and increasing soil depths from south to north. A special action was given to the parameter for fraction of ground-water inflow that flows to inactive ground water, DEEPFR. The basis for this special action was related to the seasonal movement of the water table and transpiration from trees. The models were most sensitive to DEEPFR and the parameter for interception storage capacity, CEPSC. The models were also fairly sensitive to the parameter for an index representing the infiltration capacity of the soil, INFILT; the parameter for indicating the behavior of the ground-water recession flow, KVARY; the parameter for the basic ground-water recession rate, AGWRC; the parameter for nominal capacity of the upper zone storage, UZSN; the parameter for the interflow inflow, INTFW; the parameter for the interflow recession constant, IRC; and the parameter for lower zone evapotranspiration, LZETP.

Temporal variation and scaling of parameters for a monthly hydrologic model

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2017-05-01

An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semi-arid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

Uncertainty in dual permeability model parameters for structured soils.

PubMed

Arora, B; Mohanty, B P; McGuire, J T

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface ( K sa ) and macropore tortuosity ( l f ) but also of other parameters of the matrix and macropore domains.

Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

DOE PAGES

Covey, Curt; Lucas, Donald D.; Tannahill, John; ...

2013-07-01

Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

An analysis of sensitivity of CLIMEX parameters in mapping species potential distribution and the broad-scale changes observed with minor variations in parameters values: an investigation using open-field Solanum lycopersicum and Neoleucinodes elegantalis as an example

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho

2018-04-01

A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.

Uncertainty in dual permeability model parameters for structured soils

NASA Astrophysics Data System (ADS)

Arora, B.; Mohanty, B. P.; McGuire, J. T.

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

Discrete Event Simulation Modeling and Analysis of Key Leader Engagements

DTIC Science & Technology

2012-06-01

to offer. GreenPlayer agents require four parameters, pC, pKLK, pTK, and pRK , which give probabilities for being corrupt, having key leader...HandleMessageRequest component. The same parameter constraints apply to these four parameters. The parameter pRK is the same parameter from the CreatePlayers component...whether the local Green player has resource critical knowledge by using the parameter pRK . It schedules an EndResourceKnowledgeRequest event, passing

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

PubMed

Waller, Niels G; Feuerstahler, Leah

2017-01-01

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

Innovation Analysis Approach to Design Parameters of High Speed Train Carriage and Their Intrinsic Complexity Relationships

NASA Astrophysics Data System (ADS)

Xiao, Shou-Ne; Wang, Ming-Meng; Hu, Guang-Zhong; Yang, Guang-Wu

2017-09-01

In view of the problem that it's difficult to accurately grasp the influence range and transmission path of the vehicle top design requirements on the underlying design parameters. Applying directed-weighted complex network to product parameter model is an important method that can clarify the relationships between product parameters and establish the top-down design of a product. The relationships of the product parameters of each node are calculated via a simple path searching algorithm, and the main design parameters are extracted by analysis and comparison. A uniform definition of the index formula for out-in degree can be provided based on the analysis of out-in-degree width and depth and control strength of train carriage body parameters. Vehicle gauge, axle load, crosswind and other parameters with higher values of the out-degree index are the most important boundary conditions; the most considerable performance indices are the parameters that have higher values of the out-in-degree index including torsional stiffness, maximum testing speed, service life of the vehicle, and so on; the main design parameters contain train carriage body weight, train weight per extended metre, train height and other parameters with higher values of the in-degree index. The network not only provides theoretical guidance for exploring the relationship of design parameters, but also further enriches the application of forward design method to high-speed trains.

Acceptable Tolerances for Matching Icing Similarity Parameters in Scaling Applications

NASA Technical Reports Server (NTRS)

Anderson, David N.

2003-01-01

This paper reviews past work and presents new data to evaluate how changes in similarity parameters affect ice shapes and how closely scale values of the parameters should match reference values. Experimental ice shapes presented are from tests by various researchers in the NASA Glenn Icing Research Tunnel. The parameters reviewed are the modified inertia parameter (which determines the stagnation collection efficiency), accumulation parameter, freezing fraction, Reynolds number, and Weber number. It was demonstrated that a good match of scale and reference ice shapes could sometimes be achieved even when values of the modified inertia parameter did not match precisely. Consequently, there can be some flexibility in setting scale droplet size, which is the test condition determined from the modified inertia parameter. A recommended guideline is that the modified inertia parameter be chosen so that the scale stagnation collection efficiency is within 10 percent of the reference value. The scale accumulation parameter and freezing fraction should also be within 10 percent of their reference values. The Weber number based on droplet size and water properties appears to be a more important scaling parameter than one based on model size and air properties. Scale values of both the Reynolds and Weber numbers need to be in the range of 60 to 160 percent of the corresponding reference values. The effects of variations in other similarity parameters have yet to be established.

Automatic parameter selection for feature-based multi-sensor image registration

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

2006-05-01

Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

40 CFR 62.15280 - What minimum amount of monitoring data must I collect with my continuous parameter monitoring...

Code of Federal Regulations, 2010 CFR

2010-07-01

... must I collect with my continuous parameter monitoring systems and is this requirement enforceable? 62... with my continuous parameter monitoring systems and is this requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for three parameters: (1...

40 CFR 62.15280 - What minimum amount of monitoring data must I collect with my continuous parameter monitoring...

Code of Federal Regulations, 2011 CFR

2011-07-01

... must I collect with my continuous parameter monitoring systems and is this requirement enforceable? 62... with my continuous parameter monitoring systems and is this requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for three parameters: (1...

40 CFR 60.1335 - What is the minimum amount of monitoring data I must collect with my continuous parameter...

Code of Federal Regulations, 2011 CFR

2011-07-01

... monitoring data I must collect with my continuous parameter monitoring systems and is the data collection... parameter monitoring systems and is the data collection requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for three parameters: (1) Load...

40 CFR 60.1335 - What is the minimum amount of monitoring data I must collect with my continuous parameter...

Code of Federal Regulations, 2010 CFR

2010-07-01

... monitoring data I must collect with my continuous parameter monitoring systems and is the data collection... parameter monitoring systems and is the data collection requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for three parameters: (1) Load...

Dynamic parameter identification of robot arms with servo-controlled electrical motors

NASA Astrophysics Data System (ADS)

Jiang, Zhao-Hui; Senda, Hiroshi

2005-12-01

This paper addresses the issue of dynamic parameter identification of the robot manipulator with servo-controlled electrical motors. An assumption is made that all kinematical parameters, such as link lengths, are known, and only dynamic parameters containing mass, moment of inertia, and their functions need to be identified. First, we derive dynamics of the robot arm with a linear form of the unknown dynamic parameters by taking dynamic characteristics of the motor and servo unit into consideration. Then, we implement the parameter identification approach to identify the unknown parameters with respect to individual link separately. A pseudo-inverse matrix is used for formulation of the parameter identification. The optimal solution is guaranteed in a sense of least-squares of the mean errors. A Direct Drive (DD) SCARA type industrial robot arm AdeptOne is used as an application example of the parameter identification. Simulations and experiments for both open loop and close loop controls are carried out. Comparison of the results confirms the correctness and usefulness of the parameter identification and the derived dynamic model.

ZASPE: A Code to Measure Stellar Atmospheric Parameters and their Covariance from Spectra

NASA Astrophysics Data System (ADS)

Brahm, Rafael; Jordán, Andrés; Hartman, Joel; Bakos, Gáspár

2017-05-01

We describe the Zonal Atmospheric Stellar Parameters Estimator (zaspe), a new algorithm, and its associated code, for determining precise stellar atmospheric parameters and their uncertainties from high-resolution echelle spectra of FGK-type stars. zaspe estimates stellar atmospheric parameters by comparing the observed spectrum against a grid of synthetic spectra only in the most sensitive spectral zones to changes in the atmospheric parameters. Realistic uncertainties in the parameters are computed from the data itself, by taking into account the systematic mismatches between the observed spectrum and the best-fitting synthetic one. The covariances between the parameters are also estimated in the process. zaspe can in principle use any pre-calculated grid of synthetic spectra, but unbiased grids are required to obtain accurate parameters. We tested the performance of two existing libraries, and we concluded that neither is suitable for computing precise atmospheric parameters. We describe a process to synthesize a new library of synthetic spectra that was found to generate consistent results when compared with parameters obtained with different methods (interferometry, asteroseismology, equivalent widths).

Waveform Tomography of Two-Dimensional Three-Component Seismic Data for HTI Anisotropic Media

NASA Astrophysics Data System (ADS)

Gao, Fengxia; Wang, Yanghua; Wang, Yun

2018-06-01

Reservoirs with vertically aligned fractures can be represented equivalently by horizontal transverse isotropy (HTI) media. But inverting for the anisotropic parameters of HTI media is a challenging inverse problem, because of difficulties inherent in a multiple parameter inversion. In this paper, when we invert for the anisotropic parameters, we consider for the first time the azimuthal rotation of a two-dimensional seismic survey line from the symmetry of HTI. The established wave equations for the HTI media with azimuthal rotation consist of nine elastic coefficients, expressed in terms of five modified Thomsen parameters. The latter are parallel to the Thomsen parameters for describing velocity characteristics of weak vertical transverse isotropy media. We analyze the sensitivity differences of the five modified Thomsen parameters from their radiation patterns, and attempt to balance the magnitude and sensitivity differences between the parameters through normalization and tuning factors which help to update the model parameters properly. We demonstrate an effective inversion strategy by inverting velocity parameters in the first stage and updates the five modified Thomsen parameters simultaneously in the second stage, for generating reliably reconstructed models.

A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

USGS Publications Warehouse

Heidari, M.; Ranjithan, S.R.

1998-01-01

In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.

Visual exploration of parameter influence on phylogenetic trees.

PubMed

Hess, Martin; Bremm, Sebastian; Weissgraeber, Stephanie; Hamacher, Kay; Goesele, Michael; Wiemeyer, Josef; von Landesberger, Tatiana

2014-01-01

Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.

Introduction of Two Novel Stiffness Parameters and Interpretation of Air Puff-Induced Biomechanical Deformation Parameters With a Dynamic Scheimpflug Analyzer.

PubMed

Roberts, Cynthia J; Mahmoud, Ashraf M; Bons, Jeffrey P; Hossain, Arif; Elsheikh, Ahmed; Vinciguerra, Riccardo; Vinciguerra, Paolo; Ambrósio, Renato

2017-04-01

To investigate two new stiffness parameters and their relationships with the dynamic corneal response (DCR) parameters and compare normal and keratoconic eyes. Stiffness parameters are defined as Resultant Pressure at inward applanation (A1) divided by corneal displacement. Stiffness parameter A1 uses displacement between the undeformed cornea and A1 and stiffness parameter highest concavity (HC) uses displacement from A1 to maximum deflection during HC. The spatial and temporal profiles of the Corvis ST (Oculus Optikgeräte, Wetzlar, Germany) air puff were characterized using hot wire anemometry. An adjusted air pressure impinging on the cornea at A1 (adjAP1) and an algorithm to biomechanically correct intraocular pressure based on finite element modelling (bIOP) were used for Resultant Pressure calculation (adjAP1 - bIOP). Linear regression analyses between DCR parameters and stiffness parameters were performed on a retrospective dataset of 180 keratoconic eyes and 482 normal eyes. DCR parameters from a subset of 158 eyes of 158 patients in each group were matched for bIOP and compared using t tests. A P value of less than .05 was considered statistically significant. All DCR parameters evaluated showed significant differences between normal and keratoconic eyes, except peak distance. Keratoconic eyes had lower stiffness parameter values, thinner pachymetry, shorter applanation lengths, greater absolute values of applanation velocities, earlier A1 times and later second applanation times, greater HC deformation amplitudes and HC deflection amplitudes, and lower HC radius of concave curvature (greater concave curvature). Most DCR parameters showed a significant relationship with both stiffness parameters in both groups. Keratoconic eyes demonstrated less resistance to deformation than normal eyes with similar IOP. The stiffness parameters may be useful in future biomechanical studies as potential biomarkers. [J Refract Surg. 2017;33(4):266-273.]. Copyright 2017, SLACK Incorporated.

[Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model].

PubMed

He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong

2016-02-01

Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

On averaging aspect ratios and distortion parameters over ice crystal population ensembles for estimating effective scattering asymmetry parameters

PubMed Central

van Diedenhoven, Bastiaan; Ackerman, Andrew S.; Fridlind, Ann M.; Cairns, Brian

2017-01-01

The use of ensemble-average values of aspect ratio and distortion parameter of hexagonal ice prisms for the estimation of ensemble-average scattering asymmetry parameters is evaluated. Using crystal aspect ratios greater than unity generally leads to ensemble-average values of aspect ratio that are inconsistent with the ensemble-average asymmetry parameters. When a definition of aspect ratio is used that limits the aspect ratio to below unity (α≤1) for both hexagonal plates and columns, the effective asymmetry parameters calculated using ensemble-average aspect ratios are generally consistent with ensemble-average asymmetry parameters, especially if aspect ratios are geometrically averaged. Ensemble-average distortion parameters generally also yield effective asymmetry parameters that are largely consistent with ensemble-average asymmetry parameters. In the case of mixtures of plates and columns, it is recommended to geometrically average the α≤1 aspect ratios and to subsequently calculate the effective asymmetry parameter using a column or plate geometry when the contribution by columns to a given mixture’s total projected area is greater or lower than 50%, respectively. In addition, we show that ensemble-average aspect ratios, distortion parameters and asymmetry parameters can generally be retrieved accurately from simulated multi-directional polarization measurements based on mixtures of varying columns and plates. However, such retrievals tend to be somewhat biased toward yielding column-like aspect ratios. Furthermore, generally large retrieval errors can occur for mixtures with approximately equal contributions of columns and plates and for ensembles with strong contributions of thin plates. PMID:28983127

Optimized microsystems-enabled photovoltaics

DOEpatents

Cruz-Campa, Jose Luis; Nielson, Gregory N.; Young, Ralph W.; Resnick, Paul J.; Okandan, Murat; Gupta, Vipin P.

2015-09-22

Technologies pertaining to designing microsystems-enabled photovoltaic (MEPV) cells are described herein. A first restriction for a first parameter of an MEPV cell is received. Subsequently, a selection of a second parameter of the MEPV cell is received. Values for a plurality of parameters of the MEPV cell are computed such that the MEPV cell is optimized with respect to the second parameter, wherein the values for the plurality of parameters are computed based at least in part upon the restriction for the first parameter.

A design methodology for nonlinear systems containing parameter uncertainty

NASA Technical Reports Server (NTRS)

Young, G. E.; Auslander, D. M.

1983-01-01

In the present design methodology for nonlinear systems containing parameter uncertainty, a generalized sensitivity analysis is incorporated which employs parameter space sampling and statistical inference. For the case of a system with j adjustable and k nonadjustable parameters, this methodology (which includes an adaptive random search strategy) is used to determine the combination of j adjustable parameter values which maximize the probability of those performance indices which simultaneously satisfy design criteria in spite of the uncertainty due to k nonadjustable parameters.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

Determination of representative dimension parameter values of Korean knee joints for knee joint implant design.

PubMed

Kwak, Dai Soon; Tao, Quang Bang; Todo, Mitsugu; Jeon, Insu

2012-05-01

Knee joint implants developed by western companies have been imported to Korea and used for Korean patients. However, many clinical problems occur in knee joints of Korean patients after total knee joint replacement owing to the geometric mismatch between the western implants and Korean knee joint structures. To solve these problems, a method to determine the representative dimension parameter values of Korean knee joints is introduced to aid in the design of knee joint implants appropriate for Korean patients. Measurements of the dimension parameters of 88 male Korean knee joint subjects were carried out. The distribution of the subjects versus each measured parameter value was investigated. The measured dimension parameter values of each parameter were grouped by suitable intervals called the "size group," and average values of the size groups were calculated. The knee joint subjects were grouped as the "patient group" based on "size group numbers" of each parameter. From the iterative calculations to decrease the errors between the average dimension parameter values of each "patient group" and the dimension parameter values of the subjects, the average dimension parameter values that give less than the error criterion were determined to be the representative dimension parameter values for designing knee joint implants for Korean patients.

Regression analysis and transfer function in estimating the parameters of central pulse waves from brachial pulse wave.

PubMed

Chai Rui; Li Si-Man; Xu Li-Sheng; Yao Yang; Hao Li-Ling

2017-07-01

This study mainly analyzed the parameters such as ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad) and systolic area (As) diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO) and peripheral resistance (RS) of central pulse wave invasively and non-invasively measured. These parameters extracted from the central pulse wave invasively measured were compared with the parameters measured from the brachial pulse waves by a regression model and a transfer function model. The accuracy of the parameters which were estimated by the regression model and the transfer function model was compared too. Our findings showed that in addition to the k value, the above parameters of the central pulse wave and the brachial pulse wave invasively measured had positive correlation. Both the regression model parameters including A_slope, DBP, SEVR and the transfer function model parameters had good consistency with the parameters invasively measured, and they had the same effect of consistency. The regression equations of the three parameters were expressed by Y'=a+bx. The SBP, PP, SV, CO of central pulse wave could be calculated through the regression model, but their accuracies were worse than that of transfer function model.

Estimation of Ecosystem Parameters of the Community Land Model with DREAM: Evaluation of the Potential for Upscaling Net Ecosystem Exchange

NASA Astrophysics Data System (ADS)

Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.

2015-12-01

Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.

Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model

ERIC Educational Resources Information Center

Custer, Michael

2015-01-01

This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…

The Impact of Three Factors on the Recovery of Item Parameters for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2017-01-01

This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…

Tachyon constant-roll inflation

NASA Astrophysics Data System (ADS)

Mohammadi, A.; Saaidi, Kh.; Golanbari, T.

2018-04-01

The constant-roll inflation is studied where the inflaton is taken as a tachyon field. Based on this approach, the second slow-roll parameter is taken as a constant which leads to a differential equation for the Hubble parameter. Finding an exact solution for the Hubble parameter is difficult and leads us to a numerical solution for the Hubble parameter. On the other hand, since in this formalism the slow-roll parameter η is constant and could not be assumed to be necessarily small, the perturbation parameters should be reconsidered again which, in turn, results in new terms appearing in the amplitude of scalar perturbations and the scalar spectral index. Utilizing the numerical solution for the Hubble parameter, we estimate the perturbation parameter at the horizon exit time and compare it with observational data. The results show that, for specific values of the constant parameter η , we could have an almost scale-invariant amplitude of scalar perturbations. Finally, the attractor behavior for the solution of the model is presented, and we determine that the feature could be properly satisfied.

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2009-01-01

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Comparison of Regression Analysis and Transfer Function in Estimating the Parameters of Central Pulse Waves from Brachial Pulse Wave.

PubMed

Chai, Rui; Xu, Li-Sheng; Yao, Yang; Hao, Li-Ling; Qi, Lin

2017-01-01

This study analyzed ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad) and systolic area (As) diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO), and peripheral resistance (RS) of central pulse wave invasively and non-invasively measured. Invasively measured parameters were compared with parameters measured from brachial pulse waves by regression model and transfer function model. Accuracy of parameters estimated by regression and transfer function model, was compared too. Findings showed that k value, central pulse wave and brachial pulse wave parameters invasively measured, correlated positively. Regression model parameters including A_slope, DBP, SEVR, and transfer function model parameters had good consistency with parameters invasively measured. They had same effect of consistency. SBP, PP, SV, and CO could be calculated through the regression model, but their accuracies were worse than that of transfer function model.

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

PubMed

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.

System health monitoring using multiple-model adaptive estimation techniques

NASA Astrophysics Data System (ADS)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary. Customizable rules define the specific resample behavior when the GRAPE parameter estimates converge. Convergence itself is determined from the derivatives of the parameter estimates using a simple moving average window to filter out noise. The system can be tuned to match the desired performance goals by making adjustments to parameters such as the sample size, convergence criteria, resample criteria, initial sampling method, resampling method, confidence in prior sample covariances, sample delay, and others.

Speaker verification system using acoustic data and non-acoustic data

DOEpatents

Gable, Todd J [Walnut Creek, CA; Ng, Lawrence C [Danville, CA; Holzrichter, John F [Berkeley, CA; Burnett, Greg C [Livermore, CA

2006-03-21

A method and system for speech characterization. One embodiment includes a method for speaker verification which includes collecting data from a speaker, wherein the data comprises acoustic data and non-acoustic data. The data is used to generate a template that includes a first set of "template" parameters. The method further includes receiving a real-time identity claim from a claimant, and using acoustic data and non-acoustic data from the identity claim to generate a second set of parameters. The method further includes comparing the first set of parameters to the set of parameters to determine whether the claimant is the speaker. The first set of parameters and the second set of parameters include at least one purely non-acoustic parameter, including a non-acoustic glottal shape parameter derived from averaging multiple glottal cycle waveforms.

Determination of JWL Parameters for Non-Ideal Explosive

NASA Astrophysics Data System (ADS)

Hamashima, H.; Kato, Y.; Itoh, S.

2004-07-01

JWL equation of state is widely used in numerical simulation of detonation phenomena. JWL parameters are determined by cylinder test. Detonation characteristics of non-ideal explosive depend strongly on confinement, and JWL parameters determined by cylinder test do not represent the state of detonation products in many applications. We developed a method to determine JWL parameters from the underwater explosion test. JWL parameters were determined through a method of characteristics applied to the configuration of the underwater shock waves of cylindrical explosives. The numerical results obtained using JWL parameters determined by the underwater explosion test and those obtained using JWL parameters determined by cylinder test were compared with experimental results for typical non-ideal explosive; emulsion explosive. Good agreement was confirmed between the results obtained using JWL parameters determined by the underwater explosion test and experimental results.

[Study on the automatic parameters identification of water pipe network model].

PubMed

Jia, Hai-Feng; Zhao, Qi-Feng

2010-01-01

Based on the problems analysis on development and application of water pipe network model, the model parameters automatic identification is regarded as a kernel bottleneck of model's application in water supply enterprise. The methodology of water pipe network model parameters automatic identification based on GIS and SCADA database is proposed. Then the kernel algorithm of model parameters automatic identification is studied, RSA (Regionalized Sensitivity Analysis) is used for automatic recognition of sensitive parameters, and MCS (Monte-Carlo Sampling) is used for automatic identification of parameters, the detail technical route based on RSA and MCS is presented. The module of water pipe network model parameters automatic identification is developed. At last, selected a typical water pipe network as a case, the case study on water pipe network model parameters automatic identification is conducted and the satisfied results are achieved.

[Application of CWT to extract characteristic monitoring parameters during spine surgery].

PubMed

Chen, Penghui; Wu, Baoming; Hu, Yong

2005-10-01

It is necessary to monitor intraoperative spinal function in order to prevent spinal neurological deficit during spine surgery. This study aims to extract characteristic electrophysiological monitoring parameters during surgical treatment of scoliosis. The problem, "the monitoring parameters in time domain are of great variability and are sensitive to noise", may also be solved in this study. By use of continuous wavelet transform to analyze the intraoperative cortical somatosensory evoked potential (CSEP), three new characteristic monitoring parameters in time-frequency domain (TFD) are extracted. The results indicate that the variability of CSEP characteristic parameters in TFD is lower than the variability of those in time domain. Therefore, the TFD characteristic monitoring parameters are more stable and reliable parameters of latency and amplitude in time domain. The application of TFD monitoring parameters during spine surgery may avoid spinal injury effectively.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

Parameter estimation of qubit states with unknown phase parameter

NASA Astrophysics Data System (ADS)

Suzuki, Jun

2015-02-01

We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér-Rao (CR) bound and Hayashi-Gill-Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.

PAR -- Interface to the ADAM Parameter System

NASA Astrophysics Data System (ADS)

Currie, Malcolm J.; Chipperfield, Alan J.

PAR is a library of Fortran subroutines that provides convenient mechanisms for applications to exchange information with the outside world, through input-output channels called parameters. Parameters enable a user to control an application's behaviour. PAR supports numeric, character, and logical parameters, and is currently implemented only on top of the ADAM parameter system. The PAR library permits parameter values to be obtained, without or with a variety of constraints. Results may be put into parameters to be passed onto other applications. Other facilities include setting a prompt string, and suggested defaults. This document also introduces a preliminary C interface for the PAR library -- this may be subject to change in the light of experience.

Determination of the optimal mesh parameters for Iguassu centrifuge flow and separation calculations

NASA Astrophysics Data System (ADS)

Romanihin, S. M.; Tronin, I. V.

2016-09-01

We present the method and the results of the determination for optimal computational mesh parameters for axisymmetric modeling of flow and separation in the Iguasu gas centrifuge. The aim of this work was to determine the mesh parameters which provide relatively low computational cost whithout loss of accuracy. We use direct search optimization algorithm to calculate optimal mesh parameters. Obtained parameters were tested by the calculation of the optimal working regime of the Iguasu GC. Separative power calculated using the optimal mesh parameters differs less than 0.5% from the result obtained on the detailed mesh. Presented method can be used to determine optimal mesh parameters of the Iguasu GC with different rotor speeds.

Preliminary design study of a regenerative life support system information management and display system

NASA Technical Reports Server (NTRS)

Parker, C. D.; Tommerdahl, J. B.

1972-01-01

The instrumentation requirements for a regenerative life support systems were studied to provide the earliest possible indication of a malfunction that will permit degradation of the environment. Four categories of parameters were investigated: environmental parameters that directly and immediately influence the health and safety of the cabin crew; subsystems' inputs to the cabin that directly maintain the cabin environmental parameters; indications for maintenance or repair; and parameters useful as diagnostic indicators. A data averager concept is introduced which provides a moving average of parameter values that is not influenced by spurious changes, and is convenient for detecting parameter rates of change. A system is included to provide alarms at preselected parameter levels.

Attitude determination and parameter estimation using vector observations - Theory

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1989-01-01

Procedures for attitude determination based on Wahba's loss function are generalized to include the estimation of parameters other than the attitude, such as sensor biases. Optimization with respect to the attitude is carried out using the q-method, which does not require an a priori estimate of the attitude. Optimization with respect to the other parameters employs an iterative approach, which does require an a priori estimate of these parameters. Conventional state estimation methods require a priori estimates of both the parameters and the attitude, while the algorithm presented in this paper always computes the exact optimal attitude for given values of the parameters. Expressions for the covariance of the attitude and parameter estimates are derived.

Comparative Sensitivity Analysis of Muscle Activation Dynamics

PubMed Central

Günther, Michael; Götz, Thomas

2015-01-01

We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379

Parameter redundancy in discrete state-space and integrated models.

PubMed

Cole, Diana J; McCrea, Rachel S

2016-09-01

Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

NASA Astrophysics Data System (ADS)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis.

PubMed

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

PubMed Central

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum. PMID:23766941

Overview of Icing Physics Relevant to Scaling

NASA Technical Reports Server (NTRS)

Anderson, David N.; Tsao, Jen-Ching

2005-01-01

An understanding of icing physics is required for the development of both scaling methods and ice-accretion prediction codes. This paper gives an overview of our present understanding of the important physical processes and the associated similarity parameters that determine the shape of Appendix C ice accretions. For many years it has been recognized that ice accretion processes depend on flow effects over the model, on droplet trajectories, on the rate of water collection and time of exposure, and, for glaze ice, on a heat balance. For scaling applications, equations describing these events have been based on analyses at the stagnation line of the model and have resulted in the identification of several non-dimensional similarity parameters. The parameters include the modified inertia parameter of the water drop, the accumulation parameter and the freezing fraction. Other parameters dealing with the leading edge heat balance have also been used for convenience. By equating scale expressions for these parameters to the values to be simulated a set of equations is produced which can be solved for the scale test conditions. Studies in the past few years have shown that at least one parameter in addition to those mentioned above is needed to describe surface-water effects, and some of the traditional parameters may not be as significant as once thought. Insight into the importance of each parameter, and the physical processes it represents, can be made by viewing whether ice shapes change, and the extent of the change, when each parameter is varied. Experimental evidence is presented to establish the importance of each of the traditionally used parameters and to identify the possible form of a new similarity parameter to be used for scaling.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Constitutive parameter de-embedding using inhomogeneously-filled rectangular waveguides with longitudinal section modes

NASA Technical Reports Server (NTRS)

Park, A.; Dominek, A. K.

1990-01-01

Constitutive parameter extraction from S parameter data using a rectangular waveguide whose cross section is partially filled with a material sample as opposed to being completely filled was examined. One reason for studying a partially filled geometry is to analyze the effect of air gaps between the sample and fixture for the extraction of constitutive parameters. Air gaps can occur in high temperature parameter measurements when the sample was prepared at room temperature. Single port and two port measurement approaches to parameter extraction are also discussed.

Control and optimization system

DOEpatents

Xinsheng, Lou

2013-02-12

A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

LRS Bianchi type-I cosmological model with constant deceleration parameter in f(R,T) gravity

NASA Astrophysics Data System (ADS)

Bishi, Binaya K.; Pacif, S. K. J.; Sahoo, P. K.; Singh, G. P.

A spatially homogeneous anisotropic LRS Bianchi type-I cosmological model is studied in f(R,T) gravity with a special form of Hubble's parameter, which leads to constant deceleration parameter. The parameters involved in the considered form of Hubble parameter can be tuned to match, our models with the ΛCDM model. With the present observed value of the deceleration parameter, we have discussed physical and kinematical properties of a specific model. Moreover, we have discussed the cosmological distances for our model.

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

Ashraf, M. Bilal, E-mail: bilalashraf-qau@yahoo.com; Hayat, T.; Department of Mathematics, Faculty of Science, King Abdulaziz University, P. O. Box 80257, Jeddah 21589

Three dimensional radiative flow of Maxwell fluid over an inclined stretching surface with convective boundary condition is investigated. Heat and mass transfer analysis is taken into account with thermophoresis effects. Similarity transformations are utilized to reduce the partial differential equations into ordinary differential equations. Series solutions of velocity, temperature and concentration are developed. Influence of different parameters Biot number, therrmophoretic parameter, Deborah number, ratio parameter, inclined stretching angle, radiation parameter, mixed convection parameter and concentration buoyancy parameter on the non-dimensional velocity components, temperature and concentration are plotted and discussed in detail. Physical quantities of interests are tabulated and examined.

Research on Product Conceptual Design Based on Integrated of TRIZ and HOQ

NASA Astrophysics Data System (ADS)

Xie, Jianmin; Tang, Xiaowo; Shao, Yunfei

The conceptual design determines the success of the final product quality and competition of market. The determination of design parameters and the effective method to resolve parameters contradiction are the key to success. In this paper, the concept of HOQ products designed to determine the parameters, then using the TRIZ contradiction matrix and inventive principles of design parameters to solve the problem of contradictions. Facts have proved that the effective method is to obtain the product concept design parameters and to resolve contradictions line parameters.

Recursive Branching Simulated Annealing Algorithm

NASA Technical Reports Server (NTRS)

Bolcar, Matthew; Smith, J. Scott; Aronstein, David

2012-01-01

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.

Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

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

Kao, Jim; Flicker, Dawn; Ide, Kayo

2006-05-20

This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from amore » single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand.« less

Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

NASA Astrophysics Data System (ADS)

Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben; Christiansen, Anders Vest

2017-12-01

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.

[Study on differences between pharmacokinetics and chromatopharmacodynamics for Chinese materia medica formulae].

PubMed

He, Fuyuan; Deng, Kaiwen; Zou, Huan; Qiu, Yun; Chen, Feng; Zhou, Honghao

2011-01-01

To study on the differences between chromatopharmacokinetics (pharmacokinetics with fingerprint chromatography) and chromatopharmacodynamics (pharmacodynamics with fingerprint chromatography) of Chinese materia medica formulae to answer the question whether the pharmacokinetic parameters of multiple composites can be utilized to guide the medication of multiple composites. On the base of established four chromatopharmacology (pharmacology with chromatographic fingerprint), the pharmacokinetics, and pharmacodynamics were analyzed comparably on their mathematical model and parameter definition. On the basis of quantitative pharmacology, the function expressions and total statistical parameters, such as total zero moment, total first moment, total second moment of the pharmacokinetics, and pharmacodynamics were analyzed to the common expressions and elucidated results for single and multiple components in Chinese materia medica formulae. Total quantitative pharmacokinetic, i.e., chromatopharmacokinetic parameter were decided by each component pharmacokinetic parameters, whereas the total quantitative pharmacodynamic, i.e., chromatopharmacodynamic parameter were decided by both of pharmacokinetic and pharmacodynamic parameters of each components. The pharmacokinetic parameters were corresponded to pharmacodynamic parameters with an existing stable effective coefficient when the constitutive ratio of each composite was a constant. The effects of Chinese materia medica were all controlled by pharmacokinetic and pharmacodynamic coefficient. It is a special case that the pharmacokinetic parameter could independently guide the clinical medication for single component whereas the chromatopharmacokinetic parameters are not applied to the multiple drug combination system, and not be used to solve problems of chromatopharmacokinetic of Chinese materia medica formulae.

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

NASA Technical Reports Server (NTRS)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Learning the manifold of quality ultrasound acquisition.

PubMed

El-Zehiry, Noha; Yan, Michelle; Good, Sara; Fang, Tong; Zhou, S Kevin; Grady, Leo

2013-01-01

Ultrasound acquisition is a challenging task that requires simultaneous adjustment of several acquisition parameters (the depth, the focus, the frequency and its operation mode). If the acquisition parameters are not properly chosen, the resulting image will have a poor quality and will degrade the patient diagnosis and treatment workflow. Several hardware-based systems for autotuning the acquisition parameters have been previously proposed, but these solutions were largely abandoned because they failed to properly account for tissue inhomogeneity and other patient-specific characteristics. Consequently, in routine practice the clinician either uses population-based parameter presets or manually adjusts the acquisition parameters for each patient during the scan. In this paper, we revisit the problem of autotuning the acquisition parameters by taking a completely novel approach and producing a solution based on image analytics. Our solution is inspired by the autofocus capability of conventional digital cameras, but is significantly more challenging because the number of acquisition parameters is large and the determination of "good quality" images is more difficult to assess. Surprisingly, we show that the set of acquisition parameters which produce images that are favored by clinicians comprise a 1D manifold, allowing for a real-time optimization to maximize image quality. We demonstrate our method for acquisition parameter autotuning on several live patients, showing that our system can start with a poor initial set of parameters and automatically optimize the parameters to produce high quality images.

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

Comparative Analyses of Creep Models of a Solid Propellant

NASA Astrophysics Data System (ADS)

Zhang, J. B.; Lu, B. J.; Gong, S. F.; Zhao, S. P.

2018-05-01

The creep experiments of a solid propellant samples under five different stresses are carried out at 293.15 K and 323.15 K. In order to express the creep properties of this solid propellant, the viscoelastic model i.e. three Parameters solid, three Parameters fluid, four Parameters solid, four Parameters fluid and exponential model are involved. On the basis of the principle of least squares fitting, and different stress of all the parameters for the models, the nonlinear fitting procedure can be used to analyze the creep properties. The study shows that the four Parameters solid model can best express the behavior of creep properties of the propellant samples. However, the three Parameters solid and exponential model cannot very well reflect the initial value of the creep process, while the modified four Parameters models are found to agree well with the acceleration characteristics of the creep process.

Cosmological parameter estimation using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Prasad, J.; Souradeep, T.

2014-03-01

Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

PubMed

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor); Madavan, Nateri K. (Inventor)

2007-01-01

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

FLASH Interface; a GUI for managing runtime parameters in FLASH simulations

NASA Astrophysics Data System (ADS)

Walker, Christopher; Tzeferacos, Petros; Weide, Klaus; Lamb, Donald; Flocke, Norbert; Feister, Scott

2017-10-01

We present FLASH Interface, a novel graphical user interface (GUI) for managing runtime parameters in simulations performed with the FLASH code. FLASH Interface supports full text search of available parameters; provides descriptions of each parameter's role and function; allows for the filtering of parameters based on categories; performs input validation; and maintains all comments and non-parameter information already present in existing parameter files. The GUI can be used to edit existing parameter files or generate new ones. FLASH Interface is open source and was implemented with the Electron framework, making it available on Mac OSX, Windows, and Linux operating systems. The new interface lowers the entry barrier for new FLASH users and provides an easy-to-use tool for experienced FLASH simulators. U.S. Department of Energy (DOE), NNSA ASC/Alliances Center for Astrophysical Thermonuclear Flashes, U.S. DOE NNSA ASC through the Argonne Institute for Computing in Science, U.S. National Science Foundation.

Application and optimization of input parameter spaces in mass flow modelling: a case study with r.randomwalk and r.ranger

NASA Astrophysics Data System (ADS)

Krenn, Julia; Zangerl, Christian; Mergili, Martin

2017-04-01

r.randomwalk is a GIS-based, multi-functional, conceptual open source model application for forward and backward analyses of the propagation of mass flows. It relies on a set of empirically derived, uncertain input parameters. In contrast to many other tools, r.randomwalk accepts input parameter ranges (or, in case of two or more parameters, spaces) in order to directly account for these uncertainties. Parameter spaces represent a possibility to withdraw from discrete input values which in most cases are likely to be off target. r.randomwalk automatically performs multiple calculations with various parameter combinations in a given parameter space, resulting in the impact indicator index (III) which denotes the fraction of parameter value combinations predicting an impact on a given pixel. Still, there is a need to constrain the parameter space used for a certain process type or magnitude prior to performing forward calculations. This can be done by optimizing the parameter space in terms of bringing the model results in line with well-documented past events. As most existing parameter optimization algorithms are designed for discrete values rather than for ranges or spaces, the necessity for a new and innovative technique arises. The present study aims at developing such a technique and at applying it to derive guiding parameter spaces for the forward calculation of rock avalanches through back-calculation of multiple events. In order to automatize the work flow we have designed r.ranger, an optimization and sensitivity analysis tool for parameter spaces which can be directly coupled to r.randomwalk. With r.ranger we apply a nested approach where the total value range of each parameter is divided into various levels of subranges. All possible combinations of subranges of all parameters are tested for the performance of the associated pattern of III. Performance indicators are the area under the ROC curve (AUROC) and the factor of conservativeness (FoC). This strategy is best demonstrated for two input parameters, but can be extended arbitrarily. We use a set of small rock avalanches from western Austria, and some larger ones from Canada and New Zealand, to optimize the basal friction coefficient and the mass-to-drag ratio of the two-parameter friction model implemented with r.randomwalk. Thereby we repeat the optimization procedure with conservative and non-conservative assumptions of a set of complementary parameters and with different raster cell sizes. Our preliminary results indicate that the model performance in terms of AUROC achieved with broad parameter spaces is hardly surpassed by the performance achieved with narrow parameter spaces. However, broad spaces may result in very conservative or very non-conservative predictions. Therefore, guiding parameter spaces have to be (i) broad enough to avoid the risk of being off target; and (ii) narrow enough to ensure a reasonable level of conservativeness of the results. The next steps will consist in (i) extending the study to other types of mass flow processes in order to support forward calculations using r.randomwalk; and (ii) in applying the same strategy to the more complex, dynamic model r.avaflow.

Eye and Head Movement Characteristics in Free Visual Search of Flight-Simulator Imagery

DTIC Science & Technology

2010-03-01

conspicuity. However, only gaze amplitude varied significantly with IFOV. A two- parameter (scale and exponent) power function was fitted to the...main-sequence amplitude-duration data. Both parameters varied significantly with target conspicuity, but in opposite directions. Neither parameter ...IFOV. A two- parameter (scale and exponent) power function was fitted to the main-sequence amplitude-duration data. Both parameters varied

Use of an anaerobic sequencing batch reactor for parameter estimation in modelling of anaerobic digestion.

PubMed

Batstone, D J; Torrijos, M; Ruiz, C; Schmidt, J E

2004-01-01

The model structure in anaerobic digestion has been clarified following publication of the IWA Anaerobic Digestion Model No. 1 (ADM1). However, parameter values are not well known, and uncertainty and variability in the parameter values given is almost unknown. Additionally, platforms for identification of parameters, namely continuous-flow laboratory digesters, and batch tests suffer from disadvantages such as long run times, and difficulty in defining initial conditions, respectively. Anaerobic sequencing batch reactors (ASBRs) are sequenced into fill-react-settle-decant phases, and offer promising possibilities for estimation of parameters, as they are by nature, dynamic in behaviour, and allow repeatable behaviour to establish initial conditions, and evaluate parameters. In this study, we estimated parameters describing winery wastewater (most COD as ethanol) degradation using data from sequencing operation, and validated these parameters using unsequenced pulses of ethanol and acetate. The model used was the ADM1, with an extension for ethanol degradation. Parameter confidence spaces were found by non-linear, correlated analysis of the two main Monod parameters; maximum uptake rate (k(m)), and half saturation concentration (K(S)). These parameters could be estimated together using only the measured acetate concentration (20 points per cycle). From interpolating the single cycle acetate data to multiple cycles, we estimate that a practical "optimal" identifiability could be achieved after two cycles for the acetate parameters, and three cycles for the ethanol parameters. The parameters found performed well in the short term, and represented the pulses of acetate and ethanol (within 4 days of the winery-fed cycles) very well. The main discrepancy was poor prediction of pH dynamics, which could be due to an unidentified buffer with an overall influence the same as a weak base (possibly CaCO3). Based on this work, ASBR systems are effective for parameter estimation, especially for comparative wastewater characterisation. The main disadvantages are heavy computational requirements for multiple cycles, and difficulty in establishing the correct biomass concentration in the reactor, though the last is also a disadvantage for continuous fixed film reactors, and especially, batch tests.

Exploration of DGVM Parameter Solution Space Using Simulated Annealing: Implications for Forecast Uncertainties

NASA Astrophysics Data System (ADS)

Wells, J. R.; Kim, J. B.

2011-12-01

Parameters in dynamic global vegetation models (DGVMs) are thought to be weakly constrained and can be a significant source of errors and uncertainties. DGVMs use between 5 and 26 plant functional types (PFTs) to represent the average plant life form in each simulated plot, and each PFT typically has a dozen or more parameters that define the way it uses resource and responds to the simulated growing environment. Sensitivity analysis explores how varying parameters affects the output, but does not do a full exploration of the parameter solution space. The solution space for DGVM parameter values are thought to be complex and non-linear; and multiple sets of acceptable parameters may exist. In published studies, PFT parameters are estimated from published literature, and often a parameter value is estimated from a single published value. Further, the parameters are "tuned" using somewhat arbitrary, "trial-and-error" methods. BIOMAP is a new DGVM created by fusing MAPSS biogeography model with Biome-BGC. It represents the vegetation of North America using 26 PFTs. We are using simulated annealing, a global search method, to systematically and objectively explore the solution space for the BIOMAP PFTs and system parameters important for plant water use. We defined the boundaries of the solution space by obtaining maximum and minimum values from published literature, and where those were not available, using +/-20% of current values. We used stratified random sampling to select a set of grid cells representing the vegetation of the conterminous USA. Simulated annealing algorithm is applied to the parameters for spin-up and a transient run during the historical period 1961-1990. A set of parameter values is considered acceptable if the associated simulation run produces a modern potential vegetation distribution map that is as accurate as one produced by trial-and-error calibration. We expect to confirm that the solution space is non-linear and complex, and that multiple acceptable parameter sets exist. Further we expect to demonstrate that the multiple parameter sets produce significantly divergent future forecasts in NEP, C storage, and ET and runoff; and thereby identify a highly important source of DGVM uncertainty

Handling the unknown soil hydraulic parameters in data assimilation for unsaturated flow problems

NASA Astrophysics Data System (ADS)

Lange, Natascha; Erdal, Daniel; Neuweiler, Insa

2017-04-01

Model predictions of flow in the unsaturated zone require the soil hydraulic parameters. However, these parameters cannot be determined easily in applications, in particular if observations are indirect and cover only a small range of possible states. Correlation of parameters or their correlation in the range of states that are observed is a problem, as different parameter combinations may reproduce approximately the same measured water content. In field campaigns this problem can be helped by adding more measurement devices. Often, observation networks are designed to feed models for long term prediction purposes (i.e. for weather forecasting). A popular way of making predictions with such kind of observations are data assimilation methods, like the ensemble Kalman filter (Evensen, 1994). These methods can be used for parameter estimation if the unknown parameters are included in the state vector and updated along with the model states. Given the difficulties related to estimation of the soil hydraulic parameters in general, it is questionable, though, whether these methods can really be used for parameter estimation under natural conditions. Therefore, we investigate the ability of the ensemble Kalman filter to estimate the soil hydraulic parameters. We use synthetic identical twin-experiments to guarantee full knowledge of the model and the true parameters. We use the van Genuchten model to describe the soil water retention and relative permeability functions. This model is unfortunately prone to the above mentioned pseudo-correlations of parameters. Therefore, we also test the simpler Russo Gardner model, which is less affected by that problem, in our experiments. The total number of unknown parameters is varied by considering different layers of soil. Besides, we study the influence of the parameter updates on the water content predictions. We test different iterative filter approaches and compare different observation strategies for parameter identification. Considering heterogeneous soils, we discuss the representativeness of different observation types to be used for the assimilation. G. Evensen. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99(C5):10143-10162, 1994

Advanced interactive display formats for terminal area traffic control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.

1996-01-01

This report describes the basic design considerations for perspective air traffic control displays. A software framework has been developed for manual viewing parameter setting (MVPS) in preparation for continued, ongoing developments on automated viewing parameter setting (AVPS) schemes. Two distinct modes of MVPS operations are considered, both of which utilize manipulation pointers imbedded in the three-dimensional scene: (1) direct manipulation of the viewing parameters -- in this mode the manipulation pointers act like the control-input device, through which the viewing parameter changes are made. Part of the parameters are rate controlled, and part of them position controlled. This mode is intended for making fast, iterative small changes in the parameters. (2) Indirect manipulation of the viewing parameters -- this mode is intended primarily for introducing large, predetermined changes in the parameters. Requests for changes in viewing parameter setting are entered manually by the operator by moving viewing parameter manipulation pointers on the screen. The motion of these pointers, which are an integral part of the 3-D scene, is limited to the boundaries of the screen. This arrangement has been chosen in order to preserve the correspondence between the spatial lay-outs of the new and the old viewing parameter setting, a feature which contributes to preventing spatial disorientation of the operator. For all viewing operations, e.g. rotation, translation and ranging, the actual change is executed automatically by the system, through gradual transitions with an exponentially damped, sinusoidal velocity profile, in this work referred to as 'slewing' motions. The slewing functions, which eliminate discontinuities in the viewing parameter changes, are designed primarily for enhancing the operator's impression that he, or she, is dealing with an actually existing physical system, rather than an abstract computer-generated scene. The proposed, continued research efforts will deal with the development of automated viewing parameter setting schemes. These schemes employ an optimization strategy, aimed at identifying the best possible vantage point, from which the air traffic control scene can be viewed for a given traffic situation. They determine whether a change in viewing parameter setting is required and determine the dynamic path along which the change to the new viewing parameter setting should take place.

Developing a methodology for the inverse estimation of root architectural parameters from field based sampling schemes

NASA Astrophysics Data System (ADS)

Morandage, Shehan; Schnepf, Andrea; Vanderborght, Jan; Javaux, Mathieu; Leitner, Daniel; Laloy, Eric; Vereecken, Harry

2017-04-01

Root traits are increasingly important in breading of new crop varieties. E.g., longer and fewer lateral roots are suggested to improve drought resistance of wheat. Thus, detailed root architectural parameters are important. However, classical field sampling of roots only provides more aggregated information such as root length density (coring), root counts per area (trenches) or root arrival curves at certain depths (rhizotubes). We investigate the possibility of obtaining the information about root system architecture of plants using field based classical root sampling schemes, based on sensitivity analysis and inverse parameter estimation. This methodology was developed based on a virtual experiment where a root architectural model was used to simulate root system development in a field, parameterized for winter wheat. This information provided the ground truth which is normally unknown in a real field experiment. The three sampling schemes coring, trenching, and rhizotubes where virtually applied to and aggregated information computed. Morris OAT global sensitivity analysis method was then performed to determine the most sensitive parameters of root architecture model for the three different sampling methods. The estimated means and the standard deviation of elementary effects of a total number of 37 parameters were evaluated. Upper and lower bounds of the parameters were obtained based on literature and published data of winter wheat root architectural parameters. Root length density profiles of coring, arrival curve characteristics observed in rhizotubes, and root counts in grids of trench profile method were evaluated statistically to investigate the influence of each parameter using five different error functions. Number of branches, insertion angle inter-nodal distance, and elongation rates are the most sensitive parameters and the parameter sensitivity varies slightly with the depth. Most parameters and their interaction with the other parameters show highly nonlinear effect to the model output. The most sensitive parameters will be subject to inverse estimation from the virtual field sampling data using DREAMzs algorithm. The estimated parameters can then be compared with the ground truth in order to determine the suitability of the sampling schemes to identify specific traits or parameters of the root growth model.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Systematic parameter estimation and sensitivity analysis using a multidimensional PEMFC model coupled with DAKOTA.

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

Wang, Chao Yang; Luo, Gang; Jiang, Fangming

2010-05-01

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated inmore » order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.« less

A sensitivity analysis of cloud properties to CLUBB parameters in the single-column Community Atmosphere Model (SCAM5)

DOE PAGES

Guo, Zhun; Wang, Minghuai; Qian, Yun; ...

2014-08-13

In this study, we investigate the sensitivity of simulated shallow cumulus and stratocumulus clouds to selected tunable parameters of Cloud Layers Unified by Binormals (CLUBB) in the single column version of Community Atmosphere Model version 5 (SCAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is adopted to study the responses of simulated cloud fields to tunable parameters. One stratocumulus and two shallow convection cases are configured at both coarse and fine vertical resolutions in this study.. Our results show that most of the variance in simulated cloudmore » fields can be explained by a small number of tunable parameters. The parameters related to Newtonian and buoyancy-damping terms of total water flux are found to be the most influential parameters for stratocumulus. For shallow cumulus, the most influential parameters are those related to skewness of vertical velocity, reflecting the strong coupling between cloud properties and dynamics in this regime. The influential parameters in the stratocumulus case are sensitive to the choice of the vertical resolution while little sensitivity is found for the shallow convection cases, as eddy mixing length (or dissipation time scale) plays a more important role and depends more strongly on the vertical resolution in stratocumulus than in shallow convections. The influential parameters remain almost unchanged when the number of tunable parameters increases from 16 to 35. This study improves understanding of the CLUBB behavior associated with parameter uncertainties.« less

Sensitivity and Specificity of Eustachian Tube Function Tests in Adults

PubMed Central

Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.

2013-01-01

Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429

Measures of GCM Performance as Functions of Model Parameters Affecting Clouds and Radiation

NASA Astrophysics Data System (ADS)

Jackson, C.; Mu, Q.; Sen, M.; Stoffa, P.

2002-05-01

This abstract is one of three related presentations at this meeting dealing with several issues surrounding optimal parameter and uncertainty estimation of model predictions of climate. Uncertainty in model predictions of climate depends in part on the uncertainty produced by model approximations or parameterizations of unresolved physics. Evaluating these uncertainties is computationally expensive because one needs to evaluate how arbitrary choices for any given combination of model parameters affects model performance. Because the computational effort grows exponentially with the number of parameters being investigated, it is important to choose parameters carefully. Evaluating whether a parameter is worth investigating depends on two considerations: 1) does reasonable choices of parameter values produce a large range in model response relative to observational uncertainty? and 2) does the model response depend non-linearly on various combinations of model parameters? We have decided to narrow our attention to selecting parameters that affect clouds and radiation, as it is likely that these parameters will dominate uncertainties in model predictions of future climate. We present preliminary results of ~20 to 30 AMIPII style climate model integrations using NCAR's CCM3.10 that show model performance as functions of individual parameters controlling 1) critical relative humidity for cloud formation (RHMIN), and 2) boundary layer critical Richardson number (RICR). We also explore various definitions of model performance that include some or all observational data sources (surface air temperature and pressure, meridional and zonal winds, clouds, long and short-wave cloud forcings, etc...) and evaluate in a few select cases whether the model's response depends non-linearly on the parameter values we have selected.

Quantification of tumor perfusion using dynamic contrast-enhanced ultrasound: impact of mathematical modeling

NASA Astrophysics Data System (ADS)

Doury, Maxime; Dizeux, Alexandre; de Cesare, Alain; Lucidarme, Olivier; Pellot-Barakat, Claire; Bridal, S. Lori; Frouin, Frédérique

2017-02-01

Dynamic contrast-enhanced ultrasound has been proposed to monitor tumor therapy, as a complement to volume measurements. To assess the variability of perfusion parameters in ideal conditions, four consecutive test-retest studies were acquired in a mouse tumor model, using controlled injections. The impact of mathematical modeling on parameter variability was then investigated. Coefficients of variation (CV) of tissue blood volume (BV) and tissue blood flow (BF) based-parameters were estimated inside 32 sub-regions of the tumors, comparing the log-normal (LN) model with a one-compartment model fed by an arterial input function (AIF) and improved by the introduction of a time delay parameter. Relative perfusion parameters were also estimated by normalization of the LN parameters and normalization of the one-compartment parameters estimated with the AIF, using a reference tissue (RT) region. A direct estimation (rRTd) of relative parameters, based on the one-compartment model without using the AIF, was also obtained by using the kinetics inside the RT region. Results of test-retest studies show that absolute regional parameters have high CV, whatever the approach, with median values of about 30% for BV, and 40% for BF. The positive impact of normalization was established, showing a coherent estimation of relative parameters, with reduced CV (about 20% for BV and 30% for BF using the rRTd approach). These values were significantly lower (p  <  0.05) than the CV of absolute parameters. The rRTd approach provided the smallest CV and should be preferred for estimating relative perfusion parameters.

Are quantitative sensitivity analysis methods always reliable?

NASA Astrophysics Data System (ADS)

Huang, X.

2016-12-01

Physical parameterizations developed to represent subgrid-scale physical processes include various uncertain parameters, leading to large uncertainties in today's Earth System Models (ESMs). Sensitivity Analysis (SA) is an efficient approach to quantitatively determine how the uncertainty of the evaluation metric can be apportioned to each parameter. Also, SA can identify the most influential parameters, as a result to reduce the high dimensional parametric space. In previous studies, some SA-based approaches, such as Sobol' and Fourier amplitude sensitivity testing (FAST), divide the parameters into sensitive and insensitive groups respectively. The first one is reserved but the other is eliminated for certain scientific study. However, these approaches ignore the disappearance of the interactive effects between the reserved parameters and the eliminated ones, which are also part of the total sensitive indices. Therefore, the wrong sensitive parameters might be identified by these traditional SA approaches and tools. In this study, we propose a dynamic global sensitivity analysis method (DGSAM), which iteratively removes the least important parameter until there are only two parameters left. We use the CLM-CASA, a global terrestrial model, as an example to verify our findings with different sample sizes ranging from 7000 to 280000. The result shows DGSAM has abilities to identify more influential parameters, which is confirmed by parameter calibration experiments using four popular optimization methods. For example, optimization using Top3 parameters filtered by DGSAM could achieve substantial improvement against Sobol' by 10%. Furthermore, the current computational cost for calibration has been reduced to 1/6 of the original one. In future, it is necessary to explore alternative SA methods emphasizing parameter interactions.

Relationships of stroke patients' gait parameters with fear of falling.

PubMed

Park, Jin; Yoo, Ingyu

2014-12-01

[Purpose] The purpose of this study was to assess the correlation of gait parameters with fear of falling in stroke survivors. [Subjects] In total, 12 patients with stroke participated. [Methods] The subjects performed on a Biodex Gait Trainer 2 for 5 min to evaluate characteristic gait parameters. The kinematic gait parameters measured were gait speed, step cycle, step length, and time on each foot (step symmetry). All the subjects also completed a fall anxiety survey. [Results] Correlations between gait parameters and fear of falling scores were calculated. There was a moderate degree of correlation between fear of falling scores and the step cycle item of gait parameters. [Conclusions] According to our results, the step cycle gait parameter may be related to increased fall anxiety.

Selection of solubility parameters for characterization of pharmaceutical excipients.

PubMed

Adamska, Katarzyna; Voelkel, Adam; Héberger, Károly

2007-11-09

The solubility parameter (delta(2)), corrected solubility parameter (delta(T)) and its components (delta(d), delta(p), delta(h)) were determined for series of pharmaceutical excipients by using inverse gas chromatography (IGC). Principal component analysis (PCA) was applied for the selection of the solubility parameters which assure the complete characterization of examined materials. Application of PCA suggests that complete description of examined materials is achieved with four solubility parameters, i.e. delta(2) and Hansen solubility parameters (delta(d), delta(p), delta(h)). Selection of the excipients through PCA of their solubility parameters data can be used for prediction of their behavior in a multi-component system, e.g. for selection of the best materials to form stable pharmaceutical liquid mixtures or stable coating formulation.

On the problem of modeling for parameter identification in distributed structures

NASA Technical Reports Server (NTRS)

Norris, Mark A.; Meirovitch, Leonard

1988-01-01

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

The application of neural networks to the SSME startup transient

NASA Technical Reports Server (NTRS)

Meyer, Claudia M.; Maul, William A.

1991-01-01

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Macular versus Retinal Nerve Fiber Layer Parameters for Diagnosing Manifest Glaucoma: A Systematic Review of Diagnostic Accuracy Studies.

PubMed

Oddone, Francesco; Lucenteforte, Ersilia; Michelessi, Manuele; Rizzo, Stanislao; Donati, Simone; Parravano, Mariacristina; Virgili, Gianni

2016-05-01

Macular parameters have been proposed as an alternative to retinal nerve fiber layer (RNFL) parameters to diagnose glaucoma. Comparing the diagnostic accuracy of macular parameters, specifically the ganglion cell complex (GCC) and ganglion cell inner plexiform layer (GCIPL), with the accuracy of RNFL parameters for detecting manifest glaucoma is important to guide clinical practice and future research. Studies using spectral domain optical coherence tomography (SD OCT) and reporting macular parameters were included if they allowed the extraction of accuracy data for diagnosing manifest glaucoma, as confirmed with automated perimetry or a clinician's optic nerve head (ONH) assessment. Cross-sectional cohort studies and case-control studies were included. The QUADAS 2 tool was used to assess methodological quality. Only direct comparisons of macular versus RNFL parameters (i.e., in the same study) were conducted. Summary sensitivity and specificity of each macular or RNFL parameter were reported, and the relative diagnostic odds ratio (DOR) was calculated in hierarchical summary receiver operating characteristic (HSROC) models to compare them. Thirty-four studies investigated macular parameters using RTVue OCT (Optovue Inc., Fremont, CA) (19 studies, 3094 subjects), Cirrus OCT (Carl Zeiss Meditec Inc., Dublin, CA) (14 studies, 2164 subjects), or 3D Topcon OCT (Topcon, Inc., Tokyo, Japan) (4 studies, 522 subjects). Thirty-two of these studies allowed comparisons between macular and RNFL parameters. Studies generally reported sensitivities at fixed specificities, more commonly 0.90 or 0.95, with sensitivities of most best-performing parameters between 0.65 and 0.75. For all OCT devices, compared with RNFL parameters, macular parameters were similarly or slightly less accurate for detecting glaucoma at the highest reported specificity, which was confirmed in analyses at the lowest specificity. Included studies suffered from limitations, especially the case-control study design, which is known to overestimate accuracy. However, this flaw is less relevant as a source of bias in direct comparisons conducted within studies. With the use of OCT, RNFL parameters are still preferable to macular parameters for diagnosing manifest glaucoma, but the differences are small. Because of high heterogeneity, direct comparative or randomized studies of OCT devices or OCT parameters and diagnostic strategies are essential. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Fracture characterization by hybrid enumerative search and Gauss-Newton least-squares inversion methods

NASA Astrophysics Data System (ADS)

Alkharji, Mohammed N.

Most fracture characterization methods provide a general description of the fracture parameters as part of the reservoirs parameters; the fracture interaction and geometry within the reservoir is given less attention. T-Matrix and Linear Slip effective medium fracture models are implemented to invert the elastic tensor for the parameters and geometries of the fractures within the reservoir. The fracture inverse problem has an ill-posed, overdetermined, underconstrained rank-deficit system of equations. Least-squares inverse methods are used to solve the problem. A good starting initial model for the parameters is a key factor in the reliability of the inversion. Most methods assume that the starting parameters are close to the solution to avoid inaccurate local minimum solutions. The prior knowledge of the fracture parameters and their geometry is not available. We develop a hybrid, enumerative and Gauss-Newton, method that estimates the fracture parameters and geometry from the elastic tensor with no prior knowledge of the initial parameter values. The fracture parameters are separated into two groups. The first group contains the fracture parameters with no prior information, and the second group contains the parameters with known prior information. Different models are generated from the first group parameters by sampling the solution space over a predefined range of possible solutions for each parameter. Each model generated by the first group is fixed and used as a starting model to invert for the second group of parameters using the Gauss-Newton method. The least-squares residual between the observed elastic tensor and the estimated elastic tensor is calculated for each model. The model parameters that yield the least-squares residual corresponds to the correct fracture reservoir parameters and geometry. Two synthetic examples of fractured reservoirs with oil and gas saturations were inverted with no prior information about the fracture properties. The results showed that the hybrid algorithm successfully predicted the fracture parametrization, geometry, and the fluid content within the modeled reservoir. The method was also applied on an elastic tensor extracted from the Weyburn field in Saskatchewan, Canada. The solution suggested no presence of fractures but only a VTI system caused by the shale layering in the targeted reservoir, this interpretation is supported by other Weyburn field data.

Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R

USGS Publications Warehouse

Asquith, William H.

2014-01-01

The implementation characteristics of two method of L-moments (MLM) algorithms for parameter estimation of the 4-parameter Asymmetric Exponential Power (AEP4) distribution are studied using the R environment for statistical computing. The objective is to validate the algorithms for general application of the AEP4 using R. An algorithm was introduced in the original study of the L-moments for the AEP4. A second or alternative algorithm is shown to have a larger L-moment-parameter domain than the original. The alternative algorithm is shown to provide reliable parameter production and recovery of L-moments from fitted parameters. A proposal is made for AEP4 implementation in conjunction with the 4-parameter Kappa distribution to create a mixed-distribution framework encompassing the joint L-skew and L-kurtosis domains. The example application provides a demonstration of pertinent algorithms with L-moment statistics and two 4-parameter distributions (AEP4 and the Generalized Lambda) for MLM fitting to a modestly asymmetric and heavy-tailed dataset using R.

Improved parameter inference in catchment models: 1. Evaluating parameter uncertainty

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-10-01

A Bayesian methodology is developed to evaluate parameter uncertainty in catchment models fitted to a hydrologic response such as runoff, the goal being to improve the chance of successful regionalization. The catchment model is posed as a nonlinear regression model with stochastic errors possibly being both autocorrelated and heteroscedastic. The end result of this methodology, which may use Box-Cox power transformations and ARMA error models, is the posterior distribution, which summarizes what is known about the catchment model parameters. This can be simplified to a multivariate normal provided a linearization in parameter space is acceptable; means of checking and improving this assumption are discussed. The posterior standard deviations give a direct measure of parameter uncertainty, and study of the posterior correlation matrix can indicate what kinds of data are required to improve the precision of poorly determined parameters. Finally, a case study involving a nine-parameter catchment model fitted to monthly runoff and soil moisture data is presented. It is shown that use of ordinary least squares when its underlying error assumptions are violated gives an erroneous description of parameter uncertainty.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Ground Data System Analysis Tools to Track Flight System State Parameters for the Mars Science Laboratory (MSL) and Beyond

NASA Technical Reports Server (NTRS)

Allard, Dan; Deforrest, Lloyd

2014-01-01

Flight software parameters enable space mission operators fine-tuned control over flight system configurations, enabling rapid and dynamic changes to ongoing science activities in a much more flexible manner than can be accomplished with (otherwise broadly used) configuration file based approaches. The Mars Science Laboratory (MSL), Curiosity, makes extensive use of parameters to support complex, daily activities via commanded changes to said parameters in memory. However, as the loss of Mars Global Surveyor (MGS) in 2006 demonstrated, flight system management by parameters brings with it risks, including the possibility of losing track of the flight system configuration and the threat of invalid command executions. To mitigate this risk a growing number of missions have funded efforts to implement parameter tracking parameter state software tools and services including MSL and the Soil Moisture Active Passive (SMAP) mission. This paper will discuss the engineering challenges and resulting software architecture of MSL's onboard parameter state tracking software and discuss the road forward to make parameter management tools suitable for use on multiple missions.

Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models

PubMed Central

2011-01-01

In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison. PMID:21989173

Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

PubMed

Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

2018-01-01

Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Useful surface parameters for biomaterial discrimination.

PubMed

Etxeberria, Marina; Escuin, Tomas; Vinas, Miquel; Ascaso, Carlos

2015-01-01

Topographical features of biomaterials' surfaces are determinant when addressing their application site. Unfortunately up to date there has not been an agreement regarding which surface parameters are more representative in discriminating between materials. Discs (n = 16) of different currently used materials for implant prostheses fabrication, such as cast cobalt-chrome, direct laser metal soldered (DLMS) cobalt-chrome, titanium grade V, zirconia (Y-TZP), E-glass fiber-reinforced composite and polyetheretherketone (PEEK) were manufactured. Nanoscale topographical surface roughness parameters generated by atomic force microscopy (AFM), microscale surface roughness parameters obtained by white light interferometry (WLI) and water angle values obtained by the sessile-water-drop method were analyzed in order to assess which parameter provides the best optimum surface characterization method. Correlations between nanoroughness, microroughness, and hydrophobicity data were performed to achieve the best parameters giving the highest discriminatory power. A subset of six parameters for surface characterization were proposed. AFM and WLI techniques gave complementary information. Wettability did not correlate with any of the nanoroughness parameters while it however showed a weak correlation with microroughness parameters. © Wiley Periodicals, Inc.

Description of the Hexadecapole Deformation Parameter in the sdg Interacting Boson Model

NASA Astrophysics Data System (ADS)

Liu, Yu-xin; Sun, Di; Wang, Jia-jun; Han, Qi-zhi

1998-04-01

The hexadecapole deformation parameter β4 of the rare-earth and actinide nuclei is investigated in the framework of the sdg interacing boson model. An explicit relation between the geometric hexadecapole deformation parameter β4 and the intrinsic deformation parameters epsilon4, epsilon2 are obtained. The deformation parameters β4 of the rare-earths and actinides are determined without any free parameter. The calculated results agree with experimental data well. It also shows that the SU(5) limit of the sdg interacting boson model can describe the β4 systematics as well as the SU(3) limit.

Four-parameter potential box with inverse square singular boundaries

NASA Astrophysics Data System (ADS)

Alhaidari, A. D.; Taiwo, T. J.

2018-03-01

Using the Tridiagonal Representation Approach (TRA), we obtain solutions (energy spectrum and corresponding wavefunctions) for a four-parameter potential box with inverse square singularity at the boundaries. It could be utilized in physical applications to replace the widely used one-parameter infinite square potential well (ISPW). The four parameters of the potential provide an added flexibility over the one-parameter ISPW to control the physical features of the system. The two potential parameters that give the singularity strength at the boundaries are naturally constrained to avoid the inherent quantum anomalies associated with the inverse square potential.

PV cells electrical parameters measurement

NASA Astrophysics Data System (ADS)

Cibira, Gabriel

2017-12-01

When measuring optical parameters of a photovoltaic silicon cell, precise results bring good electrical parameters estimation, applying well-known physical-mathematical models. Nevertheless, considerable re-combination phenomena might occur in both surface and intrinsic thin layers within novel materials. Moreover, rear contact surface parameters may influence close-area re-combination phenomena, too. Therefore, the only precise electrical measurement approach is to prove assumed cell electrical parameters. Based on theoretical approach with respect to experiments, this paper analyses problems within measurement procedures and equipment used for electrical parameters acquisition within a photovoltaic silicon cell, as a case study. Statistical appraisal quality is contributed.

Markov Chain Monte Carlo Used in Parameter Inference of Magnetic Resonance Spectra

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

Hock, Kiel; Earle, Keith

2016-02-06

In this paper, we use Boltzmann statistics and the maximum likelihood distribution derived from Bayes’ Theorem to infer parameter values for a Pake Doublet Spectrum, a lineshape of historical significance and contemporary relevance for determining distances between interacting magnetic dipoles. A Metropolis Hastings Markov Chain Monte Carlo algorithm is implemented and designed to find the optimum parameter set and to estimate parameter uncertainties. In conclusion, the posterior distribution allows us to define a metric on parameter space that induces a geometry with negative curvature that affects the parameter uncertainty estimates, particularly for spectra with low signal to noise.

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

PubMed

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

New fundamental parameters for attitude representation

NASA Astrophysics Data System (ADS)

Patera, Russell P.

2017-08-01

A new attitude parameter set is developed to clarify the geometry of combining finite rotations in a rotational sequence and in combining infinitesimal angular increments generated by angular rate. The resulting parameter set of six Pivot Parameters represents a rotation as a great circle arc on a unit sphere that can be located at any clocking location in the rotation plane. Two rotations are combined by linking their arcs at either of the two intersection points of the respective rotation planes. In a similar fashion, linking rotational increments produced by angular rate is used to derive the associated kinematical equations, which are linear and have no singularities. Included in this paper is the derivation of twelve Pivot Parameter elements that represent all twelve Euler Angle sequences, which enables efficient conversions between Pivot Parameters and any Euler Angle sequence. Applications of this new parameter set include the derivation of quaternions and the quaternion composition rule, as well as, the derivation of the analytical solution to time dependent coning motion. The relationships between Pivot Parameters and traditional parameter sets are included in this work. Pivot Parameters are well suited for a variety of aerospace applications due to their effective composition rule, singularity free kinematic equations, efficient conversion to and from Euler Angle sequences and clarity of their geometrical foundation.

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

NASA Astrophysics Data System (ADS)

Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

Towards simplification of hydrologic modeling: Identification of dominant processes

USGS Publications Warehouse

Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

2016-01-01

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Edge Modeling by Two Blur Parameters in Varying Contrasts.

PubMed

Seo, Suyoung

2018-06-01

This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Dependencies and Ill-designed Parameters Within High-speed Videoendoscopy and Acoustic Signal Analysis.

PubMed

Schlegel, Patrick; Stingl, Michael; Kunduk, Melda; Kniesburges, Stefan; Bohr, Christopher; Döllinger, Michael

2018-05-31

The phonatory process is often judged during sustained phonation by analyzing the acoustic voice signal and the vocal fold vibrations. Many formulas and parameters have been suggested for qualifying the characteristics of the acoustic signal and the vocal fold vibrations during sustained phonation. These parameters are directly computed from the acoustic signal and the endoscopic glottal area waveform (GAW). The GAW is calculated from laryngeal high-speed videoendoscopy (HSV) recordings and describes the increase and decrease of the glottal area during the phonation process, that is, the opening and closing of the two oscillating vocal folds over time. However, some of the parameters have strong mathematical dependencies with one another and some are ill-defined. The purpose of this study is to identify mathematical dependencies between parameters with the aim of reducing their numbers and suggesting which parameters may best describe the properties of the GAW and the acoustical signal. In this preliminary investigation, 20 frequently used parameters are examined: 10 GAW only and 10 both GAW and acoustic parameters. In total 13 parameters can be neglected because of mathematical dependencies. In addition, nine of these parameters show problematic features that range from unexpected behavior to ill definition. Reducing the number of parameters appears to be necessary to standardize vocal fold function analysis. This may lead to better comparability of research results from different studies. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Identification of hydrological model parameter variation using ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao

2016-12-01

Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.

A new Bayesian recursive technique for parameter estimation

NASA Astrophysics Data System (ADS)

Kaheil, Yasir H.; Gill, M. Kashif; McKee, Mac; Bastidas, Luis

2006-08-01

The performance of any model depends on how well its associated parameters are estimated. In the current application, a localized Bayesian recursive estimation (LOBARE) approach is devised for parameter estimation. The LOBARE methodology is an extension of the Bayesian recursive estimation (BARE) method. It is applied in this paper on two different types of models: an artificial intelligence (AI) model in the form of a support vector machine (SVM) application for forecasting soil moisture and a conceptual rainfall-runoff (CRR) model represented by the Sacramento soil moisture accounting (SAC-SMA) model. Support vector machines, based on statistical learning theory (SLT), represent the modeling task as a quadratic optimization problem and have already been used in various applications in hydrology. They require estimation of three parameters. SAC-SMA is a very well known model that estimates runoff. It has a 13-dimensional parameter space. In the LOBARE approach presented here, Bayesian inference is used in an iterative fashion to estimate the parameter space that will most likely enclose a best parameter set. This is done by narrowing the sampling space through updating the "parent" bounds based on their fitness. These bounds are actually the parameter sets that were selected by BARE runs on subspaces of the initial parameter space. The new approach results in faster convergence toward the optimal parameter set using minimum training/calibration data and fewer sets of parameter values. The efficacy of the localized methodology is also compared with the previously used BARE algorithm.

Parameter estimation in 3D affine and similarity transformation: implementation of variance component estimation

NASA Astrophysics Data System (ADS)

Amiri-Simkooei, A. R.

2018-01-01

Three-dimensional (3D) coordinate transformations, generally consisting of origin shifts, axes rotations, scale changes, and skew parameters, are widely used in many geomatics applications. Although in some geodetic applications simplified transformation models are used based on the assumption of small transformation parameters, in other fields of applications such parameters are indeed large. The algorithms of two recent papers on the weighted total least-squares (WTLS) problem are used for the 3D coordinate transformation. The methodology can be applied to the case when the transformation parameters are generally large of which no approximate values of the parameters are required. Direct linearization of the rotation and scale parameters is thus not required. The WTLS formulation is employed to take into consideration errors in both the start and target systems on the estimation of the transformation parameters. Two of the well-known 3D transformation methods, namely affine (12, 9, and 8 parameters) and similarity (7 and 6 parameters) transformations, can be handled using the WTLS theory subject to hard constraints. Because the method can be formulated by the standard least-squares theory with constraints, the covariance matrix of the transformation parameters can directly be provided. The above characteristics of the 3D coordinate transformation are implemented in the presence of different variance components, which are estimated using the least squares variance component estimation. In particular, the estimability of the variance components is investigated. The efficacy of the proposed formulation is verified on two real data sets.

Real-Time Classification of Exercise Exertion Levels Using Discriminant Analysis of HRV Data.

PubMed

Jeong, In Cheol; Finkelstein, Joseph

2015-01-01

Heart rate variability (HRV) was shown to reflect activation of sympathetic nervous system however it is not clear which set of HRV parameters is optimal for real-time classification of exercise exertion levels. There is no studies that compared potential of two types of HRV parameters (time-domain and frequency-domain) in predicting exercise exertion level using discriminant analysis. The main goal of this study was to compare potential of HRV time-domain parameters versus HRV frequency-domain parameters in classifying exercise exertion level. Rest, exercise, and recovery categories were used in classification models. Overall 79.5% classification agreement by the time-domain parameters as compared to overall 52.8% classification agreement by frequency-domain parameters demonstrated that the time-domain parameters had higher potential in classifying exercise exertion levels.

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

Quadratic semiparametric Von Mises calculus

PubMed Central

Robins, James; Li, Lingling; Tchetgen, Eric

2009-01-01

We discuss a new method of estimation of parameters in semiparametric and nonparametric models. The method is based on U-statistics constructed from quadratic influence functions. The latter extend ordinary linear influence functions of the parameter of interest as defined in semiparametric theory, and represent second order derivatives of this parameter. For parameters for which the matching cannot be perfect the method leads to a bias-variance trade-off, and results in estimators that converge at a slower than n–1/2-rate. In a number of examples the resulting rate can be shown to be optimal. We are particularly interested in estimating parameters in models with a nuisance parameter of high dimension or low regularity, where the parameter of interest cannot be estimated at n–1/2-rate. PMID:23087487

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

Experience of the JPL Exploratory Data Analysis Team at validating HIRS2/MSU cloud parameters

NASA Technical Reports Server (NTRS)

Kahn, Ralph; Haskins, Robert D.; Granger-Gallegos, Stephanie; Pursch, Andrew; Delgenio, Anthony

1992-01-01

Validation of the HIRS2/MSU cloud parameters began with the cloud/climate feedback problem. The derived effective cloud amount is less sensitive to surface temperature for higher clouds. This occurs because as the cloud elevation increases, the difference between surface temperature and cloud temperature increases, so only a small change in cloud amount is needed to effect a large change in radiance at the detector. By validating the cloud parameters it is meant 'developing a quantitative sense for the physical meaning of the measured parameters', by: (1) identifying the assumptions involved in deriving parameters from the measured radiances, (2) testing the input data and derived parameters for statistical error, sensitivity, and internal consistency, and (3) comparing with similar parameters obtained from other sources using other techniques.

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

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

Sun, Yu; Hou, Zhangshuan; Huang, Maoyi

2013-12-10

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find thatmore » using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.« less

Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Moroz, I.; Palmer, T.

2015-12-01

It is now acknowledged that representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic ensemble forecasts, and a number of different techniques have been proposed for this purpose. Stochastic convection parameterization schemes use random numbers to represent the difference between a deterministic parameterization scheme and the true atmosphere, accounting for the unresolved sub grid-scale variability associated with convective clouds. An alternative approach varies the values of poorly constrained physical parameters in the model to represent the uncertainty in these parameters. This study presents new perturbed parameter schemes for use in the European Centre for Medium Range Weather Forecasts (ECMWF) convection scheme. Two types of scheme are developed and implemented. Both schemes represent the joint uncertainty in four of the parameters in the convection parametrisation scheme, which was estimated using the Ensemble Prediction and Parameter Estimation System (EPPES). The first scheme developed is a fixed perturbed parameter scheme, where the values of uncertain parameters are changed between ensemble members, but held constant over the duration of the forecast. The second is a stochastically varying perturbed parameter scheme. The performance of these schemes was compared to the ECMWF operational stochastic scheme, Stochastically Perturbed Parametrisation Tendencies (SPPT), and to a model which does not represent uncertainty in convection. The skill of probabilistic forecasts made using the different models was evaluated. While the perturbed parameter schemes improve on the stochastic parametrisation in some regards, the SPPT scheme outperforms the perturbed parameter approaches when considering forecast variables that are particularly sensitive to convection. Overall, SPPT schemes are the most skilful representations of model uncertainty due to convection parametrisation. Reference: H. M. Christensen, I. M. Moroz, and T. N. Palmer, 2015: Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization. J. Atmos. Sci., 72, 2525-2544.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

Enamel surface topography analysis for diet discrimination. A methodology to enhance and select discriminative parameters

NASA Astrophysics Data System (ADS)

Francisco, Arthur; Blondel, Cécile; Brunetière, Noël; Ramdarshan, Anusha; Merceron, Gildas

2018-03-01

Tooth wear and, more specifically, dental microwear texture is a dietary proxy that has been used for years in vertebrate paleoecology and ecology. DMTA, dental microwear texture analysis, relies on a few parameters related to the surface complexity, anisotropy and heterogeneity of the enamel facets at the micrometric scale. Working with few but physically meaningful parameters helps in comparing published results and in defining levels for classification purposes. Other dental microwear approaches are based on ISO parameters and coupled with statistical tests to find the more relevant ones. The present study roughly utilizes most of the aforementioned parameters in their more or less modified form. But more than parameters, we here propose a new approach: instead of a single parameter characterizing the whole surface, we sample the surface and thus generate 9 derived parameters in order to broaden the parameter set. The identification of the most discriminative parameters is performed with an automated procedure which is an extended and refined version of the workflows encountered in some studies. The procedure in its initial form includes the most common tools, like the ANOVA and the correlation analysis, along with the required mathematical tests. The discrimination results show that a simplified form of the procedure is able to more efficiently identify the desired number of discriminative parameters. Also highlighted are some trends like the relevance of working with both height and spatial parameters, as well as the potential benefits of dimensionless surfaces. On a set of 45 surfaces issued from 45 specimens of three modern ruminants with differences in feeding preferences (grazing, leaf-browsing and fruit-eating), it is clearly shown that the level of wear discrimination is improved with the new methodology compared to the other ones.

Behavior of sensitivities in the one-dimensional advection-dispersion equation: Implications for parameter estimation and sampling design

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1987-01-01

The spatial and temporal variability of sensitivities has a significant impact on parameter estimation and sampling design for studies of solute transport in porous media. Physical insight into the behavior of sensitivities is offered through an analysis of analytically derived sensitivities for the one-dimensional form of the advection-dispersion equation. When parameters are estimated in regression models of one-dimensional transport, the spatial and temporal variability in sensitivities influences variance and covariance of parameter estimates. Several principles account for the observed influence of sensitivities on parameter uncertainty. (1) Information about a physical parameter may be most accurately gained at points in space and time with a high sensitivity to the parameter. (2) As the distance of observation points from the upstream boundary increases, maximum sensitivity to velocity during passage of the solute front increases and the consequent estimate of velocity tends to have lower variance. (3) The frequency of sampling must be “in phase” with the S shape of the dispersion sensitivity curve to yield the most information on dispersion. (4) The sensitivity to the dispersion coefficient is usually at least an order of magnitude less than the sensitivity to velocity. (5) The assumed probability distribution of random error in observations of solute concentration determines the form of the sensitivities. (6) If variance in random error in observations is large, trends in sensitivities of observation points may be obscured by noise and thus have limited value in predicting variance in parameter estimates among designs. (7) Designs that minimize the variance of one parameter may not necessarily minimize the variance of other parameters. (8) The time and space interval over which an observation point is sensitive to a given parameter depends on the actual values of the parameters in the underlying physical system.

What predicts inattention in adolescents? An experience-sampling study comparing chronotype, subjective, and objective sleep parameters.

PubMed

Hennig, Timo; Krkovic, Katarina; Lincoln, Tania M

2017-10-01

Many adolescents sleep insufficiently, which may negatively affect their functioning during the day. To improve sleep interventions, we need a better understanding of the specific sleep-related parameters that predict poor functioning. We investigated to which extent subjective and objective parameters of sleep in the preceding night (state parameters) and the trait variable chronotype predict daytime inattention as an indicator of poor functioning. We conducted an experience-sampling study over one week with 61 adolescents (30 girls, 31 boys; mean age = 15.5 years, standard deviation = 1.1 years). Participants rated their inattention two times each day (morning, afternoon) on a smartphone. Subjective sleep parameters (feeling rested, positive affect upon awakening) were assessed each morning on the smartphone. Objective sleep parameters (total sleep time, sleep efficiency, wake after sleep onset) were assessed with a permanently worn actigraph. Chronotype was assessed with a self-rated questionnaire at baseline. We tested the effect of subjective and objective state parameters of sleep on daytime inattention, using multilevel multiple regressions. Then, we tested whether the putative effect of the trait parameter chronotype on inattention is mediated through state sleep parameters, again using multilevel regressions. We found that short sleep time, but no other state sleep parameter, predicted inattention to a small effect. As expected, the trait parameter chronotype also predicted inattention: morningness was associated with less inattention. However, this association was not mediated by state sleep parameters. Our results indicate that short sleep time causes inattention in adolescents. Extended sleep time might thus alleviate inattention to some extent. However, it cannot alleviate the effect of being an 'owl'. Copyright © 2017 Elsevier B.V. All rights reserved.

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global sensitivity analysis results.

NWP model forecast skill optimization via closure parameter variations

NASA Astrophysics Data System (ADS)

Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.

2012-04-01

We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.

Allergy-immunology practice parameters and strength of recommendation data: an evolutionary perspective.

PubMed

Park, Matthew H; Banks, Taylor A; Nelson, Michael R

2016-03-01

The practice parameters for allergy and immunology (A/I) are a valuable tool guiding practitioners' clinical practice. The A/I practice parameters have evolved over time in the context of evidence-based medicine milestones. To identify evolutionary trends in the character, scope, and evidence underlying recommendations in the A/I practice parameters. Practice parameters that have guided A/I from 1995 through 2014 were analyzed. Statements and recommendations with strength of recommendation categories A and B were considered to have a basis in evidence from controlled trials. Forty-three publications and updates covering 25 unique topics were identified. There was great variability in the number of recommendations made and the proportion of statements with controlled trial evidence. The mean number of recommendations made per practice parameter has decreased significantly, from 95.8 to a mean of 38.3. There also is a trend toward an increased proportion of recommendations based on controlled trial evidence in practice parameters with fewer recommendations, with a mean of 30.7% in practice parameters with at least 100 recommendations based on controlled trial evidence compared with 48.3% in practice parameters with 30 to 100 recommendations and 51.0% in those with fewer than 30 recommendations. The A/I practice parameters have evolved significantly over time. Encouragingly, greater controlled trial evidence is associated with updated practice parameters and a recent trend of more narrowly focused topics. These findings should only bolster and inspire confidence in the utility of the A/I practice parameters in assisting practitioners to navigate through the uncertainty that is intrinsic to medicine in making informed decisions with patients. Published by Elsevier Inc.

Surveillance and Control of Malaria Transmission Using Remotely Sensed Meteorological and Environmental Parameters

NASA Technical Reports Server (NTRS)

Kiang, R.; Adimi, F.; Nigro, J.

2007-01-01

Meteorological and environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters can most conveniently be obtained using remote sensing. Selected provinces and districts in Thailand and Indonesia are used to illustrate how remotely sensed meteorological and environmental parameters may enhance the capabilities for malaria surveillance and control. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.

Planning Robot-Control Parameters With Qualitative Reasoning

NASA Technical Reports Server (NTRS)

Peters, Stephen F.

1993-01-01

Qualitative-reasoning planning algorithm helps to determine quantitative parameters controlling motion of robot. Algorithm regarded as performing search in multidimensional space of control parameters from starting point to goal region in which desired result of robotic manipulation achieved. Makes use of directed graph representing qualitative physical equations describing task, and interacts, at each sampling period, with history of quantitative control parameters and sensory data, to narrow search for reliable values of quantitative control parameters.

Reference tissue modeling with parameter coupling: application to a study of SERT binding in HIV

NASA Astrophysics Data System (ADS)

Endres, Christopher J.; Hammoud, Dima A.; Pomper, Martin G.

2011-04-01

When applicable, it is generally preferred to evaluate positron emission tomography (PET) studies using a reference tissue-based approach as that avoids the need for invasive arterial blood sampling. However, most reference tissue methods have been shown to have a bias that is dependent on the level of tracer binding, and the variability of parameter estimates may be substantially affected by noise level. In a study of serotonin transporter (SERT) binding in HIV dementia, it was determined that applying parameter coupling to the simplified reference tissue model (SRTM) reduced the variability of parameter estimates and yielded the strongest between-group significant differences in SERT binding. The use of parameter coupling makes the application of SRTM more consistent with conventional blood input models and reduces the total number of fitted parameters, thus should yield more robust parameter estimates. Here, we provide a detailed evaluation of the application of parameter constraint and parameter coupling to [11C]DASB PET studies. Five quantitative methods, including three methods that constrain the reference tissue clearance (kr2) to a common value across regions were applied to the clinical and simulated data to compare measurement of the tracer binding potential (BPND). Compared with standard SRTM, either coupling of kr2 across regions or constraining kr2 to a first-pass estimate improved the sensitivity of SRTM to measuring a significant difference in BPND between patients and controls. Parameter coupling was particularly effective in reducing the variance of parameter estimates, which was less than 50% of the variance obtained with standard SRTM. A linear approach was also improved when constraining kr2 to a first-pass estimate, although the SRTM-based methods yielded stronger significant differences when applied to the clinical study. This work shows that parameter coupling reduces the variance of parameter estimates and may better discriminate between-group differences in specific binding.

Enhanced Diagnostic Capability for Glaucoma of 3-Dimensional versus 2-Dimensional Neuroretinal Rim Parameters Using Spectral Domain Optical Coherence Tomography

PubMed Central

Fan, Kenneth Chen; Tsikata, Edem; Khoueir, Ziad; Simavli, Huseyin; Guo, Rong; DeLuna, Regina; Pandit, Sumir; Que, Christian John; de Boer, Johannes F.; Chen, Teresa C.

2017-01-01

Purpose To compare the diagnostic capability of 3-dimensional (3D) neuroretinal rim parameters with existing 2-dimensional (2D) neuroretinal and retinal nerve fiber layer (RNFL) thickness rim parameters using spectral domain optical coherence tomography (SD-OCT) volume scans Materials and Methods Design Institutional prospective pilot study. Study population 65 subjects (35 open angle glaucoma patients, 30 normal patients). Observation procedures One eye of each subject was included. SD-OCT was used to obtain 2D retinal nerve fiber layer (RNFL) thickness values and five neuroretinal rim parameters [i.e. 3D minimum distance band (MDB) thickness, 3D Bruch’s membrane opening-minimum rim width (BMO-MRW), 3D rim volume, 2D rim area, and 2D rim thickness]. Main outcome measures Area under the receiver operating characteristic (AUROC) curve values, sensitivity, specificity. Results Comparing all 3D with all 2D parameters, 3D rim parameters (MDB, BMO-MRW, rim volume) generally had higher AUROC curve values (range 0.770–0.946) compared to 2D parameters (RNFL thickness, rim area, rim thickness; range 0.678–0.911). For global region analyses, all 3D rim parameters (BMO-MRW, rim volume, MDB) were equal to or better than 2D parameters (RNFL thickness, rim area, rim thickness; p-values from 0.023–1.0). Among the three 3D rim parameters (MDB, BMO-MRW, and rim volume), there were no significant differences in diagnostic capability (false discovery rate > 0.05 at 95% specificity). Conclusion 3D neuroretinal rim parameters (MDB, BMO-MRW, and rim volume) demonstrated better diagnostic capability for primary and secondary open angle glaucomas compared to 2D neuroretinal parameters (rim area, rim thickness). Compared to 2D RNFL thickness, 3D neuroretinal rim parameters have the same or better diagnostic capability. PMID:28234677

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

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

Lu, W; Southern Medical University, Guangzhou; Yan, H

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Threemore » different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)« less

Further comments on sensitivities, parameter estimation, and sampling design in one-dimensional analysis of solute transport in porous media

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1988-01-01

Sensitivities of solute concentration to parameters associated with first-order chemical decay, boundary conditions, initial conditions, and multilayer transport are examined in one-dimensional analytical models of transient solute transport in porous media. A sensitivity is a change in solute concentration resulting from a change in a model parameter. Sensitivity analysis is important because minimum information required in regression on chemical data for the estimation of model parameters by regression is expressed in terms of sensitivities. Nonlinear regression models of solute transport were tested on sets of noiseless observations from known models that exceeded the minimum sensitivity information requirements. Results demonstrate that the regression models consistently converged to the correct parameters when the initial sets of parameter values substantially deviated from the correct parameters. On the basis of the sensitivity analysis, several statements may be made about design of sampling for parameter estimation for the models examined: (1) estimation of parameters associated with solute transport in the individual layers of a multilayer system is possible even when solute concentrations in the individual layers are mixed in an observation well; (2) when estimating parameters in a decaying upstream boundary condition, observations are best made late in the passage of the front near a time chosen by adding the inverse of an hypothesized value of the source decay parameter to the estimated mean travel time at a given downstream location; (3) estimation of a first-order chemical decay parameter requires observations to be made late in the passage of the front, preferably near a location corresponding to a travel time of √2 times the half-life of the solute; and (4) estimation of a parameter relating to spatial variability in an initial condition requires observations to be made early in time relative to passage of the solute front.

Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

NASA Astrophysics Data System (ADS)

Harshan, S.; Roth, M.; Velasco, E.

2014-12-01

Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model validation studies to identify inherent deficiencies in model physics.

Sensitivity and specificity of eustachian tube function tests in adults.

PubMed

Doyle, William J; Swarts, J Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M

2013-07-01

The study demonstrates the utility of eustachian tube (ET) function (ETF) test results for accurately assigning ears to disease state. To determine if ETF tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and to define the interrelatedness of ETF test parameters. Through use of the forced-response, inflation-deflation, Valsalva, and sniffing tests, ETF was evaluated in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). Data were analyzed using logistic regression including each parameter independently and then a step-down discriminant analysis including all ETF test parameters to predict group assignment. Factor analysis operating over all parameters was used to explore relatedness. ETF testing. ETF parameters for the forced response, inflation-deflation, Valsalva, and sniffing tests measured in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). The discriminant analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency, and percentage of positive pressure equilibrated) that together correctly assigned ears to group 2 at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters: the first had negative loadings of the ETF structural parameters; the second had positive loadings of the muscle-assisted ET opening parameters; and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules

NASA Astrophysics Data System (ADS)

Hejri, Mohammad; Mokhtari, Hossein; Azizian, Mohammad Reza; Söder, Lennart

2016-04-01

Parameter extraction of the five-parameter single-diode model of solar cells and modules from experimental data is a challenging problem. These parameters are evaluated from a set of nonlinear equations that cannot be solved analytically. On the other hand, a numerical solution of such equations needs a suitable initial guess to converge to a solution. This paper presents a new set of approximate analytical solutions for the parameters of a five-parameter single-diode model of photovoltaic (PV) cells and modules. The proposed solutions provide a good initial point which guarantees numerical analysis convergence. The proposed technique needs only a few data from the PV current-voltage characteristics, i.e. open circuit voltage Voc, short circuit current Isc and maximum power point current and voltage Im; Vm making it a fast and low cost parameter determination technique. The accuracy of the presented theoretical I-V curves is verified by experimental data.

Improving hot region prediction by parameter optimization of density clustering in PPI.

PubMed

Hu, Jing; Zhang, Xiaolong

2016-11-01

This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius. Copyright © 2016. Published by Elsevier Inc.

TCP performance in ATM networks: ABR parameter tuning and ABR/UBR comparisons

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

Chien Fang; Lin, A.

1996-02-27

This paper explores two issues on TOP performance over ATM networks: ABR parameter tuning and performance comparison of binary mode ABR with enhanced UBR services. Of the fifteen parameters defined for ABR, two parameters dominate binary mode ABR performance: Rate Increase Factor (RIF) and Rate Decrease Factor (RDF). Using simulations, we study the effects of these two parameters on TOP over ABR performance. We compare TOP performance with different ABR parameter settings in terms of through-puts and fairness. The effects of different buffer sizes and LAN/WAN distances are also examined. We then compare TOP performance with the best ABR parametermore » setting with corresponding UBR service enhanced with Early Packet Discard and also with a fair buffer allocation scheme. The results show that TOP performance over binary mode ABR is very sensitive to parameter value settings, and that a poor choice of parameters can result in ABR performance worse than that of the much less expensive UBR-EPD scheme.« less

Mixed convection flow of couple stress nanofluid over oscillatory stretching sheet with heat absorption/generation effects

NASA Astrophysics Data System (ADS)

Khan, Sami Ullah; Shehzad, Sabir Ali; Rauf, Amar; Ali, Nasir

2018-03-01

The aim of this article is to highlight the unsteady mixed convective couple stress nanoliquid flow passed through stretching surface. The flow is generated due to periodic oscillations of sheet. An appropriate set of dimensionless variables are used to reduce the independent variables in governing equations arising from mathematical modeling. An analytical solution has been computed by employing the technique of homotopy method. The outcomes of various sundry parameters like couple stress parameter, the ratio of angular velocity to stretching rate, thermophoresis parameter, Hartmann number, Prandtl number, heat source/sink parameter, Schmidt number described graphically and in tabular form. It is observed that the velocity profile increases by increasing mixed convection parameter and concentration buoyancy parameter. The temperature enhances for larger values of Hartmann number and Brownian. The concentration profile increases by increasing thermophoresis parameter. Results show that wall shear stress increases by increasing couple stress parameter and ratio of oscillating frequency to stretching rate.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Identifiability, reducibility, and adaptability in allosteric macromolecules.

PubMed

Bohner, Gergő; Venkataraman, Gaurav

2017-05-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed "allostery," is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca 2+ -activated K + (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. © 2017 Bohner and Venkataraman.

Identifiability, reducibility, and adaptability in allosteric macromolecules

PubMed Central

Bohner, Gergő

2017-01-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed “allostery,” is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca2+-activated K+ (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. PMID:28416647

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Hydrodynamic Aspects of Particle Clogging in Porous Media

PubMed Central

MAYS, DAVID C.; HUNT, JAMES R.

2010-01-01

Data from 6 filtration studies, representing 43 experiments, are analyzed with a simplified version of the single-parameter O’Melia and Ali clogging model. The model parameter displays a systematic dependence on fluid velocity, which was an independent variable in each study. A cake filtration model also explains the data from one filtration study by varying a single, velocity-dependent parameter, highlighting that clogging models, because they are empirical, are not unique. Limited experimental data indicate exponential depth dependence of particle accumulation, whose impact on clogging is quantified with an extended O’Melia and Ali model. The resulting two-parameter model successfully describes the increased clogging that is always observed in the top segment of a filter. However, even after accounting for particle penetration, the two-parameter model suggests that a velocity-dependent parameter representing deposit morphology must also be included to explain the data. Most of the experimental data are described by the single-parameter O’Melia and Ali model, and the model parameter is correlated to the collector Peclet number. PMID:15707058

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

NASA Astrophysics Data System (ADS)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

A Comparative Study of Distribution System Parameter Estimation Methods

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

Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

2016-07-17

In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less

Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics

PubMed Central

Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna

2011-01-01

A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157

Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

NASA Astrophysics Data System (ADS)

Laakso, Petri; Riipinen, Tuomas; Laukkanen, Anssi; Andersson, Tom; Jokinen, Antero; Revuelta, Alejandro; Ruusuvuori, Kimmo

This paper demonstrates the successful printing and optimization of processing parameters of high-strength H13 tool steel by Selective Laser Melting (SLM). D-Optimal Design of Experiments (DOE) approach is used for parameter optimization of laser power, scanning speed and hatch width. With 50 test samples (1×1×1cm) we establish parameter windows for these three parameters in relation to part density. The calculated numerical model is found to be in good agreement with the density data obtained from the samples using image analysis. A thermomechanical finite element simulation model is constructed of the SLM process and validated by comparing the calculated densities retrieved from the model with the experimentally determined densities. With the simulation tool one can explore the effect of different parameters on density before making any printed samples. Establishing a parameter window provides the user with freedom for parameter selection such as choosing parameters that result in fastest print speed.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

A probabilistic approach for the estimation of earthquake source parameters from spectral inversion

NASA Astrophysics Data System (ADS)

Supino, M.; Festa, G.; Zollo, A.

2017-12-01

The amplitude spectrum of a seismic signal related to an earthquake source carries information about the size of the rupture, moment, stress and energy release. Furthermore, it can be used to characterize the Green's function of the medium crossed by the seismic waves. We describe the earthquake amplitude spectrum assuming a generalized Brune's (1970) source model, and direct P- and S-waves propagating in a layered velocity model, characterized by a frequency-independent Q attenuation factor. The observed displacement spectrum depends indeed on three source parameters, the seismic moment (through the low-frequency spectral level), the corner frequency (that is a proxy of the fault length) and the high-frequency decay parameter. These parameters are strongly correlated each other and with the quality factor Q; a rigorous estimation of the associated uncertainties and parameter resolution is thus needed to obtain reliable estimations.In this work, the uncertainties are characterized adopting a probabilistic approach for the parameter estimation. Assuming an L2-norm based misfit function, we perform a global exploration of the parameter space to find the absolute minimum of the cost function and then we explore the cost-function associated joint a-posteriori probability density function around such a minimum, to extract the correlation matrix of the parameters. The global exploration relies on building a Markov chain in the parameter space and on combining a deterministic minimization with a random exploration of the space (basin-hopping technique). The joint pdf is built from the misfit function using the maximum likelihood principle and assuming a Gaussian-like distribution of the parameters. It is then computed on a grid centered at the global minimum of the cost-function. The numerical integration of the pdf finally provides mean, variance and correlation matrix associated with the set of best-fit parameters describing the model. Synthetic tests are performed to investigate the robustness of the method and uncertainty propagation from the data-space to the parameter space. Finally, the method is applied to characterize the source parameters of the earthquakes occurring during the 2016-2017 Central Italy sequence, with the goal of investigating the source parameter scaling with magnitude.

A derivation of the Cramer-Rao lower bound of euclidean parameters under equality constraints via score function

NASA Astrophysics Data System (ADS)

Susyanto, Nanang

2017-12-01

We propose a simple derivation of the Cramer-Rao Lower Bound (CRLB) of parameters under equality constraints from the CRLB without constraints in regular parametric models. When a regular parametric model and an equality constraint of the parameter are given, a parametric submodel can be defined by restricting the parameter under that constraint. The tangent space of this submodel is then computed with the help of the implicit function theorem. Finally, the score function of the restricted parameter is obtained by projecting the efficient influence function of the unrestricted parameter on the appropriate inner product spaces.

Multiple Kernel Learning with Data Augmentation

DTIC Science & Technology

2016-11-22

model, we further show how to make inference and learn parameters in the following section. Note that we still need hyper -parameters (i.e., κ0, θ0, µ0...parameter α and sparsity tuning parameter β, these hyper -parameters are not sensitive to data. As in the BEMKL method, we fix the values of these... hyper -parameters for all datasets. αxn β yn wmf λmf µ0 σ0κ0 θ0 N M × F α ∼ G (κ0, θ0) β ∼ N ( µ0, σ 2 0 ) wmf , λmf | α, β ∼ Equation (8) yn | xn,wmf

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Seven-parameter statistical model for BRDF in the UV band.

PubMed

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

Estimation of parameters in rational reaction rates of molecular biological systems via weighted least squares

NASA Astrophysics Data System (ADS)

Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke

2010-01-01

The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.

Robust design of configurations and parameters of adaptable products

NASA Astrophysics Data System (ADS)

Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua

2014-03-01

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

Effects of expected-value information and display format on recognition of aircraft subsystem abnormalities

NASA Technical Reports Server (NTRS)

Palmer, Michael T.; Abbott, Kathy H.

1994-01-01

This study identifies improved methods to present system parameter information for detecting abnormal conditions and to identify system status. Two workstation experiments were conducted. The first experiment determined if including expected-value-range information in traditional parameter display formats affected subject performance. The second experiment determined if using a nontraditional parameter display format, which presented relative deviation from expected value, was better than traditional formats with expected-value ranges included. The inclusion of expected-value-range information onto traditional parameter formats was found to have essentially no effect. However, subjective results indicated support for including this information. The nontraditional column deviation parameter display format resulted in significantly fewer errors compared with traditional formats with expected-value-ranges included. In addition, error rates for the column deviation parameter display format remained stable as the scenario complexity increased, whereas error rates for the traditional parameter display formats with expected-value ranges increased. Subjective results also indicated that the subjects preferred this new format and thought that their performance was better with it. The column deviation parameter display format is recommended for display applications that require rapid recognition of out-of-tolerance conditions, especially for a large number of parameters.

Updating national standards for drinking-water: a Philippine experience.

PubMed

Lomboy, M; Riego de Dios, J; Magtibay, B; Quizon, R; Molina, V; Fadrilan-Camacho, V; See, J; Enoveso, A; Barbosa, L; Agravante, A

2017-04-01

The latest version of the Philippine National Standards for Drinking-Water (PNSDW) was issued in 2007 by the Department of Health (DOH). Due to several issues and concerns, the DOH decided to make an update which is relevant and necessary to meet the needs of the stakeholders. As an output, the water quality parameters are now categorized into mandatory, primary, and secondary. The ten mandatory parameters are core parameters which all water service providers nationwide are obligated to test. These include thermotolerant coliforms or Escherichia coli, arsenic, cadmium, lead, nitrate, color, turbidity, pH, total dissolved solids, and disinfectant residual. The 55 primary parameters are site-specific and can be adopted as enforceable parameters when developing new water sources or when the existing source is at high risk of contamination. The 11 secondary parameters include operational parameters and those that affect the esthetic quality of drinking-water. In addition, the updated PNSDW include new sections: (1) reporting and interpretation of results and corrective actions; (2) emergency drinking-water parameters; (3) proposed Sustainable Development Goal parameters; and (4) standards for other drinking-water sources. The lessons learned and insights gained from the updating of standards are likewise incorporated in this paper.

Oracle estimation of parametric models under boundary constraints.

PubMed

Wong, Kin Yau; Goldberg, Yair; Fine, Jason P

2016-12-01

In many classical estimation problems, the parameter space has a boundary. In most cases, the standard asymptotic properties of the estimator do not hold when some of the underlying true parameters lie on the boundary. However, without knowledge of the true parameter values, confidence intervals constructed assuming that the parameters lie in the interior are generally over-conservative. A penalized estimation method is proposed in this article to address this issue. An adaptive lasso procedure is employed to shrink the parameters to the boundary, yielding oracle inference which adapt to whether or not the true parameters are on the boundary. When the true parameters are on the boundary, the inference is equivalent to that which would be achieved with a priori knowledge of the boundary, while if the converse is true, the inference is equivalent to that which is obtained in the interior of the parameter space. The method is demonstrated under two practical scenarios, namely the frailty survival model and linear regression with order-restricted parameters. Simulation studies and real data analyses show that the method performs well with realistic sample sizes and exhibits certain advantages over standard methods. © 2016, The International Biometric Society.

The power and robustness of maximum LOD score statistics.

PubMed

Yoo, Y J; Mendell, N R

2008-07-01

The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.

Application of Cox model in coagulation function in patients with primary liver cancer.

PubMed

Guo, Xuan; Chen, Mingwei; Ding, Li; Zhao, Shan; Wang, Yuefei; Kang, Qinjiong; Liu, Yi

2011-01-01

To analyze the distribution of coagulation parameters in patients with primary liver cancer; explore the relationship between clinical staging, survival, and coagulation parameters by using Coxproportional hazard model; and provide a parameter for clinical management and prognosis. Coagulation parameters were evaluated in 228 patients with primary liver cancer, 52 patients with common liver disease, and 52 normal healthy controls. The relationship between primary livercancer staging and coagulation parameters wasanalyzed. Follow-up examinations were performed. The Cox proportional hazard model was used to analyze the relationship between coagulationparameters and survival. The changes in the coagulation parameters in patients with primary liver cancer were significantly different from those in normal controls. The effect of the disease on coagulation function became more obvious as the severity of liver cancer increased (p<0.05). The levels of D-dimer, fibrinogen degradation products (FDP), fibrinogen (FIB), and platelets (PLT) were negatively correlated with the long-term survival of patients with advanced liver cancer. The stages of primary liver cancer are associated with coagulation parameters. Coagulation parameters are related to survival and risk factors. Monitoring of coagulation parameters may help ensure better surveillance and treatment for liver cancer patients.

Kurtosis parameter K of arbitrary electromagnetic beams propagating through non-Kolmogorov turbulence

NASA Astrophysics Data System (ADS)

Xu, Yonggen; Dan, Youquan; Yu, Jiayi; Cai, Yangjian

2017-10-01

General analytical formulae for the kurtosis parameters K (K parameters) of the arbitrary electromagnetic (AE) beams propagating through non-Kolmogorov turbulence are derived, and according to the unified theory of polarization and coherence, the effect of degree of polarization (DOP) of an electromagnetic beam on the K parameter is studied. The analytical formulae can be given by the second-order moments and fourth-order moments of the Wigner distribution function for AE beams at source plane, the two turbulence quantities relating to the spatial power spectrum, and the propagation distance. Our results can also be extended to the arbitrary beams and the arbitrary spatial power spectra of Kolmogorov turbulence or non-Kolmogorov turbulence. Taking the stochastic electromagnetic Gaussian Schell-model (SEGSM) beam as an example, the numerical examples indicate that the K parameters of a SEGSM beam in non-Kolmogorov turbulence depend on propagation distance, the beam parameters and turbulence parameters. The K parameter of a SEGM beam is more sensitive to effect of turbulence with smaller inner scale and generalized exponent parameter. A non-polarized light has the strongest ability of resisting turbulence (ART), however, a fully polarized SEGSM beam has the poorest ART.

Peritoneal Fluid Transport rather than Peritoneal Solute Transport Associates with Dialysis Vintage and Age of Peritoneal Dialysis Patients.

PubMed

Waniewski, Jacek; Antosiewicz, Stefan; Baczynski, Daniel; Poleszczuk, Jan; Pietribiasi, Mauro; Lindholm, Bengt; Wankowicz, Zofia

2016-01-01

During peritoneal dialysis (PD), the peritoneal membrane undergoes ageing processes that affect its function. Here we analyzed associations of patient age and dialysis vintage with parameters of peritoneal transport of fluid and solutes, directly measured and estimated based on the pore model, for individual patients. Thirty-three patients (15 females; age 60 (21-87) years; median time on PD 19 (3-100) months) underwent sequential peritoneal equilibration test. Dialysis vintage and patient age did not correlate. Estimation of parameters of the two-pore model of peritoneal transport was performed. The estimated fluid transport parameters, including hydraulic permeability (LpS), fraction of ultrasmall pores (α u), osmotic conductance for glucose (OCG), and peritoneal absorption, were generally independent of solute transport parameters (diffusive mass transport parameters). Fluid transport parameters correlated whereas transport parameters for small solutes and proteins did not correlate with dialysis vintage and patient age. Although LpS and OCG were lower for older patients and those with long dialysis vintage, αu was higher. Thus, fluid transport parameters--rather than solute transport parameters--are linked to dialysis vintage and patient age and should therefore be included when monitoring processes linked to ageing of the peritoneal membrane.

Interactive model evaluation tool based on IPython notebook

NASA Astrophysics Data System (ADS)

Balemans, Sophie; Van Hoey, Stijn; Nopens, Ingmar; Seuntjes, Piet

2015-04-01

In hydrological modelling, some kind of parameter optimization is mostly performed. This can be the selection of a single best parameter set, a split in behavioural and non-behavioural parameter sets based on a selected threshold or a posterior parameter distribution derived with a formal Bayesian approach. The selection of the criterion to measure the goodness of fit (likelihood or any objective function) is an essential step in all of these methodologies and will affect the final selected parameter subset. Moreover, the discriminative power of the objective function is also dependent from the time period used. In practice, the optimization process is an iterative procedure. As such, in the course of the modelling process, an increasing amount of simulations is performed. However, the information carried by these simulation outputs is not always fully exploited. In this respect, we developed and present an interactive environment that enables the user to intuitively evaluate the model performance. The aim is to explore the parameter space graphically and to visualize the impact of the selected objective function on model behaviour. First, a set of model simulation results is loaded along with the corresponding parameter sets and a data set of the same variable as the model outcome (mostly discharge). The ranges of the loaded parameter sets define the parameter space. A selection of the two parameters visualised can be made by the user. Furthermore, an objective function and a time period of interest need to be selected. Based on this information, a two-dimensional parameter response surface is created, which actually just shows a scatter plot of the parameter combinations and assigns a color scale corresponding with the goodness of fit of each parameter combination. Finally, a slider is available to change the color mapping of the points. Actually, the slider provides a threshold to exclude non behaviour parameter sets and the color scale is only attributed to the remaining parameter sets. As such, by interactively changing the settings and interpreting the graph, the user gains insight in the model structural behaviour. Moreover, a more deliberate choice of objective function and periods of high information content can be identified. The environment is written in an IPython notebook and uses the available interactive functions provided by the IPython community. As such, the power of the IPython notebook as a development environment for scientific computing is illustrated (Shen, 2014).

Recovering Parameters of Johnson's SB Distribution

Treesearch

Bernard R. Parresol

2003-01-01

A new parameter recovery model for Johnson's SB distribution is developed. This latest alternative approach permits recovery of the range and both shape parameters. Previous models recovered only the two shape parameters. Also, a simple procedure for estimating the distribution minimum from sample values is presented. The new methodology...

Theoretical Calculations of XeF Ground State Kinetics.

DTIC Science & Technology

1988-03-01

potential parameters for XeF are taken from Tellinghuisen et al. 3 The values of the Lennard - Jones parameters for HeF...parameters for the Morse potential and the Lennard - Jones potentials are listed in Table 1. These parameters for the Lennard - Jones potentials produce the...relaxation and dissociation. 13 ~ o Table 1. Potential Parameters. Morse Function (XeF)3 De = 3.35 kcal/mol ae=1.726 a.u.-1 re =4.367 a.u. Lennard Jones

An improved method for nonlinear parameter estimation: a case study of the Rössler model

NASA Astrophysics Data System (ADS)

He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan

2016-08-01

Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.

Estimation of soil saturated hydraulic conductivity by artificial neural networks ensemble in smectitic soils

NASA Astrophysics Data System (ADS)

Sedaghat, A.; Bayat, H.; Safari Sinegani, A. A.

2016-03-01

The saturated hydraulic conductivity ( K s ) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K s by using available soil data and fractal parameters. There were found significant correlations between K s and fractal parameters of particles and microaggregates. Estimation of K s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K s . Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K s .

Approximate Bayesian computation in large-scale structure: constraining the galaxy-halo connection

NASA Astrophysics Data System (ADS)

Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Campbell, Duncan

2017-08-01

Standard approaches to Bayesian parameter inference in large-scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as approximate Bayesian computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter haloes with galaxies. Using specific implementation of ABC supplemented with population Monte Carlo importance sampling, a generative forward model using HOD and a distance metric based on galaxy number density, two-point correlation function and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected 'true' HOD parameters. The parameter constraints we obtain from ABC are consistent with the 'true' HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately, our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

The Effect of Roughness Model on Scattering Properties of Ice Crystals.

NASA Technical Reports Server (NTRS)

Geogdzhayev, Igor V.; Van Diedenhoven, Bastiaan

2016-01-01

We compare stochastic models of microscale surface roughness assuming uniform and Weibull distributions of crystal facet tilt angles to calculate scattering by roughened hexagonal ice crystals using the geometric optics (GO) approximation. Both distributions are determined by similar roughness parameters, while the Weibull model depends on the additional shape parameter. Calculations were performed for two visible wavelengths (864 nm and 410 nm) for roughness values between 0.2 and 0.7 and Weibull shape parameters between 0 and 1.0 for crystals with aspect ratios of 0.21, 1 and 4.8. For this range of parameters we find that, for a given roughness level, varying the Weibull shape parameter can change the asymmetry parameter by up to about 0.05. The largest effect of the shape parameter variation on the phase function is found in the backscattering region, while the degree of linear polarization is most affected at the side-scattering angles. For high roughness, scattering properties calculated using the uniform and Weibull models are in relatively close agreement for a given roughness parameter, especially when a Weibull shape parameter of 0.75 is used. For smaller roughness values, a shape parameter close to unity provides a better agreement. Notable differences are observed in the phase function over the scattering angle range from 5deg to 20deg, where the uniform roughness model produces a plateau while the Weibull model does not.

On the Interplay between Order Parameter Dynamics and System Parameter Dynamics in Human Perceptual-Cognitive-Behavioral Systems.

PubMed

Frank, T D

2015-04-01

Previous research has demonstrated that perceiving, thinking, and acting are human activities that correspond to self-organized patterns. The emergence of such patterns can be completely described in terms of the dynamics of the pattern amplitudes, which are referred to as order parameters. The patterns emerge at bifurcations points when certain system parameters internal and external to a human agent exceed critical values. At issue is how one might study the order parameter dynamics for sequences of consecutive, emergent perceptual, cognitive, or behavioral activities. In particular, these activities may in turn impact the system parameters that have led to the emergence of the activities in the first place. This interplay between order parameter dynamics and system parameter dynamics is discussed in general and formulated in mathematical terms. Previous work that has made use of this two-tiered framework of order parameter and system parameter dynamics are briefly addressed. As an application, a model for perception under functional fixedness is presented. Finally, it is argued that the phenomena that emerge in this framework and can be observed when human agents perceive, think, and act are just as likely to occur in pattern formation systems of the inanimate world. Consequently, these phenomena do not necessarily have a neurophysiological basis but should instead be understood from the perspective of the theory of self-organization.

Quantifying model-structure- and parameter-driven uncertainties in spring wheat phenology prediction with Bayesian analysis

DOE PAGES

Alderman, Phillip D.; Stanfill, Bryan

2016-10-06

Recent international efforts have brought renewed emphasis on the comparison of different agricultural systems models. Thus far, analysis of model-ensemble simulated results has not clearly differentiated between ensemble prediction uncertainties due to model structural differences per se and those due to parameter value uncertainties. Additionally, despite increasing use of Bayesian parameter estimation approaches with field-scale crop models, inadequate attention has been given to the full posterior distributions for estimated parameters. The objectives of this study were to quantify the impact of parameter value uncertainty on prediction uncertainty for modeling spring wheat phenology using Bayesian analysis and to assess the relativemore » contributions of model-structure-driven and parameter-value-driven uncertainty to overall prediction uncertainty. This study used a random walk Metropolis algorithm to estimate parameters for 30 spring wheat genotypes using nine phenology models based on multi-location trial data for days to heading and days to maturity. Across all cases, parameter-driven uncertainty accounted for between 19 and 52% of predictive uncertainty, while model-structure-driven uncertainty accounted for between 12 and 64%. Here, this study demonstrated the importance of quantifying both model-structure- and parameter-value-driven uncertainty when assessing overall prediction uncertainty in modeling spring wheat phenology. More generally, Bayesian parameter estimation provided a useful framework for quantifying and analyzing sources of prediction uncertainty.« less

Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

PubMed

Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

2018-07-01

Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

NASA Astrophysics Data System (ADS)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

Probabilistic evaluation of damage potential in earthquake-induced liquefaction in a 3-D soil deposit

NASA Astrophysics Data System (ADS)

Halder, A.; Miller, F. J.

1982-03-01

A probabilistic model to evaluate the risk of liquefaction at a site and to limit or eliminate damage during earthquake induced liquefaction is proposed. The model is extended to consider three dimensional nonhomogeneous soil properties. The parameters relevant to the liquefaction phenomenon are identified, including: (1) soil parameters; (2) parameters required to consider laboratory test and sampling effects; and (3) loading parameters. The fundamentals of risk based design concepts pertient to liquefaction are reviewed. A detailed statistical evaluation of the soil parameters in the proposed liquefaction model is provided and the uncertainty associated with the estimation of in situ relative density is evaluated for both direct and indirect methods. It is found that the liquefaction potential the uncertainties in the load parameters could be higher than those in the resistance parameters.

Influence of additive laser manufacturing parameters on surface using density of partially melted particles

NASA Astrophysics Data System (ADS)

Rosa, Benoit; Brient, Antoine; Samper, Serge; Hascoët, Jean-Yves

2016-12-01

Mastering the additive laser manufacturing surface is a real challenge and would allow functional surfaces to be obtained without finishing. Direct Metal Deposition (DMD) surfaces are composed by directional and chaotic textures that are directly linked to the process principles. The aim of this work is to obtain surface topographies by mastering the operating process parameters. Based on experimental investigation, the influence of operating parameters on the surface finish has been modeled. Topography parameters and multi-scale analysis have been used in order to characterize the DMD obtained surfaces. This study also proposes a methodology to characterize DMD chaotic texture through topography filtering and 3D image treatment. In parallel, a new parameter is proposed: density of particles (D p). Finally, this study proposes a regression modeling between process parameters and density of particles parameter.

Distributed traffic signal control using fuzzy logic

NASA Technical Reports Server (NTRS)

Chiu, Stephen

1992-01-01

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

A Model Parameter Extraction Method for Dielectric Barrier Discharge Ozone Chamber using Differential Evolution

NASA Astrophysics Data System (ADS)

Amjad, M.; Salam, Z.; Ishaque, K.

2014-04-01

In order to design an efficient resonant power supply for ozone gas generator, it is necessary to accurately determine the parameters of the ozone chamber. In the conventional method, the information from Lissajous plot is used to estimate the values of these parameters. However, the experimental setup for this purpose can only predict the parameters at one operating frequency and there is no guarantee that it results in the highest ozone gas yield. This paper proposes a new approach to determine the parameters using a search and optimization technique known as Differential Evolution (DE). The desired objective function of DE is set at the resonance condition and the chamber parameter values can be searched regardless of experimental constraints. The chamber parameters obtained from the DE technique are validated by experiment.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

Significant consequences of heat generation/absorption and homogeneous-heterogeneous reactions in second grade fluid due to rotating disk

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Qayyum, Sumaira; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

Flow of second grade fluid by a rotating disk with heat and mass transfer is discussed. Additional effects of heat generation/absorption are also analyzed. Flow is also subjected to homogeneous-heterogeneous reactions. The convergence of computed solution is assured through appropriate choices of initial guesses and auxiliary parameters. Investigation is made for the effects of involved parameters on velocities (radial, axial, tangential), temperature and concentration. Skin friction and Nusselt number are also analyzed. Graphical results depict that an increase in viscoelastic parameter enhances the axial, radial and tangential velocities. Opposite behavior of temperature is observed for larger values of viscoelastic and heat generation/absorption parameters. Concentration profile is increasing function of Schmidt number, viscoelastic parameter and heterogeneous reaction parameter. Magnitude of skin friction and Nusselt number are enhanced for larger viscoelastic parameter.

Optimization Under Uncertainty for Electronics Cooling Design

NASA Astrophysics Data System (ADS)

Bodla, Karthik K.; Murthy, Jayathi Y.; Garimella, Suresh V.

Optimization under uncertainty is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, produces output uncertainties, helping the designer choose input parameters that would result in satisfactory thermal solutions. Apart from providing basic statistical information such as mean and standard deviation in the output quantities, auxiliary data from an uncertainty based optimization, such as local and global sensitivities, help the designer decide the input parameter(s) to which the output quantity of interest is most sensitive. This helps the design of experiments based on the most sensitive input parameter(s). A further crucial output of such a methodology is the solution to the inverse problem - finding the allowable uncertainty range in the input parameter(s), given an acceptable uncertainty range in the output quantity of interest...

Modeling parameters that characterize pacing of elite female 800-m freestyle swimmers.

PubMed

Lipińska, Patrycja; Allen, Sian V; Hopkins, Will G

2016-01-01

Pacing offers a potential avenue for enhancement of endurance performance. We report here a novel method for characterizing pacing in 800-m freestyle swimming. Websites provided 50-m lap and race times for 192 swims of 20 elite female swimmers between 2000 and 2013. Pacing for each swim was characterized with five parameters derived from a linear model: linear and quadratic coefficients for effect of lap number, reductions from predicted time for first and last laps, and lap-time variability (standard error of the estimate). Race-to-race consistency of the parameters was expressed as intraclass correlation coefficients (ICCs). The average swim was a shallow negative quadratic with slowest time in the eleventh lap. First and last laps were faster by 6.4% and 3.6%, and lap-time variability was ±0.64%. Consistency between swimmers ranged from low-moderate for the linear and quadratic parameters (ICC = 0.29 and 0.36) to high for the last-lap parameter (ICC = 0.62), while consistency for race time was very high (ICC = 0.80). Only ~15% of swimmers had enough swims (~15 or more) to provide reasonable evidence of optimum parameter values in plots of race time vs. each parameter. The modest consistency of most of the pacing parameters and lack of relationships between parameters and performance suggest that swimmers usually compensated for changes in one parameter with changes in another. In conclusion, pacing in 800-m elite female swimmers can be characterized with five parameters, but identifying an optimal pacing profile is generally impractical.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.

A New Goodness-of-Fit Test for the Weibull Distribution Based on Spacings

DTIC Science & Technology

1993-03-01

Values for Z* test statistic: Samplesize N, shape parameter 1.0, a levels are 0.20 thru 0.01 ........................... .. 24 3. Skewness of the...parameter K=0.5, a levels are 0.20 thru 0.01 ....... ............................ 30 5. Power of the Test: Samplesize N=20, shape parameter K=1.0, a ...parameter 1.0, alpha level 0.01 ...... ... 36 12. Power of the Test: Samplesize N=30, shape parameter K=1.5, a levels are 0.20 thru 0.01

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

Isa, Sharena Mohamad; Ali, Anati

In this paper, the hydromagnetic flow of dusty fluid over a vertical stretching sheet with thermal radiation is investigated. The governing partial differential equations are reduced to nonlinear ordinary differential equations using similarity transformation. These nonlinear ordinary differential equations are solved numerically using Runge-Kutta Fehlberg fourth-fifth order method (RKF45 Method). The behavior of velocity and temperature profiles of hydromagnetic fluid flow of dusty fluid is analyzed and discussed for different parameters of interest such as unsteady parameter, fluid-particle interaction parameter, the magnetic parameter, radiation parameter and Prandtl number on the flow.

Analyzing parameters optimisation in minimising warpage on side arm using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

This paper presents a systematic methodology to analyse the warpage of the side arm part using Autodesk Moldflow Insight software. Response Surface Methodology (RSM) was proposed to optimise the processing parameters that will result in optimal solutions by efficiently minimising the warpage of the side arm part. The variable parameters considered in this study was based on most significant parameters affecting warpage stated by previous researchers, that is melt temperature, mould temperature and packing pressure while adding packing time and cooling time as these is the commonly used parameters by researchers. The results show that warpage was improved by 10.15% and the most significant parameters affecting warpage are packing pressure.

Effects of clouds on the Earth radiation budget; Seasonal and inter-annual patterns

NASA Technical Reports Server (NTRS)

Dhuria, Harbans L.

1992-01-01

Seasonal and regional variations of clouds and their effects on the climatological parameters were studied. The climatological parameters surface temperature, solar insulation, short-wave absorbed, long wave emitted, and net radiation were considered. The data of climatological parameters consisted of about 20 parameters of Earth radiation budget and clouds of 2070 target areas which covered the globe. It consisted of daily and monthly averages of each parameter for each target area for the period, Jun. 1979 - May 1980. Cloud forcing and black body temperature at the top of the atmosphere were calculated. Interactions of clouds, cloud forcing, black body temperature, and the climatological parameters were investigated and analyzed.

How to Select the most Relevant Roughness Parameters of a Surface: Methodology Research Strategy

NASA Astrophysics Data System (ADS)

Bobrovskij, I. N.

2018-01-01

In this paper, the foundations for new methodology creation which provides solving problem of surfaces structure new standards parameters huge amount conflicted with necessary actual floors quantity of surfaces structure parameters which is related to measurement complexity decreasing are considered. At the moment, there is no single assessment of the importance of a parameters. The approval of presented methodology for aerospace cluster components surfaces allows to create necessary foundation, to develop scientific estimation of surfaces texture parameters, to obtain material for investigators of chosen technological procedure. The methods necessary for further work, the creation of a fundamental reserve and development as a scientific direction for assessing the significance of microgeometry parameters are selected.

Research on filter’s parameter selection based on PROMETHEE method

NASA Astrophysics Data System (ADS)

Zhu, Hui-min; Wang, Hang-yu; Sun, Shi-yan

2018-03-01

The selection of filter’s parameters in target recognition was studied in this paper. The PROMETHEE method was applied to the optimization problem of Gabor filter parameters decision, the correspondence model of the elemental relation between two methods was established. The author took the identification of military target as an example, problem about the filter’s parameter decision was simulated and calculated by PROMETHEE. The result showed that using PROMETHEE method for the selection of filter’s parameters was more scientific. The human disturbance caused by the experts method and empirical method could be avoided by this way. The method can provide reference for the parameter configuration scheme decision of the filter.

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

Visual Image Sensor Organ Replacement: Implementation

NASA Technical Reports Server (NTRS)

Maluf, A. David (Inventor)

2011-01-01

Method and system for enhancing or extending visual representation of a selected region of a visual image, where visual representation is interfered with or distorted, by supplementing a visual signal with at least one audio signal having one or more audio signal parameters that represent one or more visual image parameters, such as vertical and/or horizontal location of the region; region brightness; dominant wavelength range of the region; change in a parameter value that characterizes the visual image, with respect to a reference parameter value; and time rate of change in a parameter value that characterizes the visual image. Region dimensions can be changed to emphasize change with time of a visual image parameter.

Spatial trends in Pearson Type III statistical parameters

USGS Publications Warehouse

Lichty, R.W.; Karlinger, M.R.

1995-01-01

Spatial trends in the statistical parameters (mean, standard deviation, and skewness coefficient) of a Pearson Type III distribution of the logarithms of annual flood peaks for small rural basins (less than 90 km2) are delineated using a climate factor CT, (T=2-, 25-, and 100-yr recurrence intervals), which quantifies the effects of long-term climatic data (rainfall and pan evaporation) on observed T-yr floods. Maps showing trends in average parameter values demonstrate the geographically varying influence of climate on the magnitude of Pearson Type III statistical parameters. The spatial trends in variability of the parameter values characterize the sensitivity of statistical parameters to the interaction of basin-runoff characteristics (hydrology) and climate. -from Authors

System and method for regulating resonant inverters

DOEpatents

Stevanovic, Ljubisa Dragoljub [Clifton Park, NY; Zane, Regan Andrew [Superior, CO

2007-08-28

A technique is provided for direct digital phase control of resonant inverters based on sensing of one or more parameters of the resonant inverter. The resonant inverter control system includes a switching circuit for applying power signals to the resonant inverter and a sensor for sensing one or more parameters of the resonant inverter. The one or more parameters are representative of a phase angle. The resonant inverter control system also includes a comparator for comparing the one or more parameters to a reference value and a digital controller for determining timing of the one or more parameters and for regulating operation of the switching circuit based upon the timing of the one or more parameters.

Numerical study of unsteady Williamson fluid flow and heat transfer in the presence of MHD through a permeable stretching surface

NASA Astrophysics Data System (ADS)

Bibi, Madiha; Khalil-Ur-Rehman; Malik, M. Y.; Tahir, M.

2018-04-01

In the present article, unsteady flow field characteristics of the Williamson fluid model are explored. The nanosized particles are suspended in the flow regime having the interaction of a magnetic field. The fluid flow is induced due to a stretching permeable surface. The flow model is controlled through coupled partial differential equations to the used shooting method for a numerical solution. The obtained partial differential equations are converted into ordinary differential equations as an initial value problem. The shooting method is used to find a numerical solution. The mathematical modeling yields physical parameters, namely the Weissenberg number, the Prandtl number, the unsteadiness parameter, the magnetic parameter, the mass transfer parameter, the Lewis number, the thermophoresis parameter and Brownian parameters. It is found that the Williamson fluid velocity, temperature and nanoparticles concentration are a decreasing function of the unsteadiness parameter.

Calculating the mounting parameters for Taylor Spatial Frame correction using computed tomography.

PubMed

Kucukkaya, Metin; Karakoyun, Ozgur; Armagan, Raffi; Kuzgun, Unal

2011-07-01

The Taylor Spatial Frame uses a computer program-based six-axis deformity analysis. However, there is often a residual deformity after the initial correction, especially in deformities with a rotational component. This problem can be resolved by recalculating the parameters and inputting all new deformity and mounting parameters. However, this may necessitate repeated x-rays and delay treatment. We believe that error in the mounting parameters is the main reason for most residual deformities. To prevent these problems, we describe a new calculation technique for determining the mounting parameters that uses computed tomography. This technique is especially advantageous for deformities with a rotational component. Using this technique, exact calculation of the mounting parameters is possible and the residual deformity and number of repeated x-rays can be minimized. This new technique is an alternative method to accurately calculating the mounting parameters.

EPR, optical and modeling of Mn(2+) doped sarcosinium oxalate monohydrate.

PubMed

Kripal, Ram; Singh, Manju

2015-01-25

Electron paramagnetic resonance (EPR) study of Mn(2+) ions doped in sarcosinium oxalate monohydrate (SOM) single crystal is done at liquid nitrogen temperature (LNT). EPR spectrum shows a bunch of five fine structure lines and further they split into six hyperfine components. Only one interstitial site was observed. With the help of EPR spectra the spin Hamiltonian parameters including zero field splitting (ZFS) parameters are evaluated. The optical absorption study at room temperature is also done in the wavelength range 195-1100 nm. From this study cubic crystal field splitting parameter, Dq=730 cm(-1) and Racah inter-electronic repulsion parameters B=792 cm(-1), C=2278 cm(-1) are determined. ZFS parameters D and E are also calculated using crystal field parameters from superposition model and microscopic spin Hamiltonian theory. The calculated ZFS parameter values are in good match with the experimental values obtained by EPR. Copyright © 2014 Elsevier B.V. All rights reserved.

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

Parameter recovery, bias and standard errors in the linear ballistic accumulator model.

PubMed

Visser, Ingmar; Poessé, Rens

2017-05-01

The linear ballistic accumulator (LBA) model (Brown & Heathcote, , Cogn. Psychol., 57, 153) is increasingly popular in modelling response times from experimental data. An R package, glba, has been developed to fit the LBA model using maximum likelihood estimation which is validated by means of a parameter recovery study. At sufficient sample sizes parameter recovery is good, whereas at smaller sample sizes there can be large bias in parameters. In a second simulation study, two methods for computing parameter standard errors are compared. The Hessian-based method is found to be adequate and is (much) faster than the alternative bootstrap method. The use of parameter standard errors in model selection and inference is illustrated in an example using data from an implicit learning experiment (Visser et al., , Mem. Cogn., 35, 1502). It is shown that typical implicit learning effects are captured by different parameters of the LBA model. © 2017 The British Psychological Society.

Analysis of convergence of an evolutionary algorithm with self-adaptation using a stochastic Lyapunov function.

PubMed

Semenov, Mikhail A; Terkel, Dmitri A

2003-01-01

This paper analyses the convergence of evolutionary algorithms using a technique which is based on a stochastic Lyapunov function and developed within the martingale theory. This technique is used to investigate the convergence of a simple evolutionary algorithm with self-adaptation, which contains two types of parameters: fitness parameters, belonging to the domain of the objective function; and control parameters, responsible for the variation of fitness parameters. Although both parameters mutate randomly and independently, they converge to the "optimum" due to the direct (for fitness parameters) and indirect (for control parameters) selection. We show that the convergence velocity of the evolutionary algorithm with self-adaptation is asymptotically exponential, similar to the velocity of the optimal deterministic algorithm on the class of unimodal functions. Although some martingale inequalities have not be proved analytically, they have been numerically validated with 0.999 confidence using Monte-Carlo simulations.

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

Selection of noisy measurement locations for error reduction in static parameter identification

NASA Astrophysics Data System (ADS)

Sanayei, Masoud; Onipede, Oladipo; Babu, Suresh R.

1992-09-01

An incomplete set of noisy static force and displacement measurements is used for parameter identification of structures at the element level. Measurement location and the level of accuracy in the measured data can drastically affect the accuracy of the identified parameters. A heuristic method is presented to select a limited number of degrees of freedom (DOF) to perform a successful parameter identification and to reduce the impact of measurement errors on the identified parameters. This pretest simulation uses an error sensitivity analysis to determine the effect of measurement errors on the parameter estimates. The selected DOF can be used for nondestructive testing and health monitoring of structures. Two numerical examples, one for a truss and one for a frame, are presented to demonstrate that using the measurements at the selected subset of DOF can limit the error in the parameter estimates.

A Three-Parameter Model for Predicting Fatigue Life of Ductile Metals Under Constant Amplitude Multiaxial Loading

NASA Astrophysics Data System (ADS)

Liu, Jia; Li, Jing; Zhang, Zhong-ping

2013-04-01

In this article, a fatigue damage parameter is proposed to assess the multiaxial fatigue lives of ductile metals based on the critical plane concept: Fatigue crack initiation is controlled by the maximum shear strain, and the other important effect in the fatigue damage process is the normal strain and stress. This fatigue damage parameter introduces a stress-correlated factor, which describes the degree of the non-proportional cyclic hardening. Besides, a three-parameter multiaxial fatigue criterion is used to correlate the fatigue lifetime of metallic materials with the proposed damage parameter. Under the uniaxial loading, this three-parameter model reduces to the recently developed Zhang's model for predicting the uniaxial fatigue crack initiation life. The accuracy and reliability of this three-parameter model are checked against the experimental data found in literature through testing six different ductile metals under various strain paths with zero/non-zero mean stress.

White LED compared with other light sources: age-dependent photobiological effects and parameters for evaluation.

PubMed

Rebec, Katja Malovrh; Klanjšek-Gunde, Marta; Bizjak, Grega; Kobav, Matej B

2015-01-01

Ergonomic science at work and living places should appraise human factors concerning the photobiological effects of lighting. Thorough knowledge on this subject has been gained in the past; however, few attempts have been made to propose suitable evaluation parameters. The blue light hazard and its influence on melatonin secretion in age-dependent observers is considered in this paper and parameters for its evaluation are proposed. New parameters were applied to analyse the effects of white light-emitting diode (LED) light sources and to compare them with the currently applied light sources. The photobiological effects of light sources with the same illuminance but different spectral power distribution were determined for healthy 4-76-year-old observers. The suitability of new parameters is discussed. Correlated colour temperature, the only parameter currently used to assess photobiological effects, is evaluated and compared to new parameters.

Shadow casted by a Konoplya-Zhidenko rotating non-Kerr black hole

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

Wang, Mingzhi; Chen, Songbai; Jing, Jiliang, E-mail: wmz9085@126.com, E-mail: csb3752@hunnu.edu.cn, E-mail: jljing@hunnu.edu.cn

We have investigated the shadow of a Konoplya-Zhidenko rotating non-Kerr black hole with an extra deformation parameter. The spacetime structure arising from the deformed parameter affects sharply the black hole shadow. With the increase of the deformation parameter, the size of the shadow of black hole increase and its shape becomes more rounded for arbitrary rotation parameter. The D-shape shadow of black hole emerges only in the case a <2√3/3\\, M with the proper deformation parameter. Especially, the black hole shadow possesses a cusp shape with small eye lashes in the cases with a >M, and the shadow becomes lessmore » cuspidal with the increase of the deformation parameter. Our result show that the presence of the deformation parameter yields a series of significant patterns for the shadow casted by a Konoplya-Zhidenko rotating non-Kerr black hole.« less

Determination of the Parameter Sets for the Best Performance of IPS-driven ENLIL Model

NASA Astrophysics Data System (ADS)

Yun, Jongyeon; Choi, Kyu-Cheol; Yi, Jonghyuk; Kim, Jaehun; Odstrcil, Dusan

2016-12-01

Interplanetary scintillation-driven (IPS-driven) ENLIL model was jointly developed by University of California, San Diego (UCSD) and National Aeronaucics and Space Administration/Goddard Space Flight Center (NASA/GSFC). The model has been in operation by Korean Space Weather Cetner (KSWC) since 2014. IPS-driven ENLIL model has a variety of ambient solar wind parameters and the results of the model depend on the combination of these parameters. We have conducted researches to determine the best combination of parameters to improve the performance of the IPS-driven ENLIL model. The model results with input of 1,440 combinations of parameters are compared with the Advanced Composition Explorer (ACE) observation data. In this way, the top 10 parameter sets showing best performance were determined. Finally, the characteristics of the parameter sets were analyzed and application of the results to IPS-driven ENLIL model was discussed.

Perceptual Calibration for Immersive Display Environments

PubMed Central

Ponto, Kevin; Gleicher, Michael; Radwin, Robert G.; Shin, Hyun Joon

2013-01-01

The perception of objects, depth, and distance has been repeatedly shown to be divergent between virtual and physical environments. We hypothesize that many of these discrepancies stem from incorrect geometric viewing parameters, specifically that physical measurements of eye position are insufficiently precise to provide proper viewing parameters. In this paper, we introduce a perceptual calibration procedure derived from geometric models. While most research has used geometric models to predict perceptual errors, we instead use these models inversely to determine perceptually correct viewing parameters. We study the advantages of these new psychophysically determined viewing parameters compared to the commonly used measured viewing parameters in an experiment with 20 subjects. The perceptually calibrated viewing parameters for the subjects generally produced new virtual eye positions that were wider and deeper than standard practices would estimate. Our study shows that perceptually calibrated viewing parameters can significantly improve depth acuity, distance estimation, and the perception of shape. PMID:23428454

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

Extremes in ecology: Avoiding the misleading effects of sampling variation in summary analyses

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1996-01-01

Surveys such as the North American Breeding Bird Survey (BBS) produce large collections of parameter estimates. One's natural inclination when confronted with lists of parameter estimates is to look for the extreme values: in the BBS, these correspond to the species that appear to have the greatest changes in population size through time. Unfortunately, extreme estimates are liable to correspond to the most poorly estimated parameters. Consequently, the most extreme parameters may not match up with the most extreme parameter estimates. The ranking of parameter values on the basis of their estimates are a difficult statistical problem. We use data from the BBS and simulations to illustrate the potential misleading effects of sampling variation in rankings of parameters. We describe empirical Bayes and constrained empirical Bayes procedures which provide partial solutions to the problem of ranking in the presence of sampling variation.

Measurement of agricultural parameters using wireless sensor network (WSN)

NASA Astrophysics Data System (ADS)

Guaña-Moya, Javier; Sánchez-Almeida, Tarquino; Salgado-Reyes, Nelson

2018-04-01

The technological advances have allowed to create new applications in telecommunications, applying low power and reduced costs in their equipment, thus achieving the evolution of new wireless networks or also denominated Wireless Sensor Network. These technologies allow the generation of measurements and analysis of environmental parameter data and soil. Precision agriculture requires parameters for the improvement of production, obtained through WSN technologies. This research analyzes the climatic requirements and soil parameters in a rose plantation in a greenhouse at an altitude of 3,100 meters above sea level. In the present investigation, maximum parameters were obtained in the production of roses, which are in the optimum range of production, whereas the minimum parameters of temperature, humidity and luminosity, evidenced that these parameters can damage the plants, since temperatures less than 10 °C slow down the growth of the plant and allow the proliferation of diseases and fungi.

A Stepwise Test Characteristic Curve Method to Detect Item Parameter Drift

ERIC Educational Resources Information Center

Guo, Rui; Zheng, Yi; Chang, Hua-Hua

2015-01-01

An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the…

Sensitivity analysis of the add-on price estimate for the edge-defined film-fed growth process

NASA Technical Reports Server (NTRS)

Mokashi, A. R.; Kachare, A. H.

1981-01-01

The analysis is in terms of cost parameters and production parameters. The cost parameters include equipment, space, direct labor, materials, and utilities. The production parameters include growth rate, process yield, and duty cycle. A computer program was developed specifically to do the sensitivity analysis.

An Evaluation of Three Approximate Item Response Theory Models for Equating Test Scores.

ERIC Educational Resources Information Center

Marco, Gary L.; And Others

Three item response models were evaluated for estimating item parameters and equating test scores. The models, which approximated the traditional three-parameter model, included: (1) the Rasch one-parameter model, operationalized in the BICAL computer program; (2) an approximate three-parameter logistic model based on coarse group data divided…

Bibliography for aircraft parameter estimation

NASA Technical Reports Server (NTRS)

Iliff, Kenneth W.; Maine, Richard E.

1986-01-01

An extensive bibliography in the field of aircraft parameter estimation has been compiled. This list contains definitive works related to most aircraft parameter estimation approaches. Theoretical studies as well as practical applications are included. Many of these publications are pertinent to subjects peripherally related to parameter estimation, such as aircraft maneuver design or instrumentation considerations.

Genome-wide association study of swine farrowing traits. Part I: Genetic and genomic parameter estimates

USDA-ARS?s Scientific Manuscript database

The primary objective of this study was to determine genetic and genomic parameters among swine farrowing traits. Genetic parameters were obtained by using MTDFREML and genomic parameters were obtained using GenSel. Genetic and residual variances obtained from MTDFREML were used as priors for the ...

The Hildebrand solubility parameters of ionic liquids-part 2.

PubMed

Marciniak, Andrzej

2011-01-01

The Hildebrand solubility parameters have been calculated for eight ionic liquids. Retention data from the inverse gas chromatography measurements of the activity coefficients at infinite dilution were used for the calculation. From the solubility parameters, the enthalpies of vaporization of ionic liquids were estimated. Results are compared with solubility parameters estimated by different methods.

Scalable Online Network Modeling and Simulation

DTIC Science & Technology

2005-08-01

ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski , Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...performance for a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature ...a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature interactions

Gender may have an influence on the relationship between Functional Movement Screen scores and gait parameters in elite junior athletes - A pilot study.

PubMed

Magyari, N; Szakács, V; Bartha, C; Szilágyi, B; Galamb, K; Magyar, M O; Hortobágyi, T; Kiss, R M; Tihanyi, J; Négyesi, J

2017-09-01

Aims The aim of this study was to examine the effects of gender on the relationship between Functional Movement Screen (FMS) and treadmill-based gait parameters. Methods Twenty elite junior athletes (10 women and 10 men) performed the FMS tests and gait analysis at a fixed speed. Between-gender differences were calculated for the relationship between FMS test scores and gait parameters, such as foot rotation, step length, and length of gait line. Results Gender did not affect the relationship between FMS and treadmill-based gait parameters. The nature of correlations between FMS test scores and gait parameters was different in women and men. Furthermore, different FMS test scores predicted different gait parameters in female and male athletes. FMS asymmetry and movement asymmetries measured by treadmill-based gait parameters did not correlate in either gender. Conclusion There were no interactions between FMS, gait parameters, and gender; however, correlation analyses support the idea that strength and conditioning coaches need to pay attention not only to how to score but also how to correctly use FMS.

A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

NASA Astrophysics Data System (ADS)

Bhattacharjya, Rajib Kumar

2018-05-01

The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

Observational constraints on Hubble parameter in viscous generalized Chaplygin gas

NASA Astrophysics Data System (ADS)

Thakur, P.

2018-04-01

Cosmological model with viscous generalized Chaplygin gas (in short, VGCG) is considered here to determine observational constraints on its equation of state parameters (in short, EoS) from background data. These data consists of H(z)-z (OHD) data, Baryonic Acoustic Oscillations peak parameter, CMB shift parameter and SN Ia data (Union 2.1). Best-fit values of the EoS parameters including present Hubble parameter (H0) and their acceptable range at different confidence limits are determined. In this model the permitted range for the present Hubble parameter and the transition redshift (zt) at 1σ confidence limits are H0= 70.24^{+0.34}_{-0.36} and zt=0.76^{+0.07}_{-0.07} respectively. These EoS parameters are then compared with those of other models. Present age of the Universe (t0) have also been determined here. Akaike information criterion and Bayesian information criterion for the model selection have been adopted for comparison with other models. It is noted that VGCG model satisfactorily accommodates the present accelerating phase of the Universe.

ASTROPHYSICAL PRIOR INFORMATION AND GRAVITATIONAL-WAVE PARAMETER ESTIMATION

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

Pankow, Chris; Sampson, Laura; Perri, Leah

The detection of electromagnetic counterparts to gravitational waves (GWs) has great promise for the investigation of many scientific questions. While it is well known that certain orientation parameters can reduce uncertainty in other related parameters, it was also hoped that the detection of an electromagnetic signal in conjunction with a GW could augment the measurement precision of the mass and spin from the gravitational signal itself. That is, knowledge of the sky location, inclination, and redshift of a binary could break degeneracies between these extrinsic, coordinate-dependent parameters and the physical parameters that are intrinsic to the binary. In this paper,more » we investigate this issue by assuming perfect knowledge of extrinsic parameters, and assessing the maximal impact of this knowledge on our ability to extract intrinsic parameters. We recover similar gains in extrinsic recovery to earlier work; however, we find only modest improvements in a few intrinsic parameters—namely the primary component’s spin. We thus conclude that, even in the best case, the use of additional information from electromagnetic observations does not improve the measurement of the intrinsic parameters significantly.« less

Correlation of Electric Field and Critical Design Parameters for Ferroelectric Tunable Microwave Filters

NASA Technical Reports Server (NTRS)

Subramanyam, Guru; VanKeuls, Fred W.; Miranda, Felix A.; Canedy, Chadwick L.; Aggarwal, Sanjeev; Venkatesan, Thirumalai; Ramesh, Ramamoorthy

2000-01-01

The correlation of electric field and critical design parameters such as the insertion loss, frequency ability return loss, and bandwidth of conductor/ferroelectric/dielectric microstrip tunable K-band microwave filters is discussed in this work. This work is based primarily on barium strontium titanate (BSTO) ferroelectric thin film based tunable microstrip filters for room temperature applications. Two new parameters which we believe will simplify the evaluation of ferroelectric thin films for tunable microwave filters, are defined. The first of these, called the sensitivity parameter, is defined as the incremental change in center frequency with incremental change in maximum applied electric field (EPEAK) in the filter. The other, the loss parameter, is defined as the incremental or decremental change in insertion loss of the filter with incremental change in maximum applied electric field. At room temperature, the Au/BSTO/LAO microstrip filters exhibited a sensitivity parameter value between 15 and 5 MHz/cm/kV. The loss parameter varied for different bias configurations used for electrically tuning the filter. The loss parameter varied from 0.05 to 0.01 dB/cm/kV at room temperature.

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

USGS Publications Warehouse

Wagener, T.; Hogue, T.; Schaake, J.; Duan, Q.; Gupta, H.; Andreassian, V.; Hall, A.; Leavesley, G.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

Selective laser melting of Ni-rich NiTi: selection of process parameters and the superelastic response

NASA Astrophysics Data System (ADS)

Shayesteh Moghaddam, Narges; Saedi, Soheil; Amerinatanzi, Amirhesam; Saghaian, Ehsan; Jahadakbar, Ahmadreza; Karaca, Haluk; Elahinia, Mohammad

2018-03-01

Material and mechanical properties of NiTi shape memory alloys strongly depend on the fabrication process parameters and the resulting microstructure. In selective laser melting, the combination of parameters such as laser power, scanning speed, and hatch spacing determine the microstructural defects, grain size and texture. Therefore, processing parameters can be adjusted to tailor the microstructure and mechanical response of the alloy. In this work, NiTi samples were fabricated using Ni50.8Ti (at.%) powder via SLM PXM by Phenix/3D Systems and the effects of processing parameters were systematically studied. The relationship between the processing parameters and superelastic properties were investigated thoroughly. It will be shown that energy density is not the only parameter that governs the material response. It will be shown that hatch spacing is the dominant factor to tailor the superelastic response. It will be revealed that with the selection of right process parameters, perfect superelasticity with recoverable strains of up to 5.6% can be observed in the as-fabricated condition.

Shifted one-parameter supersymmetric family of quartic asymmetric double-well potentials

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

Rosu, Haret C., E-mail: hcr@ipicyt.edu.mx; Mancas, Stefan C., E-mail: mancass@erau.edu; Chen, Pisin, E-mail: pisinchen@phys.ntu.edu.tw

2014-10-15

Extending our previous work (Rosu, 2014), we define supersymmetric partner potentials through a particular Riccati solution of the form F(x)=(x−c){sup 2}−1, where c is a real shift parameter, and work out the quartic double-well family of one-parameter isospectral potentials obtained by using the corresponding general Riccati solution. For these parametric double well potentials, we study how the localization properties of the two wells depend on the parameter of the potentials for various values of the shifting parameter. We also consider the supersymmetric parametric family of the first double-well potential in the Razavy chain of double well potentials corresponding to F(x)=1/2more » sinh2x−2((1+√(2))sinh2x)/((1+√(2))cosh2x+1) , both unshifted and shifted, to test and compare the localization properties. - Highlights: • Quartic one-parameter DWs with an additional shift parameter are introduced. • Anomalous localization feature of their zero modes is confirmed at different shifts. • Razavy one-parameter DWs are also introduced and shown not to have this feature.« less

Optimization of reaction parameters of radiation induced grafting of 1-vinylimidazole onto poly(ethylene-co-tetraflouroethene) using response surface method

NASA Astrophysics Data System (ADS)

Nasef, Mohamed Mahmoud; Aly, Amgad Ahmed; Saidi, Hamdani; Ahmad, Arshad

2011-11-01

Radiation induced grafting of 1-vinylimidazole (1-VIm) onto poly(ethylene-co-tetraflouroethene) (ETFE) was investigated. The grafting parameters such as absorbed dose, monomer concentration, grafting time and temperature were optimized using response surface method (RSM). The Box-Behnken module available in the design expert software was used to investigate the effect of reaction conditions (independent parameters) varied in four levels on the degree of grafting ( G%) (response parameter). The model yielded a polynomial equation that relates the linear, quadratic and interaction effects of the independent parameters to the response parameter. The analysis of variance (ANOVA) was used to evaluate the results of the model and detect the significant values for the independent parameters. The optimum parameters to achieve a maximum G% were found to be monomer concentration of 55 vol%, absorbed dose of 100 kGy, time in the range of 14-20 h and a temperature of 61 °C. Fourier transform infrared (FTIR), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used to investigate the properties of the obtained films and provide evidence for grafting.

Analysis of activation energy in Couette-Poiseuille flow of nanofluid in the presence of chemical reaction and convective boundary conditions

NASA Astrophysics Data System (ADS)

Zeeshan, A.; Shehzad, N.; Ellahi, R.

2018-03-01

The motivation of the current article is to explore the energy activation in MHD radiative Couette-Poiseuille flow nanofluid in horizontal channel with convective boundary conditions. The mathematical model of Buongiorno [1] effectively describes the current flow analysis. Additionally, the impact of chemical reaction is also taken in account. The governing flow equations are simplified with the help of boundary layer approximations. Non-linear coupled equations for momentum, energy and mass transfer are tackled with analytical (HAM) technique. The influence of dimensionless convergence parameter like Brownian motion parameter, radiation parameter, buoyancy ratio parameter, dimensionless activation energy, thermophoresis parameter, temperature difference parameter, dimensionless reaction rate, Schmidt number, Brinkman number, Biot number and convection diffusion parameter on velocity, temperature and concentration profiles are discussed graphically and in tabular form. From the results, it is elaborate that the nanoparticle concentration is directly proportional to the chemical reaction with activation energy and the performance of Brownian motion on nanoparticle concentration gives reverse pattern to that of thermophoresis parameter.

Definition and application of a five-parameter characterization of one-dimensional cellular automata rule space.

PubMed

Oliveira, G M; de Oliveira, P P; Omar, N

2001-01-01

Cellular automata (CA) are important as prototypical, spatially extended, discrete dynamical systems. Because the problem of forecasting dynamic behavior of CA is undecidable, various parameter-based approximations have been developed to address the problem. Out of the analysis of the most important parameters available to this end we proposed some guidelines that should be followed when defining a parameter of that kind. Based upon the guidelines, new parameters were proposed and a set of five parameters was selected; two of them were drawn from the literature and three are new ones, defined here. This article presents all of them and makes their qualities evident. Then, two results are described, related to the use of the parameter set in the Elementary Rule Space: a phase transition diagram, and some general heuristics for forecasting the dynamics of one-dimensional CA. Finally, as an example of the application of the selected parameters in high cardinality spaces, results are presented from experiments involving the evolution of radius-3 CA in the Density Classification Task, and radius-2 CA in the Synchronization Task.

A Modified MinMax k-Means Algorithm Based on PSO.

PubMed

Wang, Xiaoyan; Bai, Yanping

The MinMax k -means algorithm is widely used to tackle the effect of bad initialization by minimizing the maximum intraclustering errors. Two parameters, including the exponent parameter and memory parameter, are involved in the executive process. Since different parameters have different clustering errors, it is crucial to choose appropriate parameters. In the original algorithm, a practical framework is given. Such framework extends the MinMax k -means to automatically adapt the exponent parameter to the data set. It has been believed that if the maximum exponent parameter has been set, then the programme can reach the lowest intraclustering errors. However, our experiments show that this is not always correct. In this paper, we modified the MinMax k -means algorithm by PSO to determine the proper values of parameters which can subject the algorithm to attain the lowest clustering errors. The proposed clustering method is tested on some favorite data sets in several different initial situations and is compared to the k -means algorithm and the original MinMax k -means algorithm. The experimental results indicate that our proposed algorithm can reach the lowest clustering errors automatically.

Effective theories of universal theories

DOE PAGES

Wells, James D.; Zhang, Zhengkang

2016-01-20

It is well-known but sometimes overlooked that constraints on the oblique parameters (most notably S and T parameters) are generally speaking only applicable to a special class of new physics scenarios known as universal theories. The oblique parameters should not be associated with Wilson coefficients in a particular operator basis in the effective field theory (EFT) framework, unless restrictions have been imposed on the EFT so that it describes universal theories. Here, we work out these restrictions, and present a detailed EFT analysis of universal theories. We find that at the dimension-6 level, universal theories are completely characterized by 16more » parameters. They are conveniently chosen to be: 5 oblique parameters that agree with the commonly-adopted ones, 4 anomalous triple-gauge couplings, 3 rescaling factors for the h 3, hff, hV V vertices, 3 parameters for hV V vertices absent in the Standard Model, and 1 four-fermion coupling of order yf 2. Furthermore, all these parameters are defined in an unambiguous and basis-independent way, allowing for consistent constraints on the universal theories parameter space from precision electroweak and Higgs data.« less

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

Effective theories of universal theories

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

Wells, James D.; Zhang, Zhengkang

It is well-known but sometimes overlooked that constraints on the oblique parameters (most notably S and T parameters) are generally speaking only applicable to a special class of new physics scenarios known as universal theories. The oblique parameters should not be associated with Wilson coefficients in a particular operator basis in the effective field theory (EFT) framework, unless restrictions have been imposed on the EFT so that it describes universal theories. Here, we work out these restrictions, and present a detailed EFT analysis of universal theories. We find that at the dimension-6 level, universal theories are completely characterized by 16more » parameters. They are conveniently chosen to be: 5 oblique parameters that agree with the commonly-adopted ones, 4 anomalous triple-gauge couplings, 3 rescaling factors for the h 3, hff, hV V vertices, 3 parameters for hV V vertices absent in the Standard Model, and 1 four-fermion coupling of order yf 2. Furthermore, all these parameters are defined in an unambiguous and basis-independent way, allowing for consistent constraints on the universal theories parameter space from precision electroweak and Higgs data.« less

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Error propagation of partial least squares for parameters optimization in NIR modeling.

PubMed

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

Error propagation of partial least squares for parameters optimization in NIR modeling

NASA Astrophysics Data System (ADS)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

Investigation of relationships between removals of tetracycline and degradation products and physicochemical parameters in municipal wastewater treatment plant.

PubMed

Topal, Murat; Uslu Şenel, Gülşad; Öbek, Erdal; Arslan Topal, E Işıl

2016-05-15

Determination of the effect of physicochemical parameters on the removal of tetracycline (TC) and degradation products is important because of the importance of the removal of antibiotics in Wastewater Treatment Plant (WWTP). Therefore, the purpose of this study was to investigate the relationships between removals of TC and degradation products and physicochemical parameters in Municipal Wastewater Treatment Plant (MWWTP). For this aim, (i) the removals of physicochemical parameters in a MWWTP located in Elazığ city (Turkey) were determined (ii) the removals of TC and degradation products in MWWTP were determined (iii) the relationships between removals of TC and degradation products and physicochemical parameters were investigated. TC, 4-epitetracycline (ETC), 4-epianhydrotetracycline (EATC), anhydrotetracycline (ATC), and physicochemical parameters (pH, temperature, electrical conductivity (EC), suspended solids (SS), BOD5, COD, total organic carbon (TOC), NH4(+)-N, NO2(-)-N, NO3(-)-N and O-PO4(-3)) were determined. The calculation of the correlation coefficients of relationships between the physicochemical parameters and TC, EATC, ATC showed that, among the investigated parameters, EATC and SS most correlated. The removals of other physicochemical parameters were not correlated with TC, EATC and ATC. Copyright © 2016 Elsevier Ltd. All rights reserved.

The dimensional reduction method for identification of parameters that trade-off due to similar model roles.

PubMed

Davidson, Shaun M; Docherty, Paul D; Murray, Rua

2017-03-01

Parameter identification is an important and widely used process across the field of biomedical engineering. However, it is susceptible to a number of potential difficulties, such as parameter trade-off, causing premature convergence at non-optimal parameter values. The proposed Dimensional Reduction Method (DRM) addresses this issue by iteratively reducing the dimension of hyperplanes where trade off occurs, and running subsequent identification processes within these hyperplanes. The DRM was validated using clinical data to optimize 4 parameters of the widely used Bergman Minimal Model of glucose and insulin kinetics, as well as in-silico data to optimize 5 parameters of the Pulmonary Recruitment (PR) Model. Results were compared with the popular Levenberg-Marquardt (LMQ) Algorithm using a Monte-Carlo methodology, with both methods afforded equivalent computational resources. The DRM converged to a lower or equal residual value in all tests run using the Bergman Minimal Model and actual patient data. For the PR model, the DRM attained significantly lower overall median parameter error values and lower residuals in the vast majority of tests. This shows the DRM has potential to provide better resolution of optimum parameter values for the variety of biomedical models in which significant levels of parameter trade-off occur. Copyright © 2017 Elsevier Inc. All rights reserved.

a Comparison Between Two Ols-Based Approaches to Estimating Urban Multifractal Parameters

NASA Astrophysics Data System (ADS)

Huang, Lin-Shan; Chen, Yan-Guang

Multifractal theory provides a new spatial analytical tool for urban studies, but many basic problems remain to be solved. Among various pending issues, the most significant one is how to obtain proper multifractal dimension spectrums. If an algorithm is improperly used, the parameter spectrums will be abnormal. This paper is devoted to investigating two ordinary least squares (OLS)-based approaches for estimating urban multifractal parameters. Using empirical study and comparative analysis, we demonstrate how to utilize the adequate linear regression to calculate multifractal parameters. The OLS regression analysis has two different approaches. One is that the intercept is fixed to zero, and the other is that the intercept is not limited. The results of comparative study show that the zero-intercept regression yields proper multifractal parameter spectrums within certain scale range of moment order, while the common regression method often leads to abnormal multifractal parameter values. A conclusion can be reached that fixing the intercept to zero is a more advisable regression method for multifractal parameters estimation, and the shapes of spectral curves and value ranges of fractal parameters can be employed to diagnose urban problems. This research is helpful for scientists to understand multifractal models and apply a more reasonable technique to multifractal parameter calculations.

Parameter interdependence and uncertainty induced by lumping in a hydrologic model

NASA Astrophysics Data System (ADS)

Gallagher, Mark R.; Doherty, John

2007-05-01

Throughout the world, watershed modeling is undertaken using lumped parameter hydrologic models that represent real-world processes in a manner that is at once abstract, but nevertheless relies on algorithms that reflect real-world processes and parameters that reflect real-world hydraulic properties. In most cases, values are assigned to the parameters of such models through calibration against flows at watershed outlets. One criterion by which the utility of the model and the success of the calibration process are judged is that realistic values are assigned to parameters through this process. This study employs regularization theory to examine the relationship between lumped parameters and corresponding real-world hydraulic properties. It demonstrates that any kind of parameter lumping or averaging can induce a substantial amount of "structural noise," which devices such as Box-Cox transformation of flows and autoregressive moving average (ARMA) modeling of residuals are unlikely to render homoscedastic and uncorrelated. Furthermore, values estimated for lumped parameters are unlikely to represent average values of the hydraulic properties after which they are named and are often contaminated to a greater or lesser degree by the values of hydraulic properties which they do not purport to represent at all. As a result, the question of how rigidly they should be bounded during the parameter estimation process is still an open one.

Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

NASA Astrophysics Data System (ADS)

Neverov, V. V.; Kozhukhov, Y. V.; Yablokov, A. M.; Lebedev, A. A.

2017-08-01

Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.

Transformation to equivalent dimensions—a new methodology to study earthquake clustering

NASA Astrophysics Data System (ADS)

Lasocki, Stanislaw

2014-05-01

A seismic event is represented by a point in a parameter space, quantified by the vector of parameter values. Studies of earthquake clustering involve considering distances between such points in multidimensional spaces. However, the metrics of earthquake parameters are different, hence the metric in a multidimensional parameter space cannot be readily defined. The present paper proposes a solution of this metric problem based on a concept of probabilistic equivalence of earthquake parameters. Under this concept the lengths of parameter intervals are equivalent if the probability for earthquakes to take values from either interval is the same. Earthquake clustering is studied in an equivalent rather than the original dimensions space, where the equivalent dimension (ED) of a parameter is its cumulative distribution function. All transformed parameters are of linear scale in [0, 1] interval and the distance between earthquakes represented by vectors in any ED space is Euclidean. The unknown, in general, cumulative distributions of earthquake parameters are estimated from earthquake catalogues by means of the model-free non-parametric kernel estimation method. Potential of the transformation to EDs is illustrated by two examples of use: to find hierarchically closest neighbours in time-space and to assess temporal variations of earthquake clustering in a specific 4-D phase space.

Three-dimensional biofilm structure quantification.

PubMed

Beyenal, Haluk; Donovan, Conrad; Lewandowski, Zbigniew; Harkin, Gary

2004-12-01

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Effects of melody and technique on acoustical and musical features of western operatic singing voices.

PubMed

Larrouy-Maestri, Pauline; Magis, David; Morsomme, Dominique

2014-05-01

The operatic singing technique is frequently used in classical music. Several acoustical parameters of this specific technique have been studied but how these parameters combine remains unclear. This study aims to further characterize the Western operatic singing technique by observing the effects of melody and technique on acoustical and musical parameters of the singing voice. Fifty professional singers performed two contrasting melodies (popular song and romantic melody) with two vocal techniques (with and without operatic singing technique). The common quality parameters (energy distribution, vibrato rate, and extent), perturbation parameters (standard deviation of the fundamental frequency, signal-to-noise ratio, jitter, and shimmer), and musical features (fundamental frequency of the starting note, average tempo, and sound pressure level) of the 200 sung performances were analyzed. The results regarding the effect of melody and technique on the acoustical and musical parameters show that the choice of melody had a limited impact on the parameters observed, whereas a particular vocal profile appeared depending on the vocal technique used. This study confirms that vocal technique affects most of the parameters examined. In addition, the observation of quality, perturbation, and musical parameters contributes to a better understanding of the Western operatic singing technique. Copyright © 2014 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

On the biosorption, by brown seaweed, Lobophora variegata, of Ni(II) from aqueous solutions: equilibrium and thermodynamic studies.

PubMed

Basha, Shaik; Jaiswar, Santlal; Jha, Bhavanath

2010-09-01

The biosorption equilibrium isotherms of Ni(II) onto marine brown algae Lobophora variegata, which was chemically-modified by CaCl(2) were studied and modeled. To predict the biosorption isotherms and to determine the characteristic parameters for process design, twenty-three one-, two-, three-, four- and five-parameter isotherm models were applied to experimental data. The interaction among biosorbed molecules is attractive and biosorption is carried out on energetically different sites and is an endothermic process. The five-parameter Fritz-Schluender model gives the most accurate fit with high regression coefficient, R (2) (0.9911-0.9975) and F-ratio (118.03-179.96), and low standard error, SE (0.0902-0.0.1556) and the residual or sum of square error, SSE (0.0012-0.1789) values to all experimental data in comparison to other models. The biosorption isotherm models fitted the experimental data in the order: Fritz-Schluender (five-parameter) > Freundlich (two-parameter) > Langmuir (two-parameter) > Khan (three-parameter) > Fritz-Schluender (four-parameter). The thermodynamic parameters such as DeltaG (0), DeltaH (0) and DeltaS (0) have been determined, which indicates the sorption of Ni(II) onto L. variegata was spontaneous and endothermic in nature.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

[Individual social factors and their association with environmental socioeconomic factors--a descriptive small-area analysis in the city of Dortmund].

PubMed

Neuner, B; Berger, K

2010-11-01

Apart from individual resources and individual risk factors, environmental socioeconomic factors are determinants of individual health and illness. The aim of this investigation was to evaluate the association of small-area environmental socioeconomic parameters (proportion of 14-year-old and younger population, proportion of married citizens, proportion of unemployed, and the number of private cars per inhabitant) with individual socioeconomic parameters (education, income, unemployment, social class and the country of origin) in Dortmund, a major city in Germany. After splitting the small-area environmental socioeconomic parameters of 62 statistical administration units into quintiles, differences in the distribution of individual social parameters were evaluated using adjusted tests for trend. Overall, 1,312 study participants (mean age 53.6 years, 52.9% women) were included. Independently of age and gender, individual social parameters were unequally distributed across areas with different small-area environmental socioeconomic parameters. A place of birth abroad and social class were significantly associated with all small-area environmental socioeconomic parameters. If the impact of environmental socioeconomic parameters on individual health or illness is determined, the unequal small-area distribution of individual social parameters should be considered. © Georg Thieme Verlag KG Stuttgart · New York.

Evaluating Glaucomatous Retinal Nerve Fiber Damage by GDx VCC Polarimetry in Taiwan Chinese Population

PubMed Central

Chen, Hsin-Yi; Huang, Mei-Ling; Huang, Wei-Cheng

2010-01-01

Purpose To study the capability of scanning laser polarimetry with variable corneal compensation (GDx VCC) to detect differences in retinal nerve fiber layer thickness between normal and glaucomatous eyes in a Taiwan Chinese population. Methods This study included 44 normal eyes and 107 glaucomatous eyes. The glaucomatous eyes were divided into three subgroups on the basis of its visual field defects (early, moderate, severe). Each subject underwent a GDx-VCC exam and visual field testing. The area under the receiver-operating characteristic curve (AROC) of each relevant parameter was used to differentiate normal from each glaucoma subgroup, respectively. The correlation between visual field index and each parameter was evaluated for the eyes in the glaucoma group. Results For normal vs. early glaucoma, the parameter with the best AROC was Nerve fiber indicator (NFI) (0.942). For normal vs. moderate glaucoma, the parameter showing the best AROC was NFI (0.985). For normal vs. severe glaucoma, the parameter that had the best AROC was NFI (1.000). For early vs. moderate glaucoma, the parameter with the best AROC was NFI (0.732). For moderate vs. severe, the parameter showing the best AROC was temporal-superior-nasal-inferior-temporal average (0.652). For early vs. severe, the parameter with the best AROC was NFI (0.852). Conclusions GDx-VCC-measured parameters may serve as a useful tool to distinguish normal from glaucomatous eyes; in particular, NFI turned out to be the best discriminating parameter.

On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy.

PubMed

Svolos, Patricia; Tsougos, Ioannis; Kyrgias, Georgios; Kappas, Constantine; Theodorou, Kiki

2011-04-01

In this study we sought to evaluate and accent the importance of radiobiological parameter selection and implementation to the normal tissue complication probability (NTCP) models. The relative seriality (RS) and the Lyman-Kutcher-Burman (LKB) models were studied. For each model, a minimum and maximum set of radiobiological parameter sets was selected from the overall published sets applied in literature and a theoretical mean parameter set was computed. In order to investigate the potential model weaknesses in NTCP estimation and to point out the correct use of model parameters, these sets were used as input to the RS and the LKB model, estimating radiation induced complications for a group of 36 breast cancer patients treated with radiotherapy. The clinical endpoint examined was Radiation Pneumonitis. Each model was represented by a certain dose-response range when the selected parameter sets were applied. Comparing the models with their ranges, a large area of coincidence was revealed. If the parameter uncertainties (standard deviation) are included in the models, their area of coincidence might be enlarged, constraining even greater their predictive ability. The selection of the proper radiobiological parameter set for a given clinical endpoint is crucial. Published parameter values are not definite but should be accompanied by uncertainties, and one should be very careful when applying them to the NTCP models. Correct selection and proper implementation of published parameters provides a quite accurate fit of the NTCP models to the considered endpoint.

Parameter Estimation of Partial Differential Equation Models.

PubMed

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

Assessing the accuracy of subject-specific, muscle-model parameters determined by optimizing to match isometric strength.

PubMed

DeSmitt, Holly J; Domire, Zachary J

2016-12-01

Biomechanical models are sensitive to the choice of model parameters. Therefore, determination of accurate subject specific model parameters is important. One approach to generate these parameters is to optimize the values such that the model output will match experimentally measured strength curves. This approach is attractive as it is inexpensive and should provide an excellent match to experimentally measured strength. However, given the problem of muscle redundancy, it is not clear that this approach generates accurate individual muscle forces. The purpose of this investigation is to evaluate this approach using simulated data to enable a direct comparison. It is hypothesized that the optimization approach will be able to recreate accurate muscle model parameters when information from measurable parameters is given. A model of isometric knee extension was developed to simulate a strength curve across a range of knee angles. In order to realistically recreate experimentally measured strength, random noise was added to the modeled strength. Parameters were solved for using a genetic search algorithm. When noise was added to the measurements the strength curve was reasonably recreated. However, the individual muscle model parameters and force curves were far less accurate. Based upon this examination, it is clear that very different sets of model parameters can recreate similar strength curves. Therefore, experimental variation in strength measurements has a significant influence on the results. Given the difficulty in accurately recreating individual muscle parameters, it may be more appropriate to perform simulations with lumped actuators representing similar muscles.

Utility of a novel error-stepping method to improve gradient-based parameter identification by increasing the smoothness of the local objective surface: a case-study of pulmonary mechanics.

PubMed

Docherty, Paul D; Schranz, Christoph; Chase, J Geoffrey; Chiew, Yeong Shiong; Möller, Knut

2014-05-01

Accurate model parameter identification relies on accurate forward model simulations to guide convergence. However, some forward simulation methodologies lack the precision required to properly define the local objective surface and can cause failed parameter identification. The role of objective surface smoothness in identification of a pulmonary mechanics model was assessed using forward simulation from a novel error-stepping method and a proprietary Runge-Kutta method. The objective surfaces were compared via the identified parameter discrepancy generated in a Monte Carlo simulation and the local smoothness of the objective surfaces they generate. The error-stepping method generated significantly smoother error surfaces in each of the cases tested (p<0.0001) and more accurate model parameter estimates than the Runge-Kutta method in three of the four cases tested (p<0.0001) despite a 75% reduction in computational cost. Of note, parameter discrepancy in most cases was limited to a particular oblique plane, indicating a non-intuitive multi-parameter trade-off was occurring. The error-stepping method consistently improved or equalled the outcomes of the Runge-Kutta time-integration method for forward simulations of the pulmonary mechanics model. This study indicates that accurate parameter identification relies on accurate definition of the local objective function, and that parameter trade-off can occur on oblique planes resulting prematurely halted parameter convergence. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)

DOE PAGES

Guo, Zhun; Wang, Minghuai; Qian, Yun; ...

2015-07-03

In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher order closure (HOC) scheme, and 4 parameters of the Zhang-McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low-cloud properties (cloud fraction and liquid water path) can be explained bymore » the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussians closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud-regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in-cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low-cloud fraction. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.« less

To Find a Better Dosimetric Parameter in the Predicting of Radiation-Induced Lung Toxicity Individually: Ventilation, Perfusion or CT based.

PubMed

Xiao, Lin-Lin; Yang, Guoren; Chen, Jinhu; Wang, Xiaohui; Wu, Qingwei; Huo, Zongwei; Yu, Qingxi; Yu, Jinming; Yuan, Shuanghu

2017-03-15

This study aimed to find a better dosimetric parameter in predicting of radiation-induced lung toxicity (RILT) in patients with non-small cell lung cancer (NSCLC) individually: ventilation(V), perfusion (Q) or computerized tomography (CT) based. V/Q single-photon emission computerized tomography (SPECT) was performed within 1 week prior to radiotherapy (RT). All V/Q imaging data was integrated into RT planning system, generating functional parameters based on V/Q SPECT. Fifty-seven NSCLC patients were enrolled in this prospective study. Fifteen (26.3%) patients underwent grade ≥2 RILT, the remaining forty-two (73.7%) patients didn't. Q-MLD, Q-V20, V-MLD, V-V20 of functional parameters correlated more significantly with the occurrence of RILT compared to V20, MLD of anatomical parameters (r = 0.630; r = 0.644; r = 0.617; r = 0.651 vs. r = 0.424; r = 0.520 p < 0.05, respectively). In patients with chronic obstructive pulmonary diseases (COPD), V functional parameters reflected significant advantage in predicting RILT; while in patients without COPD, Q functional parameters reflected significant advantage. Analogous results were existed in fractimal analysis of global pulmonary function test (PFT). In patients with central-type NSCLC, V parameters were better than Q parameters; while in patients with peripheral-type NSCLC, the results were inverse. Therefore, this study demonstrated that choosing a suitable dosimetric parameter individually can help us predict RILT accurately.

Hands-on parameter search for neural simulations by a MIDI-controller.

PubMed

Eichner, Hubert; Borst, Alexander

2011-01-01

Computational neuroscientists frequently encounter the challenge of parameter fitting--exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems.

Hands-On Parameter Search for Neural Simulations by a MIDI-Controller

PubMed Central

Eichner, Hubert; Borst, Alexander

2011-01-01

Computational neuroscientists frequently encounter the challenge of parameter fitting – exploring a usually high dimensional variable space to find a parameter set that reproduces an experimental data set. One common approach is using automated search algorithms such as gradient descent or genetic algorithms. However, these approaches suffer several shortcomings related to their lack of understanding the underlying question, such as defining a suitable error function or getting stuck in local minima. Another widespread approach is manual parameter fitting using a keyboard or a mouse, evaluating different parameter sets following the users intuition. However, this process is often cumbersome and time-intensive. Here, we present a new method for manual parameter fitting. A MIDI controller provides input to the simulation software, where model parameters are then tuned according to the knob and slider positions on the device. The model is immediately updated on every parameter change, continuously plotting the latest results. Given reasonably short simulation times of less than one second, we find this method to be highly efficient in quickly determining good parameter sets. Our approach bears a close resemblance to tuning the sound of an analog synthesizer, giving the user a very good intuition of the problem at hand, such as immediate feedback if and how results are affected by specific parameter changes. In addition to be used in research, our approach should be an ideal teaching tool, allowing students to interactively explore complex models such as Hodgkin-Huxley or dynamical systems. PMID:22066027

Tuning Parameters in Heuristics by Using Design of Experiments Methods

NASA Technical Reports Server (NTRS)

Arin, Arif; Rabadi, Ghaith; Unal, Resit

2010-01-01

With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

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

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

2016-07-04

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

Analysis of sagittal spinopelvic parameters in achondroplasia.

PubMed

Hong, Jae-Young; Suh, Seung-Woo; Modi, Hitesh N; Park, Jong-Woong; Park, Jung-Ho

2011-08-15

Prospective radiological analysis of patients with achondroplasia. To analyze sagittal spinal alignment and pelvic orientation in achondroplasia patients. Knowledge of sagittal spinopelvic parameters is important for the treatment of achondroplasia, because they differ from those of the normal population and can induce pain. The study and control groups were composed of 32 achondroplasia patients and 24 healthy volunteers, respectively. All underwent lateral radiography of the whole spine including hip joints. The radiographic parameters examined were sacral slope (SS), pelvic tilt, pelvic incidence (PI), S1 overhang, thoracic kyphosis, T10-L2 kyphosis, lumbar lordosis (LL1, LL2), and sagittal balance. Statistical analysis was performed to identify significant differences between the two groups. In addition, correlations between parameters and symptoms were sought. Sagittal spinopelvic parameters, namely, pelvic tilt, pelvic incidence, S1 overhang, thoracic kyphosis, T10-L2 kyphosis, lumbar lordosis 1 and sagittal balance were found to be significantly different in the patient and control groups (P < 0.05). In addition, sagittal parameters were found to be related to each other in the patient group (P < 0.05), that is, PI was related to SS and pelvic tilt, and LL was related to thoracic kyphosis. Furthermore, in terms of relations between spinal and pelvic parameters, LL was related to SS and PI, and sagittal balance was related to SS and PI. Furthermore, LL and T10-L2 kyphosis were found to be related to pain (P < 0.05), whereas no other parameter was found to be related to VAS scores. Sagittal parameters and possible relationships between sagittal parameters and symptoms were found to be significantly different in achondroplasia patients and normal healthy controls. The present study shows that sagittal spinal and pelvic parameters can assist the treatment of spinal disorders in achondroplasia patients.

Non-extensive entropy and properties of polaron in RbCl delta quantum dot under an applied electric field and Coulombic impurity

NASA Astrophysics Data System (ADS)

Tiotsop, M.; Fotue, A. J.; Fotsin, H. B.; Fai, L. C.

2017-08-01

Bound polaron in RbCl delta quantum dot under electric field and Coulombic impurity were considered. The ground and first excited state energy were derived by employing Pekar variational and unitary transformation methods. Applying Fermi golden rule, the expression of temperature and polaron lifetime were derived. The decoherence was studied trough the Tsallis entropy. Results shows that decreasing (or increasing) the lifetime increases (or decreases) the temperature and delta parameter (electric field strength and hydrogenic impurity). This suggests that to accelerate quantum transition in nanostructure, temperature and delta have to be enhanced. The improvement of electric field and coulomb parameter, increases the lifetime of the delta quantum dot qubit. Energy spectrum of polaron increases with increase in temperature, electric field strength, Coulomb parameter, delta parameter, and polaronic radius. The control of the delta quantum dot energies can be done via the electric field, coulomb impurity, and delta parameter. Results also show that the non-extensive entropy is an oscillatory function of time. With the enhancement of delta parameter, non-extensive parameter, Coulombic parameter, and electric field strength, the entropy has a sinusoidal increase behavior with time. With the study of decoherence through the Tsallis entropy, it may be advised that to have a quantum system with efficient transmission of information, the non-extensive and delta parameters need to be significant. The study of the probability density showed an increase from the boundary to the center of the dot where it has its maximum value and oscillates with period T0 = ℏ / ΔE with the tunneling of the delta parameter, electric field strength, and Coulombic parameter. The results may be very helpful in the transmission of information in nanostructures and control of decoherence

Arrhenius parameter determination as a function of heating method and cellular microenvironment based on spatial cell viability analysis.

PubMed

Whitney, Jon; Carswell, William; Rylander, Nichole

2013-06-01

Predictions of injury in response to photothermal therapy in vivo are frequently made using Arrhenius parameters obtained from cell monolayers exposed to laser or water bath heating. However, the impact of different heating methods and cellular microenvironments on Arrhenius predictions has not been thoroughly investigated. This study determined the influence of heating method (water bath and laser irradiation) and cellular microenvironment (cell monolayers and tissue phantoms) on Arrhenius parameters and spatial viability. MDA-MB-231 cells seeded in monolayers and sodium alginate phantoms were heated with a water bath for 3-20 min at 46, 50, and 54 °C or laser irradiated (wavelength of 1064 nm and fluences of 40 W/cm(2) or 3.8 W/cm(2) for 0-4 min) in combination with photoabsorptive carbon nanohorns. Spatial viability was measured using digital image analysis of cells stained with calcein AM and propidium iodide and used to determine Arrhenius parameters. The influence of microenvironment and heating method on Arrhenius parameters and capability of parameters derived from more simplistic experimental conditions (e.g. water bath heating of monolayers) to predict more physiologically relevant systems (e.g. laser heating of phantoms) were assessed. Arrhenius predictions of the treated area (<1% viable) under-predicted the measured areas in photothermally treated phantoms by 23 mm(2) using water bath treated cell monolayer parameters, 26 mm(2) using water bath treated phantom parameters, 27 mm(2) using photothermally treated monolayer parameters, and 0.7 mm(2) using photothermally treated phantom parameters. Heating method and cellular microenvironment influenced Arrhenius parameters, with heating method having the greater impact.

Reference intervals for 24 laboratory parameters determined in 24-hour urine collections.

PubMed

Curcio, Raffaele; Stettler, Helen; Suter, Paolo M; Aksözen, Jasmin Barman; Saleh, Lanja; Spanaus, Katharina; Bochud, Murielle; Minder, Elisabeth; von Eckardstein, Arnold

2016-01-01

Reference intervals for many laboratory parameters determined in 24-h urine collections are either not publicly available or based on small numbers, not sex specific or not from a representative sample. Osmolality and concentrations or enzymatic activities of sodium, potassium, chloride, glucose, creatinine, citrate, cortisol, pancreatic α-amylase, total protein, albumin, transferrin, immunoglobulin G, α1-microglobulin, α2-macroglobulin, as well as porphyrins and their precursors (δ-aminolevulinic acid and porphobilinogen) were determined in 241 24-h urine samples of a population-based cohort of asymptomatic adults (121 men and 120 women). For 16 of these 24 parameters creatinine-normalized ratios were calculated based on 24-h urine creatinine. The reference intervals for these parameters were calculated according to the CLSI C28-A3 statistical guidelines. By contrast to most published reference intervals, which do not stratify for sex, reference intervals of 12 of 24 laboratory parameters in 24-h urine collections and of eight of 16 parameters as creatinine-normalized ratios differed significantly between men and women. For six parameters calculated as 24-h urine excretion and four parameters calculated as creatinine-normalized ratios no reference intervals had been published before. For some parameters we found significant and relevant deviations from previously reported reference intervals, most notably for 24-h urine cortisol in women. Ten 24-h urine parameters showed weak or moderate sex-specific correlations with age. By applying up-to-date analytical methods and clinical chemistry analyzers to 24-h urine collections from a large population-based cohort we provide as yet the most comprehensive set of sex-specific reference intervals calculated according to CLSI guidelines for parameters determined in 24-h urine collections.

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE PAGES

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; ...

2016-06-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

Comparisons of Solar Wind Coupling Parameters with Auroral Energy Deposition Rates

NASA Technical Reports Server (NTRS)

Elsen, R.; Brittnacher, M. J.; Fillingim, M. O.; Parks, G. K.; Germany G. A.; Spann, J. F., Jr.

1997-01-01

Measurement of the global rate of energy deposition in the ionosphere via auroral particle precipitation is one of the primary goals of the Polar UVI program and is an important component of the ISTP program. The instantaneous rate of energy deposition for the entire month of January 1997 has been calculated by applying models to the UVI images and is presented by Fillingim et al. In this session. A number of parameters that predict the rate of coupling of solar wind energy into the magnetosphere have been proposed in the last few decades. Some of these parameters, such as the epsilon parameter of Perrault and Akasofu, depend on the instantaneous values in the solar wind. Other parameters depend on the integrated values of solar wind parameters, especially IMF Bz, e.g. applied flux which predicts the net transfer of magnetic flux to the tail. While these parameters have often been used successfully with substorm studies, their validity in terms of global energy input has not yet been ascertained, largely because data such as that supplied by the ISTP program was lacking. We have calculated these and other energy coupling parameters for January 1997 using solar wind data provided by WIND and other solar wind monitors. The rates of energy input predicted by these parameters are compared to those measured through UVI data and correlations are sought. Whether these parameters are better at providing an instantaneous rate of energy input or an average input over some time period is addressed. We also study if either type of parameter may provide better correlations if a time delay is introduced; if so, this time delay may provide a characteristic time for energy transport in the coupled solar wind-magnetosphere-ionosphere system.

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

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

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites

NASA Astrophysics Data System (ADS)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; Ren, Huiying; Liu, Ying; Swiler, Laura

2016-07-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

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

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

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

Able, CM; Baydush, AH; Nguyen, C

2014-06-15

Purpose: To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. Methods: A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, andmore » cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. Results: There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. Conclusion: Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.« less

Characterization of breast lesion using T1-perfusion magnetic resonance imaging: Qualitative vs. quantitative analysis.

PubMed

Thakran, S; Gupta, P K; Kabra, V; Saha, I; Jain, P; Gupta, R K; Singh, A

2018-06-14

The objective of this study was to quantify the hemodynamic parameters using first pass analysis of T 1 -perfusion magnetic resonance imaging (MRI) data of human breast and to compare these parameters with the existing tracer kinetic parameters, semi-quantitative and qualitative T 1 -perfusion analysis in terms of lesion characterization. MRI of the breast was performed in 50 women (mean age, 44±11 [SD] years; range: 26-75) years with a total of 15 benign and 35 malignant breast lesions. After pre-processing, T 1 -perfusion MRI data was analyzed using qualitative approach by two radiologists (visual inspection of the kinetic curve into types I, II or III), semi-quantitative (characterization of kinetic curve types using empirical parameters), generalized-tracer-kinetic-model (tracer kinetic parameters) and first pass analysis (hemodynamic-parameters). Chi-squared test, t-test, one-way analysis-of-variance (ANOVA) using Bonferroni post-hoc test and receiver-operating-characteristic (ROC) curve were used for statistical analysis. All quantitative parameters except leakage volume (Ve), qualitative (type-I and III) and semi-quantitative curves (type-I and III) provided significant differences (P<0.05) between benign and malignant lesions. Kinetic parameters, particularly volume transfer coefficient (K trans ) provided a significant difference (P<0.05) between all grades except grade-II vs III. The hemodynamic parameter (relative-leakage-corrected-breast-blood-volume [rBBVcorr) provided a statistically significant difference (P<0.05) between all grades. It also provided highest sensitivity and specificity among all parameters in differentiation between different grades of malignant breast lesions. Quantitative parameters, particularly rBBVcorr and K trans provided similar sensitivity and specificity in differentiating benign from malignant breast lesions for this cohort. Moreover, rBBVcorr provided better differentiation between different grades of malignant breast lesions among all the parameters. Copyright © 2018. Published by Elsevier Masson SAS.

Catchment Tomography - Joint Estimation of Surface Roughness and Hydraulic Conductivity with the EnKF

NASA Astrophysics Data System (ADS)

Baatz, D.; Kurtz, W.; Hendricks Franssen, H. J.; Vereecken, H.; Kollet, S. J.

2017-12-01

Parameter estimation for physically based, distributed hydrological models becomes increasingly challenging with increasing model complexity. The number of parameters is usually large and the number of observations relatively small, which results in large uncertainties. A moving transmitter - receiver concept to estimate spatially distributed hydrological parameters is presented by catchment tomography. In this concept, precipitation, highly variable in time and space, serves as a moving transmitter. As response to precipitation, runoff and stream discharge are generated along different paths and time scales, depending on surface and subsurface flow properties. Stream water levels are thus an integrated signal of upstream parameters, measured by stream gauges which serve as the receivers. These stream water level observations are assimilated into a distributed hydrological model, which is forced with high resolution, radar based precipitation estimates. Applying a joint state-parameter update with the Ensemble Kalman Filter, the spatially distributed Manning's roughness coefficient and saturated hydraulic conductivity are estimated jointly. The sequential data assimilation continuously integrates new information into the parameter estimation problem, especially during precipitation events. Every precipitation event constrains the possible parameter space. In the approach, forward simulations are performed with ParFlow, a variable saturated subsurface and overland flow model. ParFlow is coupled to the Parallel Data Assimilation Framework for the data assimilation and the joint state-parameter update. In synthetic, 3-dimensional experiments including surface and subsurface flow, hydraulic conductivity and the Manning's coefficient are efficiently estimated with the catchment tomography approach. A joint update of the Manning's coefficient and hydraulic conductivity tends to improve the parameter estimation compared to a single parameter update, especially in cases of biased initial parameter ensembles. The computational experiments additionally show to which degree of spatial heterogeneity and to which degree of uncertainty of subsurface flow parameters the Manning's coefficient and hydraulic conductivity can be estimated efficiently.

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool.

PubMed

Wu, Q; Zhao, X; You, H

2017-05-18

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver fibrosis assessment in different stages of PBC compared with CHB.

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool

PubMed Central

Wu, Q.; Zhao, X.; You, H.

2017-01-01

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver fibrosis assessment in different stages of PBC compared with CHB. PMID:28538834

Relative sensitivity of developmental and immune parameters in juvenile versus adult male rats after exposure to di(2-ethylhexyl) phthalate

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

Tonk, Elisa C.M., E-mail: ilse.tonk@rivm.nl; Laboratory for Health Protection Research, National Institute for Public Health and the Environment; Verhoef, Aart

The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 atmore » doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the developing immune system for DEHP.« less

Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil

NASA Technical Reports Server (NTRS)

Schluessel, G.; Dickinson, R. E.; Privette, J. L.; Emery, W. J.; Kokaly, R.

1994-01-01

An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al., 1988). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. The most stable parameter was the single-scattering albedo of the vegetation. Canopy albedo could be derived with an accuracy of less than 5% relative error in the visible and less than 1% in the near-infrared. Sensitivity were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI values the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (greater than 2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the seven least significant parameters, gave higher rms values but was less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model.

GaAs, AlAs, and AlxGa1-xAs: Material parameters for use in research and device applications

NASA Astrophysics Data System (ADS)

Adachi, Sadao

1985-08-01

The AlxGa1-xAs/GaAs heterostructure system is potentially useful material for high-speed digital, high-frequency microwave, and electro-optic device applications. Even though the basic AlxGa1-xAs/GaAs heterostructure concepts are understood at this time, some practical device parameters in this system have been hampered by a lack of definite knowledge of many material parameters. Recently, Blakemore has presented numerical and graphical information about many of the physical and electronic properties of GaAs [J. S. Blakemore, J. Appl. Phys. 53, R123 (1982)]. The purpose of this review is (i) to obtain and clarify all the various material parameters of AlxGa1-xAs alloy from a systematic point of view, and (ii) to present key properties of the material parameters for a variety of research works and device applications. A complete set of material parameters are considered in this review for GaAs, AlAs, and AlxGa1-xAs alloys. The model used is based on an interpolation scheme and, therefore, necessitates known values of the parameters for the related binaries (GaAs and AlAs). The material parameters and properties considered in the present review can be classified into sixteen groups: (1) lattice constant and crystal density, (2) melting point, (3) thermal expansion coefficient, (4) lattice dynamic properties, (5) lattice thermal properties, (6) electronic-band structure, (7) external perturbation effects on the band-gap energy, (8) effective mass, (9) deformation potential, (10) static and high-frequency dielectric constants, (11) magnetic susceptibility, (12) piezoelectric constant, (13) Fröhlich coupling parameter, (14) electron transport properties, (15) optical properties, and (16) photoelastic properties. Of particular interest is the deviation of material parameters from linearity with respect to the AlAs mole fraction x. Some material parameters, such as lattice constant, crystal density, thermal expansion coefficient, dielectric constant, and elastic constant, obey Vegard's rule well. Other parameters, e.g., electronic-band energy, lattice vibration (phonon) energy, Debye temperature, and impurity ionization energy, exhibit quadratic dependence upon the AlAs mole fraction. However, some kinds of the material parameters, e.g., lattice thermal conductivity, exhibit very strong nonlinearity with respect to x, which arises from the effects of alloy disorder. It is found that the present model provides generally acceptable parameters in good agreement with the existing experimental data. A detailed discussion is also given of the acceptability of such interpolated parameters from an aspect of solid-state physics. Key properties of the material parameters for use in research work and a variety of AlxGa1-xAs/GaAs device applications are also discussed in detail.

Parameter estimation in Probabilistic Seismic Hazard Analysis: current problems and some solutions

NASA Astrophysics Data System (ADS)

Vermeulen, Petrus

2017-04-01

A typical Probabilistic Seismic Hazard Analysis (PSHA) comprises identification of seismic source zones, determination of hazard parameters for these zones, selection of an appropriate ground motion prediction equation (GMPE), and integration over probabilities according the Cornell-McGuire procedure. Determination of hazard parameters often does not receive the attention it deserves, and, therefore, problems therein are often overlooked. Here, many of these problems are identified, and some of them addressed. The parameters that need to be identified are those associated with the frequency-magnitude law, those associated with earthquake recurrence law in time, and the parameters controlling the GMPE. This study is concerned with the frequency-magnitude law and temporal distribution of earthquakes, and not with GMPEs. TheGutenberg-Richter frequency-magnitude law is usually adopted for the frequency-magnitude law, and a Poisson process for earthquake recurrence in time. Accordingly, the parameters that need to be determined are the slope parameter of the Gutenberg-Richter frequency-magnitude law, i.e. the b-value, the maximum value at which the Gutenberg-Richter law applies mmax, and the mean recurrence frequency,λ, of earthquakes. If, instead of the Cornell-McGuire, the "Parametric-Historic procedure" is used, these parameters do not have to be known before the PSHA computations, they are estimated directly during the PSHA computation. The resulting relation for the frequency of ground motion vibration parameters has an analogous functional form to the frequency-magnitude law, which is described by parameters γ (analogous to the b¬-value of the Gutenberg-Richter law) and the maximum possible ground motion amax (analogous to mmax). Originally, the approach was possible to apply only to the simple GMPE, however, recently a method was extended to incorporate more complex forms of GMPE's. With regards to the parameter mmax, there are numerous methods of estimation, none of which is accepted as the standard one. There is also much controversy surrounding this parameter. In practice, when estimating the above mentioned parameters from seismic catalogue, the magnitude, mmin, from which a seismic catalogue is complete becomes important.Thus, the parameter mmin is also considered as a parameter to be estimated in practice. Several methods are discussed in the literature, and no specific method is preferred. Methods usually aim at identifying the point where a frequency-magnitude plot starts to deviate from linearity due to data loss. Parameter estimation is clearly a rich field which deserves much attention and, possibly standardization, of methods. These methods should be the sound and efficient, and a query into which methods are to be used - and for that matter which ones are not to be used - is in order.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Inverse modeling with RZWQM2 to predict water quality

USGS Publications Warehouse

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which reflect the total information provided by the observations for a parameter, indicated that most of the RZWQM2 parameters at the California study site (CA) and Iowa study site (IA) could be reliably estimated by regression. Correlations obtained in the CA case indicated that all model parameters could be uniquely estimated by inverse modeling. Although water content at field capacity was highly correlated with bulk density (−0.94), the correlation is less than the threshold for nonuniqueness (0.95, absolute value basis). Additionally, we used truncated singular value decomposition (SVD) at CA to mitigate potential problems with highly correlated and insensitive parameters. Singular value decomposition estimates linear combinations (eigenvectors) of the original process-model parameters. Parameter confidence intervals (CIs) at CA indicated that parameters were reliably estimated with the possible exception of an organic pool transfer coefficient (R45), which had a comparatively wide CI. However, the 95% confidence interval for R45 (0.03–0.35) is mostly within the range of values reported for this parameter. Predictive analysis at CA generated confidence intervals that were compared with independently measured annual water flux (groundwater recharge) and median nitrate concentration in a collocated monitoring well as part of model evaluation. Both the observed recharge (42.3 cm yr−1) and nitrate concentration (24.3 mg L−1) were within their respective 90% confidence intervals, indicating that overall model error was within acceptable limits.

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

NASA Astrophysics Data System (ADS)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification techniques for model calibration. For Bayesian model calibration, we employ adaptive Metropolis algorithms to construct densities for input parameters in the heat model and the HIV model. To quantify the uncertainty in the parameters, we employ two MCMC algorithms: Delayed Rejection Adaptive Metropolis (DRAM) [33] and Differential Evolution Adaptive Metropolis (DREAM) [66, 68]. The densities obtained using these methods are compared to those obtained through the direct numerical evaluation of the Bayes' formula. We also combine uncertainties in input parameters and measurement errors to construct predictive estimates for a model response. A significant emphasis is on the development and illustration of techniques to verify the accuracy of sampling-based Metropolis algorithms. We verify the accuracy of DRAM and DREAM by comparing chains, densities and correlations obtained using DRAM, DREAM and the direct evaluation of Bayes formula. We also perform similar analysis for credible and prediction intervals for responses. Once the parameters are estimated, we employ energy statistics test [63, 64] to compare the densities obtained by different methods for the HIV model. The energy statistics are used to test the equality of distributions. We also consider parameter selection and verification techniques for models having one or more parameters that are noninfluential in the sense that they minimally impact model outputs. We illustrate these techniques for a dynamic HIV model but note that the parameter selection and verification framework is applicable to a wide range of biological and physical models. To accommodate the nonlinear input to output relations, which are typical for such models, we focus on global sensitivity analysis techniques, including those based on partial correlations, Sobol indices based on second-order model representations, and Morris indices, as well as a parameter selection technique based on standard errors. A significant objective is to provide verification strategies to assess the accuracy of those techniques, which we illustrate in the context of the HIV model. Finally, we examine active subspace methods as an alternative to parameter subset selection techniques. The objective of active subspace methods is to determine the subspace of inputs that most strongly affect the model response, and to reduce the dimension of the input space. The major difference between active subspace methods and parameter selection techniques is that parameter selection identifies influential parameters whereas subspace selection identifies a linear combination of parameters that impacts the model responses significantly. We employ active subspace methods discussed in [22] for the HIV model and present a verification that the active subspace successfully reduces the input dimensions.

Developing an Interpretation of Item Parameters for Personality Items: Content Correlates of Parameter Estimates.

ERIC Educational Resources Information Center

Zickar, Michael J.; Ury, Karen L.

2002-01-01

Attempted to relate content features of personality items to item parameter estimates from the partial credit model of E. Muraki (1990) by administering the Adjective Checklist (L. Goldberg, 1992) to 329 undergraduates. As predicted, the discrimination parameter was related to the item subtlety ratings of personality items but the level of word…

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

Anderson, Mark A.; Bigelow, Matthew; Gilkey, Jeff C.

The Super Strypi SWIL is a six degree-of-freedom (6DOF) simulation for the Super Strypi Launch Vehicle that includes a subset of the Super Strypi NGC software (guidance, ACS and sequencer). Aerodynamic and propulsive forces, mass properties, ACS (attitude control system) parameters, guidance parameters and Monte-Carlo parameters are defined in input files. Output parameters are saved to a Matlab mat file.

Inversion of scattered radiance horizon profiles for gaseous concentrations and aerosol parameters

NASA Technical Reports Server (NTRS)

Malchow, H. L.; Whitney, C. K.

1977-01-01

Techniques have been developed and used to invert limb scan measurements for vertical profiles of atmospheric state parameters. The parameters which can be found are concentrations of Rayleigh scatters, ozone, NO2, and aerosols, and aerosol physical properties including a Junge-size distribution parameter and real and imaginary parts of the index of refraction.

Uncertainties in the Item Parameter Estimates and Robust Automated Test Assembly

ERIC Educational Resources Information Center

Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G.

2013-01-01

Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…

Meta-Learning Approach for Automatic Parameter Tuning: A Case Study with Educational Datasets

ERIC Educational Resources Information Center

Molina, M. M.; Luna, J. M.; Romero, C.; Ventura, S.

2012-01-01

This paper proposes to the use of a meta-learning approach for automatic parameter tuning of a well-known decision tree algorithm by using past information about algorithm executions. Fourteen educational datasets were analysed using various combinations of parameter values to examine the effects of the parameter values on accuracy classification.…

Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

ERIC Educational Resources Information Center

Glockner, Andreas; Pachur, Thorsten

2012-01-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

40 CFR 60.3043 - What operating parameter monitoring equipment must I install, and what operating parameters must...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 6 2011-07-01 2011-07-01 false What operating parameter monitoring equipment must I install, and what operating parameters must I monitor? 60.3043 Section 60.3043 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission...

40 CFR 60.2944 - What operating parameter monitoring equipment must I install, and what operating parameters must...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 6 2011-07-01 2011-07-01 false What operating parameter monitoring equipment must I install, and what operating parameters must I monitor? 60.2944 Section 60.2944 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Operator...

The Hildebrand Solubility Parameters of Ionic Liquids—Part 2

PubMed Central

Marciniak, Andrzej

2011-01-01

The Hildebrand solubility parameters have been calculated for eight ionic liquids. Retention data from the inverse gas chromatography measurements of the activity coefficients at infinite dilution were used for the calculation. From the solubility parameters, the enthalpies of vaporization of ionic liquids were estimated. Results are compared with solubility parameters estimated by different methods. PMID:21747694

The Multiple-Choice Model: Some Solutions for Estimation of Parameters in the Presence of Omitted Responses

ERIC Educational Resources Information Center

Abad, Francisco J.; Olea, Julio; Ponsoda, Vicente

2009-01-01

This article deals with some of the problems that have hindered the application of Samejima's and Thissen and Steinberg's multiple-choice models: (a) parameter estimation difficulties owing to the large number of parameters involved, (b) parameter identifiability problems in the Thissen and Steinberg model, and (c) their treatment of omitted…

40 CFR 60.1825 - What is the minimum amount of monitoring data I must collect with my continuous parameter...

Code of Federal Regulations, 2010 CFR

2010-07-01

... monitoring data I must collect with my continuous parameter monitoring systems and is the data collection... must collect with my continuous parameter monitoring systems and is the data collection requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for...

40 CFR 60.1825 - What is the minimum amount of monitoring data I must collect with my continuous parameter...

Code of Federal Regulations, 2011 CFR

2011-07-01

... monitoring data I must collect with my continuous parameter monitoring systems and is the data collection... must collect with my continuous parameter monitoring systems and is the data collection requirement enforceable? (a) Where continuous parameter monitoring systems are used, obtain 1-hour arithmetic averages for...

Synthesis and Characterization of Liquid Crystalline Epoxy Resins

DTIC Science & Technology

2014-01-01

Temperature dependence of the four parameters in the Burgers model. ......... 81 Figure 4.7 Dependence of creep compliance on creep time at different...Kinetic parameters for LCERs. ......................................................................... 65 Table 3.4 Kinetic parameters for non-LCERs...curing in a high strength magnetic field. The orientation was quantified by an orientation parameter determined with two-dimensional X-ray diffraction

Two phase modeling of nanofluid flow in existence of melting heat transfer by means of HAM

NASA Astrophysics Data System (ADS)

Sheikholeslami, M.; Jafaryar, M.; Bateni, K.; Ganji, D. D.

2018-02-01

In this article, Buongiorno Model is applied for investigation of nanofluid flow over a stretching plate in existence of magnetic field. Radiation and Melting heat transfer are taken into account. Homotopy analysis method (HAM) is selected to solve ODEs which are obtained from similarity transformation. Roles of Brownian motion, thermophoretic parameter, Hartmann number, porosity parameter, Melting parameter and Eckert number are presented graphically. Results indicate that nanofluid velocity and concentration enhance with rise of melting parameter. Nusselt number reduces with increase of porosity and melting parameters.

A bivariate gamma probability distribution with application to gust modeling. [for the ascent flight of the space shuttle

NASA Technical Reports Server (NTRS)

Smith, O. E.; Adelfang, S. I.; Tubbs, J. D.

1982-01-01

A five-parameter gamma distribution (BGD) having two shape parameters, two location parameters, and a correlation parameter is investigated. This general BGD is expressed as a double series and as a single series of the modified Bessel function. It reduces to the known special case for equal shape parameters. Practical functions for computer evaluations for the general BGD and for special cases are presented. Applications to wind gust modeling for the ascent flight of the space shuttle are illustrated.

An AI-based approach to structural damage identification by modal analysis

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1990-01-01

Flexible-structure damage is presently addressed by a combined model- and parameter-identification approach which employs the AI methodologies of classification, heuristic search, and object-oriented model knowledge representation. The conditions for model-space search convergence to the best model are discussed in terms of search-tree organization and initial model parameter error. In the illustrative example of a truss structure presented, the use of both model and parameter identification is shown to lead to smaller parameter corrections than would be required by parameter identification alone.

Study on friction coefficient of soft soil based on particle flow code

NASA Astrophysics Data System (ADS)

Lei, Xiaohong; Zhang, Zhongwei

2017-04-01

There has no uniform method for determining the micro parameters in particle flow code, and the corresponding formulas obtained by each scholar can only be applied to similar situations. In this paper, the relationship between the micro parameters friction coefficient and macro parameters friction angle is established by using the two axis servo compression as the calibration experiment, and the corresponding formula is fitted to solve the difficulties of determining the PFC micro parameters which provide a reference for determination of the micro parameters of soft soil.

Finding Top-kappa Unexplained Activities in Video

DTIC Science & Technology

2012-03-09

parameters that define an UAP instance affect the running time by varying the values of each parameter while keeping the others fixed to a default...value. Runtime of Top-k TUA. Table 1 reports the values we considered for each parameter along with the corresponding default value. Parameter Values...Default value k 1, 2, 5, All All τ 0.4, 0.6, 0.8 0.6 L 160, 200, 240, 280 200 # worlds 7 E+04, 4 E+05, 2 E+07 2 E+07 TABLE 1: Parameter values used in

Reduction of low frequency vibration of truck driver and seating system through system parameter identification, sensitivity analysis and active control

NASA Astrophysics Data System (ADS)

Wang, Xu; Bi, Fengrong; Du, Haiping

2018-05-01

This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.

High Entropy Alloys: Criteria for Stable Structure

NASA Astrophysics Data System (ADS)

Tripathy, Snehashish; Gupta, Gaurav; Chowdhury, Sandip Ghosh

2018-01-01

An effort has been made to reassess the phase predicting capability of various thermodynamic and topological parameters across a wide range of HEA systems. These parameters are valence electron concentration, atomic mismatch ( δ), electronegativity difference (Δ χ), mixing entropy (Δ S mix), entropy of fusion (Δ S f), and mismatch entropy ( S σ ). In continuation of that, two new parameters (a) Modified Darken-Gurry parameter ( A = Sσ * χ) and (b) Modified Mismatch Entropy parameter ( B = δ* Sσ) have been designed to predict the stable crystal structure that would form in the HEA systems considered for assessment.

Vector-algebra approach to extract Denavit-Hartenberg parameters of assembled robot arms

NASA Technical Reports Server (NTRS)

Barker, L. K.

1983-01-01

The Denavit-Hartenberg parameters characterize the joint axis systems in a robot arm and, naturally, appear in the transformation matrices from one joint axis system to another. These parameters are needed in the control of robot arms and in the passage of sensor information along the arm. This paper presents a vector algebra method to determine these parameters for any assembled robot arm. The idea is to measure the location of the robot hand (or extension) for different joint angles and then use these measurements to calculate the parameters.

Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

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

Goldstein, Peter

2014-01-24

This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.

The shape parameter and its modification for defining coastal profiles

NASA Astrophysics Data System (ADS)

Türker, Umut; Kabdaşli, M. Sedat

2009-03-01

The shape parameter is important for the theoretical description of the sandy coastal profiles. This parameter has previously been defined as a function of the sediment-settling velocity. However, the settling velocity cannot be characterized over a wide range of sediment grains. This, in turn, limits the calculation of the shape parameter over a wide range. This paper provides a simpler and faster analytical equation to describe the shape parameter. The validity of the equation has been tested and compared with the previously estimated values given in both graphical and tabular forms. The results of this study indicate that the analytical solutions of the shape parameter improved the usability of profile better than graphical solutions, predicting better results both at the surf zone and offshore.

The Effect of Nondeterministic Parameters on Shock-Associated Noise Prediction Modeling

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Khavaran, Abbas

2010-01-01

Engineering applications for aircraft noise prediction contain models for physical phenomenon that enable solutions to be computed quickly. These models contain parameters that have an uncertainty not accounted for in the solution. To include uncertainty in the solution, nondeterministic computational methods are applied. Using prediction models for supersonic jet broadband shock-associated noise, fixed model parameters are replaced by probability distributions to illustrate one of these methods. The results show the impact of using nondeterministic parameters both on estimating the model output uncertainty and on the model spectral level prediction. In addition, a global sensitivity analysis is used to determine the influence of the model parameters on the output, and to identify the parameters with the least influence on model output.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

PubMed

Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

2005-06-01

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Brownian motion model with stochastic parameters for asset prices

NASA Astrophysics Data System (ADS)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

Volume-energy parameters for heat transfer to supercritical fluids

NASA Technical Reports Server (NTRS)

Kumakawa, A.; Niino, M.; Hendricks, R. C.; Giarratano, P. J.; Arp, V. D.

1986-01-01

Reduced Nusselt numbers of supercritical fluids from different sources were grouped by several volume-energy parameters. A modified bulk expansion parameter was introduced based on a comparative analysis of data scatter. Heat transfer experiments on liquefied methane were conducted under near-critical conditions in order to confirm the usefulness of the parameters. It was experimentally revealed that heat transfer characteristics of near-critical methane are similar to those of hydrogen. It was shown that the modified bulk expansion parameter and the Gibbs-energy parameter grouped the heat transfer data of hydrogen, oxygen and methane including the present data on near-critical methane. It was also indicated that the effects of surface roughness on heat transfer were very important in grouping the data of high Reynolds numbers.

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation.

PubMed

Layton, D M; Bundschuh, R

2005-01-01

Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already that for changes corresponding to the actual experimental error to which these parameters have been determined, 30% of the structure are falsely predicted whereas the ground state structure is preserved under parameter perturbation in only 5% of all the cases. We establish that base-pairing probabilities calculated in a thermal ensemble are viable although not a perfect measure for the reliability of the prediction of individual structure elements. Here, a new measure of stability using parameter perturbation is proposed, and its limitations are discussed.

Calculation of Optical Parameters of Liquid Crystals

NASA Astrophysics Data System (ADS)

Kumar, A.

2007-12-01

Validation of a modified four-parameter model describing temperature effect on liquid crystal refractive indices is being reported in the present article. This model is based upon the Vuks equation. Experimental data of ordinary and extraordinary refractive indices for two liquid crystal samples MLC-9200-000 and MLC-6608 are used to validate the above-mentioned theoretical model. Using these experimental data, birefringence, order parameter, normalized polarizabilities, and the temperature gradient of refractive indices are determined. Two methods: directly using birefringence measurements and using Haller's extrapolation procedure are adopted for the determination of order parameter. Both approches of order parameter calculation are compared. The temperature dependences of all these parameters are discussed. A close agreement between theory and experiment is obtained.

Real-Time Parameter Estimation in the Frequency Domain

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented

Testing local-realism and macro-realism under generalized dichotomic measurements

NASA Astrophysics Data System (ADS)

Das, Debarshi; Mal, Shiladitya; Home, Dipankar

2018-04-01

Generalized quantum measurements with two outcomes are fully characterized by two real parameters, dubbed as sharpness parameter and biasedness parameter and they can be linked with different aspects of the experimental setup. It is known that sharpness parameter characterizes precision of the measurements and decreasing sharpness parameter of the measurements reduces the possibility of probing quantum features like quantum mechanical (QM) violation of local-realism (LR) or macro-realism (MR). Here we investigate the effect of biasedness together with that of sharpness of measurements and find a trade-off between those two parameters in the context of probing QM violations of LR and MR. Interestingly, we also find that the above mentioned trade-off is more robust in the latter case.

Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine

2002-01-01

The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

PubMed Central

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

Chaotic processes using the two-parameter derivative with non-singular and non-local kernel: Basic theory and applications

NASA Astrophysics Data System (ADS)

Doungmo Goufo, Emile Franc

2016-08-01

After having the issues of singularity and locality addressed recently in mathematical modelling, another question regarding the description of natural phenomena was raised: How influent is the second parameter β of the two-parameter Mittag-Leffler function E α , β ( z ) , z ∈ ℂ ? To answer this question, we generalize the newly introduced one-parameter derivative with non-singular and non-local kernel [A. Atangana and I. Koca, Chaos, Solitons Fractals 89, 447 (2016); A. Atangana and D. Bealeanu (e-print)] by developing a similar two-parameter derivative with non-singular and non-local kernel based on Eα,β(z). We exploit the Agarwal/Erdelyi higher transcendental functions together with their Laplace transforms to explicitly establish the Laplace transform's expressions of the two-parameter derivatives, necessary for solving related fractional differential equations. Explicit expression of the associated two-parameter fractional integral is also established. Concrete applications are done on atmospheric convection process by using Lorenz non-linear simple system. Existence result for the model is provided and a numerical scheme established. As expected, solutions exhibit chaotic behaviors for α less than 0.55, and this chaos is not interrupted by the impact of β. Rather, this second parameter seems to indirectly squeeze and rotate the solutions, giving an impression of twisting. The whole graphics seem to have completely changed its orientation to a particular direction. This is a great observation that clearly shows the substantial impact of the second parameter of Eα,β(z), certainly opening new doors to modeling with two-parameter derivatives.

Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach.

PubMed

Fountas, Grigorios; Sarwar, Md Tawfiq; Anastasopoulos, Panagiotis Ch; Blatt, Alan; Majka, Kevin

2018-04-01

Traditional accident analysis typically explores non-time-varying (stationary) factors that affect accident occurrence on roadway segments. However, the impact of time-varying (dynamic) factors is not thoroughly investigated. This paper seeks to simultaneously identify pre-crash stationary and dynamic factors of accident occurrence, while accounting for unobserved heterogeneity. Using highly disaggregate information for the potential dynamic factors, and aggregate data for the traditional stationary elements, a dynamic binary random parameters (mixed) logit framework is employed. With this approach, the dynamic nature of weather-related, and driving- and pavement-condition information is jointly investigated with traditional roadway geometric and traffic characteristics. To additionally account for the combined effect of the dynamic and stationary factors on the accident occurrence, the developed random parameters logit framework allows for possible correlations among the random parameters. The analysis is based on crash and non-crash observations between 2011 and 2013, drawn from urban and rural highway segments in the state of Washington. The findings show that the proposed methodological framework can account for both stationary and dynamic factors affecting accident occurrence probabilities, for panel effects, for unobserved heterogeneity through the use of random parameters, and for possible correlation among the latter. The comparative evaluation among the correlated grouped random parameters, the uncorrelated random parameters logit models, and their fixed parameters logit counterpart, demonstrate the potential of the random parameters modeling, in general, and the benefits of the correlated grouped random parameters approach, specifically, in terms of statistical fit and explanatory power. Published by Elsevier Ltd.

Macular ganglion cell imaging study: glaucoma diagnostic accuracy of spectral-domain optical coherence tomography.

PubMed

Jeoung, Jin Wook; Choi, Yun Jeong; Park, Ki Ho; Kim, Dong Myung

2013-07-01

We evaluated the diagnostic accuracy of macular ganglion cell-inner plexiform layer (GCIPL) measurements using a high-definition optical coherence tomography (Cirrus HD-OCT) ganglion cell analysis algorithm for detecting early and moderate-to-severe glaucoma. Totals of 119 normal subjects and 306 glaucoma patients (164 patients with early glaucoma and 142 with moderate-to-severe glaucoma) were enrolled from the Macular Ganglion Cell Imaging Study. Macular GCIPL, peripapillary retinal nerve fiber layer (RNFL) thickness, and optic nerve head (ONH) parameters were measured in each subject. Areas under the receiver operating characteristic curves (AUROCs) were calculated and compared. Based on the internal normative database, the sensitivity and specificity for detecting early and moderate-to-severe glaucoma were calculated. There was no statistically significant difference between the AUROCs for the best OCT parameters. For detecting early glaucoma, the sensitivity of the Cirrus GCIPL parameters ranged from 26.8% to 73.2% and that of the Cirrus RNFL parameters ranged from 6.1% to 61.6%. For the early glaucoma group, the best parameter from the GCIPL generally had a higher sensitivity than those of the RNFL and ONH parameters with comparable specificity (P < 0.05, McNemar's test). There were no significant differences between the AUROCs for Cirrus GCIPL, RNFL, and ONH parameters, indicating that these maps have similar diagnostic potentials for glaucoma. The minimum GCIPL showed better glaucoma diagnostic performance than the other parameters at comparable specificities. However, other GCIPL parameters showed performances comparable to those of the RNFL parameters.

Pulsed Electromagnetic Acceleration of Plasmas

NASA Technical Reports Server (NTRS)

Thio, Y. C. Francis; Cassibry, Jason T.; Markusic, Tom E.; Rodgers, Stephen L. (Technical Monitor)

2002-01-01

A major shift in paradigm in driving pulsed plasma thruster is necessary if the original goal of accelerating a plasma sheet efficiently to high velocities as a plasma "slug" is to be realized. Firstly, the plasma interior needs to be highly collisional so that it can be dammed by the plasma edge layer not (upstream) adjacent to the driving 'vacuum' magnetic field. Secondly, the plasma edge layer needs to be strongly magnetized so that its Hall parameter is of the order of unity in this region to ensure excellent coupling of the Lorentz force to the plasma. Thirdly, to prevent and/or suppress the occurrence of secondary arcs or restrike behind the plasma, the region behind the plasma needs to be collisionless and extremely magnetized with sufficiently large Hall parameter. This places a vacuum requirement on the bore conditions prior to the shot. These requirements are quantified in the paper and lead to the introduction of three new design parameters corresponding to these three plasma requirements. The first parameter, labeled in the paper as gamma (sub 1), pertains to the permissible ratio of the diffusive excursion of the plasma during the course of the acceleration to the plasma longitudinal dimension. The second parameter is the required Hall parameter of the edge plasma region, and the third parameter the required Hall parameter of the region behind the plasma. Experimental research is required to quantify the values of these design parameters. Based upon fundamental theory of the transport processes in plasma, some theoretical guidance on the choice of these parameters are provided to help designing the necessary experiments to acquire these data.

A Sensitivity Analysis of an Inverted Pendulum Balance Control Model.

PubMed

Pasma, Jantsje H; Boonstra, Tjitske A; van Kordelaar, Joost; Spyropoulou, Vasiliki V; Schouten, Alfred C

2017-01-01

Balance control models are used to describe balance behavior in health and disease. We identified the unique contribution and relative importance of each parameter of a commonly used balance control model, the Independent Channel (IC) model, to identify which parameters are crucial to describe balance behavior. The balance behavior was expressed by transfer functions (TFs), representing the relationship between sensory perturbations and body sway as a function of frequency, in terms of amplitude (i.e., magnitude) and timing (i.e., phase). The model included an inverted pendulum controlled by a neuromuscular system, described by several parameters. Local sensitivity of each parameter was determined for both the magnitude and phase using partial derivatives. Both the intrinsic stiffness and proportional gain shape the magnitude at low frequencies (0.1-1 Hz). The derivative gain shapes the peak and slope of the magnitude between 0.5 and 0.9 Hz. The sensory weight influences the overall magnitude, and does not have any effect on the phase. The effect of the time delay becomes apparent in the phase above 0.6 Hz. The force feedback parameters and intrinsic stiffness have a small effect compared with the other parameters. All parameters shape the TF magnitude and phase and therefore play a role in the balance behavior. The sensory weight, time delay, derivative gain, and the proportional gain have a unique effect on the TFs, while the force feedback parameters and intrinsic stiffness contribute less. More insight in the unique contribution and relative importance of all parameters shows which parameters are crucial and critical to identify underlying differences in balance behavior between different patient groups.

Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

PubMed Central

Liebermeister, Wolfram; Klipp, Edda

2006-01-01

Background Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. Results We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. Conclusion Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases. PMID:17173669

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

NASA Astrophysics Data System (ADS)

Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten

2007-06-01

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

DOE PAGES

Qian, Yun; Yan, Huiping; Hou, Zhangshuan; ...

2015-04-10

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less

From global to local: exploring the relationship between parameters and behaviors in models of electrical excitability.

PubMed

Fletcher, Patrick; Bertram, Richard; Tabak, Joel

2016-06-01

Models of electrical activity in excitable cells involve nonlinear interactions between many ionic currents. Changing parameters in these models can produce a variety of activity patterns with sometimes unexpected effects. Further more, introducing new currents will have different effects depending on the initial parameter set. In this study we combined global sampling of parameter space and local analysis of representative parameter sets in a pituitary cell model to understand the effects of adding K (+) conductances, which mediate some effects of hormone action on these cells. Global sampling ensured that the effects of introducing K (+) conductances were captured across a wide variety of contexts of model parameters. For each type of K (+) conductance we determined the types of behavioral transition that it evoked. Some transitions were counterintuitive, and may have been missed without the use of global sampling. In general, the wide range of transitions that occurred when the same current was applied to the model cell at different locations in parameter space highlight the challenge of making accurate model predictions in light of cell-to-cell heterogeneity. Finally, we used bifurcation analysis and fast/slow analysis to investigate why specific transitions occur in representative individual models. This approach relies on the use of a graphics processing unit (GPU) to quickly map parameter space to model behavior and identify parameter sets for further analysis. Acceleration with modern low-cost GPUs is particularly well suited to exploring the moderate-sized (5-20) parameter spaces of excitable cell and signaling models.

The on-orbit calibration of geometric parameters of the Tian-Hui 1 (TH-1) satellite

NASA Astrophysics Data System (ADS)

Wang, Jianrong; Wang, Renxiang; Hu, Xin; Su, Zhongbo

2017-02-01

The on-orbit calibration of geometric parameters is a key step in improving the location accuracy of satellite images without using Ground Control Points (GCPs). Most methods of on-orbit calibration are based on the self-calibration using additional parameters. When using additional parameters, different number of additional parameters may lead to different results. The triangulation bundle adjustment is another way to calibrate the geometric parameters of camera, which can describe the changes in each geometric parameter. When triangulation bundle adjustment method is applied to calibrate geometric parameters, a prerequisite is that the strip model can avoid systematic deformation caused by the rate of attitude changes. Concerning the stereo camera, the influence of the intersection angle should be considered during calibration. The Equivalent Frame Photo (EFP) bundle adjustment based on the Line-Matrix CCD (LMCCD) image can solve the systematic distortion of the strip model, and obtain high accuracy location without using GCPs. In this paper, the triangulation bundle adjustment is used to calibrate the geometric parameters of TH-1 satellite cameras based on LMCCD image. During the bundle adjustment, the three-line array cameras are reconstructed by adopting the principle of inverse triangulation. Finally, the geometric accuracy is validated before and after on-orbit calibration using 5 testing fields. After on-orbit calibration, the 3D geometric accuracy is improved to 11.8 m from 170 m. The results show that the location accuracy of TH-1 without using GCPs is significantly improved using the on-orbit calibration of the geometric parameters.

Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation

PubMed Central

Hall, Sheldon K.; Ooi, Ean H.; Payne, Stephen J.

2015-01-01

Abstract Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understanding the role of uncertainty and when comparing the model predictions to experimental data. Materials and methods: The Morris method was chosen to perform the sensitivity analysis because it is ideal for models with many parameters or that take a significant length of time to obtain solutions. A comprehensive literature review was performed to obtain ranges over which the model parameters are expected to vary, crucial input information. Results: The most important parameters in predicting the ablation zone size in our model of RFA are those representing the blood perfusion, electrical conductivity and the cell death model. The size of the 50 °C isotherm is sensitive to the electrical properties of tissue while the heat source is active, and to the thermal parameters during cooling. Conclusions: The parameter ranges chosen for the sensitivity analysis are believed to represent all that is currently known about their values in combination. The Morris method is able to compute global parameter sensitivities taking into account the interaction of all parameters, something that has not been done before. Research is needed to better understand the uncertainties in the cell death, electrical conductivity and perfusion models, but the other parameters are only of second order, providing a significant simplification. PMID:26000972

Relationships and redundancies of selected hemodynamic and structural parameters for characterizing virtual treatment of cerebral aneurysms with flow diverter devices.

PubMed

Karmonik, C; Anderson, J R; Beilner, J; Ge, J J; Partovi, S; Klucznik, R P; Diaz, O; Zhang, Y J; Britz, G W; Grossman, R G; Lv, N; Huang, Q

2016-07-26

To quantify the relationship and to demonstrate redundancies between hemodynamic and structural parameters before and after virtual treatment with a flow diverter device (FDD) in cerebral aneurysms. Steady computational fluid dynamics (CFD) simulations were performed for 10 cerebral aneurysms where FDD treatment with the SILK device was simulated by virtually reducing the porosity at the aneurysm ostium. Velocity and pressure values proximal and distal to and at the aneurysm ostium as well as inside the aneurysm were quantified. In addition, dome-to-neck ratios and size ratios were determined. Multiple correlation analysis (MCA) and hierarchical cluster analysis (HCA) were conducted to demonstrate dependencies between both structural and hemodynamic parameters. Velocities in the aneurysm were reduced by 0.14m/s on average and correlated significantly (p<0.05) with velocity values in the parent artery (average correlation coefficient: 0.70). Pressure changes in the aneurysm correlated significantly with pressure values in the parent artery and aneurysm (average correlation coefficient: 0.87). MCA found statistically significant correlations between velocity values and between pressure values, respectively. HCA sorted velocity parameters, pressure parameters and structural parameters into different hierarchical clusters. HCA of aneurysms based on the parameter values yielded similar results by either including all (n=22) or only non-redundant parameters (n=2, 3 and 4). Hemodynamic and structural parameters before and after virtual FDD treatment show strong inter-correlations. Redundancy of parameters was demonstrated with hierarchical cluster analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Chaotic processes using the two-parameter derivative with non-singular and non-local kernel: Basic theory and applications.

PubMed

Doungmo Goufo, Emile Franc

2016-08-01

After having the issues of singularity and locality addressed recently in mathematical modelling, another question regarding the description of natural phenomena was raised: How influent is the second parameter β of the two-parameter Mittag-Leffler function Eα,β(z), z∈ℂ? To answer this question, we generalize the newly introduced one-parameter derivative with non-singular and non-local kernel [A. Atangana and I. Koca, Chaos, Solitons Fractals 89, 447 (2016); A. Atangana and D. Bealeanu (e-print)] by developing a similar two-parameter derivative with non-singular and non-local kernel based on Eα , β(z). We exploit the Agarwal/Erdelyi higher transcendental functions together with their Laplace transforms to explicitly establish the Laplace transform's expressions of the two-parameter derivatives, necessary for solving related fractional differential equations. Explicit expression of the associated two-parameter fractional integral is also established. Concrete applications are done on atmospheric convection process by using Lorenz non-linear simple system. Existence result for the model is provided and a numerical scheme established. As expected, solutions exhibit chaotic behaviors for α less than 0.55, and this chaos is not interrupted by the impact of β. Rather, this second parameter seems to indirectly squeeze and rotate the solutions, giving an impression of twisting. The whole graphics seem to have completely changed its orientation to a particular direction. This is a great observation that clearly shows the substantial impact of the second parameter of Eα , β(z), certainly opening new doors to modeling with two-parameter derivatives.

Parameter Analysis of the VPIN (Volume synchronized Probability of Informed Trading) Metric

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

Song, Jung Heon; Wu, Kesheng; Simon, Horst D.

2014-03-01

VPIN (Volume synchronized Probability of Informed trading) is a leading indicator of liquidity-induced volatility. It is best known for having produced a signal more than hours before the Flash Crash of 2010. On that day, the market saw the biggest one-day point decline in the Dow Jones Industrial Average, which culminated to the market value of $1 trillion disappearing, but only to recover those losses twenty minutes later (Lauricella 2010). The computation of VPIN requires the user to set up a handful of free parameters. The values of these parameters significantly affect the effectiveness of VPIN as measured by themore » false positive rate (FPR). An earlier publication reported that a brute-force search of simple parameter combinations yielded a number of parameter combinations with FPR of 7%. This work is a systematic attempt to find an optimal parameter set using an optimization package, NOMAD (Nonlinear Optimization by Mesh Adaptive Direct Search) by Audet, le digabel, and tribes (2009) and le digabel (2011). We have implemented a number of techniques to reduce the computation time with NOMAD. Tests show that we can reduce the FPR to only 2%. To better understand the parameter choices, we have conducted a series of sensitivity analysis via uncertainty quantification on the parameter spaces using UQTK (Uncertainty Quantification Toolkit). Results have shown dominance of 2 parameters in the computation of FPR. Using the outputs from NOMAD optimization and sensitivity analysis, We recommend A range of values for each of the free parameters that perform well on a large set of futures trading records.« less

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

USGS Publications Warehouse

Hill, Mary Catherine

1992-01-01

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

A Quadriparametric Model to Describe the Diversity of Waves Applied to Hormonal Data.

PubMed

Abdullah, Saman; Bouchard, Thomas; Klich, Amna; Leiva, Rene; Pyper, Cecilia; Genolini, Christophe; Subtil, Fabien; Iwaz, Jean; Ecochard, René

2018-05-01

Even in normally cycling women, hormone level shapes may widely vary between cycles and between women. Over decades, finding ways to characterize and compare cycle hormone waves was difficult and most solutions, in particular polynomials or splines, do not correspond to physiologically meaningful parameters. We present an original concept to characterize most hormone waves with only two parameters. The modelling attempt considered pregnanediol-3-alpha-glucuronide (PDG) and luteinising hormone (LH) levels in 266 cycles (with ultrasound-identified ovulation day) in 99 normally fertile women aged 18 to 45. The study searched for a convenient wave description process and carried out an extended search for the best fitting density distribution. The highly flexible beta-binomial distribution offered the best fit of most hormone waves and required only two readily available and understandable wave parameters: location and scale. In bell-shaped waves (e.g., PDG curves), early peaks may be fitted with a low location parameter and a low scale parameter; plateau shapes are obtained with higher scale parameters. I-shaped, J-shaped, and U-shaped waves (sometimes the shapes of LH curves) may be fitted with high scale parameter and, respectively, low, high, and medium location parameter. These location and scale parameters will be later correlated with feminine physiological events. Our results demonstrate that, with unimodal waves, complex methods (e.g., functional mixed effects models using smoothing splines, second-order growth mixture models, or functional principal-component- based methods) may be avoided. The use, application, and, especially, result interpretation of four-parameter analyses might be advantageous within the context of feminine physiological events. Schattauer GmbH.

Comparison of petroleum generation kinetics by isothermal hydrous and nonisothermal open-system pyrolysis

USGS Publications Warehouse

Lewan, M.D.; Ruble, T.E.

2002-01-01

This study compares kinetic parameters determined by open-system pyrolysis and hydrous pyrolysis using aliquots of source rocks containing different kerogen types. Kinetic parameters derived from these two pyrolysis methods not only differ in the conditions employed and products generated, but also in the derivation of the kinetic parameters (i.e., isothermal linear regression and non-isothermal nonlinear regression). Results of this comparative study show that there is no correlation between kinetic parameters derived from hydrous pyrolysis and open-system pyrolysis. Hydrous-pyrolysis kinetic parameters determine narrow oil windows that occur over a wide range of temperatures and depths depending in part on the organic-sulfur content of the original kerogen. Conversely, open-system kinetic parameters determine broad oil windows that show no significant differences with kerogen types or their organic-sulfur contents. Comparisons of the kinetic parameters in a hypothetical thermal-burial history (2.5 ??C/my) show open-system kinetic parameters significantly underestimate the extent and timing of oil generation for Type-US kerogen and significantly overestimate the extent and timing of petroleum formation for Type-I kerogen compared to hydrous pyrolysis kinetic parameters. These hypothetical differences determined by the kinetic parameters are supported by natural thermal-burial histories for the Naokelekan source rock (Type-IIS kerogen) in the Zagros basin of Iraq and for the Green River Formation (Type-I kerogen) in the Uinta basin of Utah. Differences in extent and timing of oil generation determined by open-system pyrolysis and hydrous pyrolysis can be attributed to the former not adequately simulating natural oil generation conditions, products, and mechanisms.

Time- and frequency-domain parameters of heart rate variability and sympathetic skin response in Parkinson's disease.

PubMed

Maetzler, Walter; Karam, Marie; Berger, Monika Fruhmann; Heger, Tanja; Maetzler, Corina; Ruediger, Heinz; Bronzova, Juliana; Lobo, Patricia Pita; Ferreira, Joaquim J; Ziemssen, Tjalf; Berg, Daniela

2015-03-01

The autonomic nervous system (ANS) is regularly affected in Parkinson's disease (PD). Information on autonomic dysfunction can be derived from e.g. altered heart rate variability (HRV) and sympathetic skin response (SSR). Such parameters can be quantified easily and measured repeatedly which might be helpful for evaluating disease progression and therapeutic outcome. In this 2-center study, HRV and SSR of 45 PD patients and 26 controls were recorded. HRV was measured during supine metronomic breathing and analyzed in time- and frequency-domains. SSR was evoked by repetitive auditory stimulation. Various ANS parameters were compared (1) between patients and healthy controls, (2) to clinical scales (Unified Parkinson's disease rating scale, Mini-Mental State Examination, Becks Depression Inventory), and (3) to disease duration. Root mean square of successive differences (RMSSD) and low frequency/high frequency (LF/HF) ratio differed significantly between PD and controls. Both, HRV and SSR parameters showed low or no association with clinical scores. Time-domain parameters tended to be affected already at early PD stages but did not consistently change with longer disease duration. In contrast, frequency-domain parameters were not altered in early PD phases but tended to be lower (LF, LF/HF ratio), respectively higher (HF) with increasing disease duration. This report confirms previous results of altered ANS parameters in PD. In addition, it suggests that (1) these ANS parameters are not relevantly associated with motor, behavioral, and cognitive changes in PD, (2) time-domain parameters are useful for the assessment of early PD, and (3) frequency-domain parameters are more closely associated with disease duration.

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

GGOS and the EOP - the key role of SLR for a stable estimation of highly accurate Earth orientation parameters

NASA Astrophysics Data System (ADS)

Bloßfeld, Mathis; Panzetta, Francesca; Müller, Horst; Gerstl, Michael

2016-04-01

The GGOS vision is to integrate geometric and gravimetric observation techniques to estimate consistent geodetic-geophysical parameters. In order to reach this goal, the common estimation of station coordinates, Stokes coefficients and Earth Orientation Parameters (EOP) is necessary. Satellite Laser Ranging (SLR) provides the ability to study correlations between the different parameter groups since the observed satellite orbit dynamics are sensitive to the above mentioned geodetic parameters. To decrease the correlations, SLR observations to multiple satellites have to be combined. In this paper, we compare the estimated EOP of (i) single satellite SLR solutions and (ii) multi-satellite SLR solutions. Therefore, we jointly estimate station coordinates, EOP, Stokes coefficients and orbit parameters using different satellite constellations. A special focus in this investigation is put on the de-correlation of different geodetic parameter groups due to the combination of SLR observations. Besides SLR observations to spherical satellites (commonly used), we discuss the impact of SLR observations to non-spherical satellites such as, e.g., the JASON-2 satellite. The goal of this study is to discuss the existing parameter interactions and to present a strategy how to obtain reliable estimates of station coordinates, EOP, orbit parameter and Stokes coefficients in one common adjustment. Thereby, the benefits of a multi-satellite SLR solution are evaluated.

Determination techniques of Archie’s parameters: a, m and n in heterogeneous reservoirs

NASA Astrophysics Data System (ADS)

Mohamad, A. M.; Hamada, G. M.

2017-12-01

The determination of water saturation in a heterogeneous reservoir is becoming more challenging, as Archie’s equation is only suitable for clean homogeneous formation and Archie’s parameters are highly dependent on the properties of the rock. This study focuses on the measurement of Archie’s parameters in carbonate and sandstone core samples around Malaysian heterogeneous carbonate and sandstone reservoirs. Three techniques for the determination of Archie’s parameters a, m and n will be implemented: the conventional technique, core Archie parameter estimation (CAPE) and the three-dimensional regression technique (3D). By using the results obtained by the three different techniques, water saturation graphs were produced to observe the symbolic difference of Archie’s parameter and its relevant impact on water saturation values. The difference in water saturation values can be primarily attributed to showing the uncertainty level of Archie’s parameters, mainly in carbonate and sandstone rock samples. It is obvious that the accuracy of Archie’s parameters has a profound impact on the calculated water saturation values in carbonate sandstone reservoirs due to regions of high stress reducing electrical conduction resulting from the raised electrical heterogeneity of the heterogeneous carbonate core samples. Due to the unrealistic assumptions involved in the conventional method, it is better to use either the CAPE or 3D method to accurately determine Archie’s parameters in heterogeneous as well as homogeneous reservoirs.

Observational constraint on spherical inhomogeneity with CMB and local Hubble parameter

NASA Astrophysics Data System (ADS)

Tokutake, Masato; Ichiki, Kiyotomo; Yoo, Chul-Moon

2018-03-01

We derive an observational constraint on a spherical inhomogeneity of the void centered at our position from the angular power spectrum of the cosmic microwave background (CMB) and local measurements of the Hubble parameter. The late time behaviour of the void is assumed to be well described by the so-called Λ-Lemaȋtre-Tolman-Bondi (ΛLTB) solution. Then, we restrict the models to the asymptotically homogeneous models each of which is approximated by a flat Friedmann-Lemaȋtre-Robertson-Walker model. The late time ΛLTB models are parametrized by four parameters including the value of the cosmological constant and the local Hubble parameter. The other two parameters are used to parametrize the observed distance-redshift relation. Then, the ΛLTB models are constructed so that they are compatible with the given distance-redshift relation. Including conventional parameters for the CMB analysis, we characterize our models by seven parameters in total. The local Hubble measurements are reflected in the prior distribution of the local Hubble parameter. As a result of a Markov-Chains-Monte-Carlo analysis for the CMB temperature and polarization anisotropies, we found that the inhomogeneous universe models with vanishing cosmological constant are ruled out as is expected. However, a significant under-density around us is still compatible with the angular power spectrum of CMB and the local Hubble parameter.

An Improved Interferometric Calibration Method Based on Independent Parameter Decomposition

NASA Astrophysics Data System (ADS)

Fan, J.; Zuo, X.; Li, T.; Chen, Q.; Geng, X.

2018-04-01

Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM). The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs). However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD). Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

Correlations between skin hydration parameters and corneocyte-derived parameters to characterize skin conditions.

PubMed

Masaki, Hitoshi; Yamashita, Yuki; Kyotani, Daiki; Honda, Tatsuya; Takano, Kenichi; Tamura, Toshiyasu; Mizutani, Taeko; Okano, Yuri

2018-03-30

Skin hydration is generally assessed using the parameters of skin surface water content (SWC) and trans-epidermal water loss (TEWL). To date, few studies have characterized skin conditions using correlations between skin hydration parameters and corneocyte parameters. The parameters SWC and TEWL allow the classification of skin conditions into four distinct Groups. The purpose of this study was to assess the characteristics of skin conditions classified by SWC and TEWL for correlations with parameters from corneocytes. A human volunteer test was conducted that measured SWC and TEWL. As corneocyte-derived parameters, the size and thick abrasion ratios, the ratio of sulfhydryl groups and disulfide bonds (SH/SS) and CP levels were analyzed. Volunteers were classified by their median SWC and TEWL values into 4 Groups: Group I (high SWC/low TEWL), Group II (high SWC/high TEWL), Group III (low SWC/low TEWL), and Group IV (low SWC/high TEWL). Group IV showed a significantly smaller size of corneocytes. Groups III and IV had significantly higher thick abrasion ratios and CP levels. Group I had a significantly lower SH/SS value. The SWC/TEWL value showed a decline in order from Group I to Group IV. Groups classified by their SWC and TEWL values showed characteristic skin conditions. We propose that the SWC and TEWL ratio is a comprehensive parameter to assess skin conditions. © 2018 Wiley Periodicals, Inc.

Usefulness and diagnostic value of the NEMA parameter combined with other selected bedside tests for prediction of difficult intubation.

PubMed

Torres, Kamil; Błoński, Marcin; Pietrzyk, Łukasz; Piasecka-Twaróg, Małgorzata; Maciejewski, Ryszard; Torres, Anna

2017-02-01

To assess the usefulness of the new NEMA (Neck Circumference Minus Acromion-Acromion Distance) parameter, in preoperative identification of patients' difficult intubation and compare it with other commonly used scales and tests. Prospective study. District Specialist Hospital of Lublin, Poland. Six hundreds twenty-nine patients underwent nonemergency surgical interventions. The NEMA parameter was confronted with: Modified Mallampati classification, TMD, RHTMD, NC, MPND, SMD, I-I D, A-AD, and medical history of difficult intubation and diagnosed obstructive sleep apnea syndrome or snoring. Higher medians of NEMA and Mallampati parameters were reported in patients with difficult intubation. AUC for Mallampati parameter was 0.733 while the NEMA parameter's AUC was 0.625. Sensitivity and specificity for Mallampati and NEMA parameter were respectively 0.79; 0.55 and 0.42; 0.75. Significantly higher MPN, RHTMD, Mallampati, and NEMA parameter were observed in patients in whom the BURP was used. Easy intubation occurs more frequently in patients with a history of OSAS or snoring than in those with difficult intubation. It seems that none of the known bedside tests for predicting difficult intubation have a discriminating power sufficient for clinicians. Our study draws attention to a novel parameter, called NEMA, which appears to be a strong predictor of DEI, especially in combination with the Mallampati scale. Copyright © 2016 Elsevier Inc. All rights reserved.

Accuracy Estimation and Parameter Advising for Protein Multiple Sequence Alignment

PubMed Central

DeBlasio, Dan

2013-01-01

Abstract We develop a novel and general approach to estimating the accuracy of multiple sequence alignments without knowledge of a reference alignment, and use our approach to address a new task that we call parameter advising: the problem of choosing values for alignment scoring function parameters from a given set of choices to maximize the accuracy of a computed alignment. For protein alignments, we consider twelve independent features that contribute to a quality alignment. An accuracy estimator is learned that is a polynomial function of these features; its coefficients are determined by minimizing its error with respect to true accuracy using mathematical optimization. Compared to prior approaches for estimating accuracy, our new approach (a) introduces novel feature functions that measure nonlocal properties of an alignment yet are fast to evaluate, (b) considers more general classes of estimators beyond linear combinations of features, and (c) develops new regression formulations for learning an estimator from examples; in addition, for parameter advising, we (d) determine the optimal parameter set of a given cardinality, which specifies the best parameter values from which to choose. Our estimator, which we call Facet (for “feature-based accuracy estimator”), yields a parameter advisor that on the hardest benchmarks provides more than a 27% improvement in accuracy over the best default parameter choice, and for parameter advising significantly outperforms the best prior approaches to assessing alignment quality. PMID:23489379

Soret and Dufour effects on thermohaline convection in rotating fluids

NASA Astrophysics Data System (ADS)

Duba, C. T.; Shekar, M.; Narayana, M.; Sibanda, P.

2016-07-01

Using linear and weakly nonlinear stability theory, the effects of Soret and Dufour parameters are investigated on thermohaline convection in a horizontal layer of rotating fluid, specifically the ocean. Thermohaline circulation is important in mixing processes and contributes to heat and mass transports and hence the earth's climate. A general conception is that due to the smallness of the Soret and Dufour parameters their effect is negligible. However, it is shown here that the Soret parameter, salinity and rotation stabilise the system, whereas temperature destabilises it and the Dufour parameter has minimal effect on stationary convection. For oscillatory convection, the analysis is difficult as it shows that the Rayleigh number depends on six parameters, the Soret and Dufour parameters, the salinity Rayleigh number, the Lewis number, the Prandtl number, and the Taylor number. We demonstrate the interplay between these parameters and their effects on oscillatory convection in a graphical manner. Furthermore, we find that the Soret parameter enhances oscillatory convection whereas the Dufour parameter, salinity Rayleigh number, the Lewis number, and rotation delay instability. We believe that these results have not been elucidated in this way before for large-scale fluids. Furthermore, we investigate weakly nonlinear stability and the effect of cross diffusive terms on heat and mass transports. We show the existence of new solution bifurcations not previously identified in literature.

Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

PubMed Central

Parida, Arun Kumar; Routara, Bharat Chandra

2014-01-01

Taguchi's design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (R a). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v 3-f 2-d 3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v 1-f 1-d 3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach. PMID:27437503

Investigation of uncertainty in CO 2 reservoir models: A sensitivity analysis of relative permeability parameter values

DOE PAGES

Yoshida, Nozomu; Levine, Jonathan S.; Stauffer, Philip H.

2016-03-22

Numerical reservoir models of CO 2 injection in saline formations rely on parameterization of laboratory-measured pore-scale processes. Here, we have performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO 2 injected using the finite element heat and mass-transfer code (FEHM) numerical reservoir simulator. Experimentally measured relative permeability parameter values were used to generate distribution functions for parameter sampling. The parameter sensitivity study analyzed five different levels for each of the relative permeability model parameters. All but one of the parameters changed the CO 2 injectivity by <10%, less than the geostatistical uncertainty that applies to all large subsurface systems due to natural geophysical variability and inherently small sample sizes. The exception was the end-point CO 2 relative permeability, kmore » $$0\\atop{r}$$ CO2, the maximum attainable effective CO 2 permeability during CO 2 invasion, which changed CO2 injectivity by as much as 80%. Similarly, Monte Carlo simulation using 1000 realizations of relative permeability parameters showed no relationship between CO 2 injectivity and any of the parameters but k$$0\\atop{r}$$ CO2, which had a very strong (R 2 = 0.9685) power law relationship with total CO 2 injected. Model sensitivity to k$$0\\atop{r}$$ CO2 points to the importance of accurate core flood and wettability measurements.« less

Investigation of uncertainty in CO 2 reservoir models: A sensitivity analysis of relative permeability parameter values

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

Yoshida, Nozomu; Levine, Jonathan S.; Stauffer, Philip H.

Numerical reservoir models of CO 2 injection in saline formations rely on parameterization of laboratory-measured pore-scale processes. Here, we have performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO 2 injected using the finite element heat and mass-transfer code (FEHM) numerical reservoir simulator. Experimentally measured relative permeability parameter values were used to generate distribution functions for parameter sampling. The parameter sensitivity study analyzed five different levels for each of the relative permeability model parameters. All but one of the parameters changed the CO 2 injectivity by <10%, less than the geostatistical uncertainty that applies to all large subsurface systems due to natural geophysical variability and inherently small sample sizes. The exception was the end-point CO 2 relative permeability, kmore » $$0\\atop{r}$$ CO2, the maximum attainable effective CO 2 permeability during CO 2 invasion, which changed CO2 injectivity by as much as 80%. Similarly, Monte Carlo simulation using 1000 realizations of relative permeability parameters showed no relationship between CO 2 injectivity and any of the parameters but k$$0\\atop{r}$$ CO2, which had a very strong (R 2 = 0.9685) power law relationship with total CO 2 injected. Model sensitivity to k$$0\\atop{r}$$ CO2 points to the importance of accurate core flood and wettability measurements.« less

Emulating Simulations of Cosmic Dawn for 21 cm Power Spectrum Constraints on Cosmology, Reionization, and X-Ray Heating

NASA Astrophysics Data System (ADS)

Kern, Nicholas S.; Liu, Adrian; Parsons, Aaron R.; Mesinger, Andrei; Greig, Bradley

2017-10-01

Current and upcoming radio interferometric experiments are aiming to make a statistical characterization of the high-redshift 21 cm fluctuation signal spanning the hydrogen reionization and X-ray heating epochs of the universe. However, connecting 21 cm statistics to the underlying physical parameters is complicated by the theoretical challenge of modeling the relevant physics at computational speeds quick enough to enable exploration of the high-dimensional and weakly constrained parameter space. In this work, we use machine learning algorithms to build a fast emulator that can accurately mimic an expensive simulation of the 21 cm signal across a wide parameter space. We embed our emulator within a Markov Chain Monte Carlo framework in order to perform Bayesian parameter constraints over a large number of model parameters, including those that govern the Epoch of Reionization, the Epoch of X-ray Heating, and cosmology. As a worked example, we use our emulator to present an updated parameter constraint forecast for the Hydrogen Epoch of Reionization Array experiment, showing that its characterization of a fiducial 21 cm power spectrum will considerably narrow the allowed parameter space of reionization and heating parameters, and could help strengthen Planck's constraints on {σ }8. We provide both our generalized emulator code and its implementation specifically for 21 cm parameter constraints as publicly available software.