Sample records for nanocrystallite based models

  1. Endo-Fullerene and Doped Diamond Nanocrystallite Based Models of Qubits for Solid-State Quantum Computers

    NASA Technical Reports Server (NTRS)

    Park, Seongjun; Srivastava, Deepak; Cho, Kyeongjae; Biegel, Bryan (Technical Monitor)

    2001-01-01

    Models of encapsulated 1/2 nuclear spin H-1 and P-31 atoms in fullerene and diamond nanocrystallite, respectively, are proposed and examined with ab-initio local density functional method for possible applications as single quantum bits (qubits) in solid-state quantum computers. A H-1 atom encapsulated in a fully deuterated fullerene, C(sub 20)D(sub 20), forms the first model system and ab-initio calculation shows that H-1 atom is stable in atomic state at the center of the fullerene with a barrier of about 1 eV to escape. A P-31 atom positioned at the center of a diamond nanocrystallite is the second model system, and 3 1P atom is found to be stable at the substitutional site relative to interstitial sites by 15 eV, Vacancy formation energy is 6 eV in diamond so that substitutional P-31 atom will be stable against diffusion during the formation mechanisms within the nanocrystallite. The coupling between the nuclear spin and weakly bound (valance) donor electron coupling in both systems is found to be suitable for single qubit applications, where as the spatial distributions of (valance) donor electron wave functions are found to be preferentially spread along certain lattice directions facilitating two or more qubit applications. The feasibility of the fabrication pathways for both model solid-state qubit systems within practical quantum computers is discussed with in the context of our proposed solid-state qubits.

  2. Endo-Fullerenes and Doped Diamond Nanocrystallite Based Solid-State Qubits

    NASA Technical Reports Server (NTRS)

    Park, Seongjun; Srivastava, Deepak; Cho, K.

    2001-01-01

    This viewgraph presentation provides information on the use of endo-fullerenes and doped diamond nanocrystallites in the development of a solid state quantum computer. Arrays of qubits, which have 1/2 nuclear spin, are more easily fabricated than arrays of similar bare atoms. H-1 can be encapsulated in a C20D20 fullerene, while P-31 can be encapsulated in a diamond nanocrystallite.

  3. Modeling of Disordered Binary Alloys Under Thermal Forcing: Effect of Nanocrystallite Dissociation on Thermal Expansion of AuCu3

    NASA Astrophysics Data System (ADS)

    Kim, Y. W.; Cress, R. P.

    2016-11-01

    Disordered binary alloys are modeled as a randomly close-packed assembly of nanocrystallites intermixed with randomly positioned atoms, i.e., glassy-state matter. The nanocrystallite size distribution is measured in a simulated macroscopic medium in two dimensions. We have also defined, and measured, the degree of crystallinity as the probability of a particle being a member of nanocrystallites. Both the distribution function and the degree of crystallinity are found to be determined by alloy composition. When heated, the nanocrystallites become smaller in size due to increasing thermal fluctuation. We have modeled this phenomenon as a case of thermal dissociation by means of the law of mass action. The crystallite size distribution function is computed for AuCu3 as a function of temperature by solving some 12 000 coupled algebraic equations for the alloy. The results show that linear thermal expansion of the specimen has contributions from the temperature dependence of the degree of crystallinity, in addition to respective thermal expansions of the nanocrystallites and glassy-state matter.

  4. A photodiode based on PbS nanocrystallites for FYTRONIX solar panel automatic tracking controller

    NASA Astrophysics Data System (ADS)

    Wageh, S.; Farooq, W. A.; Tataroğlu, A.; Dere, A.; Al-Sehemi, Abdullah G.; Al-Ghamdi, Ahmed A.; Yakuphanoglu, F.

    2017-12-01

    The structural, optical and photoelectrical properties of the fabricated Al/PbS/p-Si/Al photodiode based on PbS nanocrystallites were investigated. The PbS nanocrystallites were characterized by X-ray diffraction (XRD), UV-VIS-NIR, Infrared and Raman spectroscopy. The XRD diffraction peaks show that the prepared PbS nanostructure is in high crystalline state. Various electrical parameters of the prepared photodiode were analyzed from the electrical characteristics based on I-V and C-V-G. The photodiode has a high rectification ratio of 5.85×104 at dark and ±4 V. Moreover, The photocurrent results indicate a strong photovoltaic behavior. The frequency dependence of capacitance and conductance characteristics was attributed to depletion region behavior of the photodiode. The diode was used to control solar panel power automatic tracking controller in dual axis. The fabricated photodiode works as a photosensor to control Solar tracking systems.

  5. Thermal Behaviour of Nanocomposites based on Glycerol Plasticized Thermoplastic Starch and Cellulose Nanocrystallites

    NASA Astrophysics Data System (ADS)

    Kaushik, Anupama; Kaur, Ramanpreet

    2011-12-01

    The objective of this study was to study the thermal behaviour of cellulose nanocrystals/TPS based nanocomposites. Nanocrystalline cellulose was isolated from cotton linters using sonochemical method and characterized through WAXRD & TEM. These nanocrystals were then dispersed in glycerol plasticized starch in varying proportions and films were cast. The thermal degradation of thermoplastic starch/cellulose nanocrystallite nanocomposites was studied using TGA under nitrogen atmosphere. Thermal degradation was carried out for nanocomposites at a rate of 10 °C/min and at different rates under nitrogen atmosphere namely 2, 5, 10, 20 and 40 °C/min for nanocomposites containing 10% cellulose nanocrystals. Ozawa and Flynn and Kissinger methods were used to determine the apparent activation energy of these nanocomposites. The addition of cellulose nanocrystallites produced a significant effect on the activation energy for thermal degradation of the composites materials in comparison with the matrix alone. These nanocomposites are potential applicant for food packaging applications.

  6. Defect and adsorbate induced ferromagnetic spin-order in magnesium oxide nanocrystallites

    NASA Astrophysics Data System (ADS)

    Kumar, Ashok; Kumar, Jitendra; Priya, Shashank

    2012-05-01

    We report the correlation between d0 ferromagnetism, photoluminescence (PL), and adsorbed hydrogen (H-) species in magnesium oxide (MgO) nanocrystallites. Our study suggests that the oxygen vacancies, namely singly ionized anionic vacancies (F+) and dimers (F22+) induce characteristic photoluminescence and the room-temperature ferromagnetic spin-order. Nanocrystallites with low population of oxygen vacancies have revealed diamagnetic behavior. Intriguingly, on adsorption of hydrogen (H-) species in the MgO nanocrystallites, ferromagnetic behavior was either enhanced (in the case of highly oxygen deficient nanocrystallites) or begun to percolate (in the case of nanocrystallite with low population density of oxygen vacancies).

  7. Effects of coordination agents on the morphology of CdS nanocrystallites synthesized by the hydrothermal method

    NASA Astrophysics Data System (ADS)

    Nie, Qiulin; Yuan, Qiuli; Chen, Weixiang; Xu, Zhude

    2004-05-01

    CdS nanocrystallites were synthesized by the hydrothermal method and characterized by XRD, TEM, and XPS, respectively. Different coordination agents were chosen as the template to investigate their effects on the product morphology. It was found that the CdS nanocrystallites displayed a rod-like shape when ethylenediamine or methylamine were employed as the template. In contrast, only nanoparticles of CdS were observed when ammonia or pyridine were used. Based on our experimental results, a complex structure-controlling mechanism is proposed.

  8. Nanouric acid or nanocalcium phosphate as central nidus to induce calcium oxalate stone formation: a high-resolution transmission electron microscopy study on urinary nanocrystallites

    PubMed Central

    Gao, Jie; Xue, Jun-Fa; Xu, Meng; Gui, Bao-Song; Wang, Feng-Xin; Ouyang, Jian-Ming

    2014-01-01

    Purpose This study aimed to accurately analyze the relationship between calcium oxalate (CaOx) stone formation and the components of urinary nanocrystallites. Method High-resolution transmission electron microscopy (HRTEM), selected area electron diffraction, fast Fourier transformation of HRTEM, and energy dispersive X-ray spectroscopy were performed to analyze the components of these nanocrystallites. Results The main components of CaOx stones are calcium oxalate monohydrate and a small amount of dehydrate, while those of urinary nanocrystallites are calcium oxalate monohydrate, uric acid, and calcium phosphate. The mechanism of formation of CaOx stones was discussed based on the components of urinary nanocrystallites. Conclusion The formation of CaOx stones is closely related both to the properties of urinary nanocrystallites and to the urinary components. The combination of HRTEM, fast Fourier transformation, selected area electron diffraction, and energy dispersive X-ray spectroscopy could be accurately performed to analyze the components of single urinary nanocrystallites. This result provides evidence for nanouric acid and/or nanocalcium phosphate crystallites as the central nidus to induce CaOx stone formation. PMID:25258530

  9. A pathway of nanocrystallite fabrication by photo-assisted growth in pure water

    NASA Astrophysics Data System (ADS)

    Jeem, Melbert; Bin Julaihi, Muhammad Rafiq Mirza; Ishioka, Junya; Yatsu, Shigeo; Okamoto, Kazumasa; Shibayama, Tamaki; Iwasaki, Tomio; Kato, Takahiko; Watanabe, Seiichi

    2015-06-01

    We report a new production pathway for a variety of metal oxide nanocrystallites via submerged illumination in water: submerged photosynthesis of crystallites (SPSC). Similar to the growth of green plants by photosynthesis, nanocrystallites shaped as nanoflowers and nanorods are hereby shown to grow at the protruded surfaces via illumination in pure, neutral water. The process is photocatalytic, accompanied with hydroxyl radical generation via water splitting; hydrogen gas is generated in some cases, which indicates potential for application in green technologies. Together with the aid of ab initio calculation, it turns out that the nanobumped surface, as well as aqueous ambience and illumination are essential for the SPSC method. Therefore, SPSC is a surfactant-free, low-temperature technique for metal oxide nanocrystallites fabrication.

  10. Synthesis and optical properties of Eu 3+ and Tb 3+ doped GaN nanocrystallite powders

    NASA Astrophysics Data System (ADS)

    Nyk, M.; Kudrawiec, R.; Strek, W.; Misiewicz, J.

    2006-05-01

    The GaN nanocrystallite powders obtained by thermal decomposition of pure and doped gallium nitrate followed by nitridation with ammonia are investigated in this paper. The evolution of the phase composition, structure and morphology was studied. The average size of GaN nanocrystallites estimated from the broadening of XRD diffraction peaks was found to be ˜9-21 nm. The photoluminescence and cathodoluminescence properties of pure and Eu 3+ and Tb 3+ doped GaN nanocrystallites were measured and analyzed. A strong emission related to f-f electron transition in Eu and Tb ions has been observed. In addition, a red/yellow emission related to a recombination in the GaN nanocrystalline grains has been observed. It has been shown that this emission strongly depends on the excitation source.

  11. Enhancement of the Si p-n diode NIR photoresponse by embedding β-FeSi2 nanocrystallites.

    PubMed

    Shevlyagin, A V; Goroshko, D L; Chusovitin, E A; Galkin, K N; Galkin, N G; Gutakovskii, A K

    2015-10-05

    By using solid phase epitaxy of thin Fe films and molecular beam epitaxy of Si, a p(+)-Si/p-Si/β-FeSi2 nanocrystallites/n-Si(111) diode structure was fabricated. Transmission electron microscopy data confirmed a well-defined multilayered structure with embedded nanocrystallites of two typical sizes: 3-4 and 15-20 nm, and almost coherent epitaxy of the nanocrystallites with the Si matrix. The diode at zero bias conditions exhibited a current responsivity of 1.7 mA/W, an external quantum efficiency of about 0.2%, and a specific detectivity of 1.2 × 10(9) cm × Hz(1/2)/W at a wavelength of 1300 nm at room temperature. In the avalanche mode, the responsivity reached up to 20 mA/W (2% in terms of efficiency) with a value of avalanche gain equal to 5. The data obtained indicate that embedding of β-FeSi2 nanocrystallites into the depletion region of the Si p-n junction results in expansion of the spectral sensitivity up to 1600 nm and an increase of the photoresponse by more than two orders of magnitude in comparison with a conventional Si p-n junction. Thereby, fabricated structure combines advantage of the silicon photodiode functionality and simplicity with near infrared light detection capability of β-FeSi2.

  12. Synthesis and characterization of magnesium oxide nanocrystallites and probing the vacancy-type defects through positron annihilation studies

    NASA Astrophysics Data System (ADS)

    Das, Anjan; Mandal, Atis Chandra; Roy, Soma; Prashanth, Pendem; Ahamed, Sk Izaz; Kar, Subhrasmita; Prasad, Mithun S.; Nambissan, P. M. G.

    2016-09-01

    Magnesium oxide nanocrystallites exhibit certain abnormal characteristics when compared to those of other wide band gap oxide semiconductors in the sense they are most prone to water absorption and formation of a hydroxide layer on the surface. The problem can be rectified by heating and pure nanocrystallites can be synthesized with controllable sizes. Inevitably the defect properties are distinctly divided between two stages, the one with the hydroxide layer (region I) and the other after the removal of the layer by annealing (region II). The lattice parameters, the optical band gap and even the positron annihilation characteristics are conspicuous by their distinct behavior in the two stages of the surface configurations of nanoparticles. While region I was specific with the formation of positronium-hydrogen complexes that drastically altered the defect-specific positron lifetimes, pick-off annihilation of orthopositronium atoms marked region II. The vacancy clusters within the nanocrystallites also trapped positrons. They agglomerated due to the effect of the higher temperatures and resulted in the growth of the nanocrystallites. The coincidence Doppler broadening spectroscopic measurements supported these findings and all the more indicated the trapping of positrons additionally into the neutral divacancies and negatively charged trivacancies. This is apart from the Mg2+ monovacancies which acted as the dominant trapping centers for positrons.

  13. Enhancement of the Si p-n diode NIR photoresponse by embedding β-FeSi2 nanocrystallites

    PubMed Central

    Shevlyagin, A. V.; Goroshko, D. L.; Chusovitin, E. A.; Galkin, K. N.; Galkin, N. G.; Gutakovskii, A. K.

    2015-01-01

    By using solid phase epitaxy of thin Fe films and molecular beam epitaxy of Si, a p+-Si/p-Si/β-FeSi2 nanocrystallites/n-Si(111) diode structure was fabricated. Transmission electron microscopy data confirmed a well-defined multilayered structure with embedded nanocrystallites of two typical sizes: 3–4 and 15–20 nm, and almost coherent epitaxy of the nanocrystallites with the Si matrix. The diode at zero bias conditions exhibited a current responsivity of 1.7 mA/W, an external quantum efficiency of about 0.2%, and a specific detectivity of 1.2 × 109 cm × Hz1/2/W at a wavelength of 1300 nm at room temperature. In the avalanche mode, the responsivity reached up to 20 mA/W (2% in terms of efficiency) with a value of avalanche gain equal to 5. The data obtained indicate that embedding of β-FeSi2 nanocrystallites into the depletion region of the Si p-n junction results in expansion of the spectral sensitivity up to 1600 nm and an increase of the photoresponse by more than two orders of magnitude in comparison with a conventional Si p-n junction. Thereby, fabricated structure combines advantage of the silicon photodiode functionality and simplicity with near infrared light detection capability of β-FeSi2. PMID:26434582

  14. Structural and Spectroscopic Studies of Sm3+/CdS Nanocrystallites in Sol-Gel TiO2-ZrO2 Matrix

    NASA Astrophysics Data System (ADS)

    Karthika, S.; Prathibha, Vasudevan; Ann, Mary K. A.; Viji, Vidyadharan; Biju, P. R.; Unnikrishnan, N. V.

    2014-02-01

    A sol-gel method was used to prepare titania-zirconia matrices doped with Sm3+/CdS nanocrystallites. The structural properties of the matrices were characterized using transmission electron microscopy (TEM), thermogravimetric analysis (TGA), differential thermal analysis (DTA), and Fourier-transform infrared spectroscopy studies. The thermal stability of the material was determined by TGA/DTA analysis. The absorption spectrum shows the characteristic peaks of the Sm3+ ions and the absorption peak corresponding to the CdS nanocrystallites. The optical bandgap and size of the CdS nanoparticles were calculated from the absorption spectrum. From TEM, the interplanar distance ( d) was estimated to be 3.533 Å, which matches with the (1 0 0) plane of bulk CdS. The measurements yield a nanocrystallite size of around 7.8 nm. The optical absorption and emission spectra confirmed the formation of CdS nanoparticles along with samarium ions in the titania-zirconia matrices. The fluorescence intensity of the samarium ions was found to be greatly enhanced by codoping with CdS nanocrystallites.

  15. Anchoring alpha-manganese oxide nanocrystallites on multi-walled carbon nanotubes as electrode materials for supercapacitor

    NASA Astrophysics Data System (ADS)

    Li, Li; Qin, Zong-Yi; Wang, Ling-Feng; Liu, Hong-Jin; Zhu, Mei-Fang

    2010-09-01

    The partial coverage of manganese oxide (MnO2) particles was achieved on the surfaces of multi-walled carbon nanotubes (MWCNTs) through a facile hydrothermal process. These particles were demonstrated to be alpha-manganese dioxide (α-MnO2) nanocrystallites, and exhibited the appearance of the whisker-shaped crystals with the length of 80-100 nm. In such a configuration, the uncovered CNTs in the nanocomposite acted as a good conductive pathway and the whisker-shaped MnO2 nanocrystallites efficiently increased the contact of the electrolyte with the active materials. Thus, the highest specific capacitance of 550 F g-1 was achieved using the resulting nanocomposites as the supercapacitor electrode. In addition, the enhancement of the capacity retention was observed, with the nanocomposite losing only 10% of the maximum capacity after 1,500 cycles.

  16. Component analyses of urinary nanocrystallites of uric acid stone formers by combination of high-resolution transmission electron microscopy, fast Fourier transformation, energy dispersive X-ray spectroscopy, X-ray diffraction and Fourier transform infrared spectroscopy.

    PubMed

    Sun, Xin-Yuan; Xue, Jun-Fa; Xia, Zhi-Yue; Ouyang, Jian-Ming

    2015-06-01

    This study aimed to analyse the components of nanocrystallites in urines of patients with uric acid (UA) stones. X-ray diffraction (XRD), Fourier transform infrared spectroscopy, high-resolution transmission electron microscopy (HRTEM), fast Fourier transformation (FFT) of HRTEM, and energy dispersive X-ray spectroscopy (EDS) were performed to analyse the components of these nanocrystallites. XRD and FFT showed that the main component of urinary nanocrystallites was UA, which contains a small amount of calcium oxalate monohydrate and phosphates. EDS showed the characteristic absorption peaks of C, O, Ca and P. The formation of UA stones was closely related to a large number of UA nanocrystallites in urine. A combination of HRTEM, FFT, EDS and XRD analyses could be performed accurately to analyse the components of urinary nanocrystallites.

  17. Template-mediated nano-crystallite networks in semiconducting polymers.

    PubMed

    Kwon, Sooncheol; Yu, Kilho; Kweon, Kyoungchun; Kim, Geunjin; Kim, Junghwan; Kim, Heejoo; Jo, Yong-Ryun; Kim, Bong-Joong; Kim, Jehan; Lee, Seoung Ho; Lee, Kwanghee

    2014-06-18

    Unlike typical inorganic semiconductors with a crystal structure, the charge dynamics of π-conjugated polymers (π-CPs) are severely limited by the presence of amorphous portions between the ordered crystalline regions. Thus, the formation of interconnected pathways along crystallites of π-CPs is desired to ensure highly efficient charge transport in printable electronics. Here we report the formation of nano-crystallite networks in π-CP films by employing novel template-mediated crystallization (TMC) via polaron formation and electrostatic interaction. The lateral and vertical charge transport of TMC-treated films increased by two orders of magnitude compared with pristine π-CPs. In particular, because of the unprecedented room temperature and solution-processing advantages of our TMC method, we achieve a field-effect mobility of 0.25 cm(2) V(-1) s(-1) using a plastic substrate, which corresponds to the highest value reported thus far. Because our findings can be applied to various π-conjugated semiconductors, our approach is universal and is expected to yield high-performance printable electronics.

  18. Preparation of TiO₂ nanocrystallite powders coated with 9 mol% ZnO for cosmetic applications in sunscreens.

    PubMed

    Ko, Horng-Huey; Chen, Hui-Ting; Yen, Feng-Ling; Lu, Wan-Chen; Kuo, Chih-Wei; Wang, Moo-Chin

    2012-01-01

    The preparation of TiO(2) nanocrystallite powders coated with and without 9 mol% ZnO has been studied for cosmetic applications in sunscreens by a co-precipitation process using TiCl(4) and Zn(NO(3))(2)·6H(2)O as starting materials. XRD results show that the phases of anatase TiO(2) and rutile TiO(2) coexist for precursor powders without added ZnO (T-0Z) and calcined at 523 to 973 K for 2 h. When the T-0Z precursor powders are calcined at 1273 K for 2 h, only the rutile TiO(2) appears. In addition, when the TiO(2) precursor powders contain 9 mol% ZnO (T-9Z) are calcined at 873 to 973 K for 2 h, the crystallized samples are composed of the major phase of rutile TiO(2) and the minor phases of anatase TiO(2) and Zn(2)Ti(3)O(8). The analyses of UV/VIS/NIR spectra reveal that the absorption of the T-9Z precursor powders after being calcined has a red-shift effect in the UV range with increasing calcination temperature. Therefore, the TiO(2) nanocrystallite powders coated with 9 mol% ZnO can be used as the attenuate agent in the UV-A region for cosmetic applications in sunscreens.

  19. Preparation of TiO2 Nanocrystallite Powders Coated with 9 mol% ZnO for Cosmetic Applications in Sunscreens

    PubMed Central

    Ko, Horng-Huey; Chen, Hui-Ting; Yen, Feng-Ling; Lu, Wan-Chen; Kuo, Chih-Wei; Wang, Moo-Chin

    2012-01-01

    The preparation of TiO2 nanocrystallite powders coated with and without 9 mol% ZnO has been studied for cosmetic applications in sunscreens by a co-precipitation process using TiCl4 and Zn(NO3)2·6H2O as starting materials. XRD results show that the phases of anatase TiO2 and rutile TiO2 coexist for precursor powders without added ZnO (T-0Z) and calcined at 523 to 973 K for 2 h. When the T-0Z precursor powders are calcined at 1273 K for 2 h, only the rutile TiO2 appears. In addition, when the TiO2 precursor powders contain 9 mol% ZnO (T-9Z) are calcined at 873 to 973 K for 2 h, the crystallized samples are composed of the major phase of rutile TiO2 and the minor phases of anatase TiO2 and Zn2Ti3O8. The analyses of UV/VIS/NIR spectra reveal that the absorption of the T-9Z precursor powders after being calcined has a red-shift effect in the UV range with increasing calcination temperature. Therefore, the TiO2 nanocrystallite powders coated with 9 mol% ZnO can be used as the attenuate agent in the UV-A region for cosmetic applications in sunscreens. PMID:22408415

  20. Flower-shaped ZnO nanocrystallite aggregates synthesized through a template-free aqueous solution method for dye-sensitized solar cells

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

    Chang, Wei-Chen, E-mail: changpeter@iner.gov.tw; Institute of Nuclear Energy Research, Atomic Energy Council, Executive Yuan, 1000 Wenhua Rd., Chiaan Village, Lungtan, Taoyuan 325, Taiwan; Chen, Hung-Shuo

    Hierarchically structured flower-shaped aggregates composed of ZnO nanocrystals were synthesized through a template-free aqueous solution method. The synthesized nanocrystallite aggregates were demonstrated to be promising photoanode materials for dye-sensitized solar cells (DSSCs). Compared with commercially available ZnO nanoparticles (ZnONPs), the flower-like aggregates (ZnONFs), each having an overall dimension of 400–600 nm, exhibited similar dye loading but higher light-scattering ability, which led to a substantial increase in the light-harvesting efficiency of resulting cells. The unique morphology of ZnONFs also boosted the absorbed photon-to-electric current generation efficiency. Consequently, DSSCs constructed from ZnONFs showed significantly improved photocurrent and achieved an overall conversion efficiency ofmore » 4.42%, which was 47% higher than that attained by ZnONP-based cells.« less

  1. Room temperature visible photoluminescence of silicon nanocrystallites embedded in amorphous silicon carbide matrix

    NASA Astrophysics Data System (ADS)

    Coscia, U.; Ambrosone, G.; Basa, D. K.

    2008-03-01

    The nanocrystalline silicon embedded in amorphous silicon carbide matrix was prepared by varying rf power in high vacuum plasma enhanced chemical vapor deposition system using silane methane gas mixture highly diluted in hydrogen. In this paper, we have studied the evolution of the structural, optical, and electrical properties of this material as a function of rf power. We have observed visible photoluminescence at room temperature and also have discussed the role played by the Si nanocrystallites and the amorphous silicon carbide matrix. The decrease of the nanocrystalline size, responsible for quantum confinement effect, facilitated by the amorphous silicon carbide matrix, is shown to be the primary cause for the increase in the PL intensity, blueshift of the PL peak position, decrease of the PL width (full width at half maximum) as well as the increase of the optical band gap and the decrease of the dark conductivity.

  2. Controlling the opto-electronic properties of nc-SiOx:H films by promotion of 〈220〉 orientation in the growth of ultra-nanocrystallites at the grain boundary

    NASA Astrophysics Data System (ADS)

    Das, Debajyoti; Samanta, Subhashis

    2018-01-01

    A systematic development of undoped nc-SiOx:H thin films from (SiH4 + CO2) plasma diluted by a combination of H2 and He has been investigated through structural, optical and electrical characterization and correlation. Gradual inclusion of O into a highly crystalline silicon network progressively produces a two-phase structure where Si-nanocrystals (Si-nc) are embedded into the a-SiOx:H matrix. However, at the intermediate grain boundary region the growth of ultra-nanocrystallites controls the effectiveness of the material. The ultra-nanocrystallites are the part and portion of crystallinity accommodating the dominant fraction of thermodynamically preferred 〈220〉 crystallographic orientation, most favourable for stacked layer device performance. Atomic H plays a dominant role in maintaining an improved nanocrystalliny in the network even during O inclusion, while He in its excited state (He*) maintains a good energy balance at the grain boundary and produces a significant fraction of ultra-nanocrystalline component which has been demonstrated to organize the energetically favourable 〈220〉 crystallographic orientation in the network. The nc-SiOx:H films, maintaining proportionally good electrical conductivity over an wide range of optical band gap, remarkably low microstructure factor and simultaneous high crystalline volume fraction dominantly populated by ultra-nanocrystallites of 〈220〉 crystallographic orientation mostly at the grain boundary, have been obtained in technologically most popular 13.56 MHz PECVD SiH4 plasma even at a low substrate temperature ∼250 °C, convenient for device fabrication.

  3. Microstructure and optical properties of TiO2 nanocrystallites-CaTiO3:Pr3+ hybrid thick films

    NASA Astrophysics Data System (ADS)

    Xia, Chang-Kui; Gao, Xiang-Dong; Yu, Changjiang; Yu, Aimin; Li, Xiaomin; Gao, Dongsheng; Shi, Ying

    Long afterglow CaTiO3:Pr3+ ceramic powders were integrated with hydrothermal TiO2 nanocrystallites via “doctor-blade” and TiO2-CaTiO3:Pr3+ hybrid thick films on FTO substrate were fabricated. Effects of the Pr3+ doping level (0.06%, 0.3%) and the CaTiO3:Pr3+/TiO2 weight ratio (0.23, 0.92) on the crystallinity, morphologies, optical transmittance and photoluminescence (PL) properties were investigated. Results showed that the crystallinity of the hybrid films originated from both TiO2 nanocrystallites and CaTiO3:Pr3+ ceramic particles, affected little by the integrating process. The film surface became denser and coarser due to the incorporation of CaTiO3:Pr3+ micron/submicron particles, and the film thickness varied little (˜2.2μm). The optical transmittance of the hybrid film decreased sharply (<20% for 0.92 incorporation level) due to the scattering effects of the CaTiO3:Pr3+ micron/submicron particles to the incident light. All the hybrid films exhibited strong PL at ˜613nm when excited with 332-335nm, and the film with the Ca0.997TiO3:Pr0.0033+/TiO2 weight ratio of 0.23 showed the highest emission. In addition, the film exhibited a photoresponce to a broad ultraviolet excitation ranging from 288-369nm and a long emission decay time up to 30min at 613nm, possible for use in the ultraviolet detectors, solar cells and other photoelectrical devices.

  4. A New Commercializable Route for the Preparation of Single-Source Precursors for Bulk, Thin-Film, and Nanocrystallite I-III-IV Semiconductors

    NASA Technical Reports Server (NTRS)

    Banger, Kulbinder K.; Jin, Michael H. C.; Harris, Jerry D.; Fanwick, Philip E.; Hepp, Aloysius F.

    2004-01-01

    We report a new simplified synthetic procedure for commercial manufacture of ternary single source precursors (SSP). This new synthetic process has been successfully implemented to fabricate known SSPs on bulk scale and the first liquid SSPs to the semiconductors CuInSe2 and AgIn(x)S(y). Single crystal X-ray determination reveals the first unsolvated ternary AgInS SSP. SSPs prepared via this new route have successfully been used in a spray assisted chemical vapor deposition (CVD) process to deposit polycrystalline thin films, and for preparing ternary nanocrystallites.

  5. Sol-Gel Synthesis and Antioxidant Properties of Yttrium Oxide Nanocrystallites Incorporating P-123.

    PubMed

    Mellado-Vázquez, Rebeca; García-Hernández, Margarita; López-Marure, Arturo; López-Camacho, Perla Yolanda; de Jesús Morales-Ramírez, Ángel; Beltrán-Conde, Hiram Isaac

    2014-09-19

    Yttrium oxide (Y₂O₃) nanocrystallites were synthesized by mean of a sol-gel method using two different precursors. Raw materials used were yttrium nitrate and yttrium chloride, in methanol. In order to promote oxygen vacancies, P-123 poloxamer was incorporated. Synthesized systems were heat-treated at temperatures from 700 °C to 900 °C. Systems at 900 °C were prepared in the presence and absence of P-123 using different molar ratios (P-123:Y = 1:1 and 2:1). Fourier transform infrared spectroscopy (FTIR) results revealed a characteristic absorption band of Y-O vibrations typical of Y₂O₃ matrix. The structural phase was analyzed by X-ray diffraction (XRD), showing the characteristic cubic phase in all systems. The diffraction peak that presented the major intensity corresponded to the sample prepared from yttrium chloride incorporating P-123 in a molar ratio of P-123:Y = 2:1 at 900 °C. Crystallites sizes were determined by Scherrer equation as between 21 nm and 32 nm. Antioxidant properties were estimated by 2,2-diphenyl-1-picrylhydrazyl (DPPH•) assays; the results are discussed.

  6. Controllable reflection properties of nanocomposite photonic crystals constructed by semiconductor nanocrystallites and natural periodic bio-matrices.

    PubMed

    Han, Jie; Su, Huilan; Song, Fang; Zhang, Di; Chen, Zhixin

    2010-10-01

    In this contribution, the subtle periodic nanostructures in butterfly wings and peacock feathers are applied as natural PhC matrices to in situ embed CdS nanocrystallites (nano-CdS) on the structure surface via a convenient solution process. The resulting nano-CdS/natural PhCs nanocomposites show typical 1D, quasi 1D and 2D PhC structures at the nanoscale, which is inherited from the corresponding natural periodic bio-matrices. Moreover, their reflection properties are investigated and show dependence on PhC type, structure parameter, loading amount, as well as collecting angle. This work suggests that natural periodic bio-structures could be perfect matrices to construct novel nanocomposite PhCs, whose photonic band structures are tunable and thus achieve controllable optical properties. Related ideas could inspire the design and synthesis of future nanocomposite PhCs.

  7. Sol-Gel Synthesis and Antioxidant Properties of Yttrium Oxide Nanocrystallites Incorporating P-123

    PubMed Central

    Mellado-Vázquez, Rebeca; García-Hernández, Margarita; López-Marure, Arturo; López-Camacho, Perla Yolanda; Morales-Ramírez, Ángel de Jesús; Beltrán-Conde, Hiram Isaac

    2014-01-01

    Yttrium oxide (Y2O3) nanocrystallites were synthesized by mean of a sol-gel method using two different precursors. Raw materials used were yttrium nitrate and yttrium chloride, in methanol. In order to promote oxygen vacancies, P-123 poloxamer was incorporated. Synthesized systems were heat-treated at temperatures from 700 °C to 900 °C. Systems at 900 °C were prepared in the presence and absence of P-123 using different molar ratios (P-123:Y = 1:1 and 2:1). Fourier transform infrared spectroscopy (FTIR) results revealed a characteristic absorption band of Y–O vibrations typical of Y2O3 matrix. The structural phase was analyzed by X-ray diffraction (XRD), showing the characteristic cubic phase in all systems. The diffraction peak that presented the major intensity corresponded to the sample prepared from yttrium chloride incorporating P-123 in a molar ratio of P-123:Y = 2:1 at 900 °C. Crystallites sizes were determined by Scherrer equation as between 21 nm and 32 nm. Antioxidant properties were estimated by 2,2-diphenyl-1-picrylhydrazyl (DPPH•) assays; the results are discussed. PMID:28788211

  8. Modeling of the Structure of Disordered Metallic Alloys and Its Transformation Under Thermal Forcing

    NASA Astrophysics Data System (ADS)

    Cress, Ryan Paul

    The morphology of disordered binary metallic alloys is investigated. The structure of disordered binary metallic alloys is modeled as a randomly close packed (RCP) assembly of atoms. It was observed through a 2-D binary hard sphere experiment that RCP structure can be modeled as a mixture of nano-crystallites and glassy matter. We define the degree of crystallinity as the fraction of atoms contained in nano-crystallites in an RCP medium. Nano-crystallites by size in a crystallite size distribution were determined experimentally to define the morphology of the RCP medium. Both the degree of crystallinity and the crystallite size distribution have been found to be determined by the composition of a given binary mixture. A 2-D Monte Carlo simulation was developed in order to replicate the RCP structure observed in the experiment which is then extended to cases of arbitrary composition. Crystallites were assumed to be spherical with isotropic cross sections. The number of atoms in an individual crystallite in 2-D is simply transformed into the number of atoms in 3-D; we then obtain the crystallite size distribution in 3-D. This experiment accounts for the contribution from the repulsive core of the inter-atomic potential. The attractive part of the potential is recovered by constructing spherical nano-crystallites of a given radius from a crystalline specimen of each given alloy. A structural model of a disordered alloy is thus obtained. With the basic structure of the RCP medium defined, the response to heating would be in the form of changes to the crystallite size distribution. This was first investigated in a hard sphere mechanical oven experiment. The experimental setup consists of a 2-D cell which is driven by two independent stepper motors. The motors drive a binary RCP bed of spheres on a slightly tilted plane according to a chaotic algorithmm. The motors are driven at four different speed settings. The RCP medium was analyzed using a sequence of digital images

  9. High-performance carbon-coated ZnMn2O4 nanocrystallite supercapacitors with tailored microstructures enabled by a novel solution combustion method

    NASA Astrophysics Data System (ADS)

    Abdollahifar, Mozaffar; Huang, Sheng-Siang; Lin, Yu-Hsiang; Lin, Yan-Cheng; Shih, Bing-Yi; Sheu, Hwo-Shuenn; Liao, Yen-Fa; Wu, Nae-Lih

    2018-02-01

    Although ZnMn2O4 is widely studied as Li-ion battery anodes, it remains a challenge to tailor suitable microstructures of the oxide for supercapacitor applications. Carbon-coated ZnMn2O4 (C@ZMO) nanocrystallites showing high-performance pseudocapacitor behaviours in neutral aqueous electrolyte are for the first time successfully synthesised via a novel solution combustion process using polyethylene glycol as a multifunctional microstructure-directing agent. Controlling the molecular weight and amount of the polymer in the combustion solution enables the formation of highly-crystalline C@ZMO having substantially higher, by more than 5 folds, specific surface areas with mesoporous structures and conformal carbon coating via the one-pot synthesis process. The resulting C@ZMO supercapacitor electrodes in Na2SO4(aq) electrolyte exhibit ideal capacitive behaviours with specific capacitances up to 150 F g-1 and cycle stability showing no capacitance fade after 10,000 cycles at 60% of full capacity and >99% Coulombic efficiency. This study not only illustrates a new powerful synthesis route capable of producing conductive mesoporous crystalline oxide-based nanomaterials for energy storage applications but also reveals a new class of high-performance pseudocapacitive materials for neutral aqueous electrolytes.

  10. Models for Amorphous Calcium Carbonate

    NASA Astrophysics Data System (ADS)

    Sinha, Sourabh

    Many species e.g. sea urchin form amorphous calcium carbonate (ACC) precursor phases that subsequently transform into crystalline CaCO3. It is certainly possible that the biogenic ACC might have more than 10 wt% Mg and ˜3 wt% of water. The structure of ACC and the mechanisms by which it transforms to crystalline phase are still poorly understood. In this dissertation our goal is to determine an atomic structure model that is consistent with diffraction and IR measurements of ACC. For this purpose a calcite supercell with 24 formula units, containing 120 atoms, was constructed. Various configurations with substitution of Ca by 6 Mg ions (6 wt.%) and insertion of 3-5 H 2O molecules (2.25-3.75 wt.%) in the interstitial positions of the supercell, were relaxed using a robust density function code VASP. The most noticeable effects were the tilts of CO3 groups and the distortion of Ca sub-lattice, especially in the hydrated case. The distributions of Ca-Ca nearest neighbor distance and CO3 tilts were extracted from various configurations. The same methods were also applied to aragonite. Sampling from the calculated distortion distributions, we built models for amorphous calcite/aragonite of size ˜ 1700 nm3 based on a multi-scale modeling scheme. We used these models to generate diffraction patterns and profiles with our diffraction code. We found that the induced distortions were not enough to generate a diffraction profile typical of an amorphous material. We then studied the diffraction profiles from several nano-crystallites as recent studies suggest that ACC might be a random array of nano-cryatallites. It was found that the generated diffraction profile from a nano-crystallite of size ˜ 2 nm3 is similar to that from the ACC.

  11. Bimetallic CoNiSx nanocrystallites embedded in nitrogen-doped carbon anchored on reduced graphene oxide for high-performance supercapacitors.

    PubMed

    Chen, Qidi; Miao, Jinkang; Quan, Liang; Cai, Daoping; Zhan, Hongbing

    2018-02-22

    Exploring high-performance and low-priced electrode materials for supercapacitors is important but remains challenging. In this work, a unique sandwich-like nanocomposite of reduced graphene oxide (rGO)-supported N-doped carbon embedded with ultrasmall CoNiS x nanocrystallites (rGO/CoNiS x /N-C nanocomposite) has been successfully designed and synthesized by a simple one-step carbonization/sulfurization treatment of the rGO/Co-Ni precursor. The intriguing structural/compositional/morphological advantages endow the as-synthesized rGO/CoNiS x /N-C nanocomposite with excellent electrochemical performance as an advanced electrode material for supercapacitors. Compared with the other two rGO/CoNiO x and rGO/CoNiS x nanocomposites, the rGO/CoNiS x /N-C nanocomposite exhibits much enhanced performance, including a high specific capacitance (1028.2 F g -1 at 1 A g -1 ), excellent rate capability (89.3% capacitance retention at 10 A g -1 ) and good cycling stability (93.6% capacitance retention over 2000 cycles). In addition, an asymmetric supercapacitor (ASC) device based on the rGO/CoNiS x /N-C nanocomposite as the cathode and activated carbon (AC) as the anode is also fabricated, which can deliver a high energy density of 32.9 W h kg -1 at a power density of 229.2 W kg -1 with desirable cycling stability. These electrochemical results evidently indicate the great potential of the sandwich-like rGO/CoNiS x /N-C nanocomposite for applications in high-performance supercapacitors.

  12. Silver nanocrystallites: Facile biofabrication using Shewanella oneidensis, and an evaluation of their comparative toxicity on Gram-negative and Gram-positive bacteria

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

    Suresh, Anil K; Wang, Wei; Pelletier, Dale A

    Microorganisms have long been known to develop resistance to metal ions either by sequestering metals inside the cell or by effluxing them into the extracellular media. Here we report the biosynthesis of extracellular silver based single nanocrystallites of well-defined composition and homogeneous morphology utilizing the -proteobacterium, Shewanella oneidensis strain MR-1, upon incubation with an aqueous solution of silver nitrate. Further characterization of these particles revealed that the crystals consist of small, reasonably monodispersed spheres in the size range 2 11 nm (with an average of 4 1.5 nm). The bactericidal effect of these biologically synthesized silver nanoparticles (biogenic-Ag) are comparedmore » to similar chemically synthesized nanoparticles (colloidal silver [colloidal-Ag] and oleate capped silver [oleate-Ag]). The determination of the bactericidal effect of these different silver nanoparticles was assessed using both Gram-negative (E. coli) and Gram-positive (B. subtilis) bacteria and based on the diameter of the inhibition zone in disc diffusion tests, minimum inhibitory concentrations, Live/Dead staining assays, and atomic force microscopy. From a toxicity perspective, a clear synthesis procedure, and a surface coat- and strain-dependent inhibition were observed for silver nanoparticles. Biogenic-Ag was found to be of higher toxicity when compared to colloidal-Ag for both E. coli and B. subtilis. E. coli was found to be more resistant to either of these nanoparticles than B. subtilis. In contrast, Oleate-Ag was not toxic to either of the bacteria. These findings have important implications for the potential uses of Ag nanomaterials and for their fate in biological and environmental systems.« less

  13. Vacancy defects and defect clusters in alkali metal ion-doped MgO nanocrystallites studied by positron annihilation and photoluminescence spectroscopy

    NASA Astrophysics Data System (ADS)

    Sellaiyan, S.; Uedono, A.; Sivaji, K.; Janet Priscilla, S.; Sivasankari, J.; Selvalakshmi, T.

    2016-10-01

    Pure and alkali metal ion (Li, Na, and K)-doped MgO nanocrystallites synthesized by solution combustion technique have been studied by positron lifetime and Doppler broadening spectroscopy methods. Positron lifetime analysis exhibits four characteristic lifetime components for all the samples. Doping reduces the Mg vacancy after annealing to 800 °C. It was observed that Li ion migrates to the vacancy site to recover Mg vacancy-type defects, reducing cluster vacancies and micropores. For Na- and K-doped MgO, the aforementioned defects are reduced and immobile at 800 °C. Coincidence Doppler broadening studies show the positron trapping sites as vacancy clusters. The decrease in the S parameter is due to the particle growth and reduction in the defect concentration at 800 °C. Photoluminescence study shows an emission peak at 445 nm and 498 nm, associated with F2 2+ and recombination of higher-order vacancy complexes. Further, annealing process is likely to dissociate F2 2+ to F+ and this F+ is converted into F centers at 416 nm.

  14. Polymer composites reinforced by locking-in a liquid-crystalline assembly of cellulose nanocrystallites.

    PubMed

    Tatsumi, Mio; Teramoto, Yoshikuni; Nishio, Yoshiyuki

    2012-05-14

    An attempt was made to synthesize novel composites comprising poly(2-hydroxyethyl methacrylate) (PHEMA) and cellulose nanocrystallites (CNC) (acid-treated cotton microfibrils) from suspensions of CNC in an aqueous 2-hydroxyethyl methacrylate (HEMA) monomer solution. The starting suspensions (∼5 wt % CNC) separated into an isotropic upper phase and an anisotropic bottom one in the course of quiescent standing. By way of polymerization of HEMA in different phase situations of the suspensions, we obtained films of three polymer composites, PHEMA-CNC(iso), PHEMA-CNC(aniso), and PHEMA-CNC(mix), coming from the isotropic phase, anisotropic phase, and embryonic nonseparating mixture, respectively. All the composites were transparent and, more or less, birefringent under a polarized optical microscope. A fingerprint texture typical of cholesteric liquid crystals of longer pitch spread widely in PHEMA-CNC(aniso) but rather locally appeared in PHEMA-CNC(iso). Any of the CNC incorporations into the PHEMA matrix improved the original thermal and mechanical properties of this amorphous polymer material. In dynamic mechanical measurements, the locking-in of the respective CNC assemblies gave rise to an increase in the glass-state modulus E' of PHEMA as well as a marked suppression of the E'-falling at temperatures higher than T(g) (≈ 110 °C) of the vinyl polymer. It was also observed for the composites that their modulus E' rerose in a range of about 150-190 °C, which was attributable to a secondary cross-linking formation between PHEMA chains mediated by the acidic CNC filler. The mechanical reinforcement effect of the CNC dispersions was ensured in a tensile test, whereby PHEMA-CNC(aniso) was found to surpass the other two composites in stiffness and strength.

  15. Room temperature synthesis of β-NaGdF 4 : RE 3+ (RE= Eu, Er) nanocrystallites and their luminescence

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

    Tessitore, Gabriella; Mudring, Anja-Verena; Kr?mer, Karl W.

    In this study, a room temperature synthesis was developed for phase pure β-NaGdF 4 nanocrystallites as well as 5, 10, and 20% Eu 3+ or 5% Er 3+ doped material. Rare earth acetates and NaCl react in a 1:2 M ratio with a variable excess of NH 4F in ethylene glycol within 24 hours. Since the thermodynamic stability of the hexagonal phase decreases along the lanthanide series, a larger excess of NH 4F was required for the synthesis of luminescent samples doped with the smaller Er 3+ ions than for Eu 3+ doped or pure β-NaGdF 4. The materials weremore » characterized by powder X-ray diffraction, electron microscopy, and luminescence spectroscopy. The Eu 3+-doped samples show 5D 0→ 7F J and 5D 1→ 7F J luminescence after Eu 3+ excitation at 394 nm or Gd 3+ excitation at 273 nm and 308 nm. The ratio of 5D 1 vs. 5D 0 luminescence is influenced by the excitation wavelength and the Eu 3+ concentration. Lastly, the Er 3+-doped samples show green and red upconversion luminescence, respectively, from the 2H 11/2+ 4S 3/2→ 4I 15/2 and 4F 9/2→ 4I 15/2 transitions after 970 nm excitation.« less

  16. Room temperature synthesis of β-NaGdF 4 : RE 3+ (RE= Eu, Er) nanocrystallites and their luminescence

    DOE PAGES

    Tessitore, Gabriella; Mudring, Anja-Verena; Kr?mer, Karl W.

    2017-09-01

    In this study, a room temperature synthesis was developed for phase pure β-NaGdF 4 nanocrystallites as well as 5, 10, and 20% Eu 3+ or 5% Er 3+ doped material. Rare earth acetates and NaCl react in a 1:2 M ratio with a variable excess of NH 4F in ethylene glycol within 24 hours. Since the thermodynamic stability of the hexagonal phase decreases along the lanthanide series, a larger excess of NH 4F was required for the synthesis of luminescent samples doped with the smaller Er 3+ ions than for Eu 3+ doped or pure β-NaGdF 4. The materials weremore » characterized by powder X-ray diffraction, electron microscopy, and luminescence spectroscopy. The Eu 3+-doped samples show 5D 0→ 7F J and 5D 1→ 7F J luminescence after Eu 3+ excitation at 394 nm or Gd 3+ excitation at 273 nm and 308 nm. The ratio of 5D 1 vs. 5D 0 luminescence is influenced by the excitation wavelength and the Eu 3+ concentration. Lastly, the Er 3+-doped samples show green and red upconversion luminescence, respectively, from the 2H 11/2+ 4S 3/2→ 4I 15/2 and 4F 9/2→ 4I 15/2 transitions after 970 nm excitation.« less

  17. Thin film solar cells with Si nanocrystallites embedded in amorphous intrinsic layers by hot-wire chemical vapor deposition.

    PubMed

    Park, Seungil; Parida, Bhaskar; Kim, Keunjoo

    2013-05-01

    We investigated the thin film growths of hydrogenated silicon by hot-wire chemical vapor deposition with different flow rates of SiH4 and H2 mixture ambient and fabricated thin film solar cells by implementing the intrinsic layers to SiC/Si heterojunction p-i-n structures. The film samples showed the different infrared absorption spectra of 2,000 and 2,100 cm(-1), which are corresponding to the chemical bonds of SiH and SiH2, respectively. The a-Si:H sample with the relatively high silane concentration provides the absorption peak of SiH bond, but the microc-Si:H sample with the relatively low silane concentration provides the absorption peak of SiH2 bond as well as SiH bond. Furthermore, the microc-Si:H sample showed the Raman spectral shift of 520 cm(-1) for crystalline phase Si bonds as well as the 480 cm(-1) for the amorphous phase Si bonds. These bonding structures are very consistent with the further analysis of the long-wavelength photoconduction tail and the formation of nanocrystalline Si structures. The microc-Si:H thin film solar cell has the photovoltaic behavior of open circuit voltage similar to crystalline silicon thin film solar cell, indicating that microc-Si:H thin film with the mixed phase of amorphous and nanocrystalline structures show the carrier transportation through the channel of nanocrystallites.

  18. Theoretical approach to embed nanocrystallites into a bulk crystalline matrix and the embedding influence on the electronic band structure and optical properties of the resulting heterostructures

    NASA Astrophysics Data System (ADS)

    Balagan, Semyon A.; Nazarov, Vladimir U.; Shevlyagin, Alexander V.; Goroshko, Dmitrii L.; Galkin, Nikolay G.

    2018-06-01

    We develop an approach and present results of the combined molecular dynamics and density functional theory calculations of the structural and optical properties of the nanometer-sized crystallites embedded in a bulk crystalline matrix. The method is designed and implemented for both compatible and incompatible lattices of the nanocrystallite (NC) and the host matrix, when determining the NC optimal orientation relative to the matrix constitutes a challenging problem. We suggest and substantiate an expression for the cost function of the search algorithm, which is the energy per supercell generalized for varying number of atoms in the latter. The epitaxial relationships at the Si/NC interfaces and the optical properties are obtained and found to be in a reasonable agreement with experimental data. Dielectric functions show significant sensitivity to the NC’s orientation relative to the matrix at energies below 0.5 eV.

  19. Modeling of Amorphous Calcium Carbonate

    NASA Astrophysics Data System (ADS)

    Sinha, Sourabh; Rez, Peter

    2011-10-01

    Many species (e.g. sea urchin) form amorphous calcium carbonate (ACC) precursor phases that subsequently transform into crystalline CaCO3. It is certainly possible that ACC might have up to 10 wt% Mg and ˜3 wt% of water. The structure of ACC and mechanisms by which it transforms to crystalline phase are still unknown. Our goal here is to determine an atomic structure model that is consistent with diffraction and IR measurements of ACC. For this purpose a calcite supercell with 24 formula units (120 atoms) was constructed. Various configurations with 6 Mg atoms substituting for Ca (6 wt%) and 3-5 H2O molecules (2.25- 3.75 wt%) inserted in the spaces between Ca atoms, were relaxed using VASP. Most noticeable effects were the tilts of CO3 groups and distortion of Ca sub-lattice, especially in the case of water. The distributions of nearest Ca-Ca distance and CO3 tilts were extracted from those configurations. We also performed the same analysis starting with aragonite. Sampling from above distributions we built models for amorphous calcite/aragonite of size ˜1700 nm^3. We found that the induced distortions were not enough to generate a diffraction pattern typical of an amorphous material. Next we studied diffraction pattern of several nano-crystallites as recent studies suggest that amorphous calcite might be composed of nano- crystallites. We could then generate a diffraction pattern that appeared similar to that from ACC, for a nano-crystallite of size ˜2 nm^3.

  20. Theoretical approach to embed nanocrystallites into a bulk crystalline matrix and the embedding influence on the electronic band structure and optical properties of the resulting heterostructures.

    PubMed

    Balagan, Semyon Anatolyevich; Nazarov, Vladimir U; Shevlyagin, Alexander Vladimirovich; Goroshko, Dmitrii L; Galkin, N G

    2018-05-03

    We develop an approach and present results of the combined molecular dynamics and density functional theory calculations of the structural and optical properties of the nanometer-sized crystallites embedded in a bulk crystalline matrix. The method is designed and implemented for both compatible and incompatible lattices of the nanocrystallite (NC) and the host matrix, when determining the NC optimal orientation relative to the matrix constitutes a challenging problem. We suggest and substantiate an expression for the cost function of the search algorithm, which is the energy per supercell generalized for varying number of atoms in the latter. The epitaxial relationships at the Si/NC interfaces and the optical properties are obtained and found to be in a reasonable agreement with experimental data. Dielectric functions show significant sensitivity to the NC's orientation relative to the matrix at energies below 0.5 eV. © 2018 IOP Publishing Ltd.

  1. Synthesis and Behavior of Cetyltrimethyl Ammonium Bromide Stabilized Zn1+xSnO3+x (0 ≤ x ≤1) Nano-Crystallites

    PubMed Central

    Placke, Astrid; Kumar, Ashok; Priya, Shashank

    2016-01-01

    We report synthesis of cetyltrimethyl ammonium bromide (CTAB) stabilized Zn1+xSnO3+x (0 ≤ x ≤1) nano-crystallites by facile cost-effective wet chemistry route. The X-ray diffraction patterns of as-synthesized powders at the Zn/Sn ratio of 1 exhibited formation of ZnSn(OH)6. Increasing the Zn/Sn ratio further resulted in the precipitation of an additional phase corresponding to Zn(OH)2. The decomposition of these powders at 650°C for 3h led to the formation of the orthorhombic phase of ZnSnO3 and tetragonal SnO2-type phase of Zn2SnO4 at the Zn/Sn ratio of 1 and 2, respectively, with the formation of their mixed phases at intermediate compositions, i.e., at Zn/Sn ratio of 1.25, 1.50 and 1.75, respectively. The lattice parameters of orthorhombic and tetragonal phases were a ~ 3.6203 Å, b ~ 4.2646 Å and c ~ 12.8291Å (for ZnSnO3) and a = b ~ 5.0136 Å and c ~ 3.3055Å (for Zn2SnO4). The transmission electron micrographs revealed the formation of nano-crystallites with aspect ratio ~ 2; the length and thickness being 24, 13 nm (for ZnSnO3) and 47, 22 nm (for Zn2SnO4), respectively. The estimated direct bandgap values for the ZnSnO3 and Zn2SnO4 were found to be 4.21 eV and 4.12 eV, respectively. The ac conductivity values at room temperature (at 10 kHz) for the ZnSnO3 and Zn2SnO4 samples were 8.02 × 10−8 Ω-1 cm-1 and 6.77 × 10−8 Ω-1 cm-1, respectively. The relative permittivity was found to increase with increase in temperature, the room temperature values being 14.24 and 25.22 for the samples ZnSnO3 and Zn2SnO4, respectively. Both the samples, i.e., ZnSnO3 and Zn2SnO4, exhibited low values of loss tangent up to 300 K, the room temperature values being 0.89 and 0.72, respectively. A dye-sensitized solar cell has been fabricated using the optimized sample of zinc stannate photo-anode, i.e., Zn2SnO4. The cyclic voltammetry revealed oxidation and reduction around 0.40 V (current density ~ 11.1 mA/cm2) and 0.57 V (current density– 11.7 mA/cm2) for Zn2SnO4

  2. Molten salt synthesis and luminescent properties of YVO4:Ln (Ln = Eu3+, Dy3+) nanophosphors.

    PubMed

    Liu, Chenglu; Wang, Fang; Jia, Peiyun; Lin, Jun; Zhou, Zhiqiang

    2012-01-01

    Eu3+ and Dy(3+)-doped YVO4 nanocrystallites were successfully prepared at 400 degrees C in equal moles of NaNO3 and KNO3 molten salts. X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, transmission electronic microscopy (TEM), photoluminescence (PL) spectrum and lifetime were used to characterize the nanocrystallites. XRD results demonstrate that NaOH concentration and annealing temperature play important roles in phase purity and crystallinity of the nanocrystallites, the optimum NaOH concentration and annealing temperature being 6:40 and 400 degrees C respectively. TEM micrographs show the nanocrystallites are well crystallized with a cubic morphology in an average grain size of about 18 nm. Upon excitation of the vanadate group at 314 nm, YVO4:Eu3+ and YVO4:Dy3+ nanocrystallites exhibit the characteristic emission of Eu3+ and Dy3+, which indicates that there is an energy transfer from the vanadate group to the rare earth ions. Moreover, the structure and luminescent properties of the nanocrystallites were compared with their bulk counterparts with same composition in detail.

  3. Facile synthesis of carbon-mediated porous nanocrystallite anatase TiO2 for improved sodium insertion capabilities as an anode for sodium-ion batteries

    NASA Astrophysics Data System (ADS)

    Wu, Feng; Luo, Rui; Xie, Man; Li, Li; Zhang, Xiaoxiao; Zhao, Luzi; Zhou, Jiahui; Wang, KangKang; Chen, Renjie

    2017-09-01

    Porous carbon-mediated nanocrystallite anatase TiO2 composites are synthesized successfully via a simple dilatory hydrolysis-calcination method. The structural and morphological characterizations reveal that carbon-mediated TiO2 with a carbon content of 9.9 wt % (C2-TiO2) shows a combination of mesoporous and macroporous structures with a pore volume of 0.20 cm3 g-1 and surface area of 40.3 m2 g-1. Notably, C2-TiO2 delivered enhanced electrochemical performances of a high charge capacity of 259 mA h g-1 at 0.1 C and a high rate performance of 110 mA h g-1 after 150 cycles, even at 1 C. A significant decrease is also observed in the electrochemical impedance of the carbon-mediated samples, which explains superior electrochemical performance. Compared with the bare anatase TiO2 (B-TiO2), improved sodium storage capabilities of carbon-mediated samples are attributed to the participation of carbon to form a symbiotic structure with TiO2, which not only increases pore volume of the samples but serves as highly conductive network to provide a Na+ diffusion path during the insertion/de-insertion of sodium ions. All of these encouraging results suggest that carbon-mediated TiO2 has a great potential for improving sodium insertion capabilities with a facile and low-cost synthesis process.

  4. Photo-sensitive Ge nanocrystal based films controlled by substrate deposition temperature

    NASA Astrophysics Data System (ADS)

    Stavarache, Ionel; Maraloiu, Valentin Adrian; Negrila, Catalin; Prepelita, Petronela; Gruia, Ion; Iordache, Gheorghe

    2017-10-01

    Lowering the temperature of crystallization by deposition of thin films on a heated substrate represents the easiest way to find new means to develop and improve new working devices based on nanocrystals embedded in thin films. The improvements are strongly related with the increasing of operation speed, substantially decreasing the energy consumption and reducing unit fabrication costs of the respective semiconductor devices. This approach avoids major problems, such as those related to diffusion or difficulties in controlling nanocrystallites size, which appear during thermal treatments at high temperatures after deposition. This article reports on a significant progress given by structuring Ge nanocrystals (Ge-NCs) embedded in silicon dioxide (SiO2) thin films by heating the substrate at 400 °C during co-deposition of Ge and SiO2 by magnetron sputtering. As a proof-of-concept, a Si/Ge-NCs:SiO2 photo-sensitive structure was fabricated thereof and characterized. The structure shows superior performance on broad operation bandwidth from visible to near-infrared, as strong rectification properties in dark, significant current rise in the inversion mode when illuminated, high responsivity, high photo-detectivity of 1014 Jones, quick response and significant conversion efficiency with peak value reaching 850% at -1 V and about 1000 nm. This simple preparation approach brings an important contribution to the effort of structuring Ge nanocrystallites in SiO2 thin films at a lower temperature for the purpose of using these materials for devices in optoelectronics, solar cells and electronics on flexible substrates.

  5. An insight into the mechanism of charge-transfer of hybrid polymer:ternary/quaternary chalcopyrite colloidal nanocrystals.

    PubMed

    Chawla, Parul; Singh, Son; Sharma, Shailesh Narain

    2014-01-01

    In this work, we have demonstrated the structural and optoelectronic properties of the surface of ternary/quaternary (CISe/CIGSe/CZTSe) chalcopyrite nanocrystallites passivated by tri-n-octylphosphine-oxide (TOPO) and tri-n-octylphosphine (TOP) and compared their charge transfer characteristics in the respective polymer: chalcopyrite nanocomposites by dispersing them in poly(3-hexylthiophene) polymer. It has been found that CZTSe nanocrystallites due to their high crystallinity and well-ordered 3-dimensional network in its pristine form exhibit a higher steric- and photo-stability, resistance against coagulation and homogeneity compared to the CISe and CIGSe counterparts. Moreover, CZTSe nanocrystallites display efficient photoluminescence quenching as evident from the high value of the Stern-Volmer quenching constant (K SV) and eventually higher charge transfer efficiency in their respective polymer P3HT:CZTSe composites. We modelled the dependency of the charge transfer from the donor and the charge separation mechanism across the donor-acceptor interface from the extent of crystallinity of the chalcopyrite semiconductors (CISe/CIGSe/CZTSe). Quaternary CZTSe chalcopyrites with their high crystallinity and controlled morphology in conjunction with regioregular P3HT polymer is an attractive candidate for hybrid solar cells applications.

  6. Computational studies of photoluminescence from disordered nanocrystalline systems

    NASA Astrophysics Data System (ADS)

    John, George

    2000-03-01

    The size (d) dependence of emission energies from semiconductor nanocrystallites have been shown to follow an effective exponent ( d^-β) determined by the disorder in the system(V.Ranjan, V.A.Singh and G.C.John, Phys. Rev B 58), 1158 (1998). Our earlier calculation was based on a simple quantum confinement model assuming a normal distribution of crystallites. This model is now extended to study the effects of realistic systems with a lognormal distribution in particle size, accounting for carrier hopping and nonradiative transitions. Computer simulations of this model performed using the Microcal Origin software can explain several conflicting experimental results reported in literature.

  7. Material insights of HfO2-based integrated 1-transistor-1-resistor resistive random access memory devices processed by batch atomic layer deposition

    PubMed Central

    Niu, Gang; Kim, Hee-Dong; Roelofs, Robin; Perez, Eduardo; Schubert, Markus Andreas; Zaumseil, Peter; Costina, Ioan; Wenger, Christian

    2016-01-01

    With the continuous scaling of resistive random access memory (RRAM) devices, in-depth understanding of the physical mechanism and the material issues, particularly by directly studying integrated cells, become more and more important to further improve the device performances. In this work, HfO2-based integrated 1-transistor-1-resistor (1T1R) RRAM devices were processed in a standard 0.25 μm complementary-metal-oxide-semiconductor (CMOS) process line, using a batch atomic layer deposition (ALD) tool, which is particularly designed for mass production. We demonstrate a systematic study on TiN/Ti/HfO2/TiN/Si RRAM devices to correlate key material factors (nano-crystallites and carbon impurities) with the filament type resistive switching (RS) behaviours. The augmentation of the nano-crystallites density in the film increases the forming voltage of devices and its variation. Carbon residues in HfO2 films turn out to be an even more significant factor strongly impacting the RS behaviour. A relatively higher deposition temperature of 300 °C dramatically reduces the residual carbon concentration, thus leading to enhanced RS performances of devices, including lower power consumption, better endurance and higher reliability. Such thorough understanding on physical mechanism of RS and the correlation between material and device performances will facilitate the realization of high density and reliable embedded RRAM devices with low power consumption. PMID:27312225

  8. Material insights of HfO2-based integrated 1-transistor-1-resistor resistive random access memory devices processed by batch atomic layer deposition

    NASA Astrophysics Data System (ADS)

    Niu, Gang; Kim, Hee-Dong; Roelofs, Robin; Perez, Eduardo; Schubert, Markus Andreas; Zaumseil, Peter; Costina, Ioan; Wenger, Christian

    2016-06-01

    With the continuous scaling of resistive random access memory (RRAM) devices, in-depth understanding of the physical mechanism and the material issues, particularly by directly studying integrated cells, become more and more important to further improve the device performances. In this work, HfO2-based integrated 1-transistor-1-resistor (1T1R) RRAM devices were processed in a standard 0.25 μm complementary-metal-oxide-semiconductor (CMOS) process line, using a batch atomic layer deposition (ALD) tool, which is particularly designed for mass production. We demonstrate a systematic study on TiN/Ti/HfO2/TiN/Si RRAM devices to correlate key material factors (nano-crystallites and carbon impurities) with the filament type resistive switching (RS) behaviours. The augmentation of the nano-crystallites density in the film increases the forming voltage of devices and its variation. Carbon residues in HfO2 films turn out to be an even more significant factor strongly impacting the RS behaviour. A relatively higher deposition temperature of 300 °C dramatically reduces the residual carbon concentration, thus leading to enhanced RS performances of devices, including lower power consumption, better endurance and higher reliability. Such thorough understanding on physical mechanism of RS and the correlation between material and device performances will facilitate the realization of high density and reliable embedded RRAM devices with low power consumption.

  9. Influence of Al addition on structural, crystallization and soft magnetic properties of DC Joule annealed FeCo based nanocrystalline alloys

    NASA Astrophysics Data System (ADS)

    Murugaiyan, Premkumar; Abhinav, Anand; Verma, Rahul; Panda, Ashis K.; Mitra, Amitava; Baysakh, Sandip; Roy, Rajat K.

    2018-02-01

    The effect of minor Al addition on structural, crystallization, soft magnetic behaviour and magnetic field induced anisotropy through DC Joule annealing in (Fe53.95Co29.05)83Si1.3B11.7-xNb3Cu1Alx, (X = 0, 1) alloys has been studied. The Al added as-quenched melt spun ribbons show good glass forming ability, better thermo-physical properties like a high Tx1 of 438 °C, Tcam of 435 °C and Tcnc of 906 °C, compared to Tx1 of 389 °C, Tcam of 409 °C and Tcnc of 900 °C for the alloy without Al addition. The longitudinal magnetic field annealed Al added alloy exhibits low Hc of 12.92 A/m and maximum Ms. of 1.78 T. The better soft magnetic properties of Al added alloy are achieved through a high nucleation density of BCC-FeCo(Al) nanocrystallites having low K1 and λ values. The as-quenched alloys possess high magneto-strain exceeding 30 ppm and approach near zero value on nanocrystallization. The longitudinal magnetic field assisted DC Joule annealing, having current density (J) in the range of J = 20-25 A/mm2 promotes good magnetic softening due to precipitation of 5-35 nm nanocrystallites as explained by extended-random anisotropy model. The Al added alloy shows better magnetic field induced anisotropy (Ku) on nanocrystallization and shows visible change in the shape of hysteresis loop.

  10. Producing Quantum Dots by Spray Pyrolysis

    NASA Technical Reports Server (NTRS)

    Banger, Kulbinder; Jin, Michael H.; Hepp, Aloysius

    2006-01-01

    An improved process for making nanocrystallites, commonly denoted quantum dots (QDs), is based on spray pyrolysis. Unlike the process used heretofore, the improved process is amenable to mass production of either passivated or non-passivated QDs, with computer control to ensure near uniformity of size.

  11. Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

    Sukumar, Sreenivas R; Nutaro, James J

    This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

  12. Unifying Model-Based and Reactive Programming within a Model-Based Executive

    NASA Technical Reports Server (NTRS)

    Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

    1999-01-01

    Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

  13. Imaging the Ultrafast Photoelectron Transfer Process in Alizarin-TiO2.

    PubMed

    Gomez, Tatiana; Hermann, Gunter; Zarate, Ximena; Pérez-Torres, Jhon Fredy; Tremblay, Jean Christophe

    2015-07-30

    In this work, we adopt a quantum mechanical approach based on time-dependent density functional theory (TDDFT) to study the optical and electronic properties of alizarin supported on TiO2 nano-crystallites, as a prototypical dye-sensitized solar cell. To ensure proper alignment of the donor (alizarin) and acceptor (TiO2 nano-crystallite) levels, static optical excitation spectra are simulated using time-dependent density functional theory in response. The ultrafast photoelectron transfer from the dye to the cluster is simulated using an explicitly time-dependent, one-electron TDDFT ansatz. The model considers the δ-pulse excitation of a single active electron localized in the dye to the complete set of energetically accessible, delocalized molecular orbitals of the dye/nano-crystallite complex. A set of quantum mechanical tools derived from the transition electronic flux density is introduced to visualize and analyze the process in real time. The evolution of the created wave packet subject to absorbing boundary conditions at the borders of the cluster reveal that, while the electrons of the aromatic rings of alizarin are heavily involved in an ultrafast charge redistribution between the carbonyl groups of the dye molecule, they do not contribute positively to the electron injection and, overall, they delay the process.

  14. Merging high doxorubicin loading with pronounced magnetic response and bio-repellent properties in hybrid drug nanocarriers.

    PubMed

    Bakandritsos, Aristides; Papagiannopoulos, Aristeidis; Anagnostou, Eleni N; Avgoustakis, Konstantinos; Zboril, Radek; Pispas, Stergios; Tucek, Jiri; Ryukhtin, Vasyl; Bouropoulos, Nikolaos; Kolokithas-Ntoukas, Argiris; Steriotis, Theodore A; Keiderling, Uwe; Winnefeld, Frank

    2012-08-06

    Hybrid magnetic drug nanocarriers are prepared via a self-assembly process of poly(methacrylic acid)-graft-poly(ethyleneglycol methacrylate) (p(MAA-g-EGMA)) on growing iron oxide nanocrystallites. The nanocarriers successfully merge together bio-repellent properties, pronounced magnetic response, and high loading capacity for the potent anticancer drug doxorubicin (adriamicin), in a manner not observed before in such hybrid colloids. High magnetic responses are accomplished by engineering the size of the magnetic nanocrystallites (∼13.5 nm) following an aqueous single-ferrous precursor route, and through adjustment of the number of cores in each colloidal assembly. Complementing conventional magnetometry, the magnetic response of the nanocarriers is evaluated by magnetophoretic experiments providing insight into their internal organization and on their response to magnetic manipulation. The structural organization of the graft-copolymer, locked on the surface of the nanocrystallites, is further probed by small-angle neutron scattering on single-core colloids. Analysis showed that the MAA segments selectively populate the area around the magnetic nanocrystallites, while the poly(ethylene glycol)-grafted chains are arranged as protrusions, pointing towards the aqueous environment. These nanocarriers are screened at various pHs and in highly salted media by light scattering and electrokinetic measurements. According to the results, their stability is dramatically enhanced, as compared to uncoated nanocrystallites, owing to the presence of the external protective PEG canopy. The nanocarriers are also endowed with bio-repellent properties, as evidenced by stability assays using human blood plasma as the medium. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Temperature and frequency response of conductivity in Ag2S doped chalcogenide glassy semiconductor

    NASA Astrophysics Data System (ADS)

    Ojha, Swarupa; Das, Anindya Sundar; Roy, Madhab; Bhattacharya, Sanjib

    2018-06-01

    The electric conductivity of chalcogenide glassy semiconductor xAg2S-(1-x)(0.5S-0.5Te) has been presented here as a function of temperature and frequency. Formation of different nanocrystallites has been confirmed from X-ray diffraction study. It is also noteworthy that average size of nanocrystallites decreases with the increase of dislocation density. Dc conductivity data have been interpreted using Mott's model and Greaves's model in low and high temperature regions respectively. Ac conductivity above the room temperature has been analyzed using Meyer-Neldel (MN) conduction rule. It is interestingly noted that Correlated Barrier Hopping (CBH) model is the most appropriate conduction mechanism for x = 0.35, where pairs of charge carrier are considered to hop over the potential barrier between the sites via thermal activation. To interpret experimental data for x = 0.45, modified non-overlapping small polaron tunnelling (NSPT) model is supposed to be appropriate model due to tunnelling through grain boundary. The conductivity spectra at various temperatures have been analyzed using Almond-West Formalism (power law model). Scaling of conductivity spectra reveals that electrical relaxation process of charge carriers (polaron) is temperature independent but depends upon the composition of the present chalcogenide glassy system.

  16. Rule-based simulation models

    NASA Technical Reports Server (NTRS)

    Nieten, Joseph L.; Seraphine, Kathleen M.

    1991-01-01

    Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

  17. A composite material with CeO2-ZrO2 nanocrystallines embedded in SiO2 matrices and its enhanced thermal stability and oxygen storage capacity

    NASA Astrophysics Data System (ADS)

    Yang, Runnong; Liu, Yumei; Yu, Lin; Zhao, Xiangyun; Yang, Xiaobo; Sun, Ming; Luo, Junyin; Fan, Qun; Xiao, Jianming; Zhao, Yuzhong

    2018-06-01

    A simple hydrothermal procedure is introduced, which leads to the successful synthesis of a new composite material with fine CeO2-ZrO2 nanocrystallites embedded in amorphous and porous SiO2 matrices. The composite material possesses an extraordinary high thermal stability. After being calcined at 1000 °C, it retains CeO2-ZrO2 nanocrystallites of the size around 5 nm, a BET-specific surface area of 165 m2/g, and an oxygen storage capacity of 468 μmol/g. No phase segregation for CeO2-ZrO2 nanocrystallites is detected and the SiO2 matrices remain not crystallized. The composite material shows a great potential as a support of three-way catalyst, as evidenced in catalytic tests with supported Pt.

  18. Hierarchical Model for the Analysis of Scattering Data of Complex Materials

    DOE PAGES

    Oyedele, Akinola; Mcnutt, Nicholas W.; Rios, Orlando; ...

    2016-05-16

    Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replacedmore » by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.« less

  19. Supercubes, Supersquares, and Superrods of Face-Centered Cubes (FCC): Atomic and Electronic Requirements of [Mm(SR)l(PR'3)8]q Nanoclusters (M = Coinage Metals) and Their Implications with Respect to Nucleation and Growth of FCC Metals.

    PubMed

    Teo, Boon K; Yang, Huayan; Yan, Juanzhu; Zheng, Nanfeng

    2017-10-02

    Understanding the nucleation and growth pathways of nanocrystallites allows precise control of the size and shape of functional crystalline nanomaterials of importance in nanoscience and nanotechnology. This paper provides a detailed analysis of the stereochemical and electronic requirements of three series of nanoclusters based on face-centered cubes (fcc) as the basic building blocks, namely, 1-, 2-, and 3-D assemblages of fcc to form superrods (n), supersquares (n 2 ), and supercubes (n 3 ). The generating functions for calculating the numbers (and arrangements) of surface and interior metal atoms, as well as the number and dispositions of the ligands, for these particular sequences of fcc metal clusters of the general formula [M m (SR) l (PR' 3 ) 8 ] q (where M = coinage metals; SR = thiolates (or group XI ligands), and PR' 3 = phosphines) are presented. An electron-counting scheme based on the jelliumatic shell nodel, a variant of the jellium model, predicts the electron requirements and hence the chemical compositions that are critical in the design and synthesis of the next generation of giant nanoclusters in the nanorealm. The ligand binding specificities, which are keys to effective surface ligand control of the size and shape of these nanoclusters, are defined. Finally, a connection is made with regard to the growth of fcc metals, n 3 , from fcc supercubes (n < 10) to fcc nanocrystallites/particles (10 < n < 10 2 ) and to fcc bulk phase (n > 10 2 ).

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

    Duan, Yandong; Zhang, Bingkai; Zheng, Jiaxin

    Abstract. Due to the enhanced kinetic properties, nanocrystallites have received much attention as potential electrode materials for energy storage. However, because of the large specific surface areas of nanocrystallites, they usually suffer from decreased energy density, reduced cycling stability and total electrode capacity. In this work, we report a size-dependent excess capacity beyond the theoretical value of 170 mAhg-1 in a special carbon coated LiFePO4 composite cathode material, which delivers capacities of 191.2 and 213.5 mAhg-1 with the mean particle sizes of 83 nm and 42 nm, respectively. Moreover, this LiFePO4 composite also shows excellent cycling stability and high ratemore » performance. Our further experimental tests and ab initio calculations reveal that the excess capacity comes from the charge passivation for which the C-O-Fe bonds would lead to charge redistribution on the surface of LiFePO4 and hence to enhance the bonding interaction between surface O atoms and Li-ions. The surface reconstruction for excess Li-ion storage makes full use of the large specific surface area for the nanocrystallites, which can maintain the fast Li-ion transport and enhance the capacity greatly that the nanocrystallites usually suffers.« less

  1. Superparamagnetism in carbon-coated Co particles produced by the Kratschmer carbon arc process

    NASA Astrophysics Data System (ADS)

    McHenry, M. E.; Majetich, S. A.; Artman, J. O.; Degraef, M.; Staley, S. W.

    1994-04-01

    A process based on the Kratschmer-Huffman carbon arc method of preparing fullerenes has been used to generate carbon-coated cobalt and cobalt carbide nanocrystallites. Magnetic nanocrystallites are extracted from the soot with a gradient field technique. For Co/C composites, structural characterization by x-ray diffraction and high-resolution transmission electron microscopy reveals the presence of a fcc Co phase, graphite, and a minority Co2C phase. The majority of Co nanocrystals exists as nominally spherical particles, 0.5-5 nm in radius. Hysteretic and temperature-dependent magnetic response, in randomly and magnetically aligned powder samples frozen in epoxy reveals fine-particle magnetism associated with monodomain Co particles. The magnetization exhibits a unique functional dependence on H/T, and hysteresis below a blocking temperature, TB~=160 K. Below TB, the temperature dependence of the coercivity is given by Hc=Hci[1-(T/TB)1/2], with Hci~=450 Oe.

  2. Base Flow Model Validation

    NASA Technical Reports Server (NTRS)

    Sinha, Neeraj; Brinckman, Kevin; Jansen, Bernard; Seiner, John

    2011-01-01

    A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.

  3. Model-Based Safety Analysis

    NASA Technical Reports Server (NTRS)

    Joshi, Anjali; Heimdahl, Mats P. E.; Miller, Steven P.; Whalen, Mike W.

    2006-01-01

    System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

  4. Model-free and model-based reward prediction errors in EEG.

    PubMed

    Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

    2018-05-24

    Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

  5. Guide to APA-Based Models

    NASA Technical Reports Server (NTRS)

    Robins, Robert E.; Delisi, Donald P.

    2008-01-01

    In Robins and Delisi (2008), a linear decay model, a new IGE model by Sarpkaya (2006), and a series of APA-Based models were scored using data from three airports. This report is a guide to the APA-based models.

  6. Gradient-based model calibration with proxy-model assistance

    NASA Astrophysics Data System (ADS)

    Burrows, Wesley; Doherty, John

    2016-02-01

    Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

  7. Model based design introduction: modeling game controllers to microprocessor architectures

    NASA Astrophysics Data System (ADS)

    Jungwirth, Patrick; Badawy, Abdel-Hameed

    2017-04-01

    We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

  8. The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

    NASA Astrophysics Data System (ADS)

    McConnell, William J.

    Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed

  9. EPR-based material modelling of soils

    NASA Astrophysics Data System (ADS)

    Faramarzi, Asaad; Alani, Amir M.

    2013-04-01

    In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.

  10. Testing Strategies for Model-Based Development

    NASA Technical Reports Server (NTRS)

    Heimdahl, Mats P. E.; Whalen, Mike; Rajan, Ajitha; Miller, Steven P.

    2006-01-01

    This report presents an approach for testing artifacts generated in a model-based development process. This approach divides the traditional testing process into two parts: requirements-based testing (validation testing) which determines whether the model implements the high-level requirements and model-based testing (conformance testing) which determines whether the code generated from a model is behaviorally equivalent to the model. The goals of the two processes differ significantly and this report explores suitable testing metrics and automation strategies for each. To support requirements-based testing, we define novel objective requirements coverage metrics similar to existing specification and code coverage metrics. For model-based testing, we briefly describe automation strategies and examine the fault-finding capability of different structural coverage metrics using tests automatically generated from the model.

  11. Model-based machine learning.

    PubMed

    Bishop, Christopher M

    2013-02-13

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

  12. Model-based machine learning

    PubMed Central

    Bishop, Christopher M.

    2013-01-01

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications. PMID:23277612

  13. Model-based surgical planning and simulation of cranial base surgery.

    PubMed

    Abe, M; Tabuchi, K; Goto, M; Uchino, A

    1998-11-01

    Plastic skull models of seven individual patients were fabricated by stereolithography from three-dimensional data based on computed tomography bone images. Skull models were utilized for neurosurgical planning and simulation in the seven patients with cranial base lesions that were difficult to remove. Surgical approaches and areas of craniotomy were evaluated using the fabricated skull models. In preoperative simulations, hand-made models of the tumors, major vessels and nerves were placed in the skull models. Step-by-step simulation of surgical procedures was performed using actual surgical tools. The advantages of using skull models to plan and simulate cranial base surgery include a better understanding of anatomic relationships, preoperative evaluation of the proposed procedure, increased understanding by the patient and family, and improved educational experiences for residents and other medical staff. The disadvantages of using skull models include the time and cost of making the models. The skull models provide a more realistic tool that is easier to handle than computer-graphic images. Surgical simulation using models facilitates difficult cranial base surgery and may help reduce surgical complications.

  14. PID-based error signal modeling

    NASA Astrophysics Data System (ADS)

    Yohannes, Tesfay

    1997-10-01

    This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

  15. Constraint Based Modeling Going Multicellular.

    PubMed

    Martins Conde, Patricia do Rosario; Sauter, Thomas; Pfau, Thomas

    2016-01-01

    Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

  16. In situ SAXS study on size changes of platinum nanoparticles with temperature

    NASA Astrophysics Data System (ADS)

    Wang, W.; Chen, X.; Cai, Q.; Mo, G.; Jiang, L. S.; Zhang, K.; Chen, Z. J.; Wu, Z. H.; Pan, W.

    2008-09-01

    Poly(vinylpyrrolidone) (PVP)-coated platinum (Pt) nanoparticles were prepared in methanol-water reduction method. In situ small-angle X-ray scattering (SAXS) and X-ray diffraction (XRD) techniques were used to probe the size change of particles and crystallites with temperature. Tangent-by-tangent (TBT) method of SAXS data analysis was improved and used to get the particle size distribution (PSD) from SAXS intensity. Scherrer’s equation was used to derive the crystallite size from XRD pattern. Combining SAXS and XRD results, a step-like characteristic of the Pt nanoparticle growth has been found. Three stages (diffusion, aggregation, and agglomeration) can be used to describe the growth of the Pt nanoparticles and nanocrystallites. Aggregation was found to be the main growth mode of the Pt nanoparticles during heating. The maximum growth rates of Pt nanoparticles and Pt nanocrystallites, as well as the maximum aggregation degree of Pt nanocrystallites were found, respectively, at 250 °C, 350 °C and 300 °C. These results are helpful to understanding the growth mode of nanoparticles, as well as controlling the nanoparticle size.

  17. Model-based software design

    NASA Technical Reports Server (NTRS)

    Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui; Yenne, Britt; Vansickle, Larry; Ballantyne, Michael

    1992-01-01

    Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

  18. Measurement-based reliability/performability models

    NASA Technical Reports Server (NTRS)

    Hsueh, Mei-Chen

    1987-01-01

    Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

  19. The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

    PubMed

    Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

    2016-02-01

    Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

  20. The Use of Modeling-Based Text to Improve Students' Modeling Competencies

    ERIC Educational Resources Information Center

    Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

    2015-01-01

    This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

  1. [Modeling in value-based medicine].

    PubMed

    Neubauer, A S; Hirneiss, C; Kampik, A

    2010-03-01

    Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

  2. Automated visualization of rule-based models

    PubMed Central

    Tapia, Jose-Juan; Faeder, James R.

    2017-01-01

    Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

  3. A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

    PubMed

    Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

    2018-01-01

    Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

  4. Knowledge-Based Environmental Context Modeling

    NASA Astrophysics Data System (ADS)

    Pukite, P. R.; Challou, D. J.

    2017-12-01

    As we move from the oil-age to an energy infrastructure based on renewables, the need arises for new educational tools to support the analysis of geophysical phenomena and their behavior and properties. Our objective is to present models of these phenomena to make them amenable for incorporation into more comprehensive analysis contexts. Starting at the level of a college-level computer science course, the intent is to keep the models tractable and therefore practical for student use. Based on research performed via an open-source investigation managed by DARPA and funded by the Department of Interior [1], we have adapted a variety of physics-based environmental models for a computer-science curriculum. The original research described a semantic web architecture based on patterns and logical archetypal building-blocks (see figure) well suited for a comprehensive environmental modeling framework. The patterns span a range of features that cover specific land, atmospheric and aquatic domains intended for engineering modeling within a virtual environment. The modeling engine contained within the server relied on knowledge-based inferencing capable of supporting formal terminology (through NASA JPL's Semantic Web for Earth and Environmental Technology (SWEET) ontology and a domain-specific language) and levels of abstraction via integrated reasoning modules. One of the key goals of the research was to simplify models that were ordinarily computationally intensive to keep them lightweight enough for interactive or virtual environment contexts. The breadth of the elements incorporated is well-suited for learning as the trend toward ontologies and applying semantic information is vital for advancing an open knowledge infrastructure. As examples of modeling, we have covered such geophysics topics as fossil-fuel depletion, wind statistics, tidal analysis, and terrain modeling, among others. Techniques from the world of computer science will be necessary to promote efficient

  5. Micromechanics based phenomenological damage modeling

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

    Muju, S.; Anderson, P.M.; Popelar, C.H.

    A model is developed for the study of process zone effects on dominant cracks. The model proposed here is intended to bridge the gap between the micromechanics based and the phenomenological models for the class of problems involving microcracking, transforming inclusions etc. It is based on representation of localized eigenstrains using dislocation dipoles. The eigenstrain (fitting strain) is represented as the strength (Burgers vector) of the dipole which obeys a certain phenomenological constitutive relation.

  6. Model-Based Systems

    NASA Technical Reports Server (NTRS)

    Frisch, Harold P.

    2007-01-01

    Engineers, who design systems using text specification documents, focus their work upon the completed system to meet Performance, time and budget goals. Consistency and integrity is difficult to maintain within text documents for a single complex system and more difficult to maintain as several systems are combined into higher-level systems, are maintained over decades, and evolve technically and in performance through updates. This system design approach frequently results in major changes during the system integration and test phase, and in time and budget overruns. Engineers who build system specification documents within a model-based systems environment go a step further and aggregate all of the data. They interrelate all of the data to insure consistency and integrity. After the model is constructed, the various system specification documents are prepared, all from the same database. The consistency and integrity of the model is assured, therefore the consistency and integrity of the various specification documents is insured. This article attempts to define model-based systems relative to such an environment. The intent is to expose the complexity of the enabling problem by outlining what is needed, why it is needed and how needs are being addressed by international standards writing teams.

  7. Off-target model based OPC

    NASA Astrophysics Data System (ADS)

    Lu, Mark; Liang, Curtis; King, Dion; Melvin, Lawrence S., III

    2005-11-01

    Model-based Optical Proximity correction has become an indispensable tool for achieving wafer pattern to design fidelity at current manufacturing process nodes. Most model-based OPC is performed considering the nominal process condition, with limited consideration of through process manufacturing robustness. This study examines the use of off-target process models - models that represent non-nominal process states such as would occur with a dose or focus variation - to understands and manipulate the final pattern correction to a more process robust configuration. The study will first examine and validate the process of generating an off-target model, then examine the quality of the off-target model. Once the off-target model is proven, it will be used to demonstrate methods of generating process robust corrections. The concepts are demonstrated using a 0.13 μm logic gate process. Preliminary indications show success in both off-target model production and process robust corrections. With these off-target models as tools, mask production cycle times can be reduced.

  8. Culturicon model: A new model for cultural-based emoticon

    NASA Astrophysics Data System (ADS)

    Zukhi, Mohd Zhafri Bin Mohd; Hussain, Azham

    2017-10-01

    Emoticons are popular among distributed collective interaction user in expressing their emotion, gestures and actions. Emoticons have been proved to be able to avoid misunderstanding of the message, attention saving and improved the communications among different native speakers. However, beside the benefits that emoticons can provide, the study regarding emoticons in cultural perspective is still lacking. As emoticons are crucial in global communication, culture should be one of the extensively research aspect in distributed collective interaction. Therefore, this study attempt to explore and develop model for cultural-based emoticon. Three cultural models that have been used in Human-Computer Interaction were studied which are the Hall Culture Model, Trompenaars and Hampden Culture Model and Hofstede Culture Model. The dimensions from these three models will be used in developing the proposed cultural-based emoticon model.

  9. Least-squares model-based halftoning

    NASA Astrophysics Data System (ADS)

    Pappas, Thrasyvoulos N.; Neuhoff, David L.

    1992-08-01

    A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach

  10. ALC: automated reduction of rule-based models

    PubMed Central

    Koschorreck, Markus; Gilles, Ernst Dieter

    2008-01-01

    Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705

  11. Model-based predictions for dopamine.

    PubMed

    Langdon, Angela J; Sharpe, Melissa J; Schoenbaum, Geoffrey; Niv, Yael

    2018-04-01

    Phasic dopamine responses are thought to encode a prediction-error signal consistent with model-free reinforcement learning theories. However, a number of recent findings highlight the influence of model-based computations on dopamine responses, and suggest that dopamine prediction errors reflect more dimensions of an expected outcome than scalar reward value. Here, we review a selection of these recent results and discuss the implications and complications of model-based predictions for computational theories of dopamine and learning. Copyright © 2017. Published by Elsevier Ltd.

  12. Model-Based Prognostics of Hybrid Systems

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

    2015-01-01

    Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

  13. A Correlation-Based Transition Model using Local Variables. Part 1; Model Formation

    NASA Technical Reports Server (NTRS)

    Menter, F. R.; Langtry, R. B.; Likki, S. R.; Suzen, Y. B.; Huang, P. G.; Volker, S.

    2006-01-01

    A new correlation-based transition model has been developed, which is based strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics (CFD) approaches, such as unstructured grids and massive parallel execution. The model is based on two transport equations, one for intermittency and one for the transition onset criteria in terms of momentum thickness Reynolds number. The proposed transport equations do not attempt to model the physics of the transition process (unlike, e.g., turbulence models) but from a framework for the implementation of correlation-based models into general-purpose CFD methods.

  14. Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

    PubMed

    Ulloa, Antonio; Horwitz, Barry

    2016-01-01

    A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional

  15. Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex

    PubMed Central

    Ulloa, Antonio; Horwitz, Barry

    2016-01-01

    A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were “non-task-specific” (NS) neurons that served as noise generators to “task-specific” neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional

  16. When Does Model-Based Control Pay Off?

    PubMed

    Kool, Wouter; Cushman, Fiery A; Gershman, Samuel J

    2016-08-01

    Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to "model-free" and "model-based" strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.

  17. Model Based Definition

    NASA Technical Reports Server (NTRS)

    Rowe, Sidney E.

    2010-01-01

    In September 2007, the Engineering Directorate at the Marshall Space Flight Center (MSFC) created the Design System Focus Team (DSFT). MSFC was responsible for the in-house design and development of the Ares 1 Upper Stage and the Engineering Directorate was preparing to deploy a new electronic Configuration Management and Data Management System with the Design Data Management System (DDMS) based upon a Commercial Off The Shelf (COTS) Product Data Management (PDM) System. The DSFT was to establish standardized CAD practices and a new data life cycle for design data. Of special interest here, the design teams were to implement Model Based Definition (MBD) in support of the Upper Stage manufacturing contract. It is noted that this MBD does use partially dimensioned drawings for auxiliary information to the model. The design data lifecycle implemented several new release states to be used prior to formal release that allowed the models to move through a flow of progressive maturity. The DSFT identified some 17 Lessons Learned as outcomes of the standards development, pathfinder deployments and initial application to the Upper Stage design completion. Some of the high value examples are reviewed.

  18. Evaluating model accuracy for model-based reasoning

    NASA Technical Reports Server (NTRS)

    Chien, Steve; Roden, Joseph

    1992-01-01

    Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

  19. Model-based monitoring and diagnosis of a satellite-based instrument

    NASA Technical Reports Server (NTRS)

    Bos, Andre; Callies, Jorg; Lefebvre, Alain

    1995-01-01

    For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

  20. Model-based monitoring and diagnosis of a satellite-based instrument

    NASA Astrophysics Data System (ADS)

    Bos, Andre; Callies, Jorg; Lefebvre, Alain

    1995-05-01

    For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

  1. PDF-based heterogeneous multiscale filtration model.

    PubMed

    Gong, Jian; Rutland, Christopher J

    2015-04-21

    Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.

  2. AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

    PubMed Central

    Bruch, Elizabeth; Atwell, Jon

    2014-01-01

    Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

  3. Model-based choices involve prospective neural activity

    PubMed Central

    Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.

    2015-01-01

    Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041

  4. Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

    NASA Astrophysics Data System (ADS)

    Galelli, S.; Castelletti, A.

    2012-12-01

    In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the

  5. A Comparison of Filter-based Approaches for Model-based Prognostics

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew John; Saha, Bhaskar; Goebel, Kai

    2012-01-01

    Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

  6. Using Model Replication to Improve the Reliability of Agent-Based Models

    NASA Astrophysics Data System (ADS)

    Zhong, Wei; Kim, Yushim

    The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

  7. Model-based RSA of a femoral hip stem using surface and geometrical shape models.

    PubMed

    Kaptein, Bart L; Valstar, Edward R; Spoor, Cees W; Stoel, Berend C; Rozing, Piet M

    2006-07-01

    Roentgen stereophotogrammetry (RSA) is a highly accurate three-dimensional measuring technique for assessing micromotion of orthopaedic implants. A drawback is that markers have to be attached to the implant. Model-based techniques have been developed to prevent using special marked implants. We compared two model-based RSA methods with standard marker-based RSA techniques. The first model-based RSA method used surface models, and the second method used elementary geometrical shape (EGS) models. We used a commercially available stem to perform experiments with a phantom as well as reanalysis of patient RSA radiographs. The data from the phantom experiment indicated the accuracy and precision of the elementary geometrical shape model-based RSA method is equal to marker-based RSA. For model-based RSA using surface models, the accuracy is equal to the accuracy of marker-based RSA, but its precision is worse. We found no difference in accuracy and precision between the two model-based RSA techniques in clinical data. For this particular hip stem, EGS model-based RSA is a good alternative for marker-based RSA.

  8. Stimulating Scientific Reasoning with Drawing-Based Modeling

    NASA Astrophysics Data System (ADS)

    Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

    2018-02-01

    We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each iteration, the user interface and instructions were adjusted based on students' remarks and the teacher's observations. Students' conversations were analyzed on reasoning complexity as a measurement of efficacy of the modeling tool and the instructions. These findings were also used to compose a set of recommendations for teachers and curriculum designers for using and constructing models in the classroom. Our findings suggest that to stimulate scientific reasoning in students working with a drawing-based modeling, tool instruction about the tool and the domain should be integrated. In creating models, a sufficient level of scaffolding is necessary. Without appropriate scaffolds, students are not able to create the model. With scaffolding that is too high, students may show reasoning that incorrectly assigns external causes to behavior in the model.

  9. Model based manipulator control

    NASA Technical Reports Server (NTRS)

    Petrosky, Lyman J.; Oppenheim, Irving J.

    1989-01-01

    The feasibility of using model based control (MBC) for robotic manipulators was investigated. A double inverted pendulum system was constructed as the experimental system for a general study of dynamically stable manipulation. The original interest in dynamically stable systems was driven by the objective of high vertical reach (balancing), and the planning of inertially favorable trajectories for force and payload demands. The model-based control approach is described and the results of experimental tests are summarized. Results directly demonstrate that MBC can provide stable control at all speeds of operation and support operations requiring dynamic stability such as balancing. The application of MBC to systems with flexible links is also discussed.

  10. Practical Application of Model-based Programming and State-based Architecture to Space Missions

    NASA Technical Reports Server (NTRS)

    Horvath, Gregory; Ingham, Michel; Chung, Seung; Martin, Oliver; Williams, Brian

    2006-01-01

    A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

  11. When Does Model-Based Control Pay Off?

    PubMed Central

    2016-01-01

    Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to “model-free” and “model-based” strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand. PMID:27564094

  12. Models of Quantitative Estimations: Rule-Based and Exemplar-Based Processes Compared

    ERIC Educational Resources Information Center

    von Helversen, Bettina; Rieskamp, Jorg

    2009-01-01

    The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model--the mapping model--that outperformed the…

  13. Atom-Role-Based Access Control Model

    NASA Astrophysics Data System (ADS)

    Cai, Weihong; Huang, Richeng; Hou, Xiaoli; Wei, Gang; Xiao, Shui; Chen, Yindong

    Role-based access control (RBAC) model has been widely recognized as an efficient access control model and becomes a hot research topic of information security at present. However, in the large-scale enterprise application environments, the traditional RBAC model based on the role hierarchy has the following deficiencies: Firstly, it is unable to reflect the role relationships in complicated cases effectively, which does not accord with practical applications. Secondly, the senior role unconditionally inherits all permissions of the junior role, thus if a user is under the supervisor role, he may accumulate all permissions, and this easily causes the abuse of permission and violates the least privilege principle, which is one of the main security principles. To deal with these problems, we, after analyzing permission types and role relationships, proposed the concept of atom role and built an atom-role-based access control model, called ATRBAC, by dividing the permission set of each regular role based on inheritance path relationships. Through the application-specific analysis, this model can well meet the access control requirements.

  14. NASA Software Cost Estimation Model: An Analogy Based Estimation Model

    NASA Technical Reports Server (NTRS)

    Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

    2015-01-01

    The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

  15. Characterization of core/shell structures based on CdTe and GaAs nanocrystalline layers deposited on SnO2 microwires

    NASA Astrophysics Data System (ADS)

    Ghimpu, L.; Ursaki, V. V.; Pantazi, A.; Mesterca, R.; Brâncoveanu, O.; Shree, Sindu; Adelung, R.; Tiginyanu, I. M.; Enachescu, M.

    2018-04-01

    We report the fabrication and characterization of SnO2/CdTe and SnO2/GaAs core/shell microstructures. CdTe or GaAs shell layers were deposited by radio-frequency (RF) magnetron sputtering on core SnO2 microwires synthesized by a flame-based thermal oxidation method. The produced structures were characterized by scanning electron microscopy (SEM), high-resolution scanning transmission electron microscope (HR-STEM), X-ray diffraction (XRD), Raman scattering and FTIR spectroscopy. It was found that the SnO2 core is of the rutile type, while the shells are composed of CdTe or GaAs nanocrystallites of zincblende structure with the dimensions of crystallites in the range of 10-20 nm. The Raman scattering investigations demonstrated that the quality of the porous nanostructured shell is improved by annealing at temperatures of 420-450 °C. The prospects of implementing these microstructures in intrinsic type fiber optic sensors are discussed.

  16. Dielectric response of a nondegenerate electron gas in semiconductor nanocrystallites

    NASA Astrophysics Data System (ADS)

    van Faassen, E.

    1998-12-01

    We investigate the low-frequency dielectric response of a dilute electron gas in a small spherical semiconductor particle. The flow of the electrons is described by hydrodynamic equations which incorporate the electrostatic interactions between the electrons in a self-consistent fashion. In the low-frequency regime, the dielectric loss is small and proportional to the frequency, despite substantial field penetration into the semiconductor. The loss remains small even for high doping levels due to effective cancellation between field-induced drift and diffusion. The model is used to estimate the complex dielectric constant of a system of weakly conducting nanosized semiconductor particles. The most prominent manifestation of spatial dispersion is that photoinduced changes in the real and imaginary parts of the dielectric constant are positive and of comparable magnitude.

  17. Modeling Guru: Knowledge Base for NASA Modelers

    NASA Astrophysics Data System (ADS)

    Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

    2009-05-01

    Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

  18. Predictive representations can link model-based reinforcement learning to model-free mechanisms.

    PubMed

    Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

    2017-09-01

    Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

  19. Predictive representations can link model-based reinforcement learning to model-free mechanisms

    PubMed Central

    Botvinick, Matthew M.

    2017-01-01

    Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

  20. Stimulating Scientific Reasoning with Drawing-Based Modeling

    ERIC Educational Resources Information Center

    Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

    2018-01-01

    We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

  1. Microstructures, mechanical behavior and strengthening mechanism of TiSiCN nanocomposite films

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

    Li, Wei; Liu, Ping; Xue, Zenghui

    Recently, the arguments have existed in the strengthening mechanism and microstructural model of the nanocomposite film due to lack of the convincible experimental evidences. In this investigation, the quarternary TiSiCN nanocomposite films with the different C and Si contents are synthesized by the reactive-magnetron-sputtering technique. The TiSiCN film is characterized as the nanocomposite structure with the TiN nanocrystallites surrounded by the (Si 3N 4 + C + CN x) interface phase. When the C/Si content ratio is 2:2, the TiSiCN nanocomposite film is remarkably strengthened with the maximal hardness and elastic modulus of 46.1 GPa and 425 GPa, respectively. Meanwhile,more » the (Si 3N 4 + C + CN x) interfaces exhibit as a crystallized form, which can coordinate the growth misorientations and maintain the coherently epitaxial growth between the TiN nanocrystallites and interfaces. Through the high-resolution transmission electron microscopy (HRTEM) observations, this investigation firstly provides the direct experimental evidence for the crystallized feature of the interfaces when the TiSiCN nanocomposite film is strengthened, suggesting that the strengthening effect of the TiSiCN nanocomposite film can be attributed to the coherent-interface strengthening mechanism, which is expressed as the “nc-TiN/c-Si 3N 4/c-C/c-CN x” model.« less

  2. Microstructures, mechanical behavior and strengthening mechanism of TiSiCN nanocomposite films

    DOE PAGES

    Li, Wei; Liu, Ping; Xue, Zenghui; ...

    2017-05-18

    Recently, the arguments have existed in the strengthening mechanism and microstructural model of the nanocomposite film due to lack of the convincible experimental evidences. In this investigation, the quarternary TiSiCN nanocomposite films with the different C and Si contents are synthesized by the reactive-magnetron-sputtering technique. The TiSiCN film is characterized as the nanocomposite structure with the TiN nanocrystallites surrounded by the (Si 3N 4 + C + CN x) interface phase. When the C/Si content ratio is 2:2, the TiSiCN nanocomposite film is remarkably strengthened with the maximal hardness and elastic modulus of 46.1 GPa and 425 GPa, respectively. Meanwhile,more » the (Si 3N 4 + C + CN x) interfaces exhibit as a crystallized form, which can coordinate the growth misorientations and maintain the coherently epitaxial growth between the TiN nanocrystallites and interfaces. Through the high-resolution transmission electron microscopy (HRTEM) observations, this investigation firstly provides the direct experimental evidence for the crystallized feature of the interfaces when the TiSiCN nanocomposite film is strengthened, suggesting that the strengthening effect of the TiSiCN nanocomposite film can be attributed to the coherent-interface strengthening mechanism, which is expressed as the “nc-TiN/c-Si 3N 4/c-C/c-CN x” model.« less

  3. Agent-based modeling: case study in cleavage furrow models.

    PubMed

    Mogilner, Alex; Manhart, Angelika

    2016-11-07

    The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as "differential equation based" (DE) or "agent based" (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem-positioning of the cleavage furrow in dividing cells-to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. © 2016 Mogilner and Manhart. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  4. Identification of walking human model using agent-based modelling

    NASA Astrophysics Data System (ADS)

    Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

    2018-03-01

    The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

  5. Ground-Based Telescope Parametric Cost Model

    NASA Technical Reports Server (NTRS)

    Stahl, H. Philip; Rowell, Ginger Holmes

    2004-01-01

    A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

  6. Rule-based modeling with Virtual Cell

    PubMed Central

    Schaff, James C.; Vasilescu, Dan; Moraru, Ion I.; Loew, Leslie M.; Blinov, Michael L.

    2016-01-01

    Summary: Rule-based modeling is invaluable when the number of possible species and reactions in a model become too large to allow convenient manual specification. The popular rule-based software tools BioNetGen and NFSim provide powerful modeling and simulation capabilities at the cost of learning a complex scripting language which is used to specify these models. Here, we introduce a modeling tool that combines new graphical rule-based model specification with existing simulation engines in a seamless way within the familiar Virtual Cell (VCell) modeling environment. A mathematical model can be built integrating explicit reaction networks with reaction rules. In addition to offering a large choice of ODE and stochastic solvers, a model can be simulated using a network free approach through the NFSim simulation engine. Availability and implementation: Available as VCell (versions 6.0 and later) at the Virtual Cell web site (http://vcell.org/). The application installs and runs on all major platforms and does not require registration for use on the user’s computer. Tutorials are available at the Virtual Cell website and Help is provided within the software. Source code is available at Sourceforge. Contact: vcell_support@uchc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27497444

  7. SLS Navigation Model-Based Design Approach

    NASA Technical Reports Server (NTRS)

    Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

    2018-01-01

    The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

  8. An Object-Based Requirements Modeling Method.

    ERIC Educational Resources Information Center

    Cordes, David W.; Carver, Doris L.

    1992-01-01

    Discusses system modeling and specification as it relates to object-based information systems development and software development. An automated system model based on the objects in the initial requirements document is described, the requirements document translator is explained, and a sample application of the technique is provided. (12…

  9. A logical model of cooperating rule-based systems

    NASA Technical Reports Server (NTRS)

    Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

    1989-01-01

    A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

  10. Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

    NASA Astrophysics Data System (ADS)

    Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

    2017-12-01

    This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

  11. Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

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

    Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

    System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

  12. Origin of Analyte-Induced Porous Silicon Photoluminescence Quenching.

    PubMed

    Reynard, Justin M; Van Gorder, Nathan S; Bright, Frank V

    2017-09-01

    We report on gaseous analyte-induced photoluminescence (PL) quenching of porous silicon, as-prepared (ap-pSi) and oxidized (ox-pSi). By using steady-state and emission wavelength-dependent time-resolved intensity luminescence measurements in concert with a global analysis scheme, we find that the analyte-induced quenching is best described by a three-component static quenching model. In the model, there are blue, green, and red emitters (associated with the nanocrystallite core and surface trap states) that each exhibit unique analyte-emitter association constants and these association constants are a consequence of differences in the pSi surface chemistries.

  13. Data-based Non-Markovian Model Inference

    NASA Astrophysics Data System (ADS)

    Ghil, Michael

    2015-04-01

    This talk concentrates on obtaining stable and efficient data-based models for simulation and prediction in the geosciences and life sciences. The proposed model derivation relies on using a multivariate time series of partial observations from a large-dimensional system, and the resulting low-order models are compared with the optimal closures predicted by the non-Markovian Mori-Zwanzig formalism of statistical physics. Multilayer stochastic models (MSMs) are introduced as both a very broad generalization and a time-continuous limit of existing multilevel, regression-based approaches to data-based closure, in particular of empirical model reduction (EMR). We show that the multilayer structure of MSMs can provide a natural Markov approximation to the generalized Langevin equation (GLE) of the Mori-Zwanzig formalism. A simple correlation-based stopping criterion for an EMR-MSM model is derived to assess how well it approximates the GLE solution. Sufficient conditions are given for the nonlinear cross-interactions between the constitutive layers of a given MSM to guarantee the existence of a global random attractor. This existence ensures that no blow-up can occur for a very broad class of MSM applications. The EMR-MSM methodology is first applied to a conceptual, nonlinear, stochastic climate model of coupled slow and fast variables, in which only slow variables are observed. The resulting reduced model with energy-conserving nonlinearities captures the main statistical features of the slow variables, even when there is no formal scale separation and the fast variables are quite energetic. Second, an MSM is shown to successfully reproduce the statistics of a partially observed, generalized Lokta-Volterra model of population dynamics in its chaotic regime. The positivity constraint on the solutions' components replaces here the quadratic-energy-preserving constraint of fluid-flow problems and it successfully prevents blow-up. This work is based on a close

  14. Comparison of chiller models for use in model-based fault detection

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

    Sreedharan, Priya; Haves, Philip

    Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolTools{trademark}, which ismore » empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.« less

  15. Synthesis of TiO2 nanoparticles by hydrolysis and peptization of titanium isopropoxide solution

    NASA Astrophysics Data System (ADS)

    Mahata, S.; Mahato, S. S.; Nandi, M. M.; Mondal, B.

    2012-07-01

    Here we report the synthesis and characterization of a stable suspension of modified titania nanoparticles. Phase-pure TiO2 nanocrystallites with narrow particle-size distributions were selectively prepared by hydrolysis-peptization of modified alkoxide followed by hydrothermal treatment. Autoclaving modified TiO2 in the presence of HNO3 as cooperative catalysts led to the formation of crystalline TiO2 with narrow-sized distribution. Following the hydrothermal treatment at 150°C, X-ray diffraction shows the particles to be exclusively anatase. Synthesized powder is characterized by FT-IR, scanning electron microscopy (FESEM) and transmission electron microscopy (HRTEM). The photocatalytic activity in the degradation of orange-II is quite comparable to good anatase and rutile nanocrystallites.

  16. High temperature magnetism and microstructure of ferromagnetic alloy Si1-x Mn x

    NASA Astrophysics Data System (ADS)

    Aronzon, B. A.; Davydov, A. B.; Vasiliev, A. L.; Perov, N. S.; Novodvorsky, O. A.; Parshina, L. S.; Presniakov, M. Yu; Lahderanta, E.

    2017-02-01

    The results of a detailed study of magnetic properties and of the microstructure of SiMn films with a small deviation from stoichiometry are presented. The aim was to reveal the origin of the high temperature ferromagnetic ordering in such compounds. Unlike SiMn single crystals with the Curie temperature ~30 K, considered Si1-x Mn x compounds with x  =  0.5  +Δx and Δx in the range of 0.01-0.02 demonstrate a ferromagnetic state above room temperature. Such a ferromagnetic state can be explained by the existence of highly defective B20 SiMn nanocrystallites. These defects are Si vacancies, which are suggested to possess magnetic moments. The nanocrystallites interact with each other through paramagnons (magnetic fluctuations) inside a weakly magnetic manganese silicide matrix giving rise to a long range ferromagnetic percolation cluster. The studied structures with a higher value of Δx  ≈  0.05 contained three different magnetic phases: (a)—the low temperature ferromagnetic phase related to SiMn; (b)—the above mentioned high temperature phase with Curie temperature in the range of 200-300 K depending on the growth history and (c)—superparamagnetic phase formed by separated noninteracting SiMn nanocrystallites.

  17. A hybrid agent-based approach for modeling microbiological systems.

    PubMed

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  18. Cognitive components underpinning the development of model-based learning.

    PubMed

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Marker Configuration Model-Based Roentgen Fluoroscopic Analysis.

    PubMed

    Garling, Eric H; Kaptein, Bart L; Geleijns, Koos; Nelissen, Rob G H H; Valstar, Edward R

    2005-04-01

    It remains unknown if and how the polyethylene bearing in mobile bearing knees moves during dynamic activities with respect to the tibial base plate. Marker Configuration Model-Based Roentgen Fluoroscopic Analysis (MCM-based RFA) uses a marker configuration model of inserted tantalum markers in order to accurately estimate the pose of an implant or bone using single plane Roentgen images or fluoroscopic images. The goal of this study is to assess the accuracy of (MCM-Based RFA) in a standard fluoroscopic set-up using phantom experiments and to determine the error propagation with computer simulations. The experimental set-up of the phantom study was calibrated using a calibration box equipped with 600 tantalum markers, which corrected for image distortion and determined the focus position. In the computer simulation study the influence of image distortion, MC-model accuracy, focus position, the relative distance between MC-models and MC-model configuration on the accuracy of MCM-Based RFA were assessed. The phantom study established that the in-plane accuracy of MCM-Based RFA is 0.1 mm and the out-of-plane accuracy is 0.9 mm. The rotational accuracy is 0.1 degrees. A ninth-order polynomial model was used to correct for image distortion. Marker-Based RFA was estimated to have, in a worst case scenario, an in vivo translational accuracy of 0.14 mm (x-axis), 0.17 mm (y-axis), 1.9 mm (z-axis), respectively, and a rotational accuracy of 0.3 degrees. When using fluoroscopy to study kinematics, image distortion and the accuracy of models are important factors, which influence the accuracy of the measurements. MCM-Based RFA has the potential to be an accurate, clinically useful tool for studying kinematics after total joint replacement using standard equipment.

  20. Evaluating Emulation-based Models of Distributed Computing Systems

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

    Jones, Stephen T.; Gabert, Kasimir G.; Tarman, Thomas D.

    Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses andmore » describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.« less

  1. Model-Based Reasoning in Humans Becomes Automatic with Training.

    PubMed

    Economides, Marcos; Kurth-Nelson, Zeb; Lübbert, Annika; Guitart-Masip, Marc; Dolan, Raymond J

    2015-09-01

    Model-based and model-free reinforcement learning (RL) have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

  2. Argumentation in Science Education: A Model-based Framework

    NASA Astrophysics Data System (ADS)

    Böttcher, Florian; Meisert, Anke

    2011-02-01

    The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.

  3. An overview of TOUGH-based geomechanics models

    DOE PAGES

    Rutqvist, Jonny

    2016-09-22

    After the initial development of the first TOUGH-based geomechanics model 15 years ago based on linking TOUGH2 multiphase flow simulator to the FLAC3D geomechanics simulator, at least 15 additional TOUGH-based geomechanics models have appeared in the literature. This development has been fueled by a growing demand and interest for modeling coupled multiphase flow and geomechanical processes related to a number of geoengineering applications, such as in geologic CO 2 sequestration, enhanced geothermal systems, unconventional hydrocarbon production, and most recently, related to reservoir stimulation and injection-induced seismicity. This paper provides a short overview of these TOUGH-based geomechanics models, focusing on somemore » of the most frequently applied to a diverse set of problems associated with geomechanics and its couplings to hydraulic, thermal and chemical processes.« less

  4. Solution-based colloidal synthesis of hybrid P3HT: Ternary CuInSe2 nanocomposites using a novel combination of capping agents for low-cost photovoltaics

    NASA Astrophysics Data System (ADS)

    Sharma, Shailesh Narain; Chawla, Parul; Akanksha; Srivastava, A. K.

    2016-06-01

    In this work, ternary CuInSe2 (CISe) chalcopyrite nanocrystallites efficiently passivated by a novel combination of capping agents viz: aniline and 1-octadecene during chemical route synthesis were dispersed in conducting polymer matrix poly(3-hexylthiophene) (P3HT). By varying the composition and concentration of the ligands, the properties of the resulting CISe nanocrystallites and its corresponding polymer nanocomposites thus could be tailored. The structural, morphological and optical studies accomplished by various complimentary techniques viz. Transmission Electron Microscopy (TEM), Contact angle, Photoluminescence (PL) and Raman have enabled us to compare the different hybrid organic (polymer)-inorganic nanocomposites. On the basis of aniline-octadecene equilibrium phase diagram, the polydispersity of the CISe nanocrystals could be tuned by using controlled variations in the reaction conditions of nucleation and growth such as composition of the solvent and temperature. To the best of author's knowledge, the beneficial effects of both the capping agents; aniline and octadecene contributing well in tandem in the development of large-sized (100-125 nm) high quality, sterically- and photo-oxidative stable polycrystalline CISe and its corresponding polymer (P3HT):CISe composites with enhanced charge transfer efficiency has been reported for the first time. The low-cost synthesis and ease of preparation renders this method of great potential for its possible application in low-cost hybrid organic-inorganic photovoltaics. The figure shows the Temperature vs Mole fraction graph of two different phases (aniline and 1-octadecene) in equilibrium.

  5. Simulating cancer growth with multiscale agent-based modeling.

    PubMed

    Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

    2015-02-01

    There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Simulating Cancer Growth with Multiscale Agent-Based Modeling

    PubMed Central

    Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

    2014-01-01

    There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

  7. Distributed Prognostics based on Structural Model Decomposition

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, I.

    2014-01-01

    Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATIONS

  8. Cognitive Components Underpinning the Development of Model-Based Learning

    PubMed Central

    Potter, Tracey C.S.; Bryce, Nessa V.; Hartley, Catherine A.

    2016-01-01

    Reinforcement learning theory distinguishes “model-free” learning, which fosters reflexive repetition of previously rewarded actions, from “model-based” learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9–25, we examined whether the abilities to infer sequential regularities in the environment (“statistical learning”), maintain information in an active state (“working memory”) and integrate distant concepts to solve problems (“fluid reasoning”) predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. PMID:27825732

  9. Understanding Elementary Astronomy by Making Drawing-Based Models

    NASA Astrophysics Data System (ADS)

    van Joolingen, W. R.; Aukes, Annika V. A.; Gijlers, H.; Bollen, L.

    2015-04-01

    Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a drawing-based model of the solar system. The results show that children in the target age group are capable of creating a drawing-based model of the solar system and can use it to show the situations in which eclipses occur. Structural equation modeling predicting post-test knowledge scores based on learners' pre-test knowledge scores, the quality of their drawings and motivational aspects yielded some evidence that such drawing contributes to learning. Consequences for using modeling with young children are considered.

  10. Qualitative model-based diagnosis using possibility theory

    NASA Technical Reports Server (NTRS)

    Joslyn, Cliff

    1994-01-01

    The potential for the use of possibility in the qualitative model-based diagnosis of spacecraft systems is described. The first sections of the paper briefly introduce the Model-Based Diagnostic (MBD) approach to spacecraft fault diagnosis; Qualitative Modeling (QM) methodologies; and the concepts of possibilistic modeling in the context of Generalized Information Theory (GIT). Then the necessary conditions for the applicability of possibilistic methods to qualitative MBD, and a number of potential directions for such an application, are described.

  11. Model-based Roentgen stereophotogrammetry of orthopaedic implants.

    PubMed

    Valstar, E R; de Jong, F W; Vrooman, H A; Rozing, P M; Reiber, J H

    2001-06-01

    Attaching tantalum markers to prostheses for Roentgen stereophotogrammetry (RSA) may be difficult and is sometimes even impossible. In this study, a model-based RSA method that avoids the attachment of markers to prostheses is presented and validated. This model-based RSA method uses a triangulated surface model of the implant. A projected contour of this model is calculated and this calculated model contour is matched onto the detected contour of the actual implant in the RSA radiograph. The difference between the two contours is minimized by variation of the position and orientation of the model. When a minimal difference between the contours is found, an optimal position and orientation of the model has been obtained. The method was validated by means of a phantom experiment. Three prosthesis components were used in this experiment: the femoral and tibial component of an Interax total knee prosthesis (Stryker Howmedica Osteonics Corp., Rutherfort, USA) and the femoral component of a Profix total knee prosthesis (Smith & Nephew, Memphis, USA). For the prosthesis components used in this study, the accuracy of the model-based method is lower than the accuracy of traditional RSA. For the Interax femoral and tibial components, significant dimensional tolerances were found that were probably caused by the casting process and manual polishing of the components surfaces. The largest standard deviation for any translation was 0.19mm and for any rotation it was 0.52 degrees. For the Profix femoral component that had no large dimensional tolerances, the largest standard deviation for any translation was 0.22mm and for any rotation it was 0.22 degrees. From this study we may conclude that the accuracy of the current model-based RSA method is sensitive to dimensional tolerances of the implant. Research is now being conducted to make model-based RSA less sensitive to dimensional tolerances and thereby improving its accuracy.

  12. Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

    PubMed Central

    Konovalov, Arkady; Krajbich, Ian

    2016-01-01

    Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming that experimental subjects make their decisions at the same prescribed time. PMID:27511383

  13. Model-based tomographic reconstruction

    DOEpatents

    Chambers, David H; Lehman, Sean K; Goodman, Dennis M

    2012-06-26

    A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

  14. Automated extraction of knowledge for model-based diagnostics

    NASA Technical Reports Server (NTRS)

    Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

    1990-01-01

    The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

  15. Reacting Chemistry Based Burn Model for Explosive Hydrocodes

    NASA Astrophysics Data System (ADS)

    Schwaab, Matthew; Greendyke, Robert; Steward, Bryan

    2017-06-01

    Currently, in hydrocodes designed to simulate explosive material undergoing shock-induced ignition, the state of the art is to use one of numerous reaction burn rate models. These burn models are designed to estimate the bulk chemical reaction rate. Unfortunately, these models are largely based on empirical data and must be recalibrated for every new material being simulated. We propose that the use of an equilibrium Arrhenius rate reacting chemistry model in place of these empirically derived burn models will improve the accuracy for these computational codes. Such models have been successfully used in codes simulating the flow physics around hypersonic vehicles. A reacting chemistry model of this form was developed for the cyclic nitramine RDX by the Naval Research Laboratory (NRL). Initial implementation of this chemistry based burn model has been conducted on the Air Force Research Laboratory's MPEXS multi-phase continuum hydrocode. In its present form, the burn rate is based on the destruction rate of RDX from NRL's chemistry model. Early results using the chemistry based burn model show promise in capturing deflagration to detonation features more accurately in continuum hydrocodes than previously achieved using empirically derived burn models.

  16. Overcoming limitations of model-based diagnostic reasoning systems

    NASA Technical Reports Server (NTRS)

    Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

    1989-01-01

    The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

  17. Learning of Chemical Equilibrium through Modelling-Based Teaching

    ERIC Educational Resources Information Center

    Maia, Poliana Flavia; Justi, Rosaria

    2009-01-01

    This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

  18. The practice of agent-based model visualization.

    PubMed

    Dorin, Alan; Geard, Nicholas

    2014-01-01

    We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

  19. Model predictive control based on reduced order models applied to belt conveyor system.

    PubMed

    Chen, Wei; Li, Xin

    2016-11-01

    In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Model-based diagnostics for Space Station Freedom

    NASA Technical Reports Server (NTRS)

    Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

    1991-01-01

    An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

  1. The Design of Model-Based Training Programs

    NASA Technical Reports Server (NTRS)

    Polson, Peter; Sherry, Lance; Feary, Michael; Palmer, Everett; Alkin, Marty; McCrobie, Dan; Kelley, Jerry; Rosekind, Mark (Technical Monitor)

    1997-01-01

    This paper proposes a model-based training program for the skills necessary to operate advance avionics systems that incorporate advanced autopilots and fight management systems. The training model is based on a formalism, the operational procedure model, that represents the mission model, the rules, and the functions of a modem avionics system. This formalism has been defined such that it can be understood and shared by pilots, the avionics software, and design engineers. Each element of the software is defined in terms of its intent (What?), the rationale (Why?), and the resulting behavior (How?). The Advanced Computer Tutoring project at Carnegie Mellon University has developed a type of model-based, computer aided instructional technology called cognitive tutors. They summarize numerous studies showing that training times to a specified level of competence can be achieved in one third the time of conventional class room instruction. We are developing a similar model-based training program for the skills necessary to operation the avionics. The model underlying the instructional program and that simulates the effects of pilots entries and the behavior of the avionics is based on the operational procedure model. Pilots are given a series of vertical flightpath management problems. Entries that result in violations, such as failure to make a crossing restriction or violating the speed limits, result in error messages with instruction. At any time, the flightcrew can request suggestions on the appropriate set of actions. A similar and successful training program for basic skills for the FMS on the Boeing 737-300 was developed and evaluated. The results strongly support the claim that the training methodology can be adapted to the cockpit.

  2. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    NASA Astrophysics Data System (ADS)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  3. Synthesis of TiO{sub 2} nanoparticles by hydrolysis and peptization of titanium isopropoxide solution

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

    Mahata, S.; Mahato, S. S.; Nandi, M. M.

    2012-07-23

    Here we report the synthesis and characterization of a stable suspension of modified titania nanoparticles. Phase-pure TiO{sub 2} nanocrystallites with narrow particle-size distributions were selectively prepared by hydrolysis-peptization of modified alkoxide followed by hydrothermal treatment. Autoclaving modified TiO{sub 2} in the presence of HNO3 as cooperative catalysts led to the formation of crystalline TiO{sub 2} with narrow-sized distribution. Following the hydrothermal treatment at 150 Degree-Sign C, X-ray diffraction shows the particles to be exclusively anatase. Synthesized powder is characterized by FT-IR, scanning electron microscopy (FESEM) and transmission electron microscopy (HRTEM). The photocatalytic activity in the degradation of orange-II is quitemore » comparable to good anatase and rutile nanocrystallites.« less

  4. Pixel-based meshfree modelling of skeletal muscles.

    PubMed

    Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

    2016-01-01

    This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using Magnetic Resonance Images (MRI) and DTI. The application of the proposed methods for modeling the human lower leg is demonstrated.

  5. Anthropometric measures in cardiovascular disease prediction: comparison of laboratory-based versus non-laboratory-based model.

    PubMed

    Dhana, Klodian; Ikram, M Arfan; Hofman, Albert; Franco, Oscar H; Kavousi, Maryam

    2015-03-01

    Body mass index (BMI) has been used to simplify cardiovascular risk prediction models by substituting total cholesterol and high-density lipoprotein cholesterol. In the elderly, the ability of BMI as a predictor of cardiovascular disease (CVD) declines. We aimed to find the most predictive anthropometric measure for CVD risk to construct a non-laboratory-based model and to compare it with the model including laboratory measurements. The study included 2675 women and 1902 men aged 55-79 years from the prospective population-based Rotterdam Study. We used Cox proportional hazard regression analysis to evaluate the association of BMI, waist circumference, waist-to-hip ratio and a body shape index (ABSI) with CVD, including coronary heart disease and stroke. The performance of the laboratory-based and non-laboratory-based models was evaluated by studying the discrimination, calibration, correlation and risk agreement. Among men, ABSI was the most informative measure associated with CVD, therefore ABSI was used to construct the non-laboratory-based model. Discrimination of the non-laboratory-based model was not different than laboratory-based model (c-statistic: 0.680-vs-0.683, p=0.71); both models were well calibrated (15.3% observed CVD risk vs 16.9% and 17.0% predicted CVD risks by the non-laboratory-based and laboratory-based models, respectively) and Spearman rank correlation and the agreement between non-laboratory-based and laboratory-based models were 0.89 and 91.7%, respectively. Among women, none of the anthropometric measures were independently associated with CVD. Among middle-aged and elderly where the ability of BMI to predict CVD declines, the non-laboratory-based model, based on ABSI, could predict CVD risk as accurately as the laboratory-based model among men. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  6. 3-D model-based vehicle tracking.

    PubMed

    Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

    2005-10-01

    This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

  7. Sandboxes for Model-Based Inquiry

    NASA Astrophysics Data System (ADS)

    Brady, Corey; Holbert, Nathan; Soylu, Firat; Novak, Michael; Wilensky, Uri

    2015-04-01

    In this article, we introduce a class of constructionist learning environments that we call Emergent Systems Sandboxes ( ESSs), which have served as a centerpiece of our recent work in developing curriculum to support scalable model-based learning in classroom settings. ESSs are a carefully specified form of virtual construction environment that support students in creating, exploring, and sharing computational models of dynamic systems that exhibit emergent phenomena. They provide learners with "entity"-level construction primitives that reflect an underlying scientific model. These primitives can be directly "painted" into a sandbox space, where they can then be combined, arranged, and manipulated to construct complex systems and explore the emergent properties of those systems. We argue that ESSs offer a means of addressing some of the key barriers to adopting rich, constructionist model-based inquiry approaches in science classrooms at scale. Situating the ESS in a large-scale science modeling curriculum we are implementing across the USA, we describe how the unique "entity-level" primitive design of an ESS facilitates knowledge system refinement at both an individual and social level, we describe how it supports flexible modeling practices by providing both continuous and discrete modes of executability, and we illustrate how it offers students a variety of opportunities for validating their qualitative understandings of emergent systems as they develop.

  8. Semiconducting polymers with nanocrystallites interconnected via boron-doped carbon nanotubes.

    PubMed

    Yu, Kilho; Lee, Ju Min; Kim, Junghwan; Kim, Geunjin; Kang, Hongkyu; Park, Byoungwook; Ho Kahng, Yung; Kwon, Sooncheol; Lee, Sangchul; Lee, Byoung Hun; Kim, Jehan; Park, Hyung Il; Kim, Sang Ouk; Lee, Kwanghee

    2014-12-10

    Organic semiconductors are key building blocks for future electronic devices that require unprecedented properties of low-weight, flexibility, and portability. However, the low charge-carrier mobility and undesirable processing conditions limit their compatibility with low-cost, flexible, and printable electronics. Here, we present significantly enhanced field-effect mobility (μ(FET)) in semiconducting polymers mixed with boron-doped carbon nanotubes (B-CNTs). In contrast to undoped CNTs, which tend to form undesired aggregates, the B-CNTs exhibit an excellent dispersion in conjugated polymer matrices and improve the charge transport between polymer chains. Consequently, the B-CNT-mixed semiconducting polymers enable the fabrication of high-performance FETs on plastic substrates via a solution process; the μFET of the resulting FETs reaches 7.2 cm(2) V(-1) s(-1), which is the highest value reported for a flexible FET based on a semiconducting polymer. Our approach is applicable to various semiconducting polymers without any additional undesirable processing treatments, indicating its versatility, universality, and potential for high-performance printable electronics.

  9. Extending rule-based methods to model molecular geometry and 3D model resolution.

    PubMed

    Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

    2016-08-01

    Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models

  10. Dynamic modeling method for infrared smoke based on enhanced discrete phase model

    NASA Astrophysics Data System (ADS)

    Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

    2018-03-01

    The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

  11. Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

    PubMed

    Jain, Ram B

    2016-08-01

    Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

  12. Agent Based Modeling Applications for Geosciences

    NASA Astrophysics Data System (ADS)

    Stein, J. S.

    2004-12-01

    Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

  13. Models-Based Practice: Great White Hope or White Elephant?

    ERIC Educational Resources Information Center

    Casey, Ashley

    2014-01-01

    Background: Many critical curriculum theorists in physical education have advocated a model- or models-based approach to teaching in the subject. This paper explores the literature base around models-based practice (MBP) and asks if this multi-models approach to curriculum planning has the potential to be the great white hope of pedagogical change…

  14. Model-Drive Architecture for Agent-Based Systems

    NASA Technical Reports Server (NTRS)

    Gradanin, Denis; Singh, H. Lally; Bohner, Shawn A.; Hinchey, Michael G.

    2004-01-01

    The Model Driven Architecture (MDA) approach uses a platform-independent model to define system functionality, or requirements, using some specification language. The requirements are then translated to a platform-specific model for implementation. An agent architecture based on the human cognitive model of planning, the Cognitive Agent Architecture (Cougaar) is selected for the implementation platform. The resulting Cougaar MDA prescribes certain kinds of models to be used, how those models may be prepared and the relationships of the different kinds of models. Using the existing Cougaar architecture, the level of application composition is elevated from individual components to domain level model specifications in order to generate software artifacts. The software artifacts generation is based on a metamodel. Each component maps to a UML structured component which is then converted into multiple artifacts: Cougaar/Java code, documentation, and test cases.

  15. Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

    PubMed

    Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

    2010-06-29

    In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are

  16. CDMBE: A Case Description Model Based on Evidence

    PubMed Central

    Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

    2015-01-01

    By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users' ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model. PMID:26421006

  17. Language acquisition is model-based rather than model-free.

    PubMed

    Wang, Felix Hao; Mintz, Toben H

    2016-01-01

    Christiansen & Chater (C&C) propose that learning language is learning to process language. However, we believe that the general-purpose prediction mechanism they propose is insufficient to account for many phenomena in language acquisition. We argue from theoretical considerations and empirical evidence that many acquisition tasks are model-based, and that different acquisition tasks require different, specialized models.

  18. The IRGen infrared data base modeler

    NASA Technical Reports Server (NTRS)

    Bernstein, Uri

    1993-01-01

    IRGen is a modeling system which creates three-dimensional IR data bases for real-time simulation of thermal IR sensors. Starting from a visual data base, IRGen computes the temperature and radiance of every data base surface with a user-specified thermal environment. The predicted gray shade of each surface is then computed from the user specified sensor characteristics. IRGen is based on first-principles models of heat transport and heat flux sources, and it accurately simulates the variations of IR imagery with time of day and with changing environmental conditions. The starting point for creating an IRGen data base is a visual faceted data base, in which every facet has been labeled with a material code. This code is an index into a material data base which contains surface and bulk thermal properties for the material. IRGen uses the material properties to compute the surface temperature at the specified time of day. IRGen also supports image generator features such as texturing and smooth shading, which greatly enhance image realism.

  19. INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

    PubMed

    Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

    2015-01-01

    Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

  20. Crowdsourcing Based 3d Modeling

    NASA Astrophysics Data System (ADS)

    Somogyi, A.; Barsi, A.; Molnar, B.; Lovas, T.

    2016-06-01

    Web-based photo albums that support organizing and viewing the users' images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  1. Test Platforms for Model-Based Flight Research

    NASA Astrophysics Data System (ADS)

    Dorobantu, Andrei

    Demonstrating the reliability of flight control algorithms is critical to integrating unmanned aircraft systems into the civilian airspace. For many potential applications, design and certification of these algorithms will rely heavily on mathematical models of the aircraft dynamics. Therefore, the aerospace community must develop flight test platforms to support the advancement of model-based techniques. The University of Minnesota has developed a test platform dedicated to model-based flight research for unmanned aircraft systems. This thesis provides an overview of the test platform and its research activities in the areas of system identification, model validation, and closed-loop control for small unmanned aircraft.

  2. Excess Li-Ion Storage on Reconstructed Surfaces of Nanocrystals To Boost Battery Performance

    DOE PAGES

    Duan, Yandong; Zhang, Bingkai; Zheng, Jiaxin; ...

    2017-08-03

    Because of their enhanced kinetic properties, nanocrystallites have received much attention as potential electrode materials for energy storage. However, because of the large specific surface areas of nanocrystallites, they usually suffer from decreased energy density, cycling stability, and effective electrode capacity. Here, in this work, we report a size-dependent excess capacity beyond theoretical value (170 mA h g -1) by introducing extra lithium storage at the reconstructed surface in nanosized LiFePO 4 (LFP) cathode materials (186 and 207 mA h g -1 in samples with mean particle sizes of 83 and 42 nm, respectively). Moreover, this LFP composite also showsmore » excellent cycling stability and high rate performance. Our multimodal experimental characterizations and ab initio calculations reveal that the surface extra lithium storage is mainly attributed to the charge passivation of Fe by the surface C–O–Fe bonds, which can enhance binding energy for surface lithium by compensating surface Fe truncated symmetry to create two types of extra positions for Li-ion storage at the reconstructed surfaces. Such surface reconstruction nanotechnology for excess Li-ion storage makes full use of the large specific surface area of the nanocrystallites, which can maintain the fast Li-ion transport and greatly enhance the capacity. Finally, this discovery and nanotechnology can be used for the design of high-capacity and efficient lithium ion batteries.« less

  3. Excess Li-Ion Storage on Reconstructed Surfaces of Nanocrystals To Boost Battery Performance

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

    Duan, Yandong; Zhang, Bingkai; Zheng, Jiaxin

    Because of their enhanced kinetic properties, nanocrystallites have received much attention as potential electrode materials for energy storage. However, because of the large specific surface areas of nanocrystallites, they usually suffer from decreased energy density, cycling stability, and effective electrode capacity. Here, in this work, we report a size-dependent excess capacity beyond theoretical value (170 mA h g -1) by introducing extra lithium storage at the reconstructed surface in nanosized LiFePO 4 (LFP) cathode materials (186 and 207 mA h g -1 in samples with mean particle sizes of 83 and 42 nm, respectively). Moreover, this LFP composite also showsmore » excellent cycling stability and high rate performance. Our multimodal experimental characterizations and ab initio calculations reveal that the surface extra lithium storage is mainly attributed to the charge passivation of Fe by the surface C–O–Fe bonds, which can enhance binding energy for surface lithium by compensating surface Fe truncated symmetry to create two types of extra positions for Li-ion storage at the reconstructed surfaces. Such surface reconstruction nanotechnology for excess Li-ion storage makes full use of the large specific surface area of the nanocrystallites, which can maintain the fast Li-ion transport and greatly enhance the capacity. Finally, this discovery and nanotechnology can be used for the design of high-capacity and efficient lithium ion batteries.« less

  4. Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

    ERIC Educational Resources Information Center

    Snijders, Tom A. B.; Steglich, Christian E. G.

    2015-01-01

    Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

  5. Model-Based Diagnostics for Propellant Loading Systems

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew John; Foygel, Michael; Smelyanskiy, Vadim N.

    2011-01-01

    The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are necessary to quickly identify when a fault occurs, so that recovery actions can be taken or an abort procedure can be initiated. Model-based diagnosis solutions, established using an in-depth analysis and understanding of the underlying physical processes, offer the advanced capability to quickly detect and isolate faults, identify their severity, and predict their effects on system performance. We develop a physics-based model of a cryogenic propellant loading system, which describes the complex dynamics of liquid hydrogen filling from a storage tank to an external vehicle tank, as well as the influence of different faults on this process. The model takes into account the main physical processes such as highly nonequilibrium condensation and evaporation of the hydrogen vapor, pressurization, and also the dynamics of liquid hydrogen and vapor flows inside the system in the presence of helium gas. Since the model incorporates multiple faults in the system, it provides a suitable framework for model-based diagnostics and prognostics algorithms. Using this model, we analyze the effects of faults on the system, derive symbolic fault signatures for the purposes of fault isolation, and perform fault identification using a particle filter approach. We demonstrate the detection, isolation, and identification of a number of faults using simulation-based experiments.

  6. Search-based model identification of smart-structure damage

    NASA Technical Reports Server (NTRS)

    Glass, B. J.; Macalou, A.

    1991-01-01

    This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

  7. Research on Turbofan Engine Model above Idle State Based on NARX Modeling Approach

    NASA Astrophysics Data System (ADS)

    Yu, Bing; Shu, Wenjun

    2017-03-01

    The nonlinear model for turbofan engine above idle state based on NARX is studied. Above all, the data sets for the JT9D engine from existing model are obtained via simulation. Then, a nonlinear modeling scheme based on NARX is proposed and several models with different parameters are built according to the former data sets. Finally, the simulations have been taken to verify the precise and dynamic performance the models, the results show that the NARX model can well reflect the dynamics characteristic of the turbofan engine with high accuracy.

  8. Multiple Damage Progression Paths in Model-Based Prognostics

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew; Goebel, Kai Frank

    2011-01-01

    Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active

  9. A Model-based Approach to Reactive Self-Configuring Systems

    NASA Technical Reports Server (NTRS)

    Williams, Brian C.; Nayak, P. Pandurang

    1996-01-01

    This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

  10. Genome Informed Trait-Based Models

    NASA Astrophysics Data System (ADS)

    Karaoz, U.; Cheng, Y.; Bouskill, N.; Tang, J.; Beller, H. R.; Brodie, E.; Riley, W. J.

    2013-12-01

    Trait-based approaches are powerful tools for representing microbial communities across both spatial and temporal scales within ecosystem models. Trait-based models (TBMs) represent the diversity of microbial taxa as stochastic assemblages with a distribution of traits constrained by trade-offs between these traits. Such representation with its built-in stochasticity allows the elucidation of the interactions between the microbes and their environment by reducing the complexity of microbial community diversity into a limited number of functional ';guilds' and letting them emerge across spatio-temporal scales. From the biogeochemical/ecosystem modeling perspective, the emergent properties of the microbial community could be directly translated into predictions of biogeochemical reaction rates and microbial biomass. The accuracy of TBMs depends on the identification of key traits of the microbial community members and on the parameterization of these traits. Current approaches to inform TBM parameterization are empirical (i.e., based on literature surveys). Advances in omic technologies (such as genomics, metagenomics, metatranscriptomics, and metaproteomics) pave the way to better-initialize models that can be constrained in a generic or site-specific fashion. Here we describe the coupling of metagenomic data to the development of a TBM representing the dynamics of metabolic guilds from an organic carbon stimulated groundwater microbial community. Illumina paired-end metagenomic data were collected from the community as it transitioned successively through electron-accepting conditions (nitrate-, sulfate-, and Fe(III)-reducing), and used to inform estimates of growth rates and the distribution of metabolic pathways (i.e., aerobic and anaerobic oxidation, fermentation) across a spatially resolved TBM. We use this model to evaluate the emergence of different metabolisms and predict rates of biogeochemical processes over time. We compare our results to observational

  11. Modeling method of time sequence model based grey system theory and application proceedings

    NASA Astrophysics Data System (ADS)

    Wei, Xuexia; Luo, Yaling; Zhang, Shiqiang

    2015-12-01

    This article gives a modeling method of grey system GM(1,1) model based on reusing information and the grey system theory. This method not only extremely enhances the fitting and predicting accuracy of GM(1,1) model, but also maintains the conventional routes' merit of simple computation. By this way, we have given one syphilis trend forecast method based on reusing information and the grey system GM(1,1) model.

  12. Linking agent-based models and stochastic models of financial markets

    PubMed Central

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

    2012-01-01

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

  13. Linking agent-based models and stochastic models of financial markets.

    PubMed

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

    2012-05-29

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

  14. Point-based and model-based geolocation analysis of airborne laser scanning data

    NASA Astrophysics Data System (ADS)

    Sefercik, Umut Gunes; Buyuksalih, Gurcan; Jacobsen, Karsten; Alkan, Mehmet

    2017-01-01

    Airborne laser scanning (ALS) is one of the most effective remote sensing technologies providing precise three-dimensional (3-D) dense point clouds. A large-size ALS digital surface model (DSM) covering the whole Istanbul province was analyzed by point-based and model-based comprehensive statistical approaches. Point-based analysis was performed using checkpoints on flat areas. Model-based approaches were implemented in two steps as strip to strip comparing overlapping ALS DSMs individually in three subareas and comparing the merged ALS DSMs with terrestrial laser scanning (TLS) DSMs in four other subareas. In the model-based approach, the standard deviation of height and normalized median absolute deviation were used as the accuracy indicators combined with the dependency of terrain inclination. The results demonstrate that terrain roughness has a strong impact on the vertical accuracy of ALS DSMs. From the relative horizontal shifts determined and partially improved by merging the overlapping strips and comparison of the ALS, and the TLS, data were found not to be negligible. The analysis of ALS DSM in relation to TLS DSM allowed us to determine the characteristics of the DSM in detail.

  15. Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

    PubMed

    Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J

    2016-01-27

    Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes

  16. Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

    PubMed

    Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

    2017-01-01

    Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  17. Automated Decomposition of Model-based Learning Problems

    NASA Technical Reports Server (NTRS)

    Williams, Brian C.; Millar, Bill

    1996-01-01

    A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

  18. Whole body acid-base modeling revisited.

    PubMed

    Ring, Troels; Nielsen, Søren

    2017-04-01

    The textbook account of whole body acid-base balance in terms of endogenous acid production, renal net acid excretion, and gastrointestinal alkali absorption, which is the only comprehensive model around, has never been applied in clinical practice or been formally validated. To improve understanding of acid-base modeling, we managed to write up this conventional model as an expression solely on urine chemistry. Renal net acid excretion and endogenous acid production were already formulated in terms of urine chemistry, and we could from the literature also see gastrointestinal alkali absorption in terms of urine excretions. With a few assumptions it was possible to see that this expression of net acid balance was arithmetically identical to minus urine charge, whereby under the development of acidosis, urine was predicted to acquire a net negative charge. The literature already mentions unexplained negative urine charges so we scrutinized a series of seminal papers and confirmed empirically the theoretical prediction that observed urine charge did acquire negative charge as acidosis developed. Hence, we can conclude that the conventional model is problematic since it predicts what is physiologically impossible. Therefore, we need a new model for whole body acid-base balance, which does not have impossible implications. Furthermore, new experimental studies are needed to account for charge imbalance in urine under development of acidosis. Copyright © 2017 the American Physiological Society.

  19. Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

    PubMed Central

    Grulke, Christopher M.; Chang, Daniel T.; Brooks, Raina D.; Leonard, Jeremy A.; Phillips, Martin B.; Hypes, Ethan D.; Fair, Matthew J.; Tornero-Velez, Rogelio; Johnson, Jeffre; Dary, Curtis C.; Tan, Yu-Mei

    2016-01-01

    Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals. PMID:26871706

  20. Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction.

    PubMed

    Lu, Jingtao; Goldsmith, Michael-Rock; Grulke, Christopher M; Chang, Daniel T; Brooks, Raina D; Leonard, Jeremy A; Phillips, Martin B; Hypes, Ethan D; Fair, Matthew J; Tornero-Velez, Rogelio; Johnson, Jeffre; Dary, Curtis C; Tan, Yu-Mei

    2016-02-01

    Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals.

  1. Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

    NASA Astrophysics Data System (ADS)

    Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

    2017-10-01

    Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

  2. Reduced-order model based feedback control of the modified Hasegawa-Wakatani model

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

    Goumiri, I. R.; Rowley, C. W.; Ma, Z.

    2013-04-15

    In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modified Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in flow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then, a model-based feedback controller is designed for the reduced order model using linear quadratic regulators. Finally, a linear quadratic Gaussian controller which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilizemore » the equilibrium and suppress the transition to drift-wave induced turbulence.« less

  3. Model-Based Assurance Case+ (MBAC+): Tutorial on Modeling Radiation Hardness Assurance Activities

    NASA Technical Reports Server (NTRS)

    Austin, Rebekah; Label, Ken A.; Sampson, Mike J.; Evans, John; Witulski, Art; Sierawski, Brian; Karsai, Gabor; Mahadevan, Nag; Schrimpf, Ron; Reed, Robert A.

    2017-01-01

    This presentation will cover why modeling is useful for radiation hardness assurance cases, and also provide information on Model-Based Assurance Case+ (MBAC+), NASAs Reliability Maintainability Template, and Fault Propagation Modeling.

  4. Argumentation in Science Education: A Model-Based Framework

    ERIC Educational Resources Information Center

    Bottcher, Florian; Meisert, Anke

    2011-01-01

    The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons…

  5. Construction of dynamic stochastic simulation models using knowledge-based techniques

    NASA Technical Reports Server (NTRS)

    Williams, M. Douglas; Shiva, Sajjan G.

    1990-01-01

    Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

  6. Towards Modeling False Memory With Computational Knowledge Bases.

    PubMed

    Li, Justin; Kohanyi, Emma

    2017-01-01

    One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.

  7. Model-based learning and the contribution of the orbitofrontal cortex to the model-free world

    PubMed Central

    McDannald, Michael A.; Takahashi, Yuji K.; Lopatina, Nina; Pietras, Brad W.; Jones, Josh L.; Schoenbaum, Geoffrey

    2012-01-01

    Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. PMID:22487030

  8. A technology path to tactical agent-based modeling

    NASA Astrophysics Data System (ADS)

    James, Alex; Hanratty, Timothy P.

    2017-05-01

    Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

  9. Model-Based Learning: A Synthesis of Theory and Research

    ERIC Educational Resources Information Center

    Seel, Norbert M.

    2017-01-01

    This article provides a review of theoretical approaches to model-based learning and related research. In accordance with the definition of model-based learning as an acquisition and utilization of mental models by learners, the first section centers on mental model theory. In accordance with epistemology of modeling the issues of semantics,…

  10. Modeling potential Emerald Ash Borer spread through GIS/cell-based/gravity models with data bolstered by web-based inputs

    Treesearch

    Louis R. Iverson; Anantha M. Prasad; Davis Sydnor; Jonathan Bossenbroek; Mark W. Schwartz; Mark W. Schwartz

    2006-01-01

    We model the susceptibility and potential spread of the organism across the eastern United States and especially through Michigan and Ohio using Forest Inventory and Analysis (FIA) data. We are also developing a cell-based model for the potential spread of the organism. We have developed a web-based tool for public agencies and private individuals to enter the...

  11. Abstracting event-based control models for high autonomy systems

    NASA Technical Reports Server (NTRS)

    Luh, Cheng-Jye; Zeigler, Bernard P.

    1993-01-01

    A high autonomy system needs many models on which to base control, management, design, and other interventions. These models differ in level of abstraction and in formalism. Concepts and tools are needed to organize the models into a coherent whole. The paper deals with the abstraction processes for systematic derivation of related models for use in event-based control. The multifaceted modeling methodology is briefly reviewed. The morphism concepts needed for application to model abstraction are described. A theory for supporting the construction of DEVS models needed for event-based control is then presented. An implemented morphism on the basis of this theory is also described.

  12. Model Based Analysis and Test Generation for Flight Software

    NASA Technical Reports Server (NTRS)

    Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

    2009-01-01

    We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

  13. Haptics-based dynamic implicit solid modeling.

    PubMed

    Hua, Jing; Qin, Hong

    2004-01-01

    This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.

  14. Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

    NASA Astrophysics Data System (ADS)

    Gluhih, I. N.; Akhmadulin, R. K.

    2017-07-01

    One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

  15. Model-based reinforcement learning with dimension reduction.

    PubMed

    Tangkaratt, Voot; Morimoto, Jun; Sugiyama, Masashi

    2016-12-01

    The goal of reinforcement learning is to learn an optimal policy which controls an agent to acquire the maximum cumulative reward. The model-based reinforcement learning approach learns a transition model of the environment from data, and then derives the optimal policy using the transition model. However, learning an accurate transition model in high-dimensional environments requires a large amount of data which is difficult to obtain. To overcome this difficulty, in this paper, we propose to combine model-based reinforcement learning with the recently developed least-squares conditional entropy (LSCE) method, which simultaneously performs transition model estimation and dimension reduction. We also further extend the proposed method to imitation learning scenarios. The experimental results show that policy search combined with LSCE performs well for high-dimensional control tasks including real humanoid robot control. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Data-Flow Based Model Analysis

    NASA Technical Reports Server (NTRS)

    Saad, Christian; Bauer, Bernhard

    2010-01-01

    The concept of (meta) modeling combines an intuitive way of formalizing the structure of an application domain with a high expressiveness that makes it suitable for a wide variety of use cases and has therefore become an integral part of many areas in computer science. While the definition of modeling languages through the use of meta models, e.g. in Unified Modeling Language (UML), is a well-understood process, their validation and the extraction of behavioral information is still a challenge. In this paper we present a novel approach for dynamic model analysis along with several fields of application. Examining the propagation of information along the edges and nodes of the model graph allows to extend and simplify the definition of semantic constraints in comparison to the capabilities offered by e.g. the Object Constraint Language. Performing a flow-based analysis also enables the simulation of dynamic behavior, thus providing an "abstract interpretation"-like analysis method for the modeling domain.

  17. New approaches in agent-based modeling of complex financial systems

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

    2017-12-01

    Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

  18. Magnetic properties of carbon-coated, ferromagnetic nanoparticles produced by a carbon-arc method

    NASA Astrophysics Data System (ADS)

    Brunsman, E. M.; Sutton, R.; Bortz, E.; Kirkpatrick, S.; Midelfort, K.; Williams, J.; Smith, P.; McHenry, M. E.; Majetich, S. A.; Artman, J. O.; De Graef, M.; Staley, S. W.

    1994-05-01

    The Krätschmer-Huffman carbon-arc method of preparing fullerenes has been used to generate carbon-coated transition metal (TM) and TM-carbide nanocrystallites. The magnetic nanocrystallites were extracted from the soot with a magnetic gradient field technique. For TM=Co the majority of nanocrystals exist as nominally spherical particles, 0.5-5 nm in radius. Hysteretic and temperature-dependent magnetic response, in randomly and magnetically aligned powder samples frozen in epoxy, correspond to fine particle magnetism associated with monodomain TM particles. The magnetization exhibits a unique functional dependence on H/T, and hysteresis below a blocking temperature TB. Below TB, the temperature dependence of the coercivity can be expressed as Hc=Hc0[1-(T/TB)1/2], where Hc0 is the 0 K coercivity.

  19. Video-Based Modeling: Differential Effects due to Treatment Protocol

    ERIC Educational Resources Information Center

    Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Boles, Margot B.; Davis, Heather S.; Rispoli, Mandy J.

    2013-01-01

    Identifying evidence-based practices for individuals with disabilities requires specification of procedural implementation. Video-based modeling (VBM), consisting of both video self-modeling and video modeling with others as model (VMO), is one class of interventions that has frequently been explored in the literature. However, current information…

  20. Design of a component-based integrated environmental modeling framework

    EPA Science Inventory

    Integrated environmental modeling (IEM) includes interdependent science-based components (e.g., models, databases, viewers, assessment protocols) that comprise an appropriate software modeling system. The science-based components are responsible for consuming and producing inform...

  1. Evaluating Water Demand Using Agent-Based Modeling

    NASA Astrophysics Data System (ADS)

    Lowry, T. S.

    2004-12-01

    The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

  2. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    ERIC Educational Resources Information Center

    Xiang, Lin

    2011-01-01

    This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

  3. Nonlinear system modeling based on bilinear Laguerre orthonormal bases.

    PubMed

    Garna, Tarek; Bouzrara, Kais; Ragot, José; Messaoud, Hassani

    2013-05-01

    This paper proposes a new representation of discrete bilinear model by developing its coefficients associated to the input, to the output and to the crossed product on three independent Laguerre orthonormal bases. Compared to classical bilinear model, the resulting model entitled bilinear-Laguerre model ensures a significant parameter number reduction as well as simple recursive representation. However, such reduction still constrained by an optimal choice of Laguerre pole characterizing each basis. To do so, we develop a pole optimization algorithm which constitutes an extension of that proposed by Tanguy et al.. The bilinear-Laguerre model as well as the proposed pole optimization algorithm are illustrated and tested on a numerical simulations and validated on the Continuous Stirred Tank Reactor (CSTR) System. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Diagnosis by integrating model-based reasoning with knowledge-based reasoning

    NASA Technical Reports Server (NTRS)

    Bylander, Tom

    1988-01-01

    Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

  5. Performability modeling based on real data: A casestudy

    NASA Technical Reports Server (NTRS)

    Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

    1987-01-01

    Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

  6. Electrophysiological correlates reflect the integration of model-based and model-free decision information.

    PubMed

    Eppinger, Ben; Walter, Maik; Li, Shu-Chen

    2017-04-01

    In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

  7. The fractional volatility model: An agent-based interpretation

    NASA Astrophysics Data System (ADS)

    Vilela Mendes, R.

    2008-06-01

    Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

  8. The Iterative Research Cycle: Process-Based Model Evaluation

    NASA Astrophysics Data System (ADS)

    Vrugt, J. A.

    2014-12-01

    The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex physics based models that simulate a myriad of processes at different spatial and temporal scales. Reconciling these high-order system models with perpetually larger volumes of field data is becoming more and more difficult, particularly because classical likelihood-based fitting methods lack the power to detect and pinpoint deficiencies in the model structure. In this talk I will give an overview of our latest research on process-based model calibration and evaluation. This approach, rooted in Bayesian theory, uses summary metrics of the calibration data rather than the data itself to help detect which component(s) of the model is (are) malfunctioning and in need of improvement. A few case studies involving hydrologic and geophysical models will be used to demonstrate the proposed methodology.

  9. Model-based multiple patterning layout decomposition

    NASA Astrophysics Data System (ADS)

    Guo, Daifeng; Tian, Haitong; Du, Yuelin; Wong, Martin D. F.

    2015-10-01

    As one of the most promising next generation lithography technologies, multiple patterning lithography (MPL) plays an important role in the attempts to keep in pace with 10 nm technology node and beyond. With feature size keeps shrinking, it has become impossible to print dense layouts within one single exposure. As a result, MPL such as double patterning lithography (DPL) and triple patterning lithography (TPL) has been widely adopted. There is a large volume of literature on DPL/TPL layout decomposition, and the current approach is to formulate the problem as a classical graph-coloring problem: Layout features (polygons) are represented by vertices in a graph G and there is an edge between two vertices if and only if the distance between the two corresponding features are less than a minimum distance threshold value dmin. The problem is to color the vertices of G using k colors (k = 2 for DPL, k = 3 for TPL) such that no two vertices connected by an edge are given the same color. This is a rule-based approach, which impose a geometric distance as a minimum constraint to simply decompose polygons within the distance into different masks. It is not desired in practice because this criteria cannot completely capture the behavior of the optics. For example, it lacks of sufficient information such as the optical source characteristics and the effects between the polygons outside the minimum distance. To remedy the deficiency, a model-based layout decomposition approach to make the decomposition criteria base on simulation results was first introduced at SPIE 2013.1 However, the algorithm1 is based on simplified assumption on the optical simulation model and therefore its usage on real layouts is limited. Recently AMSL2 also proposed a model-based approach to layout decomposition by iteratively simulating the layout, which requires excessive computational resource and may lead to sub-optimal solutions. The approach2 also potentially generates too many stiches. In this

  10. A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

    NASA Astrophysics Data System (ADS)

    Jaxa-Rozen, M.

    2016-12-01

    The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

  11. Psychophysically based model of surface gloss perception

    NASA Astrophysics Data System (ADS)

    Ferwerda, James A.; Pellacini, Fabio; Greenberg, Donald P.

    2001-06-01

    In this paper we introduce a new model of surface appearance that is based on quantitative studies of gloss perception. We use image synthesis techniques to conduct experiments that explore the relationships between the physical dimensions of glossy reflectance and the perceptual dimensions of glossy appearance. The product of these experiments is a psychophysically-based model of surface gloss, with dimensions that are both physically and perceptually meaningful and scales that reflect our sensitivity to gloss variations. We demonstrate that the model can be used to describe and control the appearance of glossy surfaces in synthesis images, allowing prediction of gloss matches and quantification of gloss differences. This work represents some initial steps toward developing psychophyscial models of the goniometric aspects of surface appearance to complement widely-used colorimetric models.

  12. Model-based learning and the contribution of the orbitofrontal cortex to the model-free world.

    PubMed

    McDannald, Michael A; Takahashi, Yuji K; Lopatina, Nina; Pietras, Brad W; Jones, Josh L; Schoenbaum, Geoffrey

    2012-04-01

    Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  13. Model-based Clustering of High-Dimensional Data in Astrophysics

    NASA Astrophysics Data System (ADS)

    Bouveyron, C.

    2016-05-01

    The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

  14. A simple computational algorithm of model-based choice preference.

    PubMed

    Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

    2017-08-01

    A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

  15. Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

    PubMed Central

    Snijders, Tom A.B.; Steglich, Christian E.G.

    2014-01-01

    Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

  16. Design-based and model-based inference in surveys of freshwater mollusks

    USGS Publications Warehouse

    Dorazio, R.M.

    1999-01-01

    Well-known concepts in statistical inference and sampling theory are used to develop recommendations for planning and analyzing the results of quantitative surveys of freshwater mollusks. Two methods of inference commonly used in survey sampling (design-based and model-based) are described and illustrated using examples relevant in surveys of freshwater mollusks. The particular objectives of a survey and the type of information observed in each unit of sampling can be used to help select the sampling design and the method of inference. For example, the mean density of a sparsely distributed population of mollusks can be estimated with higher precision by using model-based inference or by using design-based inference with adaptive cluster sampling than by using design-based inference with conventional sampling. More experience with quantitative surveys of natural assemblages of freshwater mollusks is needed to determine the actual benefits of different sampling designs and inferential procedures.

  17. In defence of model-based inference in phylogeography

    PubMed Central

    Beaumont, Mark A.; Nielsen, Rasmus; Robert, Christian; Hey, Jody; Gaggiotti, Oscar; Knowles, Lacey; Estoup, Arnaud; Panchal, Mahesh; Corander, Jukka; Hickerson, Mike; Sisson, Scott A.; Fagundes, Nelson; Chikhi, Lounès; Beerli, Peter; Vitalis, Renaud; Cornuet, Jean-Marie; Huelsenbeck, John; Foll, Matthieu; Yang, Ziheng; Rousset, Francois; Balding, David; Excoffier, Laurent

    2017-01-01

    Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics. PMID:29284924

  18. Viewing Knowledge Bases as Qualitative Models.

    ERIC Educational Resources Information Center

    Clancey, William J.

    The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

  19. A standard protocol for describing individual-based and agent-based models

    USGS Publications Warehouse

    Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

    2006-01-01

    Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

  20. Model Documentation of Base Case Data | Regional Energy Deployment System

    Science.gov Websites

    Model | Energy Analysis | NREL Documentation of Base Case Data Model Documentation of Base Case base case of the model. The base case was developed simply as a point of departure for other analyses Base Case derives many of its inputs from the Energy Information Administration's (EIA's) Annual Energy

  1. Satellite-based terrestrial production efficiency modeling

    PubMed Central

    McCallum, Ian; Wagner, Wolfgang; Schmullius, Christiane; Shvidenko, Anatoly; Obersteiner, Michael; Fritz, Steffen; Nilsson, Sten

    2009-01-01

    Production efficiency models (PEMs) are based on the theory of light use efficiency (LUE) which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP) monitoring. The objectives of this review are as follows: 1) to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS) identified in the literature; 2) to review each model to determine potential improvements to the general PEM methodology; 3) to review the related literature on satellite-based gross primary productivity (GPP) and NPP modeling for additional possibilities for improvement; and 4) based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT) or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra); there is an urgent need for satellite-based

  2. Model-Based Diagnosis in a Power Distribution Test-Bed

    NASA Technical Reports Server (NTRS)

    Scarl, E.; McCall, K.

    1998-01-01

    The Rodon model-based diagnosis shell was applied to a breadboard test-bed, modeling an automated power distribution system. The constraint-based modeling paradigm and diagnostic algorithm were found to adequately represent the selected set of test scenarios.

  3. Defeaturing CAD models using a geometry-based size field and facet-based reduction operators.

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

    Quadros, William Roshan; Owen, Steven James

    2010-04-01

    We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant featuremore » and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.« less

  4. Embracing model-based designs for dose-finding trials

    PubMed Central

    Love, Sharon B; Brown, Sarah; Weir, Christopher J; Harbron, Chris; Yap, Christina; Gaschler-Markefski, Birgit; Matcham, James; Caffrey, Louise; McKevitt, Christopher; Clive, Sally; Craddock, Charlie; Spicer, James; Cornelius, Victoria

    2017-01-01

    Background: Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose finding, such as the continual reassessment method (CRM). Methods: We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation. Results: We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators’ preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome. Conclusions: There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for dose-finding trials in academia. PMID:28664918

  5. Assessment of Energy Efficient and Model Based Control

    DTIC Science & Technology

    2017-06-15

    ARL-TR-8042 ● JUNE 2017 US Army Research Laboratory Assessment of Energy -Efficient and Model- Based Control by Craig Lennon...originator. ARL-TR-8042 ● JUNE 2017 US Army Research Laboratory Assessment of Energy -Efficient and Model- Based Control by Craig...

  6. Predictor-Based Model Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2009-01-01

    This paper is devoted to robust, Predictor-based Model Reference Adaptive Control (PMRAC) design. The proposed adaptive system is compared with the now-classical Model Reference Adaptive Control (MRAC) architecture. Simulation examples are presented. Numerical evidence indicates that the proposed PMRAC tracking architecture has better than MRAC transient characteristics. In this paper, we presented a state-predictor based direct adaptive tracking design methodology for multi-input dynamical systems, with partially known dynamics. Efficiency of the design was demonstrated using short period dynamics of an aircraft. Formal proof of the reported PMRAC benefits constitute future research and will be reported elsewhere.

  7. Intelligent model-based diagnostics for vehicle health management

    NASA Astrophysics Data System (ADS)

    Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

    2003-08-01

    The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

  8. Logic-Based Models for the Analysis of Cell Signaling Networks†

    PubMed Central

    2010-01-01

    Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

  9. Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning

    PubMed Central

    Bath, Kevin G.; Daw, Nathaniel D.; Frank, Michael J.

    2016-01-01

    Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by “model-free” learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by “model-based” learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. SIGNIFICANCE STATEMENT Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative

  10. Thermodynamics-based models of transcriptional regulation with gene sequence.

    PubMed

    Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing

    2015-12-01

    Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

  11. Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

    PubMed

    Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

    2013-05-01

    Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

  12. Cellular-based modeling of oscillatory dynamics in brain networks.

    PubMed

    Skinner, Frances K

    2012-08-01

    Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

    NASA Technical Reports Server (NTRS)

    Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

    2005-01-01

    Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

  14. Surrogate-Based Optimization of Biogeochemical Transport Models

    NASA Astrophysics Data System (ADS)

    Prieß, Malte; Slawig, Thomas

    2010-09-01

    First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

  15. Agent-Based Modeling in Systems Pharmacology.

    PubMed

    Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

    2015-11-01

    Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

  16. Vehicle-specific emissions modeling based upon on-road measurements.

    PubMed

    Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

    2010-05-01

    Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

  17. Agent-based models in translational systems biology

    PubMed Central

    An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

    2013-01-01

    Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

  18. Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

    NASA Technical Reports Server (NTRS)

    Evans, John W.; DiVenti, Tony

    2016-01-01

    The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

  19. [GSH fermentation process modeling using entropy-criterion based RBF neural network model].

    PubMed

    Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

    2008-05-01

    The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

  20. SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

    PubMed

    Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

    2010-01-01

    Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

  1. Model-based metabolism design: constraints for kinetic and stoichiometric models

    PubMed Central

    Stalidzans, Egils; Seiman, Andrus; Peebo, Karl; Komasilovs, Vitalijs; Pentjuss, Agris

    2018-01-01

    The implementation of model-based designs in metabolic engineering and synthetic biology may fail. One of the reasons for this failure is that only a part of the real-world complexity is included in models. Still, some knowledge can be simplified and taken into account in the form of optimization constraints to improve the feasibility of model-based designs of metabolic pathways in organisms. Some constraints (mass balance, energy balance, and steady-state assumption) serve as a basis for many modelling approaches. There are others (total enzyme activity constraint and homeostatic constraint) proposed decades ago, but which are frequently ignored in design development. Several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance. Constraints for kinetic and stoichiometric models are grouped according to their applicability preconditions in (1) general constraints, (2) organism-level constraints, and (3) experiment-level constraints. General constraints are universal and are applicable for any system. Organism-level constraints are applicable for biological systems and usually are organism-specific, but these constraints can be applied without information about experimental conditions. To apply experimental-level constraints, peculiarities of the organism and the experimental set-up have to be taken into account to calculate the values of constraints. The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed. PMID:29472367

  2. NHPP-Based Software Reliability Models Using Equilibrium Distribution

    NASA Astrophysics Data System (ADS)

    Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

    Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

  3. Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.

    PubMed

    Henley, B C; Shin, D C; Zhang, R; Marmarelis, V Z

    Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.

  4. Effects of annealing temperature on the physicochemical, optical and photoelectrochemical properties of nanostructured hematite thin films prepared via electrodeposition method

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

    Phuan, Yi Wen; Chong, Meng Nan, E-mail: Chong.Meng.Nan@monash.edu; Sustainable Water Alliance, Advanced Engineering Platform, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway 46150 Selangor DE

    2015-09-15

    Highlights: • Nanostructured hematite thin films were synthesized via electrodeposition method. • Effects of annealing on size, grain boundary and PEC properties were examined. • Photocurrents generation was enhanced when the thin films were annealed at 600 °C. • The highest photocurrent density of 1.6 mA/cm{sup 2} at 0.6 V vs Ag/AgCl was achieved. - Abstract: Hematite (α-Fe{sub 2}O{sub 3}) is a promising photoanode material for hydrogen production from photoelectrochemical (PEC) water splitting due to its wide abundance, narrow band-gap energy, efficient light absorption and high chemical stability under aqueous environment. The key challenge to the wider utilisation of nanostructuredmore » hematite-based photoanode in PEC water splitting, however, is limited by its low photo-assisted water oxidation caused by large overpotential in the nominal range of 0.5–0.6 V. The main aim of this study was to enhance the performance of hematite for photo-assisted water oxidation by optimising the annealing temperature used during the synthesis of nanostructured hematite thin films on fluorine-doped tin oxide (FTO)-based photoanodes prepared via the cathodic electrodeposition method. The resultant nanostructured hematite thin films were characterised using field emission-scanning electron microscopy (FE-SEM) coupled with energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), UV-visible spectroscopy and Fourier transform infrared spectroscopy (FTIR) for their elemental composition, average nanocrystallites size and morphology; phase and crystallinity; UV-absorptivity and band gap energy; and the functional groups, respectively. Results showed that the nanostructured hematite thin films possess good ordered nanocrystallites array and high crystallinity after annealing treatment at 400–600 °C. FE-SEM images illustrated an increase in the average hematite nanocrystallites size from 65 nm to 95 nm when the annealing temperature was varied from 400

  5. A Model-Based Prognostics Approach Applied to Pneumatic Valves

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Goebel, Kai

    2011-01-01

    Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

  6. Integrated Turbine-Based Combined Cycle Dynamic Simulation Model

    NASA Technical Reports Server (NTRS)

    Haid, Daniel A.; Gamble, Eric J.

    2011-01-01

    A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.

  7. Model-based phase-shifting interferometer

    NASA Astrophysics Data System (ADS)

    Liu, Dong; Zhang, Lei; Shi, Tu; Yang, Yongying; Chong, Shiyao; Miao, Liang; Huang, Wei; Shen, Yibing; Bai, Jian

    2015-10-01

    A model-based phase-shifting interferometer (MPI) is developed, in which a novel calculation technique is proposed instead of the traditional complicated system structure, to achieve versatile, high precision and quantitative surface tests. In the MPI, the partial null lens (PNL) is employed to implement the non-null test. With some alternative PNLs, similar as the transmission spheres in ZYGO interferometers, the MPI provides a flexible test for general spherical and aspherical surfaces. Based on modern computer modeling technique, a reverse iterative optimizing construction (ROR) method is employed for the retrace error correction of non-null test, as well as figure error reconstruction. A self-compiled ray-tracing program is set up for the accurate system modeling and reverse ray tracing. The surface figure error then can be easily extracted from the wavefront data in forms of Zernike polynomials by the ROR method. Experiments of the spherical and aspherical tests are presented to validate the flexibility and accuracy. The test results are compared with those of Zygo interferometer (null tests), which demonstrates the high accuracy of the MPI. With such accuracy and flexibility, the MPI would possess large potential in modern optical shop testing.

  8. An EKV-based high voltage MOSFET model with improved mobility and drift model

    NASA Astrophysics Data System (ADS)

    Chauhan, Yogesh Singh; Gillon, Renaud; Bakeroot, Benoit; Krummenacher, Francois; Declercq, Michel; Ionescu, Adrian Mihai

    2007-11-01

    An EKV-based high voltage MOSFET model is presented. The intrinsic channel model is derived based on the charge based EKV-formalism. An improved mobility model is used for the modeling of the intrinsic channel to improve the DC characteristics. The model uses second order dependence on the gate bias and an extra parameter for the smoothening of the saturation voltage of the intrinsic drain. An improved drift model [Chauhan YS, Anghel C, Krummenacher F, Ionescu AM, Declercq M, Gillon R, et al. A highly scalable high voltage MOSFET model. In: IEEE European solid-state device research conference (ESSDERC), September 2006. p. 270-3; Chauhan YS, Anghel C, Krummenacher F, Maier C, Gillon R, Bakeroot B, et al. Scalable general high voltage MOSFET model including quasi-saturation and self-heating effect. Solid State Electron 2006;50(11-12):1801-13] is used for the modeling of the drift region, which gives smoother transition on output characteristics and also models well the quasi-saturation region of high voltage MOSFETs. First, the model is validated on the numerical device simulation of the VDMOS transistor and then, on the measured characteristics of the SOI-LDMOS transistor. The accuracy of the model is better than our previous model [Chauhan YS, Anghel C, Krummenacher F, Maier C, Gillon R, Bakeroot B, et al. Scalable general high voltage MOSFET model including quasi-saturation and self-heating effect. Solid State Electron 2006;50(11-12):1801-13] especially in the quasi-saturation region of output characteristics.

  9. Model-Based and Model-Free Pavlovian Reward Learning: Revaluation, Revision and Revelation

    PubMed Central

    Dayan, Peter; Berridge, Kent C.

    2014-01-01

    Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation. PMID:24647659

  10. Model-based and model-free Pavlovian reward learning: revaluation, revision, and revelation.

    PubMed

    Dayan, Peter; Berridge, Kent C

    2014-06-01

    Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations, and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response, and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation.

  11. The HackensackUMC Value-Based Care Model: Building Essentials for Value-Based Purchasing.

    PubMed

    Douglas, Claudia; Aroh, Dianne; Colella, Joan; Quadri, Mohammed

    2016-01-01

    The Affordable Care Act, 2010, and the subsequent shift from a quantity-focus to a value-centric reimbursement model led our organization to create the HackensackUMC Value-Based Care Model to improve our process capability and performance to meet and sustain the triple aims of value-based purchasing: higher quality, lower cost, and consumer perception. This article describes the basics of our model and illustrates how we used it to reduce the costs of our patient sitter program.

  12. Model based control of dynamic atomic force microscope.

    PubMed

    Lee, Chibum; Salapaka, Srinivasa M

    2015-04-01

    A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

  13. A demonstrative model of a lunar base simulation on a personal computer

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The initial demonstration model of a lunar base simulation is described. This initial model was developed on the personal computer level to demonstrate feasibility and technique before proceeding to a larger computer-based model. Lotus Symphony Version 1.1 software was used to base the demonstration model on an personal computer with an MS-DOS operating system. The personal computer-based model determined the applicability of lunar base modeling techniques developed at an LSPI/NASA workshop. In addition, the personnal computer-based demonstration model defined a modeling structure that could be employed on a larger, more comprehensive VAX-based lunar base simulation. Refinement of this personal computer model and the development of a VAX-based model is planned in the near future.

  14. Model-Based Development of Automotive Electronic Climate Control Software

    NASA Astrophysics Data System (ADS)

    Kakade, Rupesh; Murugesan, Mohan; Perugu, Bhupal; Nair, Mohanan

    With increasing complexity of software in today's products, writing and maintaining thousands of lines of code is a tedious task. Instead, an alternative methodology must be employed. Model-based development is one candidate that offers several benefits and allows engineers to focus on the domain of their expertise than writing huge codes. In this paper, we discuss the application of model-based development to the electronic climate control software of vehicles. The back-to-back testing approach is presented that ensures flawless and smooth transition from legacy designs to the model-based development. Simulink report generator to create design documents from the models is presented along with its usage to run the simulation model and capture the results into the test report. Test automation using model-based development tool that support the use of unique set of test cases for several testing levels and the test procedure that is independent of software and hardware platform is also presented.

  15. Model-based influences on humans’ choices and striatal prediction errors

    PubMed Central

    Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

    2011-01-01

    Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

  16. Model-based influences on humans' choices and striatal prediction errors.

    PubMed

    Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

    2011-03-24

    The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

    PubMed

    Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

    2017-10-03

    In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  18. Scalable Entity-Based Modeling of Population-Based Systems, Final LDRD Report

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

    Cleary, A J; Smith, S G; Vassilevska, T K

    2005-01-27

    The goal of this project has been to develop tools, capabilities and expertise in the modeling of complex population-based systems via scalable entity-based modeling (EBM). Our initial focal application domain has been the dynamics of large populations exposed to disease-causing agents, a topic of interest to the Department of Homeland Security in the context of bioterrorism. In the academic community, discrete simulation technology based on individual entities has shown initial success, but the technology has not been scaled to the problem sizes or computational resources of LLNL. Our developmental emphasis has been on the extension of this technology to parallelmore » computers and maturation of the technology from an academic to a lab setting.« less

  19. Predictor-Based Model Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Lavretsky, Eugene; Gadient, Ross; Gregory, Irene M.

    2010-01-01

    This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

  20. IRT Models for Ability-Based Guessing

    ERIC Educational Resources Information Center

    Martin, Ernesto San; del Pino, Guido; De Boeck, Paul

    2006-01-01

    An ability-based guessing model is formulated and applied to several data sets regarding educational tests in language and in mathematics. The formulation of the model is such that the probability of a correct guess does not only depend on the item but also on the ability of the individual, weighted with a general discrimination parameter. By so…

  1. Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties.

    PubMed

    Salahinejad, Maryam

    2015-01-01

    Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

  2. Enabling Accessibility Through Model-Based User Interface Development.

    PubMed

    Ziegler, Daniel; Peissner, Matthias

    2017-01-01

    Adaptive user interfaces (AUIs) can increase the accessibility of interactive systems. They provide personalized display and interaction modes to fit individual user needs. Most AUI approaches rely on model-based development, which is considered relatively demanding. This paper explores strategies to make model-based development more attractive for mainstream developers.

  3. Clinic expert information extraction based on domain model and block importance model.

    PubMed

    Zhang, Yuanpeng; Wang, Li; Qian, Danmin; Geng, Xingyun; Yao, Dengfu; Dong, Jiancheng

    2015-11-01

    To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Two-phase nc-TiN/a-(C,CN{sub x}) nanocomposite films: A HRTEM and MC simulation study

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

    Guo, J.; Lu, Y. H.; Hu, X. J.

    2013-06-18

    The grain growth in two-phase nanocomposite Ti-C{sub x}-N{sub y} thin films grown by reactive close-field unbalanced magnetron sputtering in an Ar-N{sub 2} gas mixture with microstructures comprising of nanocrystalline (nc-) Ti(N,C) phase surrounded by amorphous (a-) (C,CN{sub x}) phase was investigated by a combination of high-resolution transmission electron microscopy (HRTEM) and Monte Carlo (MC) simulations. The HRTEM results revealed that amorphous-free solid solution Ti(C,N) thin films exhibited polycrystallites with different sizes, orientations and irregular shapes. The grain size varied in the range between several nanometers and several decade nanometers. Further increase of C content (up to {approx}19 at.% C) mademore » the amorphous phase wet nanocrystallites, which strongly hindered the growth of nanocrystallites. As a result, more regular Ti(C,N) nanocrystallites with an average size of {approx}5 nm were found to be separated by {approx}0.5-nm amorphous phases. When C content was further increased (up to {approx}48 at.% in this study), thicker amorphous matrices were produced and followed by the formation of smaller sized grains with lognormal distribution. Our MC analysis indicated that with increasing amorphous volume fraction (i.e. increasing C content), the transformation from nc/nc grain boundary (GB)-curvature-driven growth to a/nc GB-curvature-driven growth is directly responsible for the observed grain growth from great inhomogeneity to homogeneity process.« less

  5. An object-based storage model for distributed remote sensing images

    NASA Astrophysics Data System (ADS)

    Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

    2006-10-01

    It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

  6. Consideration of VT5 etch-based OPC modeling

    NASA Astrophysics Data System (ADS)

    Lim, ChinTeong; Temchenko, Vlad; Kaiser, Dieter; Meusel, Ingo; Schmidt, Sebastian; Schneider, Jens; Niehoff, Martin

    2008-03-01

    Including etch-based empirical data during OPC model calibration is a desired yet controversial decision for OPC modeling, especially for process with a large litho to etch biasing. While many OPC software tools are capable of providing this functionality nowadays; yet few were implemented in manufacturing due to various risks considerations such as compromises in resist and optical effects prediction, etch model accuracy or even runtime concern. Conventional method of applying rule-based alongside resist model is popular but requires a lot of lengthy code generation to provide a leaner OPC input. This work discusses risk factors and their considerations, together with introduction of techniques used within Mentor Calibre VT5 etch-based modeling at sub 90nm technology node. Various strategies are discussed with the aim of better handling of large etch bias offset without adding complexity into final OPC package. Finally, results were presented to assess the advantages and limitations of the final method chosen.

  7. Model-based Utility Functions

    NASA Astrophysics Data System (ADS)

    Hibbard, Bill

    2012-05-01

    Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.

  8. An MPI-based MoSST core dynamics model

    NASA Astrophysics Data System (ADS)

    Jiang, Weiyuan; Kuang, Weijia

    2008-09-01

    Distributed systems are among the main cost-effective and expandable platforms for high-end scientific computing. Therefore scalable numerical models are important for effective use of such systems. In this paper, we present an MPI-based numerical core dynamics model for simulation of geodynamo and planetary dynamos, and for simulation of core-mantle interactions. The model is developed based on MPI libraries. Two algorithms are used for node-node communication: a "master-slave" architecture and a "divide-and-conquer" architecture. The former is easy to implement but not scalable in communication. The latter is scalable in both computation and communication. The model scalability is tested on Linux PC clusters with up to 128 nodes. This model is also benchmarked with a published numerical dynamo model solution.

  9. Applying the X-ray diffraction analysis for estimating the height and width of nanorods in low symmetry crystal multiphase materials

    NASA Astrophysics Data System (ADS)

    Mokhtari, Ali; Soleimanian, Vishtasb; Dehkordi, Hamed Aleebrahim; Dastafkan, Kamran

    2017-11-01

    In this work the potential of Rietveld refinement procedure is used to study the shape and size of non-spherical nanocrystallites. The main advantages of this approach are that not only it can successfully extend to all nanomaterials with different crystal symmetries but also it can evaluate the various phases of multiple materials comparing to electron microscopy methods. Therefore, between seven crystal systems, the formulation of monoclinic and hexagonal crystals is developed. This procedure is applied for the mixture of sodium carbonate and zinc oxide nanocrystallites at different fractions of doped gadolinium oxide. It is found that the crystallites of sodium carbonate and zinc oxide have the rod and ellipsoidal shapes, respectively. The microstructure results are compared with the results of scanning electron microscopy imaging. Good agreement is achieved between the results of scanning electron microscopy and Rietveld methods.

  10. Low-energy electron irradiation induced top-surface nanocrystallization of amorphous carbon film

    NASA Astrophysics Data System (ADS)

    Chen, Cheng; Fan, Xue; Diao, Dongfeng

    2016-10-01

    We report a low-energy electron irradiation method to nanocrystallize the top-surface of amorphous carbon film in electron cyclotron resonance plasma system. The nanostructure evolution of the carbon film as a function of electron irradiation density and time was examined by transmission electron microscope (TEM) and Raman spectroscopy. The results showed that the electron irradiation gave rise to the formation of sp2 nanocrystallites in the film top-surface within 4 nm thickness. The formation of sp2 nanocrystallite was ascribed to the inelastic electron scattering in the top-surface of carbon film. The frictional property of low-energy electron irradiated film was measured by a pin-on-disk tribometer. The sp2 nanocrystallized top-surface induced a lower friction coefficient than that of the original pure amorphous film. This method enables a convenient nanocrystallization of amorphous surface.

  11. Adsorption of vitamin E on mesoporous titania nanocrystals

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

    Shih, C.J., E-mail: cjshih@kmu.edu.tw; Lin, C.T.; Wu, S.M.

    2010-07-15

    Tri-block nonionic surfactant and titanium chloride were used as starting materials for the synthesis of mesoporous titania nanocrystallite powders. The main objective of the present study was to examine the synthesis of mesoporous titania nanocrystals and the adsorption of vitamin E on those nanocrystals using X-ray diffraction (XRD), transmission electron microscopy, and nitrogen adsorption and desorption isotherms. When the calcination temperature was increased to 300 {sup o}C, the reflection peaks in the XRD pattern indicated the presence of an anatase phase. The crystallinity of the nanocrystallites increased from 80% to 98.6% with increasing calcination temperature from 465 {sup o}C tomore » 500 {sup o}C. The N{sub 2} adsorption data and XRD data taken after vitamin E adsorption revealed that the vitamin E molecules were adsorbed in the mesopores of the titania nanocrystals.« less

  12. Model-based clustering for RNA-seq data.

    PubMed

    Si, Yaqing; Liu, Peng; Li, Pinghua; Brutnell, Thomas P

    2014-01-15

    RNA-seq technology has been widely adopted as an attractive alternative to microarray-based methods to study global gene expression. However, robust statistical tools to analyze these complex datasets are still lacking. By grouping genes with similar expression profiles across treatments, cluster analysis provides insight into gene functions and networks, and hence is an important technique for RNA-seq data analysis. In this manuscript, we derive clustering algorithms based on appropriate probability models for RNA-seq data. An expectation-maximization algorithm and another two stochastic versions of expectation-maximization algorithms are described. In addition, a strategy for initialization based on likelihood is proposed to improve the clustering algorithms. Moreover, we present a model-based hybrid-hierarchical clustering method to generate a tree structure that allows visualization of relationships among clusters as well as flexibility of choosing the number of clusters. Results from both simulation studies and analysis of a maize RNA-seq dataset show that our proposed methods provide better clustering results than alternative methods such as the K-means algorithm and hierarchical clustering methods that are not based on probability models. An R package, MBCluster.Seq, has been developed to implement our proposed algorithms. This R package provides fast computation and is publicly available at http://www.r-project.org

  13. Image-Based Predictive Modeling of Heart Mechanics.

    PubMed

    Wang, V Y; Nielsen, P M F; Nash, M P

    2015-01-01

    Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation.

  14. Web-based Interactive Landform Simulation Model - Grand Canyon

    NASA Astrophysics Data System (ADS)

    Luo, W.; Pelletier, J. D.; Duffin, K.; Ormand, C. J.; Hung, W.; Iverson, E. A.; Shernoff, D.; Zhai, X.; Chowdary, A.

    2013-12-01

    Earth science educators need interactive tools to engage and enable students to better understand how Earth systems work over geologic time scales. The evolution of landforms is ripe for interactive, inquiry-based learning exercises because landforms exist all around us. The Web-based Interactive Landform Simulation Model - Grand Canyon (WILSIM-GC, http://serc.carleton.edu/landform/) is a continuation and upgrade of the simple cellular automata (CA) rule-based model (WILSIM-CA, http://www.niu.edu/landform/) that can be accessed from anywhere with an Internet connection. Major improvements in WILSIM-GC include adopting a physically based model and the latest Java technology. The physically based model is incorporated to illustrate the fluvial processes involved in land-sculpting pertaining to the development and evolution of one of the most famous landforms on Earth: the Grand Canyon. It is hoped that this focus on a famous and specific landscape will attract greater student interest and provide opportunities for students to learn not only how different processes interact to form the landform we observe today, but also how models and data are used together to enhance our understanding of the processes involved. The latest development in Java technology (such as Java OpenGL for access to ubiquitous fast graphics hardware, Trusted Applet for file input and output, and multithreaded ability to take advantage of modern multi-core CPUs) are incorporated into building WILSIM-GC and active, standards-aligned curricula materials guided by educational psychology theory on science learning will be developed to accompany the model. This project is funded NSF-TUES program.

  15. Structural and optical properties of ZnO thin films prepared by RF sputtering at different thicknesses

    NASA Astrophysics Data System (ADS)

    Hammad, Ahmed H.; Abdel-wahab, M. Sh.; Vattamkandathil, Sajith; Ansari, Akhalakur Rahman

    2018-07-01

    Hexagonal nanocrystallites of ZnO in the form of thin films were prepared by radio frequency sputtering technique. X-ray diffraction analysis reveals two prominent diffraction planes (002) and (103) at diffraction angles around 34.3 and 62.8°, respectively. The crystallite size increases through (103) plane from 56.1 to 64.8 Å as film thickness changed from 31 nm up to 280 nm while crystallites growth through (002) increased from 124 to 136 Å as film thickness varies from 31 to 107 nm and dropped to 115.8 Å at thickness 280 nm. The particle shape changes from spherical to longitudinal form. The particle size is 25 nm for films of thickness below 107 nm and increases at higher thicknesses (134 and 280 nm) from 30 to 40 nm, respectively. Optical band gap is deduced to be direct with values varied from 3.22 to 3.28 eV and the refractive index are evaluated based on the optical band values according to Moss, Ravindra-Srivastava, and Dimitrov-Sakka models. All refractive index models gave values around 2.3.

  16. Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

    PubMed

    Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

    2011-11-01

    There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

  17. Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

    DTIC Science & Technology

    2009-08-01

    has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

  18. SHM-Based Probabilistic Fatigue Life Prediction for Bridges Based on FE Model Updating

    PubMed Central

    Lee, Young-Joo; Cho, Soojin

    2016-01-01

    Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed. PMID:26950125

  19. Problem Solving: Physics Modeling-Based Interactive Engagement

    ERIC Educational Resources Information Center

    Ornek, Funda

    2009-01-01

    The purpose of this study was to investigate how modeling-based instruction combined with an interactive-engagement teaching approach promotes students' problem solving abilities. I focused on students in a calculus-based introductory physics course, based on the matter and interactions curriculum of Chabay & Sherwood (2002) at a large state…

  20. Differential geometry based solvation model. III. Quantum formulation

    PubMed Central

    Chen, Zhan; Wei, Guo-Wei

    2011-01-01

    Solvation is of fundamental importance to biomolecular systems. Implicit solvent models, particularly those based on the Poisson-Boltzmann equation for electrostatic analysis, are established approaches for solvation analysis. However, ad hoc solvent-solute interfaces are commonly used in the implicit solvent theory. Recently, we have introduced differential geometry based solvation models which allow the solvent-solute interface to be determined by the variation of a total free energy functional. Atomic fixed partial charges (point charges) are used in our earlier models, which depends on existing molecular mechanical force field software packages for partial charge assignments. As most force field models are parameterized for a certain class of molecules or materials, the use of partial charges limits the accuracy and applicability of our earlier models. Moreover, fixed partial charges do not account for the charge rearrangement during the solvation process. The present work proposes a differential geometry based multiscale solvation model which makes use of the electron density computed directly from the quantum mechanical principle. To this end, we construct a new multiscale total energy functional which consists of not only polar and nonpolar solvation contributions, but also the electronic kinetic and potential energies. By using the Euler-Lagrange variation, we derive a system of three coupled governing equations, i.e., the generalized Poisson-Boltzmann equation for the electrostatic potential, the generalized Laplace-Beltrami equation for the solvent-solute boundary, and the Kohn-Sham equations for the electronic structure. We develop an iterative procedure to solve three coupled equations and to minimize the solvation free energy. The present multiscale model is numerically validated for its stability, consistency and accuracy, and is applied to a few sets of molecules, including a case which is difficult for existing solvation models. Comparison is made

  1. Multiscale agent-based cancer modeling.

    PubMed

    Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

    2009-04-01

    Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

  2. Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

    NASA Technical Reports Server (NTRS)

    Benazera, Emmanuel; Trave-Massuyes, Louise

    2004-01-01

    Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

  3. Individual-based models in ecology after four decades

    PubMed Central

    Grimm, Volker

    2014-01-01

    Individual-based models simulate populations and communities by following individuals and their properties. They have been used in ecology for more than four decades, with their use and ubiquity in ecology growing rapidly in the last two decades. Individual-based models have been used for many applied or “pragmatic” issues, such as informing the protection and management of particular populations in specific locations, but their use in addressing theoretical questions has also grown rapidly, recently helping us to understand how the sets of traits of individual organisms influence the assembly of communities and food webs. Individual-based models will play an increasingly important role in questions posed by complex ecological systems. PMID:24991416

  4. Model for the design of distributed data bases

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

    Ram, S.

    This research focuses on developing a model to solve the File Allocation Problem (FAP). The model integrates two major design issues, namely Concurrently Control and Data Distribution. The central node locking mechanism is incorporated in developing a nonlinear integer programming model. Two solution algorithms are proposed, one of which was implemented in FORTRAN.V. The allocation of data bases and programs are examined using this heuristic. Several decision rules were also formulated based on the results of the heuristic. A second more comprehensive heuristic was proposed, based on the knapsack problem. The development and implementation of this algorithm has been leftmore » as a topic for future research.« less

  5. Model Hierarchies in Edge-Based Compartmental Modeling for Infectious Disease Spread

    PubMed Central

    Miller, Joel C.; Volz, Erik M.

    2012-01-01

    We consider the family of edge-based compartmental models for epidemic spread developed in [11]. These models allow for a range of complex behaviors, and in particular allow us to explicitly incorporate duration of a contact into our mathematical models. Our focus here is to identify conditions under which simpler models may be substituted for more detailed models, and in so doing we define a hierarchy of epidemic models. In particular we provide conditions under which it is appropriate to use the standard mass action SIR model, and we show what happens when these conditions fail. Using our hierarchy, we provide a procedure leading to the choice of the appropriate model for a given population. Our result about the convergence of models to the Mass Action model gives clear, rigorous conditions under which the Mass Action model is accurate. PMID:22911242

  6. Wet spinning of fibers made of chitosan and chitin nanofibrils.

    PubMed

    Yudin, Vladimir E; Dobrovolskaya, Irina P; Neelov, Igor M; Dresvyanina, Elena N; Popryadukhin, Pavel V; Ivan'kova, Elena M; Elokhovskii, Vladimir Yu; Kasatkin, Igor A; Okrugin, Boris M; Morganti, Pierfrancesco

    2014-08-08

    Biocompatible and bioresorbable composite fibers consisting of chitosan filled with anisotropic chitin nanofibrils with the length of 600-800 nm and cross section of about 11-12 nm as revealed by SEM and XRD were prepared by coagulation. Both chitin and chitosan components of the composite fibers displayed preferred orientations. Orientation of chitosan molecules induced by chitin nanocrystallites was confirmed by molecular modeling. The incorporation of 0.1-0.3 wt.% of chitin nanofibrils into chitosan matrix led to an increase in strength and Young modulus of the composite fibers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Charge-based MOSFET model based on the Hermite interpolation polynomial

    NASA Astrophysics Data System (ADS)

    Colalongo, Luigi; Richelli, Anna; Kovacs, Zsolt

    2017-04-01

    An accurate charge-based compact MOSFET model is developed using the third order Hermite interpolation polynomial to approximate the relation between surface potential and inversion charge in the channel. This new formulation of the drain current retains the same simplicity of the most advanced charge-based compact MOSFET models such as BSIM, ACM and EKV, but it is developed without requiring the crude linearization of the inversion charge. Hence, the asymmetry and the non-linearity in the channel are accurately accounted for. Nevertheless, the expression of the drain current can be worked out to be analytically equivalent to BSIM, ACM and EKV. Furthermore, thanks to this new mathematical approach the slope factor is rigorously defined in all regions of operation and no empirical assumption is required.

  8. Agent-Based Modeling of Growth Processes

    ERIC Educational Resources Information Center

    Abraham, Ralph

    2014-01-01

    Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

  9. Development of uncertainty-based work injury model using Bayesian structural equation modelling.

    PubMed

    Chatterjee, Snehamoy

    2014-01-01

    This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

  10. Leveraging annotation-based modeling with Jump.

    PubMed

    Bergmayr, Alexander; Grossniklaus, Michael; Wimmer, Manuel; Kappel, Gerti

    2018-01-01

    The capability of UML profiles to serve as annotation mechanism has been recognized in both research and industry. Today's modeling tools offer profiles specific to platforms, such as Java, as they facilitate model-based engineering approaches. However, considering the large number of possible annotations in Java, manually developing the corresponding profiles would only be achievable by huge development and maintenance efforts. Thus, leveraging annotation-based modeling requires an automated approach capable of generating platform-specific profiles from Java libraries. To address this challenge, we present the fully automated transformation chain realized by Jump, thereby continuing existing mapping efforts between Java and UML by emphasizing on annotations and profiles. The evaluation of Jump shows that it scales for large Java libraries and generates profiles of equal or even improved quality compared to profiles currently used in practice. Furthermore, we demonstrate the practical value of Jump by contributing profiles that facilitate reverse engineering and forward engineering processes for the Java platform by applying it to a modernization scenario.

  11. Diagnosing Students' Mental Models via the Web-Based Mental Models Diagnosis System

    ERIC Educational Resources Information Center

    Wang, Tzu-Hua; Chiu, Mei-Hung; Lin, Jing-Wen; Chou, Chin-Cheng

    2013-01-01

    Mental models play an important role in science education research. To extend the effectiveness of conceptual change research and to improve mental model identi?cation and diagnosis, the authors developed and tested the Web-Based Mental Models Diagnosis (WMMD) system. In this article, they describe their WMMD system, which goes beyond the…

  12. Dopamine selectively remediates 'model-based' reward learning: a computational approach.

    PubMed

    Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

    2016-02-01

    Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. CAD-based Automatic Modeling Method for Geant4 geometry model Through MCAM

    NASA Astrophysics Data System (ADS)

    Wang, Dong; Nie, Fanzhi; Wang, Guozhong; Long, Pengcheng; LV, Zhongliang; LV, Zhongliang

    2014-06-01

    Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problem existed in most of present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics & Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling.

  14. Modeling of driver's collision avoidance maneuver based on controller switching model.

    PubMed

    Kim, Jong-Hae; Hayakawa, Soichiro; Suzuki, Tatsuya; Hayashi, Koji; Okuma, Shigeru; Tsuchida, Nuio; Shimizu, Masayuki; Kido, Shigeyuki

    2005-12-01

    This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

  15. MECHANISTIC-BASED DISINFECTION AND DISINFECTION BYPRODUCT MODELS

    EPA Science Inventory

    We propose developing a mechanistic-based numerical model for chlorine decay and regulated DBP (THM and HAA) formation derived from (free) chlorination; the model framework will allow future modifications for other DBPs and chloramination. Predicted chlorine residual and DBP r...

  16. Deep particle bed dryout model based on flooding

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

    Kuan, P.

    1987-01-01

    Examination of the damaged Three Mile island Unit 2 (TMI-2) reactor indicates that a deep (approx. 1-m) bed of relatively large (approx. 1-mm) particles was formed in the core. Cooling of such beds is crucial to the arrest of core damage progression. The Lipinski model, based on flows in the bed, has been used to predict the coolability, but uncertainties exist in the turbulent permeability. Models based on flooding at the top of the bed either have a dimensional viscosity term, or no viscosity dependence, thus limiting their applicability. This paper presents a dimensionless correlation based on flooding data thatmore » involves a liquid Reynolds number. The derived dryout model from this correlation is compared with data for deep beds of large particles at atmospheric pressure, and with other models over a wide pressure range. It is concluded that the present model can give quite accurate predictions for the dryout heat flux of particle beds formed during a light water reactor accident and it is easy to use and agrees with the Lipinski n = 5 model, which requires iterative calculations.« less

  17. A global parallel model based design of experiments method to minimize model output uncertainty.

    PubMed

    Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

    2012-03-01

    Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

  18. Modeling Micro-cracking Behavior of Bukit Timah Granite Using Grain-Based Model

    NASA Astrophysics Data System (ADS)

    Peng, Jun; Wong, Louis Ngai Yuen; Teh, Cee Ing; Li, Zhihuan

    2018-01-01

    Rock strength and deformation behavior has long been recognized to be closely related to the microstructure and the associated micro-cracking process. A good understanding of crack initiation and coalescence mechanisms will thus allow us to account for the variation of rock strength and deformation properties from a microscopic view. This paper numerically investigates the micro-cracking behavior of Bukit Timah granite by using a grain-based modeling approach. First, the principles of grain-based model adopted in the two-dimensional Particle Flow Code and the numerical model generation procedure are reviewed. The micro-parameters of the numerical model are then calibrated to match the macro-properties of the rock obtained from tension and compression tests in the laboratory. The simulated rock properties are in good agreement with the laboratory test results with the errors less than ±6%. Finally, the calibrated model is used to study the micro-cracking behavior and the failure modes of the rock under direct tension and under compression with different confining pressures. The results reveal that when the numerical model is loaded in direct tension, only grain boundary tensile cracks are generated, and the simulated macroscopic fracture agrees well with the results obtained in laboratory tests. When the model is loaded in compression, the ratio of grain boundary tensile cracks to grain boundary shear cracks decreases with the increase in confining pressure. In other words, the results show that as the confining pressure increases, the failure mechanism changes from tension to shear. The simulated failure mode of the model changes from splitting to shear as the applied confining pressure gradually increases, which is comparable with that observed in laboratory tests. The grain-based model used in this study thus appears promising for further investigation of microscopic and macroscopic behavior of crystalline rocks under different loading conditions.

  19. FacetModeller: Software for manual creation, manipulation and analysis of 3D surface-based models

    NASA Astrophysics Data System (ADS)

    Lelièvre, Peter G.; Carter-McAuslan, Angela E.; Dunham, Michael W.; Jones, Drew J.; Nalepa, Mariella; Squires, Chelsea L.; Tycholiz, Cassandra J.; Vallée, Marc A.; Farquharson, Colin G.

    2018-01-01

    The creation of 3D models is commonplace in many disciplines. Models are often built from a collection of tessellated surfaces. To apply numerical methods to such models it is often necessary to generate a mesh of space-filling elements that conforms to the model surfaces. While there are meshing algorithms that can do so, they place restrictive requirements on the surface-based models that are rarely met by existing 3D model building software. Hence, we have developed a Java application named FacetModeller, designed for efficient manual creation, modification and analysis of 3D surface-based models destined for use in numerical modelling.

  20. Information visualisation based on graph models

    NASA Astrophysics Data System (ADS)

    Kasyanov, V. N.; Kasyanova, E. V.

    2013-05-01

    Information visualisation is a key component of support tools for many applications in science and engineering. A graph is an abstract structure that is widely used to model information for its visualisation. In this paper, we consider practical and general graph formalism called hierarchical graphs and present the Higres and Visual Graph systems aimed at supporting information visualisation on the base of hierarchical graph models.

  1. CAN-Care: an innovative model of practice-based learning.

    PubMed

    Raines, Deborah A

    2006-01-01

    The "Collaborative Approach to Nursing Care" (CAN-Care) Model of practice-based education is designed to meet the unique learning needs of the accelerated nursing program student. The model is based on a synergistic partnership between the academic and service settings, the vision of which is to create an innovative practice-based learning model, resulting in a positive experience for both the student and unit-based nurse. Thus, the objectives of quality outcomes for both the college and Health Care Organization are fulfilled. Specifically, the goal is the education of nurses ready to meet the challenges of caring for persons in the complex health care environment of the 21st century.

  2. Dependability modeling and assessment in UML-based software development.

    PubMed

    Bernardi, Simona; Merseguer, José; Petriu, Dorina C

    2012-01-01

    Assessment of software nonfunctional properties (NFP) is an important problem in software development. In the context of model-driven development, an emerging approach for the analysis of different NFPs consists of the following steps: (a) to extend the software models with annotations describing the NFP of interest; (b) to transform automatically the annotated software model to the formalism chosen for NFP analysis; (c) to analyze the formal model using existing solvers; (d) to assess the software based on the results and give feedback to designers. Such a modeling→analysis→assessment approach can be applied to any software modeling language, be it general purpose or domain specific. In this paper, we focus on UML-based development and on the dependability NFP, which encompasses reliability, availability, safety, integrity, and maintainability. The paper presents the profile used to extend UML with dependability information, the model transformation to generate a DSPN formal model, and the assessment of the system properties based on the DSPN results.

  3. Dependability Modeling and Assessment in UML-Based Software Development

    PubMed Central

    Bernardi, Simona; Merseguer, José; Petriu, Dorina C.

    2012-01-01

    Assessment of software nonfunctional properties (NFP) is an important problem in software development. In the context of model-driven development, an emerging approach for the analysis of different NFPs consists of the following steps: (a) to extend the software models with annotations describing the NFP of interest; (b) to transform automatically the annotated software model to the formalism chosen for NFP analysis; (c) to analyze the formal model using existing solvers; (d) to assess the software based on the results and give feedback to designers. Such a modeling→analysis→assessment approach can be applied to any software modeling language, be it general purpose or domain specific. In this paper, we focus on UML-based development and on the dependability NFP, which encompasses reliability, availability, safety, integrity, and maintainability. The paper presents the profile used to extend UML with dependability information, the model transformation to generate a DSPN formal model, and the assessment of the system properties based on the DSPN results. PMID:22988428

  4. Model based rib-cage unfolding for trauma CT

    NASA Astrophysics Data System (ADS)

    von Berg, Jens; Klinder, Tobias; Lorenz, Cristian

    2018-03-01

    A CT rib-cage unfolding method is proposed that does not require to determine rib centerlines but determines the visceral cavity surface by model base segmentation. Image intensities are sampled across this surface that is flattened using a model based 3D thin-plate-spline registration. An average rib centerline model projected onto this surface serves as a reference system for registration. The flattening registration is designed so that ribs similar to the centerline model are mapped onto parallel lines preserving their relative length. Ribs deviating from this model appear deviating from straight parallel ribs in the unfolded view, accordingly. As the mapping is continuous also the details in intercostal space and those adjacent to the ribs are rendered well. The most beneficial application area is Trauma CT where a fast detection of rib fractures is a crucial task. Specifically in trauma, automatic rib centerline detection may not be guaranteed due to fractures and dislocations. The application by visual assessment on the large public LIDC data base of lung CT proved general feasibility of this early work.

  5. Sandboxes for Model-Based Inquiry

    ERIC Educational Resources Information Center

    Brady, Corey; Holbert, Nathan; Soylu, Firat; Novak, Michael; Wilensky, Uri

    2015-01-01

    In this article, we introduce a class of constructionist learning environments that we call "Emergent Systems Sandboxes" ("ESSs"), which have served as a centerpiece of our recent work in developing curriculum to support scalable model-based learning in classroom settings. ESSs are a carefully specified form of virtual…

  6. Bridging process-based and empirical approaches to modeling tree growth

    Treesearch

    Harry T. Valentine; Annikki Makela; Annikki Makela

    2005-01-01

    The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

  7. Model-Based Fault Tolerant Control

    NASA Technical Reports Server (NTRS)

    Kumar, Aditya; Viassolo, Daniel

    2008-01-01

    The Model Based Fault Tolerant Control (MBFTC) task was conducted under the NASA Aviation Safety and Security Program. The goal of MBFTC is to develop and demonstrate real-time strategies to diagnose and accommodate anomalous aircraft engine events such as sensor faults, actuator faults, or turbine gas-path component damage that can lead to in-flight shutdowns, aborted take offs, asymmetric thrust/loss of thrust control, or engine surge/stall events. A suite of model-based fault detection algorithms were developed and evaluated. Based on the performance and maturity of the developed algorithms two approaches were selected for further analysis: (i) multiple-hypothesis testing, and (ii) neural networks; both used residuals from an Extended Kalman Filter to detect the occurrence of the selected faults. A simple fusion algorithm was implemented to combine the results from each algorithm to obtain an overall estimate of the identified fault type and magnitude. The identification of the fault type and magnitude enabled the use of an online fault accommodation strategy to correct for the adverse impact of these faults on engine operability thereby enabling continued engine operation in the presence of these faults. The performance of the fault detection and accommodation algorithm was extensively tested in a simulation environment.

  8. A Model-Based Expert System for Space Power Distribution Diagnostics

    NASA Technical Reports Server (NTRS)

    Quinn, Todd M.; Schlegelmilch, Richard F.

    1994-01-01

    When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

  9. Development of a GCR Event-based Risk Model

    NASA Technical Reports Server (NTRS)

    Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

    2009-01-01

    A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how

  10. Model Based Verification of Cyber Range Event Environments

    DTIC Science & Technology

    2015-12-10

    Model Based Verification of Cyber Range Event Environments Suresh K. Damodaran MIT Lincoln Laboratory 244 Wood St., Lexington, MA, USA...apply model based verification to cyber range event environment configurations, allowing for the early detection of errors in event environment...Environment Representation (CCER) ontology. We also provide an overview of a methodology to specify verification rules and the corresponding error

  11. Probability based models for estimation of wildfire risk

    Treesearch

    Haiganoush Preisler; D. R. Brillinger; R. E. Burgan; John Benoit

    2004-01-01

    We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km²-day cell level. We fit a spatially and temporally explicit non-...

  12. Modeling Web-Based Educational Systems: Process Design Teaching Model

    ERIC Educational Resources Information Center

    Rokou, Franca Pantano; Rokou, Elena; Rokos, Yannis

    2004-01-01

    Using modeling languages is essential to the construction of educational systems based on software engineering principles and methods. Furthermore, the instructional design is undoubtedly the cornerstone of the design and development of educational systems. Although several methodologies and languages have been proposed for the specification of…

  13. A semi-analytical bearing model considering outer race flexibility for model based bearing load monitoring

    NASA Astrophysics Data System (ADS)

    Kerst, Stijn; Shyrokau, Barys; Holweg, Edward

    2018-05-01

    This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.

  14. An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling.

    PubMed

    Blanton, Brian; Dresback, Kendra; Colle, Brian; Kolar, Randy; Vergara, Humberto; Hong, Yang; Leonardo, Nicholas; Davidson, Rachel; Nozick, Linda; Wachtendorf, Tricia

    2018-04-25

    Hurricane track and intensity can change rapidly in unexpected ways, thus making predictions of hurricanes and related hazards uncertain. This inherent uncertainty often translates into suboptimal decision-making outcomes, such as unnecessary evacuation. Representing this uncertainty is thus critical in evacuation planning and related activities. We describe a physics-based hazard modeling approach that (1) dynamically accounts for the physical interactions among hazard components and (2) captures hurricane evolution uncertainty using an ensemble method. This loosely coupled model system provides a framework for probabilistic water inundation and wind speed levels for a new, risk-based approach to evacuation modeling, described in a companion article in this issue. It combines the Weather Research and Forecasting (WRF) meteorological model, the Coupled Routing and Excess STorage (CREST) hydrologic model, and the ADvanced CIRCulation (ADCIRC) storm surge, tide, and wind-wave model to compute inundation levels and wind speeds for an ensemble of hurricane predictions. Perturbations to WRF's initial and boundary conditions and different model physics/parameterizations generate an ensemble of storm solutions, which are then used to drive the coupled hydrologic + hydrodynamic models. Hurricane Isabel (2003) is used as a case study to illustrate the ensemble-based approach. The inundation, river runoff, and wind hazard results are strongly dependent on the accuracy of the mesoscale meteorological simulations, which improves with decreasing lead time to hurricane landfall. The ensemble envelope brackets the observed behavior while providing "best-case" and "worst-case" scenarios for the subsequent risk-based evacuation model. © 2018 Society for Risk Analysis.

  15. SWIFT MODELLER: a Java based GUI for molecular modeling.

    PubMed

    Mathur, Abhinav; Shankaracharya; Vidyarthi, Ambarish S

    2011-10-01

    MODELLER is command line argument based software which requires tedious formatting of inputs and writing of Python scripts which most people are not comfortable with. Also the visualization of output becomes cumbersome due to verbose files. This makes the whole software protocol very complex and requires extensive study of MODELLER manuals and tutorials. Here we describe SWIFT MODELLER, a GUI that automates formatting, scripting and data extraction processes and present it in an interactive way making MODELLER much easier to use than before. The screens in SWIFT MODELLER are designed keeping homology modeling in mind and their flow is a depiction of its steps. It eliminates the formatting of inputs, scripting processes and analysis of verbose output files through automation and makes pasting of the target sequence as the only prerequisite. Jmol (3D structure visualization tool) has been integrated into the GUI which opens and demonstrates the protein data bank files created by the MODELLER software. All files required and created by the software are saved in a folder named after the work instance's date and time of execution. SWIFT MODELLER lowers the skill level required for the software through automation of many of the steps in the original software protocol, thus saving an enormous amount of time per instance and making MODELLER very easy to work with.

  16. Model reduction for agent-based social simulation: coarse-graining a civil violence model.

    PubMed

    Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  17. Model reduction for agent-based social simulation: Coarse-graining a civil violence model

    NASA Astrophysics Data System (ADS)

    Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  18. Performability modeling based on real data: A case study

    NASA Technical Reports Server (NTRS)

    Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

    1988-01-01

    Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

  19. Second Generation Models for Strain-Based Design

    DOT National Transportation Integrated Search

    2011-08-30

    This project covers the development of tensile strain design models which form a key part of the strain-based design of pipelines. The strain-based design includes at least two limit states, tensile rupture, and compressive buckling. The tensile stra...

  20. Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

    NASA Astrophysics Data System (ADS)

    Tang, W.; Cohan, D. S.; Lamsal, L. N.; Xiao, X.; Zhou, W.

    2013-11-01

    Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

  1. Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

    NASA Astrophysics Data System (ADS)

    Tang, W.; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

    2013-07-01

    Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

  2. Toward semantic-based retrieval of visual information: a model-based approach

    NASA Astrophysics Data System (ADS)

    Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

    2002-07-01

    This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

  3. Influence Diffusion Model in Text-Based Communication

    NASA Astrophysics Data System (ADS)

    Matsumura, Naohiro; Ohsawa, Yukio; Ishizuka, Mitsuru

    Business people, especially marketing researchers, are keen to understand peoples' potential sense of value to create fascinating topics stimulating peoples' interest. In this paper, we aim at finding influential people, comments, and terms contributing the discovery of such topics. For this purpose, we propose an Influence Diffusion Model in text-based communication, where the influence of people, comments, and terms are defined as the degree of text-based relevance of messages. We apply this model to Bulletin Board Service(BBS) on the Internet, and present our discoveries on experimental evaluations.

  4. Not just the norm: exemplar-based models also predict face aftereffects.

    PubMed

    Ross, David A; Deroche, Mickael; Palmeri, Thomas J

    2014-02-01

    The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted toward a face with attributes opposite to those of the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here, we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation.

  5. Not Just the Norm: Exemplar-Based Models also Predict Face Aftereffects

    PubMed Central

    Ross, David A.; Deroche, Mickael; Palmeri, Thomas J.

    2014-01-01

    The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted towards a face with opposite attributes to the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation. PMID:23690282

  6. AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

    EPA Science Inventory

    We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

  7. Knowledge representation to support reasoning based on multiple models

    NASA Technical Reports Server (NTRS)

    Gillam, April; Seidel, Jorge P.; Parker, Alice C.

    1990-01-01

    Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

  8. [Model-based biofuels system analysis: a review].

    PubMed

    Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

    2011-03-01

    Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

  9. Modeling analysis of pulsed magnetization process of magnetic core based on inverse Jiles-Atherton model

    NASA Astrophysics Data System (ADS)

    Liu, Yi; Zhang, He; Liu, Siwei; Lin, Fuchang

    2018-05-01

    The J-A (Jiles-Atherton) model is widely used to describe the magnetization characteristics of magnetic cores in a low-frequency alternating field. However, this model is deficient in the quantitative analysis of the eddy current loss and residual loss in a high-frequency magnetic field. Based on the decomposition of magnetization intensity, an inverse J-A model is established which uses magnetic flux density B as an input variable. Static and dynamic core losses under high frequency excitation are separated based on the inverse J-A model. Optimized parameters of the inverse J-A model are obtained based on particle swarm optimization. The platform for the pulsed magnetization characteristic test is designed and constructed. The hysteresis curves of ferrite and Fe-based nanocrystalline cores at high magnetization rates are measured. The simulated and measured hysteresis curves are presented and compared. It is found that the inverse J-A model can be used to describe the magnetization characteristics at high magnetization rates and to separate the static loss and dynamic loss accurately.

  10. Cognitive control predicts use of model-based reinforcement learning.

    PubMed

    Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

    2015-02-01

    Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

  11. Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

    PubMed Central

    Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

    2015-01-01

    Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

  12. Mechanics model for actin-based motility

    NASA Astrophysics Data System (ADS)

    Lin, Yuan

    2009-02-01

    We present here a mechanics model for the force generation by actin polymerization. The possible adhesions between the actin filaments and the load surface, as well as the nucleation and capping of filament tips, are included in this model on top of the well-known elastic Brownian ratchet formulation. A closed form solution is provided from which the force-velocity relationship, summarizing the mechanics of polymerization, can be drawn. Model predictions on the velocity of moving beads driven by actin polymerization are consistent with experiment observations. This model also seems capable of explaining the enhanced actin-based motility of Listeria monocytogenes and beads by the presence of Vasodilator-stimulated phosphoprotein, as observed in recent experiments.

  13. Mechanics model for actin-based motility.

    PubMed

    Lin, Yuan

    2009-02-01

    We present here a mechanics model for the force generation by actin polymerization. The possible adhesions between the actin filaments and the load surface, as well as the nucleation and capping of filament tips, are included in this model on top of the well-known elastic Brownian ratchet formulation. A closed form solution is provided from which the force-velocity relationship, summarizing the mechanics of polymerization, can be drawn. Model predictions on the velocity of moving beads driven by actin polymerization are consistent with experiment observations. This model also seems capable of explaining the enhanced actin-based motility of Listeria monocytogenes and beads by the presence of Vasodilator-stimulated phosphoprotein, as observed in recent experiments.

  14. Promoting Model-based Definition to Establish a Complete Product Definition

    PubMed Central

    Ruemler, Shawn P.; Zimmerman, Kyle E.; Hartman, Nathan W.; Hedberg, Thomas; Feeny, Allison Barnard

    2016-01-01

    The manufacturing industry is evolving and starting to use 3D models as the central knowledge artifact for product data and product definition, or what is known as Model-based Definition (MBD). The Model-based Enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that models represent all the relevant information needed for processes to continue efficiently. Finding this information can help define what data is common amongst different models in different stages of the lifecycle, which could help establish a Common Information Model. The Common Information Model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this Common Information Model, information about how models are used in industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a Common Information Model could not be established. However, the results gave great insight that will help in further investigation of the Common Information Model. PMID:28070155

  15. Cluster-based analysis of multi-model climate ensembles

    NASA Astrophysics Data System (ADS)

    Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

    2018-06-01

    Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and

  16. A model-based approach to estimating forest area

    Treesearch

    Ronald E. McRoberts

    2006-01-01

    A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...

  17. Understanding photoluminescence of metal nanostructures based on an oscillator model.

    PubMed

    Cheng, Yuqing; Zhang, Weidong; Zhao, Jingyi; Wen, Te; Hu, Aiqin; Gong, Qihuang; Lu, Guowei

    2018-08-03

    Scattering and absorption properties of metal nanostructures have been well understood based on the classic oscillator theory. Here, we demonstrate that photoluminescence of metal nanostructures can also be explained based on a classic model. The model shows that inelastic radiation of an oscillator resembles its resonance band after external excitation, and is related to the photoluminescence from metallic nanostructures. The understanding based on the classic oscillator model is in agreement with that predicted by a quantum electromagnetic cavity model. Moreover, by correlating a two-temperature model and the electron distributions, we demonstrate that both one-photon and two-photon luminescence of the metal nanostructures undergo the same mechanism. Furthermore, the model explains most of the emission characteristics of the metallic nanostructures, such as quantum yield, spectral shape, excitation polarization and power dependence. The model based on an oscillator provides an intuitive description of the photoluminescence process and may enable rapid optimization and exploration of the plasmonic properties.

  18. FlyBase portals to human disease research using Drosophila models

    PubMed Central

    Millburn, Gillian H.; Crosby, Madeline A.; Gramates, L. Sian; Tweedie, Susan

    2016-01-01

    ABSTRACT The use of Drosophila melanogaster as a model for studying human disease is well established, reflected by the steady increase in both the number and proportion of fly papers describing human disease models in recent years. In this article, we highlight recent efforts to improve the availability and accessibility of the disease model information in FlyBase (http://flybase.org), the model organism database for Drosophila. FlyBase has recently introduced Human Disease Model Reports, each of which presents background information on a specific disease, a tabulation of related disease subtypes, and summaries of experimental data and results using fruit flies. Integrated presentations of relevant data and reagents described in other sections of FlyBase are incorporated into these reports, which are specifically designed to be accessible to non-fly researchers in order to promote collaboration across model organism communities working in translational science. Another key component of disease model information in FlyBase is that data are collected in a consistent format ­­– using the evolving Disease Ontology (an open-source standardized ontology for human-disease-associated biomedical data) – to allow robust and intuitive searches. To facilitate this, FlyBase has developed a dedicated tool for querying and navigating relevant data, which include mutations that model a disease and any associated interacting modifiers. In this article, we describe how data related to fly models of human disease are presented in individual Gene Reports and in the Human Disease Model Reports. Finally, we discuss search strategies and new query tools that are available to access the disease model data in FlyBase. PMID:26935103

  19. FlyBase portals to human disease research using Drosophila models.

    PubMed

    Millburn, Gillian H; Crosby, Madeline A; Gramates, L Sian; Tweedie, Susan

    2016-03-01

    The use of Drosophila melanogaster as a model for studying human disease is well established, reflected by the steady increase in both the number and proportion of fly papers describing human disease models in recent years. In this article, we highlight recent efforts to improve the availability and accessibility of the disease model information in FlyBase (http://flybase.org), the model organism database for Drosophila. FlyBase has recently introduced Human Disease Model Reports, each of which presents background information on a specific disease, a tabulation of related disease subtypes, and summaries of experimental data and results using fruit flies. Integrated presentations of relevant data and reagents described in other sections of FlyBase are incorporated into these reports, which are specifically designed to be accessible to non-fly researchers in order to promote collaboration across model organism communities working in translational science. Another key component of disease model information in FlyBase is that data are collected in a consistent format --- using the evolving Disease Ontology (an open-source standardized ontology for human-disease-associated biomedical data) - to allow robust and intuitive searches. To facilitate this, FlyBase has developed a dedicated tool for querying and navigating relevant data, which include mutations that model a disease and any associated interacting modifiers. In this article, we describe how data related to fly models of human disease are presented in individual Gene Reports and in the Human Disease Model Reports. Finally, we discuss search strategies and new query tools that are available to access the disease model data in FlyBase. © 2016. Published by The Company of Biologists Ltd.

  20. Qualitative-Modeling-Based Silicon Neurons and Their Networks

    PubMed Central

    Kohno, Takashi; Sekikawa, Munehisa; Li, Jing; Nanami, Takuya; Aihara, Kazuyuki

    2016-01-01

    The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. PMID:27378842

  1. Simulation of large-scale rule-based models

    PubMed Central

    Colvin, Joshua; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.; Von Hoff, Daniel D.; Posner, Richard G.

    2009-01-01

    Motivation: Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. Results: DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein–protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of StochSim. DYNSTOC differs from StochSim by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. Availability: DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at http://public.tgen.org/dynstoc/. Contact: dynstoc@tgen.org Supplementary information

  2. Augment clinical measurement using a constraint-based esophageal model

    NASA Astrophysics Data System (ADS)

    Kou, Wenjun; Acharya, Shashank; Kahrilas, Peter; Patankar, Neelesh; Pandolfino, John

    2017-11-01

    Quantifying the mechanical properties of the esophageal wall is crucial to understanding impairments of trans-esophageal flow characteristic of several esophageal diseases. However, these data are unavailable owing to technological limitations of current clinical diagnostic instruments that instead display esophageal luminal cross sectional area based on intraluminal impedance change. In this work, we developed an esophageal model to predict bolus flow and the wall property based on clinical measurements. The model used the constraint-based immersed-boundary method developed previously by our group. Specifically, we first approximate the time-dependent wall geometry based on impedance planimetry data on luminal cross sectional area. We then fed these along with pressure data into the model and computed wall tension based on simulated pressure and flow fields, and the material property based on the strain-stress relationship. As examples, we applied this model to augment FLIP (Functional Luminal Imaging Probe) measurements in three clinical cases: a normal subject, achalasia, and eosinophilic esophagitis (EoE). Our findings suggest that the wall stiffness was greatest in the EoE case, followed by the achalasia case, and then the normal. This is supported by NIH Grant R01 DK56033 and R01 DK079902.

  3. A future Outlook: Web based Simulation of Hydrodynamic models

    NASA Astrophysics Data System (ADS)

    Islam, A. S.; Piasecki, M.

    2003-12-01

    Despite recent advances to present simulation results as 3D graphs or animation contours, the modeling user community still faces some shortcomings when trying to move around and analyze data. Typical problems include the lack of common platforms with standard vocabulary to exchange simulation results from different numerical models, insufficient descriptions about data (metadata), lack of robust search and retrieval tools for data, and difficulties to reuse simulation domain knowledge. This research demonstrates how to create a shared simulation domain in the WWW and run a number of models through multi-user interfaces. Firstly, meta-datasets have been developed to describe hydrodynamic model data based on geographic metadata standard (ISO 19115) that has been extended to satisfy the need of the hydrodynamic modeling community. The Extended Markup Language (XML) is used to publish this metadata by the Resource Description Framework (RDF). Specific domain ontology for Web Based Simulation (WBS) has been developed to explicitly define vocabulary for the knowledge based simulation system. Subsequently, this knowledge based system is converted into an object model using Meta Object Family (MOF). The knowledge based system acts as a Meta model for the object oriented system, which aids in reusing the domain knowledge. Specific simulation software has been developed based on the object oriented model. Finally, all model data is stored in an object relational database. Database back-ends help store, retrieve and query information efficiently. This research uses open source software and technology such as Java Servlet and JSP, Apache web server, Tomcat Servlet Engine, PostgresSQL databases, Protégé ontology editor, RDQL and RQL for querying RDF in semantic level, Jena Java API for RDF. Also, we use international standards such as the ISO 19115 metadata standard, and specifications such as XML, RDF, OWL, XMI, and UML. The final web based simulation product is deployed as

  4. Model identification methodology for fluid-based inerters

    NASA Astrophysics Data System (ADS)

    Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew

    2018-06-01

    Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.

  5. A model of proto-object based saliency

    PubMed Central

    Russell, Alexander F.; Mihalaş, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

    2013-01-01

    Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, how-ever, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

  6. A 4DCT imaging-based breathing lung model with relative hysteresis

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

    Miyawaki, Shinjiro; Choi, Sanghun; Hoffman, Eric A.

    To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for bothmore » models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.« less

  7. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

    EPA Pesticide Factsheets

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

  8. Online Knowledge-Based Model for Big Data Topic Extraction.

    PubMed

    Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

    2016-01-01

    Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half.

  9. Comparison of Fuzzy-Based Models in Landslide Hazard Mapping

    NASA Astrophysics Data System (ADS)

    Mijani, N.; Neysani Samani, N.

    2017-09-01

    Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR) and Quality Sum (QS). The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P) and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

  10. Examination of Modeling Languages to Allow Quantitative Analysis for Model-Based Systems Engineering

    DTIC Science & Technology

    2014-06-01

    x THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF ACRONYMS AND ABBREVIATIONS BOM Base Object Model BPMN Business Process Model & Notation DOD...SysML. There are many variants such as the Unified Profile for DODAF/MODAF (UPDM) and Business Process Model & Notation ( BPMN ) that have origins in

  11. MRI-based modeling for radiocarpal joint mechanics: validation criteria and results for four specimen-specific models.

    PubMed

    Fischer, Kenneth J; Johnson, Joshua E; Waller, Alexander J; McIff, Terence E; Toby, E Bruce; Bilgen, Mehmet

    2011-10-01

    The objective of this study was to validate the MRI-based joint contact modeling methodology in the radiocarpal joints by comparison of model results with invasive specimen-specific radiocarpal contact measurements from four cadaver experiments. We used a single validation criterion for multiple outcome measures to characterize the utility and overall validity of the modeling approach. For each experiment, a Pressurex film and a Tekscan sensor were sequentially placed into the radiocarpal joints during simulated grasp. Computer models were constructed based on MRI visualization of the cadaver specimens without load. Images were also acquired during the loaded configuration used with the direct experimental measurements. Geometric surface models of the radius, scaphoid and lunate (including cartilage) were constructed from the images acquired without the load. The carpal bone motions from the unloaded state to the loaded state were determined using a series of 3D image registrations. Cartilage thickness was assumed uniform at 1.0 mm with an effective compressive modulus of 4 MPa. Validation was based on experimental versus model contact area, contact force, average contact pressure and peak contact pressure for the radioscaphoid and radiolunate articulations. Contact area was also measured directly from images acquired under load and compared to the experimental and model data. Qualitatively, there was good correspondence between the MRI-based model data and experimental data, with consistent relative size, shape and location of radioscaphoid and radiolunate contact regions. Quantitative data from the model generally compared well with the experimental data for all specimens. Contact area from the MRI-based model was very similar to the contact area measured directly from the images. For all outcome measures except average and peak pressures, at least two specimen models met the validation criteria with respect to experimental measurements for both articulations

  12. A unified classification model for modeling of seismic liquefaction potential of soil based on CPT

    PubMed Central

    Samui, Pijush; Hariharan, R.

    2014-01-01

    The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi–Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (qc) and Cyclic Stress Ratio (CSR) as input variables. qc and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on qc and PGA. PMID:26199749

  13. A unified classification model for modeling of seismic liquefaction potential of soil based on CPT.

    PubMed

    Samui, Pijush; Hariharan, R

    2015-07-01

    The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi-Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (q c) and Cyclic Stress Ratio (CSR) as input variables. q c and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on q c and PGA.

  14. Development of Ensemble Model Based Water Demand Forecasting Model

    NASA Astrophysics Data System (ADS)

    Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

    2014-05-01

    In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

  15. Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

    NASA Astrophysics Data System (ADS)

    Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

    2014-09-01

    Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

  16. Adaptive MPC based on MIMO ARX-Laguerre model.

    PubMed

    Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

    2017-03-01

    This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Individual-based modelling and control of bovine brucellosis

    NASA Astrophysics Data System (ADS)

    Nepomuceno, Erivelton G.; Barbosa, Alípio M.; Silva, Marcos X.; Perc, Matjaž

    2018-05-01

    We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory.

  18. Nanoscale deformation mechanism of TiC/a-C nanocomposite thin films

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

    Chen, C. Q.; Pei, Y. T.; Shaha, K. P.

    2009-06-01

    This paper concentrates on the deformation behavior of amorphous diamondlike carbon composite materials. Combined nanoindentation and ex situ cross-sectional transmission electron microscopy investigations are carried out on TiC/a-C nanocomposite films, with and without multilayered structures deposited by pulse dc magnetron sputtering. It is shown that by controlling the distribution of nanocrystallites forming nanoscale multilayers, the system can be used as a 'microstructural ruler' that is able to distinguish various deformation patterns, which can be hardly detected otherwise in a homogeneous structure. It is shown that rearrangement of nanocrystallites and displacement of a-C matrix occur at length scales from tens ofmore » nanometer down to 1 nm. At submicrometer scale homogeneous nucleation of multiple shear bands has been observed within the nanocomposites. The multilayered structure in the TiC/a-C nanocomposite film contributes to an enhanced toughness.« less

  19. RuleMonkey: software for stochastic simulation of rule-based models

    PubMed Central

    2010-01-01

    Background The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems. Results Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods. Conclusions RuleMonkey enables the simulation of

  20. High-level PC-based laser system modeling

    NASA Astrophysics Data System (ADS)

    Taylor, Michael S.

    1991-05-01

    Since the inception of the Strategic Defense Initiative (SDI) there have been a multitude of comparison studies done in an attempt to evaluate the effectiveness and relative sizes of complementary, and sometimes competitive, laser weapon systems. It became more and more apparent that what the systems analyst needed was not only a fast, but a cost effective way to perform high-level trade studies. In the present investigation, a general procedure is presented for the development of PC-based algorithmic systems models for laser systems. This procedure points out all of the major issues that should be addressed in the design and development of such a model. Issues addressed include defining the problem to be modeled, defining a strategy for development, and finally, effective use of the model once developed. Being a general procedure, it will allow a systems analyst to develop a model to meet specific needs. To illustrate this method of model development, a description of the Strategic Defense Simulation - Design To (SDS-DT) model developed and used by Science Applications International Corporation (SAIC) is presented. SDS-DT is a menu-driven, fast executing, PC-based program that can be used to either calculate performance, weight, volume, and cost values for a particular design or, alternatively, to run parametrics on particular system parameters to perhaps optimize a design.

  1. Models of filter-based particle light absorption measurements

    NASA Astrophysics Data System (ADS)

    Hamasha, Khadeejeh M.

    Light absorption by aerosol is very important in the visible, near UN, and near I.R region of the electromagnetic spectrum. Aerosol particles in the atmosphere have a great influence on the flux of solar energy, and also impact health in a negative sense when they are breathed into lungs. Aerosol absorption measurements are usually performed by filter-based methods that are derived from the change in light transmission through a filter where particles have been deposited. These methods suffer from interference between light-absorbing and light-scattering aerosol components. The Aethalometer is the most commonly used filter-based instrument for aerosol light absorption measurement. This dissertation describes new understanding of aerosol light absorption obtained by the filter method. The theory uses a multiple scattering model for the combination of filter and particle optics. The theory is evaluated using Aethalometer data from laboratory and ambient measurements in comparison with photoacoustic measurements of aerosol light absorption. Two models were developed to calculate aerosol light absorption coefficients from the Aethalometer data, and were compared to the in-situ aerosol light absorption coefficients. The first is an approximate model and the second is a "full" model. In the approximate model two extreme cases of aerosol optics were used to develop a model-based calibration scheme for the 7-wavelength Aethalometer. These cases include those of very strong scattering aerosols (Ammonium sulfate sample) and very absorbing aerosols (kerosene soot sample). The exponential behavior of light absorption in the strong multiple scattering limit is shown to be the square root of the total absorption optical depth rather than linear with optical depth as is commonly assumed with Beer's law. 2-stream radiative transfer theory was used to develop the full model to calculate the aerosol light absorption coefficients from the Aethalometer data. This comprehensive model

  2. Stochastic Watershed Models for Risk Based Decision Making

    NASA Astrophysics Data System (ADS)

    Vogel, R. M.

    2017-12-01

    Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

  3. A sediment graph model based on SCS-CN method

    NASA Astrophysics Data System (ADS)

    Singh, P. K.; Bhunya, P. K.; Mishra, S. K.; Chaube, U. C.

    2008-01-01

    SummaryThis paper proposes new conceptual sediment graph models based on coupling of popular and extensively used methods, viz., Nash model based instantaneous unit sediment graph (IUSG), soil conservation service curve number (SCS-CN) method, and Power law. These models vary in their complexity and this paper tests their performance using data of the Nagwan watershed (area = 92.46 km 2) (India). The sensitivity of total sediment yield and peak sediment flow rate computations to model parameterisation is analysed. The exponent of the Power law, β, is more sensitive than other model parameters. The models are found to have substantial potential for computing sediment graphs (temporal sediment flow rate distribution) as well as total sediment yield.

  4. Agent-Based Models in Empirical Social Research

    ERIC Educational Resources Information Center

    Bruch, Elizabeth; Atwell, Jon

    2015-01-01

    Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…

  5. A Memory-Based Model of Hick's Law

    ERIC Educational Resources Information Center

    Schneider, Darryl W.; Anderson, John R.

    2011-01-01

    We propose and evaluate a memory-based model of Hick's law, the approximately linear increase in choice reaction time with the logarithm of set size (the number of stimulus-response alternatives). According to the model, Hick's law reflects a combination of associative interference during retrieval from declarative memory and occasional savings…

  6. SLS Model Based Design: A Navigation Perspective

    NASA Technical Reports Server (NTRS)

    Oliver, T. Emerson; Anzalone, Evan; Park, Thomas; Geohagan, Kevin

    2018-01-01

    The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

  7. A continuum mechanics-based musculo-mechanical model for esophageal transport

    NASA Astrophysics Data System (ADS)

    Kou, Wenjun; Griffith, Boyce E.; Pandolfino, John E.; Kahrilas, Peter J.; Patankar, Neelesh A.

    2017-11-01

    In this work, we extend our previous esophageal transport model using an immersed boundary (IB) method with discrete fiber-based structural model, to one using a continuum mechanics-based model that is approximated based on finite elements (IB-FE). To deal with the leakage of flow when the Lagrangian mesh becomes coarser than the fluid mesh, we employ adaptive interaction quadrature points to deal with Lagrangian-Eulerian interaction equations based on a previous work (Griffith and Luo [1]). In particular, we introduce a new anisotropic adaptive interaction quadrature rule. The new rule permits us to vary the interaction quadrature points not only at each time-step and element but also at different orientations per element. This helps to avoid the leakage issue without sacrificing the computational efficiency and accuracy in dealing with the interaction equations. For the material model, we extend our previous fiber-based model to a continuum-based model. We present formulations for general fiber-reinforced material models in the IB-FE framework. The new material model can handle non-linear elasticity and fiber-matrix interactions, and thus permits us to consider more realistic material behavior of biological tissues. To validate our method, we first study a case in which a three-dimensional short tube is dilated. Results on the pressure-displacement relationship and the stress distribution matches very well with those obtained from the implicit FE method. We remark that in our IB-FE case, the three-dimensional tube undergoes a very large deformation and the Lagrangian mesh-size becomes about 6 times of Eulerian mesh-size in the circumferential orientation. To validate the performance of the method in handling fiber-matrix material models, we perform a second study on dilating a long fiber-reinforced tube. Errors are small when we compare numerical solutions with analytical solutions. The technique is then applied to the problem of esophageal transport. We use two

  8. Online Knowledge-Based Model for Big Data Topic Extraction

    PubMed Central

    Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

    2016-01-01

    Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half. PMID:27195004

  9. Neuman systems model-based research: an integrative review project.

    PubMed

    Fawcett, J; Giangrande, S K

    2001-07-01

    The project integrated Neuman systems model-based research literature. Two hundred published studies were located. This article is limited to the 59 full journal articles and 3 book chapters identified. A total of 37% focused on prevention interventions; 21% on perception of stressors; and 10% on stressor reactions. Only 50% of the reports explicitly linked the model with the study variables, and 61% did not include conclusions regarding model utility or credibility. No programs of research were identified. Academic courses and continuing education workshops are needed to help researchers design programs of Neuman systems model-based research and better explicate linkages between the model and the research.

  10. Wildlife tradeoffs based on landscape models of habitat preference

    USGS Publications Warehouse

    Loehle, C.; Mitchell, M.S.; White, M.

    2000-01-01

    Wildlife tradeoffs based on landscape models of habitat preference were presented. Multiscale logistic regression models were used and based on these models a spatial optimization technique was utilized to generate optimal maps. The tradeoffs were analyzed by gradually increasing the weighting on a single species in the objective function over a series of simulations. Results indicated that efficiency of habitat management for species diversity could be maximized for small landscapes by incorporating spatial context.

  11. Model-based Bayesian inference for ROC data analysis

    NASA Astrophysics Data System (ADS)

    Lei, Tianhu; Bae, K. Ty

    2013-03-01

    This paper presents a study of model-based Bayesian inference to Receiver Operating Characteristics (ROC) data. The model is a simple version of general non-linear regression model. Different from Dorfman model, it uses a probit link function with a covariate variable having zero-one two values to express binormal distributions in a single formula. Model also includes a scale parameter. Bayesian inference is implemented by Markov Chain Monte Carlo (MCMC) method carried out by Bayesian analysis Using Gibbs Sampling (BUGS). Contrast to the classical statistical theory, Bayesian approach considers model parameters as random variables characterized by prior distributions. With substantial amount of simulated samples generated by sampling algorithm, posterior distributions of parameters as well as parameters themselves can be accurately estimated. MCMC-based BUGS adopts Adaptive Rejection Sampling (ARS) protocol which requires the probability density function (pdf) which samples are drawing from be log concave with respect to the targeted parameters. Our study corrects a common misconception and proves that pdf of this regression model is log concave with respect to its scale parameter. Therefore, ARS's requirement is satisfied and a Gaussian prior which is conjugate and possesses many analytic and computational advantages is assigned to the scale parameter. A cohort of 20 simulated data sets and 20 simulations from each data set are used in our study. Output analysis and convergence diagnostics for MCMC method are assessed by CODA package. Models and methods by using continuous Gaussian prior and discrete categorical prior are compared. Intensive simulations and performance measures are given to illustrate our practice in the framework of model-based Bayesian inference using MCMC method.

  12. Fuzzy model-based servo and model following control for nonlinear systems.

    PubMed

    Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

    2009-12-01

    This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

  13. A bottom-up building process of nanostructured La0.75Sr0.25Cr0.5Mn0.5O3-δ electrodes for symmetrical-solid oxide fuel cell: Synthesis, characterization and electrocatalytic testing

    NASA Astrophysics Data System (ADS)

    Chanquía, Corina M.; Montenegro-Hernández, Alejandra; Troiani, Horacio E.; Caneiro, Alberto

    2014-01-01

    Pure-phase La0.75Sr0.25Cr0.5Mn0.5O3-δ (LSCM) nanocrystallites have been successfully synthesized by the combustion method, employing glycine as fuel and complexing agent, and ammonium nitrate as combustion trigger. A detailed morphological and structural characterization is performed, by using of X-ray diffraction, N2 physisorption and electron microscopy. The LSCM material consists in interconnected nanocrystallites (∼30 nm) forming a sponge-like structure with meso and macropores, being its specific surface area around 10 m2 g-1. Crystalline structural analyses show that the LSCM nanopowder has trigonal/rhombohedral symmetry in the R-3c space group. By employing the spin coating technique and quick-stuck thermal treatments of the ink-electrolyte, electrodes with different crystallite size (95, 160 and 325 nm) are built onto both sides of the La0.8Sr0.2Ga0.8Mg0.2O3-δ-disk electrolyte. To test the influence of the electrode crystallite size on the electrocatalytic behavior of the symmetrical cells, electrochemical impedance spectroscopy measurements at 800 °C were performed. When the electrode crystallite size becomes smaller, the area specific resistance decreases from 3.6 to 1.31 Ω cm2 under 0.2O2-0.8Ar atmosphere, possibly due to the enlarging of the triple-phase boundary, while this value increases from 7.04 to 13.78 Ω cm2 under 0.17H2-0.03H2O-0.8Ar atmosphere, probably due to thermodynamic instability of the LSCM nanocrystallites.

  14. A burnout prediction model based around char morphology

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

    Tao Wu; Edward Lester; Michael Cloke

    Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coalmore » particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.« less

  15. Life prediction modeling based on cyclic damage accumulation

    NASA Technical Reports Server (NTRS)

    Nelson, Richard S.

    1988-01-01

    A high temperature, low cycle fatigue life prediction method was developed. This method, Cyclic Damage Accumulation (CDA), was developed for use in predicting the crack initiation lifetime of gas turbine engine materials, where initiation was defined as a 0.030 inch surface length crack. A principal engineering feature of the CDA method is the minimum data base required for implementation. Model constants can be evaluated through a few simple specimen tests such as monotonic loading and rapic cycle fatigue. The method was expanded to account for the effects on creep-fatigue life of complex loadings such as thermomechanical fatigue, hold periods, waveshapes, mean stresses, multiaxiality, cumulative damage, coatings, and environmental attack. A significant data base was generated on the behavior of the cast nickel-base superalloy B1900+Hf, including hundreds of specimen tests under such loading conditions. This information is being used to refine and extend the CDA life prediction model, which is now nearing completion. The model is also being verified using additional specimen tests on wrought INCO 718, and the final version of the model is expected to be adaptable to most any high-temperature alloy. The model is currently available in the form of equations and related constants. A proposed contract addition will make the model available in the near future in the form of a computer code to potential users.

  16. Model based defect characterization in composites

    NASA Astrophysics Data System (ADS)

    Roberts, R.; Holland, S.

    2017-02-01

    Work is reported on model-based defect characterization in CFRP composites. The work utilizes computational models of the interaction of NDE probing energy fields (ultrasound and thermography), to determine 1) the measured signal dependence on material and defect properties (forward problem), and 2) an assessment of performance-critical defect properties from analysis of measured NDE signals (inverse problem). Work is reported on model implementation for inspection of CFRP laminates containing multi-ply impact-induced delamination, with application in this paper focusing on ultrasound. A companion paper in these proceedings summarizes corresponding activity in thermography. Inversion of ultrasound data is demonstrated showing the quantitative extraction of damage properties.

  17. Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model.

    PubMed

    Chakraborty, Arindom

    2016-12-01

    A common objective in longitudinal studies is to characterize the relationship between a longitudinal response process and a time-to-event data. Ordinal nature of the response and possible missing information on covariates add complications to the joint model. In such circumstances, some influential observations often present in the data may upset the analysis. In this paper, a joint model based on ordinal partial mixed model and an accelerated failure time model is used, to account for the repeated ordered response and time-to-event data, respectively. Here, we propose an influence function-based robust estimation method. Monte Carlo expectation maximization method-based algorithm is used for parameter estimation. A detailed simulation study has been done to evaluate the performance of the proposed method. As an application, a data on muscular dystrophy among children is used. Robust estimates are then compared with classical maximum likelihood estimates. © The Author(s) 2014.

  18. A measurement-based performability model for a multiprocessor system

    NASA Technical Reports Server (NTRS)

    Ilsueh, M. C.; Iyer, Ravi K.; Trivedi, K. S.

    1987-01-01

    A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

  19. Stochastic simulation by image quilting of process-based geological models

    NASA Astrophysics Data System (ADS)

    Hoffimann, Júlio; Scheidt, Céline; Barfod, Adrian; Caers, Jef

    2017-09-01

    Process-based modeling offers a way to represent realistic geological heterogeneity in subsurface models. The main limitation lies in conditioning such models to data. Multiple-point geostatistics can use these process-based models as training images and address the data conditioning problem. In this work, we further develop image quilting as a method for 3D stochastic simulation capable of mimicking the realism of process-based geological models with minimal modeling effort (i.e. parameter tuning) and at the same time condition them to a variety of data. In particular, we develop a new probabilistic data aggregation method for image quilting that bypasses traditional ad-hoc weighting of auxiliary variables. In addition, we propose a novel criterion for template design in image quilting that generalizes the entropy plot for continuous training images. The criterion is based on the new concept of voxel reuse-a stochastic and quilting-aware function of the training image. We compare our proposed method with other established simulation methods on a set of process-based training images of varying complexity, including a real-case example of stochastic simulation of the buried-valley groundwater system in Denmark.

  20. Word-level language modeling for P300 spellers based on discriminative graphical models

    NASA Astrophysics Data System (ADS)

    Delgado Saa, Jaime F.; de Pesters, Adriana; McFarland, Dennis; Çetin, Müjdat

    2015-04-01

    Objective. In this work we propose a probabilistic graphical model framework that uses language priors at the level of words as a mechanism to increase the performance of P300-based spellers. Approach. This paper is concerned with brain-computer interfaces based on P300 spellers. Motivated by P300 spelling scenarios involving communication based on a limited vocabulary, we propose a probabilistic graphical model framework and an associated classification algorithm that uses learned statistical models of language at the level of words. Exploiting such high-level contextual information helps reduce the error rate of the speller. Main results. Our experimental results demonstrate that the proposed approach offers several advantages over existing methods. Most importantly, it increases the classification accuracy while reducing the number of times the letters need to be flashed, increasing the communication rate of the system. Significance. The proposed approach models all the variables in the P300 speller in a unified framework and has the capability to correct errors in previous letters in a word, given the data for the current one. The structure of the model we propose allows the use of efficient inference algorithms, which in turn makes it possible to use this approach in real-time applications.

  1. MAC/FAC: A Model of Similarity-Based Retrieval.

    ERIC Educational Resources Information Center

    Forbus, Kenneth D.; And Others

    1995-01-01

    Presents MAC/FAC, a model of similarity-based retrieval that attempts to capture psychological phenomena; discusses its limitations and extensions, its relationship with other retrieval models, and its placement in the context of other work on the nature of similarity. Examines the utility of the model through psychological experiments and…

  2. Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model

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

    Goumiri, I. R.; Rowley, C. W.; Ma, Z.

    2013-01-28

    In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modi ed Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in ow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using linear quadratic regulators (LQR). Finally, a linear quadratic gaussian (LQG) controller, which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHWmore » equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.« less

  3. Development of a recursion RNG-based turbulence model

    NASA Technical Reports Server (NTRS)

    Zhou, YE; Vahala, George; Thangam, S.

    1993-01-01

    Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.

  4. Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage

    NASA Astrophysics Data System (ADS)

    Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

    2018-03-01

    This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.

  5. Field Evaluation of the Pedostructure-Based Model (Kamel®)

    USDA-ARS?s Scientific Manuscript database

    This study involves a field evaluation of the pedostructure-based model Kamel and comparisons between Kamel and the Hydrus-1D model for predicting profile soil moisture. This paper also presents a sensitivity analysis of Kamel with an evaluation field site used as the base scenario. The field site u...

  6. An Active Learning Exercise for Introducing Agent-Based Modeling

    ERIC Educational Resources Information Center

    Pinder, Jonathan P.

    2013-01-01

    Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

  7. Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

    PubMed Central

    Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

    2015-01-01

    6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448

  8. Combining Model-driven and Schema-based Program Synthesis

    NASA Technical Reports Server (NTRS)

    Denney, Ewen; Whittle, John

    2004-01-01

    We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

  9. Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

    EPA Science Inventory

    Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-v...

  10. Integration of a three-dimensional process-based hydrological model into the Object Modeling System

    USDA-ARS?s Scientific Manuscript database

    The integration of a spatial process model into an environmental modelling framework can enhance the model’s capabilities. We present the integration of the GEOtop model into the Object Modeling System (OMS) version 3.0 and illustrate its application in a small watershed. GEOtop is a physically base...

  11. A family systems-based model of organizational intervention.

    PubMed

    Shumway, Sterling T; Kimball, Thomas G; Korinek, Alan W; Arredondo, Rudy

    2007-04-01

    Employee assistance professionals are expected to be proficient at intervening in organizations and creating meaningful behavioral change in interpersonal functioning. Because of their training in family systems theories and concepts, marriage and family therapists (MFTs) are well suited to serve organizations as "systems consultants." Unfortunately, the authors were unable to identify any family systems-based models for organizational intervention that have been empirically tested and supported. In this article, the authors present a family systems-based model of intervention that they developed while working in an employee assistance program (EAP). They also present research that was used to refine the model and to provide initial support for its effectiveness.

  12. A modeling approach to describe ZVI-based anaerobic system.

    PubMed

    Xiao, Xiao; Sheng, Guo-Ping; Mu, Yang; Yu, Han-Qing

    2013-10-15

    Zero-valent iron (ZVI) is increasingly being added into anaerobic reactors to enhance the biological conversion of various less biodegradable pollutants (LBPs). Our study aimed to establish a new structure model based on the Anaerobic Digestion Model No. 1 (ADM1) to simulate such a ZVI-based anaerobic reactor. Three new processes, i.e., electron release from ZVI corrosion, H2 formation from ZVI corrosion, and transformation of LBPs, were integrated into ADM1. The established model was calibrated and tested using the experimental data from one published study, and validated using the data from another work. A good relationship between the predicted and measured results indicates that the proposed model was appropriate to describe the performance of the ZVI-based anaerobic system. Our model could provide more precise strategies for the design, development, and application of anaerobic systems especially for treating various LBPs-containing wastewaters. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Mathematical modeling of acid-base physiology

    PubMed Central

    Occhipinti, Rossana; Boron, Walter F.

    2015-01-01

    pH is one of the most important parameters in life, influencing virtually every biological process at the cellular, tissue, and whole-body level. Thus, for cells, it is critical to regulate intracellular pH (pHi) and, for multicellular organisms, to regulate extracellular pH (pHo). pHi regulation depends on the opposing actions of plasma-membrane transporters that tend to increase pHi, and others that tend to decrease pHi. In addition, passive fluxes of uncharged species (e.g., CO2, NH3) and charged species (e.g., HCO3− , NH4+) perturb pHi. These movements not only influence one another, but also perturb the equilibria of a multitude of intracellular and extracellular buffers. Thus, even at the level of a single cell, perturbations in acid-base reactions, diffusion, and transport are so complex that it is impossible to understand them without a quantitative model. Here we summarize some mathematical models developed to shed light onto the complex interconnected events triggered by acids-base movements. We then describe a mathematical model of a spherical cell–which to our knowledge is the first one capable of handling a multitude of buffer reaction–that our team has recently developed to simulate changes in pHi and pHo caused by movements of acid-base equivalents across the plasma membrane of a Xenopus oocyte. Finally, we extend our work to a consideration of the effects of simultaneous CO2 and HCO3− influx into a cell, and envision how future models might extend to other cell types (e.g., erythrocytes) or tissues (e.g., renal proximal-tubule epithelium) important for whole-body pH homeostasis. PMID:25617697

  14. Constraints based analysis of extended cybernetic models.

    PubMed

    Mandli, Aravinda R; Venkatesh, Kareenhalli V; Modak, Jayant M

    2015-11-01

    The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

    NASA Technical Reports Server (NTRS)

    Tang, Wei; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

    2013-01-01

    Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

  16. Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

    PubMed

    Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

    2016-01-01

    A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

  17. A Nonlinear Model for Gene-Based Gene-Environment Interaction.

    PubMed

    Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

    2016-06-04

    A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

  18. Toward a Transdisciplinary Model of Evidence-Based Practice

    PubMed Central

    Satterfield, Jason M; Spring, Bonnie; Brownson, Ross C; Mullen, Edward J; Newhouse, Robin P; Walker, Barbara B; Whitlock, Evelyn P

    2009-01-01

    Context This article describes the historical context and current developments in evidence-based practice (EBP) for medicine, nursing, psychology, social work, and public health, as well as the evolution of the seminal “three circles” model of evidence-based medicine, highlighting changes in EBP content, processes, and philosophies across disciplines. Methods The core issues and challenges in EBP are identified by comparing and contrasting EBP models across various health disciplines. Then a unified, transdisciplinary EBP model is presented, drawing on the strengths and compensating for the weaknesses of each discipline. Findings Common challenges across disciplines include (1) how “evidence” should be defined and comparatively weighted; (2) how and when the patient's and/or other contextual factors should enter the clinical decision-making process; (3) the definition and role of the “expert”; and (4) what other variables should be considered when selecting an evidence-based practice, such as age, social class, community resources, and local expertise. Conclusions A unified, transdisciplinary EBP model would address historical shortcomings by redefining the contents of each model circle, clarifying the practitioner's expertise and competencies, emphasizing shared decision making, and adding both environmental and organizational contexts. Implications for academia, practice, and policy also are discussed. PMID:19523122

  19. Working-memory capacity protects model-based learning from stress.

    PubMed

    Otto, A Ross; Raio, Candace M; Chiang, Alice; Phelps, Elizabeth A; Daw, Nathaniel D

    2013-12-24

    Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive-dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response--believed to have detrimental effects on prefrontal cortex function--should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress.

  20. Working-memory capacity protects model-based learning from stress

    PubMed Central

    Otto, A. Ross; Raio, Candace M.; Chiang, Alice; Phelps, Elizabeth A.; Daw, Nathaniel D.

    2013-01-01

    Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive–dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response—believed to have detrimental effects on prefrontal cortex function—should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress. PMID:24324166

  1. Model-based verification and validation of the SMAP uplink processes

    NASA Astrophysics Data System (ADS)

    Khan, M. O.; Dubos, G. F.; Tirona, J.; Standley, S.

    Model-Based Systems Engineering (MBSE) is being used increasingly within the spacecraft design community because of its benefits when compared to document-based approaches. As the complexity of projects expands dramatically with continually increasing computational power and technology infusion, the time and effort needed for verification and validation (V& V) increases geometrically. Using simulation to perform design validation with system-level models earlier in the life cycle stands to bridge the gap between design of the system (based on system-level requirements) and verifying those requirements/validating the system as a whole. This case study stands as an example of how a project can validate a system-level design earlier in the project life cycle than traditional V& V processes by using simulation on a system model. Specifically, this paper describes how simulation was added to a system model of the Soil Moisture Active-Passive (SMAP) mission's uplink process. Also discussed are the advantages and disadvantages of the methods employed and the lessons learned; which are intended to benefit future model-based and simulation-based development efforts.

  2. Intelligent-based Structural Damage Detection Model

    NASA Astrophysics Data System (ADS)

    Lee, Eric Wai Ming; Yu, Kin Fung

    2010-05-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  3. Mesoscale Particle-Based Model of Electrophoresis

    DOE PAGES

    Giera, Brian; Zepeda-Ruiz, Luis A.; Pascall, Andrew J.; ...

    2015-07-31

    Here, we develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using only measurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.

  4. Mesoscale Particle-Based Model of Electrophoresis

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

    Giera, Brian; Zepeda-Ruiz, Luis A.; Pascall, Andrew J.

    Here, we develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using only measurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.

  5. Research on light rail electric load forecasting based on ARMA model

    NASA Astrophysics Data System (ADS)

    Huang, Yifan

    2018-04-01

    The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

  6. Solution algorithm of dwell time in slope-based figuring model

    NASA Astrophysics Data System (ADS)

    Li, Yong; Zhou, Lin

    2017-10-01

    Surface slope profile is commonly used to evaluate X-ray reflective optics, which is used in synchrotron radiation beam. Moreover, the measurement result of measuring instrument for X-ray reflective optics is usually the surface slope profile rather than the surface height profile. To avoid the conversion error, the slope-based figuring model is introduced introduced by processing the X-ray reflective optics based on surface height-based model. However, the pulse iteration method, which can quickly obtain the dell time solution of the traditional height-based figuring model, is not applied to the slope-based figuring model because property of the slope removal function have both positive and negative values and complex asymmetric structure. To overcome this problem, we established the optimal mathematical model for the dwell time solution, By introducing the upper and lower limits of the dwell time and the time gradient constraint. Then we used the constrained least squares algorithm to solve the dwell time in slope-based figuring model. To validate the proposed algorithm, simulations and experiments are conducted. A flat mirror with effective aperture of 80 mm is polished on the ion beam machine. After iterative polishing three times, the surface slope profile error of the workpiece is converged from RMS 5.65 μrad to RMS 1.12 μrad.

  7. An Inter-Personal Information Sharing Model Based on Personalized Recommendations

    NASA Astrophysics Data System (ADS)

    Kamei, Koji; Funakoshi, Kaname; Akahani, Jun-Ichi; Satoh, Tetsuji

    In this paper, we propose an inter-personal information sharing model among individuals based on personalized recommendations. In the proposed model, we define an information resource as shared between people when both of them consider it important --- not merely when they both possess it. In other words, the model defines the importance of information resources based on personalized recommendations from identifiable acquaintances. The proposed method is based on a collaborative filtering system that focuses on evaluations from identifiable acquaintances. It utilizes both user evaluations for documents and their contents. In other words, each user profile is represented as a matrix of credibility to the other users' evaluations on each domain of interests. We extended the content-based collaborative filtering method to distinguish other users to whom the documents should be recommended. We also applied a concept-based vector space model to represent the domain of interests instead of the previous method which represented them by a term-based vector space model. We introduce a personalized concept-base compiled from each user's information repository to improve the information retrieval in the user's environment. Furthermore, the concept-spaces change from user to user since they reflect the personalities of the users. Because of different concept-spaces, the similarity between a document and a user's interest varies for each user. As a result, a user receives recommendations from other users who have different view points, achieving inter-personal information sharing based on personalized recommendations. This paper also describes an experimental simulation of our information sharing model. In our laboratory, five participants accumulated a personal repository of e-mails and web pages from which they built their own concept-base. Then we estimated the user profiles according to personalized concept-bases and sets of documents which others evaluated. We simulated

  8. Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

    PubMed Central

    Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

    2018-01-01

    Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

  9. Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

    PubMed

    Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

    2018-05-04

    Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

  10. Revisiting node-based SIR models in complex networks with degree correlations

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

    2015-11-01

    In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.

  11. The Geolocation model for lunar-based Earth observation

    NASA Astrophysics Data System (ADS)

    Ding, Yixing; Liu, Guang; Ren, Yuanzhen; Ye, Hanlin; Guo, Huadong; Lv, Mingyang

    2016-07-01

    In recent years, people are more and more aware of that the earth need to treated as an entirety, and consequently to be observed in a holistic, systematic and multi-scale view. However, the interaction mechanism between the Earth's inner layers and outer layers is still unclear. Therefore, we propose to observe the Earth's inner layers and outer layers instantaneously on the Moon which may be helpful to the studies in climatology, meteorology, seismology, etc. At present, the Moon has been proved to be an irreplaceable platform for Earth's outer layers observation. Meanwhile, some discussions have been made in lunar-based observation of the Earth's inner layers, but the geolocation model of lunar-based observation has not been specified yet. In this paper, we present a geolocation model based on transformation matrix. The model includes six coordinate systems: The telescope coordinate system, the lunar local coordinate system, the lunar-reference coordinate system, the selenocentric inertial coordinate system, the geocentric inertial coordinate system and the geo-reference coordinate system. The parameters, lncluding the position of the Sun, the Earth, the Moon, the libration and the attitude of the Earth, can be acquired from the Ephemeris. By giving an elevation angle and an azimuth angle of the lunar-based telescope, this model links the image pixel to the ground point uniquely.

  12. A fugacity-based indoor residential pesticide fate model

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

    Bennett, Deborah H.; Furtaw, Edward J.; McKone, Thomas E.

    Dermal and non-dietary pathways are potentially significant exposure pathways to pesticides used in residences. Exposure pathways include dermal contact with residues on surfaces, ingestion from hand- and object-to-mouth activities, and absorption of pesticides into food. A limited amount of data has been collected on pesticide concentrations in various residential compartments following an application. But models are needed to interpret this data and make predictions about other pesticides based on chemical properties. In this paper, we propose a mass-balance compartment model based on fugacity principles. We include air (both gas phase and aerosols), carpet, smooth flooring, and walls as model compartments.more » Pesticide concentrations on furniture and toys, and in food, are being added to the model as data becomes available. We determine the compartmental fugacity capacity and mass transfer-rate coefficient for wallboard as an example. We also present the framework and equations needed for a dynamic mass-balance model.« less

  13. Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

    NASA Astrophysics Data System (ADS)

    Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

    2014-02-01

    Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation

  14. Dynamic, physical-based landslide susceptibility modelling based on real-time weather data

    NASA Astrophysics Data System (ADS)

    Canli, Ekrem; Glade, Thomas

    2016-04-01

    By now there seem to be a broad consensus that due to human-induced global change the frequency and magnitude of precipitation intensities within extensive rainstorm events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as one of the most common triggers for landslide initiation, also an increased landside activity might be expected. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled by a variety of concepts, methods, and models. However, most of the research done with respect to landslides deals with retrospect cases, thus classical back-analysis approaches do not incorporate real-time data. This is remarkable, as most destructive landslides are related to immediate events due to external triggering factors. Only few works so far addressed real-time dynamic components for spatial landslide susceptibility and hazard assessment. Here we present an approach for integrating real-time web-based rainfall data from different sources into an automated workflow. Rain gauge measurements are interpolated into a continuous raster which in return is directly utilized in a dynamic, physical-based model. We use the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) model that was modified in a way that it is automatically updated with the most recent rainfall raster for producing hourly landslide susceptibility maps on a regional scale. To account for the uncertainties involved in spatial modelling, the model was further adjusted by not only applying single values for given geotechnical parameters, but ranges instead. The values are determined randomly between user-defined thresholds defining the parameter ranges. Consequently, a slope failure probability from a larger number of model runs is computed rather than just the distributed factor of safety. This will ultimately allow a near-real time spatial landslide alert for a given region.

  15. Copula based prediction models: an application to an aortic regurgitation study

    PubMed Central

    Kumar, Pranesh; Shoukri, Mohamed M

    2007-01-01

    Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre

  16. Model-based hierarchical reinforcement learning and human action control

    PubMed Central

    Botvinick, Matthew; Weinstein, Ari

    2014-01-01

    Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822

  17. Stability of subsystem solutions in agent-based models

    NASA Astrophysics Data System (ADS)

    Perc, Matjaž

    2018-01-01

    The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

  18. Practical Application of Model-based Programming and State-based Architecture to Space Missions

    NASA Technical Reports Server (NTRS)

    Horvath, Gregory A.; Ingham, Michel D.; Chung, Seung; Martin, Oliver; Williams, Brian

    2006-01-01

    Innovative systems and software engineering solutions are required to meet the increasingly challenging demands of deep-space robotic missions. While recent advances in the development of an integrated systems and software engineering approach have begun to address some of these issues, they are still at the core highly manual and, therefore, error-prone. This paper describes a task aimed at infusing MIT's model-based executive, Titan, into JPL's Mission Data System (MDS), a unified state-based architecture, systems engineering process, and supporting software framework. Results of the task are presented, including a discussion of the benefits and challenges associated with integrating mature model-based programming techniques and technologies into a rigorously-defined domain specific architecture.

  19. Rank-based methods for modeling dependence between loss triangles.

    PubMed

    Côté, Marie-Pier; Genest, Christian; Abdallah, Anas

    2016-01-01

    In order to determine the risk capital for their aggregate portfolio, property and casualty insurance companies must fit a multivariate model to the loss triangle data relating to each of their lines of business. As an inadequate choice of dependence structure may have an undesirable effect on reserve estimation, a two-stage inference strategy is proposed in this paper to assist with model selection and validation. Generalized linear models are first fitted to the margins. Standardized residuals from these models are then linked through a copula selected and validated using rank-based methods. The approach is illustrated with data from six lines of business of a large Canadian insurance company for which two hierarchical dependence models are considered, i.e., a fully nested Archimedean copula structure and a copula-based risk aggregation model.

  20. Model-Based Method for Sensor Validation

    NASA Technical Reports Server (NTRS)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  1. Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

    PubMed

    Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

    2018-07-01

    Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

  2. Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

    PubMed Central

    Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

    2016-01-01

    A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

  3. Investigation of model-based physical design restrictions (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Lucas, Kevin; Baron, Stanislas; Belledent, Jerome; Boone, Robert; Borjon, Amandine; Couderc, Christophe; Patterson, Kyle; Riviere-Cazaux, Lionel; Rody, Yves; Sundermann, Frank; Toublan, Olivier; Trouiller, Yorick; Urbani, Jean-Christophe; Wimmer, Karl

    2005-05-01

    As lithography and other patterning processes become more complex and more non-linear with each generation, the task of physical design rules necessarily increases in complexity also. The goal of the physical design rules is to define the boundary between the physical layout structures which will yield well from those which will not. This is essentially a rule-based pre-silicon guarantee of layout correctness. However the rapid increase in design rule requirement complexity has created logistical problems for both the design and process functions. Therefore, similar to the semiconductor industry's transition from rule-based to model-based optical proximity correction (OPC) due to increased patterning complexity, opportunities for improving physical design restrictions by implementing model-based physical design methods are evident. In this paper we analyze the possible need and applications for model-based physical design restrictions (MBPDR). We first analyze the traditional design rule evolution, development and usage methodologies for semiconductor manufacturers. Next we discuss examples of specific design rule challenges requiring new solution methods in the patterning regime of low K1 lithography and highly complex RET. We then evaluate possible working strategies for MBPDR in the process development and product design flows, including examples of recent model-based pre-silicon verification techniques. Finally we summarize with a proposed flow and key considerations for MBPDR implementation.

  4. MATTS- A Step Towards Model Based Testing

    NASA Astrophysics Data System (ADS)

    Herpel, H.-J.; Willich, G.; Li, J.; Xie, J.; Johansen, B.; Kvinnesland, K.; Krueger, S.; Barrios, P.

    2016-08-01

    In this paper we describe a Model Based approach to testing of on-board software and compare it with traditional validation strategy currently applied to satellite software. The major problems that software engineering will face over at least the next two decades are increasing application complexity driven by the need for autonomy and serious application robustness. In other words, how do we actually get to declare success when trying to build applications one or two orders of magnitude more complex than today's applications. To solve the problems addressed above the software engineering process has to be improved at least for two aspects: 1) Software design and 2) Software testing. The software design process has to evolve towards model-based approaches with extensive use of code generators. Today, testing is an essential, but time and resource consuming activity in the software development process. Generating a short, but effective test suite usually requires a lot of manual work and expert knowledge. In a model-based process, among other subtasks, test construction and test execution can also be partially automated. The basic idea behind the presented study was to start from a formal model (e.g. State Machines), generate abstract test cases which are then converted to concrete executable test cases (input and expected output pairs). The generated concrete test cases were applied to an on-board software. Results were collected and evaluated wrt. applicability, cost-efficiency, effectiveness at fault finding, and scalability.

  5. Unified Modeling Language (UML) for hospital-based cancer registration processes.

    PubMed

    Shiki, Naomi; Ohno, Yuko; Fujii, Ayumi; Murata, Taizo; Matsumura, Yasushi

    2008-01-01

    Hospital-based cancer registry involves complex processing steps that span across multiple departments. In addition, management techniques and registration procedures differ depending on each medical facility. Establishing processes for hospital-based cancer registry requires clarifying specific functions and labor needed. In recent years, the business modeling technique, in which management evaluation is done by clearly spelling out processes and functions, has been applied to business process analysis. However, there are few analytical reports describing the applications of these concepts to medical-related work. In this study, we initially sought to model hospital-based cancer registration processes using the Unified Modeling Language (UML), to clarify functions. The object of this study was the cancer registry of Osaka University Hospital. We organized the hospital-based cancer registration processes based on interview and observational surveys, and produced an As-Is model using activity, use-case, and class diagrams. After drafting every UML model, it was fed-back to practitioners to check its validity and improved. We were able to define the workflow for each department using activity diagrams. In addition, by using use-case diagrams we were able to classify each department within the hospital as a system, and thereby specify the core processes and staff that were responsible for each department. The class diagrams were effective in systematically organizing the information to be used for hospital-based cancer registries. Using UML modeling, hospital-based cancer registration processes were broadly classified into three separate processes, namely, registration tasks, quality control, and filing data. An additional 14 functions were also extracted. Many tasks take place within the hospital-based cancer registry office, but the process of providing information spans across multiple departments. Moreover, additional tasks were required in comparison to using a

  6. Model-based adaptive 3D sonar reconstruction in reverberating environments.

    PubMed

    Saucan, Augustin-Alexandru; Sintes, Christophe; Chonavel, Thierry; Caillec, Jean-Marc Le

    2015-10-01

    In this paper, we propose a novel model-based approach for 3D underwater scene reconstruction, i.e., bathymetry, for side scan sonar arrays in complex and highly reverberating environments like shallow water areas. The presence of multipath echoes and volume reverberation generates false depth estimates. To improve the resulting bathymetry, this paper proposes and develops an adaptive filter, based on several original geometrical models. This multimodel approach makes it possible to track and separate the direction of arrival trajectories of multiple echoes impinging the array. Echo tracking is perceived as a model-based processing stage, incorporating prior information on the temporal evolution of echoes in order to reject cluttered observations generated by interfering echoes. The results of the proposed filter on simulated and real sonar data showcase the clutter-free and regularized bathymetric reconstruction. Model validation is carried out with goodness of fit tests, and demonstrates the importance of model-based processing for bathymetry reconstruction.

  7. Model-based vision for space applications

    NASA Technical Reports Server (NTRS)

    Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

    1992-01-01

    This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

  8. Model-based sensor-less wavefront aberration correction in optical coherence tomography.

    PubMed

    Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

    2015-12-15

    Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

  9. The Effect of Modeling Based Science Education on Critical Thinking

    ERIC Educational Resources Information Center

    Bati, Kaan; Kaptan, Fitnat

    2015-01-01

    In this study to what degree the modeling based science education can influence the development of the critical thinking skills of the students was investigated. The research was based on pre-test-post-test quasi-experimental design with control group. The Modeling Based Science Education Program which was prepared with the purpose of exploring…

  10. Variable cycle control model for intersection based on multi-source information

    NASA Astrophysics Data System (ADS)

    Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

    2018-05-01

    In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

  11. A Cognitive Model Based on Neuromodulated Plasticity

    PubMed Central

    Ruan, Xiaogang

    2016-01-01

    Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model. PMID:27872638

  12. Promoting Evidence-Based Practice: Models and Mechanisms from Cross-Sector Review

    ERIC Educational Resources Information Center

    Nutley, Sandra; Walter, Isabel; Davies, Huw T. O.

    2009-01-01

    This article draws on both a cross-sector literature review of mechanisms to promote evidence-based practice and a specific review of ways of improving research use in social care. At the heart of the article is a discussion of three models of evidence-based practice: the research-based practitioner model, the embedded research model, and the…

  13. Agent-based modeling in ecological economics.

    PubMed

    Heckbert, Scott; Baynes, Tim; Reeson, Andrew

    2010-01-01

    Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

  14. REAL-TIME MODEL-BASED ELECTRICAL POWERED WHEELCHAIR CONTROL

    PubMed Central

    Wang, Hongwu; Salatin, Benjamin; Grindle, Garrett G.; Ding, Dan; Cooper, Rory A.

    2009-01-01

    The purpose of this study was to evaluate the effects of three different control methods on driving speed variation and wheel-slip of an electric-powered wheelchair (EPW). A kinematic model as well as 3-D dynamic model was developed to control the velocity and traction of the wheelchair. A smart wheelchair platform was designed and built with a computerized controller and encoders to record wheel speeds and to detect the slip. A model based, a proportional-integral-derivative (PID) and an open-loop controller were applied with the EPW driving on four different surfaces at three specified speeds. The speed errors, variation, rise time, settling time and slip coefficient were calculated and compared for a speed step-response input. Experimental results showed that model based control performed best on all surfaces across the speeds. PMID:19733494

  15. Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

    PubMed

    Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

    2018-02-01

    This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Group-Based Active Learning of Classification Models.

    PubMed

    Luo, Zhipeng; Hauskrecht, Milos

    2017-05-01

    Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

  17. DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation.

    PubMed

    Zhang, Laobing; Landucci, Gabriele; Reniers, Genserik; Khakzad, Nima; Zhou, Jianfeng

    2017-12-19

    Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases. © 2017 Society for Risk Analysis.

  18. Reliability modeling of fault-tolerant computer based systems

    NASA Technical Reports Server (NTRS)

    Bavuso, Salvatore J.

    1987-01-01

    Digital fault-tolerant computer-based systems have become commonplace in military and commercial avionics. These systems hold the promise of increased availability, reliability, and maintainability over conventional analog-based systems through the application of replicated digital computers arranged in fault-tolerant configurations. Three tightly coupled factors of paramount importance, ultimately determining the viability of these systems, are reliability, safety, and profitability. Reliability, the major driver affects virtually every aspect of design, packaging, and field operations, and eventually produces profit for commercial applications or increased national security. However, the utilization of digital computer systems makes the task of producing credible reliability assessment a formidable one for the reliability engineer. The root of the problem lies in the digital computer's unique adaptability to changing requirements, computational power, and ability to test itself efficiently. Addressed here are the nuances of modeling the reliability of systems with large state sizes, in the Markov sense, which result from systems based on replicated redundant hardware and to discuss the modeling of factors which can reduce reliability without concomitant depletion of hardware. Advanced fault-handling models are described and methods of acquiring and measuring parameters for these models are delineated.

  19. Agent-based Modeling with MATSim for Hazards Evacuation Planning

    NASA Astrophysics Data System (ADS)

    Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

    2015-12-01

    Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

  20. Cloud-Based Tools to Support High-Resolution Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Jones, N.; Nelson, J.; Swain, N.; Christensen, S.

    2013-12-01

    The majority of watershed models developed to support decision-making by water management agencies are simple, lumped-parameter models. Maturity in research codes and advances in the computational power from multi-core processors on desktop machines, commercial cloud-computing resources, and supercomputers with thousands of cores have created new opportunities for employing more accurate, high-resolution distributed models for routine use in decision support. The barriers for using such models on a more routine basis include massive amounts of spatial data that must be processed for each new scenario and lack of efficient visualization tools. In this presentation we will review a current NSF-funded project called CI-WATER that is intended to overcome many of these roadblocks associated with high-resolution modeling. We are developing a suite of tools that will make it possible to deploy customized web-based apps for running custom scenarios for high-resolution models with minimal effort. These tools are based on a software stack that includes 52 North, MapServer, PostGIS, HT Condor, CKAN, and Python. This open source stack provides a simple scripting environment for quickly configuring new custom applications for running high-resolution models as geoprocessing workflows. The HT Condor component facilitates simple access to local distributed computers or commercial cloud resources when necessary for stochastic simulations. The CKAN framework provides a powerful suite of tools for hosting such workflows in a web-based environment that includes visualization tools and storage of model simulations in a database to archival, querying, and sharing of model results. Prototype applications including land use change, snow melt, and burned area analysis will be presented. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

  1. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    NASA Astrophysics Data System (ADS)

    Xiang, Lin

    This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8 th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on natural selection implemented in a charter school of a major California city during spring semester of 2009. Eight 8th grade students, two boys and six girls, participated in this study. All of them were low socioeconomic status (SES). English was a second language for all of them, but they had been identified as fluent English speakers at least a year before the study. None of them had learned either natural selection or programming before the study. The study spanned over 7 weeks and was comprised of two study phases. In phase one the subject students learned natural selection in science classroom and how to do programming in NetLogo, an ABPM tool, in a computer lab; in phase two, the subject students were asked to program a simulation of adaptation based on the natural selection model in NetLogo. Both qualitative and quantitative data were collected in this study. The data resources included (1) pre and post test questionnaire, (2) student in-class worksheet, (3) programming planning sheet, (4) code-conception matching sheet, (5) student NetLogo projects, (6) videotaped programming processes, (7) final interview, and (8) investigator's field notes. Both qualitative and quantitative approaches were applied to analyze the gathered data. The findings suggested that students made progress on understanding adaptation phenomena and natural selection at the end of ABPM-supported MBI learning but the progress was limited. These students still held some misconceptions in their conceptual models, such as the idea that animals need to "learn" to adapt into the environment. Besides, their models of natural selection appeared to be

  2. An ontology for component-based models of water resource systems

    NASA Astrophysics Data System (ADS)

    Elag, Mostafa; Goodall, Jonathan L.

    2013-08-01

    Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.

  3. Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

    NASA Astrophysics Data System (ADS)

    Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

    2017-12-01

    Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

  4. Development and validation of deterioration models for concrete bridge decks - phase 2 : mechanics-based degradation models.

    DOT National Transportation Integrated Search

    2013-06-01

    This report summarizes a research project aimed at developing degradation models for bridge decks in the state of Michigan based on durability mechanics. A probabilistic framework to implement local-level mechanistic-based models for predicting the c...

  5. Luminance-model-based DCT quantization for color image compression

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Peterson, Heidi A.

    1992-01-01

    A model is developed to approximate visibility thresholds for discrete cosine transform (DCT) coefficient quantization error based on the peak-to-peak luminance of the error image. Experimentally measured visibility thresholds for R, G, and B DCT basis functions can be predicted by a simple luminance-based detection model. This model allows DCT coefficient quantization matrices to be designed for display conditions other than those of the experimental measurements: other display luminances, other veiling luminances, and other spatial frequencies (different pixel spacings, viewing distances, and aspect ratios).

  6. Circulation-based Modeling of Gravity Currents

    NASA Astrophysics Data System (ADS)

    Meiburg, E. H.; Borden, Z.

    2013-05-01

    Atmospheric and oceanic flows driven by predominantly horizontal density differences, such as sea breezes, thunderstorm outflows, powder snow avalanches, and turbidity currents, are frequently modeled as gravity currents. Efforts to develop simplified models of such currents date back to von Karman (1940), who considered a two-dimensional gravity current in an inviscid, irrotational and infinitely deep ambient. Benjamin (1968) presented an alternative model, focusing on the inviscid, irrotational flow past a gravity current in a finite-depth channel. More recently, Shin et al. (2004) proposed a model for gravity currents generated by partial-depth lock releases, considering a control volume that encompasses both fronts. All of the above models, in addition to the conservation of mass and horizontal momentum, invoke Bernoulli's law along some specific streamline in the flow field, in order to obtain a closed system of equations that can be solved for the front velocity as function of the current height. More recent computational investigations based on the Navier-Stokes equations, on the other hand, reproduce the dynamics of gravity currents based on the conservation of mass and momentum alone. We propose that it should therefore be possible to formulate a fundamental gravity current model without invoking Bernoulli's law. The talk will show that the front velocity of gravity currents can indeed be predicted as a function of their height from mass and momentum considerations alone, by considering the evolution of interfacial vorticity. This approach does not require information on the pressure field and therefore avoids the need for an energy closure argument such as those invoked by the earlier models. Predictions by the new theory are shown to be in close agreement with direct numerical simulation results. References Von Karman, T. 1940 The engineer grapples with nonlinear problems, Bull. Am. Math Soc. 46, 615-683. Benjamin, T.B. 1968 Gravity currents and related

  7. Task Delegation Based Access Control Models for Workflow Systems

    NASA Astrophysics Data System (ADS)

    Gaaloul, Khaled; Charoy, François

    e-Government organisations are facilitated and conducted using workflow management systems. Role-based access control (RBAC) is recognised as an efficient access control model for large organisations. The application of RBAC in workflow systems cannot, however, grant permissions to users dynamically while business processes are being executed. We currently observe a move away from predefined strict workflow modelling towards approaches supporting flexibility on the organisational level. One specific approach is that of task delegation. Task delegation is a mechanism that supports organisational flexibility, and ensures delegation of authority in access control systems. In this paper, we propose a Task-oriented Access Control (TAC) model based on RBAC to address these requirements. We aim to reason about task from organisational perspectives and resources perspectives to analyse and specify authorisation constraints. Moreover, we present a fine grained access control protocol to support delegation based on the TAC model.

  8. Detailed Primitive-Based 3d Modeling of Architectural Elements

    NASA Astrophysics Data System (ADS)

    Remondino, F.; Lo Buglio, D.; Nony, N.; De Luca, L.

    2012-07-01

    The article describes a pipeline, based on image-data, for the 3D reconstruction of building façades or architectural elements and the successive modeling using geometric primitives. The approach overcome some existing problems in modeling architectural elements and deliver efficient-in-size reality-based textured 3D models useful for metric applications. For the 3D reconstruction, an opensource pipeline developed within the TAPENADE project is employed. In the successive modeling steps, the user manually selects an area containing an architectural element (capital, column, bas-relief, window tympanum, etc.) and then the procedure fits geometric primitives and computes disparity and displacement maps in order to tie visual and geometric information together in a light but detailed 3D model. Examples are reported and commented.

  9. Development and verification of an agent-based model of opinion leadership.

    PubMed

    Anderson, Christine A; Titler, Marita G

    2014-09-27

    The use of opinion leaders is a strategy used to speed the process of translating research into practice. Much is still unknown about opinion leader attributes and activities and the context in which they are most effective. Agent-based modeling is a methodological tool that enables demonstration of the interactive and dynamic effects of individuals and their behaviors on other individuals in the environment. The purpose of this study was to develop and test an agent-based model of opinion leadership. The details of the design and verification of the model are presented. The agent-based model was developed by using a software development platform to translate an underlying conceptual model of opinion leadership into a computer model. Individual agent attributes (for example, motives and credibility) and behaviors (seeking or providing an opinion) were specified as variables in the model in the context of a fictitious patient care unit. The verification process was designed to test whether or not the agent-based model was capable of reproducing the conditions of the preliminary conceptual model. The verification methods included iterative programmatic testing ('debugging') and exploratory analysis of simulated data obtained from execution of the model. The simulation tests included a parameter sweep, in which the model input variables were adjusted systematically followed by an individual time series experiment. Statistical analysis of model output for the 288 possible simulation scenarios in the parameter sweep revealed that the agent-based model was performing, consistent with the posited relationships in the underlying model. Nurse opinion leaders act on the strength of their beliefs and as a result, become an opinion resource for their uncertain colleagues, depending on their perceived credibility. Over time, some nurses consistently act as this type of resource and have the potential to emerge as opinion leaders in a context where uncertainty exists. The

  10. Template-based structure modeling of protein-protein interactions

    PubMed Central

    Szilagyi, Andras; Zhang, Yang

    2014-01-01

    The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been witnessed in genome-wide applications of template-based modeling, with modeling accuracy comparable to high-throughput experimental data. Nevertheless, bottlenecks exist due to the incompleteness of the proteinprotein complex structure library and the lack of methods for distant homologous template identification and full-length complex structure refinement. PMID:24721449

  11. GTM-Based QSAR Models and Their Applicability Domains.

    PubMed

    Gaspar, H A; Baskin, I I; Marcou, G; Horvath, D; Varnek, A

    2015-06-01

    In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to QSAR modelling using probability distribution functions (PDF) computed in the latent 2-dimensional space. Several different scenarios of the activity assessment were considered: (i) the "activity landscape" approach based on direct use of PDF, (ii) QSAR models involving GTM-generated on descriptors derived from PDF, and, (iii) the k-Nearest Neighbours approach in 2D latent space. Benchmarking calculations were performed on five different datasets: stability constants of metal cations Ca(2+) , Gd(3+) and Lu(3+) complexes with organic ligands in water, aqueous solubility and activity of thrombin inhibitors. It has been shown that the performance of GTM-based regression models is similar to that obtained with some popular machine-learning methods (random forest, k-NN, M5P regression tree and PLS) and ISIDA fragment descriptors. By comparing GTM activity landscapes built both on predicted and experimental activities, we may visually assess the model's performance and identify the areas in the chemical space corresponding to reliable predictions. The applicability domain used in this work is based on data likelihood. Its application has significantly improved the model performances for 4 out of 5 datasets. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Model-Based Sensor-Augmented Pump Therapy

    PubMed Central

    Grosman, Benyamin; Voskanyan, Gayane; Loutseiko, Mikhail; Roy, Anirban; Mehta, Aloke; Kurtz, Natalie; Parikh, Neha; Kaufman, Francine R.; Mastrototaro, John J.; Keenan, Barry

    2013-01-01

    Background In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient’s pump. Methods A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject’s BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested. Results The percentage of time in glucose range 80–180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61–231 mg/dl min–max envelope, whereas use of the simulator’s default treatment resulted in BG measurements 90–210 mg/dl min–max envelope. Conclusions The study results demonstrate the potential of this method, which could serve as a platform for improving, facilitating, and standardizing insulin pump therapy based on a single download of data. PMID:23567006

  13. Catchment area-based evaluation of the AMC-dependent SCS-CN-based rainfall-runoff models

    NASA Astrophysics Data System (ADS)

    Mishra, S. K.; Jain, M. K.; Pandey, R. P.; Singh, V. P.

    2005-09-01

    Using a large set of rainfall-runoff data from 234 watersheds in the USA, a catchment area-based evaluation of the modified version of the Mishra and Singh (2002a) model was performed. The model is based on the Soil Conservation Service Curve Number (SCS-CN) methodology and incorporates the antecedent moisture in computation of direct surface runoff. Comparison with the existing SCS-CN method showed that the modified version performed better than did the existing one on the data of all seven area-based groups of watersheds ranging from 0.01 to 310.3 km2.

  14. Feedback loops and temporal misalignment in component-based hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.

    2011-12-01

    In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

  15. Agent-based model for rural-urban migration: A dynamic consideration

    NASA Astrophysics Data System (ADS)

    Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

    2015-10-01

    This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

  16. THE FUTURE OF COMPUTER-BASED TOXICITY PREDICTION: MECHANISM-BASED MODELS VS. INFORMATION MINING APPROACHES

    EPA Science Inventory


    The Future of Computer-Based Toxicity Prediction:
    Mechanism-Based Models vs. Information Mining Approaches

    When we speak of computer-based toxicity prediction, we are generally referring to a broad array of approaches which rely primarily upon chemical structure ...

  17. Model-based quality assessment and base-calling for second-generation sequencing data.

    PubMed

    Bravo, Héctor Corrada; Irizarry, Rafael A

    2010-09-01

    Second-generation sequencing (sec-gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads-strings of A,C,G, or T's, between 30 and 100 characters long-which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base-calling. The complexity of the base-calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across-sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec-gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base-calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base-calling allowing for informative and easily interpretable metrics that capture the variability in

  18. Marker-based or model-based RSA for evaluation of hip resurfacing arthroplasty? A clinical validation and 5-year follow-up.

    PubMed

    Lorenzen, Nina Dyrberg; Stilling, Maiken; Jakobsen, Stig Storgaard; Gustafson, Klas; Søballe, Kjeld; Baad-Hansen, Thomas

    2013-11-01

    The stability of implants is vital to ensure a long-term survival. RSA determines micro-motions of implants as a predictor of early implant failure. RSA can be performed as a marker- or model-based analysis. So far, CAD and RE model-based RSA have not been validated for use in hip resurfacing arthroplasty (HRA). A phantom study determined the precision of marker-based and CAD and RE model-based RSA on a HRA implant. In a clinical study, 19 patients were followed with stereoradiographs until 5 years after surgery. Analysis of double-examination migration results determined the clinical precision of marker-based and CAD model-based RSA, and at the 5-year follow-up, results of the total translation (TT) and the total rotation (TR) for marker- and CAD model-based RSA were compared. The phantom study showed that comparison of the precision (SDdiff) in marker-based RSA analysis was more precise than model-based RSA analysis in TT (p CAD < 0.001; p RE = 0.04) and TR (p CAD = 0.01; p RE < 0.001). The clinical precision (double examination in 8 patients) comparing the precision SDdiff was better evaluating the TT using the marker-based RSA analysis (p = 0.002), but showed no difference between the marker- and CAD model-based RSA analysis regarding the TR (p = 0.91). Comparing the mean signed values regarding the TT and the TR at the 5-year follow-up in 13 patients, the TT was lower (p = 0.03) and the TR higher (p = 0.04) in the marker-based RSA compared to CAD model-based RSA. The precision of marker-based RSA was significantly better than model-based RSA. However, problems with occluded markers lead to exclusion of many patients which was not a problem with model-based RSA. HRA were stable at the 5-year follow-up. The detection limit was 0.2 mm TT and 1° TR for marker-based and 0.5 mm TT and 1° TR for CAD model-based RSA for HRA.

  19. Web-based reactive transport modeling using PFLOTRAN

    NASA Astrophysics Data System (ADS)

    Zhou, H.; Karra, S.; Lichtner, P. C.; Versteeg, R.; Zhang, Y.

    2017-12-01

    Actionable understanding of system behavior in the subsurface is required for a wide spectrum of societal and engineering needs by both commercial firms and government entities and academia. These needs include, for example, water resource management, precision agriculture, contaminant remediation, unconventional energy production, CO2 sequestration monitoring, and climate studies. Such understanding requires the ability to numerically model various coupled processes that occur across different temporal and spatial scales as well as multiple physical domains (reservoirs - overburden, surface-subsurface, groundwater-surface water, saturated-unsaturated zone). Currently, this ability is typically met through an in-house approach where computational resources, model expertise, and data for model parameterization are brought together to meet modeling needs. However, such an approach has multiple drawbacks which limit the application of high-end reactive transport codes such as the Department of Energy funded[?] PFLOTRAN code. In addition, while many end users have a need for the capabilities provided by high-end reactive transport codes, they do not have the expertise - nor the time required to obtain the expertise - to effectively use these codes. We have developed and are actively enhancing a cloud-based software platform through which diverse users are able to easily configure, execute, visualize, share, and interpret PFLOTRAN models. This platform consists of a web application and available on-demand HPC computational infrastructure. The web application consists of (1) a browser-based graphical user interface which allows users to configure models and visualize results interactively, and (2) a central server with back-end relational databases which hold configuration, data, modeling results, and Python scripts for model configuration, and (3) a HPC environment for on-demand model execution. We will discuss lessons learned in the development of this platform, the

  20. Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies

    PubMed Central

    Khamassi, Mehdi; Humphries, Mark D.

    2012-01-01

    Behavior in spatial navigation is often organized into map-based (place-driven) vs. map-free (cue-driven) strategies; behavior in operant conditioning research is often organized into goal-directed vs. habitual strategies. Here we attempt to unify the two. We review one powerful theory for distinct forms of learning during instrumental conditioning, namely model-based (maintaining a representation of the world) and model-free (reacting to immediate stimuli) learning algorithms. We extend these lines of argument to propose an alternative taxonomy for spatial navigation, showing how various previously identified strategies can be distinguished as “model-based” or “model-free” depending on the usage of information and not on the type of information (e.g., cue vs. place). We argue that identifying “model-free” learning with dorsolateral striatum and “model-based” learning with dorsomedial striatum could reconcile numerous conflicting results in the spatial navigation literature. From this perspective, we further propose that the ventral striatum plays key roles in the model-building process. We propose that the core of the ventral striatum is positioned to learn the probability of action selection for every transition between states of the world. We further review suggestions that the ventral striatal core and shell are positioned to act as “critics” contributing to the computation of a reward prediction error for model-free and model-based systems, respectively. PMID:23205006

  1. High-Throughput Physiologically Based Toxicokinetic Models for ToxCast Chemicals

    EPA Science Inventory

    Physiologically based toxicokinetic (PBTK) models aid in predicting exposure doses needed to create tissue concentrations equivalent to those identified as bioactive by ToxCast. We have implemented four empirical and physiologically-based toxicokinetic (TK) models within a new R ...

  2. Understanding Elementary Astronomy by Making Drawing-Based Models

    ERIC Educational Resources Information Center

    van Joolingen, W. R.; Aukes, Annika V.; Gijlers, H.; Bollen, L.

    2015-01-01

    Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a…

  3. Symbolic Processing Combined with Model-Based Reasoning

    NASA Technical Reports Server (NTRS)

    James, Mark

    2009-01-01

    A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

  4. Intelligent model-based OPC

    NASA Astrophysics Data System (ADS)

    Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

    2006-03-01

    Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm

  5. Magnetic properties evolution of the CoxFe3-xO4/SiO2 system due to advanced thermal treatment at 700 °C and 1000 °C

    NASA Astrophysics Data System (ADS)

    Dippong, Thomas; Levei, Erika Andrea; Tanaselia, Claudiu; Gabor, Mihai; Nasui, Mircea; Barbu Tudoran, Lucian; Borodi, Gheorghe

    2016-07-01

    The CoxFe3-xO4 (x=0.5-2.5) system embedded in the silica matrix was synthesised by sol-gel method using cobalt nitrate, iron nitrate, 1.4-butanediol and tetraethyl orthosilicate. Five different Co/Fe molar ratios in the presence of diol and one without diol were used for the synthesis. The obtained gels were subjected to thermal treatment at 700 °C and 1000 °C. The oxide species formed in the silica matrix, the optimum temperature for the CoFe2O4 phase formation, the evolution of nanocrystallites size and magnetic properties with the calcination temperature were studied. The formed oxide species were studied using X-ray diffraction, Fourier transformed infrared spectrometry, the Co/Fe molar ratio was confirmed using inductively coupled plasma optical emission spectrometry, the nanocrystallites size, shape and clustering was identified by transmission electron microscopy and scanning electron microscopy, while the formation of magnetic phases was investigated by hysteresis and magnetization derivatives measurements.

  6. Structural hysteresis in dragline spider silks induced by supercontraction: an X-ray fiber micro-diffraction study

    DOE PAGES

    Sampath, Sujatha; Yarger, Jeffery L.

    2014-11-27

    Interaction with water causes shrinkage and significant changes in the structure of spider dragline silks, which has been referred to as supercontraction in the literature. Preferred orientation or alignment of protein chains with respect to the fiber axis is extensively changed during this supercontraction process. Synchrotron X-ray micro-fiber diffraction experiments have been performed on Nephila clavipes and Argiope aurantia major and minor ampullate dragline spider fibers in the native dry, contracted (by immersion in water) and restretched (from contracted) states. Changes in the orientation of β-sheet nanocrystallites and the oriented component of the amorphous network have been determined from wide-anglemore » X-ray diffraction patterns. While both the crystalline and amorphous components lose preferred orientation on wetting with water, the nano-crystallites regain their orientation on wet-restretching, whereas the oriented amorphous components only partially regain their orientation. Dragline major ampullate silks in both the species contract more than their minor ampullate silks.« less

  7. Stability of model-based event-triggered control systems: a separation property

    NASA Astrophysics Data System (ADS)

    Hao, Fei; Yu, Hao

    2017-04-01

    To save resource of communication, this paper investigates the model-based event-triggered control systems. Two main problems are considered in this paper. One is, for given plant and model, to design event conditions to guarantee the stability of the systems. The other is to consider the effect of the model matrices on the stability. The results show that the closed-loop systems can be asymptotically stabilised with any model matrices in compact sets if the parameters in the event conditions are within the designed ranges. Then, a separation property of model-based event-triggered control is proposed. Namely, the design of the controller gain and the event condition can be separated from the selection of the model matrices. Based on this property, an adaption mechanism is introduced to the model-based event-triggered control systems, which can further improve the sampling performance. Finally, a numerical example is given to show the efficiency and feasibility of the developed results.

  8. A Framework for Model-Based Inquiry through Agent-Based Programming

    ERIC Educational Resources Information Center

    Xiang, Lin; Passmore, Cynthia

    2015-01-01

    There has been increased recognition in the past decades that model-based inquiry (MBI) is a promising approach for cultivating deep understandings by helping students unite phenomena and underlying mechanisms. Although multiple technology tools have been used to improve the effectiveness of MBI, there are not enough detailed examinations of how…

  9. Comparing and combining process-based crop models and statistical models with some implications for climate change

    NASA Astrophysics Data System (ADS)

    Roberts, Michael J.; Braun, Noah O.; Sinclair, Thomas R.; Lobell, David B.; Schlenker, Wolfram

    2017-09-01

    We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model.

  10. Organization-based Model-driven Development of High-assurance Multiagent Systems

    DTIC Science & Technology

    2009-02-27

    based Model -driven Development of High-assurance Multiagent Systems " performed by Dr. Scott A . DeLoach and Dr Robby at Kansas State University... A Capabilities Based Model for Artificial Organizations. Journal of Autonomous Agents and Multiagent Systems . Volume 16, no. 1, February 2008, pp...Matson, E . T. (2007). A capabilities based theory of artificial organizations. Journal of Autonomous Agents and Multiagent Systems

  11. Model-Based Battery Management Systems: From Theory to Practice

    NASA Astrophysics Data System (ADS)

    Pathak, Manan

    Lithium-ion batteries are now extensively being used as the primary storage source. Capacity and power fade, and slow recharging times are key issues that restrict its use in many applications. Battery management systems are critical to address these issues, along with ensuring its safety. This dissertation focuses on exploring various control strategies using detailed physics-based electrochemical models developed previously for lithium-ion batteries, which could be used in advanced battery management systems. Optimal charging profiles for minimizing capacity fade based on SEI-layer formation are derived and the benefits of using such control strategies are shown by experimentally testing them on a 16 Ah NMC-based pouch cell. This dissertation also explores different time-discretization strategies for non-linear models, which gives an improved order of convergence for optimal control problems. Lastly, this dissertation also explores a physics-based model for predicting the linear impedance of a battery, and develops a freeware that is extremely robust and computationally fast. Such a code could be used for estimating transport, kinetic and material properties of the battery based on the linear impedance spectra.

  12. DEM Based Modeling: Grid or TIN? The Answer Depends

    NASA Astrophysics Data System (ADS)

    Ogden, F. L.; Moreno, H. A.

    2015-12-01

    The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

  13. Densification behavior, nanocrystallization, and mechanical properties of spark plasma sintered Fe-based bulk amorphous alloys

    NASA Astrophysics Data System (ADS)

    Singh, Ashish Kumar

    Fe-based amorphous alloys are gaining increasing attention due to their exceptional wear and corrosion resistance for potential structural applications. Two major challenges that are hindering the commercialization of these amorphous alloys are difficulty in processing of bulk shapes (diameter > 10 mm) and lack of ductility. Spark plasma sintering (SPS) is evolving as a promising technique for processing bulk shapes of amorphous and nanocrystalline materials. The objective of this work is to investigate densification behavior, nanocrystallization, and mechanical properties of SPS sintered Fe-based amorphous alloys of composition Fe48Cr15Mo14Y2C15B6. SPS processing was performed in three distinct temperature ranges of amorphous alloys: (a) below glass transition temperature (Tg), (b) between Tg and crystallization temperature (Tx), and (c) above Tx. Punch displacement data obtained during SPS sintering was correlated with the SPS processing parameters such as temperature, pressure, and sintering time. Powder rearrangement, plastic deformation below T g, and viscous flow of the material between Tg and Tx were observed as the main densification stages during SPS sintering. Micro-scale temperature distributions at the point of contact and macro-scale temperature distribution throughout the sample during SPS of amorphous alloys were modeled. The bulk amorphous alloys are expected to undergo structural relaxation and nanocrystallization during SPS sintering. X-ray diffraction (XRD), small angle neutron scattering (SANS), and transmission electron microscopy (TEM) was performed to investigate the evolution of nanocrystallites in SPS sintered Fe-based bulk amorphous alloys. The SANS analysis showed significant scattering for the samples sintered in the supercooled region indicating local structural and compositional changes with the profuse nucleation of nano-clusters (~4 nm). Compression tests and microhardness were performed on the samples sintered at different

  14. A biodynamic feedthrough model based on neuromuscular principles.

    PubMed

    Venrooij, Joost; Abbink, David A; Mulder, Mark; van Paassen, Marinus M; Mulder, Max; van der Helm, Frans C T; Bulthoff, Heinrich H

    2014-07-01

    A biodynamic feedthrough (BDFT) model is proposed that describes how vehicle accelerations feed through the human body, causing involuntary limb motions and so involuntary control inputs. BDFT dynamics strongly depend on limb dynamics, which can vary between persons (between-subject variability), but also within one person over time, e.g., due to the control task performed (within-subject variability). The proposed BDFT model is based on physical neuromuscular principles and is derived from an established admittance model-describing limb dynamics-which was extended to include control device dynamics and account for acceleration effects. The resulting BDFT model serves primarily the purpose of increasing the understanding of the relationship between neuromuscular admittance and biodynamic feedthrough. An added advantage of the proposed model is that its parameters can be estimated using a two-stage approach, making the parameter estimation more robust, as the procedure is largely based on the well documented procedure required for the admittance model. To estimate the parameter values of the BDFT model, data are used from an experiment in which both neuromuscular admittance and biodynamic feedthrough are measured. The quality of the BDFT model is evaluated in the frequency and time domain. Results provide strong evidence that the BDFT model and the proposed method of parameter estimation put forward in this paper allows for accurate BDFT modeling across different subjects (accounting for between-subject variability) and across control tasks (accounting for within-subject variability).

  15. A physiologically based toxicokinetic model for lake trout (Salvelinus namaycush).

    PubMed

    Lien, G J; McKim, J M; Hoffman, A D; Jenson, C T

    2001-01-01

    A physiologically based toxicokinetic (PB-TK) model for fish, incorporating chemical exchange at the gill and accumulation in five tissue compartments, was parameterized and evaluated for lake trout (Salvelinus namaycush). Individual-based model parameterization was used to examine the effect of natural variability in physiological, morphological, and physico-chemical parameters on model predictions. The PB-TK model was used to predict uptake of organic chemicals across the gill and accumulation in blood and tissues in lake trout. To evaluate the accuracy of the model, a total of 13 adult lake trout were exposed to waterborne 1,1,2,2-tetrachloroethane (TCE), pentachloroethane (PCE), and hexachloroethane (HCE), concurrently, for periods of 6, 12, 24 or 48 h. The measured and predicted concentrations of TCE, PCE and HCE in expired water, dorsal aortic blood and tissues were generally within a factor of two, and in most instances much closer. Variability noted in model predictions, based on the individual-based model parameterization used in this study, reproduced variability observed in measured concentrations. The inference is made that parameters influencing variability in measured blood and tissue concentrations of xenobiotics are included and accurately represented in the model. This model contributes to a better understanding of the fundamental processes that regulate the uptake and disposition of xenobiotic chemicals in the lake trout. This information is crucial to developing a better understanding of the dynamic relationships between contaminant exposure and hazard to the lake trout.

  16. A Multiagent Based Model for Tactical Planning

    DTIC Science & Technology

    2002-10-01

    Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

  17. Carbon matrix based magnetic nanocomposites for potential biomedical applications.

    PubMed

    Izydorzak-Wozniak, M; Leonowicz, M

    2014-03-01

    It was found that by varying the pyrolysis temperature of the polymeric precursor, carbon matrix magnetic nanocomposites with different constitution and fractions of magnetic component were made. X-ray diffraction, transmission electron microscopy and Raman spectroscopy revealed the presence of nanocrystallites (NCs) of Co, Fe3C and Ni embedded in porous, partially-graphitized carbon matrix. Vibrating sample magnetometer measurements enabled to determine the correlation between NCs size distribution and magnetic properties. The magnetic studies confirmed that the coercivity, saturation and remanent magnetizations, as well as fraction of the magnetic component depend on the pyrolysis temperature. The Co#C and Fe3C#C composites exhibited ferromagnetic behavior with a remanent to saturation magnetization (M(R)/M(S)) ratio ranging from 0.25 to 0.3, whereas in the Ni containing samples a relatively small M(R)/M(S) ratio point to significant contribution of superparamagnetic interactions. As the carbon matrix magnetic nanocomposites are proposed for biomedical application the basic cytotoxicity test were performed to evaluate a potential toxic effect of the materials on MG-63 cells line.

  18. Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

    NASA Astrophysics Data System (ADS)

    Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

    2017-12-01

    Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

  19. Physiologically Based Pharmacokinetic (PBPK) Modeling of ...

    EPA Pesticide Factsheets

    Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, inter-individual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data.Objectives: To evaluate the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. Methods: We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and one hybrid mouse strains to calibrate and extend existing physiologically-based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). A Bayesian population analysis of inter-strain variability was used to quantify variability in TCE metabolism. Results: Concentration-time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation was less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production was less variable (2-fold range) than DCA production (5-fold range), although uncertainty bounds for DCA exceeded the predicted variability. Conclusions:

  20. Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

    NASA Astrophysics Data System (ADS)

    Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

    2017-05-01

    Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.