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Sample records for crust-mantle system inferred

  1. Early history of Earth's crust-mantle system inferred from hafnium isotopes in chondrites.

    PubMed

    Bizzarro, Martin; Baker, Joel A; Haack, Henning; Ulfbeck, David; Rosing, Minik

    2003-02-27

    The 176Lu to 176Hf decay series has been widely used to understand the nature of Earth's early crust-mantle system. The interpretation, however, of Lu-Hf isotope data requires accurate knowledge of the radioactive decay constant of 176Lu (lambda176Lu), as well as bulk-Earth reference parameters. A recent calibration of the lambda176Lu value calls for the presence of highly unradiogenic hafnium in terrestrial zircons with ages greater than 3.9 Gyr, implying widespread continental crust extraction from an isotopically enriched mantle source more than 4.3 Gyr ago, but does not provide evidence for a complementary depleted mantle reservoir. Here we report Lu-Hf isotope measurements of different Solar System objects including chondrites and basaltic eucrites. The chondrites define a Lu-Hf isochron with an initial 176Hf/177Hf ratio of 0.279628 +/- 0.000047, corresponding to lambda176Lu = 1.983 +/- 0.033 x 10-11 yr-1 using an age of 4.56 Gyr for the chondrite-forming event. This lambda176Lu value indicates that Earth's oldest minerals were derived from melts of a mantle source with a time-integrated history of depletion rather than enrichment. The depletion event must have occurred no later than 320 Myr after planetary accretion, consistent with timing inferred from extinct radionuclides.

  2. Early Differentiation of the Crust-Mantle System: a Hf Isotope Perspective

    NASA Astrophysics Data System (ADS)

    Scherer, E.; Munker, C.; Mezger, K.

    2001-12-01

    The Lu decay constant recently determined by Scherer et al. 2001 (i.e., 1.865 x 10-11 yr-1) agrees with the results of the two latest physical counting experiments (1.86 x 10-11 yr-1; Dalmasso et al 1992, Nir-El and Lavi 1998), but is ca. 4 percent lower than the decay constants that have been used throughout the Hf isotope literature (e.g., 1.94 x 10-11, Tatsumoto et al., 1981; 1.93 x 10-11 Sguigna et al, 1982). In addition to making Lu-Hf ages older by ca. 4 percent, the revised decay constant also shifts the calculated initial epsilon Hf values of early Archean and Hadean rocks and zircons that are used to constrain crust-mantle differentiation in the early Earth. The initial epsilon Hf values for low-Lu/Hf samples such as zircons and evolved felsic rocks shift downward by 2-4 epsilon units, primarily due to the shift in the position of the CHUR evolution curve rather than that of the samples themselves. Mafic rocks, such as komatiites have higher Lu/Hf ratios that are closer to that of CHUR and therefore their initial epsilon Hf values do not shift as much (up to 1.3 epsilon units lower or 0.4 epsilon units higher). Using the old decay constant, some early Archean rocks (e.g., Amitsoq gneisses; Vervoort et al., 1996, Vervoort and Blichert-Toft, 1999) seemed to have very high initial epsilon Hf values (up to +6), implying that the upper mantle was moderately depleted in the early Archean and that a substantial volume of crust was produced in the Hadean. However, when recalculated with the new decay constant, the data suggest that the mantle was only slightly depleted, requiring less early crust extraction, and allowing a later date for the onset of significant crust production. In contrast, the extremely low recalculated epsilon Hf values of Earth's oldest zircons (Amelin et al., 1999, Amelin et al., 2000) indicate that Earth's first crust formed at or before 4.3 Ga, and that this crust remained intact long enough (>200 million years) to evolve to such low

  3. Metasedimentary and igneous xenoliths from Tallante (Betic Cordillera, Spain): Inferences on crust-mantle interactions and clues for post-collisional volcanism magma sources

    NASA Astrophysics Data System (ADS)

    Bianchini, Gianluca; Braga, Roberto; Langone, Antonio; Natali, Claudio; Tiepolo, Massimo

    2015-04-01

    The deep seated xenolith association exhumed in the Pliocenic volcano of Tallante (Betic Cordillera, Spain) includes protogranular mantle peridotites, felsic (metasedimentary) crustal rocks, as well as cumulus igneous rocks such as norites and amphibole (± phlogopite)-clinopyroxenites. The whole xenolith suite equilibrated at the same pressure (0.7-0.9 GPa) representing the local crust-mantle boundary (MOHO) characterized by extreme lithological heterogeneity. This heterogeneity resulted from orogenic processes that induced the juxtaposition of crustal rocks (variably depleted in fusible components) within mantle domains including metasomes, as it is commonly observed in orogenic mantle massifs of the Mediterranean area. In this contribution, we report new mineral compositions of igneous parageneses recorded in these xenoliths, and we present Sr-Nd isotope data on both igneous and metasedimentary xenoliths that integrate those from the literature. Sr-Nd isotopes coherently indicate a restitic character of the metasedimentary xenoliths, which according to model ages were affected by partial melting in Paleozoic times. Sr-Nd isotopic errorchrons on the igneous xenoliths, on the other hand, qualitatively indicate Tertiary ages, which are corroborated by U-Pb zircon datings of one norite xenolith and two composite xenoliths having zircon-bearing norite veinlets. The new data are discussed proposing that MOHO lithologies of Tallante could provide significant source compositions for the genesis of the Neogene volcanics of the Betic area, which included calcalkaline lavas as well as more potassic products such as lamproites.

  4. Crust-mantle boundaries in the Taiwan - Luzon arc-continent collision system determined from local earthquake tomography and layered Vp models

    NASA Astrophysics Data System (ADS)

    Ustaszewski, K. M.; Wu, Y.; Suppe, J.; Huang, H.; Carena, S.; Chang, C.

    2011-12-01

    We performed 3D mapping of crust-mantle boundaries in the Taiwan-Luzon arc-continent collision zone using a local earthquake tomographic model, providing better insight into the mode of subduction polarity reversal. The mapped crust-mantle discontinuities include three tectonically distinct Mohos. Furthermore, a crust-mantle boundary marks the eastern limit of the Eurasian lower crust against the mantle of the Philippine Sea plate. It dips steeply to the east underneath eastern and southern Taiwan and steepens progressively towards north until it becomes vertical at 23.7°N. From there it continues northward in a slightly overturned orientation, where the limit of the tomographic model at the northern tip of the island prevents further mapping. In order to map several Moho discontinuities, we contoured a surface of constant Vp = 7.5 km s-1 constrained from local earthquake tomography and confined to regions with a minimum of 500 rays per tomography cell. Additional constraints for the Moho were derived from layered (1D) Vp models using P-wave arrivals of local earthquakes recorded at 52 seismic stations, employing a genetic algorithm. The Moho of the Eurasian and the Philippine Sea plates are topologically disconnected across the plate boundary. Beneath southern Taiwan, the Eurasian Moho dips to the E at 50-60°, following the orientation of the plate boundary and continuous with the Benioff zone. Towards north, the Eurasian Moho twists to become subvertical, again together with the plate boundary. At the same time, it steps westward into a more external position underneath the thrust belt, giving way to the north-dipping Philippine Sea plate. The Philippine Sea plate Moho shallows towards the surface along the Longitudinal Valley suture. It forms a synform-like crustal root with an axis parallel to the trend of geological units at surface and it is interpreted as the base of the magmatic Luzon arc. Towards the north, the crustal root deepens from 30 km to about 70

  5. Petrology, geochemistry and modelling of the granulitic-ultramafic rocks in Beni Bousera (Rif, Morocco): implications for direct crust-mantle interactions and melt-extraction systems

    NASA Astrophysics Data System (ADS)

    Manthei, C. D.; Álvarez-Valero, A.; Jagoutz, O. E.

    2011-12-01

    The Beni Bousera (N. Morocco) and Ronda (S. Spain) ultramafic massifs of the Betic-Rif orogenic belt are two of the most pristine exposures of upper-mantle/lower crustal material on Earth's surface. Unlike other samples of the mantle, they are relatively unaltered and preserve a record of ultra-high pressure conditions, within the diamond-stability field (e.g. Slodkevich, 1980; Pearson et al., 1989). The process of removing of the massifs from the diamond-stability field, and the ensuing emplacement into the continental crust, is an ongoing area of research in regional tectonics. Here, we focus specifically on Beni Bousera, and note that the up-risen material is of higher density than its host, prompting the development of models that use melt-induced buoyancy forces as the primary driver of exhumation (Jagoutz et al., 2006; Gerya and Burg, 2007). We find evidence for discrete reaction zones in the ultramafic rocks that were formed by pervasive infiltration of melt, which may have channelized, lowered the integrated bulk density of the massif (e.g., Jagoutz et al., 2006), and driven exhumation. Since key questions concerning the emplacement mechanisms are still unanswered, complementary studies of the surrounding crustal material -granulitic rocks, which are mostly metapelitic with local intercalation of mafic composition-, assist in deepening our understanding crust-mantle processes. We will discuss our ongoing research at Beni Bousera, focusing on: (1) the petrological, structural, geochronological and physical relationships between mantle and crust by combining field petrology, petrography and phase diagram modeling, geochemistry, zircons/monazite dating, and numerical modeling; (2) the emplacement mechanisms of ultramafic and granulitic rocks by proposing a new hypothesis of very rapid exhumation of the mantle material. This rapid ascent is currently being constrained/tested by combining geobarometric calculations and high precision U-Pb zircon geochronology on

  6. Moho vs crust-mantle boundary: Evolution of an idea

    NASA Astrophysics Data System (ADS)

    O'Reilly, Suzanne Y.; Griffin, W. L.

    2013-12-01

    The concept that the Mohorovicic Discontinuity (Moho) does not necessarily coincide with the base of the continental crust as defined by rock-type compositions was introduced in the early 1980s. This had an important impact on understanding the nature of the crust-mantle boundary using information from seismology and from deep-seated samples brought to the surface as xenoliths in magmas, or as tectonic terranes. The use of empirically-constrained P-T estimates to plot the locus of temperature vs depth for xenoliths defined a variety of geotherms depending on tectonic environment. The xenolith geotherms provided a framework for constructing lithological sections through the deep lithosphere, and revealed that the crust-mantle boundary in off-craton regions commonly is transitional over a depth range of about 5-20 km. Early seismic-reflection data showed common layering near the Moho, correlating with the petrological observation of multiple episodes of basaltic intrusion around the crust-mantle boundary. Developments in seismology, petrophysics and experimental petrology have refined interpretation of lithospheric domains. The expansion of in situ geochronology (especially zircon U-Pb ages and Hf-isotopes; Os isotopes of mantle sulfides) has defined tectonic events that affected whole crust-mantle sections, and revealed that the crust-mantle boundary can change in depth through time. However, the nature of the crust-mantle boundary in cratonic regions remains enigmatic, mainly due to lack of key xenoliths or exposed sections. The observation that the Moho may lie significantly deeper than the crust-mantle boundary has important implications for modeling the volume of the crust. Mapping the crust using seismic techniques alone, without consideration of the petrological problems, may lead to an overestimation of crustal thickness by 15-30%. This will propagate to large uncertainties in the calculation of elemental mass balances relevant to crust-formation processes

  7. Nitrogen Recycling in the Atmosphere - Crust - Mantle Systems: Evidence From Secular Variation of Crustal N Abundances and δ 15N Values, Archean to Present

    NASA Astrophysics Data System (ADS)

    Jia, Y.; Kerrich, R.

    2001-12-01

    The origin and evolution of nitrogen in the Earth's major reservoirs of atmosphere, crust, and mantle is controversial. The initial mantle acquired a δ 15N of -m 25‰ corresponding to enstatite chondrite as found in rare diamonds, and the secondary atmosphere from late accretion of volatile-rich C1 carbonaceous chondrites was +30 to +43‰ . Most diamonds and mid-ocean ridge basalts (MORBs) are -m 5‰ , and the present atmosphere 0‰ , requiring shifts of +20‰ and -m 30 to -m 43‰ in these two reservoirs. The present mass of N in the mantle and atmosphere are estimated at 3.5 x 1019 kg and 3.8 x 1018 kg, respectively. Initial atmospheric δ 15N could have been shifted to lower values by degassing of 15N depleted N from the mantle. However, the mantle would remain more depleted than is observed. The crustal record shows that shifts of both atmosphere and mantle could have occurred by recycling. Sedimentary rocks, and crustal hydrothermal systems that proxy for bulk crust, both show systematic trends over 2.7 Ga from the Archean (δ 15N = 15.0 +/- 1.8‰ ; 16.5 +/- 3.3‰ ); through Paleoproterozoic (δ 15N = 9.7 +/- 1.0‰ ; 9.5 +/- 2.4‰ ); to the Phanerozoic (δ 15N = 3.5 +/- 1.0‰ ; 3.0 +/- 1.2‰ ). Crustal N content has increased in parallel from 84 +/- 67 ppm, through 266 +/- 195 ppm, to 1550 +/- 1135 ppm in the Phanerozoic. These trends are consistent with progressive sequestering of atmospheric N2 into sediments, recycling of 15N enriched continental crust into the mantle, and degassing of 15N depleted from the mantle N into the atmosphere.

  8. Crust-mantle evolution in active arcs

    NASA Astrophysics Data System (ADS)

    Dimalanta, Carla B.; Hsu, Shu-Kun; Shyu, J. Bruce H.; Faustino-Eslava, Decibel V.

    2017-07-01

    The East-Southeast Asia has been regarded as one of the most tectonically complex regions in the world. It is essentially located at junctions between major plate systems, including the Sundaland, the Philippine Sea Plate and the Indo-Australian Plate. The region, thus, presents a very challenging laboratory for understanding the many operative processes that have shaped and continue to shape it. By integrating researches involving geological, structural, paleontological, geochemical, geochronological and geophysical interests on the Philippines and the region, fresh insights are produced that help better explain its geodynamic history. The integration of these different methods advance our understanding on the timing, causes and environmental impacts of tectonic processes, such as the generation of oceanic crust, ophiolite emplacement, magmatism, deposition of sediments, mineralization, earthquake and faulting.

  9. Hydrothermal experiments on serpentinization at crust/mantle boundary

    NASA Astrophysics Data System (ADS)

    Oyanagi, R.; Okamoto, A.; Tsuchiya, N.

    2013-12-01

    Serpentinization commonly proceeds in seafloor hydrothermal systems at mid-ocean ridges, along the bending faults, and at the boundary of wedge mantle and subducting plate. Silica activity are key factors in controlling reaction paths and the rate of serpentinization (e.g., Frost and Beard, 2007; Klein et al., 2009; Ogasawara et al.,2013). However, most of the previous experimental studies focused on bulk solid materials and solutions within the reaction vessel, and local changes of products reaction rate in response to concentration gradient have not been clarified. Ogasawara et al. (2013) conducted hydrothermal experiments in Ol-Opx-H2O system, and modeled the progress of serpentinization by coupled reactions and silica diffusion. In their experiment, reaction product is only serpentine and no talc or brucite were found. In this study, we conducted hydrothermal experiments in olivine (Ol)-quartz (Qtz)-H2O and Ol-plagioclase (Pl)-H2O systems as the analogue of crust/mantle boundary. The condition was 250 degreeC and at a vapor-saturated pressure. Composite powders (composed of Qtz/Ol zone, or Pl/Ol zone) were set in tube-in-tube vessels, and then loaded into autocrave with fluid ( NaOHaq, pH = 13.8 at 25 degreeC ). Runnig time is up to 25 days and maximum water content in the products is 12 wt% H2O. After the experiments, solution chemistry and the extent of serpentinization were analyzed in detail. In the Ol-Qtz-H2O experiments, we observed systematic changes of reaction products in the Ol zone. Smectite and serpentine was formed at Ol-Qtz boundary due to high Na concentration although talc is expected to form in MgO-SiO2-H2O system at Ol-Qtz boundary. Mg/Si ratio of products from EDS analyze shows high Si gradient near the boundary indicate that amount of smectite decreased with increasing distance from the Ol-Qtz boundary and only serpentine zone was observed at ~10mm. At >10mm away from Ol-Qtz boundary, serpentine ( chrysotile nano tubes) and brucite was

  10. What Hf isotopes in zircon tell us about crust-mantle evolution

    NASA Astrophysics Data System (ADS)

    Iizuka, Tsuyoshi; Yamaguchi, Takao; Itano, Keita; Hibiya, Yuki; Suzuki, Kazue

    2017-03-01

    The 176Lu-176Hf radioactive decay system has been widely used to study planetary crust-mantle differentiation. Of considerable utility in this regard is zircon, a resistant mineral that can be precisely dated by the U-Pb chronometer and record its initial Hf isotope composition due to having low Lu/Hf. Here we review zircon U-Pb age and Hf isotopic data mainly obtained over the last two decades and discuss their contributions to our current understanding of crust-mantle evolution, with emphasis on the Lu-Hf isotope composition of the bulk silicate Earth (BSE), early differentiation of the silicate Earth, and the evolution of the continental crust over geologic history. Meteorite zircon encapsulates the most primitive Hf isotope composition of our solar system, which was used to identify chondritic meteorites best representative of the BSE (176Hf/177Hf = 0.282793 ± 0.000011; 176Lu/177Hf = 0.0338 ± 0.0001). Hadean-Eoarchean detrital zircons yield highly unradiogenic Hf isotope compositions relative to the BSE, providing evidence for the development of a geochemically enriched silicate reservoir as early as 4.5 Ga. By combining the Hf and O isotope systematics, we propose that the early enriched silicate reservoir has resided at depth within the Earth rather than near the surface and may represent a fractionated residuum of a magma ocean underlying the proto-crust, like urKREEP beneath the anorthositic crust on the Moon. Detrital zircons from world major rivers potentially provide the most robust Hf isotope record of the preserved granitoid crust on a continental scale, whereas mafic rocks with various emplacement ages offer an opportunity to trace the Hf isotope evolution of juvenile continental crust (from εHf[4.5 Ga] = 0 to εHf[present] = + 13). The river zircon data as compared to the juvenile crust composition highlight that the supercontinent cycle has controlled the evolution of the continental crust by regulating the rates of crustal generation and intra

  11. Crust-mantle mechanical coupling in Eastern Mediterranean and Eastern Turkey

    PubMed Central

    Sinan Özeren, M.

    2012-01-01

    Present-day crust-mantle coupling in the Eastern Mediterranean and eastern Turkey is studied using the Global Positioning System (GPS) and seismic anisotropy data. The general trend of the shear wave fast-splitting directions in NE Turkey and Lesser Caucaus align well with the geodetic velocities in an absolute plate motion frame of reference pointing to an effective coupling in this part of the region of weak surface deformation. Farther south, underneath the Bitlis Suture, however, there are significant Pn delays with E-W anisotropy axes indicating significant lateral escape. Meanwhile, the GPS reveals very little surface deformation. This mismatch possibly suggests a decoupling along the suture. In the Aegean, the shear wave anisotropy and the Pn anisotropy directions agree with the extensional component of the right-lateral shear strains except under the Crete Basin and other parts of the southern Aegean Sea. This extensional direction matches perfectly also with the southward pulling force vectors across the Hellenic trench; however, the maximum right-lateral shear directions obtained from the GPS data in the Aegean do not match either of these anisotropies. Seismic anisotropy from Rayleigh waves sampled at 15 s, corresponding to the lower crust, match the maximum right-lateral maximum shear directions from the GPS indicating decoupling between the crust and the mantle. This decoupling most likely results from the lateral variations of the gravitational potential energies and the slab-pull forces. PMID:22592788

  12. Crust-mantle mechanical coupling in Eastern Mediterranean and eastern Turkey.

    PubMed

    Özeren, M Sinan

    2012-05-29

    Present-day crust-mantle coupling in the Eastern Mediterranean and eastern Turkey is studied using the Global Positioning System (GPS) and seismic anisotropy data. The general trend of the shear wave fast-splitting directions in NE Turkey and Lesser Caucaus align well with the geodetic velocities in an absolute plate motion frame of reference pointing to an effective coupling in this part of the region of weak surface deformation. Farther south, underneath the Bitlis Suture, however, there are significant Pn delays with E-W anisotropy axes indicating significant lateral escape. Meanwhile, the GPS reveals very little surface deformation. This mismatch possibly suggests a decoupling along the suture. In the Aegean, the shear wave anisotropy and the Pn anisotropy directions agree with the extensional component of the right-lateral shear strains except under the Crete Basin and other parts of the southern Aegean Sea. This extensional direction matches perfectly also with the southward pulling force vectors across the Hellenic trench; however, the maximum right-lateral shear directions obtained from the GPS data in the Aegean do not match either of these anisotropies. Seismic anisotropy from Rayleigh waves sampled at 15 s, corresponding to the lower crust, match the maximum right-lateral maximum shear directions from the GPS indicating decoupling between the crust and the mantle. This decoupling most likely results from the lateral variations of the gravitational potential energies and the slab-pull forces.

  13. The Crust Mantle Transition Beneath the Variscan Domain of the Iberian Peninsula

    NASA Astrophysics Data System (ADS)

    Carbonell, R.; Díaz, J.; Brown, D.; Palomeras, I.; Martí, D.; Ayarza, P.; Afonso, J.; Simancas, F.; Perez-Estaun, A.; Gallart, J.

    2009-12-01

    The Mohorovičić discontinuity (Moho) was defined by Andrija Mohorovičić in 1910 on the basis of an interpretation of regional earthquake records in Eastern Europe as a relatively abrupt increase in P-wave seismic velocities. The Moho is observed/detected world wide. It is the most important boundary within the Earth's lithosphere. The high resolution subsurface geophysical images have demonstrated that the crust-mantle boundary is a far more complex structure that the initial seismological definition established. The purpose of this contribution is to bring together some of the findings related to the crust-mantle transition beneath the Iberian peninsula and to synthesize these results into a perspective that has global implications. For the last three decades an extensive acquisition of varieties of geophysical and geological data has been carried out. These data include controlled-source seismic (refraction and reflection), natural source seismic, and regional geology. In NW Iberia an analog of the continental crust-mantle transition is exposed within the Paleozoic Cabo Ortegal Complex and can be used for comparison and model building. This provides a unique view into the nature of the crust-mantle transition. From the multi-seismic data the character of the Moho is highly variable, in some areas there are no reflections visible in the normal incidence (e.g. ESCI-BETICS-1), in others reflections are prominent single events (e.g. IBERSEIS) and in still others complex geometric features are observed (ESCI-NORTE). There are also time (depth) differences between the wide-angle and the normal incidence seismic Moho's. Laboratory measurements of P- and S-wave velocities reflect an overall increase from middle to lower crustal velocities in the felsic gneisses and intermediate-to-mafic granulites to mantle velocities in the eclogites and ultramafic rocks. The surface outcrops of Cabo Ortegal complex suggests that the seismic Moho is reached at the contact between

  14. Mapping the crust/mantle boundary with the Moon Mineralogy Mapper instrument data

    NASA Astrophysics Data System (ADS)

    Martinot, M.; Besse, S.; Flahaut, J.; Blanchette-Guertin, J.-F.; Isaacson, P.; van Westrenen, W.

    2015-10-01

    Determining the composition and structure of the lunar crust is crucial to study its origin and evolution[5]. Several space missions were sent to the Moon in order to study its gravity field, which can be used to derive information about its crustal thickness [9]. Results from the Clementine mission (1990s) suggested a lunar crustal thickness varying between 20 and 120 km[6], and enabled studies of the mineralogy of the lunar crust [8]. From September 2011 to December 2012, the Gravity Recovery and Interior Laboratory (GRAIL) mission acquired more precise gravimetric data from the Moon. GRAIL data suggest a significantly smaller average lunar crustal thickness between 34 and 43 km depending on the model considered [9].This survey aims to study the crust/mantle boundary region, and evaluate the lunar crustal thickness using impact craters as natural drill holes. To this end, the proximity to the mantle was calculated for all craters in the lunar crater database, using the method described in [4]. Craters that fall within a specific proximity range, diagnostic of the crust/mantle boundary region, and with preserved central peaks are selected for further investigations. The mineralogy of the selected craters central peaks is derived from the Moon Mineralogy Mapper (M3) data [7] to evaluate the presence or absence of mantle material. One ultimate goal is to place constraints on the crust/mantle boundary depth and mineralogy, and assess which GRAIL model(s)best describe the Moon crust.

  15. Ca isotope fingerprints of early crust-mantle evolution

    NASA Astrophysics Data System (ADS)

    Kreissig, K.; Elliott, T.

    2005-01-01

    isotope ratios in some mafic samples reflect anomalous K/Ca ratios as a result of intense K-metasomatism ˜3.6 Ga. Thus Ca isotope measurements are not a robust tracer of crustal growth in the presence of intense tectono-metamorphic processes. Coupled with other isotope data, however, the degree of overprint can be estimated and the 40Ca/ 44Ca ratio of a little disturbed sample hints at a small contribution of Hadean protocrust in the coastal part of the Godthåbsfjord area (Southwest Greenland). In the majority of Zimbabwe TTG samples, unradiogenic initial Ca isotope ratios point to very little prior crustal history and minor subsequent disturbance. We thus infer that the modest initial ɛ Nd ˜0.8 of the Zimbabwean samples is representative of the depleted mantle at ˜3.6 Ga. Furthermore, Ca isotope systematics provide little support for a "steady state" model of crustal growth.

  16. Modeling crust-mantle evolution using radiogenic Sr, Nd, and Pb isotope systematics

    NASA Astrophysics Data System (ADS)

    Kumari, Seema; Paul, Debajyoti

    2015-04-01

    The present-day elemental and isotopic composition of Earth's terrestrial reservoirs can be used as geochemical constraints to study evolution of the crust-mantle system. A flexible open system evolutionary model of the Earth, comprising continental crust (CC), upper depleted mantle (UM) -source of mid-ocean ridge basalts (MORB), and lower mantle (LM) reservoir with a D" layer -source of ocean island basalts (OIB), and incorporating key radioactive isotope systematics (Rb-Sr, Sm-Nd, and U-Th-Pb), is solved numerically at 1 Ma time step for 4.55 Ga, the age of the Earth. The best possible solution is the one that produces the present-day concentrations as well as isotopic ratios in terrestrial reservoirs, compiled from published data. Different crustal growth scenarios (exponential, episodic, early and late growth), proposed in earlier studies, and its effect on the evolution of isotope systematics of terrestrial reservoirs is studied. Model simulations strongly favor a layered mantle structure satisfying majority of the isotopic constraints. In the successful model, which is similar to that proposed by Kellogg et al. (1999), the present-day UM comprises of 60% of mantle mass and extends to a depth 1600 km, whereas the LM becomes non-primitive and more enriched than the bulk silicate Earth, mainly due to addition of recycled crustal material. Modeling suggest that isotopic evolution of reservoirs is affected by the mode of crustal growth. Only two scenarios satisfied majority of the Rb-Sr and Sm-Nd isotopic constraints but failed to reproduce the present-day Pb-isotope systematics; exponential growth of crust (mean age, tc=2.3 Ga) and delayed and episodic growth (no growth for initial 900 Ma, tc=2.05 Ga) proposed by Patchett and Arndt (1986). However, assuming a slightly young Earth (4.45 Ga) better satisfies the Pb-isotope systematics. Although, the delayed crustal growth model satisfied Sr-Nd isotopic constraints, presence of early Hadean crust (4.03 and 4.4 Ga

  17. Constrained potential field modeling of the crustal architecture of the Musgrave Province in central Australia: Evidence for lithospheric strengthening due to crust-mantle boundary uplift

    NASA Astrophysics Data System (ADS)

    Aitken, Alan R. A.; Betts, Peter G.; Weinberg, Roberto F.; Gray, Daniel

    2009-12-01

    We image the crustal architecture of the Musgrave Province with petrophysically constrained forward models of new potential field data. These models image divergent shallow-dipping crustal scale thrusts that, at depth, link with an axial zone defined by steeper, lithospheric scale transpressional shear zones. They also show that to permit a near-surface density distribution that is consistent with petrophysical and geological observations, approximately 15-20 km of crust-mantle boundary uplift is necessary beneath the axial zone. The long-term preservation of this crust-mantle boundary offset implies a change from relatively weak lithosphere to relatively strong lithosphere during the intraplate Petermann Orogeny. To explain this, we propose a model in which uplift of the axial zone of the orogen leads to local lithospheric strengthening as a result of the uplift of mantle rocks into the lower crust, coupled with long-term lithospheric cooling due to the erosion of a radioactive upper crust. Brace-Goetze lithospheric strength models suggest that these processes may have increased the integrated strength of the lithosphere by a factor of 1.4-2.8. Because of this strengthening, this system is self-limiting, and activity will cease when lithospheric strength is sufficient to resist external forces and support isostatic imbalances. A simple force-balance model demonstrates that the force required to uplift the axial zone is tectonically reasonable and that the system can subsequently withstand significant tensional forces. This example shows that crust-mantle boundary uplift coupled with reduced crustal heat production can profoundly affect the long-term strength of the continental lithosphere and may be a critical process in the tectonic stabilization of intraplate regions.

  18. Compositional variations in spinel-hosted pargasite inclusions in the olivine-rich rock from the oceanic crust-mantle boundary zone

    NASA Astrophysics Data System (ADS)

    Tamura, Akihiro; Morishita, Tomoaki; Ishimaru, Satoko; Hara, Kaori; Sanfilippo, Alessio; Arai, Shoji

    2016-05-01

    The crust-mantle boundary zone of the oceanic lithosphere is composed mainly of olivine-rich rocks represented by dunite and troctolite. However, we still do not fully understand the global variations in the boundary zone, and an effective classification of the boundary rocks, in terms of their petrographical features and origin, is an essential step in achieving such an understanding. In this paper, to highlight variations in olivine-rich rocks from the crust-mantle boundary, we describe the compositional variations in spinel-hosted hydrous silicate mineral inclusions in rock samples from the ocean floor near a mid-ocean ridge and trench. Pargasite is the dominant mineral among the inclusions, and all of them are exceptionally rich in incompatible elements. The host spinel grains are considered to be products of melt-peridotite reactions, because their origin cannot be ascribed to simple fractional crystallization of a melt. Trace-element compositions of pargasite inclusions are characteristically different between olivine-rich rock samples, in terms of the degree of Eu and Zr anomalies in the trace-element pattern. When considering the nature of the reaction that produced the inclusion-hosting spinel, the compositional differences between samples were found to reflect a diversity in the origin of the olivine-rich rocks, as for example in whether or not a reaction was accompanied by the fractional crystallization of plagioclase. The differences also reflect the fact that the melt flow system (porous or focused flow) controlled the melt/rock ratios during reaction. The pargasite inclusions provide useful data for constraining the history and origin of the olivine-rich rocks and therefore assist in our understanding of the crust-mantle boundary of the oceanic lithosphere.

  19. A deep crust-mantle boundary in the asteroid 4 Vesta.

    PubMed

    Clenet, Harold; Jutzi, Martin; Barrat, Jean-Alix; Asphaug, Erik I; Benz, Willy; Gillet, Philippe

    2014-07-17

    The asteroid 4 Vesta was recently found to have two large impact craters near its south pole, exposing subsurface material. Modelling suggested that surface material in the northern hemisphere of Vesta came from a depth of about 20 kilometres, whereas the exposed southern material comes from a depth of 60 to 100 kilometres. Large amounts of olivine from the mantle were not seen, suggesting that the outer 100 kilometres or so is mainly igneous crust. Here we analyse the data on Vesta and conclude that the crust-mantle boundary (or Moho) is deeper than 80 kilometres.

  20. Postcollisional mafic igneous rocks record crust-mantle interaction during continental deep subduction

    PubMed Central

    Zhao, Zi-Fu; Dai, Li-Qun; Zheng, Yong-Fei

    2013-01-01

    Findings of coesite and microdiamond in metamorphic rocks of supracrustal protolith led to the recognition of continental subduction to mantle depths. The crust-mantle interaction is expected to take place during subduction of the continental crust beneath the subcontinental lithospheric mantle wedge. This is recorded by postcollisional mafic igneous rocks in the Dabie-Sulu orogenic belt and its adjacent continental margin in the North China Block. These rocks exhibit the geochemical inheritance of whole-rock trace elements and Sr-Nd-Pb isotopes as well as zircon U-Pb ages and Hf-O isotopes from felsic melts derived from the subducted continental crust. Reaction of such melts with the overlying wedge peridotite would transfer the crustal signatures to the mantle sources for postcollisional mafic magmatism. Therefore, postcollisonal mafic igneous rocks above continental subduction zones are an analog to arc volcanics above oceanic subduction zones, providing an additional laboratory for the study of crust-mantle interaction at convergent plate margins. PMID:24301173

  1. Postcollisional mafic igneous rocks record crust-mantle interaction during continental deep subduction.

    PubMed

    Zhao, Zi-Fu; Dai, Li-Qun; Zheng, Yong-Fei

    2013-12-04

    Findings of coesite and microdiamond in metamorphic rocks of supracrustal protolith led to the recognition of continental subduction to mantle depths. The crust-mantle interaction is expected to take place during subduction of the continental crust beneath the subcontinental lithospheric mantle wedge. This is recorded by postcollisional mafic igneous rocks in the Dabie-Sulu orogenic belt and its adjacent continental margin in the North China Block. These rocks exhibit the geochemical inheritance of whole-rock trace elements and Sr-Nd-Pb isotopes as well as zircon U-Pb ages and Hf-O isotopes from felsic melts derived from the subducted continental crust. Reaction of such melts with the overlying wedge peridotite would transfer the crustal signatures to the mantle sources for postcollisional mafic magmatism. Therefore, postcollisonal mafic igneous rocks above continental subduction zones are an analog to arc volcanics above oceanic subduction zones, providing an additional laboratory for the study of crust-mantle interaction at convergent plate margins.

  2. Extension velocity partitioning, rheological crust-mantle and intra-crustal decoupling and tectonically inherited structures: consequences for continental rifting dynamics.

    NASA Astrophysics Data System (ADS)

    Wang, Kun; Mezri, Leila; Burov, Evgueni; Le Pourhiet, Laetitia

    2015-04-01

    We implemented series of systematic thermo-mechanical numerical models testing the importance of the rheological structure and extension rate partitioning for continental rift evolution. It is generally assumed that styles of continental rifting are mainly conditioned by the initial integrated strength of the lithosphere. For example, strong plates are expected to undergo extension in narrow rifting mode, while weak lithospheres would stretch in wide rifting mode. However, we show that this classification is largely insufficient because the notion of the integrated strength ignores the internal rheological structure of the lithosphere that may include several zones of crust-mantle or upper-crust-intermediate (etc) crust decoupling. As well, orogenic crusts characterizing most common sites of continental extension may exhibit inverted lithological sequences, with stronger and denser formerly lower crustal units on top of weaker and lighter upper crustal units. This all may result in the appearance of sharp rheological strength gradients and presence of decoupling zones, which may lead to substantially different evolution of the rift system. Indeed, strong jump-like contrasts in the mechanical properties result in mechanical instabilities while mechanical decoupling between the competent layers results in overall drop of the flexural strength of the system and may also lead to important horizontal flow of the ductile material. In particular, the commonly inferred concept of level of necking (that assumes the existence of a stationary horizontal stretching level during rifting) looses its sense if necking occurs at several distinct levels. In this case, due to different mechanical strength of the rheological layers, several necking levels develop and switch from one depth to another resulting in step-like variations of rifting style and accelerations/decelerations of subsidence during the active phase of rifting. During the post-rifting phase, initially decoupled

  3. Competitive hydration and dehydration at olivine-quartz boundary revealed by hydrothermal experiments: Implications for silica metasomatism at the crust-mantle boundary

    NASA Astrophysics Data System (ADS)

    Oyanagi, Ryosuke; Okamoto, Atsushi; Hirano, Nobuo; Tsuchiya, Noriyoshi

    2015-09-01

    Serpentinization occurs via interactions between mantle peridotite and water that commonly passes through the crust. Given that such a fluid has a high silica activity compared with mantle peridotite, it is thought that serpentinization and silica metasomatism occur simultaneously at the crust-mantle boundary. In this study, we conducted hydrothermal experiments in the olivine (Ol)-quartz (Qtz)-H2O system at 250 °C and vapor-saturated pressure under highly alkaline conditions (NaOHaq, pH = 13.8 at 25 °C) to clarify the mechanism of silica metasomatism at the crust-mantle boundary. Composite powders consisting of a Qtz layer and an Ol layer were set in tube-in-tube vessels. After the experiments, the extents of serpentinization and metasomatic reactions were evaluated as a function of distance from the Ol-Qtz boundary. The mineralogy of the reaction products in the Ol-hosted region changed with increasing distance from the Ol-Qtz boundary, from smectite + serpentine (Smc zone) to serpentine + brucite + magnetite (Brc zone). Olivine hydration proceeded in both zones, but the total H2O content in the products was greater in the Brc zone than in the Smc zone. Mass balance calculations revealed that olivine hydration occurred without any supply of silica in the brucite zone. In contrast, the Smc zone was formed by silica metasomatism via competitive hydration and dehydration reactions. In the Smc zone, smectite formed via the simultaneous progress of olivine hydration and serpentine dehydration, and around the boundary of the Smc and Brc zones, serpentine formation occurred by olivine hydration and brucite dehydration. The relative extent of hydration and dehydration reactions controlled the along-tube variation in the rate of H2O production/consumption and the rate of volume increase. Our findings suggest that the competitive progress of serpentinization and silica metasomatic reactions would cause fluctuations in pore fluid pressure, possibly affecting the

  4. The Moho as a magnetic boundary. [Earth crust-mantle boundary

    NASA Technical Reports Server (NTRS)

    Wasilewski, P. J.; Thomas, H. H.; Mayhew, M. A.

    1979-01-01

    Magnetism in the crust and the upper mantle and magnetic results indicating that the seismic Moho is a magnetic boundary are considered. Mantle derived rocks - peridotites from St. Pauls rocks, dunite xenoliths from the Kaupulehu flow, and peridotite, dunite, and eclogite xenoliths from Roberts Victor and San Carlos diatremes - are weakly magnetic with saturation magnetization values from 0.013 emu/gm to less than 0.001 emu/gm which is equivalent to 0.01 to 0.001 wt% Fe304. Literature on the minerals in mantle xenoliths shows that metals and primary Fe304 are absent, and that complex Cr, Mg, Al, and Fe spinels are dominant. These spinels are non-magnetic at mantle temperatures, and the crust/mantle boundary can be specified as a magnetic mineralogy discontinuity. The new magnetic results indicate that the seismic Moho is a magnetic boundary, the source of magnetization is in the crust, and the maximum Curie isotherm depends on magnetic mineralogy and is located at depths which vary with the regional geothermal gradient.

  5. Crustal thickness controlled by plate tectonics: A review of crust-mantle interaction processes illustrated by European examples

    NASA Astrophysics Data System (ADS)

    Artemieva, Irina M.; Meissner, Rolf

    2012-03-01

    The continental crust on Earth cannot be extracted directly from the mantle, and the primary crust extracted directly from an early magma ocean is not preserved on Earth. We review geophysical and geochemical aspects of global crust-mantle material exchange processes and examine the processes which, on one side, form and transform the continental crust and, on the other side, chemically modify the mantle residue from which the continental crust has been extracted. Major mechanisms that provide crust-mantle material exchange are oceanic and continental subduction, lithosphere delamination, and mafic magmatism. While both subduction and delamination recycle crustal material into the mantle, mafic magmatism transports mantle material upward and participates in growth of new oceanic and continental crusts and significant structural and chemical modification of the latter. We discuss the role of basalt/gabbro-eclogite phase transition in crustal evolution and the links between lithosphere recycling, mafic magmatism, and crustal underplating. We advocate that plate tectonics processes, together with basalt/gabbro-eclogite transition, limit crustal thickness worldwide by providing effective mechanisms of crustal (lithosphere) recycling. The processes of crust-mantle interaction have created very dissimilar crustal styles in Europe, as seen by its seismic structure, crustal thickness, and average seismic velocities in the basement. Our special focus is on processes responsible for the formation of the thin crust of central and western Europe, which was largely formed during the Variscan (430-280 Ma) orogeny but has the present structure of an “extended” crust, similar to that of the Basin and Range province in western USA. Major geophysical characteristics of the Variscan lithosphere are discussed within the frame of possible sequences of crust-mantle material exchange mechanisms during and after main orogenic events in the European Variscides.

  6. Geothermal profile and crust-mantle transition beneath east-central Queensland: Volcanology, xenolith petrology and seismic data

    NASA Astrophysics Data System (ADS)

    Griffin, W. L.; Sutherland, F. L.; Hollis, J. D.

    1987-04-01

    Geothermobarometry of garnet granulite and garnet websterite xenoliths in basalts from numerous localities in east-central Queensland gives P-T points that fall along the geotherm previously defined for southeastern Australia. This elevated geotherm is ascribed to the advective transport of heat by Tertiary-Recent magmas ponded at the crust-mantle boundary. The lower crust in this region consists dominantly of mafic granulites, representing frozen basaltic melts and cumulates. Spinel lherzolite becomes a dominant rock type at depths of ca. 30 km, and persists, interlayered with pyroxenites, to depths of ca. 55 km. Seismic reflection profiles show a "layered lower crust" between depths of 20 and 36 km depth. The lithologically defined crust-mantle boundary lies within this zone, at least 6 km above the seismically defined Moho. This interpretation is consistent with the observed velocity ( Vp) gradient downward through the layered zone. The constructed geotherm implies that the bottom of the lithosphere beneath eastern Australia is shallower than ca. 100 km. This makes it unlikely that the diamonds of eastern Australia are derived from local intrusions, unless these are > 200 Ma old.

  7. The world turns over: Hadean-Archean crust-mantle evolution

    NASA Astrophysics Data System (ADS)

    Griffin, W. L.; Belousova, E. A.; O'Neill, C.; O'Reilly, Suzanne Y.; Malkovets, V.; Pearson, N. J.; Spetsius, S.; Wilde, S. A.

    2014-02-01

    We integrate an updated worldwide compilation of U/Pb, Hf-isotope and trace-element data on zircon, and Re-Os model ages on sulfides and alloys in mantle-derived rocks and xenocrysts, to examine patterns of crustal evolution and crust-mantle interaction from 4.5 Ga to 2.4 Ga ago. The data suggest that during the period from 4.5 Ga to ca 3.4 Ga, Earth's crust was essentially stagnant and dominantly mafic in composition. Zircon crystallized mainly from intermediate melts, probably generated both by magmatic differentiation and by impact melting. This quiescent state was broken by pulses of juvenile magmatic activity at ca 4.2 Ga, 3.8 Ga and 3.3-3.4 Ga, which may represent mantle overturns or plume episodes. Between these pulses, there is evidence of reworking and resetting of U-Pb ages (by impact?) but no further generation of new juvenile crust. There is no evidence of plate-tectonic activity, as described for the Phanerozoic Earth, before ca 3.4 Ga, and previous modelling studies indicate that the early Earth may have been characterised by an episodic-overturn, or even stagnant-lid, regime. New thermodynamic modelling confirms that an initially hot Earth could have a stagnant lid for ca 300 Ma, and then would experience a series of massive overturns at intervals on the order of 150 Ma until the end of the EoArchean. The subcontinental lithospheric mantle (SCLM) sampled on Earth today did not exist before ca 3.5 Ga. A lull in crustal production around 3.0 Ga coincides with the rapid buildup of a highly depleted, buoyant SCLM, which peaked around 2.7-2.8 Ga; this pattern is consistent with one or more major mantle overturns. The generation of continental crust peaked later in two main pulses at ca 2.75 Ga and 2.5 Ga; the latter episode was larger and had a greater juvenile component. The age/Hf-isotope patterns of the crust generated from 3.0 to 2.4 Ga are similar to those in the internal orogens of the Gondwana supercontinent, and imply the existence of plate

  8. Three-dimensional interface modelling with two-dimensional seismic data: the Alpine crust-mantle boundary

    USGS Publications Warehouse

    Waldhauser, F.; Kissling, E.; Ansorge, J.; Mueller, St.

    1998-01-01

    We present a new approach to determine the 3-D topography and lateral continuity of seismic interfaces using 2-D-derived controlled-source seismic reflector data. The aim of the approach is to give the simplest possible structure consistent with all reflector data and error estimates. We define simplicity of seismic intrafaces by the degree of interface continuity (ie shortest length of offsets) and by the degree of interface roughness (least surface roughness). The method is applied to structural information of the crust-mantle boundary (Moho) obtained from over 250 controlled-source seismic reflection and refraction profiles in the greater Alpine region. The reflected and refracted phases from the Moho interface and their interpretation regarding crustal thickness are reviewed and their reliability weighted. Weights assigned to each reflector element are transformed to depth errors considering Fresnel volumes. The 2-D-derived reflector elements are relocated in space (3-D migration) and interpolation is performed between the observed reflector elements to obtain continuity of model parameters. Interface offsets are intoduced only where required according to the prinipal of simplicity. The resulting 3-D model of the ALpine crust-mantle boundary shows two offsets that eivide the interface into a European, an Adriatic and a Ligurian Moho, with the European Moho subducting below the Adriatic Moho, and with the Adriatic Moho underthrusting the Ligurian Moho. Each sub-interface depicts the smoothest possible (ie simplest) surface, fitting the reflector data within their assigned errors. The results are consistent with previous studies for those regions with dense and reliable controlled-source seismic data. The newly derived Alpine Moho interface, however, surpasses earlier studies by its lateral extent over an area of about 600km by 600km, by quantifying reliability estimates along the interface, and by obeying the priciple of being consistently as simple as possible.

  9. System Support for Forensic Inference

    NASA Astrophysics Data System (ADS)

    Gehani, Ashish; Kirchner, Florent; Shankar, Natarajan

    Digital evidence is playing an increasingly important role in prosecuting crimes. The reasons are manifold: financially lucrative targets are now connected online, systems are so complex that vulnerabilities abound and strong digital identities are being adopted, making audit trails more useful. If the discoveries of forensic analysts are to hold up to scrutiny in court, they must meet the standard for scientific evidence. Software systems are currently developed without consideration of this fact. This paper argues for the development of a formal framework for constructing “digital artifacts” that can serve as proxies for physical evidence; a system so imbued would facilitate sound digital forensic inference. A case study involving a filesystem augmentation that provides transparent support for forensic inference is described.

  10. The lithosphere-asthenosphere and crust-mantle boundaries in the region of the Upper Rhine Graben as seen by S-wave receiver functions

    NASA Astrophysics Data System (ADS)

    Ritter, J. R. R.; Seiberlich, C.; Wawerzinek, B.

    2012-04-01

    The Upper Rhine Graben is a branch of the European Cenozoic Rift System and is characterised by a clear rift structure which stretches more than 300 km from Basel to Frankfurt. Since 2004 we study the deep structure of the Upper Rhine Graben within the TIMO project, using the mobile seismic broadband stations of the KArlsruhe BroadBand Array (KABBA). The data are complemented with recordings from permanent stations (BFO, ECH, STU, TNS and WLF). Here we present the results from shear wave receiver function (S-RF) modelling. S-RF are waveforms which should contain only S-to-P converted phases which were generated at seismic discontinuities inside the Earth. The stacked S-RF contain clear signals from the crust-mantle boundary (Moho) under the study region. After a depth migration the Moho topography varies between 25 km and 28 km underneath the Upper Rhine Graben region; within the error limits of 5 km there is no difference between the graben itself and its shoulders. In the southern part of the graben there is an indication for a thinning of the crust to about 23 km. After the Moho signals there is a second phase with opposite polarity in the S-RF. We interpret this signal as conversion from the lithosphere-asthenosphere boundary (LAB). A depth migration results in LAB depths of 70-80 km under the Upper Rhine Graben; the graben itself does not show a specific anomaly. The most shallow LAB depths are found in the region of the Eifel (about 60 km), where a small mantle plume is active.

  11. Inherited structure and coupled crust-mantle lithosphere evolution: Numerical models of Central Australia

    NASA Astrophysics Data System (ADS)

    Heron, Philip J.; Pysklywec, Russell N.

    2016-05-01

    Continents have a rich tectonic history that have left lasting crustal impressions. In analyzing Central Australian intraplate orogenesis, complex continental features make it difficult to identify the controls of inherited structure. Here the tectonics of two types of inherited structures (e.g., a thermally enhanced or a rheologically strengthened region) are compared in numerical simulations of continental compression with and without "glacial buzzsaw" erosion. We find that although both inherited structures produce deformation in the upper crust that is confined to areas where material contrasts, patterns of deformation in the deep lithosphere differ significantly. Furthermore, our models infer that glacial buzzsaw erosion has little impact at depth. This tectonic isolation of the mantle lithosphere from glacial processes may further assist in the identification of a controlling inherited structure in intraplate orogenesis. Our models are interpreted in the context of Central Australian tectonics (specifically the Petermann and Alice Springs orogenies).

  12. Rayleigh-wave dispersion reveals crust-mantle decoupling beneath eastern Tibet

    PubMed Central

    Legendre, Cédric P.; Deschamps, Frédéric; Zhao, Li; Chen, Qi-Fu

    2015-01-01

    The Tibetan Plateau results from the collision of the Indian and Eurasian Plates during the Cenozoic, which produced at least 2,000 km of convergence. Its tectonics is dominated by an eastward extrusion of crustal material that has been explained by models implying either a mechanical decoupling between the crust and the lithosphere, or lithospheric deformation. Discriminating between these end-member models requires constraints on crustal and lithospheric mantle deformations. Distribution of seismic anisotropy may be inferred from the mapping of azimuthal anisotropy of surface waves. Here, we use data from the CNSN to map Rayleigh-wave azimuthal anisotropy in the crust and lithospheric mantle beneath eastern Tibet. Beneath Tibet, the anisotropic patterns at periods sampling the crust support an eastward flow up to 100°E in longitude, and a southward bend between 100°E and 104°E. At longer periods, sampling the lithospheric mantle, the anisotropic structures are consistent with the absolute plate motion. By contrast, in the Sino-Korean and Yangtze cratons, the direction of fast propagation remains unchanged throughout the period range sampling the crust and lithospheric mantle. These observations suggest that the crust and lithospheric mantle are mechanically decoupled beneath eastern Tibet, and coupled beneath the Sino-Korean and Yangtze cratons. PMID:26548657

  13. Rayleigh-wave dispersion reveals crust-mantle decoupling beneath eastern Tibet.

    PubMed

    Legendre, Cédric P; Deschamps, Frédéric; Zhao, Li; Chen, Qi-Fu

    2015-11-09

    The Tibetan Plateau results from the collision of the Indian and Eurasian Plates during the Cenozoic, which produced at least 2,000 km of convergence. Its tectonics is dominated by an eastward extrusion of crustal material that has been explained by models implying either a mechanical decoupling between the crust and the lithosphere, or lithospheric deformation. Discriminating between these end-member models requires constraints on crustal and lithospheric mantle deformations. Distribution of seismic anisotropy may be inferred from the mapping of azimuthal anisotropy of surface waves. Here, we use data from the CNSN to map Rayleigh-wave azimuthal anisotropy in the crust and lithospheric mantle beneath eastern Tibet. Beneath Tibet, the anisotropic patterns at periods sampling the crust support an eastward flow up to 100°E in longitude, and a southward bend between 100°E and 104°E. At longer periods, sampling the lithospheric mantle, the anisotropic structures are consistent with the absolute plate motion. By contrast, in the Sino-Korean and Yangtze cratons, the direction of fast propagation remains unchanged throughout the period range sampling the crust and lithospheric mantle. These observations suggest that the crust and lithospheric mantle are mechanically decoupled beneath eastern Tibet, and coupled beneath the Sino-Korean and Yangtze cratons.

  14. Crust-mantle accommodation of Africa-Eurasia convergence in the NW-Moroccan margin

    NASA Astrophysics Data System (ADS)

    Zlotnik, S.; Jimenez-Munt, I.; Fernandez, M.

    2011-12-01

    Recent studies carried out in NW-Africa indicate prominent variations of the lithosphere-asthenosphere boundary (LAB) depth. The studies combine gravity, geoid, surface heat flow, elevation and seismic data along a profile running from the Tagus Abyssal Plain to the Sahara Platform and crossing the Gorringe Bank, the NW Moroccan Margin and the Atlas Mountains. The resulting mantle density anomalies show a prominent lithospheric mantle thickening beneath the margin (LAB >200 km-depth) followed by thinning beneath the Atlas Mountains (LAB ~90 km-depth). A combination of mantle underthrusting due to oblique convergence together with a viscous dripping fed by lateral mantle dragging can explain the imaged lithospheric structure. The model is consistent with a strong decoupled crustal-mantle mechanical response to the Africa-Eurasia convergence and results in positive/negative dynamic topography in regions with thickened/thinned crust. In this work we go a step further analysing, by means of dynamic numerical simulations, the viscous dragging and the Rayleigh-Taylor-like process. Our goal is to understand the initial lithospheric mantle structure suitable to produce the inferred dynamic process. In addition, we study the key factors controlling the deformation of the lithospheric mantle when submitted to convergence. Using the numerical framework Underworld to carry out the simulations we found the key factors controlling the process. Chief among these factors are lithospheric/mantle viscosity ratio and initial mantle and crustal structure. Nevertheless, the process is not very sensitive to the usual power law parameters for mantle rocks (activation energy and volume, power law exponent, etc.), indicating the importance of the rheology of the upper half of the lithosphere, where the power law is not active. These results allow us to speculate on the past and future evolution of the NW-Moroccan margin which could show the appropriated conditions for subduction initiation.

  15. Decoupled crust-mantle accommodation of Africa-Eurasia convergence in the NW Moroccan margin

    NASA Astrophysics Data System (ADS)

    JiméNez-Munt, I.; Fernã Ndez, M.; VergéS, J.; Garcia-Castellanos, D.; Fullea, J.; PéRez-Gussinyé, M.; Afonso, J. C.

    2011-08-01

    The extent of the area accommodating convergence between the African and Iberian plates, how this convergence is partitioned between crust and mantle, and the role of the plate boundary in accommodating deformation are not well-understood subjects. We calculate the structure of the lithosphere derived from its density distribution along a profile running from the Tagus Abyssal Plain to the Sahara Platform and crossing the Gorringe Bank, the NW Moroccan margin, and the Atlas Mountains. The model is based on the integration of gravity, geoid, elevation, and heat flow data and on the crustal structure across the NW Moroccan margin derived from reflection and wide-angle seismic data. The resulting mantle density anomalies suggest important variations of the lithosphere-asthenosphere boundary (LAB) topography, indicating prominent lithospheric mantle thickening beneath the margin (LAB > 200 km depth) followed by thinning beneath the Atlas Mountains (LAB ˜90 km depth). At crustal levels the Iberia-Africa convergence is sparsely accommodated in a ˜950 km wide area and localized in the Atlas and Gorringe regions, with an inferred shortening of ˜50 km. In contrast, mantle thickening accommodates a 400 km wide region, thus advocating for a decoupled crustal-mantle mechanical response. A combination of mantle underthrusting due to oblique convergence, together with a viscous dripping fed by lateral mantle dragging, can explain the imaged lithospheric structure. The model is consistent with crustal shortening estimates and with the accommodation of part of the Iberia-Africa convergence farther NW of the Gorringe Bank and/or off the strike of the profile.

  16. Feedbacks between deformation and melt distribution in the crust-mantle transition zone of the Oman ophiolite

    NASA Astrophysics Data System (ADS)

    Higgie, Katherine; Tommasi, Andréa

    2012-12-01

    This study presents microstructural evidence for deformation-controlled melt organization and for changes in olivine deformation associated with the presence of melt in an 80 m vertical section of the crust-mantle transition zone in the Oman ophiolite. This zone represents an ‘end member’ case for analyzing feedbacks between deformation and melt distribution in the upper mantle, since it experienced strong shear strains in presence of large melt fractions. It is characterized by a subhorizontal compositional layering at the mm to meter scale, from weakly impregnated dunites to olivine-rich gabbros, which parallels a pervasive foliation containing a strong stretching lineation. The parallelism between the compositional layering and the foliation, the diffuse limits of the layers, the alignment of elongated plagioclase-rich aggregates devoid of internal deformation structures with the elongation of olivine crystals in the dunitic layers, and the sharp compositional changes across some, but not all layer limits suggest deformation plays an essential role on the development of the layering. The variation on a mm-scale of the olivine crystal preferred orientation (CPO) symmetry as a function of the modal content: from axial-[100] symmetry in layers with <70% modal olivine to axial-[010] in more gabbroic levels (<40% olivine), which is repeated over the entire section, implies deformation in presence of variable melt fractions. Axial-[100] olivine CPO in olivine-rich layers is consistent with deformation by dislocation creep under high temperature, low pressure, dry conditions. Axial-[010] olivine CPO patterns imply additional sliding along preferentially wetted (010) grain boundaries, increase in the activity of [001] glide, or transpression localized in the melt-rich layers. Since the change in CPO symmetry is not accompanied by dispersion, instantaneous melt fractions must have remained <30-40% in all layers. The continuous variation in olivine CPO symmetry with

  17. Mafic inclusions in Yosemite granites and Lassen Pk lavas: records of complex crust-mantle interactions

    SciTech Connect

    Reid, J.B. Jr.; Flinn, J.E.

    1985-01-01

    This study compares three small-scale magmatic systems dominated by mafic/felsic interaction that appear to be analogs to the evolution of their larger host systems: mafic inclusions from modern Lassen Pk lavas along with inclusions and related synplutonic dike materials from granitoids in the Tuolumne Intrusive Series. Each system represents quickly chilled mafic melt previously contaminated by digestion of rewarmed, super-solidus felsic hosts. Contaminants occur in part as megacrysts of reworked oligoclase with lesser hb and biot. Within each group MgO-variation diagrams for Fe, Ca, Ti, Si are strikingly linear (r>.96); alkalis are decidedly less regular, and many hybrid rocks show a curious, pronounced Na enrichment. Field data, petrography, and best fit modeling suggests this may result from flow concentration of oligoclase xenocrysts within contaminated synplutonic dikes, and is preserved in the inclusions when dike cores chill as pillows in their felsic host. Dissolution of mafic inclusions erases these anomalies and creates a more regular series of two-component mafic-felsic mixtures in the large host system. The inclusions and dikes thus appear to record a variety of late-stage mafic-felsic interactive processes that earlier and on a larger scale created much of the compositional variety of their intermediate host rocks.

  18. Accessory Mineral Records of Early Earth Crust-Mantle Systematics: an Example From West Greenland

    NASA Astrophysics Data System (ADS)

    Storey, C. D.; Hawkesworth, C. J.

    2008-12-01

    Conditions for the formation and the nature of Earth's early crust are enigmatic due to poor preservation. Before c.4 Ga the only archives are detrital minerals eroded from earlier crust, such as the Jack Hills zircons in western Australia, or extinct isotope systematics. Zircons are particularly powerful since they retain precise records of their ages of crystallisation, and the Lu-Hf radiogenic isotope and O stable isotope systematics of the reservoir from which they crystallised. In principle, this allows insight into the nature of the crust, the mantle reservoir from which the melt was extracted and any reworked material incorporated into that melt. We have used in situ methods to measure U-Pb, O and Lu-Hf within single zircon crystals from tonalitic gneisses from West Greenland in the vicinity of the Isua Supracrustal Belt. They have little disturbed ages of c.3.8 Ga, mantle-like O isotope signatures and Lu-Hf isotope signatures that lie on the CHUR evolution line at 3.8 Ga. These samples have previously been subjected to Pb isotope feldspar and 142Nd whole rock analysis and have helped constrain models in which early differentiation of a proto-crust must have occurred. The CHUR-like Lu-Hf signature, along with mantle-like O signature from these zircons suggests juvenile melt production at 3.8 Ga from undifferentiated mantle, yet the other isotope systems preclude this possibility. Alternatively, this is further strong evidence for a heterogeneous mantle in the early Earth. Whilst zircons afford insight into the nature of the early crust and mantle, it is through the Sm-Nd system that the mantle has traditionally been viewed. Titanite often contains several thousand ppm Nd, making it amenable to precise analysis, and is a common accessory phase. It has a reasonably high closure temperature for Pb and O, and it can retain cores with older ages and distinct REE chemistry. It is often the main accessory phase alongside zircon, and it is the main carrier of Nd

  19. Crustal redistribution, crust-mantle recycling and Phanerozoic evolution of the continental crust

    NASA Astrophysics Data System (ADS)

    Clift, Peter D.; Vannucchi, Paola; Morgan, Jason Phipps

    2009-12-01

    We here attempt a global scale mass balance of the continental crust during the Phanerozoic and especially the Cenozoic (65 Ma). Continental crust is mostly recycled back into the mantle as a result of the subduction of sediment in trenches (1.65 km 3/a), by the subduction of eroded forearc basement (1.3 km 3/a) and by the delamination of lower crustal material from orogenic plateaus (ca. 1.1 km 3/a). Subduction of rifted crust in continent-continent collision zones (0.4 km 3/a), and dissolved materials fixed into the oceanic crust (ca. 0.4 km 3/a) are less important crustal sinks. At these rates the entire continental crust could be reworked in around 1.8 Ga. Nd isotope data indicate that ca. 80% of the subducted continental crust is not recycled by melting at shallow levels back into arcs, but is subducted to depth into the upper mantle. Continent-continent collision zones do not generally form new crust, but rather cause crustal loss by subduction and as a result of their physical erosion, which exports crust from the orogen to ocean basins where it may be subducted. Regional sedimentation rates suggest that most orogens have their topography eliminated within 100-200 million years. We estimate that during the Cenozoic the global rivers exported an average of 1.8 km 3/a to the oceans, approximately balancing the subducted loss. Accretion of sediment to active continental margins is a small contribution to crustal construction (ca. 0.3 km 3/a). Similarly, continental large igneous provinces (flood basalts) represent construction of only around 0.12 km 3/a, even after accounting for their intrusive roots. If oceanic plateaus are accreted to continental margins then they would average construction rates of 1.1 km 3/a, meaning that to keep constant crustal volumes, arc magmatism would have to maintain production of around 3.8 km 3/a (or 94 km 3/Ma/km of trench). This slightly exceeds the rates derived from sparse seismic experiments in oceanic arc systems. Although

  20. Xenoliths in ultrapotassic volcanic rocks in the Lhasa block: direct evidence for crust-mantle mixing and metamorphism in the deep crust

    NASA Astrophysics Data System (ADS)

    Wang, Rui; Collins, William J.; Weinberg, Roberto F.; Li, Jin-xiang; Li, Qiu-yun; He, Wen-yan; Richards, Jeremy P.; Hou, Zengqian; Zhou, Li-min; Stern, Richard A.

    2016-07-01

    δ18O (+6 to 7.5 ‰), intermediate (δ18O +8.5 to 9.0 ‰), and high δ18O (+11.0 to 12.0 ‰). The fourth is almost pure andradite with δ18O 10-12 ‰. Both the low and intermediate δ18O groups show significant variation in Fe content, whereas the two high δ18O groups are compositionally homogeneous. We interpret these features to indicate that the low and intermediate δ18O group garnets grew in separate fractionating magmas that were brought together through magma mixing, whereas the high δ18O groups formed under high-grade metamorphic conditions accompanied by metasomatic exchange. The garnets record complex, open-system magmatic and metamorphic processes in a single rock. Based on these features, we consider that ultrapotassic magmas interacted with juvenile 35-20 Ma crust after they intruded in the deep crust (>50 km) at ~13 Ma to form hybridized Miocene granitoid magmas, leaving a refractory residue. The ~13 Ma zircons retain the original, evolved isotopic character of the ultrapotassic magmas, and the garnets record successive stages of the melting and mixing process, along with subsequent high-grade metamorphism followed by low-temperature alteration and brecciation during entrainment and ascent in a late UPV dyke. This is an excellent example of in situ crust-mantle hybridization in the deep Tibetan crust.

  1. An inference engine for embedded diagnostic systems

    NASA Technical Reports Server (NTRS)

    Fox, Barry R.; Brewster, Larry T.

    1987-01-01

    The implementation of an inference engine for embedded diagnostic systems is described. The system consists of two distinct parts. The first is an off-line compiler which accepts a propositional logical statement of the relationship between facts and conclusions and produces data structures required by the on-line inference engine. The second part consists of the inference engine and interface routines which accept assertions of fact and return the conclusions which necessarily follow. Given a set of assertions, it will generate exactly the conclusions which logically follow. At the same time, it will detect any inconsistencies which may propagate from an inconsistent set of assertions or a poorly formulated set of rules. The memory requirements are fixed and the worst case execution times are bounded at compile time. The data structures and inference algorithms are very simple and well understood. The data structures and algorithms are described in detail. The system has been implemented on Lisp, Pascal, and Modula-2.

  2. Single board system for fuzzy inference

    NASA Technical Reports Server (NTRS)

    Symon, James R.; Watanabe, Hiroyuki

    1991-01-01

    The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.

  3. Lithium systematics in howardite-eucrite-diogenite meteorites: Implications for crust-mantle evolution of planetary embryos

    NASA Astrophysics Data System (ADS)

    Magna, Tomáš; Šimčíková, Magdalena; Moynier, Frédéric

    2014-01-01

    We present lithium (Li) abundances and isotope compositions in a suite of howardites, eucrites and diogenites (HEDs). These meteorites most likely originated from asteroid Vesta and were delivered to Earth by a series of independent impact events. The Li concentrations show striking differences between Li-poor diogenites plus cumulate eucrites and Li-enriched eucrites whilst howardites have Li abundances intermediate between eucrites and diogenites. Contrary to Li elemental inter-group differences, Li isotope compositions are irresolvable among these individual groups of HED meteorites despite their wildly distinct petrography, attesting to insignificant Li isotope fractionation during formation of a thick basaltic crust by melting of the Vestan mantle. The mean Li isotope composition of Bulk Silicate Vesta is estimated at 3.7 ± 0.6‰ (1σ), intermediate to that of the Earth versus Mars and Moon but identical with these terrestrial bodies within uncertainty. This further validates largely homogeneous inner Solar System solids from the Li isotope perspective and supports the lack of loss of moderately volatile elements from planetary embryos during their magmatic histories because Li does not follow depletion trends inferred from more volatile elements. Pasamonte eucrite has the same Li isotope composition as other eucrites although it may not be directly linked to Vesta. These observations are also important for generating Li elemental and isotope signatures in juvenile basaltic crusts of large terrestrial planets and numerous planetary embryos in the early Solar System. A combination of CV + L chondrites may be less suitable for building Vesta from Li perspective but this may face sampling bias of available data and only further analyses may resolve this issue. Alternatively, significant shift of ∼1‰ towards heavier Li isotope compositions must have occurred during thermal processing of CV + L (2.2-2.8‰) mixture in order to account for the observed Li

  4. Evidence for chondritic Lu/Hf in the early crust - mantle system from Antarctic and Western Australian Eoarchean zircon

    NASA Astrophysics Data System (ADS)

    Hiess, J.; Bennett, V. C.; Black, L.; Eggins, S. M.

    2009-12-01

    The timing and extent of early continental crust formation and mantle differentiation remain contentious issues in Earth Sciences. Here we report new, SHRIMP U-Pb zircon geochronology (n = 142 spot analyses on 69 grains), combined with LA-MC-ICPMS 176Hf determinations (n = 110 spot analyses on 59 grains), in three well-characterized orthogneiss samples of the Napier Complex (Mt Sones and Gage Ridge), East Antarctica and the Narryer Complex, West Australia. Prior to analysis all crystals were extensively documented by cathodoluminesence, reflected and transmitted light imaging to guide beam placement and to identify zones of magmatic oscillatory growth from metamorphic recrystallisation textures. Each sample records complex 207Pb/206Pb age structures that can extend from Hadean through to the Neoarchean, while displaying concordant, reverse-discordant and normal-discordant behaviour. U-Pb systematics within individual grains can be correlated with distinct variations in their measured Lu and Hf isotopic compositions. These features lead to the presence of multiple Lu/Hf arrays within each rock sample evolving towards progressively un-radiogenic values through time. Highly concordant populations of Eoarchean zircon from each rock represent the intrusive age of their igneous protolith at approximately 3.88, 3.85 and 3.73 Ga. Across all three samples these zircon populations typically record initial ɛHf values that lie within error of the Earth’s chondritic uniform reservoir (calculated using λ176Lu of 1.867×10-11 yr-1 and CHUR parameters of Bouvier et al., 2008, EPSL 273: 48-57). These near-chondritic results are consistent with recent LA-MC-ICPMS 176Hf work on primitive Eoarchean TTG zircon from other cratons (e.g. the Itsaq Complex of Greenland, Hiess et al., 2009, GCA 73: 4489-4516) and together argue against voluminous continental crustal growth or significant mantle Lu/Hf differentiation during the Hadean or Eoarchean on a global scale. Two grains of Antarctic zircon with ~25µm spot ages >4 Ga, made on domains of subtle oscillatory zonation, moderate Th/U (>0.36), low common 206Pb (<0.02%) and reverse-discordance (-6% and -9%) record supra-chondritic ɛHf values (c. +2 and +4). These analyses may potentially represent inherited zircon derived from an older depleted mantle reservoir. Alternatively, these positive ɛHf compositions, measured on crystals that also contain recrystallised textures, variable 207Pb/206Pb ages and fractures, may be interpreted as an artifact of Pb disturbance and do not have geological significance. These issues highlight the difficulties in determining precise and accurate initial Hf isotopic compositions in ancient, complex zircon.

  5. Inference System Integration Via Logic Morphisms

    NASA Technical Reports Server (NTRS)

    Bjorner, Nikolaj S.; Espinosa, David

    2000-01-01

    This is a final report on the accomplishments during the period of the NASA grant. The work on inference servers accomplished the integration of the SLANG logic (Specware's default specification logic) with a number of inference servers in order to make their complementary strengths available. These inverence servers are (1) SNARK. (2) Gandalf, Setheo, and Spass, (3) the Prototype Verification System (PVS) from SRI. (4) HOL98. We designed and implemented MetaSlang, an ML-like language, which we are using to specify and implement all our logic morphisms.

  6. Low velocity crustal flow and crust-mantle coupling mechanism in Yunnan, SE Tibet, revealed by 3D S-wave velocity and azimuthal anisotropy

    NASA Astrophysics Data System (ADS)

    Chen, Haopeng; Zhu, Liangbao; Su, Youjin

    2016-08-01

    We used teleseismic data recorded by a permanent seismic network in Yunnan, SE Tibet, and measured the interstation Rayleigh wave phase velocity between 10 and 60 s. A two-step inversion scheme was used to invert for the 3D S-wave velocity and azimuthal anisotropy structure of 10-110 km. The results show that there are two low velocity channels between depths of 20-30 km in Yunnan and that the fast axes are sub-parallel to the strikes of the low velocity channels, which supports the crustal flow model. The azimuthal anisotropy pattern is quite complicated and reveals a complex crust-mantle coupling mechanism in Yunnan. The N-S trending Lüzhijiang Fault separates the Dianzhong Block into two parts. In the western Dianzhong Block, the fast axis of the S-wave changes with depth, which indicates that the crust and the lithospheric mantle are decoupled. In the eastern Dianzhong Block and the western Yangtze Craton, the crust and the lithospheric mantle may be decoupled because of crustal flow, despite a coherent S-wave fast axis at depths of 10-110 km. In addition, the difference between the S-wave fast axis in the lithosphere and the SKS splitting measurement suggests that the lithosphere and the upper mantle are decoupled there. In the Baoshan Block, the stratified anisotropic pattern suggests that the crust and the upper mantle are decoupled.

  7. Lithology and evolution of the crust-mantle boundary region in the southwestern Basin and Range province

    SciTech Connect

    Wilshire, H.G. )

    1990-01-10

    Seismic transects in this area show a strongly reflective Moho of generally low relief, which, in the area of modern transects, consists of a thin zone (< 2 km thick) of short reflectors. The upper mantle is transparent and has a P{sub n} of 7.8-8.0 km/s similar to much of the western US. A lower crustal zone, 2-13 km thick, has variable internal reflectivity and a relatively low velocity of 6.6-6.8 km/s. Upper mantle peridotite xenoliths show both ductile and brittle deformational features and have structures and composition affected by magmatic intrusion; intrusions form complex dike systems and extensive zones of grain boundary infiltration in peridotite xenoliths. Whereas melt infiltration preceded and followed ductile deformation, brittle deformation, represented by closely spaced joint systems and faults, followed ductile deformation and is related to the youngest magmatic episodes. Lower crustal xenoliths are dominantly igneous-textured pyroxenites and mafic to intermediate gabbros identical to the dikes in peridotite xenoliths. The crustal xenoliths also commonly are jointed, and in addition many show partial melting and have abundant cavities that probably were filled with CO{sub 2}-rich fluids. These rocks are interpreted as products of underplated magmas that were fed through the mantle dike systems and may represent the lowest crustal unit identified in the seismic records. The mafic compositions and high densities of the crustal xenoliths indicate that the low velocity of the lower crust mat be caused in part by fracture systems, partial melts, and high temperatures. The preferred model for the evolution of the lower lithosphere is one in which extension affects the upper mantle as well as the crust and is overlapped in time by multiple magmatic episodes. The earliest magmatic events preceded extension, and later events accompanied and followed extension.

  8. An Ada inference engine for expert systems

    NASA Technical Reports Server (NTRS)

    Lavallee, David B.

    1986-01-01

    The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.

  9. Implementation of Fuzzy Inference Systems Using Neural Network Techniques

    DTIC Science & Technology

    1992-03-01

    rules required to implement the system, which are usually supplied by ’experts’. One alternative is to use a neural network -type architecture to implement...the fuzzy inference system, and neural network -type training techniques to ’learn’ the control parameters needed by the fuzzy inference system. By...using a generalized version of a neural network , the rules of the fuzzy inference system can be learned without the assistance of experts.

  10. Inference by replication in densely connected systems

    SciTech Connect

    Neirotti, Juan P.; Saad, David

    2007-10-15

    An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a large number of replicated variable systems exposed to the same evidential nodes. An assumption about the symmetry of the solutions is required for carrying out the averages; here we extend the previous derivation based on a replica-symmetric- (RS)-like structure to include a more complex one-step replica-symmetry-breaking-like (1RSB-like) ansatz. To demonstrate the potential of the approach it is employed for studying critical properties of the Ising linear perceptron and for multiuser detection in code division multiple access (CDMA) under different noise models. Results obtained under the RS assumption in the noncritical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also observed. While the 1RSB ansatz is not required for the original problems, it was applied to the CDMA signal detection problem with a more complex noise model that exhibits RSB behavior, resulting in an improvement in performance.

  11. Causal Inferences in the Campbellian Validity System

    ERIC Educational Resources Information Center

    Lund, Thorleif

    2010-01-01

    The purpose of the present paper is to critically examine causal inferences and internal validity as defined by Campbell and co-workers. Several arguments are given against their counterfactual effect definition, and this effect definition should be considered inadequate for causal research in general. Moreover, their defined independence between…

  12. Causal Inferences in the Campbellian Validity System

    ERIC Educational Resources Information Center

    Lund, Thorleif

    2010-01-01

    The purpose of the present paper is to critically examine causal inferences and internal validity as defined by Campbell and co-workers. Several arguments are given against their counterfactual effect definition, and this effect definition should be considered inadequate for causal research in general. Moreover, their defined independence between…

  13. Crustal magnetization and temperature at depth beneath the Yilgarn block, Western Australia inferred from Magsat data

    NASA Technical Reports Server (NTRS)

    Mayhew, M. A.; Wasilewski, Peter J.; Johnson, B. D.

    1991-01-01

    Variations in crustal magnetization along a seismic section across the Archean Yilgarn block of Western Australia inferred from Magsat data are interpreted as a subtle thermal effect arising from variations in depth to the Curie isotherm. The isotherm lies deep within the mantle of the eastern part of the province, but transects the crust-mantle transition and rises well into the crust on the western side. The model is consistent with heat flow variations along the section line. The mean crustal magnetization implied by the model is approximately 2 A/m. The temperature variation implied by the model is consistent with the hypothesis that the crust-mantle transition seen seismically corresponds to the mafic granulite-eclogite phase transition within a zone of igneous crustal underplating.

  14. Parameter Inference for Biochemical Systems that Undergo a Hopf Bifurcation

    PubMed Central

    Kirk, Paul D. W.; Toni, Tina; Stumpf, Michael P. H.

    2008-01-01

    The increasingly widespread use of parametric mathematical models to describe biological systems means that the ability to infer model parameters is of great importance. In this study, we consider parameter inferability in nonlinear ordinary differential equation models that undergo a bifurcation, focusing on a simple but generic biochemical reaction model. We systematically investigate the shape of the likelihood function for the model's parameters, analyzing the changes that occur as the model undergoes a Hopf bifurcation. We demonstrate that there exists an intrinsic link between inference and the parameters' impact on the modeled system's dynamical stability, which we hope will motivate further research in this area. PMID:18456830

  15. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

  16. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, R.M.; Kery, M.; Royle, J. Andrew; Plattner, M.

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species-and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity. ?? 2010 by the Ecological Society of America.

  17. Alternative Theories of Inference in Expert Systems for Image Analysis.

    DTIC Science & Technology

    1985-02-01

    D-A153 649 ALTERNATIVE THEORIES OF INFERENCE IN EXPERT SYSTEMS FR 12 IMAGE ANALYSIS (U) DECISION SCIENCE CONSORTIUM INC FALLS CHURCH VAl M S COHEN ET...TEST CHART NATIONAL BUREAU OF StANDARDS-1963 A .- ., mETLN..b ? (0 Alentv thoreso inference in expert systems * for image analysis Marvin Cohen Decision...distribution unlimited 4. P[RFCR%0.NG ORCANIZATION REPORT NUMBERIS) s. MONITORING ORGANIZATION REPORT h.UMdiRISI 6. NAMAE 0F PERFORMING ORGANIZATION

  18. LOWER LEVEL INFERENCE CONTROL IN STATISTICAL DATABASE SYSTEMS

    SciTech Connect

    Lipton, D.L.; Wong, H.K.T.

    1984-02-01

    An inference is the process of transforming unclassified data values into confidential data values. Most previous research in inference control has studied the use of statistical aggregates to deduce individual records. However, several other types of inference are also possible. Unknown functional dependencies may be apparent to users who have 'expert' knowledge about the characteristics of a population. Some correlations between attributes may be concluded from 'commonly-known' facts about the world. To counter these threats, security managers should use random sampling of databases of similar populations, as well as expert systems. 'Expert' users of the DATABASE SYSTEM may form inferences from the variable performance of the user interface. Users may observe on-line turn-around time, accounting statistics. the error message received, and the point at which an interactive protocol sequence fails. One may obtain information about the frequency distributions of attribute values, and the validity of data object names from this information. At the back-end of a database system, improved software engineering practices will reduce opportunities to bypass functional units of the database system. The term 'DATA OBJECT' should be expanded to incorporate these data object types which generate new classes of threats. The security of DATABASES and DATABASE SySTEMS must be recognized as separate but related problems. Thus, by increased awareness of lower level inferences, system security managers may effectively nullify the threat posed by lower level inferences.

  19. INFeRS: Interactive Numeric Files Retrieval System. Final Report.

    ERIC Educational Resources Information Center

    Chiang, Katherine; And Others

    In 1988 Mann Library at Cornell University proposed to develop a computer system that would support interactive access to significant electronic files in agriculture and the life sciences. This system was titled the Interactive Numeric Files Retrieval System (INFeRS). This report describes how project goals were met and it presents the project's…

  20. Fuzzy exemplar-based inference system for flood forecasting

    NASA Astrophysics Data System (ADS)

    Chang, Li-Chiu; Chang, Fi-John; Tsai, Ya-Hsin

    2005-02-01

    Fuzzy inference systems have been successfully applied in numerous fields since they can effectively model human knowledge and adaptively make decision processes. In this paper we present an innovative fuzzy exemplar-based inference system (FEIS) for flood forecasting. The FEIS is based on a fuzzy inference system, with its clustering ability enhanced through the Exemplar-Aided Constructor of Hyper-rectangles algorithm, which can effectively simulate human intelligence by learning from experience. The FEIS exhibits three important properties: knowledge extraction from numerical data, knowledge (rule) modeling, and fuzzy reasoning processes. The proposed model is employed to predict streamflow 1 hour ahead during flood events in the Lan-Yang River, Taiwan. For the purpose of comparison the back propagation neural network (BPNN) is also performed. The results show that the FEIS model performs better than the BPNN. The FEIS provides a great learning ability, robustness, and high predictive accuracy for flood forecasting.

  1. Diagnosis of arthritis through fuzzy inference system.

    PubMed

    Singh, Sachidanand; Kumar, Atul; Panneerselvam, K; Vennila, J Jannet

    2012-06-01

    Expert or knowledge-based systems are the most common type of AIM (artificial intelligence in medicine) system in routine clinical use. They contain medical knowledge, usually about a very specifically defined task, and are able to reason with data from individual patients to come up with reasoned conclusion. Although there are many variations, the knowledge within an expert system is typically represented in the form of a set of rules. Arthritis is a chronic disease and about three fourth of the patients are suffering from osteoarthritis and rheumatoid arthritis which are undiagnosed and the delay of detection may cause the severity of the disease at higher risk. Thus, earlier detection of arthritis and treatment of its type of arthritis and related locomotry abnormalities is of vital importance. Thus the work was aimed to design a system for the diagnosis of Arthitis using fuzzy logic controller (FLC) which is, a successful application of Zadeh's fuzzy set theory. It is a potential tool for dealing with uncertainty and imprecision. Thus, the knowledge of a doctor can be modelled using an FLC. The performance of an FLC depends on its knowledge base which consists of a data base and a rule base. It is observed that the performance of an FLC mainly depends on its rule base, and optimizing the membership function distributions stored in the data base is a fine tuning process.

  2. Inferring connectivity in networked dynamical systems: Challenges using Granger causality

    NASA Astrophysics Data System (ADS)

    Lusch, Bethany; Maia, Pedro D.; Kutz, J. Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  3. Inferring connectivity in networked dynamical systems: Challenges using Granger causality.

    PubMed

    Lusch, Bethany; Maia, Pedro D; Kutz, J Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  4. Zircon U-Pb dating, geochemical and Sr-Nd-Hf isotopic characteristics of the Jintonghu monzonitic rocks in western Fujian Province, South China: Implication for Cretaceous crust-mantle interactions and lithospheric extension

    NASA Astrophysics Data System (ADS)

    Li, Bin; Jiang, Shao-Yong; Lu, An-Huai; Zhao, Hai-Xiang; Yang, Tang-Li; Hou, Ming-Lan

    2016-09-01

    Comprehensive petrological, in situ zircon U-Pb dating, Ti-in-zircon temperature and Hf isotopic compositions, whole rock geochemical and Sr-Nd isotopic data are reported for the Jintonghu monzonitic intrusions in the western Fujian Province (Interior Cathaysia Block), South China. The Jintonghu monzonitic intrusions were intruded at 95-96 Ma. Their Sr-Nd-Hf isotopic compositions are similar to the coeval and nearby enriched lithospheric mantle-derived mafic and syenitic rocks, indicating that the Jintonghu monzonitic rocks were likely derived from partial melting of the enriched mantle sources. Their high Nb/Ta ratios (average 21.6) suggest that the metasomatically enriched mantle components were involved, which was attributed to the modification of slab-derived fluid and melt by the subduction of the paleo-Pacific Plate. The presence of mafic xenoliths, together with geochemical and isotopic features indicates a mafic-felsic magma mixing. Furthermore, the Jintonghu intrusions may have experienced orthopyroxene-, biotite- and plagioclase-dominated crystallization. Crust-mantle interaction can be identified as two stages, including that the Early Cretaceous mantle metasomatism and lithospheric extension resulted from the paleo-Pacific slab subduction coupled with slab rollback, and the Late Cretaceous crustal activation and enhanced extension induced by dip-angle subduction and the underplating of mantle-derived mafic magma.

  5. An expert system shell for inferring vegetation characteristics

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann; Harrison, Patrick R.

    1992-01-01

    The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The report describes the extensions that have been made to the first generation version of VEG. An interface to a file of unkown cover type data has been constructed. An interface that allows the results of VEG to be written to a file has been implemented. A learning system that learns class descriptions from a data base of historical cover type data and then uses the learned class descriptions to classify an unknown sample has been built. This system has an interface that integrates it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented.

  6. Evaluation of fuzzy inference systems using fuzzy least squares

    NASA Technical Reports Server (NTRS)

    Barone, Joseph M.

    1992-01-01

    Efforts to develop evaluation methods for fuzzy inference systems which are not based on crisp, quantitative data or processes (i.e., where the phenomenon the system is built to describe or control is inherently fuzzy) are just beginning. This paper suggests that the method of fuzzy least squares can be used to perform such evaluations. Regressing the desired outputs onto the inferred outputs can provide both global and local measures of success. The global measures have some value in an absolute sense, but they are particularly useful when competing solutions (e.g., different numbers of rules, different fuzzy input partitions) are being compared. The local measure described here can be used to identify specific areas of poor fit where special measures (e.g., the use of emphatic or suppressive rules) can be applied. Several examples are discussed which illustrate the applicability of the method as an evaluation tool.

  7. A fuzzy inference system to evaluate contract service provider performance.

    PubMed

    Cruz, Antonio Miguel; Denis, Ernesto Rodriguez

    2005-01-01

    This paper puts forward a fuzzy inference system for evaluating the quality performance of service contract providers. An Application Service Provider was designed and put online, featuring surveys to establish the most useful indicators to evaluate the quality of the service. This model was implemented in 10 separate hospitals. As a result, the service cost-acquisition cost ratio in these cases was reduced from 16.14% to 6.09% in the period 2001-January 2003.

  8. Topological augmentation to infer hidden processes in biological systems

    PubMed Central

    Sunnåker, Mikael; Zamora-Sillero, Elias; López García de Lomana, Adrián; Rudroff, Florian; Sauer, Uwe; Stelling, Joerg; Wagner, Andreas

    2014-01-01

    Motivation: A common problem in understanding a biochemical system is to infer its correct structure or topology. This topology consists of all relevant state variables—usually molecules and their interactions. Here we present a method called topological augmentation to infer this structure in a statistically rigorous and systematic way from prior knowledge and experimental data. Results: Topological augmentation starts from a simple model that is unable to explain the experimental data and augments its topology by adding new terms that capture the experimental behavior. This process is guided by representing the uncertainty in the model topology through stochastic differential equations whose trajectories contain information about missing model parts. We first apply this semiautomatic procedure to a pharmacokinetic model. This example illustrates that a global sampling of the parameter space is critical for inferring a correct model structure. We also use our method to improve our understanding of glutamine transport in yeast. This analysis shows that transport dynamics is determined by glutamine permeases with two different kinds of kinetics. Topological augmentation can not only be applied to biochemical systems, but also to any system that can be described by ordinary differential equations. Availability and implementation: Matlab code and examples are available at: http://www.csb.ethz.ch/tools/index. Contact: mikael.sunnaker@bsse.ethz.ch; andreas.wagner@ieu.uzh.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24297519

  9. Post-collisional high-Mg granitoids from the Paleoproterozoic East Sarmatian Orogen (East European Craton): Evidence for crust-mantle interaction

    NASA Astrophysics Data System (ADS)

    Terentiev, R. A.; Santosh, M.

    2017-03-01

    The East Sarmatian Orogen (ESO) is located along the southwestern domain of the East European Craton and occupies a key tectonic link between the Sarmatian and Volgo-Uralian domains. Here we investigate the Paleoproterozoic Novaya Melovatka pluton and its mafic-ultramafic xenoliths to gain insights into the role of interaction between intermediate-felsic crustal melt with mantle rocks as a mechanism for the generation of high-Mg granitoids at crustal pressures. The pluton is composed of biotite-orthopyroxene quartz dioritic and monzodioritic porphyrites (Phase 1) and medium-grained biotite-amphibole quartz diorite, tonalite and granodiorite and commingled Phase 1 mafic magmatic enclaves (MME) (Phase 2). The general geochemical characteristics of these rocks are similar to those of Late-Archean high-Mg sanukitoids. The TDM (model) ages for intermediate Phase 1 and granitoid Phase 2 are similar and show a range of 2324-2439 and 2284-2519 M, respectively. The εNd(t) values are grouped around subchondritic values (=+1.4-+1.9 and + 1.1-+2.2) and the initial 87Sr/86Sr ratios are in the range of 0.70202-0.70390. The complex compositional zoning of minerals suggests that the rocks crystallized as synchronous but discrete magma pulses, with limited to significant mixing. Based on the geochemical features we infer that the Phase 1 rocks formed from partial melting of a mantle wedge metasomatized to different degrees by fluids/melts. The presence of MMEs, compositional zoning of minerals including reversely zoned amphiboles, plagioclases with thin calcic overgrowths, and acicular apatite, as well as the whole-rock geochemical features are consistent with a hybrid origin of the high-Mg granitoids belonging to Phase 2. Geobarometry indicates crystallization at upper-crustal depths (i.e. 1.7-2.4 kbar). The igneous suite evolved by fractional crystallization of orthopyroxene, hornblende, plagioclase and biotite. Here we propose a tectonic model involving partial melting of the

  10. Statistical inference for noisy nonlinear ecological dynamic systems.

    PubMed

    Wood, Simon N

    2010-08-26

    Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

  11. Geochronology and geochemistry of Cretaceous Nanshanping alkaline rocks from the Zijinshan district in Fujian Province, South China: Implications for crust-mantle interaction and lithospheric extension

    NASA Astrophysics Data System (ADS)

    Li, Bin; Jiang, Shao-Yong

    2014-10-01

    In situ zircon U-Pb ages and Hf isotopic data, major and trace elements, and Sr-Nd-Pb isotopic compositions are reported for Nanshanping alkaline rocks from the Zijingshan district in southwestern Fujian Province (the Interior or Western Cathaysia Block) of South China. The Nanshanping alkaline rocks, which consist of porphyritic quartz monzonite, porphyritic syenite, and syenite, revealed a Late Cretaceous age of 100-93 Ma. All of the rocks show high SiO2, K2O + Na2O, and LREE but low CaO, Fe2O3T, MgO, and HFSE (Nb, Ta, P, and Ti) concentrations. These rocks also exhibit uniform initial 87Sr/86Sr ratios of 0.7078 to 0.7087 and εNd(t) values of -4.1 to -7.2, thus falling within the compositional field of Cretaceous basalts and mafic dikes occurring in the Cathaysia Block. Additionally, these rocks display initial Pb isotopic compositions with a 206Pb/204Pbi ratio of 18.25 to 18.45, a 207Pb/204Pbi ratio of 15.63 to 15.67, and a 208Pb/204Pbi ratio of 38.45 to 38.88. Combined with the zircon Hf isotopic compositions (εHf(t) = -11.7 to -3.2), which are different from those of the basement rocks, we suggest that Nanshanping alkaline rocks were primarily derived from a subduction-related enriched mantle source. High Rb/Sr (0.29-0.65) and Zr/Hf (37.5-49.2) but relatively low Ba/Rb (4.4-8.1) ratios suggest that the parental magmas of these rocks were most likely formed via partial melting of a phlogopite-bearing mantle source with carbonate metasomatism. The relatively high SiO2 (62.35-70.79 wt.%) and low Nb/Ta (10.0-15.3) ratios, positive correlation between SiO2 and (87Sr/86Sr)I, and negative correlation between SiO2 and εNd(t) of these rocks suggest that the crustal materials were also involved in formation of the Nanshanping alkaline rocks. Combined with geochemical and isotopic features, we infer magmatic processes similar to AFC (assimilation and fractional crystallization) involving early fractionation of clinopyroxene and olivine and subsequent fractionation of

  12. Devonian granitoids and their hosted mafic enclaves in the Gorny Altai terrane, northwestern Central Asian Orogenic Belt: crust-mantle interaction in a continental arc setting

    NASA Astrophysics Data System (ADS)

    Chen, Ming; Sun, Min

    2016-04-01

    Granitoids are a major component in the upper continental crust and hold key information on how did the continental crust grow and differentiate. This study focuses on the Yaloman intrusive complex from the Gorny Altai terrane, northwestern Central Asian Orogenic Belt (CAOB). The association of granitoids and mafic enclaves can provide important clues on the source nature, petrogenetic processes and geodynamic setting of the Yaloman intrusive complex, which in turn will shed light on the crustal evolution in the northwestern CAOB. Zircon U-Pb dating shows that the granitoids, including quartz diorites and granodiorites, were emplaced in ca. 389-387 Ma. The moderate Na2O + K2O contents and low A/CNK values indicate that these rocks belong to the sub-alkaline series with metaluminous to weakly peraluminous compositions. The granitoids yield two-stage zircon Hf model ages of ca. 0.79-1.07 Ga and whole-rock Nd model ages of ca. 0.90-0.99 Ga, respectively, implying that they were mainly sourced from Neoproterozoic juvenile crustal materials. The mafic enclaves show an almost identical crystallization age of ca. 389 Ma. The identification of coarse-grained xenocrysts and acicular apatites, together with the fine-grained texture, makes us infer that these enclaves are likely to represent magmatic globules commingled with the host magmas. The low SiO2 and high MgO contents of the mafic enclaves further suggest that substantial mantle-derived mafic melts were probably involved in their formation. Importantly, the SiO2 contents of the granitoids and mafic enclaves are well correlated with other major elements and most of the trace elements. Also a broadly negative correlation exists between the SiO2 contents and whole-rock epsilon Nd (390 Ma) values of the granitoids. Given the observation of reversely zoned plagioclases within the granitoids and the common occurrence of igneous mafic enclaves, we propose that magma mixing probably played an important role in the formation

  13. Improving real time flood forecasting using fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Lohani, Anil Kumar; Goel, N. K.; Bhatia, K. K. S.

    2014-02-01

    In order to improve the real time forecasting of foods, this paper proposes a modified Takagi Sugeno (T-S) fuzzy inference system termed as threshold subtractive clustering based Takagi Sugeno (TSC-T-S) fuzzy inference system by introducing the concept of rare and frequent hydrological situations in fuzzy modeling system. The proposed modified fuzzy inference systems provide an option of analyzing and computing cluster centers and membership functions for two different hydrological situations, i.e. low to medium flows (frequent events) as well as high to very high flows (rare events) generally encountered in real time flood forecasting. The methodology has been applied for flood forecasting using the hourly rainfall and river flow data of upper Narmada basin, Central India. The available rainfall-runoff data has been classified in frequent and rare events and suitable TSC-T-S fuzzy model structures have been suggested for better forecasting of river flows. The performance of the model during calibration and validation is evaluated by performance indices such as root mean square error (RMSE), model efficiency and coefficient of correlation (R). In flood forecasting, it is very important to know the performance of flow forecasting model in predicting higher magnitude flows. The above described performance criteria do not express the prediction ability of the model precisely from higher to low flow region. Therefore, a new model performance criterion termed as peak percent threshold statistics (PPTS) is proposed to evaluate the performance of a flood forecasting model. The developed model has been tested for different lead periods using hourly rainfall and discharge data. Further, the proposed fuzzy model results have been compared with artificial neural networks (ANN), ANN models for different classes identified by Self Organizing Map (SOM) and subtractive clustering based Takagi Sugeno fuzzy model (SC-T-S fuzzy model). It has been concluded from the study that the

  14. A Theory of Conditional Information for Probabilistic Inference in Intelligent Systems: 3, Mathematical Appendix

    DTIC Science & Technology

    1994-06-01

    THEORY OF CONDITIONAL INFORMATION FOR PROBABILISTIC PR: CD32 INFERENCE IN INTELLIGENT SYSTEMS : Il, MATHEMATICAL PE: 0305108K APPENDIX WU: DN488828 6...AvailabiiitCo, A THEORY OF CONDITIONAL INFORMATION FOR PROBABILISTIC INFERENCE IN INTELLIGENT SYSTEMS : III, MATHEMATICAL APPENDIX ABSTRACT This...statements, implications, intelligent systems , logic of conditionals, probabilistic inference, quantification of if-then rules -1- OVERVIEW This

  15. An expert system shell for inferring vegetation characteristics

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann; Harrison, Patrick R.

    1993-01-01

    The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. VEG is described in detail in several references. The first generation version of VEG was extended. In the first year of this contract, an interface to a file of unknown cover type data was constructed. An interface that allowed the results of VEG to be written to a file was also implemented. A learning system that learned class descriptions from a data base of historical cover type data and then used the learned class descriptions to classify an unknown sample was built. This system had an interface that integrated it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER was completed and a number of additional techniques that inferred the proportion ground cover of a sample were implemented. This work was previously described. The work carried out in the second year of the contract is described. The historical cover type database was removed from VEG and stored as a series of flat files that are external to VEG. An interface to the files was provided. The framework and interface for two new VEG subgoals that estimate the atmospheric effect on reflectance data were built. A new interface that allows the scientist to add techniques to VEG without assistance from the developer was designed and implemented. A prototype Help System that allows the user to get more information about each screen in the VEG interface was also added to VEG.

  16. Cretaceous crust-mantle interaction and tectonic evolution of Cathaysia Block in South China: Evidence from pulsed mafic rocks and related magmatism

    NASA Astrophysics Data System (ADS)

    Li, Bin; Jiang, Shao-Yong; Zhang, Qian; Zhao, Hai-Xiang; Zhao, Kui-Dong

    2015-10-01

    Cretaceous tectono-magmatic evolution of the Cathaysia Block in South China is important but their mechanism and geodynamics remain highly disputed. In this study we carried out a detailed geochemical study on the recently found Kuokeng mafic dikes in the western Fujian Province (the Interior Cathaysia Block) to reveal the petrogenesis and geodynamics of the Cretaceous magmatism. Kuokeng mafic dikes were emplaced in three principal episodes: ~ 129 Ma (monzogabbro), ~ 107 Ma (monzodiorite), and ~ 97 Ma (gabbro). Geochemical characteristics indicate that the monzogabbros were derived from the unmodified mantle source, while gabbros were likely derived from metasomatized mantle by subducted slab (fluids and sediments). Sr-Nd isotope compositions indicate that the parental magmas of the monzodiorites were generated by mixing of enriched, mantle-derived, mafic magmas and felsic melts produced by partial melting of crustal materials. Until the Early Cretaceous (~ 123 Ma), the dominant ancient Interior Cathaysia lithospheric mantle exhibited insignificant subduction signature, indicating the melting of asthenospheric mantle and the consequent back-arc extension, producing large-scale partial melting of the crustal materials under the forward subduction regime of the paleo-Pacific plate. The monzodiorites and gabbros appear to be associated with northwestward subduction of Pacific plate under an enhanced lithospheric extensional setting, accompanying with mantle modification, which triggered shallower subduction-related metasomatically enriched lithospheric mantle to melt partially. After ca. 110 Ma, the coastal magmatic belts formed due to a retreat and rollback of the subducting Pacific Plate underneath SE China in the continental margin arc system.

  17. ANUBIS: artificial neuromodulation using a Bayesian inference system.

    PubMed

    Smith, Benjamin J H; Saaj, Chakravarthini M; Allouis, Elie

    2013-01-01

    Gain tuning is a crucial part of controller design and depends not only on an accurate understanding of the system in question, but also on the designer's ability to predict what disturbances and other perturbations the system will encounter throughout its operation. This letter presents ANUBIS (artificial neuromodulation using a Bayesian inference system), a novel biologically inspired technique for automatically tuning controller parameters in real time. ANUBIS is based on the Bayesian brain concept and modifies it by incorporating a model of the neuromodulatory system comprising four artificial neuromodulators. It has been applied to the controller of EchinoBot, a prototype walking rover for Martian exploration. ANUBIS has been implemented at three levels of the controller; gait generation, foot trajectory planning using Bézier curves, and foot trajectory tracking using a terminal sliding mode controller. We compare the results to a similar system that has been tuned using a multilayer perceptron. The use of Bayesian inference means that the system retains mathematical interpretability, unlike other intelligent tuning techniques, which use neural networks, fuzzy logic, or evolutionary algorithms. The simulation results show that ANUBIS provides significant improvements in efficiency and adaptability of the three controller components; it allows the robot to react to obstacles and uncertainties faster than the system tuned with the MLP, while maintaining stability and accuracy. As well as advancing rover autonomy, ANUBIS could also be applied to other situations where operating conditions are likely to change or cannot be accurately modeled in advance, such as process control. In addition, it demonstrates one way in which neuromodulation could fit into the Bayesian brain framework.

  18. Order restricted inference for oscillatory systems for detecting rhythmic signals

    PubMed Central

    Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A.; Peddada, Shyamal D.

    2016-01-01

    Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm. Contact: peddada@niehs.nih.gov PMID:27596593

  19. Classification of toddler nutritional status using fuzzy inference system (FIS)

    NASA Astrophysics Data System (ADS)

    Permatasari, Dian; Azizah, Isnaini Nur; Hadiat, Hanifah Latifah; Abadi, Agus Maman

    2017-08-01

    Nutrition is a major health problem and concern for parents when it is relating with their toddler. The nutritional status is an expression of the state caused by the status of the balance between the number of intake of nutrients and the amount needed by the body for a variety of biological functions. The indicators that often used to determine the nutritional status is the combination of Weight (W) and Height (H) symbolized by W/H, because it describe a sensitive and specific nutritional status. This study aims to apply the Fuzzy Inference System Mamdani method to classify the nutritional status of toddler. The inputs are weight and height of the toddler. There are nine rules that used and the output is nutritional status classification consisting of four criteria: stunting, wasting, normal, and overweight. Fuzzy Inference System that be used is Mamdani method and the defuzzification use Centroid Method. The result of this study is compared with Assessment Anthropometric Standard of Toddler Nutritional Status by Ministry of Health. The accuracy level of this fuzzy model is about 84%.

  20. Volcanism on Mercury (dikes, lava flows, pyroclastics): Crust/mantle density contrasts, the evolution of compressive stress and the presence of mantle volatiles

    NASA Astrophysics Data System (ADS)

    Wilson, L.; Head, J. W., III

    2008-09-01

    Background. There is great uncertainty about the internal structure of Mercury and the composition of the mantle [e.g., 1, 2]. The high mean density of the body suggests that it may have lost parts of its crust and mantle in a giant impact at some stage after most of its initial accretion was sufficiently complete that at least partial separation of a core had occurred. It is the uncertainty about the timing of the giant impact, and hence the physico-chemical state of proto-Mercury at the time that it occurred, that leads to difficulties in predicting the interior structure and mantle composition. However, it seems reasonable to assume that the Mercury we see today has some combination of a relatively low-density crust and a relatively highdensity mantle; uncertainty remains about the presence and types of volatiles [2]. The second uncertainty is the nature of the surface plains units, specifically, are these lava flows and pyroclastics erupted from the interior, or impact-reworked earlier crust [3-5] (Figs. 1-2)? The detection of candidate pyroclastic deposits [4] has very important implications for mantle volatiles. Furthermore, whatever the surface composition, the presence of planet-wide systems of wrinkle ridges and thrust faults implies that a compressive crustal stress regime became dominant at some stage in the planet's history [3, 6]. If the plains units are indeed lava flows, then the fact that the products of the compressive regime deform many plains units suggests that the development of the compressive stresses may have played a vital role in determining when and if surface eruptions of mantle-derived magmas could occur. This would be analogous to the way in which the change with time from extensional to compressive global stresses in the lithosphere of the Moon influenced the viability of erupting magmas from deep mantle sources [7-9]. Analysis: To investigate the relationship between lithospheric stresses and magma eruption conditions [e.g., 9-11] we

  1. Archean crust-mantle geochemical differentiation

    NASA Technical Reports Server (NTRS)

    Tilton, G. R.

    1983-01-01

    Isotope measurements on carbonatite complexes and komatiites can provide information on the geochemical character and geochemical evolution of the mantle, including the sub-continental mantle. Measurements on young samples establish the validity of the method. These are based on Sr, Nd and Pb data from the Tertiary-Mesozoic Gorgona komatiite and Sr and Pb data from the Cretaceous Oka carbonatite complex. In both cases the data describe a LIL element-depleted source similar to that observed presently in MORB. Carbonatite data have been used to study the mantle beneath the Superior Province of the Canadian Shield one billion years (1 AE) ago. The framework for this investigation was established by Bell et al., who showed that large areas of the province appear to be underlain by LIL element-depleted mantle (Sr-85/Sr-86=0.7028) at 1 AE ago. Additionally Bell et al. found four complexes to have higher initial Sr ratios (Sr-87/Sr-86=0.7038), which they correlated with less depleted (bulk earth?) mantle sources, or possibly crustal contamination. Pb isotope relationships in four of the complexes have been studied by Bell et al.

  2. Automated fluence map optimization based on fuzzy inference systems.

    PubMed

    Dias, Joana; Rocha, Humberto; Ventura, Tiago; Ferreira, Brígida; Lopes, Maria do Carmo

    2016-03-01

    The planning of an intensity modulated radiation therapy treatment requires the optimization of the fluence intensities. The fluence map optimization (FMO) is many times based on a nonlinear continuous programming problem, being necessary for the planner to define a priori weights and/or lower bounds that are iteratively changed within a trial-and-error procedure until an acceptable plan is reached. In this work, the authors describe an alternative approach for FMO that releases the human planner from trial-and-error procedures, contributing for the automation of the planning process. The FMO is represented by a voxel-based convex penalty continuous nonlinear model. This model makes use of both weights and lower/upper bounds to guide the optimization process toward interesting solutions that are able to satisfy all the constraints defined for the treatment. All the model's parameters are iteratively changed by resorting to a fuzzy inference system. This system analyzes how far the current solution is from a desirable solution, changing in a completely automated way both weights and lower/upper bounds. The fuzzy inference system is based on fuzzy reasoning that enables the use of common-sense rules within an iterative optimization process. The method is built in two stages: in a first stage, an admissible solution is calculated, trying to guarantee that all the treatment planning constraints are being satisfied. In this first stage, the algorithm tries to improve as much as possible the irradiation of the planning target volumes. In a second stage, the algorithm tries to improve organ sparing, without jeopardizing tumor coverage. The proposed methodology was applied to ten head-and-neck cancer cases already treated in the Portuguese Oncology Institute of Coimbra (IPOCFG) and signalized as complex cases. IMRT treatment was considered, with 7, 9, and 11 equidistant beam angles. It was possible to obtain admissible solutions for all the patients considered and with no

  3. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    PubMed

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  4. Restrictions for the causal inferences in an interferometric system

    NASA Astrophysics Data System (ADS)

    Rossi, R.

    2017-07-01

    Causal discovery algorithms allow for the inference of causal structures from probabilistic relations of random variables. A natural field for the application of this tool is quantum mechanics, where a long-standing debate about the role of causality in the theory has flourished since its early days. In this paper, a causal discovery algorithm is applied in the search for causal models to describe a quantum version of Wheeler's delayed-choice experiment. The outputs explicitly show the restrictions for the introduction of classical concepts in this system. The exclusion of models with two hidden variables is one of them. A consequence of such a constraint is the impossibility to construct a causal model that avoids superluminal causation and assumes an objective view of the wave and particle properties simultaneously.

  5. Automatic control of biomass gasifiers using fuzzy inference systems.

    PubMed

    Sagüés, C; García-Bacaicoa, P; Serrano, S

    2007-03-01

    A fuzzy controller for biomass gasifiers is proposed. Although fuzzy inference systems do not need models to be tuned, a plant model is proposed which has turned out very useful to prove different combinations of membership functions and rules in the proposed fuzzy control. The global control scheme is shown, including the elements to generate the set points for the process variables automatically. There, the type of biomass and its moisture content are the only data which need to be introduced to the controller by a human operator at the beginning of operation to make it work autonomously. The advantages and good performance of the fuzzy controller with the automatic generation of set points, compared to controllers utilising fixed parameters, are demonstrated.

  6. Order restricted inference for oscillatory systems for detecting rhythmic signals.

    PubMed

    Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

    2016-12-15

    Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm CONTACT: peddada@niehs.nih.gov. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  7. Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

    2009-04-01

    Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

  8. Streamflow Forecasting Using Nuero-Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Nanduri, U. V.; Swain, P. C.

    2005-12-01

    The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A

  9. Accurate telemonitoring of Parkinson's disease diagnosis using robust inference system.

    PubMed

    Mandal, Indrajit; Sairam, N

    2013-05-01

    This work presents more precise computational methods for improving the diagnosis of Parkinson's disease based on the detection of dysphonia. New methods are presented for enhanced evaluation and recognize Parkinson's disease affected patients at early stage. Analysis is performed with significant level of error tolerance rate and established our results with corrected T-test. Here new ensembles and other machine learning methods consisting of multinomial logistic regression classifier with Haar wavelets transformation as projection filter that outperform logistic regression is used. Finally a novel and reliable inference system is presented for early recognition of people affected by this disease and presents a new measure of the severity of the disease. Feature selection method is based on Support Vector Machines and ranker search method. Performance analysis of each model is compared to the existing methods and examines the main advancements and concludes with propitious results. Reliable methods are proposed for treating Parkinson's disease that includes sparse multinomial logistic regression, Bayesian network, Support Vector Machines, Artificial Neural Networks, Boosting methods and their ensembles. The study aim at improving the quality of Parkinson's disease treatment by tracking them and reinforce the viability of cost effective, regular and precise telemonitoring application.

  10. Classification of Microarray Data Using Kernel Fuzzy Inference System.

    PubMed

    Kumar, Mukesh; Kumar Rath, Santanu

    2014-01-01

    The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function.

  11. Perturbation biology: inferring signaling networks in cellular systems.

    PubMed

    Molinelli, Evan J; Korkut, Anil; Wang, Weiqing; Miller, Martin L; Gauthier, Nicholas P; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B; Pratilas, Christine A; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology.

  12. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    PubMed Central

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  13. Prediction of Earth rotation parameters by fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Akyilmaz, O.; Kutterer, H.

    2004-09-01

    The short-term prediction of Earth rotation parameters (ERP) (length-of-day and polar motion) is studied up to 10 days by means of ANFIS (adaptive network based fuzzy inference system). The prediction is then extended to 40 days into the future by using the formerly predicted values as input data. The ERP C04 time series with daily values from the International Earth Rotation Service (IERS) serve as the data base. Well-known effects in the ERP series, such as the impact of the tides of the solid Earth and the oceans or seasonal variations of the atmosphere, were removed a priori from the C04 series. The residual series were used for both training and validation of the network. Different network architectures are discussed and compared in order to optimize the network solution. The results of the prediction are analyzed and compared with those of other methods. Short-term ERP values predicted by ANFIS show root-mean-square errors which are equal to or even lower than those from the other considered methods. The presented method is easy to use.

  14. An integrated fuzzy inference based monitoring, diagnostic, and prognostic system

    NASA Astrophysics Data System (ADS)

    Garvey, Dustin

    To date the majority of the research related to the development and application of monitoring, diagnostic, and prognostic systems has been exclusive in the sense that only one of the three areas is the focus of the work. While previous research progresses each of the respective fields, the end result is a variable "grab bag" of techniques that address each problem independently. Also, the new field of prognostics is lacking in the sense that few methods have been proposed that produce estimates of the remaining useful life (RUL) of a device or can be realistically applied to real-world systems. This work addresses both problems by developing the nonparametric fuzzy inference system (NFIS) which is adapted for monitoring, diagnosis, and prognosis and then proposing the path classification and estimation (PACE) model that can be used to predict the RUL of a device that does or does not have a well defined failure threshold. To test and evaluate the proposed methods, they were applied to detect, diagnose, and prognose faults and failures in the hydraulic steering system of a deep oil exploration drill. The monitoring system implementing an NFIS predictor and sequential probability ratio test (SPRT) detector produced comparable detection rates to a monitoring system implementing an autoassociative kernel regression (AAKR) predictor and SPRT detector, specifically 80% vs. 85% for the NFIS and AAKR monitor respectively. It was also found that the NFIS monitor produced fewer false alarms. Next, the monitoring system outputs were used to generate symptom patterns for k-nearest neighbor (kNN) and NFIS classifiers that were trained to diagnose different fault classes. The NFIS diagnoser was shown to significantly outperform the kNN diagnoser, with overall accuracies of 96% vs. 89% respectively. Finally, the PACE implementing the NFIS was used to predict the RUL for different failure modes. The errors of the RUL estimates produced by the PACE-NFIS prognosers ranged from 1

  15. Automatic Road Gap Detection Using Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

    2011-09-01

    Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

  16. A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

    NASA Technical Reports Server (NTRS)

    Hancock, Thomas M., III

    1994-01-01

    This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

  17. MORB mantle hosts the missing Eu (Sr, Nb, Ta and Ti) in the continental crust: New perspectives on crustal growth, crust-mantle differentiation and chemical structure of oceanic upper mantle

    NASA Astrophysics Data System (ADS)

    Niu, Yaoling; O'Hara, Michael J.

    2009-09-01

    We have examined the high quality data of 306 mid-ocean ridge basalt (MORB) glass samples from the East Pacific Rise (EPR), near-EPR seamounts, Pacific Antarctic Ridge (PAR), near-PAR seamounts, Mid-Atlantic Ridge (MAR), and near-MAR seamounts. The data show a correlated variation between Eu/Eu* and Sr/Sr*, and both decrease with decreasing MgO, pointing to the effect of plagioclase crystallization. The observation that samples with MgO > 9.5 wt.% (before plagioclase on the liquidus) show Eu/Eu* > 1 and Sr/Sr* > 1 and that none of the major phases (i.e., olivine, orthopyroxene, clinopyroxene, spinel and garnet) in the sub-ridge mantle melting region can effectively fractionate Eu and Sr from otherwise similarly incompatible elements indicates that the depleted MORB mantle (DMM) possesses excess Sr and Eu, i.e., [Sr/Sr*]DMM > 1 and [Eu/Eu*]DMM > 1. Furthermore, the well-established observation that DNb ≈ DTh, DTa ≈ DU and DTi ≈ DSm during MORB mantle melting, yet primitive MORB melts all have [Nb/Th]PMMORB > 1, [Ta/U]PMMORB > 1 and [Ti/Sm]PMMORB > 1 (where PM indicates primitive mantle normalized), also points to the presence of excess Nb, Ta and Ti in the DMM, i.e., [Nb/Th]PMDMM > 1, [Ta/U]PMDMM > 1 and [Ti/Sm]PMDMM > 1. The excesses of Eu, Sr, Nb, Ta and Ti in the DMM complement the well-known deficiencies of these elements in the bulk continental crust (BCC). These new observations, which support the notion that the DMM and BCC are complementary in terms of the overall abundances of incompatible elements, offer new insights into the crust-mantle differentiation. These observations are best explained by partial melting of amphibolite of MORB protolith during continental collision, which produces andesitic melts with a remarkable compositional (major and trace element abundances as well as key elemental ratios) similarity to the BCC, as revealed by andesites in southern Tibet produced during the India-Asia continental collision. An average amphibolite of MORB

  18. DYNAMICAL INFERENCE FROM A KINEMATIC SNAPSHOT: THE FORCE LAW IN THE SOLAR SYSTEM

    SciTech Connect

    Bovy, Jo; Hogg, David W.; Murray, Iain

    2010-03-10

    If a dynamical system is long-lived and non-resonant (that is, if there is a set of tracers that have evolved independently through many orbital times), and if the system is observed at any non-special time, it is possible to infer the dynamical properties of the system (such as the gravitational force or acceleration law) from a snapshot of the positions and velocities of the tracer population at a single moment in time. In this paper, we describe a general inference technique that solves this problem while allowing (1) the unknown distribution function of the tracer population to be simultaneously inferred and marginalized over, and (2) prior information about the gravitational field and distribution function to be taken into account. As an example, we consider the simplest problem of this kind: we infer the force law in the solar system using only an instantaneous kinematic snapshot (valid at 2009 April 1.0) for the eight major planets. We consider purely radial acceleration laws of the form a{sub r} = -A [r/r{sub 0}]{sup -a}lpha, where r is the distance from the Sun. Using a probabilistic inference technique, we infer 1.989 < alpha < 2.052 (95% interval), largely independent of any assumptions about the distribution of energies and eccentricities in the system beyond the assumption that the system is phase-mixed. Generalizations of the methods used here will permit, among other things, inference of Milky Way dynamics from Gaia-like observations.

  19. Dynamical Inference from a Kinematic Snapshot: The Force Law in the Solar System

    NASA Astrophysics Data System (ADS)

    Bovy, Jo; Murray, Iain; Hogg, David W.

    2010-03-01

    If a dynamical system is long-lived and non-resonant (that is, if there is a set of tracers that have evolved independently through many orbital times), and if the system is observed at any non-special time, it is possible to infer the dynamical properties of the system (such as the gravitational force or acceleration law) from a snapshot of the positions and velocities of the tracer population at a single moment in time. In this paper, we describe a general inference technique that solves this problem while allowing (1) the unknown distribution function of the tracer population to be simultaneously inferred and marginalized over, and (2) prior information about the gravitational field and distribution function to be taken into account. As an example, we consider the simplest problem of this kind: we infer the force law in the solar system using only an instantaneous kinematic snapshot (valid at 2009 April 1.0) for the eight major planets. We consider purely radial acceleration laws of the form ar = -A [r/r 0]-α, where r is the distance from the Sun. Using a probabilistic inference technique, we infer 1.989 < α < 2.052 (95% interval), largely independent of any assumptions about the distribution of energies and eccentricities in the system beyond the assumption that the system is phase-mixed. Generalizations of the methods used here will permit, among other things, inference of Milky Way dynamics from Gaia-like observations.

  20. An expert system shell for inferring vegetation characteristics: Prototype help system (Task 1)

    NASA Technical Reports Server (NTRS)

    1993-01-01

    The NASA Vegetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. A prototype of the VEG subgoal HELP.SYSTEM has been completed and the Help System has been added to the VEG system. It is loaded when the user first clicks on the HELP.SYSTEM option in the Tool Box Menu. The Help System provides a user tool to support needed user information. It also provides interactive tools the scientist may use to develop new help messages and to modify existing help messages that are attached to VEG screens. The system automatically manages system and file operations needed to preserve new or modified help messages. The Help System was tested both as a help system development and a help system user tool.

  1. HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems.

    PubMed

    Kim, J; Kasabov, N

    1999-11-01

    This paper proposes an adaptive neuro-fuzzy system, HyFIS (Hybrid neural Fuzzy Inference System), for building and optimising fuzzy models. The proposed model introduces the learning power of neural networks to fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training examples by a hybrid learning scheme comprised of two phases: rule generation phase from data; and rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate the performance and applicability of the proposed neuro-fuzzy hybrid model, extensive simulation studies of nonlinear complex dynamic systems are carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction and control of nonlinear dynamical systems. Two benchmark case studies are used to demonstrate that the proposed HyFIS system is a superior neuro-fuzzy modelling technique.

  2. Artificial frame filling using adaptive neural fuzzy inference system for particle image velocimetry dataset

    NASA Astrophysics Data System (ADS)

    Akdemir, Bayram; Doǧan, Sercan; Aksoy, Muharrem H.; Canli, Eyüp; Özgören, Muammer

    2015-03-01

    Liquid behaviors are very important for many areas especially for Mechanical Engineering. Fast camera is a way to observe and search the liquid behaviors. Camera traces the dust or colored markers travelling in the liquid and takes many pictures in a second as possible as. Every image has large data structure due to resolution. For fast liquid velocity, there is not easy to evaluate or make a fluent frame after the taken images. Artificial intelligence has much popularity in science to solve the nonlinear problems. Adaptive neural fuzzy inference system is a common artificial intelligence in literature. Any particle velocity in a liquid has two dimension speed and its derivatives. Adaptive Neural Fuzzy Inference System has been used to create an artificial frame between previous and post frames as offline. Adaptive neural fuzzy inference system uses velocities and vorticities to create a crossing point vector between previous and post points. In this study, Adaptive Neural Fuzzy Inference System has been used to fill virtual frames among the real frames in order to improve image continuity. So this evaluation makes the images much understandable at chaotic or vorticity points. After executed adaptive neural fuzzy inference system, the image dataset increase two times and has a sequence as virtual and real, respectively. The obtained success is evaluated using R2 testing and mean squared error. R2 testing has a statistical importance about similarity and 0.82, 0.81, 0.85 and 0.8 were obtained for velocities and derivatives, respectively.

  3. Evaluating data-driven causal inference techniques in noisy physical and ecological systems

    NASA Astrophysics Data System (ADS)

    Tennant, C.; Larsen, L.

    2016-12-01

    Causal inference from observational time series challenges traditional approaches for understanding processes and offers exciting opportunities to gain new understanding of complex systems where nonlinearity, delayed forcing, and emergent behavior are common. We present a formal evaluation of the performance of convergent cross-mapping (CCM) and transfer entropy (TE) for data-driven causal inference under real-world conditions. CCM is based on nonlinear state-space reconstruction, and causality is determined by the convergence of prediction skill with an increasing number of observations of the system. TE is the uncertainty reduction based on transition probabilities of a pair of time-lagged variables. With TE, causal inference is based on asymmetry in information flow between the variables. Observational data and numerical simulations from a number of classical physical and ecological systems: atmospheric convection (the Lorenz system), species competition (patch-tournaments), and long-term climate change (Vostok ice core) were used to evaluate the ability of CCM and TE to infer causal-relationships as data series become increasingly corrupted by observational (instrument-driven) or process (model-or -stochastic-driven) noise. While both techniques show promise for causal inference, TE appears to be applicable to a wider range of systems, especially when the data series are of sufficient length to reliably estimate transition probabilities of system components. Both techniques also show a clear effect of observational noise on causal inference. For example, CCM exhibits a negative logarithmic decline in prediction skill as the noise level of the system increases. Changes in TE strongly depend on noise type and which variable the noise was added to. The ability of CCM and TE to detect driving influences suggest that their application to physical and ecological systems could be transformative for understanding driving mechanisms as Earth systems undergo change.

  4. Parameter and Structure Inference for Nonlinear Dynamical Systems

    NASA Technical Reports Server (NTRS)

    Morris, Robin D.; Smelyanskiy, Vadim N.; Millonas, Mark

    2006-01-01

    A great many systems can be modeled in the non-linear dynamical systems framework, as x = f(x) + xi(t), where f() is the potential function for the system, and xi is the excitation noise. Modeling the potential using a set of basis functions, we derive the posterior for the basis coefficients. A more challenging problem is to determine the set of basis functions that are required to model a particular system. We show that using the Bayesian Information Criteria (BIC) to rank models, and the beam search technique, that we can accurately determine the structure of simple non-linear dynamical system models, and the structure of the coupling between non-linear dynamical systems where the individual systems are known. This last case has important ecological applications.

  5. Seizure detection in intracranial EEG using a fuzzy inference system.

    PubMed

    Aarabi, A; Fazel-Rezai, R; Aghakhani, Y

    2009-01-01

    In this paper, we present a fuzzy rule-based system for the automatic detection of seizures in the intracranial EEG (IEEG) recordings. A total of 302.7 hours of the IEEG with 78 seizures, recorded from 21 patients aged between 10 and 47 years were used for the evaluation of the system. After preprocessing, temporal, spectral, and complexity features were extracted from the segmented IEEGs. The results were thresholded using the statistics of a reference window and integrated spatio-temporally using a fuzzy rule-based decision making system. The system yielded a sensitivity of 98.7%, a false detection rate of 0.27/h, and an average detection latency of 11 s. The results from the automatic system correlate well with the visual analysis of the seizures by the expert. This system may serve as a good seizure detection tool for monitoring long-term IEEG with relatively high sensitivity and low false detection rate.

  6. Bayesian Inference Networks and Spreading Activation in Hypertext Systems.

    ERIC Educational Resources Information Center

    Savoy, Jacques

    1992-01-01

    Describes a method based on Bayesian networks for searching hypertext systems. Discussion covers the use of Bayesian networks for structuring index terms and representing user information needs; use of link semantics based on constrained spreading activation to find starting points for browsing; and evaluation of a prototype system. (64…

  7. New developments of a knowledge based system (VEG) for inferring vegetation characteristics

    NASA Technical Reports Server (NTRS)

    Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

    1992-01-01

    An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

  8. FINDS: A fault inferring nonlinear detection system. User's guide

    NASA Technical Reports Server (NTRS)

    Lancraft, R. E.; Caglayan, A. K.

    1983-01-01

    The computer program FINDS is written in FORTRAN-77, and is intended for operation on a VAX 11-780 or 11-750 super minicomputer, using the VMS operating system. The program detects, isolates, and compensates for failures in navigation aid instruments and onboard flight control and navigation sensors of a Terminal Configured Vehicle aircraft in a Microwave Landing System environment. In addition, FINDS provides sensor fault tolerant estimates for the aircraft states which are then used by an automatic guidance and control system to land the aircraft along a prescribed path. FINDS monitors for failures by evaluating all sensor outputs simultaneously using the nonlinear analytic relationships between the various sensor outputs arising from the aircraft point mass equations of motion. Hence, FINDS is an integrated sensor failure detection and isolation system.

  9. An expert system shell for inferring vegetation characteristics: The learning system (tasks C and D)

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann; Harrison, Patrick R.

    1992-01-01

    This report describes the implementation of a learning system that uses a data base of historical cover type reflectance data taken at different solar zenith angles and wavelengths to learn class descriptions of classes of cover types. It has been integrated with the VEG system and requires that the VEG system be loaded to operate. VEG is the NASA VEGetation workbench - an expert system for inferring vegetation characteristics from reflectance data. The learning system provides three basic options. Using option one, the system learns class descriptions of one or more classes. Using option two, the system learns class descriptions of one or more classes and then uses the learned classes to classify an unknown sample. Using option three, the user can test the system's classification performance. The learning system can also be run in an automatic mode. In this mode, options two and three are executed on each sample from an input file. The system was developed using KEE. It is menu driven and contains a sophisticated window and mouse driven interface which guides the user through various computations. Input and output file management and data formatting facilities are also provided.

  10. Conditional Inference and Logic for Intelligent Systems: A Theory of Measure-Free Conditioning

    DTIC Science & Technology

    1991-08-01

    4 TITLE AND SUBTITLE 5 FUNDING NUMBERS CONDITIONAL INFERENCE AND LOGIC FOR INTELLIGENT SYSTEMS PR: ZE90 PR: ZW40 A Theory of Measure-Free Conditioning...200 UNCLASSIFIED tf F I CONDIT[ONAL INFERENCE AND LOGIC FOR INTELIUGENT SYSTEMS: I, A THEORY OF MEASURE-FREE CONDTONING F by L R. Goodman Command and...complete and satisfactory theory of "measure-free" conditioning. If the concept of "conditional event" can be formalized and a suitable algebra of

  11. Rifting process of the Izu-Ogasawara-Mariana arc-backarc system inferred from active source seismic studies

    NASA Astrophysics Data System (ADS)

    Takahashi, N.; Kodaira, S.; Miura, S.; Sato, T.; Yamashita, M.; No, T.; Takizawa, K.; Kaiho, Y.; Kaneda, Y.

    2008-12-01

    The Izu-Ogasawara-Mariana (IBM) arc-backarc system has continued the crustal growth through crustal thickening by magmatic activities and crustal thinning by backarc opening. Tatsumi et al (2008) proposed petrological crustal growth model started from basaltic magmas rising from the slab, and showed the consistency with the seismic velocity model. Although crustal growth by the crustal thickening are modeled, crustal structural change by the backarc opening are not still unknown yet. The Shikoku Basin and Parece Vela Basin were formed by the backarc opening during approximately 15-30 Ma. Since 6 Ma, the Mariana Trough has opened and the stage already moved to spreading process from rifting process. In the northern Izu-Ogasawara arc, the Sumisu rift is in the initial rifting stage. Therefore, understanding of the crustal change by the backarc opening from rifting to spreading is indispensable to know the crustal growth of whole Izu-Ogasawara-Mariana island arc. Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has carried out seismic studies using a multichannel reflection survey system and ocean bottom seismographs (OBSs) around the IBM arc since 2003 (Takahashi et al., 2007; Kodaira et al., 2007; Takahashi et al., 2008; Kodaira et al., 2008). We already obtained eight P-wave velocity models across the IBM arc and these structures record the crustal structural change during the backarc opening process from the rifting stage to the spreading stage. As the results, we identified characteristics of the crustal structural change accompanied with backarc opening as follows. (1) Beneath the initial rifting stage without normal faults, for example, in the northern tip of the Mariana Trough, crustal thickening are identified. (2) Beneath the initial rifting stage with normal faults, for example, in the Sumisu Rift, the crustal thickness is almost similar to that beneath the volcanic front. Although an existence of the crust-mantle transition layer with

  12. Earth system sensitivity inferred from Pliocene modelling and data

    USGS Publications Warehouse

    Lunt, D.J.; Haywood, A.M.; Schmidt, G.A.; Salzmann, U.; Valdes, P.J.; Dowsett, H.J.

    2010-01-01

    Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earths climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere-ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30-50% greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. ?? 2010 Macmillan Publishers Limited. All rights reserved.

  13. Isotopic abundances - Inferences on solar system and planetary evolution

    NASA Astrophysics Data System (ADS)

    Wasserburg, G. J.

    1987-12-01

    For matter that has been removed from a region of nucleosynthetic activity and the effects of interactions with nuclear active particles, the only changes in nuclear abundances that can occur in an isolated system derive from the decay of radioactive nuclei of an element to yield the nucleus of another element. These two related nuclei furnish the absolute chronometers of geologic and cosmic time, through the decay of spontaneously radioactive parent nuclei and the accumulation of daughter nuclei. For systems related to such cosmic processes as the formation of the solar system from the precursor interstellar medium, and involving the very early evolution of the sun, there may arise considerable complexity, due to the intrinsic isotopic heterogeneity of the medium and the presence of short-lived nuclei.

  14. Asymptotic inference in system identification for the atom maser.

    PubMed

    Catana, Catalin; van Horssen, Merlijn; Guta, Madalin

    2012-11-28

    System identification is closely related to control theory and plays an increasing role in quantum engineering. In the quantum set-up, system identification is usually equated to process tomography, i.e. estimating a channel by probing it repeatedly with different input states. However, for quantum dynamical systems such as quantum Markov processes, it is more natural to consider the estimation based on continuous measurements of the output, with a given input that may be stationary. We address this problem using asymptotic statistics tools, for the specific example of estimating the Rabi frequency of an atom maser. We compute the Fisher information of different measurement processes as well as the quantum Fisher information of the atom maser, and establish the local asymptotic normality of these statistical models. The statistical notions can be expressed in terms of spectral properties of certain deformed Markov generators, and the connection to large deviations is briefly discussed.

  15. Data-driven sensitivity inference for Thomson scattering electron density measurement systems.

    PubMed

    Fujii, Keisuke; Yamada, Ichihiro; Hasuo, Masahiro

    2017-01-01

    We developed a method to infer the calibration parameters of multichannel measurement systems, such as channel variations of sensitivity and noise amplitude, from experimental data. We regard such uncertainties of the calibration parameters as dependent noise. The statistical properties of the dependent noise and that of the latent functions were modeled and implemented in the Gaussian process kernel. Based on their statistical difference, both parameters were inferred from the data. We applied this method to the electron density measurement system by Thomson scattering for the Large Helical Device plasma, which is equipped with 141 spatial channels. Based on the 210 sets of experimental data, we evaluated the correction factor of the sensitivity and noise amplitude for each channel. The correction factor varies by ≈10%, and the random noise amplitude is ≈2%, i.e., the measurement accuracy increases by a factor of 5 after this sensitivity correction. The certainty improvement in the spatial derivative inference was demonstrated.

  16. Efficient Inference of Parsimonious Phenomenological Models of Cellular Dynamics Using S-Systems and Alternating Regression

    PubMed Central

    Daniels, Bryan C.; Nemenman, Ilya

    2015-01-01

    The nonlinearity of dynamics in systems biology makes it hard to infer them from experimental data. Simple linear models are computationally efficient, but cannot incorporate these important nonlinearities. An adaptive method based on the S-system formalism, which is a sensible representation of nonlinear mass-action kinetics typically found in cellular dynamics, maintains the efficiency of linear regression. We combine this approach with adaptive model selection to obtain efficient and parsimonious representations of cellular dynamics. The approach is tested by inferring the dynamics of yeast glycolysis from simulated data. With little computing time, it produces dynamical models with high predictive power and with structural complexity adapted to the difficulty of the inference problem. PMID:25806510

  17. Data-driven sensitivity inference for Thomson scattering electron density measurement systems

    NASA Astrophysics Data System (ADS)

    Fujii, Keisuke; Yamada, Ichihiro; Hasuo, Masahiro

    2017-01-01

    We developed a method to infer the calibration parameters of multichannel measurement systems, such as channel variations of sensitivity and noise amplitude, from experimental data. We regard such uncertainties of the calibration parameters as dependent noise. The statistical properties of the dependent noise and that of the latent functions were modeled and implemented in the Gaussian process kernel. Based on their statistical difference, both parameters were inferred from the data. We applied this method to the electron density measurement system by Thomson scattering for the Large Helical Device plasma, which is equipped with 141 spatial channels. Based on the 210 sets of experimental data, we evaluated the correction factor of the sensitivity and noise amplitude for each channel. The correction factor varies by ≈10%, and the random noise amplitude is ≈2%, i.e., the measurement accuracy increases by a factor of 5 after this sensitivity correction. The certainty improvement in the spatial derivative inference was demonstrated.

  18. Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

    PubMed Central

    Zhao, Jiangsan; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A.; Nakhforoosh, Alireza

    2017-01-01

    Abstract Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. PMID:28168270

  19. Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

    PubMed

    Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A; Nakhforoosh, Alireza

    2017-02-01

    Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  20. Field Demonstration of a Broadband Acoustical Backscattering System Mounted on a REMUS-100 for Inferences of Zooplankton Size and Abundance

    DTIC Science & Technology

    2012-09-30

    Backscattering System Mounted on a REMUS-100 for Inferences of Zooplankton Size and Abundance Andone C. Lavery Department of Applied Ocean Physics and...SUBTITLE Field Demonstration of a Broadband Acoustical Backscattering System Mounted on a REMUS-100 for Inferences of Zooplankton Size and Abundance 5a...of this REMUS- mounted broadband backscattering system with regards to inferring fish and zooplankton distribution, size and abundance in comparison

  1. PLY: A System of Plausibility Inference with a Probabilistic Basis,

    DTIC Science & Technology

    1982-12-01

    a hard time estimating. This estimation problem has been encountered in both the PROSPECTOR project [Hart 77], which deals with mineral exploration consulting...PROSPECTOR [Hart 77, Duda 79] is a computer system designed to aid mineral exploration . It takes in user information and then tells what and where...1976. [Duda 79] Duda, R., Hart, P., Konollge, K., Reboh, R. A Computer-Based Consultant for Mineral Exploration . Final Report, SRI Project 6415, SRI

  2. Shallow plumbing systems inferred from spatial analysis of pockmark arrays

    NASA Astrophysics Data System (ADS)

    Maia, A.; Cartwright, J. A.; Andersen, E.

    2016-12-01

    This study describes and analyses an extraordinary array of pockmarks at the modern seabed of the Lower Congo Basin (offshore Angola), in order to understand the fluid migration routes and shallow plumbing system of the area. The 3D seismic visualization of feeding conduits (pipes) allowed the identification of the source interval for the fluids expelled during pockmark formation. Spatial statistics are used to show the relationship between the underlying (polarised) polygonal fault (PPFs) patterns and seabed pockmarks distributions. Our results show PPFs control the linear arrangement of pockmarks and feeder pipes along fault strike, but faults do not act as conduits. Spatial statistics also revealed pockmark occurrence is not considered to be random, especially at short distances to nearest neighbours (<200m) where anti-clustering distributions suggest the presence of an exclusion zone around each pockmark in which no other pockmark will form. The results of this study are relevant for the understanding of shallow fluid plumbing systems in offshore settings, with implications on our current knowledge of overall fluid flow systems in hydrocarbon-rich continental margins.

  3. Hydroclimatic Extremes: Inferences and Prediction from a Dynamical Systems Perspective

    NASA Astrophysics Data System (ADS)

    Lall, U.

    2015-12-01

    Hydroclimatic extremes , such as major floods and droughts, or periods with a high frequency of clustered tornadoes, fires or cyclones, have often been thought of as random, rare events, and much of the literature on these topics has been obsessed with the estimation of the tail probabilities (e.g., the 100 year event) of these processes. It has taken the "acceptance" of the notion of climate change to question whether the machinery developed for such estimation or even the associated questions are reasonable. However, much of the literature that has evolved since has focused on how to detect and model changes in these probabilities using a variety of methods. In this talk, I will argue that while such efforts may be useful in a certain, outdated context, they are not necessarily leading to an improvement in eihter the science of the application of the science to disaster risk mitigation. I develop an argument that hydroclimatic extremes result from an organization of the associated global and local dynamical systems that leads to the systems trajectories locking into a particular region of state space. Such excursions could be considered as rare events, in their ultimate expression, or in their frequency of visitation and persistence in those states. An open question is whether the dynamics of the system under such conditions are marked by high or low predictabilty in the Lyapunov sense. A characterization of the dimension and predictability of hydroclimatic extremes would allow us to better understand the potential implications of climate change, and also of whether or not a regional drought or similar persistent regime is likely to dissipate or grow.

  4. An Incremental Type Inference System for the Programming Language Id

    DTIC Science & Technology

    1990-11-01

    ReerhDp.of Navy DORESS ( City . State, and ZIP Cod*) 7b. ADDRESS (CC)’. State, and ZIP Caade) 45 Technology Square Information Systems Program ambridge...AP.PA/ DOD I OORESS( City , Stat. and ZIP Code) 10. SOURCE OF FUNDING NUMBERS 400-ilsnGBld.M ’so. I TASK IWORK UNIT 40 Wlsn lv.ELMET O.EN-NO. ACCEssioN...programming imparts a nice and clean structure to programs and hides details and clutter to bring out just the basic mathematical properties that the

  5. An expert system shell for inferring vegetation characteristics: Implementation of additional techniques (task E)

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann

    1992-01-01

    The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented. Some techniques operate on sample data at a single wavelength. The techniques previously incorporated in VEG for other subgoals operated on data at a single wavelength so implementing the additional single wavelength techniques required no changes to the structure of VEG. Two techniques which use data at multiple wavelengths to infer proportion ground cover were also implemented. This work involved modifying the structure of VEG so that multiple wavelength techniques could be incorporated. All the new techniques were tested using both the VEG 'Research Mode' and the 'Automatic Mode.'

  6. Variational mean-field algorithm for efficient inference in large systems of stochastic differential equations.

    PubMed

    Vrettas, Michail D; Opper, Manfred; Cornford, Dan

    2015-01-01

    This work introduces a Gaussian variational mean-field approximation for inference in dynamical systems which can be modeled by ordinary stochastic differential equations. This new approach allows one to express the variational free energy as a functional of the marginal moments of the approximating Gaussian process. A restriction of the moment equations to piecewise polynomial functions, over time, dramatically reduces the complexity of approximate inference for stochastic differential equation models and makes it comparable to that of discrete time hidden Markov models. The algorithm is demonstrated on state and parameter estimation for nonlinear problems with up to 1000 dimensional state vectors and compares the results empirically with various well-known inference methodologies.

  7. Explorations of electric current system in solar active regions. I - Empirical inferences of the current flows

    NASA Technical Reports Server (NTRS)

    Ding, Y. J.; Hong, Q. F.; Hagyard, M. J.; Deloach, A. C.; Liu, X. P.

    1987-01-01

    Techniques to identify sources of electric current systems and their channels of flow in solar active regions are explored. Measured photospheric vector magnetic fields together with high-resolution white-light and H-alpha filtergrams provide the data base to derive the current systems in the photosphere and chromosphere. As an example, the techniques are then applied to infer current systems in AR 2372 in early April 1980.

  8. Large-Scale Optimization for Bayesian Inference in Complex Systems

    SciTech Connect

    Willcox, Karen; Marzouk, Youssef

    2013-11-12

    The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of the SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their

  9. The state of the atmosphere as inferred from the FGGE satellite observing systems during SOP-1

    NASA Technical Reports Server (NTRS)

    Halem, M.; Kalnay, E.; Baker, W. E.; Atlas, R.

    1981-01-01

    Data assimilation experiments were performed to test the influence of different elements of the satellite observing systems. Results from some of the experiments are presented. These findings show that the FGGE satellite systems are able to infer the three-dimensional motion field and improve the representation of the large-scale state of the atmosphere. Preliminary results of the forecast impact of the FGGE data sets are also presented.

  10. Review of Medical Image Classification using the Adaptive Neuro-Fuzzy Inference System

    PubMed Central

    Hosseini, Monireh Sheikh; Zekri, Maryam

    2012-01-01

    Image classification is an issue that utilizes image processing, pattern recognition and classification methods. Automatic medical image classification is a progressive area in image classification, and it is expected to be more developed in the future. Because of this fact, automatic diagnosis can assist pathologists by providing second opinions and reducing their workload. This paper reviews the application of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier in medical image classification during the past 16 years. ANFIS is a fuzzy inference system (FIS) implemented in the framework of an adaptive fuzzy neural network. It combines the explicit knowledge representation of an FIS with the learning power of artificial neural networks. The objective of ANFIS is to integrate the best features of fuzzy systems and neural networks. A brief comparison with other classifiers, main advantages and drawbacks of this classifier are investigated. PMID:23493054

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

    PubMed Central

    Murakami, Yohei

    2014-01-01

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

  12. Bayesian parameter inference and model selection by population annealing in systems biology.

    PubMed

    Murakami, Yohei

    2014-01-01

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

  13. The relative roles of visuospatial and linguistic working memory systems in generating inferences during visual narrative comprehension.

    PubMed

    Magliano, Joseph P; Larson, Adam M; Higgs, Karyn; Loschky, Lester C

    2016-02-01

    This study investigated the relative roles of visuospatial versus linguistic working memory (WM) systems in the online generation of bridging inferences while viewers comprehend visual narratives. We contrasted these relative roles in the visuospatial primacy hypothesis versus the shared (visuospatial & linguistic) systems hypothesis, and tested them in 3 experiments. Participants viewed picture stories containing multiple target episodes consisting of a beginning state, a bridging event, and an end state, respectively, and the presence of the bridging event was manipulated. When absent, viewers had to infer the bridging-event action to comprehend the end-state image. A pilot study showed that after viewing the end-state image, participants' think-aloud protocols contained more inferred actions when the bridging event was absent than when it was present. Likewise, Experiment 1 found longer viewing times for the end-state image when the bridging-event image was absent, consistent with viewing times revealing online inference generation processes. Experiment 2 showed that both linguistic and visuospatial WM loads attenuated the inference viewing time effect, consistent with the shared systems hypothesis. Importantly, however, Experiment 3 found that articulatory suppression did not attenuate the inference viewing time effect, indicating that (sub)vocalization did not support online inference generation during visual narrative comprehension. Thus, the results support a shared-systems hypothesis in which both visuospatial and linguistic WM systems support inference generation in visual narratives, with the linguistic WM system operating at a deeper level than (sub)vocalization.

  14. FINDS: A fault inferring nonlinear detection system programmers manual, version 3.0

    NASA Technical Reports Server (NTRS)

    Lancraft, R. E.

    1985-01-01

    Detailed software documentation of the digital computer program FINDS (Fault Inferring Nonlinear Detection System) Version 3.0 is provided. FINDS is a highly modular and extensible computer program designed to monitor and detect sensor failures, while at the same time providing reliable state estimates. In this version of the program the FINDS methodology is used to detect, isolate, and compensate for failures in simulated avionics sensors used by the Advanced Transport Operating Systems (ATOPS) Transport System Research Vehicle (TSRV) in a Microwave Landing System (MLS) environment. It is intended that this report serve as a programmers guide to aid in the maintenance, modification, and revision of the FINDS software.

  15. Assessing water quality in rivers with fuzzy inference systems: a case study.

    PubMed

    Ocampo-Duque, William; Ferré-Huguet, Núria; Domingo, José L; Schuhmacher, Marta

    2006-08-01

    In recent years, fuzzy-logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental problems. In the present study, a methodology based on fuzzy inference systems (FIS) to assess water quality is proposed. A water quality index calculated with fuzzy reasoning has been developed. The relative importance of water quality indicators involved in the fuzzy inference process has been dealt with a multi-attribute decision-aiding method. The potential application of the fuzzy index has been tested with a case study. A data set collected from the Ebro River (Spain) by two different environmental protection agencies has been used. The current findings, managed within a geographic information system, clearly agree with official reports and expert opinions about the pollution problems in the studied area. Therefore, this methodology emerges as a suitable and alternative tool to be used in developing effective water management plans.

  16. From free energy measurements to thermodynamic inference in nonequilibrium small systems

    NASA Astrophysics Data System (ADS)

    Alemany, A.; Ribezzi-Crivellari, M.; Ritort, F.

    2015-07-01

    Fluctuation theorems (FTs), such as the Crooks or Jarzynski equalities (JEs), have become an important tool in single-molecule biophysics where they allow experimentalists to exploit thermal fluctuations and measure free-energy differences from non-equilibrium pulling experiments. The rich phenomenology of biomolecular systems has stimulated the development of extensions to the standard FTs, to encompass different experimental situations. Here we discuss an extension of the Crooks fluctuation relation that allows the thermodynamic characterization of kinetic molecular states. This extension can be connected to the generalized JE under feedback. Finally we address the recently introduced concept of thermodynamic inference or how FTs can be used to extract the total entropy production distribution in nonequilibrium systems from partial entropy production measurements. We discuss the significance of the concept of effective temperature in this context and show how thermodynamic inference provides a unifying comprehensive picture in several nonequilibrium problems.

  17. MI-ANFIS: A Multiple Instance Adaptive Neuro-Fuzzy Inference System

    DTIC Science & Technology

    2015-08-02

    modeling power of neural networks and fuzzy logic into an adaptive inference system. Neural networks deal with imprecise data by training, while... fuzzy logic can deal with the uncertainty of human cognition [2]. ANFIS offers an alternative to rules’ identification. While Mamdani [3] and Sugeno [4...premise parameters. Layer 2 is a fixed layer, every node computes the product of all incoming inputs. In the context of multiple instance fuzzy logic

  18. Perceptual inference.

    PubMed

    Aggelopoulos, Nikolaos C

    2015-08-01

    Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience.

  19. Inference system using softcomputing and mixed data applied in metabolic pathway datamining.

    PubMed

    Arredondo, Tomás; Candel, Diego; Leiva, Mauricio; Dombrovskaia, Lioubov; Agulló, Loreine; Seeger, Michael

    2012-01-01

    This paper describes the development of an inference system used for the identification of genes that encode enzymes of metabolic pathways. Input sequence alignment values are used to classify the best candidate genes for inclusion in a metabolic pathway map. The system workflow allows the user to provide feedback, which is stored in conjunction with analysed sequences for periodic retraining. The construction of the system involved the study of several different classifiers with various topologies, data sets and parameter normalisation data models. Experimental results show an excellent prediction capability with the classifiers trained with mixed data providing the best results.

  20. Inference of biological S-system using the separable estimation method and the genetic algorithm.

    PubMed

    Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, W J

    2012-01-01

    Reconstruction of a biological system from its experimental time series data is a challenging task in systems biology. The S-system which consists of a group of nonlinear ordinary differential equations (ODEs) is an effective model to characterize molecular biological systems and analyze the system dynamics. However, inference of S-systems without the knowledge of system structure is not a trivial task due to its nonlinearity and complexity. In this paper, a pruning separable parameter estimation algorithm (PSPEA) is proposed for inferring S-systems. This novel algorithm combines the separable parameter estimation method (SPEM) and a pruning strategy, which includes adding an l₁ regularization term to the objective function and pruning the solution with a threshold value. Then, this algorithm is combined with the continuous genetic algorithm (CGA) to form a hybrid algorithm that owns the properties of these two combined algorithms. The performance of the pruning strategy in the proposed algorithm is evaluated from two aspects: the parameter estimation error and structure identification accuracy. The results show that the proposed algorithm with the pruning strategy has much lower estimation error and much higher identification accuracy than the existing method.

  1. ChemDIS: a chemical-disease inference system based on chemical-protein interactions.

    PubMed

    Tung, Chun-Wei

    2015-01-01

    The characterization of toxicities associated with environmental and industrial chemicals is required for risk assessment. However, we lack the toxicological data for a large portion of chemicals due to the high cost of experiments for a huge number of chemicals. The development of computational methods for identifying potential risks associated with chemicals is desirable for generating testable hypothesis to accelerate the hazard identification process. A chemical-disease inference system named ChemDIS was developed to facilitate hazard identification for chemicals. The chemical-protein interactions from a large database STITCH and protein-disease relationship from disease ontology and disease ontology lite were utilized for chemical-protein-disease inferences. Tools with user-friendly interfaces for enrichment analysis of functions, pathways and diseases were implemented and integrated into ChemDIS. An analysis on maleic acid and sibutramine showed that ChemDIS could be a useful tool for the identification of potential functions, pathways and diseases affected by poorly characterized chemicals. ChemDIS is an integrated chemical-disease inference system for poorly characterized chemicals with potentially affected functions and pathways for experimental validation. ChemDIS server is freely accessible at http://cwtung.kmu.edu.tw/chemdis.

  2. Path-space variational inference for non-equilibrium coarse-grained systems

    SciTech Connect

    Harmandaris, Vagelis; Katsoulakis, Markos; Plecháč, Petr

    2016-06-01

    In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

  3. Inference of gene regulatory networks using S-system: a unified approach.

    PubMed

    Wang, H; Qian, L; Dougherty, E

    2010-03-01

    With the increased availability of DNA microarray time-series data, it is possible to discover dynamic gene regulatory networks (GRNs). S-system is a promising model to capture the rich dynamics of GRNs. However, owing to the complexity of the inference problem and limited number of available data comparing to the number of unknown kinetic parameters, S-system can only be applied to a very small GRN with few parameters. This significantly limits its applications. A unified approach to infer GRNs using the S-system model is proposed. In order to discover the structure of large-scale GRNs, a simplified S-system model is proposed that enables fast parameter estimation to determine the major gene interactions. If a detailed S-system model is desirable for a subset of genes, a two-step method is proposed where the range of the parameters will be determined first using genetic programming and recursive least square estimation. Then the mean values of the parameters will be estimated using a multi-dimensional optimisation algorithm. Both the downhill simplex algorithm and modified Powell algorithm are tested for multi-dimensional optimisation. A 50-dimensional synthetic model with 51 parameters for each gene is tested for the applicability of the simplified S-system model. In addition, real measurement data pertaining to yeast protein synthesis are used to demonstrate the effectiveness of the proposed two-step method to identify the detailed interactions among genes in small GRNs.

  4. Video-based cargo fire verification system with fuzzy inference engine for commercial aircraft

    NASA Astrophysics Data System (ADS)

    Sadok, Mokhtar; Zakrzewski, Radek; Zeliff, Bob

    2005-02-01

    Conventional smoke detection systems currently installed onboard aircraft are often subject to high rates of false alarms. Under current procedures, whenever an alarm is issued the pilot is obliged to release fire extinguishers and to divert to the nearest airport. Aircraft diversions are costly and dangerous in some situations. A reliable detection system that minimizes false-alarm rate and allows continuous monitoring of cargo compartments is highly desirable. A video-based system has been recently developed by Goodrich Corporation to address this problem. The Cargo Fire Verification System (CFVS) is a multi camera system designed to provide live stream video to the cockpit crew and to perform hotspot, fire, and smoke detection in aircraft cargo bays. In addition to video frames, the CFVS uses other sensor readings to discriminate between genuine events such as fire or smoke and nuisance alarms such as fog or dust. A Mamdani-type fuzzy inference engine is developed to provide approximate reasoning for decision making. In one implementation, Gaussian membership functions for frame intensity-based features, relative humidity, and temperature are constructed using experimental data to form the system inference engine. The CFVS performed better than conventional aircraft smoke detectors in all standardized tests.

  5. Nested sampling for parameter inference in systems biology: application to an exemplar circadian model.

    PubMed

    Aitken, Stuart; Akman, Ozgur E

    2013-07-30

    Model selection and parameter inference are complex problems that have yet to be fully addressed in systems biology. In contrast with parameter optimisation, parameter inference computes both the parameter means and their standard deviations (or full posterior distributions), thus yielding important information on the extent to which the data and the model topology constrain the inferred parameter values. We report on the application of nested sampling, a statistical approach to computing the Bayesian evidence Z, to the inference of parameters, and the estimation of log Z in an established model of circadian rhythms. A ten-fold difference in the coefficient of variation between degradation and transcription parameters is demonstrated. We further show that the uncertainty remaining in the parameter values is reduced by the analysis of increasing numbers of circadian cycles of data, up to 4 cycles, but is unaffected by sampling the data more frequently. Novel algorithms for calculating the likelihood of a model, and a characterisation of the performance of the nested sampling algorithm are also reported. The methods we develop considerably improve the computational efficiency of the likelihood calculation, and of the exploratory step within nested sampling. We have demonstrated in an exemplar circadian model that the estimates of posterior parameter densities (as summarised by parameter means and standard deviations) are influenced predominately by the length of the time series, becoming more narrowly constrained as the number of circadian cycles considered increases. We have also shown the utility of the coefficient of variation for discriminating between highly-constrained and less-well constrained parameters.

  6. Nested sampling for parameter inference in systems biology: application to an exemplar circadian model

    PubMed Central

    2013-01-01

    Background Model selection and parameter inference are complex problems that have yet to be fully addressed in systems biology. In contrast with parameter optimisation, parameter inference computes both the parameter means and their standard deviations (or full posterior distributions), thus yielding important information on the extent to which the data and the model topology constrain the inferred parameter values. Results We report on the application of nested sampling, a statistical approach to computing the Bayesian evidence Z, to the inference of parameters, and the estimation of log Z in an established model of circadian rhythms. A ten-fold difference in the coefficient of variation between degradation and transcription parameters is demonstrated. We further show that the uncertainty remaining in the parameter values is reduced by the analysis of increasing numbers of circadian cycles of data, up to 4 cycles, but is unaffected by sampling the data more frequently. Novel algorithms for calculating the likelihood of a model, and a characterisation of the performance of the nested sampling algorithm are also reported. The methods we develop considerably improve the computational efficiency of the likelihood calculation, and of the exploratory step within nested sampling. Conclusions We have demonstrated in an exemplar circadian model that the estimates of posterior parameter densities (as summarised by parameter means and standard deviations) are influenced predominately by the length of the time series, becoming more narrowly constrained as the number of circadian cycles considered increases. We have also shown the utility of the coefficient of variation for discriminating between highly-constrained and less-well constrained parameters. PMID:23899119

  7. Welding Penetration Control of Fixed Pipe in TIG Welding Using Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

    This paper presents a study on welding penetration control of fixed pipe in Tungsten Inert Gas (TIG) welding using fuzzy inference system. The welding penetration control is essential to the production quality welds with a specified geometry. For pipe welding using constant arc current and welding speed, the bead width becomes wider as the circumferential welding of small diameter pipes progresses. Having welded pipe in fixed position, obviously, the excessive arc current yields burn through of metals; in contrary, insufficient arc current produces imperfect welding. In order to avoid these errors and to obtain the uniform weld bead over the entire circumference of the pipe, the welding conditions should be controlled as the welding proceeds. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position using the AC welding machine. The monitoring system used a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Simulation of welding control using fuzzy inference system was constructed to simulate the welding control process. The simulation result shows that fuzzy controller was suitable for controlling the welding speed and appropriate to be implemented into the welding system. A series of experiments was conducted to evaluate the performance of the fuzzy controller. The experimental results show the effectiveness of the control system that is confirmed by sound welds.

  8. Free-energy inference from partial work measurements in small systems

    PubMed Central

    Ribezzi-Crivellari, Marco; Ritort, Felix

    2014-01-01

    Fluctuation relations (FRs) are among the few existing general results in nonequilibrium systems. Their verification requires the measurement of the total work performed on a system. Nevertheless in many cases only a partial measurement of the work is possible. Here we consider FRs in dual-trap optical tweezers where two different forces (one per trap) are measured. With this setup we perform pulling experiments on single molecules by moving one trap relative to the other. We demonstrate that work should be measured using the force exerted by the trap that is moved. The force that is measured in the trap at rest fails to provide the full dissipation in the system, leading to a (incorrect) work definition that does not satisfy the FR. The implications to single-molecule experiments and free-energy measurements are discussed. In the case of symmetric setups a second work definition, based on differential force measurements, is introduced. This definition is best suited to measure free energies as it shows faster convergence of estimators. We discuss measurements using the (incorrect) work definition as an example of partial work measurement. We show how to infer the full work distribution from the partial one via the FR. The inference process does also yield quantitative information, e.g., the hydrodynamic drag on the dumbbell. Results are also obtained for asymmetric dual-trap setups. We suggest that this kind of inference could represent a previously unidentified and general application of FRs to extract information about irreversible processes in small systems. PMID:25099353

  9. Development of rainfall runoff models using Takagi Sugeno fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Jacquin, Alexandra P.; Shamseldin, Asaad Y.

    2006-09-01

    SummaryThis study explores the application of Takagi-Sugeno fuzzy inference systems to rainfall-runoff modelling. The models developed intend to describe the non-linear relationship between rainfall as input and runoff as output to the real system using a system based approach. Two types of fuzzy models are proposed, where the first type is intended to account for the effect of changes in catchment wetness in the rainfall-runoff transformation and the second type incorporates seasonality as a source of non-linearity in this relationship. The models developed are applied to data from six catchments of diverse climatic characteristics. The results of the fuzzy models are compared with those of the Simple Linear Model, the Linear Perturbation Model and the Nearest Neighbour Linear Perturbation Model, which use similar input information. The results of this study indicate that fuzzy inference systems are a suitable alternative to the traditional methods for modelling the non-linear relationship between rainfall and runoff.

  10. Use of fuzzy inference system for condition monitoring of induction motor

    NASA Astrophysics Data System (ADS)

    Janier, Josefina B.; Zaim Zaharia, M. F.; Karim, Samsul Ariffin Abd.

    2012-09-01

    Three phase induction motors are commonly used in industry due to its robustness, simplicity of its construction and high reliability. The tasks performed by these motors grow increasingly complex because of modern industries hence there is a need to determine the faults. Early detection of faults will reduce an unscheduled machine downtime that can upset production deadlines and may cause heavy financial losses. This paper is focused in developing a computer based system using Fuzzy Inference system's membership function. An unusual increase in vibration of the motor could be an indicator of faulty condition hence the vibration of the motor of an induction motor was used as an input, whereas the output is the motor condition. An inference system of the Fuzzy Logic was created to classify the vibration characteristics of the motor which is called vibration analysis. The system classified the motor of the gas distribution pump condition as from 'acceptable' to 'monitor closely'. The early detection of unusual increase in vibration of the induction motor is an important part of a predictive maintenance for motor driven machinery.

  11. The early solar system abundance of /sup 244/Pu as inferred from the St. Severin chondrite

    SciTech Connect

    Hudson, G.B.; Kennedy, B.M.; Podosek, F.A.; Hohenberg, C.M.

    1987-03-01

    We describe the analysis of Xe released in stepwise heating of neutron-irradiated samples of the St. Severin chondrite. This analysis indicates that at the time of formation of most chondritic meteorites, approximately 4.56 x 10/sup 9/ years ago, the atomic ratio of /sup 244/Pu//sup 238/U was 0.0068 +- 0.0010 in chondritic meteorites. We believe that this value is more reliable than that inferred from earlier analyses of St. Severin. We feel that this value is currently the best available estimate for the early solar system abundance of /sup 244/Pu. 42 refs., 2 tabs.

  12. Dynamics of Pre-3 Ga Crust-Mantle Evolution

    NASA Astrophysics Data System (ADS)

    Patchett, P. J.; Chase, C. G.; Vervoort, J. D.

    2004-05-01

    During 3.0 to 2.7 Ga, the Earth's crust underwent a non-uniformitarian change from a pre-3.0 Ga environment where long-term preservation of cratons was rare and difficult, to post-2.7 Ga conditions where cratons were established and new continental crust generation took place largely at craton margins. Many models view the Earth's surface during pre-3 Ga time as broadly equivalent to the post 2.7 Ga regime. Any such uniformitarian or gradual evolution cannot explain the conundrum that only a tiny amount of pre-3 Ga crust is preserved today coupled with the fact that very little pre-3 Ga crust was incorporated into the large amount of new craton that came into existence during 3.0-2.7 Ga. If large volumes of pre-3 Ga continental crust existed, it disappeared either just prior to 3 Ga, or during 3.0-2.7 Ga. To explain sudden appearance of surviving but dominantly juvenile continental crust in a model where continents were large prior to 3 Ga, it would be necessary either that pre-3 Ga continent was recycled into the mantle at sites systematically different from those where new 3.0-2.7 Ga crust was made, or that widespread continent destruction preceded the 3.0-2.7 Ga crustal genesis. From expected mantle overturn in response to the heat budget, it is likely that most pre-3 Ga crust was both more mafic and shorter-lived than after 3 Ga. Although Nd and Hf ratios for pre-3 Ga rocks are uncertain due to polymetamorphism, it appears that depleted upper mantle was widespread by 2.7 Ga, even pre-3 Ga. Depletion may have been largely achieved by formation, subduction and storage of mafic crust for periods of 200-500 m.y. The rapid change to large surviving continents during 3.0-2.7 Ga was due to declining mantle overturn, and particularly to development of the ability to maintain subduction in one zone of the earth's surface for the time needed to allow evolution to felsic igneous rock compositions. In as much as storage of subducted slabs is probably occurring today, and in view of the apparent Proterozoic Pb age of some present mantle plume sources, we believe sequestration of enriched material in the deep mantle is still underestimated, and that isotopic mass balance calculations involving only continent and upper mantle will overestimate the mean continental age.

  13. Crust-mantle interactions and crustal deformations, some geological observations

    NASA Astrophysics Data System (ADS)

    Jolivet, Laurent; Clerc, Camille; Sternai, Pietro; Bellahsen, Nicolas; Faccenna, Claudio; Ringenbach, Jean-Claude; Gorini, Christian; Leroy, Sylvie; Pik, Raphaël

    2015-04-01

    Crustal deformations at plate boundaries or intracontinental are governed by the relative movements of plates, and most published models consider the lithosphere as the main stress guide in extensional or compressional contexts. The possible contribution of the underlying asthenospheric flow to crustal deformation through viscous coupling is often neglected. Since the early days of plate tectonics, and even earlier, two schools of thought have been developed in parallel whether mantle convection is considered or not. This reflects nowadays in the difficulty of reconciling lithospheric-scale models and global-scale convection models to explain tectonic features observed at the surface. Still, recent studies reemphasized the role of mantle convection in shaping mountain belts or rifts and the consequences of different styles of convection on the geometry and kinematics of mountain belts. We present here a number of geological observations in convergent or divergent contexts that may suggest a strong coupling between asthenospheric flow and crustal deformation. Several of these examples, especially in extensional contexts, show a deformation distributed over wide zones, accommodated by shallow-dipping shear zones and with a constant asymmetry over large distances. This is the case of the Mediterranean back-arc basins, such as the Aegean Sea, the northern Tyrrhenian Sea or the Alboran domain, where extension is taken up by shallow-dipping extensional shear zones and normal faults with a constant asymmetry. A similar image is also observed across the Gulf of Lion passive margin that also belongs to the Mediterranean back-arc basins. Such is also the case of some of the Atlantic passive margins where shallow-dipping normal faults and extensional shear zones control the extraction of the lower crust and the mantle with a constant asymmetry across the entire margin. Finally, the distribution and geometry of normal faults across the Afar region also show a constant asymmetry. We discuss these contexts and search for the main controlling parameters for this asymmetric distributed deformation. These parameters include an original heterogeneity of the crust and lithosphere (tectonic heritage) and a possible contribution of the underlying asthenospheric flow. We discuss the relations between the observed asymmetry and the direction and sense of the mantle flow underneath. Finally, we extend this question to larger-scale processes such as obduction and continental collision.

  14. Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

    NASA Astrophysics Data System (ADS)

    Zhang, Daili

    Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications

  15. Determination of Indonesian palm-oil-based bioenergy sustainability indicators using fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Arkeman, Y.; Rizkyanti, R. A.; Hambali, E.

    2017-05-01

    Development of Indonesian palm-oil-based bioenergy faces an international challenge regarding to sustainability issue, indicated by the establishment of standards on sustainable bioenergy. Currently, Indonesia has sustainability standards limited to palm-oil cultivation, while other standards are lacking appropriateness for Indonesian palm-oil-based bioenergy sustainability regarding to real condition in Indonesia. Thus, Indonesia requires sustainability indicators for Indonesian palm-oil-based bioenergy to gain recognition and easiness in marketing it. Determination of sustainability indicators was accomplished through three stages, which were preliminary analysis, indicator assessment (using fuzzy inference system), and system validation. Global Bioenergy partnership (GBEP) was used as the standard for the assessment because of its general for use, internationally accepted, and it contained balanced proportion between environment, economic, and social aspects. Result showed that the number of sustainability indicators using FIS method are 21 indicators. The system developed has an accuracy of 85%.

  16. Reliable Identification of Vehicle-Boarding Actions Based on Fuzzy Inference System

    PubMed Central

    Ahn, DaeHan; Park, Homin; Hwang, Seokhyun; Park, Taejoon

    2017-01-01

    Existing smartphone-based solutions to prevent distracted driving suffer from inadequate system designs that only recognize simple and clean vehicle-boarding actions, thereby failing to meet the required level of accuracy in real-life environments. In this paper, exploiting unique sensory features consistently monitored from a broad range of complicated vehicle-boarding actions, we propose a reliable and accurate system based on fuzzy inference to classify the sides of vehicle entrance by leveraging built-in smartphone sensors only. The results of our comprehensive evaluation on three vehicle types with four participants demonstrate that the proposed system achieves 91.1%∼94.0% accuracy, outperforming other methods by 26.9%∼38.4% and maintains at least 87.8% accuracy regardless of smartphone positions and vehicle types. PMID:28208795

  17. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

    PubMed

    Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

    2016-01-01

    Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

  18. Application of fuzzy inference system by Sugeno method on estimating of salt production

    NASA Astrophysics Data System (ADS)

    Yulianto, Tony; Komariyah, Siti; Ulfaniyah, Nurita

    2017-08-01

    Salt is one of the most important needs in everyday life. Making traditional salt largely is done by smallholder farmers in addition by manufacturers of industrial salt. factors that affect the production of salt include seawater, soil, water influence and weather conditions including rainfall wind speed and solar radiation or long dry erratic, these conditions obviously affect the salt farmers that will affect the production quantities of salt produced by salt farmers. In this study, the fuzzy logic method is applied to Sugeno fuzzy inference systems to estimate the production of salt by variables - variables that affect it. This study aims to estimate how much production by applying fuzzy inference systems zero-order Sugeno method based on the variable wind speed, solar radiation, rainfall and the amount of production. Retrieval of data obtained from the Air Quality Meteorology and Geophysics. salt farmers in Pamekasan District of Pademawu Village Majungan. Data taken within 2 years per week from June to December of 2014 and 2015. The Sugeno fuzzy logic model in this study using output (consequent) in the form of equation constants (Sugeno models Order zero). Apparently from the research results obtained by the error value most low at 0.0917, so it can be said to be close to zero.

  19. Urban area mapping from polarimetric SAR data using fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Ahluwalia, Asmeet; Manickam, Surendar; Bhattacharya, Avik; Porwal, Alok

    2016-05-01

    In this work, we present urban area mapping from full-polarimetric synthetic aperture radar (SAR) data using fuzzy inference system (FIS). In particular, our aim is to utilize the profound knowledge available about scattering mechanism from urban targets to delineate urban environment. In this approach, we have utilized the recently developed polarimetric SAR scattering power decomposition technique (SD-Y4O) given in Bhattacharya et. al. The improved powers along with some other polarimetric parameters were used in this study. A suitable normalization procedure was adapted to handle the skewness in the estimated parameters. The fuzzy if-then rules were constructed from the in-depth knowledge of scattering mechanisms from an urban environment. Suitable methods were introduced to define the fuzzy inference system. The defuzzified membership values were thresholded using an unsupervised clustering method (k-means). The pixels lying in the range [μmax-σ, μmax+σ] corresponds to urban areas where µmax is the largest cluster center and σ is the standard deviation of the cluster corresponding to µmax. The extracted urban area is in visually good agreement with the high resolution optical image. ALOS PALSAR full-polarimetric L-band SAR data has been used in this study.

  20. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

    NASA Astrophysics Data System (ADS)

    Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  1. A Context-Aware Interactive Health Care System Based on Ontology and Fuzzy Inference.

    PubMed

    Chiang, Tzu-Chiang; Liang, Wen-Hua

    2015-09-01

    In the present society, most families are double-income families, and as the long-term care is seriously short of manpower, it contributes to the rapid development of tele-homecare equipment, and the smart home care system gradually emerges, which assists the elderly or patients with chronic diseases in daily life. This study aims at interaction between persons under care and the system in various living spaces, as based on motion-sensing interaction, and the context-aware smart home care system is proposed. The system stores the required contexts in knowledge ontology, including the physiological information and environmental information of the person under care, as the database of decision. The motion-sensing device enables the person under care to interact with the system through gestures. By the inference mechanism of fuzzy theory, the system can offer advice and rapidly execute service, thus, implementing the EHA. In addition, the system is integrated with the functions of smart phone, tablet PC, and PC, in order that users can implement remote operation and share information regarding the person under care. The health care system constructed in this study enables the decision making system to probe into the health risk of each person under care; then, from the view of preventive medicine, and through a composing system and simulation experimentation, tracks the physiological trend of the person under care, and provides early warning service, thus, promoting smart home care.

  2. Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

    PubMed

    Erguler, Kamil; Stumpf, Michael P H

    2011-05-01

    The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

  3. Another expert system rule inference based on DNA molecule logic gates

    NASA Astrophysics Data System (ADS)

    WÄ siewicz, Piotr

    2013-10-01

    With the help of silicon industry microfluidic processors were invented utilizing nano membrane valves, pumps and microreactors. These so called lab-on-a-chips combined together with molecular computing create molecular-systems-ona- chips. This work presents a new approach to implementation of molecular inference systems. It requires the unique representation of signals by DNA molecules. The main part of this work includes the concept of logic gates based on typical genetic engineering reactions. The presented method allows for constructing logic gates with many inputs and for executing them at the same quantity of elementary operations, regardless of a number of input signals. Every microreactor of the lab-on-a-chip performs one unique operation on input molecules and can be connected by dataflow output-input connections to other ones.

  4. Design of a biped locomotion controller based on adaptive neuro-fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Shieh, M.-Y.; Chang, K.-H.; Lia, Y.-S.

    2008-02-01

    This paper proposes a method for the design of a biped locomotion controller based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) inverse learning model. In the model developed here, an integrated ANFIS structure is trained to function as the system identifier for the modeling of the inverse dynamics of a biped robot. The parameters resulting from the modeling process are duplicated and integrated as those of the biped locomotion controller to provide favorable control action. As the simulation results show, the proposed controller is able to generate a stable walking cycle for a biped robot. Moreover, the experimental results demonstrate that the performance of the proposed controller is satisfactory under conditions when the robot stands in different postures or moves on a rugged surface.

  5. Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

    NASA Technical Reports Server (NTRS)

    Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.

    1986-01-01

    The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.

  6. Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

    NASA Technical Reports Server (NTRS)

    Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.

    1986-01-01

    This paper summarizes the modifications made to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of an update frequency, are also presented.

  7. Reservoir observers: Model-free inference of unmeasured variables in chaotic systems.

    PubMed

    Lu, Zhixin; Pathak, Jaideep; Hunt, Brian; Girvan, Michelle; Brockett, Roger; Ott, Edward

    2017-04-01

    Deducing the state of a dynamical system as a function of time from a limited number of concurrent system state measurements is an important problem of great practical utility. A scheme that accomplishes this is called an "observer." We consider the case in which a model of the system is unavailable or insufficiently accurate, but "training" time series data of the desired state variables are available for a short period of time, and a limited number of other system variables are continually measured. We propose a solution to this problem using networks of neuron-like units known as "reservoir computers." The measurements that are continually available are input to the network, which is trained with the limited-time data to output estimates of the desired state variables. We demonstrate our method, which we call a "reservoir observer," using the Rössler system, the Lorenz system, and the spatiotemporally chaotic Kuramoto-Sivashinsky equation. Subject to the condition of observability (i.e., whether it is in principle possible, by any means, to infer the desired unmeasured variables from the measured variables), we show that the reservoir observer can be a very effective and versatile tool for robustly reconstructing unmeasured dynamical system variables.

  8. Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

    NASA Astrophysics Data System (ADS)

    Oğuz, Yüksel; Üstün, Seydi Vakkas; Yabanova, İsmail; Yumurtaci, Mehmet; Güney, İrfan

    2012-01-01

    This article presents design of adaptive neuro-fuzzy inference system (ANFIS) for the turbine speed control for purpose of improving the power quality of the power production system of a split shaft microturbine. To improve the operation performance of the microturbine power generation system (MTPGS) and to obtain the electrical output magnitudes in desired quality and value (terminal voltage, operation frequency, power drawn by consumer and production power), a controller depended on adaptive neuro-fuzzy inference system was designed. The MTPGS consists of the microturbine speed controller, a split shaft microturbine, cylindrical pole synchronous generator, excitation circuit and voltage regulator. Modeling of dynamic behavior of synchronous generator driver with a turbine and split shaft turbine was realized by using the Matlab/Simulink and SimPowerSystems in it. It is observed from the simulation results that with the microturbine speed control made with ANFIS, when the MTPGS is operated under various loading situations, the terminal voltage and frequency values of the system can be settled in desired operation values in a very short time without significant oscillation and electrical production power in desired quality can be obtained.

  9. Transcriptome inference and systems approaches to polypharmacology and drug discovery in herbal medicine.

    PubMed

    Li, Peng; Chen, Jianxin; Zhang, Wuxia; Fu, Bangze; Wang, Wei

    2017-01-04

    Herbal medicine is a concoction of numerous chemical ingredients, and it exhibits polypharmacological effects to act on multiple pharmacological targets, regulating different biological mechanisms and treating a variety of diseases. Thus, this complexity is impossible to deconvolute by the reductionist method of extracting one active ingredient acting on one biological target. To dissect the polypharmacological effects of herbal medicines and their underling pharmacological targets as well as their corresponding active ingredients. We propose a system-biology strategy that combines omics and bioinformatical methodologies for exploring the polypharmacology of herbal mixtures. The myocardial ischemia model was induced by Ameroid constriction of the left anterior descending coronary in Ba-Ma miniature pigs. RNA-seq analysis was utilized to find the differential genes induced by myocardial ischemia in pigs treated with formula QSKL. A transcriptome-based inference method was used to find the landmark drugs with similar mechanisms to QSKL. Gene-level analysis of RNA-seq data in QSKL-treated cases versus control animals yields 279 differential genes. Transcriptome-based inference methods identified 80 landmark drugs that covered nearly all drug classes. Then, based on the landmark drugs, 155 potential pharmacological targets and 57 indications were identified for QSKL. Our results demonstrate the power of a combined approach for exploring the pharmacological target and chemical space of herbal medicines. We hope that our method could enhance our understanding of the molecular mechanisms of herbal systems and further accelerate the exploration of the value of traditional herbal medicine systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  10. Portable inference engine: An extended CLIPS for real-time production systems

    NASA Technical Reports Server (NTRS)

    Le, Thach; Homeier, Peter

    1988-01-01

    The present C-Language Integrated Production System (CLIPS) architecture has not been optimized to deal with the constraints of real-time production systems. Matching in CLIPS is based on the Rete Net algorithm, whose assumption of working memory stability might fail to be satisfied in a system subject to real-time dataflow. Further, the CLIPS forward-chaining control mechanism with a predefined conflict resultion strategy may not effectively focus the system's attention on situation-dependent current priorties, or appropriately address different kinds of knowledge which might appear in a given application. Portable Inference Engine (PIE) is a production system architecture based on CLIPS which attempts to create a more general tool while addressing the problems of real-time expert systems. Features of the PIE design include a modular knowledge base, a modified Rete Net algorithm, a bi-directional control strategy, and multiple user-defined conflict resolution strategies. Problems associated with real-time applications are analyzed and an explanation is given for how the PIE architecture addresses these problems.

  11. Evaluation of a dual processor implementation for a fault inferring nonlinear detection system

    NASA Technical Reports Server (NTRS)

    Godiwala, P. M.; Caglayan, A. K.; Morrell, F. R.

    1987-01-01

    The design of a modified fault inferring nonlinear detection system (FINDS) algorithm for a dual-processor configured flight computer is described. The algorithm was changed in order to divide it into its translational dynamics and rotational kinematics and to use it for parallel execution on the flight computer. The FINDS consists of: (1) a no-fail filter (NFF), (2) a set of test-of-mean detection tests, (3) a bank of first order filters to estimate failure levels in individual sensors, and (4) a decision function. NFF filter performance using flight recorded sensor data is analyzed using a filter autoinitialization routine. The failure detection and isolation capability of the partitioned algorithm is evaluated. A multirate implementation for the bias-free and bias filter gain and covariance matrices is discussed.

  12. An expert system shell for inferring vegetation characteristics: Atmospheric techniques (Task G)

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann; Harrison, Patrick R.

    1993-01-01

    The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The VEG Subgoals have been reorganized into categories. A new subgoal category 'Atmospheric Techniques' containing two new subgoals has been implemented. The subgoal Atmospheric Passes allows the scientist to take reflectance data measured at ground level and predict what the reflectance values would be if the data were measured at a different atmospheric height. The subgoal Atmospheric Corrections allows atmospheric corrections to be made to data collected from an aircraft or by a satellite to determine what the equivalent reflectance values would be if the data were measured at ground level. The report describes the implementation and testing of the basic framework and interface for the Atmospheric Techniques Subgoals.

  13. Prediction study on the degeneration of lithium-ion battery based on fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Shi, Jian Ping

    2017-07-01

    The degradation degree prediction of lithium-ion battery has been studied through experimental data. Characterization parameters on the degradation degree of lithium-ion battery were deduced under consideration of the internal and external factors. The analysis of discrete degree was proposed to depict the degradation degree for lithium-ion battery. Furthermore, based on fuzzy inference system (FIS), the predicted model of the degradation degree for lithium-ion battery was built and its output was defined as the degenerate coefficient β, β ∈ [0, 1]. Finally, by learning, training and simulating, the FIS model has been validated to be reliable and applicable in prediction on the degradation degree of lithium-ion battery. The simulation results show that the degradation degree of lithium-ion battery is more serious when β is closer to 1, and the degradation degree is lighter when β is closer to 0.

  14. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System

    PubMed Central

    Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

    2016-01-01

    Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP). PMID:26829639

  15. Building bridges across electronic health record systems through inferred phenotypic topics.

    PubMed

    Chen, You; Ghosh, Joydeep; Bejan, Cosmin Adrian; Gunter, Carl A; Gupta, Siddharth; Kho, Abel; Liebovitz, David; Sun, Jimeng; Denny, Joshua; Malin, Bradley

    2015-06-01

    Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution to another in a meaningful way, we need to harmonize the phenotypes in such systems. Traditionally, this has been accomplished through expert specification of phenotypes via standardized terminologies, such as billing codes. However, this approach may be biased by the experience and expectations of the experts, as well as the vocabulary used to describe such patients. The goal of this work is to develop a data-driven strategy to (1) infer phenotypic topics within patient populations and (2) assess the degree to which such topics facilitate a mapping across populations in disparate healthcare systems. We adapt a generative topic modeling strategy, based on latent Dirichlet allocation, to infer phenotypic topics. We utilize a variance analysis to assess the projection of a patient population from one healthcare system onto the topics learned from another system. The consistency of learned phenotypic topics was evaluated using (1) the similarity of topics, (2) the stability of a patient population across topics, and (3) the transferability of a topic across sites. We evaluated our approaches using four months of inpatient data from two geographically distinct healthcare systems: (1) Northwestern Memorial Hospital (NMH) and (2) Vanderbilt University Medical Center (VUMC). The method learned 25 phenotypic topics from each healthcare system. The average cosine similarity between matched topics across the two sites was 0.39, a remarkably high value given the very high dimensionality of the feature space. The average stability of VUMC and NMH patients across the topics of two sites was 0.988 and 0.812, respectively, as measured by the Pearson correlation coefficient. Also the VUMC and NMH topics have smaller variance of characterizing

  16. A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems.

    PubMed

    Schumacher, Johannes; Wunderle, Thomas; Fries, Pascal; Jäkel, Frank; Pipa, Gordon

    2015-08-01

    In neuroscience, data are typically generated from neural network activity. The resulting time series represent measurements from spatially distributed subsystems with complex interactions, weakly coupled to a high-dimensional global system. We present a statistical framework to estimate the direction of information flow and its delay in measurements from systems of this type. Informed by differential topology, gaussian process regression is employed to reconstruct measurements of putative driving systems from measurements of the driven systems. These reconstructions serve to estimate the delay of the interaction by means of an analytical criterion developed for this purpose. The model accounts for a range of possible sources of uncertainty, including temporally evolving intrinsic noise, while assuming complex nonlinear dependencies. Furthermore, we show that if information flow is delayed, this approach also allows for inference in strong coupling scenarios of systems exhibiting synchronization phenomena. The validity of the method is demonstrated with a variety of delay-coupled chaotic oscillators. In addition, we show that these results seamlessly transfer to local field potentials in cat visual cortex.

  17. Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

    PubMed

    Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

    2017-04-01

    We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its

  18. Multiple Adaptive Neuro-Fuzzy Inference System with Automatic Features Extraction Algorithm for Cervical Cancer Recognition

    PubMed Central

    Subhi Al-batah, Mohammad; Mat Isa, Nor Ashidi; Klaib, Mohammad Fadel; Al-Betar, Mohammed Azmi

    2014-01-01

    To date, cancer of uterine cervix is still a leading cause of cancer-related deaths in women worldwide. The current methods (i.e., Pap smear and liquid-based cytology (LBC)) to screen for cervical cancer are time-consuming and dependent on the skill of the cytopathologist and thus are rather subjective. Therefore, this paper presents an intelligent computer vision system to assist pathologists in overcoming these problems and, consequently, produce more accurate results. The developed system consists of two stages. In the first stage, the automatic features extraction (AFE) algorithm is performed. In the second stage, a neuro-fuzzy model called multiple adaptive neuro-fuzzy inference system (MANFIS) is proposed for recognition process. The MANFIS contains a set of ANFIS models which are arranged in parallel combination to produce a model with multi-input-multioutput structure. The system is capable of classifying cervical cell image into three groups, namely, normal, low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL). The experimental results prove the capability of the AFE algorithm to be as effective as the manual extraction by human experts, while the proposed MANFIS produces a good classification performance with 94.2% accuracy. PMID:24707316

  19. The Role of Probability-Based Inference in an Intelligent Tutoring System.

    ERIC Educational Resources Information Center

    Mislevy, Robert J.; Gitomer, Drew H.

    Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring…

  20. Eccentricity Inferences in Multi-planet systems with Transit Timing: Degeneracies and Apsidal Alignment

    NASA Astrophysics Data System (ADS)

    Jontof-Hutter, Daniel; Van Laerhoven, Christa L.; Ford, Eric B.

    2016-05-01

    Hundreds of multi-transiting systems discovered by the Kepler mission show Transit Timing Variations (TTV). In cases where the TTVs are uniquely attributable to transiting planets, the TTVs enable precise measurements of planetary masses and orbital parameters. Of particular interest are the constraints on eccentricity vectors that can be inferred in systems of low-mass exoplanets.The TTVs in these systems are dominated by a signal caused by near-resonant mean motions. This causes the well-known near-degeneracy between planetary masses and orbital eccentricities. In addition, it causes a degeneracy between the eccentricities of interacting planet pairs.For many systems, the magnitude of individual eccentricities are weakly constrained, yet the data typically provide a tight constraint on the posterior joint distribution for the eccentricity vector components. This permits tight constraints on the relative eccentricity and degree of alignment of interacting planets.For a sample of two and three-planet systems with TTVs, we highlight the effects of these correlations. While the most eccentric orbital solutions for these systems show apsidal alignment, this is often due to the degeneracy that causes correlated constraints on the eccentricity vector components. We compare the likelihood of apsidal alignment for two choices of eccentricity prior: a wide prior using a Rayleigh distribution of scale length 0.1 and a narrower prior with scale length 0.02. In all cases the narrower prior decreased the fraction of samples that exhibited apsidal alignment. However, apsidal alignment persisted in the majority of cases with a narrower eccentricity prior. For a sample of our TTV solutions, we ran simulations of these systems over secular timescales, and decomposed their eccentricity eigenmodes over time, confirming that in most cases, the eccentricities were dominated by parallel eigenmodes which favor apsidal alignment.

  1. Bayesian model comparison and parameter inference in systems biology using nested sampling.

    PubMed

    Pullen, Nick; Morris, Richard J

    2014-01-01

    Inferring parameters for models of biological processes is a current challenge in systems biology, as is the related problem of comparing competing models that explain the data. In this work we apply Skilling's nested sampling to address both of these problems. Nested sampling is a Bayesian method for exploring parameter space that transforms a multi-dimensional integral to a 1D integration over likelihood space. This approach focuses on the computation of the marginal likelihood or evidence. The ratio of evidences of different models leads to the Bayes factor, which can be used for model comparison. We demonstrate how nested sampling can be used to reverse-engineer a system's behaviour whilst accounting for the uncertainty in the results. The effect of missing initial conditions of the variables as well as unknown parameters is investigated. We show how the evidence and the model ranking can change as a function of the available data. Furthermore, the addition of data from extra variables of the system can deliver more information for model comparison than increasing the data from one variable, thus providing a basis for experimental design.

  2. Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

    PubMed

    Venkataraman, Vinay; Turaga, Pavan

    2016-12-01

    This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

  3. Shape Descriptions of Nonlinear Dynamical Systems for Video-based Inference.

    PubMed

    Venkataraman, Vinay; Turaga, Pavan

    2016-02-23

    This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification.We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

  4. Adaptive neuro-fuzzy inference system for real-time monitoring of integrated-constructed wetlands.

    PubMed

    Dzakpasu, Mawuli; Scholz, Miklas; McCarthy, Valerie; Jordan, Siobhán; Sani, Abdulkadir

    2015-01-01

    Monitoring large-scale treatment wetlands is costly and time-consuming, but required by regulators. Some analytical results are available only after 5 days or even longer. Thus, adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the effluent concentrations of 5-day biochemical oxygen demand (BOD5) and NH4-N from a full-scale integrated constructed wetland (ICW) treating domestic wastewater. The ANFIS models were developed and validated with a 4-year data set from the ICW system. Cost-effective, quicker and easier to measure variables were selected as the possible predictors based on their goodness of correlation with the outputs. A self-organizing neural network was applied to extract the most relevant input variables from all the possible input variables. Fuzzy subtractive clustering was used to identify the architecture of the ANFIS models and to optimize fuzzy rules, overall, improving the network performance. According to the findings, ANFIS could predict the effluent quality variation quite strongly. Effluent BOD5 and NH4-N concentrations were predicted relatively accurately by other effluent water quality parameters, which can be measured within a few hours. The simulated effluent BOD5 and NH4-N concentrations well fitted the measured concentrations, which was also supported by relatively low mean squared error. Thus, ANFIS can be useful for real-time monitoring and control of ICW systems.

  5. Bayesian Model Comparison and Parameter Inference in Systems Biology Using Nested Sampling

    PubMed Central

    Pullen, Nick; Morris, Richard J.

    2014-01-01

    Inferring parameters for models of biological processes is a current challenge in systems biology, as is the related problem of comparing competing models that explain the data. In this work we apply Skilling's nested sampling to address both of these problems. Nested sampling is a Bayesian method for exploring parameter space that transforms a multi-dimensional integral to a 1D integration over likelihood space. This approach focusses on the computation of the marginal likelihood or evidence. The ratio of evidences of different models leads to the Bayes factor, which can be used for model comparison. We demonstrate how nested sampling can be used to reverse-engineer a system's behaviour whilst accounting for the uncertainty in the results. The effect of missing initial conditions of the variables as well as unknown parameters is investigated. We show how the evidence and the model ranking can change as a function of the available data. Furthermore, the addition of data from extra variables of the system can deliver more information for model comparison than increasing the data from one variable, thus providing a basis for experimental design. PMID:24523891

  6. Bayesian inference of interaction properties of noisy dynamical systems with time-varying coupling: capabilities and limitations

    NASA Astrophysics Data System (ADS)

    Wilting, Jens; Lehnertz, Klaus

    2015-08-01

    We investigate a recently published analysis framework based on Bayesian inference for the time-resolved characterization of interaction properties of noisy, coupled dynamical systems. It promises wide applicability and a better time resolution than well-established methods. At the example of representative model systems, we show that the analysis framework has the same weaknesses as previous methods, particularly when investigating interacting, structurally different non-linear oscillators. We also inspect the tracking of time-varying interaction properties and propose a further modification of the algorithm, which improves the reliability of obtained results. We exemplarily investigate the suitability of this algorithm to infer strength and direction of interactions between various regions of the human brain during an epileptic seizure. Within the limitations of the applicability of this analysis tool, we show that the modified algorithm indeed allows a better time resolution through Bayesian inference when compared to previous methods based on least square fits.

  7. Data mining in forecasting PVT correlations of crude oil systems based on Type1 fuzzy logic inference systems

    NASA Astrophysics Data System (ADS)

    El-Sebakhy, Emad A.

    2009-09-01

    Pressure-volume-temperature properties are very important in the reservoir engineering computations. There are many empirical approaches for predicting various PVT properties based on empirical correlations and statistical regression models. Last decade, researchers utilized neural networks to develop more accurate PVT correlations. These achievements of neural networks open the door to data mining techniques to play a major role in oil and gas industry. Unfortunately, the developed neural networks correlations are often limited, and global correlations are usually less accurate compared to local correlations. Recently, adaptive neuro-fuzzy inference systems have been proposed as a new intelligence framework for both prediction and classification based on fuzzy clustering optimization criterion and ranking. This paper proposes neuro-fuzzy inference systems for estimating PVT properties of crude oil systems. This new framework is an efficient hybrid intelligence machine learning scheme for modeling the kind of uncertainty associated with vagueness and imprecision. We briefly describe the learning steps and the use of the Takagi Sugeno and Kang model and Gustafson-Kessel clustering algorithm with K-detected clusters from the given database. It has featured in a wide range of medical, power control system, and business journals, often with promising results. A comparative study will be carried out to compare their performance of this new framework with the most popular modeling techniques, such as neural networks, nonlinear regression, and the empirical correlations algorithms. The results show that the performance of neuro-fuzzy systems is accurate, reliable, and outperform most of the existing forecasting techniques. Future work can be achieved by using neuro-fuzzy systems for clustering the 3D seismic data, identification of lithofacies types, and other reservoir characterization.

  8. The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection

    NASA Astrophysics Data System (ADS)

    Tahriri, Farzad; Mousavi, Maryam; Hozhabri Haghighi, Siamak; Zawiah Md Dawal, Siti

    2014-06-01

    In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers' ranking. This is a complex process with many subjective and objective factors to consider before the benefits of supplier selection are achieved. This paper identifies six extremely critical criteria and thirteen sub-criteria based on the literature. A new methodology employing those criteria and sub-criteria is proposed for the assessment and ranking of a given set of suppliers. To handle the subjectivity of the decision maker's assessment, an integration of fuzzy Delphi with fuzzy inference system has been applied and a new ranking method is proposed for supplier selection problem. This supplier selection model enables decision makers to rank the suppliers based on three classifications including "extremely preferred", "moderately preferred", and "weakly preferred". In addition, in each classification, suppliers are put in order from highest final score to the lowest. Finally, the methodology is verified and validated through an example of a numerical test bed.

  9. Crop parameters estimation by fuzzy inference system using X-band scatterometer data

    NASA Astrophysics Data System (ADS)

    Pandey, Abhishek; Prasad, R.; Singh, V. P.; Jha, S. K.; Shukla, K. K.

    2013-03-01

    Learning fuzzy rule based systems with microwave remote sensing can lead to very useful applications in solving several problems in the field of agriculture. Fuzzy logic provides a simple way to arrive at a definite conclusion based upon imprecise, ambiguous, vague, noisy or missing input information. In the present paper, a subtractive based fuzzy inference system is introduced to estimate the potato crop parameters like biomass, leaf area index, plant height and soil moisture. Scattering coefficient for HH- and VV-polarizations were used as an input in the Fuzzy network. The plant height, biomass, and leaf area index of potato crop and soil moisture measured at its various growth stages were used as the target variables during the training and validation of the network. The estimated values of crop/soil parameters by this methodology are much closer to the experimental values. The present work confirms the estimation abilities of fuzzy subtractive clustering in potato crop parameters estimation. This technique may be useful for the other crops cultivated over regional or continental level.

  10. Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data

    NASA Technical Reports Server (NTRS)

    Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.

    1985-01-01

    This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

  11. Inference for Stochastic Chemical Kinetics Using Moment Equations and System Size Expansion

    PubMed Central

    Thomas, Philipp; Kazeroonian, Atefeh; Theis, Fabian J.; Grima, Ramon; Hasenauer, Jan

    2016-01-01

    Quantitative mechanistic models are valuable tools for disentangling biochemical pathways and for achieving a comprehensive understanding of biological systems. However, to be quantitative the parameters of these models have to be estimated from experimental data. In the presence of significant stochastic fluctuations this is a challenging task as stochastic simulations are usually too time-consuming and a macroscopic description using reaction rate equations (RREs) is no longer accurate. In this manuscript, we therefore consider moment-closure approximation (MA) and the system size expansion (SSE), which approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions. We introduce gradient-based parameter optimization methods and uncertainty analysis methods for MA and SSE. Efficiency and reliability of the methods are assessed using simulation examples as well as by an application to data for Epo-induced JAK/STAT signaling. The application revealed that even if merely population-average data are available, MA and SSE improve parameter identifiability in comparison to RRE. Furthermore, the simulation examples revealed that the resulting estimates are more reliable for an intermediate volume regime. In this regime the estimation error is reduced and we propose methods to determine the regime boundaries. These results illustrate that inference using MA and SSE is feasible and possesses a high sensitivity. PMID:27447730

  12. Inference in `poor` languages

    SciTech Connect

    Petrov, S.

    1996-10-01

    Languages with a solvable implication problem but without complete and consistent systems of inference rules (`poor` languages) are considered. The problem of existence of finite complete and consistent inference rule system for a ``poor`` language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.

  13. Ecological Inference

    NASA Astrophysics Data System (ADS)

    King, Gary; Rosen, Ori; Tanner, Martin A.

    2004-09-01

    This collection of essays brings together a diverse group of scholars to survey the latest strategies for solving ecological inference problems in various fields. The last half-decade has witnessed an explosion of research in ecological inference--the process of trying to infer individual behavior from aggregate data. Although uncertainties and information lost in aggregation make ecological inference one of the most problematic types of research to rely on, these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, by business in marketing research, and by governments in policy analysis.

  14. Smartphone-Based System for Learning and Inferring Hearing Aid Settings.

    PubMed

    Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J

    2016-10-01

    Previous research has shown that hearing aid wearers can successfully self-train their instruments' gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the "untrained system," that is, the manufacturer's algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The "trained system" first learned each individual's preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. An experimental within-participants study. Participants used a prototype hearing system-comprising two hearing aids, Android smartphone, and body-worn gateway device-for ∼6 weeks. Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Participants were fitted and instructed to perform daily comparisons of settings ("listening evaluations") through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase

  15. A Fuzzy Inference System for Closed-Loop Deep Brain Stimulation in Parkinson's Disease.

    PubMed

    Camara, Carmen; Warwick, Kevin; Bruña, Ricardo; Aziz, Tipu; del Pozo, Francisco; Maestú, Fernando

    2015-11-01

    Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the motor symptoms. However despite its beneficial effects on treating the symptomatology, the technique can be improved. One of its main limitations is that the parameters are fixed, and the stimulation is provided uninterruptedly, not taking into account any fluctuation in the patients state. A closed-loop system which provides stimulation by demand would adjust the stimulation to the variations in the state of the patient, stimulating only when it is necessary. It would not only perform a more intelligent stimulation, capable of adapting to the changes in real time, but also extending the devices battery life, thereby avoiding surgical interventions. In this work we design a tool that learns to recognize the principal symptom of Parkinsons disease and particularly the tremor. The goal of the designed system is to detect the moments the patient is suffering from a tremor episode and consequently to decide whether stimulation is needed or not. For that, local field potentials were recorded in the subthalamic nucleus of ten Parkinsonian patients, who were diagnosed with tremor-dominant Parkinsons disease and who underwent surgery for the implantation of a neurostimulator. Electromyographic activity in the forearm was simultaneously recorded, and the relation between both signals was evaluated using two different synchronization measures. The results of evaluating the synchronization indexes on each moment represent the inputs to the designed system. Finally, a fuzzy inference system was applied with the goal of identifying tremor episodes. Results are favourable, reaching accuracies of higher 98.7% in 70% of the patients.

  16. Condition monitoring of distributed systems using two-stage Bayesian inference data fusion

    NASA Astrophysics Data System (ADS)

    Jaramillo, Víctor H.; Ottewill, James R.; Dudek, Rafał; Lepiarczyk, Dariusz; Pawlik, Paweł

    2017-03-01

    In industrial practice, condition monitoring is typically applied to critical machinery. A particular piece of machinery may have its own condition monitoring system that allows the health condition of said piece of equipment to be assessed independently of any connected assets. However, industrial machines are typically complex sets of components that continuously interact with one another. In some cases, dynamics resulting from the inception and development of a fault can propagate between individual components. For example, a fault in one component may lead to an increased vibration level in both the faulty component, as well as in connected healthy components. In such cases, a condition monitoring system focusing on a specific element in a connected set of components may either incorrectly indicate a fault, or conversely, a fault might be missed or masked due to the interaction of a piece of equipment with neighboring machines. In such cases, a more holistic condition monitoring approach that can not only account for such interactions, but utilize them to provide a more complete and definitive diagnostic picture of the health of the machinery is highly desirable. In this paper, a Two-Stage Bayesian Inference approach allowing data from separate condition monitoring systems to be combined is presented. Data from distributed condition monitoring systems are combined in two stages, the first data fusion occurring at a local, or component, level, and the second fusion combining data at a global level. Data obtained from an experimental rig consisting of an electric motor, two gearboxes, and a load, operating under a range of different fault conditions is used to illustrate the efficacy of the method at pinpointing the root cause of a problem. The obtained results suggest that the approach is adept at refining the diagnostic information obtained from each of the different machine components monitored, therefore improving the reliability of the health assessment of

  17. Multiple Instance Fuzzy Inference

    DTIC Science & Technology

    2015-12-02

    Zhang, Xin Chen, and Wei-Bang Chen, “An online multiple instance learn - ing system for semantic image retrieval,” in Multimedia Workshops, 2007. ISMW...INFERENCE A novel fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The...fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The framework introduces a

  18. Smartphone-Based System for Learning and Inferring Hearing Aid Settings

    PubMed Central

    Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J.

    2017-01-01

    Background Previous research has shown that hearing aid wearers can successfully self-train their instruments’ gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the “untrained system,” that is, the manufacturer’s algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The “trained system” first learned each individual’s preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). Purpose To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. Research Design An experimental within-participants study. Participants used a prototype hearing system—comprising two hearing aids, Android smartphone, and body-worn gateway device—for ~6 weeks. Study Sample Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Intervention Participants were fitted and instructed to perform daily comparisons of settings (“listening evaluations”) through a smartphone-based software application called Hearing Aid

  19. Inferring the Architectures of Planetary Systems from Kepler Results with SysSim

    NASA Astrophysics Data System (ADS)

    Ford, Eric

    . Without a method to interpret and debias the Kepler planet candidates on a system-by- system basis, it is not possible to rigorously address critical NASA-relevant science questions like: 1) What fraction of stars have planets? What fraction of stars have solar system analogs? 2) What is the planetary system environment of potentially habitable planets? 3) What is the expected yield of future NASA exoplanet missions? 4) Are there different populations of planetary systems? What are their architectures? and many other valuable questions that are critical for understanding the origins of solar systems. To fill this critical gap, we have developed the Planetary System Simulator or SysSim, which empirically determines the underlying debiased distribution of planetary properties (e.g., planet size, orbital period, etc.) and planetary system architecture (e.g., relative inclinations, number of planets per star) simultaneously. The earliest version of SysSim measured the exoplanetary inclination distribution for the first time, a finding of major consequence for planet formation theorists (LR+11). We propose to extend SysSim to include new planetary architecture parameters and new observational constraints from the growing Kepler dataset. We will produce rigorously-debiased exoplanetary populations that will improve the understanding of the frequency, architecture, and origins of planetary systems. Our team is uniquely qualified to fulfill these tasks based on our extensive experience with Kepler data, metadata, multi-transiting systems, statistical inference, and previous work (LR+11, B12, Ragozzine & Holman 2010).

  20. Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

    PubMed

    Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

    2014-01-01

    The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

  1. Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level

    NASA Astrophysics Data System (ADS)

    Thakar, Juilee; Albert, Réka

    The following sections are included: * Introduction * Boolean Network Concepts and History * Extensions of the Classical Boolean Framework * Boolean Inference Methods and Examples in Biology * Dynamic Boolean Models: Examples in Plant Biology, Developmental Biology and Immunology * Conclusions * References

  2. Prediction of missing flow records using multilayer perceptron and coactive neurofuzzy inference system.

    PubMed

    Tfwala, Samkele S; Wang, Yu-Min; Lin, Yu-Chieh

    2013-01-01

    Hydrological data are often missing due to natural disasters, improper operation, limited equipment life, and other factors, which limit hydrological analysis. Therefore, missing data recovery is an essential process in hydrology. This paper investigates the accuracy of artificial neural networks (ANN) in estimating missing flow records. The purpose is to develop and apply neural networks models to estimate missing flow records in a station when data from adjacent stations is available. Multilayer perceptron neural networks model (MLP) and coactive neurofuzzy inference system model (CANFISM) are used to estimate daily flow records for Li-Lin station using daily flow data for the period 1997 to 2009 from three adjacent stations (Nan-Feng, Lao-Nung and San-Lin) in southern Taiwan. The performance of MLP is slightly better than CANFISM, having R (2) of 0.98 and 0.97, respectively. We conclude that accurate estimations of missing flow records under the complex hydrological conditions of Taiwan could be attained by intelligent methods such as MLP and CANFISM.

  3. Adaptive neuro fuzzy inference system for compressional wave velocity prediction in a carbonate reservoir

    NASA Astrophysics Data System (ADS)

    Zoveidavianpoor, Mansoor; Samsuri, Ariffin; Shadizadeh, Seyed Reza

    2013-02-01

    Compressional-wave (Vp) data are key information for estimation of rock physical properties and formation evaluation in hydrocarbon reservoirs. However, the absence of Vp will significantly delay the application of specific risk-assessment approaches for reservoir exploration and development procedures. Since Vp is affected by several factors such as lithology, porosity, density, and etc., it is difficult to model their non-linear relationships using conventional approaches. In addition, currently available techniques are not efficient for Vp prediction, especially in carbonates. There is a growing interest in incorporating advanced technologies for an accurate prediction of lacking data in wells. The objectives of this study, therefore, are to analyze and predict Vp as a function of some conventional well logs by two approaches; Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multiple Linear Regression (MLR). Also, the significant impact of selected input parameters on response variable will be investigated. A total of 2156 data points from a giant Middle Eastern carbonate reservoir, derived from conventional well logs and Dipole Sonic Imager (DSI) log were utilized in this study. The quality of the prediction was quantified in terms of the mean squared error (MSE), correlation coefficient (R-square), and prediction efficiency error (PEE). Results show that the ANFIS outperforms MLR with MSE of 0.0552, R-square of 0.964, and PEE of 2%. It is posited that porosity has a significant impact in predicting Vp in the investigated carbonate reservoir.

  4. Classifying work rate from heart rate measurements using an adaptive neuro-fuzzy inference system.

    PubMed

    Kolus, Ahmet; Imbeau, Daniel; Dubé, Philippe-Antoine; Dubeau, Denise

    2016-05-01

    In a new approach based on adaptive neuro-fuzzy inference systems (ANFIS), field heart rate (HR) measurements were used to classify work rate into four categories: very light, light, moderate, and heavy. Inter-participant variability (physiological and physical differences) was considered. Twenty-eight participants performed Meyer and Flenghi's step-test and a maximal treadmill test, during which heart rate and oxygen consumption (VO2) were measured. Results indicated that heart rate monitoring (HR, HRmax, and HRrest) and body weight are significant variables for classifying work rate. The ANFIS classifier showed superior sensitivity, specificity, and accuracy compared to current practice using established work rate categories based on percent heart rate reserve (%HRR). The ANFIS classifier showed an overall 29.6% difference in classification accuracy and a good balance between sensitivity (90.7%) and specificity (95.2%) on average. With its ease of implementation and variable measurement, the ANFIS classifier shows potential for widespread use by practitioners for work rate assessment.

  5. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    NASA Astrophysics Data System (ADS)

    Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

    2011-04-01

    Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

  6. Prediction of grain size of nanocrystalline nickel coatings using adaptive neuro-fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Hayati, M.; Rashidi, A. M.; Rezaei, A.

    2011-01-01

    This paper presents application of adaptive neuro-fuzzy inference system (ANFIS) for prediction of the grain size of nanocrystalline nickel coatings as a function of current density, saccharin concentration and bath temperature. For developing ANFIS model, the current density, saccharin concentration and bath temperature are taken as input, and the resulting grain size of the nanocrystalline coating as the output of the model. In order to provide a consistent set of experimental data, the nanocrystalline nickel coatings have been deposited from Watts-type bath using direct current electroplating within a large range of process parameters i.e., current density, saccharin concentration and bath temperature. Variation of the grain size because of the electroplating parameters has been modeled using ANFIS, and the experimental results and theoretical approaches have been compared to each other as well. Also, we have compared the proposed ANFIS model with artificial neural network (ANN) approach. The results have shown that the ANFIS model is more accurate and reliable compared to the ANN approach.

  7. Genetic-algorithm-based multiple regression with fuzzy inference system for detection of nocturnal hypoglycemic episodes.

    PubMed

    Ling, Steve S H; Nguyen, Hung T

    2011-03-01

    Hypoglycemia or low blood glucose is dangerous and can result in unconsciousness, seizures, and even death. It is a common and serious side effect of insulin therapy in patients with diabetes. Hypoglycemic monitor is a noninvasive monitor that measures some physiological parameters continuously to provide detection of hypoglycemic episodes in type 1 diabetes mellitus patients (T1DM). Based on heart rate (HR), corrected QT interval of the ECG signal, change of HR, and the change of corrected QT interval, we develop a genetic algorithm (GA)-based multiple regression with fuzzy inference system (FIS) to classify the presence of hypoglycemic episodes. GA is used to find the optimal fuzzy rules and membership functions of FIS and the model parameters of regression method. From a clinical study of 16 children with T1DM, natural occurrence of nocturnal hypoglycemic episodes is associated with HRs and corrected QT intervals. The overall data were organized into a training set (eight patients) and a testing set (another eight patients) randomly selected. The results show that the proposed algorithm performs a good sensitivity with an acceptable specificity.

  8. A Boolean Consistent Fuzzy Inference System for Diagnosing Diseases and Its Application for Determining Peritonitis Likelihood

    PubMed Central

    Dragović, Ivana; Turajlić, Nina; Pilčević, Dejan; Petrović, Bratislav; Radojević, Dragan

    2015-01-01

    Fuzzy inference systems (FIS) enable automated assessment and reasoning in a logically consistent manner akin to the way in which humans reason. However, since no conventional fuzzy set theory is in the Boolean frame, it is proposed that Boolean consistent fuzzy logic should be used in the evaluation of rules. The main distinction of this approach is that it requires the execution of a set of structural transformations before the actual values can be introduced, which can, in certain cases, lead to different results. While a Boolean consistent FIS could be used for establishing the diagnostic criteria for any given disease, in this paper it is applied for determining the likelihood of peritonitis, as the leading complication of peritoneal dialysis (PD). Given that patients could be located far away from healthcare institutions (as peritoneal dialysis is a form of home dialysis) the proposed Boolean consistent FIS would enable patients to easily estimate the likelihood of them having peritonitis (where a high likelihood would suggest that prompt treatment is indicated), when medical experts are not close at hand. PMID:27069500

  9. User's guide to the Fault Inferring Nonlinear Detection System (FINDS) computer program

    NASA Technical Reports Server (NTRS)

    Caglayan, A. K.; Godiwala, P. M.; Satz, H. S.

    1988-01-01

    Described are the operation and internal structure of the computer program FINDS (Fault Inferring Nonlinear Detection System). The FINDS algorithm is designed to provide reliable estimates for aircraft position, velocity, attitude, and horizontal winds to be used for guidance and control laws in the presence of possible failures in the avionics sensors. The FINDS algorithm was developed with the use of a digital simulation of a commercial transport aircraft and tested with flight recorded data. The algorithm was then modified to meet the size constraints and real-time execution requirements on a flight computer. For the real-time operation, a multi-rate implementation of the FINDS algorithm has been partitioned to execute on a dual parallel processor configuration: one based on the translational dynamics and the other on the rotational kinematics. The report presents an overview of the FINDS algorithm, the implemented equations, the flow charts for the key subprograms, the input and output files, program variable indexing convention, subprogram descriptions, and the common block descriptions used in the program.

  10. The Gaia astrophysical parameters inference system (Apsis). Pre-launch description

    NASA Astrophysics Data System (ADS)

    Bailer-Jones, C. A. L.; Andrae, R.; Arcay, B.; Astraatmadja, T.; Bellas-Velidis, I.; Berihuete, A.; Bijaoui, A.; Carrión, C.; Dafonte, C.; Damerdji, Y.; Dapergolas, A.; de Laverny, P.; Delchambre, L.; Drazinos, P.; Drimmel, R.; Frémat, Y.; Fustes, D.; García-Torres, M.; Guédé, C.; Heiter, U.; Janotto, A.-M.; Karampelas, A.; Kim, D.-W.; Knude, J.; Kolka, I.; Kontizas, E.; Kontizas, M.; Korn, A. J.; Lanzafame, A. C.; Lebreton, Y.; Lindstrøm, H.; Liu, C.; Livanou, E.; Lobel, A.; Manteiga, M.; Martayan, C.; Ordenovic, Ch.; Pichon, B.; Recio-Blanco, A.; Rocca-Volmerange, B.; Sarro, L. M.; Smith, K.; Sordo, R.; Soubiran, C.; Surdej, J.; Thévenin, F.; Tsalmantza, P.; Vallenari, A.; Zorec, J.

    2013-11-01

    The Gaia satellite will survey the entire celestial sphere down to 20th magnitude, obtaining astrometry, photometry, and low resolution spectrophotometry on one billion astronomical sources, plus radial velocities for over one hundred million stars. Itsmain objective is to take a census of the stellar content of our Galaxy, with the goal of revealing its formation and evolution. Gaia's unique feature is the measurement of parallaxes and proper motions with hitherto unparalleled accuracy for many objects. As a survey, the physical properties of most of these objects are unknown. Here we describe the data analysis system put together by the Gaia consortium to classify these objects and to infer their astrophysical properties using the satellite's data. This system covers single stars, (unresolved) binary stars, quasars, and galaxies, all covering a wide parameter space. Multiple methods are used for many types of stars, producing multiple results for the end user according to different models and assumptions. Prior to its application to real Gaia data the accuracy of these methods cannot be assessed definitively. But as an example of the current performance, we can attain internal accuracies (rms residuals) on F, G, K, M dwarfs and giants at G = 15 (V = 15-17) for a wide range of metallicites and interstellar extinctions of around 100 K in effective temperature (Teff), 0.1 mag in extinction (A0), 0.2 dex in metallicity ([Fe/H]), and 0.25 dex in surface gravity (log g). The accuracy is a strong function of the parameters themselves, varying by a factor of more than two up or down over this parameter range. After its launch in December 2013, Gaia will nominally observe for five years, during which the system we describe will continue to evolve in light of experience with the real data.

  11. A Neuro-Fuzzy Inference System Combining Wavelet Denoising, Principal Component Analysis, and Sequential Probability Ratio Test for Sensor Monitoring

    SciTech Connect

    Na, Man Gyun; Oh, Seungrohk

    2002-11-15

    A neuro-fuzzy inference system combined with the wavelet denoising, principal component analysis (PCA), and sequential probability ratio test (SPRT) methods has been developed to monitor the relevant sensor using the information of other sensors. The parameters of the neuro-fuzzy inference system that estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The wavelet denoising technique was applied to remove noise components in input signals into the neuro-fuzzy system. By reducing the dimension of an input space into the neuro-fuzzy system without losing a significant amount of information, the PCA was used to reduce the time necessary to train the neuro-fuzzy system, simplify the structure of the neuro-fuzzy inference system, and also, make easy the selection of the input signals into the neuro-fuzzy system. By using the residual signals between the estimated signals and the measured signals, the SPRT is applied to detect whether the sensors are degraded or not. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level, the pressurizer pressure, and the hot-leg temperature sensors in pressurized water reactors.

  12. Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study.

    PubMed

    Heddam, Salim

    2014-01-01

    This article presents a comparison of two adaptive neuro-fuzzy inference systems (ANFIS)-based neuro-fuzzy models applied for modeling dissolved oxygen (DO) concentration. The two models are developed using experimental data collected from the bottom (USGS station no: 420615121533601) and top (USGS station no: 420615121533600) stations at Klamath River at site KRS12a nr Rock Quarry, Oregon, USA. The input variables used for the ANFIS models are water pH, temperature, specific conductance, and sensor depth. Two ANFIS-based neuro-fuzzy systems are presented. The two neuro-fuzzy systems are: (1) grid partition-based fuzzy inference system, named ANFIS_GRID, and (2) subtractive-clustering-based fuzzy inference system, named ANFIS_SUB. In both models, 60 % of the data set was randomly assigned to the training set, 20 % to the validation set, and 20 % to the test set. The ANFIS results are compared with multiple linear regression models. The system proposed in this paper shows a novelty approach with regard to the usage of ANFIS models for DO concentration modeling.

  13. Physical connectivity in the Mesoamerican Barrier Reef System inferred from 9 years of ocean color observations

    NASA Astrophysics Data System (ADS)

    Soto, I.; Andréfouët, S.; Hu, C.; Muller-Karger, F. E.; Wall, C. C.; Sheng, J.; Hatcher, B. G.

    2009-06-01

    Ocean color images acquired from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) from 1998 to 2006 were used to examine the patterns of physical connectivity between land and reefs, and among reefs in the Mesoamerican Barrier Reef System (MBRS) in the northwestern Caribbean Sea. Connectivity was inferred by tracking surface water features in weekly climatologies and a time series of weekly mean chlorophyll- a concentrations derived from satellite imagery. Frequency of spatial connections between 17 pre-defined, geomorphological domains that include the major reefs in the MBRS and river deltas in Honduras and Nicaragua were recorded and tabulated as percentage of connections. The 9-year time series of 466 weekly mean images portrays clearly the seasonal patterns of connectivity, including river plumes and transitions in the aftermath of perturbations such as hurricanes. River plumes extended offshore from the Honduras coast to the Bay Islands (Utila, Cayo Cochinos, Guanaja, and Roatán) in 70% of the weekly mean images. Belizean reefs, especially those in the southern section of the barrier reef and Glovers Atoll, were also affected by riverine discharges in every one of the 9 years. Glovers Atoll was exposed to river plumes originating in Honduras 104/466 times (22%) during this period. Plumes from eastern Honduras went as far as Banco Chinchorro and Cozumel in Mexico. Chinchorro appeared to be more frequently connected to Turneffe Atoll and Honduran rivers than with Glovers and Lighthouse Atolls, despite their geographic proximity. This new satellite data analysis provides long-term, quantitative assessments of the main pathways of connectivity in the region. The percentage of connections can be used to validate predictions made using other approaches such as numerical modeling, and provides valuable information to ecosystem-based management in coral reef provinces.

  14. Information Warfare-Worthy Jamming Attack Detection Mechanism for Wireless Sensor Networks Using a Fuzzy Inference System

    PubMed Central

    Misra, Sudip; Singh, Ranjit; Rohith Mohan, S. V.

    2010-01-01

    The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes. PMID:22319307

  15. Information warfare-worthy jamming attack detection mechanism for wireless sensor networks using a fuzzy inference system.

    PubMed

    Misra, Sudip; Singh, Ranjit; Rohith Mohan, S V

    2010-01-01

    The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes.

  16. Inferring cortical function in the mouse visual system through large-scale systems neuroscience.

    PubMed

    Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

    2016-07-05

    The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort.

  17. Inferring cortical function in the mouse visual system through large-scale systems neuroscience

    PubMed Central

    Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W.; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R. Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

    2016-01-01

    The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort. PMID:27382147

  18. Prediction analysis and comparison between agriculture and mining stocks in Indonesia by using adaptive neuro-fuzzy inference system (ANFIS)

    NASA Astrophysics Data System (ADS)

    Mahandrio, Irsantyo; Budi, Andriantama; Liong, The Houw; Purqon, Acep

    2015-09-01

    The growing patterns in cultural and mining sectors are interesting particularly in developed country such as in Indonesia. Here, we investigate the local characteristics of stocks between the sectors of agriculture and mining which si representing two leading companies and two common companies in these sectors. We analyze the prediction by using Adaptive Neuro Fuzzy Inference System (ANFIS). The type of Fuzzy Inference System (FIS) is Sugeno type with Generalized Bell membership function (Gbell). Our results show that ANFIS is a proper method to predicting the stock market with the RMSE : 0.14% for AALI and 0.093% for SGRO representing the agriculture sectors, meanwhile, 0.073% for ANTM and 0.1107% for MDCO representing the mining sectors.

  19. Causal Inference and System Dynamics in Social Science Research: A Commentary with Example.

    ERIC Educational Resources Information Center

    Morris, Don R.

    The focus of this paper is causal inference in social and educational research. A concern with causality has had a profound impact on the kinds of questions that may be addressed in research, on how they must be formulated, and on the methodology that must be applied. In the social sciences the prevailing experimental paradigm is used to address…

  20. Astrophysical Site of the Origin of the Solar System Inferred from Extinct Radionuclide Abundances

    NASA Astrophysics Data System (ADS)

    Harper, Charles L., Jr.

    1996-08-01

    Extinct radionuclides in the solar abundance distribution (SAD) provide a basis with which to characterize the molecular cloud environment in which the solar system formed 4566±2 Ma ago. The low abundance of the longer-lived r-process radionuclide 129I(T½ = 16 Ma) indicates a long (˜ 102 Ma) isolation time from energetic interstellar medium (ISM) reservoirs containing most of the Galaxy's budget of freshly-synthesized Type II supernova products. However, the abundances of the shorter-lived species 60Fe (T½ = 1.5 Ma), 53Mn (T½ = 3.7 Ma), and 107Pd (T½ = 6.5 Ma) are consistent with late admixture of freshly synthesized Type II supernova products. The fit for these species is based on an average yield distribution obtained by decomposition of the SAD. The apparent timescale contradiction is resolved in a simple two timescale molecular cloud self-contamination model consistent with formation of the Sun in an old evolved stellar complex at the eroding boundary of a molecular cloud interacting with an adjacent OB association. Admixture of an ˜10-5 to ˜10-6 mass fraction of Type II supernova ejecta into the presolar cloud dominates the shorter-lived species and 107Pd, whereas longer- lived 129I preserves information on the longer timescale constraining the mean isolation/condensation/ accretion age of the molecular material in the protosolar reservoir. The inferred model age of nucleosynthetic isolation in the long timescale is consistent with cyclicity in the nucleosynthesis rate in an orbiting ISM parcel controlled by galactic spiral structure and beads-on-a-string organization of star formation in "stellar complexes" in arms. Abundant 26Al (T½ = 0.7 Ma) in the early solar system at ˜102 times the model prediction may point to 26Al/27Al ratio of ˜0.2 in the source, or an ˜102 times greater mixing fraction for pre-explosion winds over postexplosion ejecta. A mass-losing low-mass asymptotic giant branch (AGB) star model can be tuned to account for 41Ca, 26Al

  1. The new physician as unwitting quantum mechanic: is adapting Dirac's inference system best practice for personalized medicine, genomics, and proteomics?

    PubMed

    Robson, Barry

    2007-08-01

    What is the Best Practice for automated inference in Medical Decision Support for personalized medicine? A known system already exists as Dirac's inference system from quantum mechanics (QM) using bra-kets and bras where A and B are states, events, or measurements representing, say, clinical and biomedical rules. Dirac's system should theoretically be the universal best practice for all inference, though QM is notorious as sometimes leading to bizarre conclusions that appear not to be applicable to the macroscopic world of everyday world human experience and medical practice. It is here argued that this apparent difficulty vanishes if QM is assigned one new multiplication function @, which conserves conditionality appropriately, making QM applicable to classical inference including a quantitative form of the predicate calculus. An alternative interpretation with the same consequences is if every i = radical-1 in Dirac's QM is replaced by h, an entity distinct from 1 and i and arguably a hidden root of 1 such that h2 = 1. With that exception, this paper is thus primarily a review of the application of Dirac's system, by application of linear algebra in the complex domain to help manipulate information about associations and ontology in complicated data. Any combined bra-ket can be shown to be composed only of the sum of QM-like bra and ket weights c(), times an exponential function of Fano's mutual information measure I(A; B) about the association between A and B, that is, an association rule from data mining. With the weights and Fano measure re-expressed as expectations on finite data using Riemann's Incomplete (i.e., Generalized) Zeta Functions, actual counts of observations for real world sparse data can be readily utilized. Finally, the paper compares identical character, distinguishability of states events or measurements, correlation, mutual information, and orthogonal character, important issues in data mining

  2. An application of adaptive neuro-fuzzy inference system to landslide susceptibility mapping (Klang valley, Malaysia)

    NASA Astrophysics Data System (ADS)

    Sezer, Ebru; Pradhan, Biswajeet; Gokceoglu, Candan

    2010-05-01

    Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. Recently, the Klang Valley area of Selangor state has faced numerous landslide and mudflow events and much damage occurred in these areas. However, only little effort has been made to assess or predict these events which resulted in serious damages. Through scientific analyses of these landslides, one can assess and predict landslide-susceptible areas and even the events as such, and thus reduce landslide damages through proper preparation and/or mitigation. For this reason , the purpose of the present paper is to produce landslide susceptibility maps of a part of the Klang Valley areas in Malaysia by employing the results of the adaptive neuro-fuzzy inference system (ANFIS) analyses. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments and NDVI were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, plan curvature, distance from drainage, soil type, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to construct the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were obtained by using ANFIS results. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 98% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient

  3. Crustal deformation in the central California coast region inferred from Global Positioning System data

    NASA Astrophysics Data System (ADS)

    Murray-Moraleda, J. R.; Thatcher, W. R.; Onishi, C. T.; Svarc, J. L.

    2011-12-01

    The Central California Coast Region (CCCR), defined here as the area from north of Point Piedras Blancas (36°N) south to Point Arguello (34.6°N) and west of the Rinconada and East Huasna faults, is a structurally complex region cut by several subparallel, late Quaternary faults. Despite relatively low rates of deformation inferred from geologic studies of the CCCR, the occurrence of the 2003 Mw 6.5 San Simeon earthquake southeast of Point Piedras Blancas highlights the need to better understand the ongoing patterns of deformation here as a means for assessing the seismic hazard. Geological and geophysical data from this region have been interpreted as evidence for ongoing transpression due to the clockwise rotation of the Transverse Ranges which would predict crustal contraction normal to the plate boundary. However an alternative interpretation concludes that the region instead experiences the active westward transfer of right-lateral strike-slip motion in a left-stepping fashion which would result in northwest-southeast contraction. Geodetic data can be used to elucidate how strain is currently partitioned between shear parallel to the San Andreas Fault (SAF) and contraction within the CCCR and to identify actively deforming structures. We use a newly compiled Global Positioning System (GPS) secular velocity field for the CCCR as well as GPS velocities for the greater southern California region from the SCEC Crustal Motion Map v.4 and the EarthScope Plate Boundary Observatory velocity solution to constrain block models of deformation. We solve for the rotation of fault-bounded blocks, fault slip rates, and internal strain within blocks. Results thus far indicate that the data do not require substantial slip on the Rinconada fault (for which the estimated slip rate is ~2 mm/yr) or on the Oceanic and West Huasna faults that bound the eastern edge of the CCCR in an alternative block configuration (for which the estimated slip rate is <1 mm/yr). The data also do

  4. Single-trial lambda wave identification using a fuzzy inference system and predictive statistical diagnosis

    NASA Astrophysics Data System (ADS)

    Saatchi, R.

    2004-03-01

    The aim of the study was to automate the identification of a saccade-related visual evoked potential (EP) called the lambda wave. The lambda waves were extracted from single trials of electroencephalogram (EEG) waveforms using independent component analysis (ICA). A trial was a set of EEG waveforms recorded from 64 scalp electrode locations while a saccade was performed. Forty saccade-related EEG trials (recorded from four normal subjects) were used in the study. The number of waveforms per trial was reduced from 64 to 22 by pre-processing. The application of ICA to the resulting waveforms produced 880 components (i.e. 4 subjects × 10 trials per subject × 22 components per trial). The components were divided into 373 lambda and 507 nonlambda waves by visual inspection and then they were represented by one spatial and two temporal features. The classification performance of a Bayesian approach called predictive statistical diagnosis (PSD) was compared with that of a fuzzy logic approach called a fuzzy inference system (FIS). The outputs from the two classification approaches were then combined and the resulting discrimination accuracy was evaluated. For each approach, half the data from the lambda and nonlambda wave categories were used to determine the operating parameters of the classification schemes while the rest (i.e. the validation set) were used to evaluate their classification accuracies. The sensitivity and specificity values when the classification approaches were applied to the lambda wave validation data set were as follows: for the PSD 92.51% and 91.73% respectively, for the FIS 95.72% and 89.76% respectively, and for the combined FIS and PSD approach 97.33% and 97.24% respectively (classification threshold was 0.5). The devised signal processing techniques together with the classification approaches provided for an effective extraction and classification of the single-trial lambda waves. However, as only four subjects were included, it will be

  5. Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms.

    PubMed

    Razavi Termeh, Seyed Vahid; Kornejady, Aiding; Pourghasemi, Hamid Reza; Keesstra, Saskia

    2017-10-04

    Flood is one of the most destructive natural disasters which cause great financial and life losses per year. Therefore, producing susceptibility maps for flood management are necessary in order to reduce its harmful effects. The aim of the present study is to map flood hazard over the Jahrom Township in Fars Province using a combination of adaptive neuro-fuzzy inference systems (ANFIS) with different metaheuristics algorithms such as ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO) and comparing their accuracy. A total number of 53 flood locations areas were identified, 35 locations of which were randomly selected in order to model flood susceptibility and the remaining 16 locations were used to validate the models. Learning vector quantization (LVQ), as one of the supervised neural network methods, was employed in order to estimate factors' importance. Nine flood conditioning factors namely: slope degree, plan curvature, altitude, topographic wetness index (TWI), stream power index (SPI), distance from river, land use/land cover, rainfall, and lithology were selected and the corresponding maps were prepared in ArcGIS. The frequency ratio (FR) model was used to assign weights to each class within particular controlling factor, then the weights was transferred into MATLAB software for further analyses and to combine with metaheuristic models. The ANFIS-PSO was found to be the most practical model in term of producing the highly focused flood susceptibility map with lesser spatial distribution related to highly susceptible classes. The chi-square result attests the same, where the ANFIS-PSO had the highest spatial differentiation within flood susceptibility classes over the study area. The area under the curve (AUC) obtained from ROC curve indicated the accuracy of 91.4%, 91.8%, 92.6% and 94.5% for the respective models of FR, ANFIS-ACO, ANFIS-GA, and ANFIS-PSO ensembles. So, the ensemble of ANFIS-PSO was introduced as the

  6. Three dimensional model of the lithosphere-astenosphere system in the area of the apulian plate

    NASA Astrophysics Data System (ADS)

    Venisti, N.; Calcagnile, G.; Cimini, G. B.; Pierri, P.; del Gaudio, V.

    2003-04-01

    New results of tomographic processing of surface and body wave data provided some evidence of structural differences in crust-mantle transition between northern and southern part of the Apulian plate, playing an important role in the geodynamic evolution of the Central Mediterranean. In order to support the inferences derived from tomographic data and to better constrain the lateral limits of these heterogeneities, Bouguer anomalies, available in the area, based on data supplied by the Italian Petrol Agency (AGIP), were processed and interpreted through a 2D1/2 density modelling. In the southern part of the Apulian plate, the obtained results suggest the presence, with respect to the northern part, of a thinner typical crust combined with a thicker transition zone having a slightly lower density than the more typical mantle material. The northern Apulian structure either has a transition zone of marginal properties or no transition zone at all with a crust-mantle passage relatively sharp. Moreover the results obtained combining different methodologies, including inversion of teleseismic events arrival times, allowed the definitions of a three-dimensional model for the southern part of the Apulian plate down to about 200km.

  7. Measure of librarian pressure using fuzzy inference system: A case study in Longyan University

    NASA Astrophysics Data System (ADS)

    Huang, Jian-Jing

    2014-10-01

    As the hierarchy of middle managers in college's librarian. They may own much work pressure from their mind. How to adapt psychological problem, control the emotion and keep a good relationship in their work place, it becomes an important issue. Especially, they work in China mainland environment. How estimate the librarians work pressure and improve the quality of service in college libraries. Those are another serious issues. In this article, the authors would like discuss how can we use fuzzy inference to test librarian work pressure.

  8. Testing Mendelian inheritance from field-collected parasites: Revealing duplicated loci enables correct inference of reproductive mode and mating system.

    PubMed

    Detwiler, Jillian T; Criscione, Charles D

    2011-09-01

    Cryptic aspects of parasite population biology, e.g., mating systems, are increasingly being inferred from polymorphic and co-dominant genetic markers such as microsatellite loci. Underlying the use of such co-dominant markers is the assumption of Mendelian inheritance. The failure to meet this assumption can lead to artifactual statistics and erroneous population inferences. Here, we illustrate the importance of testing the Mendelian segregation and assortment of genetic markers and demonstrate how field-collected samples can be utilised for this purpose. To examine the reproductive mode and mating system of hermaphroditic parasites, we developed microsatellites for the cestode, Oochoristica javaensis. Among loci, we found a bimodal distribution of F(IS) (a fixation index that quantifies the deviation from Hardy-Weinberg equilibrium within subpopulations) values where loci were either highly negative (close to -1) or highly positive (∼0.8). By conducting tests of Mendelian segregation from natural crosses, we determined that loci with negative F(IS) values were in fact duplicated loci that were amplified by a single primer pair. Genetic crosses also provided linkage data and indicated that the duplicated loci most likely arose via tandem duplications rather than whole genome/chromosome duplications. By correcting for the duplicated loci, we were able to correctly infer that O. javaensis has sexual reproduction, but the mating system is highly inbred. To assist others in testing Mendelian segregation and independent assortment from natural samples, we discuss the benefits and limitations, and provide guidelines for particular parasite systems amenable to the methods employed here.

  9. LEON-BIS: multiple alignment evaluation of sequence neighbours using a Bayesian inference system.

    PubMed

    Vanhoutreve, Renaud; Kress, Arnaud; Legrand, Baptiste; Gass, Hélène; Poch, Olivier; Thompson, Julie D

    2016-07-07

    A standard procedure in many areas of bioinformatics is to use a multiple sequence alignment (MSA) as the basis for various types of homology-based inference. Applications include 3D structure modelling, protein functional annotation, prediction of molecular interactions, etc. These applications, however sophisticated, are generally highly sensitive to the alignment used, and neglecting non-homologous or uncertain regions in the alignment can lead to significant bias in the subsequent inferences. Here, we present a new method, LEON-BIS, which uses a robust Bayesian framework to estimate the homologous relations between sequences in a protein multiple alignment. Sequences are clustered into sub-families and relations are predicted at different levels, including 'core blocks', 'regions' and full-length proteins. The accuracy and reliability of the predictions are demonstrated in large-scale comparisons using well annotated alignment databases, where the homologous sequence segments are detected with very high sensitivity and specificity. LEON-BIS uses robust Bayesian statistics to distinguish the portions of multiple sequence alignments that are conserved either across the whole family or within subfamilies. LEON-BIS should thus be useful for automatic, high-throughput genome annotations, 2D/3D structure predictions, protein-protein interaction predictions etc.

  10. Design of a modified adaptive neuro fuzzy inference system classifier for medical diagnosis of Pima Indians Diabetes

    NASA Astrophysics Data System (ADS)

    Sagir, Abdu Masanawa; Sathasivam, Saratha

    2017-08-01

    Medical diagnosis is the process of determining which disease or medical condition explains a person's determinable signs and symptoms. Diagnosis of most of the diseases is very expensive as many tests are required for predictions. This paper aims to introduce an improved hybrid approach for training the adaptive network based fuzzy inference system with Modified Levenberg-Marquardt algorithm using analytical derivation scheme for computation of Jacobian matrix. The goal is to investigate how certain diseases are affected by patient's characteristics and measurement such as abnormalities or a decision about presence or absence of a disease. To achieve an accurate diagnosis at this complex stage of symptom analysis, the physician may need efficient diagnosis system to classify and predict patient condition by using an adaptive neuro fuzzy inference system (ANFIS) pre-processed by grid partitioning. The proposed hybridised intelligent system was tested with Pima Indian Diabetes dataset obtained from the University of California at Irvine's (UCI) machine learning repository. The proposed method's performance was evaluated based on training and test datasets. In addition, an attempt was done to specify the effectiveness of the performance measuring total accuracy, sensitivity and specificity. In comparison, the proposed method achieves superior performance when compared to conventional ANFIS based gradient descent algorithm and some related existing methods. The software used for the implementation is MATLAB R2014a (version 8.3) and executed in PC Intel Pentium IV E7400 processor with 2.80 GHz speed and 2.0 GB of RAM.

  11. Fuzzy inference systems, ASKE, knowledge value added, and Monte Carlo risk simulation for evaluating intangible human capital investments

    NASA Astrophysics Data System (ADS)

    Mun, Johnathan; de Albuquerque, Nelson R.; Liong, Choong-Yeun; Salleh, Abdul Razak

    2013-04-01

    This paper presents the ASKE-Risk method, coupled with Fuzzy Inference Systems, and Monte Carlo Risk Simulation to measure and prioritize Individual Technical Competence of a value chain to assess changes in the human capital of a company. ASKE is an extension of the method Knowledge Value Added, which proposes the use of a proxy variable for measuring the flow of knowledge used in a key process, creating a relationship between the company's financial results and the resources used in each of the business processes.

  12. Inference of S-system models of genetic networks by solving one-dimensional function optimization problems.

    PubMed

    Kimura, S; Araki, D; Matsumura, K; Okada-Hatakeyama, M

    2012-02-01

    Voit and Almeida have proposed the decoupling approach as a method for inferring the S-system models of genetic networks. The decoupling approach defines the inference of a genetic network as a problem requiring the solutions of sets of algebraic equations. The computation can be accomplished in a very short time, as the approach estimates S-system parameters without solving any of the differential equations. Yet the defined algebraic equations are non-linear, which sometimes prevents us from finding reasonable S-system parameters. In this study, we propose a new technique to overcome this drawback of the decoupling approach. This technique transforms the problem of solving each set of algebraic equations into a one-dimensional function optimization problem. The computation can still be accomplished in a relatively short time, as the problem is transformed by solving a linear programming problem. We confirm the effectiveness of the proposed approach through numerical experiments. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Fuzzy logic and adaptive neuro-fuzzy inference system for characterization of contaminant exposure through selected biomarkers in African catfish.

    PubMed

    Karami, Ali; Keiter, Steffen; Hollert, Henner; Courtenay, Simon C

    2013-03-01

    This study represents a first attempt at applying a fuzzy inference system (FIS) and an adaptive neuro-fuzzy inference system (ANFIS) to the field of aquatic biomonitoring for classification of the dosage and time of benzo[a]pyrene (BaP) injection through selected biomarkers in African catfish (Clarias gariepinus). Fish were injected either intramuscularly (i.m.) or intraperitoneally (i.p.) with BaP. Hepatic glutathione S-transferase (GST) activities, relative visceral fat weights (LSI), and four biliary fluorescent aromatic compounds (FACs) concentrations were used as the inputs in the modeling study. Contradictory rules in FIS and ANFIS models appeared after conversion of bioassay results into human language (rule-based system). A "data trimming" approach was proposed to eliminate the conflicts prior to fuzzification. However, the model produced was relevant only to relatively low exposures to BaP, especially through the i.m. route of exposure. Furthermore, sensitivity analysis was unable to raise the classification rate to an acceptable level. In conclusion, FIS and ANFIS models have limited applications in the field of fish biomarker studies.

  14. Statistical Inference

    NASA Astrophysics Data System (ADS)

    Khan, Shahjahan

    Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden "jewels" in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model

  15. Statistical Inference

    NASA Astrophysics Data System (ADS)

    Khan, Shahjahan

    Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden “jewels” in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model

  16. Non-exponential tolerance to infection in epidemic systems--modeling, inference, and assessment.

    PubMed

    Streftaris, George; Gibson, Gavin J

    2012-09-01

    The transmission dynamics of infectious diseases have been traditionally described through a time-inhomogeneous Poisson process, thus assuming exponentially distributed levels of disease tolerance following the Sellke construction. Here we focus on a generalization using Weibull individual tolerance thresholds under the susceptible-exposed-infectious-removed class of models which is widely employed in epidemics. Applications with experimental foot-and-mouth disease and historical smallpox data are discussed, and simulation results are presented. Inference is carried out using Markov chain Monte Carlo methods following a Bayesian approach. Model evaluation is performed, where the adequacy of the models is assessed using methodology based on the properties of Bayesian latent residuals, and comparison between 2 candidate models is also considered using a latent likelihood ratio-type test that avoids problems encountered with relevant methods based on Bayes factors.

  17. Structural Information Inference from Lanthanoid Complexing Systems: Photoluminescence Studies on Isolated Ions

    NASA Astrophysics Data System (ADS)

    Greisch, Jean Francois; Harding, Michael E.; Chmela, Jiri; Klopper, Willem M.; Schooss, Detlef; Kappes, Manfred M.

    2016-06-01

    The application of lanthanoid complexes ranges from photovoltaics and light-emitting diodes to quantum memories and biological assays. Rationalization of their design requires a thorough understanding of intramolecular processes such as energy transfer, charge transfer, and non-radiative decay involving their subunits. Characterization of the excited states of such complexes considerably benefits from mass spectrometric methods since the associated optical transitions and processes are strongly affected by stoichiometry, symmetry, and overall charge state. We report herein spectroscopic measurements on ensembles of ions trapped in the gas phase and soft-landed in neon matrices. Their interpretation is considerably facilitated by direct comparison with computations. The combination of energy- and time-resolved measurements on isolated species with density functional as well as ligand-field and Franck-Condon computations enables us to infer structural as well as dynamical information about the species studied. The approach is first illustrated for sets of model lanthanoid complexes whose structure and electronic properties are systematically varied via the substitution of one component (lanthanoid or alkali,alkali-earth ion): (i) systematic dependence of ligand-centered phosphorescence on the lanthanoid(III) promotion energy and its impact on sensitization, and (ii) structural changes induced by the substitution of alkali or alkali-earth ions in relation with structures inferred using ion mobility spectroscopy. The temperature dependence of sensitization is briefly discussed. The focus is then shifted to measurements involving europium complexes with doxycycline an antibiotic of the tetracycline family. Besides discussing the complexes' structural and electronic features, we report on their use to monitor enzymatic processes involving hydrogen peroxide or biologically relevant molecules such as adenosine triphosphate (ATP).

  18. Fuzzy logic inference-based Pavement Friction Management and real-time slippery warning systems: A proof of concept study.

    PubMed

    Najafi, Shahriar; Flintsch, Gerardo W; Khaleghian, Seyedmeysam

    2016-05-01

    Minimizing roadway crashes and fatalities is one of the primary objectives of highway engineers, and can be achieved in part through appropriate maintenance practices. Maintaining an appropriate level of friction is a crucial maintenance practice, due to the effect it has on roadway safety. This paper presents a fuzzy logic inference system that predicts the rate of vehicle crashes based on traffic level, speed limit, and surface friction. Mamdani and Sugeno fuzzy controllers were used to develop the model. The application of the proposed fuzzy control system in a real-time slippery road warning system is demonstrated as a proof of concept. The results of this study provide a decision support model for highway agencies to monitor their network's friction and make appropriate judgments to correct deficiencies based on crash risk. Furthermore, this model can be implemented in the connected vehicle environment to warn drivers of potentially slippery locations. Published by Elsevier Ltd.

  19. Application of Artificial Neuro-Fuzzy Logic Inference System for Predicting the Microbiological Pollution in Fresh Water

    NASA Astrophysics Data System (ADS)

    Bouharati, S.; Benmahammed, K.; Harzallah, D.; El-Assaf, Y. M.

    The classical methods for detecting the micro biological pollution in water are based on the detection of the coliform bacteria which indicators of contamination. But to check each water supply for these contaminants would be a time-consuming job and a qualify operators. In this study, we propose a novel intelligent system which provides a detection of microbiological pollution in fresh water. The proposed system is a hierarchical integration of an Artificial Neuro-Fuzzy Inference System (ANFIS). This method is based on the variations of the physical and chemical parameters occurred during bacteria growth. The instantaneous result obtained by the measurements of the variations of the physical and chemical parameters occurred during bacteria growth-temperature, pH, electrical potential and electrical conductivity of many varieties of water (surface water, well water, drinking water and used water) on the number Escherichia coli in water. The instantaneous result obtained by measurements of the inputs parameters of water from sensors.

  20. Hydrological connectivity inferred from diatom transport through the riparian-stream system

    NASA Astrophysics Data System (ADS)

    Martínez-Carreras, N.; Wetzel, C. E.; Frentress, J.; Ector, L.; McDonnell, J. J.; Hoffmann, L.; Pfister, L.

    2015-07-01

    Diatoms (Bacillariophyta) are one of the most common and diverse algal groups (ca. 200 000 species, ≈ 10-200 μm, unicellular, eukaryotic). Here we investigate the potential of aerial diatoms (i.e. diatoms nearly exclusively occurring outside water bodies, in wet, moist or temporarily dry places) to infer surface hydrological connectivity between hillslope-riparian-stream (HRS) landscape units during storm runoff events. We present data from the Weierbach catchment (0.45 km2, northwestern Luxembourg) that quantify the relative abundance of aerial diatom species on hillslopes and in riparian zones (i.e. surface soils, litter, bryophytes and vegetation) and within streams (i.e. stream water, epilithon and epipelon). We tested the hypothesis that different diatom species assemblages inhabit specific moisture domains of the catchment (i.e. HRS units) and, consequently, the presence of certain species assemblages in the stream during runoff events offers the potential for recording whether there was hydrological connectivity between these domains or not. We found that a higher percentage of aerial diatom species was present in samples collected from the riparian and hillslope zones than inside the stream. However, diatoms were absent on hillslopes covered by dry litter and the quantities of diatoms (in absolute numbers) were small in the rest of hillslope samples. This limits their use for inferring hillslope-riparian zone connectivity. Our results also showed that aerial diatom abundance in the stream increased systematically during all sampled events (n = 11, 2011-2012) in response to incident precipitation and increasing discharge. This transport of aerial diatoms during events suggested a rapid connectivity between the soil surface and the stream. Diatom transport data were compared to two-component hydrograph separation, and end-member mixing analysis (EMMA) using stream water chemistry and stable isotope data. Hillslope overland flow was insignificant during

  1. RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

    SciTech Connect

    Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna

    2010-05-26

    RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

  2. Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Akhavan, P.; Karimi, M.; Pahlavani, P.

    2014-10-01

    Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL) created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.

  3. Application of fuzzy inference systems for classification of fetal heart rate tracings in relation to neonatal outcome.

    PubMed

    Czabański, Robert; Jezewski, Janusz; Wróbel, Janusz; Sikora, Jerzy; Jezewski, Michał

    2013-01-01

    Fetal monitoring based on the analysis of the fetal heart rate (FHR) signal is the most common method of biophysical assessment of fetal condition during pregnancy and labor Visual analysis of FHR signals presents a challenge due to a complex shape of the waveforms. Therefore, computer-aided fetal monitoring systems provide a number of parameters that are the result of the quantitative analysis of the registered signals. These parameters are the basis for a qualitative assessment of the fetal condition. The guidelines for the interpretation of FHR provided by FIGO are commonly used in clinical practice. On their basis a weighted fuzzy scoring system was constructed to assess the FHR tracings using the same criteria as those applied by expert clinicians. The effectiveness of the automated classification was evaluated in relation to the fetal outcome assessed by Apgar score. The proposed automated system for fuzzy classification is an extension of the scoring systems used for qualitative evaluation of the FHR tracings. A single fuzzy rule of the system corresponds to a single evaluation principle of a signal parameter derived from the FIGO guidelines. The inputs of the fuzzy system are the values of quantitative parameters of the FHR signal, whereas the system output, which is calculated in the process of fuzzy inference, defines the interpretation of the FHR tracing. The fuzzy evaluation process is a kind of diagnostic test, giving a negative or a positive result that can be compared with the fetal outcome assessment. The present retrospective study included a set of 2124 one-hour antenatal FHR tracings derived from 333 patients, recorded between 24 and 44 weeks of gestation (mean gestational age: 36 weeks). Various approaches for the research data analysis, depending on the method of interpretation of the individual patient-tracing relation, were used in the investigation. The quality of the fuzzy analysis was defined by the number of correct classifications (CC

  4. Adaptive Neuro-Fuzzy Inference System for Classification of Background EEG Signals from ESES Patients and Controls

    PubMed Central

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3–9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved. PMID:24790547

  5. Analysis prediction of Indonesian banks (BCA, BNI, MANDIRI) using adaptive neuro-fuzzy inference system (ANFIS) and investment strategies

    NASA Astrophysics Data System (ADS)

    Trianto, Andriantama Budi; Hadi, I. M.; Liong, The Houw; Purqon, Acep

    2015-09-01

    Indonesian economical development is growing well. It has effect for their invesment in Banks and the stock market. In this study, we perform prediction for the three blue chips of Indonesian bank i.e. BCA, BNI, and MANDIRI by using the method of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Takagi-Sugeno rules and Generalized bell (Gbell) as the membership function. Our results show that ANFIS perform good prediction with RMSE for BCA of 27, BNI of 5.29, and MANDIRI of 13.41, respectively. Furthermore, we develop an active strategy to gain more benefit. We compare between passive strategy versus active strategy. Our results shows that for the passive strategy gains 13 million rupiah, while for the active strategy gains 47 million rupiah in one year. The active investment strategy significantly shows gaining multiple benefit than the passive one.

  6. Adaptive neuro-fuzzy inference system for classification of background EEG signals from ESES patients and controls.

    PubMed

    Yang, Zhixian; Wang, Yinghua; Ouyang, Gaoxiang

    2014-01-01

    Background electroencephalography (EEG), recorded with scalp electrodes, in children with electrical status epilepticus during slow-wave sleep (ESES) syndrome and control subjects has been analyzed. We considered 10 ESES patients, all right-handed and aged 3-9 years. The 10 control individuals had the same characteristics of the ESES ones but presented a normal EEG. Recordings were undertaken in the awake and relaxed states with their eyes open. The complexity of background EEG was evaluated using the permutation entropy (PE) and sample entropy (SampEn) in combination with the ANOVA test. It can be seen that the entropy measures of EEG are significantly different between the ESES patients and normal control subjects. Then, a classification framework based on entropy measures and adaptive neuro-fuzzy inference system (ANFIS) classifier is proposed to distinguish ESES and normal EEG signals. The results are promising and a classification accuracy of about 89% is achieved.

  7. TDSDMI: Inference of time-delayed gene regulatory network using S-system model with delayed mutual information.

    PubMed

    Yang, Bin; Zhang, Wei; Wang, Haifeng; Song, Chuandong; Chen, Yuehui

    2016-05-01

    Regulatory interactions among target genes and regulatory factors occur instantaneously or with time-delay. In this paper, we propose a novel approach namely TDSDMI based on time-delayed S-system model (TDSS) model and delayed mutual information (DMI) to infer time-delay gene regulatory network (TDGRN). Firstly DMI is proposed to delete redundant regulator factors for each target gene. Secondly restricted gene expression programming (RGEP) is proposed as a new representation of the TDSS model to identify instantaneous and time-delayed interactions. To verify the effectiveness of the proposed method, TDSDMI is applied to both simulated and real biological datasets. Experimental results reveal that TDSDMI performs better than the recent reconstruction methods.

  8. The use of microsatellite variation to infer population structure and demographic history in a natural model system.

    PubMed

    Goldstein, D B; Roemer, G W; Smith, D A; Reich, D E; Bergman, A; Wayne, R K

    1999-02-01

    To assess the reliability of genetic markers it is important to compare inferences that are based on them to a priori expectations. In this article we present an analysis of microsatellite variation within and among populations of island foxes (Urocyon littoralis) on California's Channel Islands. We first show that microsatellite variation at a moderate number of loci (19) can provide an essentially perfect description of the boundaries between populations and an accurate representation of their historical relationships. We also show that the pattern of variation across unlinked microsatellite loci can be used to test whether population size has been constant or increasing. Application of these approaches to the island fox system indicates that microsatellite variation may carry considerably more information about population history than is currently being used.

  9. Simulation of SiGe:C HBTs using neural network and adaptive neuro-fuzzy inference system for RF applications

    NASA Astrophysics Data System (ADS)

    Karimi, Gholamreza; Banitalebi, Roza; Babaei Sedaghat, Sedigheh

    2013-07-01

    In this article, the small-signal equivalent circuit model of SiGe:C heterojunction bipolar transistors (HBTs) has directly been extracted from S-parameter data. Moreover, in this article, we present a new modelling approach using ANFIS (adaptive neuro-fuzzy inference system), which in general has a high degree of accuracy, simplicity and novelty (independent approach). Then measured and model-calculated data show an excellent agreement with less than 1.68 × 10-5% discrepancy in the frequency range of higher than 300 GHz over a wide range of bias points in ANFIS. The results show ANFIS model is better than ANN (artificial neural network) for redeveloping the model and increasing the input parameters.

  10. European Cenozoic rift system

    NASA Astrophysics Data System (ADS)

    Ziegler, Peter A.

    1992-07-01

    The European Cenozoic rift system extends from the coast of the North Sea to the Mediterranean over a distance of some 1100 km; it finds its southern prolongation in the Valencia Trough and a Plio-Pleistocene volcanic chain crossing the Atlas ranges. Development of this mega-rift was paralleled by orogenic activity in the Alps and Pyrenees. Major rift domes, accompanied by subsidence reversal of their axial grabens, developed 20-40 Ma after beginning of rifting. Uplift of the Rhenish Shield is related to progressive thermal lithospheric thinning; the Vosges-Black Forest and the Massif Central domes are probably underlain by asthenoliths emplaced at the crust/mantle boundary. Evolution of this rift system, is thought to be governed by the interaction of the Eurasian and African plates and by early phases of a plate-boundary reorganization that may lead to the break-up of the present continent assembly.

  11. Developing a Dynamic Inference Expert System to Support Individual Learning at Work

    ERIC Educational Resources Information Center

    Hung, Yu Hsin; Lin, Chun Fu; Chang, Ray I.

    2015-01-01

    In response to the rapid growth of information in recent decades, knowledge-based systems have become an essential tool for organizational learning. The application of electronic performance-support systems in learning activities has attracted considerable attention from researchers. Nevertheless, the vast, ever-increasing amount of information is…

  12. A Theory of Conditional Information for Probabilistic Inference in Intelligent Systems: 1. Interval of Events Approach

    DTIC Science & Technology

    1994-06-01

    This paper emphasizes the need to develop further probability theory at the service of probabilistic intelligent systems . In the field of...events,’ compatible with all conditional probability quantifications. We specify applications of this theory to various problems in intelligent systems . The

  13. Developing a Dynamic Inference Expert System to Support Individual Learning at Work

    ERIC Educational Resources Information Center

    Hung, Yu Hsin; Lin, Chun Fu; Chang, Ray I.

    2015-01-01

    In response to the rapid growth of information in recent decades, knowledge-based systems have become an essential tool for organizational learning. The application of electronic performance-support systems in learning activities has attracted considerable attention from researchers. Nevertheless, the vast, ever-increasing amount of information is…

  14. Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

    NASA Astrophysics Data System (ADS)

    Christensen, Claire Petra

    Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author

  15. Complexity of time series associated to dynamical systems inferred from independent component analysis

    NASA Astrophysics Data System (ADS)

    de Lauro, E.; de Martino, S.; Falanga, M.; Ciaramella, A.; Tagliaferri, R.

    2005-10-01

    A not trivial problem for every experimental time series associated to a natural system is to individuate the significant variables to describe the dynamics, i.e., the effective degrees of freedom. The application of independent component analysis (ICA) has provided interesting results in this direction, e.g., in the seismological and atmospheric field. Since all natural phenomena can be represented by dynamical systems, our aim is to check the performance of ICA in this general context to avoid ambiguities when investigating an unknown experimental system. We show many examples, representing linear, nonlinear, and stochastic processes, in which ICA seems to be an efficacious preanalysis able to give information about the complexity of the dynamics.

  16. Information theory and signal transduction systems: from molecular information processing to network inference.

    PubMed

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Response of hydrothermal system to stress transients at Lassen Volcanic Center, California, inferred from seismic interferometry with ambient noise

    NASA Astrophysics Data System (ADS)

    Taira, Taka'aki; Brenguier, Florent

    2016-10-01

    Time-lapse monitoring of seismic velocity at volcanic areas can provide unique insight into the property of hydrothermal and magmatic fluids and their temporal variability. We established a quasi real-time velocity monitoring system by using seismic interferometry with ambient noise to explore the temporal evolution of velocity in the Lassen Volcanic Center, Northern California. Our monitoring system finds temporal variability of seismic velocity in response to stress changes imparted by an earthquake and by seasonal environmental changes. Dynamic stress changes from a magnitude 5.7 local earthquake induced a 0.1 % velocity reduction at a depth of about 1 km. The seismic velocity susceptibility defined as ratio of seismic velocity change to dynamic stress change is estimated to be about 0.006 MPa-1, which suggests the Lassen hydrothermal system is marked by high-pressurized hydrothermal fluid. By combining geodetic measurements, our observation shows that the long-term seismic velocity fluctuation closely tracks snow-induced vertical deformation without time delay, which is most consistent with an hydrological load model (either elastic or poroelastic response) in which surface loading drives hydrothermal fluid diffusion that leads to an increase of opening of cracks and subsequently reductions of seismic velocity. We infer that heated-hydrothermal fluid in a vapor-dominated zone at a depth of 2-4 km range is responsible for the long-term variation in seismic velocity[Figure not available: see fulltext.

  18. Bayesian inference for functional response in a stochastic predator-prey system.

    PubMed

    Gilioli, Gianni; Pasquali, Sara; Ruggeri, Fabrizio

    2008-02-01

    We present a Bayesian method for functional response parameter estimation starting from time series of field data on predator-prey dynamics. Population dynamics is described by a system of stochastic differential equations in which behavioral stochasticities are represented by noise terms affecting each population as well as their interaction. We focus on the estimation of a behavioral parameter appearing in the functional response of predator to prey abundance when a small number of observations is available. To deal with small sample sizes, latent data are introduced between each pair of field observations and are considered as missing data. The method is applied to both simulated and observational data. The results obtained using different numbers of latent data are compared with those achieved following a frequentist approach. As a case study, we consider an acarine predator-prey system relevant to biological control problems.

  19. Bayesian Inference for Source Term Estimation: Application to the International Monitoring System Radionuclide Network

    DTIC Science & Technology

    2014-10-01

    such as the normal operation of nuclear reactors and the production and use of medical isotopes [1] which can create difficulties in the interpretation...of the radionuclides in the nuclear reactor and the possible behavior of these materials when subjected to the reactor - core meltdown conditions. 20...ternational Monitoring System radionuclide network for the verification of the Com- prehensive Nuclear -Test-Ban Treaty. The complexity of the

  20. Properties of the Irregular Satellite System around Uranus Inferred from K2, Herschel, and Spitzer Observations

    NASA Astrophysics Data System (ADS)

    Farkas-Takács, A.; Kiss, Cs.; Pál, A.; Molnár, L.; Szabó, Gy. M.; Hanyecz, O.; Sárneczky, K.; Szabó, R.; Marton, G.; Mommert, M.; Szakáts, R.; Müller, T.; Kiss, L. L.

    2017-09-01

    In this paper, we present visible-range light curves of the irregular Uranian satellites Sycorax, Caliban, Prospero, Ferdinand, and Setebos taken with the Kepler Space Telescope over the course of the K2 mission. Thermal emission measurements obtained with the Herschel/PACS and Spitzer/MIPS instruments of Sycorax and Caliban were also analyzed and used to determine size, albedo, and surface characteristics of these bodies. We compare these properties with the rotational and surface characteristics of irregular satellites in other giant planet systems and also with those of main belt and Trojan asteroids and trans-Neptunian objects. Our results indicate that the Uranian irregular satellite system likely went through a more intense collisional evolution than the irregular satellites of Jupiter and Saturn. Surface characteristics of Uranian irregular satellites seem to resemble the Centaurs and trans-Neptunian objects more than irregular satellites around other giant planets, suggesting the existence of a compositional discontinuity in the young solar system inside the orbit of Uranus.

  1. Taal volcanic hydrothermal system (Philippines) inferred by electromagnetic and other geophysical methods

    NASA Astrophysics Data System (ADS)

    Zlotnicki, Jacques; Toutain, Jean Paul; Sasai, Yoichi; Villacorte, Egardo; Bernard, Alain; Fauquet, Frederic; Nagao, Toshiyatsu

    2010-05-01

    On volcanoes which display hydrothermal/magmatic unrests, Electromagnetic (EM) methods can be combined with geochemical (GC) and thermal methods. The integration of these methods allows to image in detail hydrothermal systems, to find out possible scenarios of volcanic unrest, and to monitor the on-going activity with knowledge on the sources of heat, gas and fluid transfers. Since the 1990's the volcano shows recurrent periods of seismic activity, ground deformation, hydrothermal activity, and surface activity (geysers). Combined EM and GC methods noticeably contribute to map in detail the hydrothermal system and to analyse the sources of the activity: - Total magnetic field mapping evidences demagnetised zones over the two main areas forming the hydrothermal system (in the northern part of Main crater (MC)). These low magnetized areas are ascribed to thermal sources located at some hundreds metres of depth, - Self-potential surveys, delineate the contours of the fluids-heat transfer, and the northern and southern structural discontinuities enclosing the hydrothermal system, - Ground temperature gradient measurements evidence the distinctive heat transfer modes, from low fluxes related to soil temperature dominated by solar input to extremely high temperature gradients of 1200 °C m-1 or to more related to magmatic fluids. - Ground temperature and surface temperature of central acidic lake calculated by Thermal Aster imaging highlight the location of the most active ground fissures, outcrops and diffuse areas. Higher and larger anomalies are observed in the northern part of MC. A rough estimation of the thermal discharge in the northern part of the volcano gives 17 MW. - CO2 concentrations and fluxes from soil supply inform on fluids origin and on local processes operating along active fractures. Much higher carbon dioxide fluxes at MC sites confirm that the source of Taal activity is presently located in the northern part of the crater. - Heat and fluids release

  2. Methane leakage from evolving petroleum systems: Masses, rates and inferences for climate feedback

    NASA Astrophysics Data System (ADS)

    Berbesi, L. A.; di Primio, R.; Anka, Z.; Horsfield, B.; Wilkes, H.

    2014-02-01

    The immense mass of organic carbon contained in sedimentary systems, currently estimated at 1.56×1010 Tg (Des Marais et al., 1992), bears the potential of affecting global climate through the release of thermally or biologically generated methane to the atmosphere. Here we investigate the potential of naturally-occurring gas leakage, controlled by petroleum generation and degradation as a forcing mechanism for climate at geologic time scales. We addressed the potential methane contributions to the atmosphere during the evolution of petroleum systems in two different, petroliferous geological settings: the Western Canada Sedimentary Basin (WCSB) and the Central Graben area of the North Sea. Besides 3D numerical simulation, different types of mass balance and theoretical approaches were applied depending on the data available and the processes taking place in each basin. In the case of the WCSB, we estimate maximum thermogenic methane leakage rates in the order of 10-2-10-3 Tg/yr, and maximum biogenic methane generation rates of 10-2 Tg/yr. In the case of the Central Graben, maximum estimates for thermogenic methane leakage are in the order in 10-3 Tg/yr. Extrapolation of our results to a global scale suggests that, at least as a single process, thermal gas generation in hydrocarbon kitchen areas would not be able to influence climate, although it may contribute to a positive feedback. Conversely, only the sudden release of subsurface methane accumulations, formed over geologic timescales, can possibly allow for petroleum systems to exert an effect on climate.

  3. From Birdsong to Human Speech Recognition: Bayesian Inference on a Hierarchy of Nonlinear Dynamical Systems

    PubMed Central

    Yildiz, Izzet B.; von Kriegstein, Katharina; Kiebel, Stefan J.

    2013-01-01

    Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents—an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments. PMID:24068902

  4. From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

    PubMed

    Yildiz, Izzet B; von Kriegstein, Katharina; Kiebel, Stefan J

    2013-01-01

    Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

  5. Recharge Regimes of the Saq Aquifer System, Saudi Arabia: Inferences from Geochemical and Isotopic Compositions

    NASA Astrophysics Data System (ADS)

    Abouelmagd, A.; McCabe, M. F.; Castro, M. C.; Sultan, M.; Jana, R. B.; Al-Mashharawi, S.

    2014-12-01

    One of the most valuable groundwater reserves in Saudi Arabia is the Saq aquifer system (SAS), a thick (400-1200 meters) sandstone unit that extends across 300,000 km2 in Saudi Arabia and neighboring Jordan. Due to its high productivity and high water quality, current pumping and overexploitation of the aquifer has significantly lowered the groundwater level over the years. Understanding the recharge regimes of the SAS is critical for the development of sustainable exploitation of water resources in the region and for the establishment of appropriate management practices. In this study, we investigate the hydrologic setting of the SAS and seek to differentiate the degree of paleo versus modern contributions using a range of geochemical approaches. Multiple groundwater samples were collected from deep production wells tapping the SAS at depths between 375-1800 m and across a range of locations. Samples were analyzed for their chemical concentrations, stable isotopic compositions (δ18O and δ2H), and dissolved noble gas concentrations and isotopic ratios. Examining these data identifies unmixed pools of fossil groundwater at deeper depths as well as mixed shallower systems that indicate contributions from modern precipitation. Through isotopic and noble gas analyses, the relative age and timing of these recharge events was examined and show contributions from both glacial and inter-glacial periods, with some modest contributions from modern meteoric sources.

  6. Optical Inference Machines

    DTIC Science & Technology

    1988-06-27

    de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

  7. Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

    NASA Astrophysics Data System (ADS)

    Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

    2017-01-01

    People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

  8. Gradient Matching Methods for Computational Inference in Mechanistic Models for Systems Biology: A Review and Comparative Analysis.

    PubMed

    Macdonald, Benn; Husmeier, Dirk

    2015-01-01

    Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimized, so as to minimize some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.

  9. Genetic diversity in the Homosporous Fern Ophioglossum vulgatum (Ophioglossaceae) from South Korea: inference of mating system and population history.

    PubMed

    Chung, Mi Yoon; López-Pujol, Jordi; Chung, Jae Min; Moon, Myung-Ok; Chung, Myong Gi

    2013-03-01

    It is generally believed that the members of Ophioglossaceae have subterranean, potentially bisexual gametophytes, which favor intragametophytic selfing. In Ophioglossaceae, previous allozyme studies revealed substantial inbreeding within Botrychium species and Mankyua chejuense. However, little is known about the mating system in species of the genus Ophioglossum. Molecular marker analyses can provide insights into the relative occurrence of selfing versus cross-fertilization in the species of Ophioglossum. We investigated allozyme variation in 8 Korean populations of the homosporous fern Ophioglossum vulgatum to infer its mating system and to get some insight into the population-establishment history in South Korea. We detected homozygous genotypes for alternative alleles at several loci, which suggest the occurrence of intragametophytic self-fertilization. Populations harbor low within-population variation (% P = 7.2, A = 1.08, and H (e) = 0.026) and a high among-population differentiation (F (ST) = 0.733). This, together with the finding that alternative alleles were fixed at several loci, suggests that the number and size of populations of O. vulgatum might have been severely reduced during the last glaciation (i.e., due to its in situ persistence in small, isolated refugia). The combined effects of severe random genetic drift and high rates of intragametophytic selfing are likely responsible for the genetic structure displayed by this homosporous fern. Its low levels of genetic diversity in South Korea justify the implementation of some conservation measures to ensure its long-term preservation.

  10. Gradient Matching Methods for Computational Inference in Mechanistic Models for Systems Biology: A Review and Comparative Analysis

    PubMed Central

    Macdonald, Benn; Husmeier, Dirk

    2015-01-01

    Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimized, so as to minimize some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data. PMID:26636071

  11. Nebulon: a system for the inference of functional relationships of gene products from the rearrangement of predicted operons

    PubMed Central

    Janga, Sarath Chandra; Collado-Vides, Julio; Moreno-Hagelsieb, Gabriel

    2005-01-01

    Since operons are unstable across Prokaryotes, it has been suggested that perhaps they re-combine in a conservative manner. Thus, genes belonging to a given operon in one genome might re-associate in other genomes revealing functional relationships among gene products. We developed a system to build networks of functional relationships of gene products based on their organization into operons in any available genome. The operon predictions are based on inter-genic distances. Our system can use different kinds of thresholds to accept a functional relationship, either related to the prediction of operons, or to the number of non-redundant genomes that support the associations. We also work by shells, meaning that we decide on the number of linking iterations to allow for the complementation of related gene sets. The method shows high reliability benchmarked against knowledge-bases of functional interactions. We also illustrate the use of Nebulon in finding new members of regulons, and of other functional groups of genes. Operon rearrangements produce thousands of high-quality new interactions per prokaryotic genome, and thousands of confirmations per genome to other predictions, making it another important tool for the inference of functional interactions from genomic context. PMID:15867197

  12. [The System of the Suborder Zoarcoidei (Pisces, Perciformes) as Inferred from Molecular Genetic Data].

    PubMed

    Radchenko, O A

    2015-11-01

    Based on an analysis of sequence variation in mitochondrial and nuclear markers, the levels of divergence, relationships, and system of the suborder Zoarcoidei was defined. It was demonstrated that DNA lineages of the families Bathymasteridae and Cebidichthyidae were positioned at the bottom ofthe suborder phylogenetic tree. The family Zoarcidae is a monophyletic group, the youngest in the evolutionary terms. Zoarcidae, Anarhichadidae, Neozorcidae, and Eulophiidae form a group of related families. The family Stichaeidae is heterogeneous and has a polyphyletic origin; within this family, the subfamilies Chirolophinae, Alectgiinae, Xiphisterinae, and Stichaeinae are sister taxa. The subfamilies Opisthocentrinae and Lumpeninae are isolated from Stichaedae; Opisthocentrinae is closely associated with the families Pholidae and Ptilichthyidae, and Lumpeninae is closely associated with Zaproridae and Cryptacanthodidae. It is suggested that the rank of subfamilies Opisthocentrinae and Lumpeninae should be raised.

  13. Observations of ionospheric gravity and diamagnetic current systems inferred from CHAMP and Swarm measurements

    NASA Astrophysics Data System (ADS)

    Alken, P.

    2015-12-01

    Large scale currents in the ionosphere are driven by a variety of sources, including neutral winds, gravity, and plasma pressure gradients. While thestronger day-time wind-driven currents have been extensively studied, gravity and diamagnetic currents in the ionosphere have receivedlittle attention, but can have substantial effects even during the night. With the availability of a new generation of magnetic field models basedon high-accuracy satellite magnetic measurements, it becomes increasingly important to account for these smaller current systems. In this study,we use over a decade of high-quality geomagnetic field measurements from the CHAMP and Swarm missions to study the seasonal and longitudinalstructure of these currents. These results allow us to visualize the global structure of these currents and quantify their magneticperturbations both on the ground and at satellite altitude.

  14. Bayesian inference-based environmental decision support systems for oil spill response strategy selection.

    PubMed

    Davies, Andrew J; Hope, Max J

    2015-07-15

    Contingency plans are essential in guiding the response to marine oil spills. However, they are written before the pollution event occurs so must contain some degree of assumption and prediction and hence may be unsuitable for a real incident when it occurs. The use of Bayesian networks in ecology, environmental management, oil spill contingency planning and post-incident analysis is reviewed and analysed to establish their suitability for use as real-time environmental decision support systems during an oil spill response. It is demonstrated that Bayesian networks are appropriate for facilitating the re-assessment and re-validation of contingency plans following pollutant release, thus helping ensure that the optimum response strategy is adopted. This can minimise the possibility of sub-optimal response strategies causing additional environmental and socioeconomic damage beyond the original pollution event. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Quantifying Modern Recharge to the Nubian Sandstone Aquifer System: Inferences from GRACE and Land Surface Models

    NASA Astrophysics Data System (ADS)

    Mohamed, A.; Sultan, M.; Ahmed, M.; Yan, E.

    2014-12-01

    The Nubian Sandstone Aquifer System (NSAS) is shared by Egypt, Libya, Chad and Sudanand is one of the largest (area: ~ 2 × 106 km2) groundwater systems in the world. Despite its importance to the population of these countries, major hydrological parameters such as modern recharge and extraction rates remain poorly investigated given: (1) the large extent of the NSAS, (2) the absence of comprehensive monitoring networks, (3) the general inaccessibility of many of the NSAS regions, (4) difficulties in collecting background information, largely included in unpublished governmental reports, and (5) limited local funding to support the construction of monitoring networks and/or collection of field and background datasets. Data from monthly Gravity Recovery and Climate Experiment (GRACE) gravity solutions were processed (Gaussian smoothed: 100 km; rescaled) and used to quantify the modern recharge to the NSAS during the period from January 2003 to December 2012. To isolate the groundwater component in GRACE data, the soil moisture and river channel storages were removed using the outputs from the most recent Community Land Model version 4.5 (CLM4.5). GRACE-derived recharge calculations were performed over the southern NSAS outcrops (area: 835 × 103 km2) in Sudan and Chad that receive average annual precipitation of 65 km3 (77.5 mm). GRACE-derived recharge rates were estimated at 2.79 ± 0.98 km3/yr (3.34 ± 1.17 mm/yr). If we take into account the total annual extraction rates (~ 0.4 km3; CEDARE, 2002) from Chad and Sudan the average annual recharge rate for the NSAS could reach up to ~ 3.20 ± 1.18 km3/yr (3.84 ± 1.42 mm/yr). Our recharge rates estimates are similar to those calculated using (1) groundwater flow modelling in the Central Sudan Rift Basins (4-8 mm/yr; Abdalla, 2008), (2) WaterGAP global scale groundwater recharge model (< 5 mm/yr, Döll and Fiedler, 2008), and (3) chloride tracer in Sudan (3.05 mm/yr; Edmunds et al. 1988). Given the available global

  16. An expert system shell for inferring vegetation characteristics: Interface for the addition of techniques (Task H)

    NASA Technical Reports Server (NTRS)

    Harrison, P. Ann

    1993-01-01

    All the NASA VEGetation Workbench (VEG) goals except the Learning System provide the scientist with several different techniques. When VEG is run, rules assist the scientist in selecting the best of the available techniques to apply to the sample of cover type data being studied. The techniques are stored in the VEG knowledge base. The design and implementation of an interface that allows the scientist to add new techniques to VEG without assistance from the developer were completed. A new interface that enables the scientist to add techniques to VEG without assistance from the developer was designed and implemented. This interface does not require the scientist to have a thorough knowledge of Knowledge Engineering Environment (KEE) by Intellicorp or a detailed knowledge of the structure of VEG. The interface prompts the scientist to enter the required information about the new technique. It prompts the scientist to enter the required Common Lisp functions for executing the technique and the left hand side of the rule that causes the technique to be selected. A template for each function and rule and detailed instructions about the arguments of the functions, the values they should return, and the format of the rule are displayed. Checks are made to ensure that the required data were entered, the functions compiled correctly, and the rule parsed correctly before the new technique is stored. The additional techniques are stored separately from the VEG knowledge base. When the VEG knowledge base is loaded, the additional techniques are not normally loaded. The interface allows the scientist the option of adding all the previously defined new techniques before running VEG. When the techniques are added, the required units to store the additional techniques are created automatically in the correct places in the VEG knowledge base. The methods file containing the functions required by the additional techniques is loaded. New rule units are created to store the new rules

  17. Rule-based fuzzy inference system for estimating the influent COD/N ratio and ammonia load to a sequencing batch reactor.

    PubMed

    Kim, Y J; Bae, H; Ko, J H; Poo, K M; Kim, S; Kim, C W; Woo, H J

    2006-01-01

    A fuzzy inference system using sensor measurements was developed to estimate the influent COD/N ratio and ammonia load. The sensors measured ORP, DO and pH. The sensor profiles had a close relationship with the influent COD/N ratio and ammonia load. To confirm this operational knowledge for constructing a rule set, a correlation analysis was conducted. The results showed that a rule generation method based only on operational knowledge did not generate a sufficiently accurate relationship between sensor measurements and target variables. To compensate for this defect, a decision tree algorithm was used as a standardized method for rule generation. Given a set of inputs, this algorithm was used to determine the output variables. However, the generated rules could not estimate the continuous influent COD/N ratio and ammonia load. Fuzzified rules and the fuzzy inference system were developed to overcome this problem. The fuzzy inference system estimated the influent COD/N ratio and ammonia load quite well. When these results were compared to the results from a predictive polynomial neural network model, the fuzzy inference system was more stable.

  18. Nyamulagira’s magma plumbing system inferred from 15 years of InSAR

    USGS Publications Warehouse

    Wauthier, Christelle; Cayol, Valérie; Poland, Michael; Kervyn, François; D'Oreye, Nicolas; Hooper, Andrew; Samsonov, Sergei; Tiampo, Kristy; Smets, Benoit; Pyle, D. M.; Mather, T.A.; Biggs, J.

    2013-01-01

    Nyamulagira, located in the east of the Democratic Republic of Congo on the western branch of the East African rift, is Africa’s most active volcano, with an average of one eruption every 3 years since 1938. Owing to the socio-economical context of that region, the volcano lacks ground-based geodetic measurements but has been monitored by interferometric synthetic aperture radar (InSAR) since 1996. A combination of 3D Mixed Boundary Element Method and inverse modelling, taking into account topography and source interactions, is used to interpret InSAR ground displacements associated with eruptive activity in 1996, 2002, 2004, 2006 and 2010. These eruptions can be fitted by models incorporating dyke intrusions, and some (namely the 2006 and 2010 eruptions) require a magma reservoir beneath the summit caldera. We investigate inter-eruptive deformation with a multi-temporal InSAR approach. We propose the following magma plumbing system at Nyamulagira by integrating numerical deformation models with other available data: a deep reservoir (c. 25 km depth) feeds a shallower reservoir (c. 4 km depth); proximal eruptions are fed from the shallow reservoir through dykes while distal eruptions can be fed directly from the deep reservoir. A dyke-like conduit is also present beneath the upper southeastern flank of Nyamulagira.

  19. Using Bayesian inference for parameter estimation when the system response and experimental conditions are measured with error and some variables are considered as nuisance variables

    NASA Astrophysics Data System (ADS)

    Emery, A. F.; Valenti, E.; Bardot, D.

    2007-01-01

    Parameter estimation is generally based upon the maximum likelihood approach and often involves regularization. Typically it is desired that the results be unbiased and of minimum variance. However, it is often better to accept biased estimates that have minimum mean square error. Bayesian inference is an attractive approach that achieves this goal and incorporates regularization automatically. More importantly, it permits us to analyse experiments in which both the system response and the independent variables (time, sensor position, experimental conditions, etc) are corrupted by noise and in which the model includes nuisance variables. This paper describes the use of Bayesian inference for an apparently simple experiment which is, in fact, fundamentally difficult and is compounded by a nuisance variable. By presenting this analysis we hope that members of the inverse community will see the value of applying Bayesian inference.

  20. Early accretion of protoplanets inferred from a reduced inner solar system (26)Al inventory.

    PubMed

    Schiller, Martin; Connelly, James N; Glad, Aslaug C; Mikouchi, Takashi; Bizzarro, Martin

    2015-06-15

    The mechanisms and timescales of accretion of 10-1000 km sized planetesimals, the building blocks of planets, are not yet well understood. With planetesimal melting predominantly driven by the decay of the short-lived radionuclide (26)Al ((26)Al→(26)Mg; t1/2 = 0.73 Ma), its initial abundance determines the permissible timeframe of planetesimal-scale melting and its subsequent cooling history. Currently, precise knowledge about the initial (26)Al abundance [((26)Al/(27)Al)0] exists only for the oldest known solids, calcium aluminum-rich inclusions (CAIs) - the so-called canonical value. We have determined the (26)Al/(27)Al of three angrite meteorites, D'Orbigny, Sahara 99555 and NWA 1670, at their time of crystallization, which corresponds to (3.98 ± 0.15)×10(-7), (3.64 ± 0.18)×10(-7), and (5.92 ± 0.59)×10(-7), respectively. Combined with a newly determined absolute U-corrected Pb-Pb age for NWA 1670 of 4564.39 ± 0.24 Ma and published U-corrected Pb-Pb ages for the other two angrites, this allows us to calculate an initial ((26)Al/(27)Al)0 of [Formula: see text] for the angrite parent body (APB) precursor material at the time of CAI formation, a value four times lower than the accepted canonical value of 5.25 × 10(-5). Based on their similar (54)Cr/(52)Cr ratios, most inner solar system materials likely accreted from material containing a similar (26)Al/(27)Al ratio as the APB precursor at the time of CAI formation. To satisfy the abundant evidence for widespread planetesimal differentiation, the subcanonical (26)Al budget requires that differentiated planetesimals, and hence protoplanets, accreted rapidly within 0.25 ± 0.15 Ma of the formation of canonical CAIs.

  1. Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

    SciTech Connect

    Ghattas, Omar

    2013-10-15

    The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUARO Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.

  2. Inferring Upper Ocean Dynamics from Horizontal Wavenumber Spectra in the Southern California Current System

    NASA Astrophysics Data System (ADS)

    Chereskin, T. K.; Gille, S. T.; Rocha, C. B.; Menemenlis, D.

    2016-02-01

    At the largest horizontal scales (> 100 km), the surface kinetic energy of the ocean appears dominated by a regime of balanced geostrophic motions. At the smallest scales, it transitions to a regime where unbalanced motions (such as internal waves, mixed-layer instabilities, etc.) dominate the surface kinetic energy. The length scale at which the transition occurs depends on the relative energies of balanced and unbalanced motions, which in turn display significant geographic variability. Wavenumber spectra in the upper ocean have been hypothesized to have slopes consistent with either quasi-geostrophic (QG) or surface quasi-geostrophic (SQG) theory. In previous analyses of repeat-track shipboard acoustic Doppler Current profiler (ADCP) velocity observations in the Gulf Stream and the Antarctic Circumpolar Current, spectral slopes were more consistent with QG than SQG theory for length scales between 40 km and 200 km. For scales less than 40 km, the spectra deviated from both QG and SQG theory, and this was attributed in part to internal wave effects. A spectral Helmholtz decomposition was used to split the kinetic energy spectra into rotational and divergent components, identified with balanced and ageostrophic motions, respectively. The California Current System (CCS) provides a contrasting environment characterized by a weak mean flow and an energetic meso- and submeso- scale. It is a nonlinear regime where the amplitude of eddies can be as large as the total steric height increase across the California Current, and hence southward flow in the CCS can, and often is, disrupted by its eddies. This study uses 10 years of shipboard ADCP observations collected on the quarterly cruises of the California Cooperative Oceanic Fisheries Investigations. Horizontal wavenumber spectra from 36 cruises along 6 repeated tracks in the southern CCS that extend from the coast to the subtropical gyre are used to diagnose the dominant governing dynamics at meso- to submeso- scales

  3. Physical Properties of the Saturnian Ring System Inferred from Cassini VIMS Opposition Observations

    NASA Astrophysics Data System (ADS)

    Hapke, B.; Nelson, R. M.; Brown, R. H.; Spilker, L. J.; Smythe, W. D.; Kamp, L.; Boryta, M.; Leader, F.; Matson, D. L.; Edgington, S.; Nicholson, P. D.; Filacchione, G.; Clark, R. N.; Bibring, J.; Baines, K. H.; Buratti, B. J.; Bellucci, G.; Capaccioni, F.; Cerroni, P.; Combes, M.; Coradini, A.; Cruikshank, D. P.; Drossart, P.; Formisano, V.; Jaumann, R.; Langevin, Y.; McCord, T.; Menella, V.; Sicardy, B.

    2005-12-01

    Much can be learned about the nature of Saturn's ring particles and their regoliths by studying the wavelength dependence of their reflectance as a function of phase angle. At small phase angles the reflectance of the rings exhibits the opposition effect (OE) a significant increase in reflectance as phase angle approaches zero degrees. The wavelength dependence of the width and the peak of the OE are indicators of important physical properties of the regoliths of the ring particles such as particle size, particle shape, packing density and albedo. The Cassini VIMS multi spectral imaging spectrometer obtained low phase observations of the Saturnian ring system from 0.4-5.2 microns during 2005. These data clearly show a pronounced (OE). Cassini VIMS opposition surge data indicate a wavelength dependence of the OE that relates to the size and separation of the scattering centers on the surface of the ring particles. Laboratory studies and theoretical models of the OE relate the size and shape of the reflectance increase to physical properties of the medium (Nelson et al, 2002; Spilker et al. 1995; Hapke et al., 1993)). The OE arises from two processes, shadow hiding (SH) and coherent backscattering (CB). The SHOE is observed because shadows cast by the particulate grains on one another are eliminated as phase angle approaches zero degrees. The CBOE is due to constructive interference between light rays traveling in opposite paths through the medium as the path length decreases with decreasing phase angle. The VIMS data at 1.9 microns, where the rings are highly reflective, indicate a strong CBOE effect, however, at 2.1 microns, where the rings are very absorbing, the shape of the phase curve is consistent with SHOE. Hapke et al. 1993,Science, 260, 509-511 Nelson, R. M. et al., 2002. Planetary and Space Science, 50, 849-856 Spilker aka Horn, L.J et al., 1995. IAU Colloquium #150 This work done at JPL under contract with NASA

  4. Early accretion of protoplanets inferred from a reduced inner solar system 26Al inventory

    NASA Astrophysics Data System (ADS)

    Schiller, Martin; Connelly, James N.; Glad, Aslaug C.; Mikouchi, Takashi; Bizzarro, Martin

    2015-06-01

    The mechanisms and timescales of accretion of 10-1000 km sized planetesimals, the building blocks of planets, are not yet well understood. With planetesimal melting predominantly driven by the decay of the short-lived radionuclide 26Al (26Al→26Mg; t1/2 = 0.73 Ma), its initial abundance determines the permissible timeframe of planetesimal-scale melting and its subsequent cooling history. Currently, precise knowledge about the initial 26Al abundance [(26Al/27Al)0] exists only for the oldest known solids, calcium aluminum-rich inclusions (CAIs) - the so-called canonical value. We have determined the 26Al/27Al of three angrite meteorites, D'Orbigny, Sahara 99555 and NWA 1670, at their time of crystallization, which corresponds to (3.98 ± 0.15) ×10-7, (3.64 ± 0.18) ×10-7, and (5.92 ± 0.59) ×10-7, respectively. Combined with a newly determined absolute U-corrected Pb-Pb age for NWA 1670 of 4564.39 ± 0.24 Ma and published U-corrected Pb-Pb ages for the other two angrites, this allows us to calculate an initial (26Al/27Al)0 of (1.33-0.18+0.21) ×10-5 for the angrite parent body (APB) precursor material at the time of CAI formation, a value four times lower than the accepted canonical value of 5.25 ×10-5. Based on their similar 54Cr/52Cr ratios, most inner solar system materials likely accreted from material containing a similar 26Al/27Al ratio as the APB precursor at the time of CAI formation. To satisfy the abundant evidence for widespread planetesimal differentiation, the subcanonical 26Al budget requires that differentiated planetesimals, and hence protoplanets, accreted rapidly within 0.25 ± 0.15 Ma of the formation of canonical CAIs.

  5. Early accretion of protoplanets inferred from a reduced inner solar system 26Al inventory

    PubMed Central

    Schiller, Martin; Connelly, James N.; Glad, Aslaug C.; Mikouchi, Takashi; Bizzarro, Martin

    2016-01-01

    The mechanisms and timescales of accretion of 10–1000 km sized planetesimals, the building blocks of planets, are not yet well understood. With planetesimal melting predominantly driven by the decay of the short-lived radionuclide 26Al (26Al→26Mg; t1/2 = 0.73 Ma), its initial abundance determines the permissible timeframe of planetesimal-scale melting and its subsequent cooling history. Currently, precise knowledge about the initial 26Al abundance [(26Al/27Al)0] exists only for the oldest known solids, calcium aluminum-rich inclusions (CAIs) – the so-called canonical value. We have determined the 26Al/27Al of three angrite meteorites, D’Orbigny, Sahara 99555 and NWA 1670, at their time of crystallization, which corresponds to (3.98 ± 0.15)×10−7, (3.64 ± 0.18)×10−7, and (5.92 ± 0.59)×10−7, respectively. Combined with a newly determined absolute U-corrected Pb–Pb age for NWA 1670 of 4564.39 ± 0.24 Ma and published U-corrected Pb–Pb ages for the other two angrites, this allows us to calculate an initial (26Al/27Al)0 of (1.33−0.18+0.21)×10−5 for the angrite parent body (APB) precursor material at the time of CAI formation, a value four times lower than the accepted canonical value of 5.25 × 10−5. Based on their similar 54Cr/52Cr ratios, most inner solar system materials likely accreted from material containing a similar 26Al/27Al ratio as the APB precursor at the time of CAI formation. To satisfy the abundant evidence for widespread planetesimal differentiation, the subcanonical 26Al budget requires that differentiated planetesimals, and hence protoplanets, accreted rapidly within 0.25 ± 0.15 Ma of the formation of canonical CAIs. PMID:27429474

  6. Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system

    SciTech Connect

    Djukanovic, M.B.; Calovic, M.S.; Vesovic, B.V.; Sobajic, D.J.

    1997-12-01

    This paper presents an attempt of nonlinear, multivariable control of low-head hydropower plants, by using adaptive-network based fuzzy inference system (ANFIS). The new design technique enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near optimal manner. The controller has flexibility for accepting more sensory information, with the main goal to improve the generator unit transients, by adjusting the exciter input, the wicket gate and runner blade positions. The developed ANFIS controller whose control signals are adjusted by using incomplete on-line measurements, can offer better damping effects to generator oscillations over a wide range of operating conditions, than conventional controllers. Digital simulations of hydropower plant equipped with low-head Kaplan turbine are performed and the comparisons of conventional excitation-governor control, state-feedback optimal control and ANFIS based output feedback control are presented. To demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired neuro-fuzzy controller, the controller has been implemented on a complex high-order non-linear hydrogenerator model.

  7. Prediction of Tensile Strength of Friction Stir Weld Joints with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network

    NASA Technical Reports Server (NTRS)

    Dewan, Mohammad W.; Huggett, Daniel J.; Liao, T. Warren; Wahab, Muhammad A.; Okeil, Ayman M.

    2015-01-01

    Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed (??), plunge force (????), and welding speed (??) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables (??,??,????,??????) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

  8. Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing electro chemical machining process

    NASA Astrophysics Data System (ADS)

    Teimouri, Reza; Sohrabpoor, Hamed

    2013-12-01

    Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

  9. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids

    PubMed Central

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models. PMID:26474167

  10. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    PubMed

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  11. A Trust Model for Ubiquitous Healthcare Environment on the Basis of Adaptable Fuzzy-Probabilistic Inference System.

    PubMed

    Athanasiou, Georgia; Anastasopoulos, George C; Tiritidou, Eleni; Lymberopoulos, Dimitrios

    2017-07-28

    Trust is considered to be a determinant on psychologist selection which can ensure patient satisfaction. Hence, trust concept is essential to be introduced into Ubiquitous Healthcare (UH) environment oriented on patients with anxiety disorders. This is accomplished by Trust Model estimating psychologists' trustworthiness, a priory to service delivery, with the use of patient's and his/her acquaintances testimonies, i.e. Personal Interaction Experience (PIE) and Reputation (R). In this paper, Trust Model is proposed to be materialized via an Adaptable Cloud Inference System (ACIS) that performs Trust Value (TV) estimation. Taking advantage of cloud theory, the introduced ACIS estimates TVs via fuzzy-probabilistic reasoning incorporating a cloud relation operator (soft AND) which is proposed to be tuned by trust information sources consistency and coherency. Theoretical analysis along with comparative study conducted within MATLAB environment and experimental investigation verify the effectiveness of the proposed ACIS materialization under different conditions. Especially, the innovative features of ACIS enable TV to be estimated with 45.5% and 62% on average higher accuracy to that providing state-of-the-art Trust Models, within clean environment and under the influence of large scale collusive malicious attacks, respectively. The enhanced robustness permits the untrustworthy UH Providers to be discriminated with True Positive Rate at the range of 0.9 although 40% of R testimonies are erroneous. Finally, experimental investigation validates that the adoption of the proposed Trust Model for psychologists trustworthiness estimation facilitates patient satisfaction to be achieved into UH environment.

  12. Modeling Pb (II) adsorption from aqueous solution by ostrich bone ash using adaptive neural-based fuzzy inference system.

    PubMed

    Amiri, Mohammad J; Abedi-Koupai, Jahangir; Eslamian, Sayed S; Mousavi, Sayed F; Hasheminejad, Hasti

    2013-01-01

    To evaluate the performance of Adaptive Neural-Based Fuzzy Inference System (ANFIS) model in estimating the efficiency of Pb (II) ions removal from aqueous solution by ostrich bone ash, a batch experiment was conducted. Five operational parameters including adsorbent dosage (C(s)), initial concentration of Pb (II) ions (C(o)), initial pH, temperature (T) and contact time (t) were taken as the input data and the adsorption efficiency (AE) of bone ash as the output. Based on the 31 different structures, 5 ANFIS models were tested against the measured adsorption efficiency to assess the accuracy of each model. The results showed that ANFIS5, which used all input parameters, was the most accurate (RMSE = 2.65 and R(2) = 0.95) and ANFIS1, which used only the contact time input, was the worst (RMSE = 14.56 and R(2) = 0.46). In ranking the models, ANFIS4, ANFIS3 and ANFIS2 ranked second, third and fourth, respectively. The sensitivity analysis revealed that the estimated AE is more sensitive to the contact time, followed by pH, initial concentration of Pb (II) ions, adsorbent dosage, and temperature. The results showed that all ANFIS models overestimated the AE. In general, this study confirmed the capabilities of ANFIS model as an effective tool for estimation of AE.

  13. EFFICIENT HAPLOTYPE INFERENCE FROM PEDIGREES WITH MISSING DATA USING LINEAR SYSTEMS WITH DISJOINT-SET DATA STRUCTURES

    PubMed Central

    Li, Xin; Li, Jing

    2010-01-01

    We study the haplotype inference problem from pedigree data under the zero recombination assumption, which is well supported by real data for tightly linked markers (i.e., single nucleotide polymorphisms (SNPs)) over a relatively large chromosome segment. We solve the problem in a rigorous mathematical manner by formulating genotype constraints as a linear system of inheritance variables. We then utilize disjoint-set structures to encode connectivity information among individuals, to detect constraints from genotypes, and to check consistency of constraints. On a tree pedigree without missing data, our algorithm can output a general solution as well as the number of total specific solutions in a nearly linear time O(mn · α(n)), where m is the number of loci, n is the number of individuals and α is the inverse Ackermann function4, which is a further improvement over existing ones3, 8, 12, 15. We also extend the idea to looped pedigrees and pedigrees with missing data by considering existing (partial) constraints on inheritance variables. The algorithm has been implemented in C++ and will be incorporated into our PedPhase package8. Experimental results show that it can correctly identify all 0-recombinant solutions with great efficiency. Comparisons with other two popular algorithms show that the proposed algorithm achieves 10 to 105-fold improvements over a variety of parameter settings. The experimental study also provides empirical evidences on the complexity bounds suggested by theoretical analysis. PMID:19642289

  14. Comparative assessment of rule-based and Bayes' theorem as inference engines in diagnosing symptoms for Islamic medication expert system

    NASA Astrophysics Data System (ADS)

    Daud, H.; Razali, R.; Low, T. J.; Sabdin, M.; Zafrul, S. Z. Mohd

    2014-06-01

    An expert system for diagnosing sickness and suggesting treatment based on Islamic Medication (IM) was constructed using Rule Based (RB) and Bayes' theorem (BT) algorithms independently as its inference engine. Comparative assessment on the quality of diagnosing based on symptoms provided by users for certain type of sickness using RB and BT reasoning that lead to the suggested treatment (based on IM) are discussed. Both approaches are found to be useful, each has its own advantages and disadvantages. Major difference of the two algorithms is the selection of symptoms during the diagnosing process. For BT, likely combinations of symptoms need to be classified for each sickness before the diagnosing process. This eliminates any irrelevant sickness based on the combination of symptoms provided by user and combination of symptoms that is unlikely. This is not the case for RB, it will diagnose the sickness as long as one the symptoms is related to the sickness regardless of unlikely combination. Few tests have been carried out using combinations of symptoms for same sickness to investigate their diagnosing accuracy in percentage. BT gives more promising diagnosing results compared to RB for each sickness that comes with common symptoms.

  15. Prediction of matching condition for a microstrip subsystem using artificial neural network and adaptive neuro-fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Salehi, Mohammad Reza; Noori, Leila; Abiri, Ebrahim

    2016-11-01

    In this paper, a subsystem consisting of a microstrip bandpass filter and a microstrip low noise amplifier (LNA) is designed for WLAN applications. The proposed filter has a small implementation area (49 mm2), small insertion loss (0.08 dB) and wide fractional bandwidth (FBW) (61%). To design the proposed LNA, the compact microstrip cells, an field effect transistor, and only a lumped capacitor are used. It has a low supply voltage and a low return loss (-40 dB) at the operation frequency. The matching condition of the proposed subsystem is predicted using subsystem analysis, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). To design the proposed filter, the transmission matrix of the proposed resonator is obtained and analysed. The performance of the proposed ANN and ANFIS models is tested using the numerical data by four performance measures, namely the correlation coefficient (CC), the mean absolute error (MAE), the average percentage error (APE) and the root mean square error (RMSE). The obtained results show that these models are in good agreement with the numerical data, and a small error between the predicted values and numerical solution is obtained.

  16. Investigation on the effect of geometrical and geotechnical parameters on elongated offshore piles using fuzzy inference systems

    NASA Astrophysics Data System (ADS)

    Aminfar, Ali; Mojtahedi, Alireza; Ahmadi, Hamid; Aminfar, Mohammad Hossain

    2017-06-01

    Among numerous offshore structures used in oil extraction, jacket platforms are still the most favorable ones in shallow waters. In such structures, log piles are used to pin the substructure of the platform to the seabed. The pile's geometrical and geotechnical properties are considered as the main parameters in designing these structures. In this study, ANSYS was used as the FE modeling software to study the geometrical and geotechnical properties of the offshore piles and their effects on supporting jacket platforms. For this purpose, the FE analysis has been done to provide the preliminary data for the fuzzy-logic post-process. The resulting data were implemented to create Fuzzy Inference System (FIS) classifications. The resultant data of the sensitivity analysis suggested that the orientation degree is the main factor in the pile's geometrical behavior because piles which had the optimal operational degree of about 5° are more sustained. Finally, the results showed that the related fuzzified data supported the FE model and provided an insight for extended offshore pile designs.

  17. A novel approach to detect respiratory phases from pulmonary acoustic signals using normalised power spectral density and fuzzy inference system.

    PubMed

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian; Huliraj, N; Revadi, S S

    2016-07-01

    Monitoring respiration is important in several medical applications. One such application is respiratory rate monitoring in patients with sleep apnoea. The respiratory rate in patients with sleep apnoea disorder is irregular compared with the controls. Respiratory phase detection is required for a proper monitoring of respiration in patients with sleep apnoea. To develop a model to detect the respiratory phases present in the pulmonary acoustic signals and to evaluate the performance of the model in detecting the respiratory phases. Normalised averaged power spectral density for each frame and change in normalised averaged power spectral density between the adjacent frames were fuzzified and fuzzy rules were formulated. The fuzzy inference system (FIS) was developed with both Mamdani and Sugeno methods. To evaluate the performance of both Mamdani and Sugeno methods, correlation coefficient and root mean square error (RMSE) were calculated. In the correlation coefficient analysis in evaluating the fuzzy model using Mamdani and Sugeno method, the strength of the correlation was found to be r = 0.9892 and r = 0.9964, respectively. The RMSE for Mamdani and Sugeno methods are RMSE = 0.0853 and RMSE = 0.0817, respectively. The correlation coefficient and the RMSE of the proposed fuzzy models in detecting the respiratory phases reveals that Sugeno method performs better compared with the Mamdani method. © 2014 John Wiley & Sons Ltd.

  18. Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

    PubMed Central

    Jhin, Changho; Hwang, Keum Taek

    2014-01-01

    Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

  19. Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

    SciTech Connect

    Marzouk, Youssef

    2016-08-31

    Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

  20. Elucidating the origin of the ExbBD components of the TonB system through Bayesian inference and maximum-likelihood phylogenies.

    PubMed

    Marmon, Livingstone

    2013-12-01

    Uptake of ferric siderophores, vitamin B12, and other molecules in gram-negative bacteria is mediated by a multi-protein complex known as the TonB system. The ExbB and ExbD protein components of the TonB system play key energizing roles and are homologous with the flagellar motor proteins MotA and MotB. Here, the phylogenetic relationships of ExbBD and MotAB were investigated using Bayesian inference and the maximum-likelihood method. Phylogenetic trees of these proteins suggest that they are separated into distinct monophyletic groups and have originated from a common ancestral system. Several horizontal gene transfer events for ExbB-ExbD are also inferred, and a model for the evolution of the TonB system is proposed. Copyright © 2013 Elsevier Inc. All rights reserved.

  1. Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

    PubMed Central

    Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

    2013-01-01

    Background An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. Methods The ANFIS and ANN models were compared in terms of six statistical indices calculated by comparing their prediction results with actual data: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R2). Graphical plots were also used for model comparison. Conclusions The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. PMID:23705023

  2. Hydrodynamic processes, velocity structure and stratification in natural turbidity currents: Results inferred from field data in the Var Turbidite System

    NASA Astrophysics Data System (ADS)

    Migeon, Sébastien; Mulder, Thierry; Savoye, Bruno; Sage, Françoise

    2012-03-01

    The Var Turbidite System (NW Mediterranean Sea) is fed during the present-day highstand sea level by large earthquake-induced ignitive turbidity currents, low-density turbidity currents resulting from retrogressive failures triggered on the upper continental slope, and hyperpycnal flows related to the Var River floods. Using a large dataset including bathymetric data, side-scan sonar images, seismic-reflection profiles, cores and photographs of the seafloor, this paper attempts to better constrain the hydrodynamic behaviour of debris flows and turbidity currents along the Upper and Middle Valley of the Var Turbidite System. The drastic change of the seafloor morphology between the Upper and the Middle Valley suggests that gravity flows undergo rapid transformation from cohesive to fully turbulent behaviour. This transformation is related to a hydraulic jump caused by an abrupt decrease in slope angle at the transition between the Upper and the Middle Valley and is associated with en masse deposition and elevation of the seafloor. Strong seafloor erosion prevails in the Middle Valley, suggesting that, for a low and constant slope angle, turbulent flows must regain a balance between concentration and flow thickness rapidly after they experience hydraulic jump. The internal stratification and vertical grain-size distribution within turbulent flows are inferred from the distribution of fine- to coarse-grained turbidites found in cores located along the crest of the Var Sedimentary Ridge with a decreasing elevation above the floor of the Middle Valley. The theoretical vertical velocity profile deduced from the vertical grain-size distribution exhibits a general trend and an inflection of the gradient curve different from those of the velocity profiles classically obtained using numerical modelling.

  3. Evolutionary processes in a continental island system: molecular phylogeography of the Aegean Nigella arvensis alliance (Ranunculaceae) inferred from chloroplast DNA.

    PubMed

    Bittkau, C; Comes, H P

    2005-11-01

    Continental shelf island systems, created by rising sea levels, provide a premier setting for studying the effects of past fragmentation, dispersal, and genetic drift on taxon diversification. We used phylogeographical (nested clade) and population genetic analyses to elucidate the relative roles of these processes in the evolutionary history of the Aegean Nigella arvensis alliance (= 'coenospecies'). We surveyed chloroplast DNA (cpDNA) variation in 455 individuals from 47 populations (nine taxa) of the alliance throughout its core range in the Aegean Archipelago and surrounding mainland areas of Greece and Turkey. The study revealed the presence of three major lineages, with largely nonoverlapping distributions in the Western, Central, and Eastern Aegean. There is evidence supporting the idea that these major lineages evolved in situ from a widespread (pan-Aegean) ancestral stock as a result of multiple fragmentation events, possibly due to the influence of post-Messinian sea flooding, Pleistocene eustatic changes and corresponding climate fluctuations. Over-sea dispersal and founder events appear to have played a rather insignificant role in the group's history. Rather, all analytical approaches identified the alliance as an organism group with poor seed dispersal capabilities and a susceptibility to genetic drift. In particular, we inferred that the observed level of cpDNA differentiation between Kikladian island populations of Nigella degenii largely reflects population history, (viz. Holocene island fragmentation) and genetic drift in the near absence of seed flow since their time of common ancestry. Overall, our cpDNA data for the N. arvensis alliance in general, and N. degenii in particular, indicate that historical events were important in determining the phylogeographical patterns seen, and that genetic drift has historically been relatively more influential on population structure than has cytoplasmic gene flow.

  4. Inferring Mealy Machines

    NASA Astrophysics Data System (ADS)

    Shahbaz, Muzammil; Groz, Roland

    Automata learning techniques are getting significant importance for their applications in a wide variety of software engineering problems, especially in the analysis and testing of complex systems. In recent studies, a previous learning approach [1] has been extended to synthesize Mealy machine models which are specifically tailored for I/O based systems. In this paper, we discuss the inference of Mealy machines and propose improvements that reduces the worst-time learning complexity of the existing algorithm. The gain over the complexity of the proposed algorithm has also been confirmed by experimentation on a large set of finite state machines.

  5. Inferring speciation modes in a clade of Iberian chafers from rates of morphological evolution in different character systems

    PubMed Central

    Ahrens, Dirk; Ribera, Ignacio

    2009-01-01

    Background Studies of speciation mode based on phylogenies usually test the predicted effect on diversification patterns or on geographical distribution of closely related species. Here we outline an approach to infer the prevalent speciation mode in Iberian Hymenoplia chafers through the comparison of the evolutionary rates of morphological character systems likely to be related to sexual or ecological selection. Assuming that mitochondrial evolution is neutral and not related to measured phenotypic differences among the species, we contrast hypothetic outcomes of three speciation modes: 1) geographic isolation with subsequent random morphological divergence, resulting in overall change proportional to the mtDNA rate; 2) sexual selection on size and shape of the male intromittent organs, resulting in an evolutionary rate decoupled to that of the mtDNA; and 3) ecological segregation, reflected in character systems presumably related to ecological or biological adaptations, with rates decoupled from that of the mtDNA. Results The evolutionary rate of qualitative external body characters was significantly correlated to that of the mtDNA both for the overall root-to-tip patristic distances and the individual inter-node branches, as measured with standard statistics and the randomization of a global comparison metric (the z-score). The rate of the body morphospace was significantly correlated to that of the mtDNA only for the individual branches, but not for the patristic distances, while that of the paramere outline was significantly correlated with mtDNA rates only for the patristic distances but not for the individual branches. Conclusion Structural morphological characters, often used for species recognition, have evolved at a rate proportional to that of the mtDNA, with no evidence of directional or stabilising selection according to our measures. The change in body morphospace seems to have evolved randomly at short term, but the overall change is different from

  6. Comparison of adaptive neuro-fuzzy inference system and artificial neutral networks model to categorize patients in the emergency department.

    PubMed

    Azeez, Dhifaf; Ali, Mohd Alauddin Mohd; Gan, Kok Beng; Saiboon, Ismail

    2013-01-01

    Unexpected disease outbreaks and disasters are becoming primary issues facing our world. The first points of contact either at the disaster scenes or emergency department exposed the frontline workers and medical physicians to the risk of infections. Therefore, there is a persuasive demand for the integration and exploitation of heterogeneous biomedical information to improve clinical practice, medical research and point of care. In this paper, a primary triage model was designed using two different methods: an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN).When the patient is presented at the triage counter, the system will capture their vital signs and chief complains beside physiology stat and general appearance of the patient. This data will be managed and analyzed in the data server and the patient's emergency status will be reported immediately. The proposed method will help to reduce the queue time at the triage counter and the emergency physician's burden especially duringdisease outbreak and serious disaster. The models have been built with 2223 data set extracted from the Emergency Department of the Universiti Kebangsaan Malaysia Medical Centre to predict the primary triage category. Multilayer feed forward with one hidden layer having 12 neurons has been used for the ANN architecture. Fuzzy subtractive clustering has been used to find the fuzzy rules for the ANFIS model. The results showed that the RMSE, %RME and the accuracy which evaluated by measuring specificity and sensitivity for binary classificationof the training data were 0.14, 5.7 and 99 respectively for the ANN model and 0.85, 32.00 and 96.00 respectively for the ANFIS model. As for unseen data the root mean square error, percentage the root mean square error and the accuracy for ANN is 0.18, 7.16 and 96.7 respectively, 1.30, 49.84 and 94 respectively for ANFIS model. The ANN model was performed better for both training and unseen data than ANFIS model in

  7. An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC light transmission system under AC fault conditions

    NASA Astrophysics Data System (ADS)

    Ajay Kumar, M.; Srikanth, N. V.

    2014-03-01

    In HVDC Light transmission systems, converter control is one of the major fields of present day research works. In this paper, fuzzy logic controller is utilized for controlling both the converters of the space vector pulse width modulation (SVPWM) based HVDC Light transmission systems. Due to its complexity in the rule base formation, an intelligent controller known as adaptive neuro fuzzy inference system (ANFIS) controller is also introduced in this paper. The proposed ANFIS controller changes the PI gains automatically for different operating conditions. A hybrid learning method which combines and exploits the best features of both the back propagation algorithm and least square estimation method is used to train the 5-layer ANFIS controller. The performance of the proposed ANFIS controller is compared and validated with the fuzzy logic controller and also with the fixed gain conventional PI controller. The simulations are carried out in the MATLAB/SIMULINK environment. The results reveal that the proposed ANFIS controller is reducing power fluctuations at both the converters. It also improves the dynamic performance of the test power system effectively when tested for various ac fault conditions.

  8. Seasonal rainfall forecasting by adaptive network-based fuzzy inference system (ANFIS) using large scale climate signals

    NASA Astrophysics Data System (ADS)

    Mekanik, F.; Imteaz, M. A.; Talei, A.

    2016-05-01

    Accurate seasonal rainfall forecasting is an important step in the development of reliable runoff forecast models. The large scale climate modes affecting rainfall in Australia have recently been proven useful in rainfall prediction problems. In this study, adaptive network-based fuzzy inference systems (ANFIS) models are developed for the first time for southeast Australia in order to forecast spring rainfall. The models are applied in east, center and west Victoria as case studies. Large scale climate signals comprising El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Inter-decadal Pacific Ocean (IPO) are selected as rainfall predictors. Eight models are developed based on single climate modes (ENSO, IOD, and IPO) and combined climate modes (ENSO-IPO and ENSO-IOD). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Pearson correlation coefficient (r) and root mean square error in probability (RMSEP) skill score are used to evaluate the performance of the proposed models. The predictions demonstrate that ANFIS models based on individual IOD index perform superior in terms of RMSE, MAE and r to the models based on individual ENSO indices. It is further discovered that IPO is not an effective predictor for the region and the combined ENSO-IOD and ENSO-IPO predictors did not improve the predictions. In order to evaluate the effectiveness of the proposed models a comparison is conducted between ANFIS models and the conventional Artificial Neural Network (ANN), the Predictive Ocean Atmosphere Model for Australia (POAMA) and climatology forecasts. POAMA is the official dynamic model used by the Australian Bureau of Meteorology. The ANFIS predictions certify a superior performance for most of the region compared to ANN and climatology forecasts. POAMA performs better in regards to RMSE and MAE in east and part of central Victoria, however, compared to ANFIS it shows weaker results in west Victoria in terms of prediction errors and RMSEP skill

  9. Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

    NASA Astrophysics Data System (ADS)

    Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

    2016-08-01

    This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS

  10. The Lithosphere of The East African Rift System: Insights From Three-Dimensional Density Modelling

    NASA Astrophysics Data System (ADS)

    Woldetinsae, G.; Götze, H. J.

    2004-12-01

    We use the gravity data that cover the large part of the Afro-Arabian rift system, the eastern branch (Ethiopia-Afar and northern Kenya), in order to produce a regional density model. In an earlier work the new and old gravity data were compiled, evaluated and homogenised using a consistent data reduction procedures. Three basic constraints widely spaced over a 1500 km rift length have been generated between 1969 and 2003 by an international consortium with information from isostatic models, global tomography, geological, geochemical evidences, and petrological and experimental results. These are integrated and applied to the model to constrain upper and lower crustal structures underneath the Rift and Plateau areas. New crustal thickness estimations (Dugda et al., 2004 in press) and inferences from recent velocity models along the axis of the Main Ethiopian Rift (Keller et al., 2004) are added to the density model. Thirty parallel planes cutting across the entire plateau region and Rift system (Afar-Ethiopia-Kenya) are interactively modelled using a starting geometry that invoke asthenospheric upwelling. Densities for the upper crust are calculated using Nafe Drake method, averaged from earlier interpretation and measured ones from the Geological Survey of Ethiopia database (e.g. Geothermal project, GSE petrophysical laboratory, pers. communication). Densities for lower crust are estimated using the approach by Sobolov and Babyko (1994). We used also lower crustal densities calculated by (Simyu and Keller, 1997) for the northern part of Kenya rift. The preliminary model offers a possibility to quantify depth, thickness and volumes of different geological interfaces and bodies. As for example, the estimation of the volume of volcanic constructs on the western plateau of Ethiopia is relatively larger than the eastern plateau. The load map derived from the model indicated maximum crustal loads at the crust/mantle interface (ca. 40km) on the eastern and western flanks

  11. Isotopic constraints on anorthosite genesis and implications for crust-mantle evolution

    SciTech Connect

    Ashwal, L.D.

    1985-01-01

    Crystallization ages of anorthosite massifs, determined from whole-rock and internal Sm-Nd and Rb-Sr isochrons range between about 1.1 and 1.6 Ga, arguing against a discrete anorthosite event. Metamorphic ages of some massifs are as much as 200-300 Ma younger, indicating that the Grenville orogeny was not a causative factor in anorthosite genesis. Variable crustal contamination effects are evident in many massifs, particularly in border zones. In some late-stage ferrogabbros, mafic silicates and/or Fe-Ti oxides are not in isotopic equilibrium with plagioclase, suggesting that crystallization took place both before and after contamination. The most isotopically primitive materials are Al-rich opx megacrysts. Isotopic data to date are compatible with a two-stage model involving (1) emplacement of basaltic magma into lower crustal chambers where fractionation and accumulation of olivine and Al-rich opx, and eventually plagioclase took place, and (2) detachment and ascent of buoyant anorthositic mushes to upper crustal emplacement sites. Besides being useful as indicators of Proterozoic mantle evolution, anorthosites can be used as tracers to map our basement types through which they were emplaced.

  12. Subduction in fancy: stripping young slabs as a result of similar crust-mantle rheologies

    NASA Astrophysics Data System (ADS)

    Agard, Philippe; Yamato, Philippe; Soret, Mathieu; Prigent, Cécile; Guillot, Stéphane; Plunder, Alexis; Dubacq, Benoît; Monié, Patrick; Chauvet, Alain

    2016-04-01

    Understanding subduction rheology in both space and time has been a challenge since the advent of plate tectonics. We herein focus on "subduction infancy", which corresponds to the first ~0-2 My immediately following subduction nucleation, when a newly born slab penetrates into the overriding plate mantle and heats up. The only remnants of this critical, yet elusive, geodynamic step are thin metamorphic soles, commonly found beneath pristine, 100-1000 km long portions of oceanic lithosphere emplaced on top of continents (i.e., ophiolites). In this study, we show how, during subduction infancy, transient mechanical properties of both the mantle and crust across the subduction plate interface (during ~100s ky) control and hinder the penetration of tectonic plates into the mantle, and how this results in strong peaks of resistance and even slicing of their surface - leaving behind thin, chopped-off metamorphic slivers (i.e., metamorphic soles). These findings constrain the mechanical behaviour of the subduction plate interface (with implications for coupling processes and earthquake generation) as well as the properties of the crust and mantle. They also highlight the role of fluids in enabling subduction to overcome this early resistance.

  13. The bearing of spinel cataclasites on the crust-mantle structure of the moon

    NASA Technical Reports Server (NTRS)

    Herzberg, C. T.

    1978-01-01

    Subsolidus thermodynamic calculations have been made to define the temperature and pressure conditions required to equilibrate lunar spinel cataclasites (olivine + high alumina orthopyroxene + pleonaste spinel + plagioclase + or - cordierite) that occur as clasts in 15445, 73263, and 72435. The results, which are subject to modification by improved thermodynamic data and experiment, indicate that those samples that are cordierite-free and of high Mg/(Mg + Fe) were derived from the lower crust and possibly from a high-velocity zone of the uppermost mantle. However, the cordierite-bearing type in 72435,8 /low Mg/(Mg + Fe)/ resided in the upper levels of the crust prior to excavation by impact. Consideration of the relevant supersolidus phase equilibria indicates that the whole-rock chemistry of all spinel cataclasites can only be explained by pleonaste spinel accumulation. These materials are interpreted to be primordial cumulate rocks formed during the differentiation of the lunar magma ocean.

  14. Copper systematics in arc magmas and implications for crust-mantle differentiation.

    PubMed

    Lee, Cin-Ty A; Luffi, Peter; Chin, Emily J; Bouchet, Romain; Dasgupta, Rajdeep; Morton, Douglas M; Le Roux, Veronique; Yin, Qing-zhu; Jin, Daphne

    2012-04-06

    Arc magmas are important building blocks of the continental crust. Because many arc lavas are oxidized, continent formation is thought to be associated with oxidizing conditions. On the basis of copper's (Cu's) affinity for reduced sulfur phases, we tracked the redox state of arc magmas from mantle source to emplacement in the crust. Primary arc and mid-ocean ridge basalts have identical Cu contents, indicating that the redox states of primitive arc magmas are indistinguishable from that of mid-ocean ridge basalts. During magmatic differentiation, the Cu content of most arc magmas decreases markedly because of sulfide segregation. Because a similar depletion in Cu characterizes global continental crust, the formation of sulfide-bearing cumulates under reducing conditions may be a critical step in continent formation.

  15. Tracking Crust-Mantle Recycling through Superdeep Diamonds and their Mineral Inclusions

    NASA Astrophysics Data System (ADS)

    Walter, Michael; Bulanova, Galina; Smith, Chris; Thomson, Andrew; Kohn, Simon; Burnham, Antony

    2013-04-01

    Sublithospheric, or 'superdeep' diamonds, originate in the deep upper mantle, transition zone, and at least as deep as the shallow lower mantle. When diamonds crystallize in the mantle from fluids or melts they occasionally entrap coexisting mineral phases. Because of their great physical resiliency, diamonds can potentially preserve information over long distance- and time-scales, revealing important information about the petrologic, tectonic and geodynamic environment in which the diamonds grew and were transported. Superdeep diamonds and their inclusions have proven especially powerful for probing processes related to subduction of slabs into the deep mantle [1-3]. In contrast to lithospheric diamonds that are effectively frozen-in geodynamically, mineral inclusions in superdeep diamonds often record hundreds of kilometers of uplift in the convecting mantle from their original depth of origin [3-5]. The phase equilibria of unmixing of original deep mantle phases such as Ca- and Mg-perovskite, NAL-phase, CF-phase, CAS-phase, and majorite provide a means to establish amounts of uplift. The few available age constraints indicate superdeep diamond growth from the Proterozoic to the Cretaceous, and further dating can potentially lead to constraining mantle upwelling rates [4]. Here we will provide several examples showing how superdeep diamonds and their inclusions record processes of subduction and slab foundering, and ultimately recycling of slab material from the transition zone and lower mantle into the shallow upper mantle. 1. Harte, B., Mineralogical Magazine, 2010. 74: p. 189-215. 2. Tappert, R., et al., Geology, 2005. 33: p. 565-568. 3. Walter, M.J., et al., Science, 2011. 333: p. 54-57. 4. Bulanova, G.P., et al., Contributions to Mineralogy and Petrology, 2010. 160: p. 489-510. 5. Harte, B. and N. Cayzer, Physics and Chemistry of Minerals, 2007.

  16. Magnetic mapping of (carbonated) oceanic crust-mantle boundary: New insights from Linnajavri, northern Norway

    NASA Astrophysics Data System (ADS)

    Tominaga, M.; Beinlich, A.; Tivey, M.; Andrade Lima, E.; Weiss, B. P.

    2012-12-01

    The contribution of lower oceanic crust and upper mantle to marine magnetic anomalies has long been recognized, but the detailed magnetic character of this non-volcanic source layer remains to be fully defined. Here, we report preliminary results of a magnetic survey and source characterization of a "carbonated" oceanic Moho (petrological "Mohorovicic discontinuity") sequence observed at the Linnajavri Serpentinite Complex (LSC), northern Norway. The LSC is located at 67° 36'N and 16° 24'E within the upper Allochthon of the Norwegian Caledonides and represents a dismembered ophiolite. Particularly in the southern ("Ridoalggicohkka") area of the LSC, gabbro, serpentinite and its talc-carbonate (soapstone) and quartz-carbonate (listvenite) altered equivalents are extraordinarily well-exposed [1]. An intact oceanic Moho is exposed here, despite its complex tectonic setting. The small degree of arctic rock weathering (≤ 2 mm weathering surface) allowed for detailed regional-scale surface magnetic mapping across alteration fronts (serpentinite-soapstone; soapstone-listvenite) and lithological contacts (soapstone-gabbro). Magnetic mapping was conducted using a handheld 3-axis magnetometer, surface-towed resistivity meter and Teka surface magnetic susceptometer with sample spacing of 1 m. Geophysical field mapping was combined with petrological observations and scanning SQUID microscopy (SM) mapping conducted on thin sections from rock samples that were drilled along the survey lines. Regional scale magnetic mapping indicates that the total magnetic field across both the "carbonated" Moho and the soapstone-serpentinite interfaces show higher frequency changes in their magnetic anomaly character and amplitudes than the surface-towed resistivity data. SQUID microscopy mapping of both natural remanence magnetization (NRM) and anhysteretic remanence magnetization (ARM) on gabbro, serpentinite, soapstone, and listvenite samples, with a sensor-sample separation of ˜190 μm, show that the distribution of microscopically measurable ferromagnetic and possibly sulfide minerals produces a different bulk intensity for each of the rock types. SM vector magnetic field maps of these samples also reveal that the magnetization associated with these grains (observed as dipole-like fields in SM maps) is variable in direction from grain to grain, which may result from different alteration histories for each grain. These complex magnetization patterns acquired through thermal and chemical alteration history may explain the short wavelength magnetic anomalies observed along our traverse lines. [1] Beinlich, A., Plümper, O., Hövelmann, J., Austrheim, H. and Jamtveit, B. (2012), Terra Nova, in press.

  17. Extensional crustal tectonics and crust-mantle coupling, a view from the geological record

    NASA Astrophysics Data System (ADS)

    Jolivet, Laurent; Menant, Armel; Clerc, Camille; Sternai, Pietro; Ringenbach, Jean-Claude; Bellahsen, Nicolas; Leroy, Sylvie; Faccenna, Claudio; Gorini, Christian

    2017-04-01

    In passive margins or back-arc regions, extensional deformation is often asymmetric, i.e. normal faults or extensional ductile shear zones dip in the same direction over large distances. We examine a number of geological examples in convergent or divergent contexts suggesting that this asymmetry results from a coupling between asthenospheric flow and crustal deformation. This is the case of the Mediterranean back-arc basins, such as the Aegean Sea, the northern Tyrrhenian Sea, the Alboran domain or the Gulf of Lion passive margin. Similar types of observation can be made on some of the Atlantic volcanic passive margins and the Afar region, which were all formed above a mantle plume. We discuss these contexts and search for the main controlling parameters for this asymmetric distributed deformation that imply a simple shear component at the scale of the lithosphere. The different geodynamic settings and tectonic histories of these different examples provide natural case-studies of the different controlling parameters, including a pre-existing heterogeneity of the crust and lithosphere (tectonic heritage) and the possible contribution of the underlying asthenospheric flow through basal drag or basal push. We show that mantle flow can induce deformation in the overlying crust in case of high heat flow and thin lithosphere. In back-arc regions, the cause of asymmetry resides in the relative motion between the asthenosphere below the overriding plate and the crust. When convergence and slab retreat work concurrently the asthenosphere flows faster than the crust toward the trench and the sense of shear is toward the upper plate. When slab retreat is the only cause of subduction, the sense of shear is opposite. In both cases, mantle flow is mostly the consequence of slab retreat and convergence. Mantle flow can however result also from larger-scale convection, controlling rifting dynamics prior to the formation of oceanic crust. In volcanic passive margins, in most cases normal faults dip toward the continent. This asymmetry may either result from the mantle flowing underneath regions evolving above a migrating plume, such as the Afar, when an asymmetry is observed at the scale of the rift, or from necking of the lithosphere when the conjugate margins show an opposite asymmetry. We summarize the various observed situations with normal faults dipping toward the continent ("hot" margins) or toward the ocean ("cold" margins) and discuss whether mantle flow is responsible for the observed asymmetry of deformation or not. Slipping along pre-existing heterogeneities seems a second-order phenomenon at lithospheric or crustal scale, except at the initiation of rifting.

  18. Crust-Mantle Interactions at Pico de Orizaba (Citlaltepetl) Volcano, Mexico.

    NASA Astrophysics Data System (ADS)

    Schaaf, P.; Carrasco, G.

    2006-12-01

    Pico de Orizaba (Citlaltepetl) volcano constitutes the easternmost and highest stratovolcano of the subduction- related Plio-Quaternary Trans-Mexican Volcanic Belt (TMVB). The volcano can be divided into three main constructional stages. Its activity started during the mid-Pleistocene. The present cone was built on the remnants of the ancestral buildings by eruption of amphibole-two pyroxene dacitic lava flows, the most recent of which was erupted in the seventeenth century. The volcano is surrounded to the SW by monogenetic Quaternary cindercones and maars. All representative units were sampled in this work for geochemical and isotopic purposes, including a small quartzitic xenolith found in the basaltic monogenetic suite. Volcanic products of the stratocone are quite heterogeneous and range from calc-alkaline basaltic andesites to dome rhyolites, also displayed by a wide range of SiO2 and MgO (72.6-53.2 and 7.0-0.3 wt. %, respectively). In comparison to other TMVB stratovolcanoes (e.g., Colima, Nevado de Toluca), Pico de Orizaba shows similar 87Sr/86Sr ratios (0.7037-0.7048) but considerably more evolved Nd-Pb isotopic ratios (eNd: -1.8 to + 1.4; 206Pb/204Pb: 18.61-18.78). Elevated LILE concentrations and depleted HFSE witness the importance of slab- derived aqueous fluids and metasomatic reactions between the subducting lithosphere and overlying mantle wedge. On the other hand, Pico de Orizaba volcano shows additionally high crustal contributions of a source with depleted Sr and enriched Nd and Pb isotopic signatures, best explained by considerable assimilation of the local Grenvillian basement in magma generation processes. In contrast to Popocatépetl volcano with a high-level magma reservoir emplacement (7-8 km) and obvious interaction with the carbonate-dominated shallow basement rocks (e.g. elevated 87Sr/86Sr ratios and CO2 in gas plumes), this effect cannot be observed at Pico de Orizaba volcano, although a regional Cretaceous limestone basement is also present. This, together with the different lithologies of crustal xenoliths in stratocone and cindercone magmas gives strong evidence for a deeper situated magma chamber.

  19. Zinc Isotopes as Tracers of Crust-Mantle Interactions and Mineralization Processes in Layered Intrusions

    NASA Astrophysics Data System (ADS)

    Day, J. M.; Moynier, F.

    2016-12-01

    Zinc isotopes are a powerful tool for studying igneous processes and may be useful for distinguishing between mantle or crustal origins for mineralization and for examining crystallization processes. Restricted ranges in δ66Zn for mantle-derived rocks (δ66Zn = 0.28±0.05‰; [{66Zn/64Znsample/66Zn/64ZnJMC-Lyon-1} × 1000] all uncertainties reported are 2SD) contrast the large δ66Zn variations in sedimentary rocks ( 0 to 1‰), or in volcanic and sedimentary hosted ore deposits (e.g., SEDEX; VHMS; MVT = -0.6 to 1.3‰). Here, we use Zn isotopes to investigate magmatic processes in the 1.27 Ga Muskox Intrusion (Canada) and 2.7 Ga Stillwater Intrusion (Montana). The Muskox main chromitite horizon has between 270-330 ppm Zn with δ66Zn ranging from 0.16 to 0.31‰. Zinc isotope compositions negatively correlate with Os isotopes. Chromitite (40a) with the lowest 187Os/188Os (0.132) has δ66Zn of 0.31±0.03‰; indistinguishable from the mantle value. CM19 glass from the co-eval Coppermine Volcanics, which has crust-like O and Nd isotopes but low 187Os/188Os (0.131), has been interpreted as the extrusive manifestation of chromitite genesis. The value of δ66Zn (0.27±0.07‰) for CM19 is within uncertainty of 40A, and permissive of formation during silicic-mafic melt mixing and large-scale chromitite crystallization. Stillwater chromitite seams exhibit a larger range in Zn (166-448 ppm), but generally lower δ66Zn (0.13±0.04‰) than Muskox chromitites, or to a JM Reef bulk sample (69 ppm Zn, δ66Zn = 0.22±0.03‰). These results suggest different sources of Zn for Ultramafic series chromitites versus the JM Reef (Banded series). Correspondingly, variations occur in Os isotopes for PGE poor chromitites (γOs = -2 to +4) versus the PGE-rich JM Reef (γOs = +12 to +34). Zinc isotope variations may be explained by either a mantle source with low δ66Zn that was subsequently contaminated by high δ66Zn crust, or from contamination of the ultramafic series by low δ66Zn continental lithospheric mantle. JM Reef sulphides span a wide range in Zn (1.8-350 ppm) and δ66Zn (-0.03 to 0.68‰) consistent with fractionation of Zn isotopes during sulphide melt-mineral crystallization. These results show promise for using Zn isotopes to study sources of mineralization and to elucidate sulphide crystallization processes.

  20. Crust-mantle Coupling Seismogenic Mechanism in Sichuan-Yunnan Region

    NASA Astrophysics Data System (ADS)

    Qiang, H.; Pei, L. S.; Yuan, Z. W.; Dong, L. S.

    2016-12-01

    The intracrustal weak zone controls strength of interaction between crust and mantle, restricts coupling relationship between lithospheric layers, and also affects mode of interaction between blocks. This effect can be analyzed in terms of comparing deformation and stress in different depth. The paper is based on GPS time series data that provided by 81 base stations from 1999 to 2015 to compute velocity field. Combining previous SKS shear wave splitting data, we analyze deformation characteristics of horizontal direction. The lithospheric bottom mantle convection stress field of the Sichuan-Yunnan region is calculated using 11 36 spherical harmonic coefficients of gravity model EGM2008. Meanwhile the focal mechanism of 1131 earthquakes that occurred from 2000 to now in Sichuan-Yunnan region is collected and organized. Through the above systematic research, this article argues that uneven development of the stress is the key of strain energy accumulation. And vertical coupling relationship of different layers greatly influences interaction of blocks. There is stress delamination in blocks which exist the intracrustal weak zone, stress of edge area changes significantly in horizontal and vertical directions, and seismic risk of crust above the weak layer is higher. We choose 81 stations from research area ,download the coordinate time series and use the monadic linear regression analysis to obtain the stations' average speed as shown in figure 1(a).the continuous variation of the velocity vector diagram.When in the process of communication, SKS wave divided into polarization direction and anisotropy of the parallel to the axis of symmetry fast slow wave and vertical wave through anisotropic medium. Fast wave polarization direction is considered to be the mantle peridotite in the crystal lattice advantage under the local stress direction, reflect the deformation of the upper mantle; Time delay of torsion wave reflect the characterization of anisotropic layer thickness and strength. This paper collected Wang Chunyong etc. [1], Chang Lijun provided in [2], such as literature research of 130 stations in the area of SKS shear wave splitting parameters (as shown in figure 1 (b)). From picture 1(c), Northwest Yunnan block and Lhasa block GPS crustal deformation direction are consistent.

  1. Estimating the DNA strand breakage using a fuzzy inference system and agarose gel electrophoresis, a case study with toothed carp Aphanius sophiae exposed to cypermethrin.

    PubMed

    Poorbagher, Hadi; Moghaddam, Maryam Nasrollahpour; Eagderi, Soheil; Farahmand, Hamid

    2016-07-01

    The DNA breakage has been widely used in ecotoxicological studies to investigate effects of pesticides in fishes. The present study used a fuzzy inference system to quantify the breakage of DNA double strand in Aphanius sophiae exposed to the cypermethrin. The specimens were adapted to different temperatures and salinity for 14 days and then exposed to cypermethrin. DNA of each specimens were extracted, electrophoresed and photographed. A fuzzy system with three input variables and 27 rules were defined. The pixel value curve of DNA on each gel lane was obtained using ImageJ. The DNA breakage was quantified using the pixel value curve and fuzzy system. The defuzzified values were analyzed using a three-way analysis of variance. Cypermethrin had significant effects on DNA breakage. Fuzzy inference systems can be used as a tool to quantify the breakage of double strand DNA. DNA double strand of the gill of A. sophiae is sensitive enough to be used to detect cypermethrin in surface waters in concentrations much lower than those reported in previous studies.

  2. Equipment fault diagnosis system of sequencing batch reactors using rule-based fuzzy inference and on-line sensing data.

    PubMed

    Kim, Y J; Bae, H; Poo, K M; Ko, J H; Kim, B G; Park, T J; Kim, C W

    2006-01-01

    The importance of a detection technique to prevent process deterioration is increasing. For the fast detection of this disturbance, a diagnostic algorithm was developed to determine types of equipment faults by using on-line ORP and DO profile in sequencing batch reactors (SBRs). To develop the rule base for fault diagnosis, the sensor profiles were obtained from a pilot-scale SBR when blower, influent pump and mixer were broken. The rules were generated based on the calculated error between an abnormal profile and a normal profile, e(ORP)(t) and e(DO)(t). To provide intermediate diagnostic results between "normal" and "fault", a fuzzy inference algorithm was incorporated to the rules. Fuzzified rules could present the diagnosis result "need to be checked". The diagnosis showed good performance in detecting and diagnosing various faults. The developed algorithm showed its applicability to detect faults and make possible fast action to correct them.

  3. Impact of Sampling Schemes on Demographic Inference: An Empirical Study in Two Species with Different Mating Systems and Demographic Histories

    PubMed Central

    St. Onge, K. R.; Palmé, A. E.; Wright, S. I.; Lascoux, M.

    2012-01-01

    Most species have at least some level of genetic structure. Recent simulation studies have shown that it is important to consider population structure when sampling individuals to infer past population history. The relevance of the results of these computer simulations for empirical studies, however, remains unclear. In the present study, we use DNA sequence datasets collected from two closely related species with very different histories, the selfing species Capsella rubella and its outcrossing relative C. grandiflora, to assess the impact of different sampling strategies on summary statistics and the inference of historical demography. Sampling strategy did not strongly influence the mean values of Tajima’s D in either species, but it had some impact on the variance. The general conclusions about demographic history were comparable across sampling schemes even when resampled data were analyzed with approximate Bayesian computation (ABC). We used simulations to explore the effects of sampling scheme under different demographic models. We conclude that when sequences from modest numbers of loci (<60) are analyzed, the sampling strategy is generally of limited importance. The same is true under intermediate or high levels of gene flow (4Nm > 2–10) in models in which global expansion is combined with either local expansion or hierarchical population structure. Although we observe a less severe effect of sampling than predicted under some earlier simulation models, our results should not be seen as an encouragement to neglect this issue. In general, a good coverage of the natural range, both within and between populations, will be needed to obtain a reliable reconstruction of a species’s demographic history, and in fact, the effect of sampling scheme on polymorphism patterns may itself provide important information about demographic history. PMID:22870403

  4. A reduced-order adaptive neuro-fuzzy inference system model as a software sensor for rapid estimation of five-day biochemical oxygen demand

    NASA Astrophysics Data System (ADS)

    Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin

    2013-07-01

    The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.

  5. Symbolic transfer entropy: inferring directionality in biosignals.

    PubMed

    Staniek, Matthäus; Lehnertz, Klaus

    2009-12-01

    Inferring directional interactions from biosignals is of crucial importance to improve understanding of dynamical interdependences underlying various physiological and pathophysiological conditions. We here present symbolic transfer entropy as a robust measure to infer the direction of interactions between multidimensional dynamical systems. We demonstrate its performance in quantifying driver-responder relationships in a network of coupled nonlinear oscillators and in the human epileptic brain.

  6. Application of Transformations in Parametric Inference

    ERIC Educational Resources Information Center

    Brownstein, Naomi; Pensky, Marianna

    2008-01-01

    The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

  7. Application of Transformations in Parametric Inference

    ERIC Educational Resources Information Center

    Brownstein, Naomi; Pensky, Marianna

    2008-01-01

    The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

  8. Inferring unknow boundary conditions of the Greenland Ice Sheet by assimilating ICESat-1 and IceBridge altimetry intothe Ice Sheet System Model.

    NASA Astrophysics Data System (ADS)

    Larour, E. Y.; Khazendar, A.; Seroussi, H. L.; Schlegel, N.; Csatho, B. M.; Schenk, A. F.; Rignot, E. J.; Morlighem, M.

    2014-12-01

    Altimetry signals from missions such as ICESat-1, CryoSat, EnviSat, as well as altimeters onboard Operation IceBridge provide vital insights into processes such as surface mass balance, mass transport and ice-flow dynamics. Historically however, ice-flow models have been focused on assimilating surface velocities from satellite-based radar observations, to infer properties such as basal friction or the position of the bedrock. Here, we leverage a new methodology based on automatic differentation of the Ice Sheet System Model to assimilate surface altimetry data into a reconstruction of the past decade of ice flow on the North Greenland area. We infer corrections to boundary conditions such as basal friction and surface mass balance, as well as corrections to the ice hardness, to best-match the observed altimetry record. We compare these corrections between glaciers such as Petermann Glacier, 79 North and Zacchariae Isstrom. The altimetry signals exhibit very different patterns between East and West, which translate into very different signatures for the inverted boundary conditions. This study gives us greater insights into what differentiates different basins, both in terms of mass transport and ice-flow dynamics, and what could bethe controlling mechanisms behind the very different evolutions of these basins.

  9. Using surface creep rate to infer fraction locked for sections of the San Andreas fault system in northern California from alignment array and GPS data

    USGS Publications Warehouse

    Lienkaemper, James J.; McFarland, Forrest S.; Simpson, Robert W.; Caskey, S. John

    2014-01-01

    Surface creep rate, observed along five branches of the dextral San Andreas fault system in northern California, varies considerably from one section to the next, indicating that so too may the depth at which the faults are locked. We model locking on 29 fault sections using each section’s mean long‐term creep rate and the consensus values of fault width and geologic slip rate. Surface creep rate observations from 111 short‐range alignment and trilateration arrays and 48 near‐fault, Global Positioning System station pairs are used to estimate depth of creep, assuming an elastic half‐space model and adjusting depth of creep iteratively by trial and error to match the creep observations along fault sections. Fault sections are delineated either by geometric discontinuities between them or by distinctly different creeping behaviors. We remove transient rate changes associated with five large (M≥5.5) regional earthquakes. Estimates of fraction locked, the ratio of moment accumulation rate to loading rate, on each section of the fault system provide a uniform means to inform source parameters relevant to seismic‐hazard assessment. From its mean creep rates, we infer the main branch (the San Andreas fault) ranges from only 20%±10% locked on its central creeping section to 99%–100% on the north coast. From mean accumulation rates, we infer that four urban faults appear to have accumulated enough seismic moment to produce major earthquakes: the northern Calaveras (M 6.8), Hayward (M 6.8), Rodgers Creek (M 7.1), and Green Valley (M 7.1). The latter three faults are nearing or past their mean recurrence interval.

  10. Bayesian Inference on Proportional Elections

    PubMed Central

    Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio

    2015-01-01

    Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259

  11. A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

    NASA Astrophysics Data System (ADS)

    El-Zoghby, Helmy M.; Bendary, Ahmed F.

    2016-10-01

    Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

  12. Higher order cycles, inferred chronostratigraphy, and impact of multiple lowstand systems tracts on hydrocarbon exploration, Pletmos basin, southern offshore, South Africa

    SciTech Connect

    Brink, G.J.

    1989-03-01

    Development of 67 middle Valanginian to middle Campanian cyclic depositional sequences is interpreted to be a response to the interplay of unique tectonics and higher order eustatic sea level cycles capable of imposing type 1 unconformities. Direct correlation of 16 sequences, within available paleontological age constraints, with Exxon's global third-order cycles encompasses the remaining 51 sequences, which are inferred to be fourth-order and fifth-order cycles. These unconformity bound sequences were grouped into genetic megasequences bound by major type 1 unconformities (third-order or fourth-order falls at the trough of a third-order cycle) typically displaying evidence of extensive erosion of thick highstand systems tracts.

  13. Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

    NASA Technical Reports Server (NTRS)

    Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

    2001-01-01

    A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

  14. Statistical inference and Aristotle's Rhetoric.

    PubMed

    Macdonald, Ranald R

    2004-11-01

    Formal logic operates in a closed system where all the information relevant to any conclusion is present, whereas this is not the case when one reasons about events and states of the world. Pollard and Richardson drew attention to the fact that the reasoning behind statistical tests does not lead to logically justifiable conclusions. In this paper statistical inferences are defended not by logic but by the standards of everyday reasoning. Aristotle invented formal logic, but argued that people mostly get at the truth with the aid of enthymemes--incomplete syllogisms which include arguing from examples, analogies and signs. It is proposed that statistical tests work in the same way--in that they are based on examples, invoke the analogy of a model and use the size of the effect under test as a sign that the chance hypothesis is unlikely. Of existing theories of statistical inference only a weak version of Fisher's takes this into account. Aristotle anticipated Fisher by producing an argument of the form that there were too many cases in which an outcome went in a particular direction for that direction to be plausibly attributed to chance. We can therefore conclude that Aristotle would have approved of statistical inference and there is a good reason for calling this form of statistical inference classical.

  15. On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Fleischer, Christian; Waag, Wladislaw; Bai, Ziou; Sauer, Dirk Uwe

    2013-12-01

    The battery management system (BMS) of a battery-electric road vehicle must ensure an optimal operation of the electrochemical storage system to guarantee for durability and reliability. In particular, the BMS must provide precise information about the battery's state-of-functionality, i.e. how much dis-/charging power can the battery accept at current state and condition while at the same time preventing it from operating outside its safe operating area. These critical limits have to be calculated in a predictive manner, which serve as a significant input factor for the supervising vehicle energy management (VEM). The VEM must provide enough power to the vehicle's drivetrain for certain tasks and especially in critical driving situations. Therefore, this paper describes a new approach which can be used for state-of-available-power estimation with respect to lowest/highest cell voltage prediction using an adaptive neuro-fuzzy inference system (ANFIS). The estimated voltage for a given time frame in the future is directly compared with the actual voltage, verifying the effectiveness and accuracy of a relative voltage prediction error of less than 1%. Moreover, the real-time operating capability of the proposed algorithm was verified on a battery test bench while running on a real-time system performing voltage prediction.

  16. OFMspert - Inference of operator intentions in supervisory control using a blackboard architecture. [operator function model expert system

    NASA Technical Reports Server (NTRS)

    Jones, Patricia S.; Mitchell, Christine M.; Rubin, Kenneth S.

    1988-01-01

    The authors proposes an architecture for an expert system that can function as an operator's associate in the supervisory control of a complex dynamic system. Called OFMspert (operator function model (OFM) expert system), the architecture uses the operator function modeling methodology as the basis for the design. The authors put emphasis on the understanding capabilities, i.e., the intent referencing property, of an operator's associate. The authors define the generic structure of OFMspert, particularly those features that support intent inferencing. They also describe the implementation and validation of OFMspert in GT-MSOCC (Georgia Tech-Multisatellite Operations Control Center), a laboratory domain designed to support research in human-computer interaction and decision aiding in complex, dynamic systems.

  17. Temporal order of evolution of DNA replication systems inferred by comparison of cellular and viral DNA polymerases

    PubMed Central

    Koonin, Eugene V

    2006-01-01

    Background The core enzymes of the DNA replication systems show striking diversity among cellular life forms and more so among viruses. In particular, and counter-intuitively, given the central role of DNA in all cells and the mechanistic uniformity of replication, the core enzymes of the replication systems of bacteria and archaea (as well as eukaryotes) are unrelated or extremely distantly related. Viruses and plasmids, in addition, possess at least two unique DNA replication systems, namely, the protein-primed and rolling circle modalities of replication. This unexpected diversity makes the origin and evolution of DNA replication systems a particularly challenging and intriguing problem in evolutionary biology. Results I propose a specific succession for the emergence of different DNA replication systems, drawing argument from the differences in their representation among viruses and other selfish replicating elements. In a striking pattern, the DNA replication systems of viruses infecting bacteria and eukaryotes are dominated by the archaeal-type B-family DNA polymerase (PolB) whereas the bacterial replicative DNA polymerase (PolC) is present only in a handful of bacteriophage genomes. There is no apparent mechanistic impediment to the involvement of the bacterial-type replication machinery in viral DNA replication. Therefore, I hypothesize that the observed, markedly unequal distribution of the replicative DNA polymerases among the known cellular and viral replication systems has a historical explanation. I propose that, among the two types of DNA replication machineries that are found in extant life forms, the archaeal-type, PolB-based system evolved first and had already given rise to a variety of diverse viruses and other selfish elements before the advent of the bacterial, PolC-based machinery. Conceivably, at that stage of evolution, the niches for DNA-viral reproduction have been already filled with viruses replicating with the help of the archaeal

  18. System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

    PubMed

    Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

    2014-01-01

    Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome

  19. Slip rates and spatially variable creep on faults of the northern San Andreas system inferred through Bayesian inversion of Global Positioning System data

    USGS Publications Warehouse

    Murray, Jessica R.; Minson, Sarah E.; Svarc, Jerry L.

    2014-01-01

    Fault creep, depending on its rate and spatial extent, is thought to reduce earthquake hazard by releasing tectonic strain aseismically. We use Bayesian inversion and a newly expanded GPS data set to infer the deep slip rates below assigned locking depths on the San Andreas, Maacama, and Bartlett Springs Faults of Northern California and, for the latter two, the spatially variable interseismic creep rate above the locking depth. We estimate deep slip rates of 21.5 ± 0.5, 13.1 ± 0.8, and 7.5 ± 0.7 mm/yr below 16 km, 9 km, and 13 km on the San Andreas, Maacama, and Bartlett Springs Faults, respectively. We infer that on average the Bartlett Springs fault creeps from the Earth's surface to 13 km depth, and below 5 km the creep rate approaches the deep slip rate. This implies that microseismicity may extend below the locking depth; however, we cannot rule out the presence of locked patches in the seismogenic zone that could generate moderate earthquakes. Our estimated Maacama creep rate, while comparable to the inferred deep slip rate at the Earth's surface, decreases with depth, implying a slip deficit exists. The Maacama deep slip rate estimate, 13.1 mm/yr, exceeds long-term geologic slip rate estimates, perhaps due to distributed off-fault strain or the presence of multiple active fault strands. While our creep rate estimates are relatively insensitive to choice of model locking depth, insufficient independent information regarding locking depths is a source of epistemic uncertainty that impacts deep slip rate estimates.

  20. Social Inference Through Technology

    NASA Astrophysics Data System (ADS)

    Oulasvirta, Antti

    Awareness cues are computer-mediated, real-time indicators of people’s undertakings, whereabouts, and intentions. Already in the mid-1970 s, UNIX users could use commands such as “finger” and “talk” to find out who was online and to chat. The small icons in instant messaging (IM) applications that indicate coconversants’ presence in the discussion space are the successors of “finger” output. Similar indicators can be found in online communities, media-sharing services, Internet relay chat (IRC), and location-based messaging applications. But presence and availability indicators are only the tip of the iceberg. Technological progress has enabled richer, more accurate, and more intimate indicators. For example, there are mobile services that allow friends to query and follow each other’s locations. Remote monitoring systems developed for health care allow relatives and doctors to assess the wellbeing of homebound patients (see, e.g., Tang and Venables 2000). But users also utilize cues that have not been deliberately designed for this purpose. For example, online gamers pay attention to other characters’ behavior to infer what the other players are like “in real life.” There is a common denominator underlying these examples: shared activities rely on the technology’s representation of the remote person. The other human being is not physically present but present only through a narrow technological channel.

  1. The evolution of reproductive systems and sex-determining mechanisms within rumex (polygonaceae) inferred from nuclear and chloroplastidial sequence data.

    PubMed

    Navajas-Pérez, Rafael; de la Herrán, Roberto; López González, Ginés; Jamilena, Manuel; Lozano, Rafael; Ruiz Rejón, Carmelo; Ruiz Rejón, Manuel; Garrido-Ramos, Manuel A

    2005-09-01

    The genus Rumex includes hermaphroditic, polygamous, gynodioecious, monoecious, and dioecious species, with the dioecious species being represented by different sex-determining mechanisms and sex-chromosome systems. Therefore, this genus represents an exceptional case study to test several hypotheses concerning the evolution of both mating systems and the genetic control of sex determination in plants. Here, we compare nuclear intergenic transcribed spacers and chloroplast intergenic sequences of 31 species of Rumex. Our phylogenetic analysis supports a systematic classification of the genus, which differs from that currently accepted. In contrast to the current view, this new phylogeny suggests a common origin for all Eurasian and American dioecious species of Rumex, with gynodioecy as an intermediate state on the way to dioecy. Our results support the contention that sex determination based on the balance between the number of X chromosomes and the number of autosomes (X/A balance) has evolved secondarily from male-determining Y mechanisms and that multiple sex-chromosome systems, XX/XY1Y2, were derived twice from an XX/XY system. The resulting phylogeny is consistent with a classification of Rumex species according to their basic chromosome number, implying that the evolution of Rumex species might have followed a process of chromosomal reduction from x = 10 toward x = 7 through intermediate stages (x = 9 and x = 8).

  2. FUNCTIONAL OVERLAP OF ROOT SYSTEMS IN AN OLD-GROWTH FOREST INFERRED FROM TRACER 15N UPTAKE

    EPA Science Inventory

    Belowground competition for nutrients and water is considered a key factor affecting spatial organization and productivity of individual stems within forest stands, yet there are few data describing the lateral extent and overlap of competing root systems. We quantified the func...

  3. FUNCTIONAL OVERLAP OF ROOT SYSTEMS IN AN OLD-GROWTH FOREST INFERRED FROM TRACER 15N UPTAKE

    EPA Science Inventory

    Belowground competition for nutrients and water is considered a key factor affecting spatial organization and productivity of individual stems within forest stands, yet there are few data describing the lateral extent and overlap of competing root systems. We quantified the func...

  4. Diatom-inferred hydrological changes and Holocene geomorphic transitioning of Africa's largest estuarine system, Lake St Lucia

    NASA Astrophysics Data System (ADS)

    Gomes, M.; Humphries, M. S.; Kirsten, K. L.; Green, A. N.; Finch, J. M.; de Lecea, A. M.

    2017-06-01

    The diverse lagoons and coastal lakes along the east coast of South Africa occupy incised valleys that were flooded during the rise and subsequent stabilisation of relative sea-level during the Holocene. Sedimentary deposits contained within these waterbodies provide an opportunity to investigate complex hydrological and sedimentological processes, and examine sea-level controls governing system geomorphic evolution. In this paper, we combine diatom and sulfur isotope analyses from two sediment cores extracted from the northern sub-basins of Lake St Lucia, a large shallow estuarine lake that is today largely isolated from direct ocean influence behind a Holocene-Pleistocene barrier complex. Analyses allow the reconstruction of hydrological changes associated with the geomorphic development of the system over the mid-to late Holocene. The sedimentary sequences indicate that St Lucia was a shallow, partially enclosed estuary/embayment dominated by strong tidal flows prior to ∼6200 cal. BP. Infilling was initiated when sea-level rise slowed and stabilised around present day levels, resulting in the accumulation of fine-grained sediment behind an emergent proto-barrier. Diatom assemblages, dominated by marine benthic and epiphytic species, reveal a system structured by marine water influx and characterised by marsh and tidal flat habitats until ∼4550 cal. BP. A shift in the biological community at ∼4550 cal. BP is linked to the development of a back-barrier water body that supported a brackish community. Marine planktonics and enrichments in δ34S suggest recurrent, large-scale barrier inundation events during this time, coincident with a mid-Holocene sea-level highstand. Periodic marine incursions associated with episodes of enhanced storminess and overwash remained prevalent until ∼1200 cal. BP, when further barrier construction ultimately isolated the northern basins from the ocean. This study provides the first reconstruction of the palaeohydrological

  5. Dioecy in Amborella trichopoda: evidence for genetically based sex determination and its consequences for inferences of the breeding system in early angiosperms.

    PubMed

    Anger, Nicolas; Fogliani, Bruno; Scutt, Charles P; Gâteblé, Gildas

    2017-03-01

    This work aimed to gain insight into the breeding system at the base of living angiosperms through both character state reconstructions and the study of sex ratios and phenotypes in the likely sister to all other living angiosperms, Amborella trichopoda . Sex phenotypes were mapped onto a phylogeny of basally diverging angiosperms using maximum parsimony. In parallel, sex ratios and phenotypes were studied over two consecutive flowering seasons in an ex situ population of A. trichopoda , while the sex ratio of an in situ population was also assessed. Parsimony analyses failed to resolve the breeding system present at the base of living angiosperms, but indicated the importance of A. trichopoda for the future elucidation of this question. The ex situ A. trichopoda population studied showed a primary sex ratio close to 1:1, though sex ratio bias was found in the in situ population studied. Instances of sexual instability were quantified in both populations. Sex ratio data support the presence of genetic sex determination in A. trichopoda , whose further elucidation may guide inferences on the breeding system at the base of living angiosperms. Sexual instability in A. trichopoda suggests the operation of epigenetic mechanisms, and the evolution of dioecy via a gynodioecious intermediate.

  6. Temporal Development of Repeated Intrusive Events in a South Iceland Volcanic System, Inferred From InSAR Measurements

    NASA Astrophysics Data System (ADS)

    Pedersen, R.; Sigmundsson, F.

    2002-12-01

    We present measurements of volcano deformation from a series of 18 interferograms spanning the years 1993-2000. The detected deformation originates from repeated intrusions in the Eyjafjallaj”kull system, an icecap covered stratovolcano situated in, what is considered to be, a propagating rift zone in southern Iceland. The volcano erupts infrequently, with only two known eruptions in historic time (last 1100 years). The eruptive products are alkaline in composition, with only small volumes produced in recent eruptions. In spite of the apparent silence of this system two intrusive episodes have been detected within the last decade, causing major concern in the local community. In 1994, and again in 1999, seismic unrest associated with magmatic intrusions occurred in the system. Crustal deformation associated with the events was detected by dry-tilt, GPS and interferometry. During the 1994 episode, the center of deformation was situated underneath the icecap, and the area experiencing maximum uplift was therefore within the zone of decorrelation. The deformation shows an oval fringe pattern, which reaches well beyond the icecap, covering more than 300 km2 in total. Up to 15 cm of LOS ("line of sight") displacement is observed. The temporal resolution of the InSAR images during the 1999 intrusive episode is better and it is possible to follow the development of the intrusive event through time. The center of deformation does not coincide with the center from the 1994 event, but is situated just south of the icecap. The deformation during this event amounts to about 20 cm of LOS. Several of the interferograms cover the whole time-span of the 1999 intrusion, but three interferograms cover different periods of the intrusive event. The data set enables us to follow the temporal development of the crustal deformation created by the intrusion, and hence the growth of the intrusion itself through time. A previous study based on forward modeling of GPS and tilt data

  7. Stress pattern of the Shanxi rift system, North China, inferred from the inversion of new focal mechanisms

    NASA Astrophysics Data System (ADS)

    Li, Bin; Atakan, Kuvvet; Sørensen, Mathilde Bøttger; Havskov, Jens

    2015-05-01

    Earthquake focal mechanisms of the Shanxi rift system, North China, are investigated for the time period 1965-April 2014. A total of 143 focal mechanisms of ML ≥ 3.0 earthquakes were compiled. Among them, 105 solutions are newly determined in this study by combining the P-wave first motions and full waveform inversion, and 38 solutions are from available published data. Stress tensor inversion was then performed based on the new database. The results show that most solutions in the Shanxi rift system exhibit normal or strike-slip faulting, and the regional stress field is transtensional and dominated by NNW-SSE extension. This correlates well with results from GPS data, geological field observations and levelling measurements across the faults. Heterogeneity exists in the regional stress field, as indicated by individual stress tensor inversions conducted for five subzones. While the minimum stress axis (σ3) appears to be consistent and stable, the orientations, especially the plunges, of the maximum and intermediate stresses (σ1 and σ2) vary significantly along the strike of the different subzones. Based on our results and combining multidisciplinary observations from geological surveys, GPS and cross-fault monitoring, a kinematic model is proposed for the Shanxi rift system, in which the rift is situated between two opposite rotating crustal blocks, exhibiting a transtensional stress regimes. This model illustrates the present-day stress field and its correlation to the regional tectonics, as well as the current crustal deformation of the Shanxi rift system. Results obtained in this study, may help to understand the geodynamics, neotectonic activity, active seismicity and potential seismic hazard in this region.

  8. Stress Pattern of the Shanxi Rift System, North China, Inferred from the Inversion of New Focal Mechanisms

    NASA Astrophysics Data System (ADS)

    Li, Bin; Sørensen, Mathilde; Atakan, Kuvvet; Havskov, Jens

    2015-04-01

    The Shanxi rift system is one of the most outstanding intra-plate transtensional fault zones in the North China block. Earthquake focal mechanisms of the rift system are investigated for the time period 1965 - Apr. 2014. A total of 143 focal mechanisms of ML ≥ 3.0 earthquakes were compiled. Among them, 105 solutions are newly determined by combining the P-wave first motions and full waveform inversion, and 38 solutions are from available published data. Stress tensor inversion was then performed based on the new database. The results show that most solutions exhibit normal or strike-slip faulting, and the regional stress field is transtensional and dominated by NNW-SSE extension. This correlates well with results from GPS data, geological field observations and leveling measurements across the faults. Heterogeneity exists in the regional stress field, as indicated by individual stress tensor inversions conducted for five subzones. While the minimum stress axis (σ3) appears to be consistent and stable, the orientations, especially the plunges, of the maximum and intermediate stresses (σ1 and σ2) vary significantly among the different subzones. Based on our results and combining multidisciplinary observations from geological surveys, GPS and cross-fault monitoring, a kinematic model is proposed, in which the Shanxi rift system is situated between two opposite rotating blocks, exhibiting a transtensional stress regime. This model illustrates the present-day stress field and its correlation with the regional tectonics, as well as the current crustal deformation of the Shanxi rift system. Results obtained in this study, may help to understand the geodynamics, neotectonic activity, active seismicity and potential seismic hazard in this region of North China.

  9. Field Demonstration of a Broadband Acoustical Backscattering System Mounted on a REMUS-100 for Inferences of Zooplankton Size and Abundancy

    DTIC Science & Technology

    2011-09-30

    the Rayleigh-to-geometric scattering transition is within the frequency band of the WHOI broadband system (e.g., copepods ), and either larger fluid...that numerical abundance of zooplankton was dominated by small copepods that were relatively evenly distributed throughout the water-column...indication in either the MONESS or the VPR that the acoustic scattering layer was correlated to an increased abundance of zooplankton. Small copepods

  10. Application of adaptive neuro-fuzzy inference system techniques and artificial neural networks to predict solid oxide fuel cell performance in residential microgeneration installation

    NASA Astrophysics Data System (ADS)

    Entchev, Evgueniy; Yang, Libing

    This study applies adaptive neuro-fuzzy inference system (ANFIS) techniques and artificial neural network (ANN) to predict solid oxide fuel cell (SOFC) performance while supplying both heat and power to a residence. A microgeneration 5 kW el SOFC system was installed at the Canadian Centre for Housing Technology (CCHT), integrated with existing mechanical systems and connected in parallel to the grid. SOFC performance data were collected during the winter heating season and used for training of both ANN and ANFIS models. The ANN model was built on back propagation algorithm as for ANFIS model a combination of least squares method and back propagation gradient decent method were developed and applied. Both models were trained with experimental data and used to predict selective SOFC performance parameters such as fuel cell stack current, stack voltage, etc. The study revealed that both ANN and ANFIS models' predictions agreed well with variety of experimental data sets representing steady-state, start-up and shut-down operations of the SOFC system. The initial data set was subjected to detailed sensitivity analysis and statistically insignificant parameters were excluded from the training set. As a result, significant reduction of computational time was achieved without affecting models' accuracy. The study showed that adaptive models can be applied with confidence during the design process and for performance optimization of existing and newly developed solid oxide fuel cell systems. It demonstrated that by using ANN and ANFIS techniques SOFC microgeneration system's performance could be modelled with minimum time demand and with a high degree of accuracy.

  11. Allogenic forcing of autogenic processes: inferences from an aggregated process-based model of fluvio-deltaic systems

    NASA Astrophysics Data System (ADS)

    Karamitopoulos, P.; Weltje, G.; Dalman, R.

    2011-12-01

    Spatial and temporal variability of sediment storage in fluvio-deltaic sedimentary systems is controlled by the interplay of allogenic and autogenic processes. In order to investigate the effects of this interplay on the resulting stratigraphy at varying spatio-temporal scales, we carried out a series of numerical experiments using an aggregated process-based model of fluvio-deltaic systems (SIMCLAST), which combines diffusive and advective transport with sub-grid channel stability algorithms in the fluvial domain. New distributary channels occur by avulsions under conditions of local superelevation or through bifurcations due to mouth bar deposition. A series of numerical experiments were performed under forcing by glacio-eustatic sealevel cycles in the order of 100 kyr. Initial conditions of all experiments are represented by classic continental-margin topography with a shelf break. In this scenario, erosional features (canyons) are developed when sea level falls below the shelf break. Sediment supply and liquid discharge remain constant throughout the experiments. In order to characterize the topographic variability during the experiments, we used a difference measure obtained by summation of local changes in net sediment accumulation rates across the entire model domain. Long-term average variability (10 kyr resolution) correlates strongly with the allogenic sea-level signal. The long-term variability reaches a maximum around the time interval corresponding to isochronous maximum flooding surfaces, when retrogradation gives way to a new episode of progradation. Long-term mean variability is lowest during periods of sea-level fall, when incision restricts sediment dispersal. Increasing the time resolution of our difference measure allows recognition of numerous small peaks which correspond to local changes in sediment accumulation rates induced by autogenic processes (avulsions and bifurcations). The amplitudes of these peaks are related to the rate of change of

  12. Late Quaternary crustal shortening rates across thrust systems beneath the Ou Ranges in the NE Japan arc inferred from fluvial terrace deformation

    NASA Astrophysics Data System (ADS)

    Matsu'ura, Tabito; Sugaya, Katsunori

    2017-06-01

    We documented the existence of a blind thrust along the volcanic front in northeast Japan and calculated the crustal shortening rate across the Ou Ranges. We detected broad anticlinal deformation of the longitudinal profiles of fluvial terraces dated by using tephro- and cryptotephrostratigraphy. We inferred that the Daizaki flexure, located along the southern extension of the 2008 Iwate-Miyagi Nairiku Earthquake (IMEQ) fault, indicated the presence of an underlying thrust (Daizaki fault, newly named) there. Therefore, we inferred the existence of a west-dipping thrust system along the volcanic front at the eastern edge of the Ou Ranges consisting from north to south of the Kitakami Teichi Seien Fault Zone, the 2008 IMEQ fault and the Daizaki fault. To estimate rates of crustal deformation due to this thrust, we determined the uplift rate distribution from a pair of accumulation terrace surfaces, one formed during the marine isotope stage (MIS) 6-5 glacial-to-interglacial transition and the other during the MIS 2-1 transition. Because the overall uplift-rate distribution includes crustal deformation at both regional and local scales, we calculated the fault-related deformation area by subtracting the regional uplift rate (0.15-0.18 m ky-1, obtained from a pair of fluvial terraces on the stable footwall) from the total uplift-rate distribution across the fault. A mass balance calculation of the fault-related deformation area showed the crustal shortening rate across the 2008 IMEQ fault to be 0.50 ± 0.19-0.59 ± 0.22 m ky-1. An east-dipping thrust system along the western edge of the Ou Ranges (eastern part of the Shinjo Basin Fault Zone) has also contributed to crustal shortening during the late Quaternary at a previously estimated rate of 0.65-1.42 m ky-1. Therefore, the shortening rates of the eastern and western thrust systems individually account for about 0.6-0.7% and 0.7-1.6%, respectively (total, 1.3-2.3%), of the convergence between the Pacific and Eurasian

  13. Inferring biotic interactions from proxies.

    PubMed

    Morales-Castilla, Ignacio; Matias, Miguel G; Gravel, Dominique; Araújo, Miguel B

    2015-06-01

    Inferring biotic interactions from functional, phylogenetic and geographical proxies remains one great challenge in ecology. We propose a conceptual framework to infer the backbone of biotic interaction networks within regional species pools. First, interacting groups are identified to order links and remove forbidden interactions between species. Second, additional links are removed by examination of the geographical context in which species co-occur. Third, hypotheses are proposed to establish interaction probabilities between species. We illustrate the framework using published food-webs in terrestrial and marine systems. We conclude that preliminary descriptions of the web of life can be made by careful integration of data with theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Structure of a low-enthalpy geothermal system inferred from magnetotellurics - A case study from Sri Lanka

    NASA Astrophysics Data System (ADS)

    Nimalsiri, Thusitha Bandara; Suriyaarachchi, Nuwan Buddhika; Hobbs, Bruce; Manzella, Adele; Fonseka, Morrel; Dharmagunawardena, H. A.; Subasinghe, Nalaka Deepal

    2015-06-01

    First comprehensive geothermal exploration in Sri Lanka was conducted in 2010 encompassing seven thermal springs, of which Kapurella records the highest temperature. The study consisted of passive magnetotelluric (MT) soundings, in which static shifts were corrected using time domain electromagnetic method (TDEM). A frequency range of 12,500-0.001 Hz was used for MT acquisition and polar diagrams were employed for dimensionality determination. MT and TDEM data were jointly inverted and 2D models were created using both transverse electric and transverse magnetic modes. A conductive southeast dipping structure is revealed from both phase pseudosections and the preferred 2D inversion model. A conductive formation starting at a depth of 7.5 km shows a direct link with the dipping structure. We suggest that these conductive structures are accounted for deep circulation and accumulation of groundwater. Our results show the geothermal reservoir of Kapurella system with a lateral extension of around 2.5 km and a depth range of 3 km. It is further found that the associated dolerite dike is not the source of heat although it could be acting as an impermeable barrier to form the reservoir. The results have indicated the location of the deep reservoir and the possible fluid path of the Kapurella system, which could be utilized to direct future geothermal studies. This pioneering study makes suggestions to improve future MT data acquisition and to use boreholes and other geophysical methods to improve the investigation of structures at depth.

  15. Stress Pattern of the Shanxi Rift System, North China, Inferred from the Inversion of New Focal Mechanisms

    NASA Astrophysics Data System (ADS)

    Li, B.; Atakan, K.; Sorensen, M. B.; Havskov, J.

    2014-12-01

    Earthquake focal mechanisms of the Shanxi rift system, North China, are investigated for the time period 1965 - Apr. 2014. A total of 143 focal mechanisms of ML ≥ 3.0 earthquakes were compiled. Among them, 105 solutions are newly determined by combining the P-wave first motions and full waveform inversion, and 38 solutions are from available published data. Stress tensor inversion was then performed based on the new database. The results show that most solutions exhibit normal or strike-slip faulting, and the regional stress field is characterized by a stable, dominating NNW-SSE extension and an ENE-WSW compression. This correlates well with results from GPS data, geological field observations and leveling measurements across the faults. Heterogeneity exists in the regional stress field, as indicated by individual stress tensor inversions conducted for five subzones. While the minimum stress axis (σ3) appears to be consistent and stable, the orientations, especially the plunges, of the maximum and intermediate stresses (σ1 and σ2) vary significantly among the different subzones. Based on our results and combining multidisciplinary observations from geological surveys, GPS and cross-fault monitoring, a kinematic model is proposed, to illustrate the present-day stress field and its correlation with the regional tectonics, as well as the current crustal deformation of the Shanxi rift system. Results obtained in this study, may help to understand the geodynamics, neotectonic activity, active seismicity and potential seismic hazard in this region of North China.

  16. Statistical analysis and decoding of neural activity in the rodent geniculate ganglion using a metric-based inference system.

    PubMed

    Wu, Wei; Mast, Thomas G; Ziembko, Christopher; Breza, Joseph M; Contreras, Robert J

    2013-01-01

    We analyzed the spike discharge patterns of two types of neurons in the rodent peripheral gustatory system, Na specialists (NS) and acid generalists (AG) to lingual stimulation with NaCl, acetic acid, and mixtures of the two stimuli. Previous computational investigations found that both spike rate and spike timing contribute to taste quality coding. These studies used commonly accepted computational methods, but they do not provide a consistent statistical evaluation of spike trains. In this paper, we adopted a new computational framework that treated each spike train as an individual data point for computing summary statistics such as mean and variance in the spike train space. We found that these statistical summaries properly characterized the firing patterns (e. g. template and variability) and quantified the differences between NS and AG neurons. The same framework was also used to assess the discrimination performance of NS and AG neurons and to remove spontaneous background activity or "noise" from the spike train responses. The results indicated that the new metric system provided the desired decoding performance and noise-removal improved stimulus classification accuracy, especially of neurons with high spontaneous rates. In summary, this new method naturally conducts statistical analysis and neural decoding under one consistent framework, and the results demonstrated that individual peripheral-gustatory neurons generate a unique and reliable firing pattern during sensory stimulation and that this pattern can be reliably decoded.

  17. "Groundwater ages" of the Lake Chad multi-layer aquifers system inferred from 14C and 36Cl data

    NASA Astrophysics Data System (ADS)

    Bouchez, Camille; Deschamps, Pierre; Goncalves, Julio; Hamelin, Bruno; Seidel, Jean-Luc; Doumnang, Jean-Claude

    2014-05-01

    Assessment of recharge, paleo-recharge and groundwater residence time of aquifer systems of the Sahel is pivotal for a sustainable management of this vulnerable resource. Due to its stratified aquifer system, the Lake Chad Basin (LCB) offers the opportunity to assess recharge processes over time and to link climate and hydrology in the Sahel. Located in north-central Africa at the fringe between the Sahel and the Sahara, the lake Chad basin (LCB) is an endorheic basin of 2,5.106 km2. With a monsoon climate, the majority of the rainfall occurs in the southern one third of the basin, the Chari/Logone River system transporting about 90% of the runoff generated within the drainage basin. A complex multi-layer aquifer system is located in the central part of the LCB. The Quaternary unconfined aquifer, covering 500 000 km2, is characterized by the occurrence of poorly understood piezometric depressions. Artesian groundwaters are found in the Plio-Pleistocene lacustrine and deltaic sedimentary aquifers (early Pliocene and Continental Terminal). The present-day lake is in hydraulic contact with the Quaternary Aquifer, but during past megalake phases, most of the Quaternary aquifer was submerged and may experience major recharge events. To identify active recharge area and assess groundwater dynamics, one hundred surface and groundwater samples of all layers have been collected over the southern part of the LCB. Major and trace elements have been analyzed. Measurements of 36Cl have been carried out at CEREGE, on the French 5 MV AMS National Facility ASTER and 14C activities have been analyzed for 17 samples on the French AMS ARTEMIS. Additionally, the stable isotopic composition was measured on the artesian aquifer samples. In the Quaternary aquifer, results show a large scatter with waters having very different isotopic and geochemical signature. In its southern part and in the vicinity of the surface waters, groundwaters are predominantly Ca-Mg-HCO3 type waters with very

  18. Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses.

    PubMed

    Mathur, Neha; Glesk, Ivan; Buis, Arjan

    2016-10-01

    Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring.

  19. A novel approach for exposure assessment in air pollution epidemiological studies using neuro-fuzzy inference systems: Comparison of exposure estimates and exposure-health associations.

    PubMed

    Blanes-Vidal, Victoria; Cantuaria, Manuella Lech; Nadimi, Esmaeil S

    2017-04-01

    Many epidemiological studies have used proximity to sources as air pollution exposure assessment method. However, proximity measures are not generally good surrogates because of their complex non-linear relationship with exposures. Neuro-fuzzy inference systems (NFIS) can be used to map complex non-linear systems, but its usefulness in exposure assessment has not been extensively explored. We present a novel approach for exposure assessment using NFIS, where the inputs of the model were easily-obtainable proximity measures, and the output was residential exposure to an air pollutant. We applied it to a case-study on NH3 pollution, and compared health effects and exposures estimated from NFIS, with those obtained from emission-dispersion models, and linear and non-linear regression proximity models, using 10-fold cross validation. The agreement between emission-dispersion and NFIS exposures was high (Root-mean-square error (RMSE) =0.275, correlation coefficient (r)=0.91) and resulted in similar health effect estimates. Linear models showed poor performance (RMSE=0.527, r=0.59), while non-linear regression models resulted in heterocedasticity, non-normality and clustered data. NFIS could be a useful tool for estimating individual air pollution exposures in epidemiological studies on large populations, when emission-dispersion data are not available. The tradeoff between simplicity and accuracy needs to be considered. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Using adaptive neuro-fuzzy inference system technique for crosstalk correction in simultaneous 99mTc/201Tl SPECT imaging: A Monte Carlo simulation study

    NASA Astrophysics Data System (ADS)

    Heidary, Saeed; Setayeshi, Saeed

    2015-01-01

    This work presents a simulation based study by Monte Carlo which uses two adaptive neuro-fuzzy inference systems (ANFIS) for cross talk compensation of simultaneous 99mTc/201Tl dual-radioisotope SPECT imaging. We have compared two neuro-fuzzy systems based on fuzzy c-means (FCM) and subtractive (SUB) clustering. Our approach incorporates eight energy-windows image acquisition from 28 keV to 156 keV and two main photo peaks of 201Tl (77±10% keV) and 99mTc (140±10% keV). The Geant4 application in emission tomography (GATE) is used as a Monte Carlo simulator for three cylindrical and a NURBS Based Cardiac Torso (NCAT) phantom study. Three separate acquisitions including two single-isotopes and one dual isotope were performed in this study. Cross talk and scatter corrected projections are reconstructed by an iterative ordered subsets expectation maximization (OSEM) algorithm which models the non-uniform attenuation in the projection/back-projection. ANFIS-FCM/SUB structures are tuned to create three to sixteen fuzzy rules for modeling the photon cross-talk of the two radioisotopes. Applying seven to nine fuzzy rules leads to a total improvement of the contrast and the bias comparatively. It is found that there is an out performance for the ANFIS-FCM due to its acceleration and accurate results.

  1. A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system.

    PubMed

    Xie, Qiuju; Ni, Ji-Qin; Su, Zhongbin

    2017-03-05

    Ammonia (NH3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human's vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with "Gbell" membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R(2)) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.

  2. From velocity and attenuation tomography to rock physical modeling: Inferences on fluid-driven earthquake processes at the Irpinia fault system in southern Italy

    NASA Astrophysics Data System (ADS)

    Amoroso, O.; Russo, G.; De Landro, G.; Zollo, A.; Garambois, S.; Mazzoli, S.; Parente, M.; Virieux, J.

    2017-07-01

    We retrieve 3-D attenuation images of the crustal volume embedding the fault system associated with the destructive Ms 6.9, 1980 Irpinia earthquake by tomographic inversion of t* measurements. A high QP anomaly is found to be correlated with the 1980 fault geometry, while the QS model shows regional-scale variations related to the NE edge of the uplifted pre-Tertiary limestone. An upscaling strategy is used to infer rock properties such as porosity, consolidation, type of fluid mixing, and relative saturation percentage at 8-10 km fault depth. We constrain the porosity and consolidation in the ranges 4-5% and 5-9, respectively, with the possible fluid mixes being both brine-CO2 and CH4-CO2. The consolidation parameter range indicates high pore pressures at the same depths. These results support the evidence for a fracture system, highly saturated in gases and a seismicity triggering mechanism at the fault zone, which is strongly controlled by fluid-induced pore pressure changes.

  3. Tectonic history of the north portion of the San Andreas fault system, California, inferred from gravity and magnetic anomalies

    USGS Publications Warehouse

    Griscom, A.; Jachens, R.C.

    1989-01-01

    Geologic and geophysical data for the San Andreas fault system north of San Francisco suggest that the eastern boundary of the Pacific plate migrated eastward from its presumed original position at the base of the continental slope to its present position along the San Andreas transform fault by means of a series of eastward jumps of the Mendocino triple junction. These eastward jumps total a distance of about 150 km since 29 Ma. Correlation of right-laterally displaced gravity and magnetic anomalies that now have components at San Francisco and on the shelf north of Point Arena indicates that the presently active strand of the San Andreas fault north of the San Francisco peninsula formed recently at about 5 Ma when the triple junction jumped eastward a minimum of 100 km to its present location at the north end of the San Andreas fault. -from Authors

  4. Spatial and temporal geochemical trends in the hydrothermal system of Yellowstone National Park: Inferences from river solute fluxes

    USGS Publications Warehouse

    Hurwitz, S.; Lowenstern, J. B.; Heasler, H.

    2007-01-01

    We present and analyze a chemical dataset that includes the concentrations and fluxes of HCO3-, SO42-, Cl-, and F- in the major rivers draining Yellowstone National Park (YNP) for the 2002-2004 water years (1 October 2001 - 30 September 2004). The total (molar) flux in all rivers decreases in the following order, HCO3- > Cl- > SO42- > F-, but each river is characterized by a distinct chemical composition, implying large-scale spatial heterogeneity in the inputs of the various solutes. The data also display non-uniform temporal trends; whereas solute concentrations and fluxes are nearly constant during base-flow conditions, concentrations decrease, solute fluxes increase, and HCO3-/Cl-, and SO42-/Cl- increase during the late-spring high-flow period. HCO3-/SO42- decreases with increasing discharge in the Madison and Falls Rivers, but increases with discharge in the Yellowstone and Snake Rivers. The non-linear relations between solute concentrations and river discharge and the change in anion ratios associated with spring runoff are explained by mixing between two components: (1) a component that is discharged during base-flow conditions and (2) a component associated with snow-melt runoff characterized by higher HCO3-/Cl- and SO42-/Cl-. The fraction of the second component is greater in the Yellowstone and Snake Rivers, which host lakes in their drainage basins and where a large fraction of the solute flux follows thaw of ice cover in the spring months. Although the total river HCO3- flux is larger than the flux of other solutes (HCO3-/Cl- ??? 3), the CO2 equivalent flux is only ??? 1% of the estimated emission of magmatic CO2 soil emissions from Yellowstone. No anomalous solute flux in response to perturbations in the hydrothermal system was observed, possibly because gage locations are too distant from areas of disturbance, or because of the relatively low sampling frequency. In order to detect changes in river hydrothermal solute fluxes, sampling at higher

  5. Model of the volcano-hydrothermal system of Tatun Volcano Group, northern Taiwan, inferred from seismicity and gas geochemistry

    NASA Astrophysics Data System (ADS)

    Konstantinou, K. I.; Rontogianni, S.; Lin, C.-H.

    2012-04-01

    The Tatun Volcano Group (TVG) is located in northern Taiwan near the capital Taipei. In this study we selected and analyzed almost four years (2004 - 2007) of its seismic activity. The seismic network established around TVG initially consisted of eight three component seismic stations with this number increasing to twelve by 2007. Local seismicity mainly involved High Frequency (HF) earthquakes occurring as isolated events or as spasmodic bursts. Mixed and Low Frequency (LF) events were observed during the same period but more rarely. During the analysis we estimated the magnitudes for the HF earthquakes and used a probabilistic non-linear method to locate all these events. We examined the temporal and spatial distribution of our data-set for each year and the monthly seismic energy distribution. In addition, complex frequencies for LF events were analyzed with the Sompi method. We juxtapose these results with gas geochemistry studies of fumaroles covering a similar period. A model for the volcano-hydrothermal system is proposed where fluids and magmatic gases ascend from a magma body that lies at around 7- 8 km depth. The movement of fluids to shallow depths increases the heat, the fracturing and also creates resonance and vibrations in cracks and conduits. This detailed analysis and previous physical volcanology observations at TVG suggest that the region is volcanically active and that measures to mitigate the risks have to be considered by the local authorities.

  6. Inferring the interconnections between surface water bodies, tile-drains and an unconfined aquifer-aquitard system: A case study

    NASA Astrophysics Data System (ADS)

    Colombani, N.; Di Giuseppe, D.; Faccini, B.; Ferretti, G.; Mastrocicco, M.; Coltorti, M.

    2016-06-01

    Shallow lenses in reclaimed coastal areas are precious sources of freshwater for crop development, but their seasonal behaviour is seldom known in tile-drained fields. In this study, field monitoring and numerical modelling provide a robust conceptual model of these complex environments. Crop and meteorological data are used to implement an unsaturated flow model to reconstruct daily recharge. Groundwater fluxes and salinity, water table elevation, tile-drains' discharge and salinity are used to calibrate a 2D density-dependent numerical model to quantify non-reactive solute transport within the aquifer-aquitard system. Results suggest that lateral fluxes in low hydraulic conductivity sediments are limited, while water table fluctuation is significant. The use of depth-integrated monitoring to calibrate the model results in poor efficiency, while multi-level soil profiles are crucial to define the mixing zone between fresh and brackish groundwater. Measured fluxes and chloride concentrations from tile-drains not fully compare with calculated ones due to preferential flow through cracks.

  7. Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification.

    PubMed

    Kang, Jin Kyu; Hong, Hyung Gil; Park, Kang Ryoung

    2017-07-08

    A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting. There are many studies on CNN-based pedestrian detection through the use of far-infrared (FIR) light cameras (i.e., thermal cameras) to address such difficulties. However, when the solar radiation increases and the background temperature reaches the same level as the body temperature, it remains difficult for the FIR light camera to detect pedestrians due to the insignificant difference between the pedestrian and non-pedestrian features within the images. Researchers have been trying to solve this issue by inputting both the visible light and the FIR camera images into the CNN as the input. This, however, takes a longer time to process, and makes the system structure more complex as the CNN needs to process both camera images. This research adaptively selects a more appropriate candidate between two pedestrian images from visible light and FIR cameras based on a fuzzy inference system (FIS), and the selected candidate is verified with a CNN. Three types of databases were tested, taking into account various environmental factors using visible light and FIR cameras. The results showed that the proposed method performs better than the previously reported methods.

  8. Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification

    PubMed Central

    Kang, Jin Kyu; Hong, Hyung Gil; Park, Kang Ryoung

    2017-01-01

    A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting. There are many studies on CNN-based pedestrian detection through the use of far-infrared (FIR) light cameras (i.e., thermal cameras) to address such difficulties. However, when the solar radiation increases and the background temperature reaches the same level as the body temperature, it remains difficult for the FIR light camera to detect pedestrians due to the insignificant difference between the pedestrian and non-pedestrian features within the images. Researchers have been trying to solve this issue by inputting both the visible light and the FIR camera images into the CNN as the input. This, however, takes a longer time to process, and makes the system structure more complex as the CNN needs to process both camera images. This research adaptively selects a more appropriate candidate between two pedestrian images from visible light and FIR cameras based on a fuzzy inference system (FIS), and the selected candidate is verified with a CNN. Three types of databases were tested, taking into account various environmental factors using visible light and FIR cameras. The results showed that the proposed method performs better than the previously reported methods. PMID:28698475

  9. Physical model of a fumarolic system inferred from a high-resolution 3-D Resistivity image of Solfatara volcano

    NASA Astrophysics Data System (ADS)

    Gresse, Marceau; Vandemeulebrouck, Jean; Byrdina, Svetlana; Chiodini, Giovanni; Rinaldi, Antonio Pio; Johnson, Timothy C.; Ricci, Tullio; Petrillo, Zaccaria; Vilardo, Giuseppe; Lebourg, Thomas; Mangiacapra, Annarita

    2017-04-01

    Solfatara crater, located inside the Phlegrean Fields caldera, is showing a significant unrest activity since 10 years with a increase of ground deformation, degassing and heating. Electrical Resistivity Imaging was performed between 2012 and 2016 with the purpose of improving our knowledge of the shallow hydrothermal system. The complete dataset includes 43,432 D-C measurements inverted using the E4D code. This 3-D inversion was compared with the mappings of surface temperature, diffuse soil CO2 flux and self-potential in order to better constrain the interpretation of the observed resistivity structure in terms of lithological contrasts and hydrothermal signatures. For the first time, we highlighted in 3-D the main geological units: Monte Olibano lava dome and Solfatara crypto-dome appear as two relatively resistive bodies (50-100 Ω.m). Furthermore, the resistivity model clearly revealed the contrasting geometry of the hydrothermal circulation in the Solfatara crater. A channel-like conductive structure (7 Ω.m) represents the condensate that flows from the main fumarolic area down to the liquid-dominated Fangaia mud pool. This interpretation is consistent with the negative Self-Potential anomaly and with the surface observations. We imaged at a metric-resolution the two main fumaroles, Bocca Grande and Bocca Nuova, that have the following geochemical characteristics. Bocca Grande vent: 162°C, ˜150 t of CO2 released per day with a mass ratio CO2/H20 = 0.4 and Bocca Nuova vent: 148°C, ˜50 t of CO2 released per day with a mass ratio CO2/H20 = 0.45. The differences between these geochemical characteristics could lead one to believe that they are fed by two distinct sources at depth. On the contrary, our resistivity model shows that the two fumarolic vents are directly connected to a common resistive body (30-50 Ω.m) at a depth of 50 meters. This structure likely represents a single gas reservoir feeding the two fumaroles. Its depth corresponds indeed to a

  10. Sulfur Isotopic Inferences of the Controls on Porewater Sulfate Profiles in the Northern Cascadia Margin Gas Hydrate System

    NASA Astrophysics Data System (ADS)

    Bui, T.; Pohlman, J.; Lapham, L.; Riedel, M.; Wing, B. A.

    2010-12-01

    The flux of methane from gas hydrate bearing seeps in the marine environment is partially mitigated by the anaerobic oxidation of methane coupled with sulfate reduction. Sedimentary porewater sulfate profiles above gas hydrate deposits are frequently used to estimate the efficacy of this important microbial biofilter. However, to differentiate how other processes (e.g., sulfate reduction coupled to organic matter oxidation, sulfide re-oxidation and sulfur disproportionation) affect sulfate profiles, a complete accounting of the sulfur cycle is necessary. To this end, we have obtained the first ever measurements of minor sulfur isotopic ratios (33S/32S, 36S/32S), in conjunction with the more commonly measured 34S -32S ratio, from porewater sulfate above a gas hydrate-bearing seep. Characteristic minor isotopic fractionations, even when major isotopic fractionations are similar in magnitude, help to quantify the contributions of different microbial processes to the overall sulfur cycling in the system. Down to sediment depths of 1.5 to 4 meters, the δ34S values of porewater sulfate generally increased in association with a decrease in sulfate concentrations as would be expected for active sulfate reduction. Of greater interest, covariance between the δ34S values and measured minor isotopic fractionation suggests sulfide reoxidation and sulfur disproportionation are important components of the local sulfur cycle. We hypothesize that sulfide reoxidation is coupled to redox processes involving Fe(III) and Mn(IV) reduction and that the reoxidized forms of sulfur are available for additional methane oxidation. Recognizing that sulfate reduction is only one of several microbial processes controlling sulfate profiles challenges current paradigms for interpreting sulfate profiles and may alter our understanding of methane oxidation at gas hydrate-bearing seeps.

  11. An expert system shell for inferring vegetation characteristics: Changes to the historical cover type database (Task F)

    NASA Technical Reports Server (NTRS)

    1993-01-01

    All the options in the NASA VEGetation Workbench (VEG) make use of a database of historical cover types. This database contains results from experiments by scientists on a wide variety of different cover types. The learning system uses the database to provide positive and negative training examples of classes that enable it to learn distinguishing features between classes of vegetation. All the other VEG options use the database to estimate the error bounds involved in the results obtained when various analysis techniques are applied to the sample of cover type data that is being studied. In the previous version of VEG, the historical cover type database was stored as part of the VEG knowledge base. This database was removed from the knowledge base. It is now stored as a series of flat files that are external to VEG. An interface between VEG and these files was provided. The interface allows the user to select which files of historical data to use. The files are then read, and the data are stored in Knowledge Engineering Environment (KEE) units using the same organization of units as in the previous version of VEG. The interface also allows the user to delete some or all of the historical database units from VEG and load new historical data from a file. This report summarizes the use of the historical cover type database in VEG. It then describes the new interface to the files containing the historical data. It describes minor changes that were made to VEG to enable the externally stored database to be used. Test runs to test the operation of the new interface and also to test the operation of VEG using historical data loaded from external files are described. Task F was completed. A Sun cartridge tape containing the KEE and Common Lisp code for the new interface and the modified version of the VEG knowledge base was delivered to the NASA GSFC technical representative.

  12. Using macroinvertebrate assemblages and multiple stressors to infer urban stream system condition: a case study in the central US

    USGS Publications Warehouse

    Nichols, John W.; Hubbart, Jason A.; Poulton, Barry C.

    2016-01-01

    Characterizing the impacts of hydrologic alterations, pollutants, and habitat degradation on macroinvertebrate species assemblages is of critical value for managers wishing to categorize stream ecosystem condition. A combination of approaches including trait-based metrics and traditional bioassessments provides greater information, particularly in anthropogenic stream ecosystems where traditional approaches can be confounded by variously interacting land use impacts. Macroinvertebrates were collected from two rural and three urban nested study sites in central Missouri, USA during the spring and fall seasons of 2011. Land use responses of conventional taxonomic and trait-based metrics were compared to streamflow indices, physical habitat metrics, and water quality indices. Results show that biotic index was significantly different (p < 0.05) between sites with differences detected in 54 % of trait-based metrics. The most consistent response to urbanization was observed in size metrics, with significantly (p < 0.05) fewer small bodied organisms. Increases in fine streambed sediment, decreased submerged woody rootmats, significantly higher winter Chloride concentrations, and decreased mean suspended sediment particle size in lower urban stream reaches also influenced macroinvertebrate assemblages. Riffle habitats in urban reaches contained 21 % more (p = 0.03) multivoltine organisms, which was positively correlated to the magnitude of peak flows (r2 = 0.91, p = 0.012) suggesting that high flow events may serve as a disturbance in those areas. Results support the use of macroinvertebrate assemblages and multiple stressors to characterize urban stream system condition and highlight the need to better understand the complex interactions of trait-based metrics and anthropogenic aquatic ecosystem stressors.

  13. Evolution and connectivity in the world-wide migration system of the mallard: inferences from mitochondrial DNA.

    PubMed

    Kraus, Robert H S; Zeddeman, Anne; van Hooft, Pim; Sartakov, Dmitry; Soloviev, Sergei A; Ydenberg, Ronald C; Prins, Herbert H T

    2011-11-17

    Main waterfowl migration systems are well understood through ringing activities. However, in mallards (Anas platyrhynchos) ringing studies suggest deviations from general migratory trends and traditions in waterfowl. Furthermore, surprisingly little is known about the population genetic structure of mallards, and studying it may yield insight into the spread of diseases such as Avian Influenza, and in management and conservation of wetlands. The study of evolution of genetic diversity and subsequent partitioning thereof during the last glaciation adds to ongoing discussions on the general evolution of waterfowl populations and flyway evolution. Hypothesised mallard flyways are tested explicitly by analysing mitochondrial mallard DNA from the whole northern hemisphere. Phylogenetic analyses confirm two mitochondrial mallard clades. Genetic differentiation within Eurasia and North-America is low, on a continental scale, but large differences occur between these two land masses (F(ST) = 0.51). Half the genetic variance lies within sampling locations, and a negligible portion between currently recognised waterfowl flyways, within Eurasia and North-America. Analysis of molecular variance (AMOVA) at continent scale, incorporating sampling localities as smallest units, also shows the absence of population structure on the flyway level. Finally, demographic modelling by coalescence simulation proposes a split between Eurasia and North-America 43,000 to 74,000 years ago and strong population growth (~100fold) since then and little migration (not statistically different from zero). Based on this first complete assessment of the mallard's world-wide population genetic structure we confirm that no more than two mtDNA clades exist. Clade A is characteristic for Eurasia, and clade B for North-America although some representatives of clade A are also found in North-America. We explain this pattern by evaluating competing hypotheses and conclude that a complex mix of historical

  14. Evolution and connectivity in the world-wide migration system of the mallard: Inferences from mitochondrial DNA

    PubMed Central

    2011-01-01

    Background Main waterfowl migration systems are well understood through ringing activities. However, in mallards (Anas platyrhynchos) ringing studies suggest deviations from general migratory trends and traditions in waterfowl. Furthermore, surprisingly little is known about the population genetic structure of mallards, and studying it may yield insight into the spread of diseases such as Avian Influenza, and in management and conservation of wetlands. The study of evolution of genetic diversity and subsequent partitioning thereof during the last glaciation adds to ongoing discussions on the general evolution of waterfowl populations and flyway evolution. Hypothesised mallard flyways are tested explicitly by analysing mitochondrial mallard DNA from the whole northern hemisphere. Results Phylogenetic analyses confirm two mitochondrial mallard clades. Genetic differentiation within Eurasia and North-America is low, on a continental scale, but large differences occur between these two land masses (FST = 0.51). Half the genetic variance lies within sampling locations, and a negligible portion between currently recognised waterfowl flyways, within Eurasia and North-America. Analysis of molecular variance (AMOVA) at continent scale, incorporating sampling localities as smallest units, also shows the absence of population structure on the flyway level. Finally, demographic modelling by coalescence simulation proposes a split between Eurasia and North-America 43,000 to 74,000 years ago and strong population growth (~100fold) since then and little migration (not statistically different from zero). Conclusions Based on this first complete assessment of the mallard's world-wide population genetic structure we confirm that no more than two mtDNA clades exist. Clade A is characteristic for Eurasia, and clade B for North-America although some representatives of clade A are also found in North-America. We explain this pattern by evaluating competing hypotheses and conclude that a

  15. Inferring genetic networks from microarray data.

    SciTech Connect

    May, Elebeoba Eni; Davidson, George S.; Martin, Shawn Bryan; Werner-Washburne, Margaret C.; Faulon, Jean-Loup Michel

    2004-06-01

    In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are: (1) inferring the network; (2) estimating the stability of the inferred network; and (3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns. The inference of genetic networks from genome-wide experimental data is an important biological problem which has received much attention. Approaches to this problem have typically included application of clustering algorithms [6]; the use of Boolean networks [12, 1, 10]; the use of Bayesian networks [8, 11]; and the use of continuous models [21, 14, 19]. Overviews of the problem and general approaches to network inference can be found in [4, 3]. Our approach to network inference is similar to earlier methods in that we use both clustering and Boolean network inference. However, we have attempted to extend the process to better serve the end-user, the biologist. In particular, we have incorporated a system to assess the reliability of our network, and we have developed tools which allow interactive visualization of the proposed network.

  16. Linguistic Markers of Inference Generation While Reading.

    PubMed

    Clinton, Virginia; Carlson, Sarah E; Seipel, Ben

    2016-06-01

    Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students ([Formula: see text]) reading narrative texts were hand-coded for inferences. These data were also processed with a computer text analysis tool, Linguistic Inquiry and Word Count, for percentages of word use in the following categories: cognitive mechanism words, nonfluencies, and nine types of function words. Findings indicate that cognitive mechanisms were an independent, positive predictor of connections to background knowledge (i.e., elaborative inference generation) and nonfluencies were an independent, negative predictor of connections within the text (i.e., bridging inference generation). Function words did not provide unique variance towards predicting inference generation. These findings are discussed in the context of a cognitive reflection model and the differences between bridging and elaborative inference generation. In addition, potential practical implications for intelligent tutoring systems and computer-based methods of inference identification are presented.

  17. Long Term Variability of the Canary Current Upwelling System inferred from Fine Scale Analysis of Satellite-derived SST

    NASA Astrophysics Data System (ADS)

    Relvas, P.; Luis, J. M.; Silva, P. L.; Santos, A. M.

    2011-12-01

    Satellite-derived sea surface temperature (SST) trends are built at the pixel scale to investigate long term changes in oceanic patterns. We consider that the SST time-series already available is long enough to attempt the analysis at the decadal scale. The analysis extends from 1982 to 2009 and is applied to the eastern boundary of the North Atlantic, from 10 to 45 N extending until 30 W, covering the Canary Current Upwelling System. Monthly mean SST data from the Advanced Very High Resolution Radiometer (AVHRR) on board NOAA series satellites, with a spatial resolution of 4x4 km, were provided by the NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory. SST estimates are derived from the Pathfinder Version 5 algorithms. Whenever possible the time series are limited to the night-time passes to avoid any solar heating effect. Only high quality SST values with a flag assignment of 6 and 7 (Kilpatrick et al., 2001) are used. Using only the highest quality values creates a data processing problem that is posed by the voids left on the temperature grids on the node positions corresponding to the rejected values. The case is further complicated by the fact that the voids, originated by unfavourable weather conditions of strong cloud cover and coastal fogs, most intense during strong upwelling events, are located on variable positions on the grids depending on the month the grid refers to. This is particular evident on the winter months where large areas of the ocean did not have any reliable measure, even on a monthly average. We apply several procedures to fill these data gaps that guarantee that annual and seasonal averages are not biased towards summer temperatures. To investigate the spatial variability of the long term SST trend a robust linear fit was applied to each individual pixel, crossing along the time the same 4x4 km pixel in all the processed monthly mean AVHRR SST images from 1982 until 2009. Fields of

  18. Active fault segments as potential earthquake sources: Inferences from integrated geophysical mapping of the Magadi fault system, southern Kenya Rift

    NASA Astrophysics Data System (ADS)

    Kuria, Z. N.; Woldai, T.; van der Meer, F. D.; Barongo, J. O.

    2010-06-01

    uplifted, heavily fractured and deformed basin to the north (highly disturbed magnetic signatures) characteristic of on going active rifting; and a refined architecture of the asymmetry graben to the south with an intrarift horst, whose western graben is 4 km deep and eastern graben is much deeper (9 km), with a zone of significant break in magnetic signatures at that depth, interpreted as source of the hot springs south of Lake Magadi (a location confirmed near surface by ground magnetic and resistivity data sets). The magnetic sources to the north are shallow at 15 km depth compared to 22 km to the south. The loss of magnetism to the north is probably due to increased heat as a result of magmatic intrusion supporting active rifting model. Conclusively, the integrated approach employed in this research confirms that fault system delineated to the north is actively deforming under E-W normal extension and is a potential earthquake source probably related to magmatic intrusion, while the presence of fluids within the south fault zone reduce intensity of faulting activity and explains lack of earthquakes in a continental rift setting.

  19. The Bayes Inference Engine

    SciTech Connect

    Hanson, K.M.; Cunningham, G.S.

    1996-04-01

    The authors are developing a computer application, called the Bayes Inference Engine, to provide the means to make inferences about models of physical reality within a Bayesian framework. The construction of complex nonlinear models is achieved by a fully object-oriented design. The models are represented by a data-flow diagram that may be manipulated by the analyst through a graphical programming environment. Maximum a posteriori solutions are achieved using a general, gradient-based optimization algorithm. The application incorporates a new technique of estimating and visualizing the uncertainties in specific aspects of the model.

  20. Cortical circuits for perceptual inference.

    PubMed

    Friston, Karl; Kiebel, Stefan

    2009-10-01

    This paper assumes that cortical circuits have evolved to enable inference about the causes of sensory input received by the brain. This provides a principled specification of what neural circuits have to achieve. Here, we attempt to address how the brain makes inferences by casting inference as an optimisation problem. We look at how the ensuing recognition dynamics could be supported by directed connections and message-passing among neuronal populations, given our knowledge of intrinsic and extrinsic neuronal connections. We assume that the brain models the world as a dynamic system, which imposes causal structure on the sensorium. Perception is equated with the optimisation or inversion of this internal model, to explain sensory input. Given a model of how sensory data are generated, we use a generic variational approach to model inversion to furnish equations that prescribe recognition; i.e., the dynamics of neuronal activity that represents the causes of sensory input. Here, we focus on a model whose hierarchical and dynamical structure enables simulated brains to recognise and predict sequences of sensory states. We first review these models and their inversion under a variational free-energy formulation. We then show that the brain has the necessary infrastructure to implement this inversion and present stimulations using synthetic birds that generate and recognise birdsongs.

  1. Prediction of effect of natural antioxidant compounds on hazelnut oil oxidation by adaptive neuro-fuzzy inference system and artificial neural network.

    PubMed

    Yalcin, Hasan; Ozturk, Ismet; Karaman, Safa; Kisi, Ozgur; Sagdic, Osman; Kayacier, Ahmed

    2011-05-01

    In this study, natural compounds including gallic acid, ellagic acid, quercetin, β-carotene, and retinol were used as antioxidant agents in order to prevent and decrease oxidation in hazelnut oil. Quercetin showed the strongest antioxidative effect among the antioxidative agents, during storage. The accuracy of adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) models was studied to estimate the oil samples' peroxide value (PV), free fatty acid (FFA), and iodine values (IV). The root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R(2)) statistics were used to evaluate the models' accuracy. Comparison of the models showed that the ANFIS model performed better than the ANN and multiple linear regressions (MLR) models for estimating the PV, FFA, and IV. The values of R(2) and RMSE were found to be 0.9966 and 2.51, 0.6269 and 88.55, 0.5120 and 101.8 for the ANFIS, ANN, and MLR models for PV in testing period, respectively. The MLR was found to be insufficient for estimating various properties of the oil samples. © 2011 Institute of Food Technologists®

  2. Comparison of adaptive neuro-fuzzy inference system and artificial neural networks for estimation of oxidation parameters of sunflower oil added with some natural byproduct extracts.

    PubMed

    Karaman, Safa; Ozturk, Ismet; Yalcin, Hasan; Kayacier, Ahmed; Sagdic, Osman

    2012-01-15

    Apple pomace, orange peel and potato peel, which have important antioxidative compounds in their structures, are byproducts obtained from fruit or vegetable processing. Use of vegetable extracts is popular and a common technique in the preservation of vegetable oils. Utilization of apple pomace, orange peel and potato peel extracts as natural antioxidant agents in refined sunflower oil during storage in order to reduce or retard oxidation was investigated. All byproduct extracts were added at 3000 ppm to sunflower oil and different nonlinear models were constructed for the estimation of oxidation parameters. Peroxide values of sunflower oil samples containing different natural extracts were found to be lower compared to control sample. Adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANN) were used for the construction of models that could predict the oxidation parameters and were compared to multiple linear regression (MLR) for the determination of the best model with high accuracy. It was shown that the ANFIS model with high coefficient of determination (R(2) = 0.999) performed better compared to ANN (R(2) = 0.899) and MLR (R(2) = 0.636) for the prediction of oxidation parameters Incorporation of different natural byproduct extracts into sunflower oil provided an important retardation in oxidation during storage. Effective predictive models were constructed for the estimation of oxidation parameters using ANFIS and ANN modeling techniques. These models can be used to predict oxidative parameter values. Copyright © 2011 Society of Chemical Industry.

  3. An exploratory investigation of an adaptive neuro fuzzy inference system (ANFIS) for estimating hydrometeors from TRMM/TMI in synergy with TRMM/PR

    NASA Astrophysics Data System (ADS)

    Islam, Tanvir; Srivastava, Prashant K.; Rico-Ramirez, Miguel A.; Dai, Qiang; Han, Dawei; Gupta, Manika

    2014-08-01

    The authors have investigated an adaptive neuro fuzzy inference system (ANFIS) for the estimation of hydrometeors from the TRMM microwave imager (TMI). The proposed algorithm, named as Hydro-Rain algorithm, is developed in synergy with the TRMM precipitation radar (PR) observed hydrometeor information. The method retrieves rain rates by exploiting the synergistic relations between the TMI and PR observations in twofold steps. First, the fundamental hydrometeor parameters, liquid water path (LWP) and ice water path (IWP), are estimated from the TMI brightness temperatures. Next, the rain rates are estimated from the retrieved hydrometeor parameters (LWP and IWP). A comparison of the hydrometeor retrievals by the Hydro-Rain algorithm is done with the TRMM PR 2A25 and GPROF 2A12 algorithms. The results reveal that the Hydro-Rain algorithm has good skills in estimating hydrometeor paths LWP and IWP, as well as surface rain rate. An examination of the Hydro-Rain algorithm is also conducted on a super typhoon case, in which the Hydro-Rain has shown very good performance in reproducing the typhoon field. Nevertheless, the passive microwave based estimate of hydrometeors appears to suffer in high rain rate regimes, and as the rain rate increases, the discrepancies with hydrometeor estimates tend to increase as well.

  4. Genetic algorithm-artificial neural network and adaptive neuro-fuzzy inference system modeling of antibacterial activity of annatto dye on Salmonella enteritidis.

    PubMed

    Yolmeh, Mahmoud; Habibi Najafi, Mohammad B; Salehi, Fakhreddin

    2014-01-01

    Annatto is commonly used as a coloring agent in the food industry and has antimicrobial and antioxidant properties. In this study, genetic algorithm-artificial neural network (GA-ANN) and adaptive neuro-fuzzy inference system (ANFIS) models were used to predict the effect of annatto dye on Salmonella enteritidis in mayonnaise. The GA-ANN and ANFIS were fed with 3 inputs of annatto dye concentration (0, 0.1, 0.2 and 0.4%), storage temperature (4 and 25°C) and storage time (1-20 days) for prediction of S. enteritidis population. Both models were trained with experimental data. The results showed that the annatto dye was able to reduce of S. enteritidis and its effect was stronger at 25°C than 4°C. The developed GA-ANN, which included 8 hidden neurons, could predict S. enteritidis population with correlation coefficient of 0.999. The overall agreement between ANFIS predictions and experimental data was also very good (r=0.998). Sensitivity analysis results showed that storage temperature was the most sensitive factor for prediction of S. enteritidis population.

  5. Design of an expert system based on neuro-fuzzy inference analyzer for on-line microstructural characterization using magnetic NDT method

    NASA Astrophysics Data System (ADS)

    Ghanei, S.; Vafaeenezhad, H.; Kashefi, M.; Eivani, A. R.; Mazinani, M.

    2015-04-01

    Tracing microstructural evolution has a significant importance and priority in manufacturing lines of dual-phase steels. In this paper, an artificial intelligence method is presented for on-line microstructural characterization of dual-phase steels. A new method for microstructure characterization based on the theory of magnetic Barkhausen noise nondestructive testing method is introduced using adaptive neuro-fuzzy inference system (ANFIS). In order to predict the accurate martensite volume fraction of dual-phase steels while eliminating the effect and interference of frequency on the magnetic Barkhausen noise outputs, the magnetic responses were fed into the ANFIS structure in terms of position, height and width of the Barkhausen profiles. The results showed that ANFIS approach has the potential to detect and characterize microstructural evolution while the considerable effect of the frequency on magnetic outputs is overlooked. In fact implementing multiple outputs simultaneously enables ANFIS to approach to the accurate results using only height, position and width of the magnetic Barkhausen noise peaks without knowing the value of the used frequency.

  6. Adaptive Neuro-Fuzzy Inference system analysis on adsorption studies of Reactive Red 198 from aqueous solution by SBA-15/CTAB composite

    NASA Astrophysics Data System (ADS)

    Aghajani, Khadijeh; Tayebi, Habib-Allah

    2017-01-01

    In this study, the Mesoporous material SBA-15 were synthesized and then, the surface was modified by the surfactant Cetyltrimethylammoniumbromide (CTAB). Finally, the obtained adsorbent was used in order to remove Reactive Red 198 (RR 198) from aqueous solution. Transmission electron microscope (TEM), Fourier transform infra-red spectroscopy (FTIR), Thermogravimetric analysis (TGA), X-ray diffraction (XRD), and BET were utilized for the purpose of examining the structural characteristics of obtained adsorbent. Parameters affecting the removal of RR 198 such as pH, the amount of adsorbent, and contact time were investigated at various temperatures and were also optimized. The obtained optimized condition is as follows: pH = 2, time = 60 min and adsorbent dose = 1 g/l. Moreover, a predictive model based on ANFIS for predicting the adsorption amount according to the input variables is presented. The presented model can be used for predicting the adsorption rate based on the input variables include temperature, pH, time, dosage, concentration. The error between actual and approximated output confirm the high accuracy of the proposed model in the prediction process. This fact results in cost reduction because prediction can be done without resorting to costly experimental efforts. SBA-15, CTAB, Reactive Red 198, adsorption study, Adaptive Neuro-Fuzzy Inference systems (ANFIS).

  7. Flash propagation and inferred charge structure relative to radar-observed ice alignment signatures in a small Florida mesoscale convective system

    NASA Astrophysics Data System (ADS)

    Biggerstaff, Michael I.; Zounes, Zackery; Addison Alford, A.; Carrie, Gordon D.; Pilkey, John T.; Uman, Martin A.; Jordan, Douglas M.

    2017-08-01

    A series of vertical cross sections taken through a small mesoscale convective system observed over Florida by the dual-polarimetric SMART radar were combined with VHF radiation source locations from a lightning mapping array (LMA) to examine the lightning channel propagation paths relative to the radar-observed ice alignment signatures associated with regions of negative specific differential phase (KDP). Additionally, charge layers inferred from analysis of LMA sources were related to the ice alignment signature. It was found that intracloud flashes initiated near the upper zero-KDP boundary surrounding the negative KDP region. The zero-KDP boundary also delineated the propagation path of the lightning channel with the negative leaders following the upper boundary and positive leaders following the lower boundary. Very few LMA sources were found in the negative KDP region. We conclude that rapid dual-polarimetric radar observations can diagnose strong electric fields and may help identify surrounding regions of charge.

  8. Use of an adaptive neuro-fuzzy inference system to obtain the correspondence among balance, gait, and depression for Parkinson's disease

    NASA Astrophysics Data System (ADS)

    Woo, Youngkeun; Lee, Juwon; Hwang, Sujin; Hong, Cheol Pyo

    2013-03-01

    The purpose of this study was to investigate the associations between gait performance, postural stability, and depression in patients with Parkinson's disease (PD) by using an adaptive neuro-fuzzy inference system (ANFIS). Twenty-two idiopathic PD patients were assessed during outpatient physical therapy by using three clinical tests: the Berg balance scale (BBS), Dynamic gait index (DGI), and Geriatric depression scale (GDS). Scores were determined from clinical observation and patient interviews, and associations among gait performance, postural stability, and depression in this PD population were evaluated. The DGI showed significant positive correlation with the BBS scores, and negative correlation with the GDS score. We assessed the relationship between the BBS score and the DGI results by using a multiple regression analysis. In this case, the GDS score was not significantly associated with the DGI, but the BBS and DGI results were. Strikingly, the ANFIS-estimated value of the DGI, based on the BBS and the GDS scores, significantly correlated with the walking ability determined by using the DGI in patients with Parkinson's disease. These findings suggest that the ANFIS techniques effectively reflect and explain the multidirectional phenomena or conditions of gait performance in patients with PD.

  9. Inference as Prediction

    ERIC Educational Resources Information Center

    Watson, Jane

    2007-01-01

    Inference, or decision making, is seen in curriculum documents as the final step in a statistical investigation. For a formal statistical enquiry this may be associated with sophisticated tests involving probability distributions. For young students without the mathematical background to perform such tests, it is still possible to draw informal…

  10. Effects of parasite pressure on parasite mortality and reproductive output in a rodent-flea system: inferring host defense trade-offs.

    PubMed

    Warburton, Elizabeth M; Kam, Michael; Bar-Shira, Enav; Friedman, Aharon; Khokhlova, Irina S; Koren, Lee; Asfur, Mustafa; Geffen, Eli; Kiefer, Daniel; Krasnov, Boris R; Degen, A Allan

    2016-09-01

    Evaluating host resistance via parasite fitness helps place host-parasite relationships within evolutionary and ecological contexts; however, few studies consider both these processes simultaneously. We investigated how different levels of parasite pressure affect parasite mortality and reproductive success in relationship to host defense efforts, using the rodent Gerbillus nanus and the flea Xenopsylla conformis as a host-parasite system. Fifteen immune-naïve male rodents were infested with 20, 50, or 100 fleas for four weeks. During this time number of new imagoes produced per adult flea (our flea reproductive output metric), flea mortality, and change in circulating anti-flea immunoglobulin G (our measure of adaptive immune defense) were monitored. Three hypotheses guided this work: (1) increasing parasite pressure would heighten host defenses; (2) parasite mortality would increase and parasite reproductive output would decrease with increasing investment in host defense; and (3) hosts under high parasite pressure could invest in behavioral and/or immune responses. We predicted that at high infestation levels (a) parasite mortality would increase; (b) flea reproductive output per individual would decrease; and (c) host circulating anti-flea antibody levels would increase. The hypotheses were partially supported. Flea mortality significantly increased and flea reproductive output significantly decreased as flea pressure increased. Host adaptive immune defense did not significantly change with increasing flea pressure. Therefore, we inferred that investment in host behavioral defense, either alone or in combination with density-dependent effects, may be more efficient at increasing flea mortality and decreasing flea reproductive output than antibody production during initial infestation in this system.

  11. Parallel optical fuzzy logic inference using improved fuzzy associative memories

    NASA Astrophysics Data System (ADS)

    Zhang, ShuQun; Karim, Mohammad A.

    1999-10-01

    A new optoelectronic fuzzy inference system is proposed for processing a large number of fuzzy rules in parallel. The proposed system using spatial light modulator implements various membership functions as well as max-min inference. It has the features of easy implementation and large data processing capability. The membership function decomposition method in the improved fuzzy associative memory is used to save both space bandwidth and accommodate multiple-input fuzzy inference.

  12. Adaptive neuro-fuzzy inference system model for adsorption of 1,3,4-thiadiazole-2,5-dithiol onto gold nanoparticales-activated carbon.

    PubMed

    Ghaedi, M; Hosaininia, R; Ghaedi, A M; Vafaei, A; Taghizadeh, F

    2014-10-15

    In this research, a novel adsorbent gold nanoparticle loaded on activated carbon (Au-NP-AC) was synthesized by ultrasound energy as a low cost routing protocol. Subsequently, this novel material characterization and identification followed by different techniques such as scanning electron microscope(SEM), Brunauer-Emmett-Teller(BET) and transmission electron microscopy (TEM) analysis. Unique properties such as high BET surface area (>1229.55m(2)/g) and low pore size (<22.46Å) and average particle size lower than 48.8Å in addition to high reactive atoms and the presence of various functional groups make it possible for efficient removal of 1,3,4-thiadiazole-2,5-dithiol (TDDT). Generally, the influence of variables, including the amount of adsorbent, initial pollutant concentration, contact time on pollutants removal percentage has great effect on the removal percentage that their influence was optimized. The optimum parameters for adsorption of 1,3,4-thiadiazole-2, 5-dithiol onto gold nanoparticales-activated carbon were 0.02g adsorbent mass, 10mgL(-1) initial 1,3,4-thiadiazole-2,5-dithiol concentration, 30min contact time and pH 7. The Adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models, have been applied for prediction of removal of 1,3,4-thiadiazole-2,5-dithiol using gold nanoparticales-activated carbon (Au-NP-AC) in a batch study. The input data are included adsorbent dosage (g), contact time (min) and pollutant concentration (mg/l). The coefficient of determination (R(2)) and mean squared error (MSE) for the training data set of optimal ANFIS model were achieved to be 0.9951 and 0.00017, respectively. These results show that ANFIS model is capable of predicting adsorption of 1,3,4-thiadiazole-2,5-dithiol using Au-NP-AC with high accuracy in an easy, rapid and cost effective way.

  13. Adaptive neuro-fuzzy inference system model for adsorption of 1,3,4-thiadiazole-2,5-dithiol onto gold nanoparticales-activated carbon

    NASA Astrophysics Data System (ADS)

    Ghaedi, M.; Hosaininia, R.; Ghaedi, A. M.; Vafaei, A.; Taghizadeh, F.

    2014-10-01

    In this research, a novel adsorbent gold nanoparticle loaded on activated carbon (Au-NP-AC) was synthesized by ultrasound energy as a low cost routing protocol. Subsequently, this novel material characterization and identification followed by different techniques such as scanning electron microscope (SEM), Brunauer-Emmett-Teller (BET) and transmission electron microscopy (TEM) analysis. Unique properties such as high BET surface area (>1229.55 m2/g) and low pore size (<22.46 Å) and average particle size lower than 48.8 Å in addition to high reactive atoms and the presence of various functional groups make it possible for efficient removal of 1,3,4-thiadiazole-2,5-dithiol (TDDT). Generally, the influence of variables, including the amount of adsorbent, initial pollutant concentration, contact time on pollutants removal percentage has great effect on the removal percentage that their influence was optimized. The optimum parameters for adsorption of 1,3,4-thiadiazole-2, 5-dithiol onto gold nanoparticales-activated carbon were 0.02 g adsorbent mass, 10 mg L-1 initial 1,3,4-thiadiazole-2,5-dithiol concentration, 30 min contact time and pH 7. The Adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models, have been applied for prediction of removal of 1,3,4-thiadiazole-2,5-dithiol using gold nanoparticales-activated carbon (Au-NP-AC) in a batch study. The input data are included adsorbent dosage (g), contact time (min) and pollutant concentration (mg/l). The coefficient of determination (R2) and mean squared error (MSE) for the training data set of optimal ANFIS model were achieved to be 0.9951 and 0.00017, respectively. These results show that ANFIS model is capable of predicting adsorption of 1,3,4-thiadiazole-2,5-dithiol using Au-NP-AC with high accuracy in an easy, rapid and cost effective way.

  14. Prediction of oxidation parameters of purified Kilka fish oil including gallic acid and methyl gallate by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network.

    PubMed

    Asnaashari, Maryam; Farhoosh, Reza; Farahmandfar, Reza

    2016-10-01

    As a result of concerns regarding possible health hazards of synthetic antioxidants, gallic acid and methyl gallate may be introduced as natural antioxidants to improve oxidative stability of marine oil. Since conventional modelling could not predict the oxidative parameters precisely, artificial neural network (ANN) and neuro-fuzzy inference system (ANFIS) modelling with three inputs, including type of antioxidant (gallic acid and methyl gallate), temperature (35, 45 and 55 °C) and concentration (0, 200, 400, 800 and 1600 mg L(-1) ) and four outputs containing induction period (IP), slope of initial stage of oxidation curve (k1 ) and slope of propagation stage of oxidation curve (k2 ) and peroxide value at the IP (PVIP ) were performed to predict the oxidation parameters of Kilka oil triacylglycerols and were compared to multiple linear regression (MLR). The results showed ANFIS was the best model with high coefficient of determination (R(2)  = 0.99, 0.99, 0.92 and 0.77 for IP, k1 , k2 and PVIP , respectively). So, the RMSE and MAE values for IP were 7.49 and 4.92 in ANFIS model. However, they were to be 15.95 and 10.88 and 34.14 and 3.60 for the best MLP structure and MLR, respectively. So, MLR showed the minimum accuracy among the constructed models. Sensitivity analysis based on the ANFIS model suggested a high sensitivity of oxidation parameters, particularly the induction period on concentrations of gallic acid and methyl gallate due to their high antioxidant activity to retard oil oxidation and enhanced Kilka oil shelf life. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  15. Adaptive neuro-fuzzy inference system (ANFIS) to predict CI engine parameters fueled with nano-particles additive to diesel fuel

    NASA Astrophysics Data System (ADS)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For ANFIS modelling, Gaussian curve membership function (gaussmf) and 200 training epochs (iteration) were found to be optimum choices for training process. The results demonstrate that ANFIS is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust emissions significantly.

  16. ARPOP: an appetitive reward-based pseudo-outer-product neural fuzzy inference system inspired from the operant conditioning of feeding behavior in Aplysia.

    PubMed

    Cheu, Eng Yeow; Quek, Chai; Ng, See Kiong

    2012-02-01

    Appetitive operant conditioning in Aplysia for feeding behavior via the electrical stimulation of the esophageal nerve contingently reinforces each spontaneous bite during the feeding process. This results in the acquisition of operant memory by the contingently reinforced animals. Analysis of the cellular and molecular mechanisms of the feeding motor circuitry revealed that activity-dependent neuronal modulation occurs at the interneurons that mediate feeding behaviors. This provides evidence that interneurons are possible loci of plasticity and constitute another mechanism for memory storage in addition to memory storage attributed to activity-dependent synaptic plasticity. In this paper, an associative ambiguity correction-based neuro-fuzzy network, called appetitive reward-based pseudo-outer-product-compositional rule of inference [ARPOP-CRI(S)], is trained based on an appetitive reward-based learning algorithm which is biologically inspired by the appetitive operant conditioning of the feeding behavior in Aplysia. A variant of the Hebbian learning rule called Hebbian concomitant learning is proposed as the building block in the neuro-fuzzy network learning algorithm. The proposed algorithm possesses the distinguishing features of the sequential learning algorithm. In addition, the proposed ARPOP-CRI(S) neuro-fuzzy system encodes fuzzy knowledge in the form of linguistic rules that satisfies the semantic criteria for low-level fuzzy model interpretability. ARPOP-CRI(S) is evaluated and compared against other modeling techniques using benchmark time-series datasets. Experimental results are encouraging and show that ARPOP-CRI(S) is a viable modeling technique for time-variant problem domains.

  17. Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro-Fuzzy Inference System and Map Correlation Method: A Case Study from Turkey

    NASA Astrophysics Data System (ADS)

    Kentel, E.; Dogulu, N.

    2015-12-01

    In Turkey the experience and data required for a hydrological model setup is limited and very often not available. Moreover there are many ungauged catchments where there are also many planned projects aimed at utilization of water resources including development of existing hydropower potential. This situation makes runoff prediction at locations with lack of data and ungauged locations where small hydropower plants, reservoirs, etc. are planned an increasingly significant challenge and concern in the country. Flow duration curves have many practical applications in hydrology and integrated water resources management. Estimation of flood duration curve (FDC) at ungauged locations is essential, particularly for hydropower feasibility studies and selection of the installed capacities. In this study, we test and compare the performances of two methods for estimating FDCs in the Western Black Sea catchment, Turkey: (i) FDC based on Map Correlation Method (MCM) flow estimates. MCM is a recently proposed method (Archfield and Vogel, 2010) which uses geospatial information to estimate flow. Flow measurements of stream gauging stations nearby the ungauged location are the only data requirement for this method. This fact makes MCM very attractive for flow estimation in Turkey, (ii) Adaptive Neuro-Fuzzy Inference System (ANFIS) is a data-driven method which is used to relate FDC to a number of variables representing catchment and climate characteristics. However, it`s ease of implementation makes it very useful for practical purposes. Both methods use easily collectable data and are computationally efficient. Comparison of the results is realized based on two different measures: the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE) value. Ref: Archfield, S. A., and R. M. Vogel (2010), Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments, Water Resour. Res., 46, W10513, doi:10.1029/2009WR008481.

  18. Water quality analysis in rivers with non-parametric probability distributions and fuzzy inference systems: application to the Cauca River, Colombia.

    PubMed

    Ocampo-Duque, William; Osorio, Carolina; Piamba, Christian; Schuhmacher, Marta; Domingo, José L

    2013-02-01

    The integration of water quality monitoring variables is essential in environmental decision making. Nowadays, advanced techniques to manage subjectivity, imprecision, uncertainty, vagueness, and variability are required in such complex evaluation process. We here propose a probabilistic fuzzy hybrid model to assess river water quality. Fuzzy logic reasoning has been used to compute a water quality integrative index. By applying a Monte Carlo technique, based on non-parametric probability distributions, the randomness of model inputs was estimated. Annual histograms of nine water quality variables were built with monitoring data systematically collected in the Colombian Cauca River, and probability density estimations using the kernel smoothing method were applied to fit data. Several years were assessed, and river sectors upstream and downstream the city of Santiago de Cali, a big city with basic wastewater treatment and high industrial activity, were analyzed. The probabilistic fuzzy water quality index was able to explain the reduction in water quality, as the river receives a larger number of agriculture, domestic, and industrial effluents. The results of the hybrid model were compared to traditional water quality indexes. The main advantage of the proposed method is that it considers flexible boundaries between the linguistic qualifiers used to define the water status, being the belongingness of water quality to the diverse output fuzzy sets or classes provided with percentiles and histograms, which allows classify better the real water condition. The results of this study show that fuzzy inference systems integrated to stochastic non-parametric techniques may be used as complementary tools in water quality indexing methodologies.

  19. Inferring Microbial Fitness Landscapes

    DTIC Science & Technology

    2016-02-25

    the foundational work on the mathematical analysis of these diffusion equations , and established the needed connections with stochastic differential ...SECURITY CLASSIFICATION OF: Microbes and viruses evolve. Their evolution is often more rapid and of greater practical importance than our own evolution ...infer from data the determinants of microbial evolution with sufficient resolution that we can quantify 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND

  20. GOSAT CO2 Inversion Inter-comparison Experiment Phase-II and multi-year global fluxes inferred from the NIES flux inversion system

    NASA Astrophysics Data System (ADS)

    Takagi, H.; Houweling, S.; Yokota, T.; Maksyutov, S. S.

    2016-12-01

    The atmospheric inversion technique infers surface fluxes of traces gases from atmospheric measurements and is used to gain insight into how anthropogenic activities modify the stocks and flows of carbon over the globe. To gain further process-level understanding of these modifications, it is important to evaluate, understand, and subsequently reduce the uncertainties in the flux estimation process. To assess the role of transport model uncertainties, the TransCom inversion inter-comparison studies were held in the late 1990s. More recently, after the advent of satellites dedicated to GHG monitoring, the GOSAT inversion inter-comparison (Phase-I) was carried out. The latter evaluated the full uncertainty of GOSAT-based CO2 flux estimation by allowing the study participants to use the inversion system and GOSAT column-mean CO2 (XCO2) retrieval dataset of their choice. The second phase of the GOSAT inversion inter-comparison explores differences between existing inversion systems and evaluates their contribution to the uncertainty in the estimated CO2 fluxes. For this purpose, the participants are asked to use a common input dataset that consists of a single GOSAT XCO2 retrieval dataset and an a priori flux dataset. The second phase study takes advantage of a five-year-long analysis period (2009-2014) during which GOSAT XCO2 retrievals are continually available, to assess the robustness of inversion-derived estimates of the impact of major weather anomalies (heat waves, droughts, and heavy precipitations, etc.) on carbon fluxes. Here, the latest on this study is reported. As an example of the results that will be generated in this experiment, we will present multi-year GOSAT CO2 fluxes from the NIES CO2 flux inversion system. The inversion uses NIES GOSAT SWIR Level 2 and ACOS B3.5 XCO2 retrievals covering the period June 2009 to early 2014 and ObsPack GVplus surface CO2 data. We evaluate how the CO2fluxes vary with respect to the handling of the observations

  1. Active inference and learning.

    PubMed

    Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O'Doherty, John; Pezzulo, Giovanni

    2016-09-01

    This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity.

  2. Network inference in the nonequilibrium steady state

    NASA Astrophysics Data System (ADS)

    Dettmer, Simon L.; Nguyen, H. Chau; Berg, Johannes

    2016-11-01

    Nonequilibrium systems lack an explicit characterization of their steady state like the Boltzmann distribution for equilibrium systems. This has drastic consequences for the inference of the parameters of a model when its dynamics lacks detailed balance. Such nonequilibrium systems occur naturally in applications like neural networks and gene regulatory networks. Here, we focus on the paradigmatic asymmetric Ising model and show that we can learn its parameters from independent samples of the nonequilibrium steady state. We present both an exact inference algorithm and a computationally more efficient, approximate algorithm for weak interactions based on a systematic expansion around mean-field theory. Obtaining expressions for magnetizations and two- and three-point spin correlations, we establish that these observables are sufficient to infer the model parameters. Further, we discuss the symmetries characterizing the different orders of the expansion around the mean field and show how different types of dynamics can be distinguished on the basis of samples from the nonequilibrium steady state.

  3. Decision generation tools and Bayesian inference

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas

    2014-05-01

    Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.

  4. GAMBIT: Global And Modular BSM Inference Tool

    NASA Astrophysics Data System (ADS)

    GAMBIT Collaboration; Athron, Peter; Balazs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrzä Szcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Dickinson, Hugh; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Lundberg, Johan; McKay, James; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje Raklev, Are; Ripken, Joachim; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Seo, Seon-Hee; Serra, Nicola; Weniger, Christoph; White, Martin; Wild, Sebastian

    2017-08-01

    GAMBIT (Global And Modular BSM Inference Tool) performs statistical global fits of generic physics models using a wide range of particle physics and astrophysics data. Modules provide native simulations of collider and astrophysics experiments, a flexible system for interfacing external codes (the backend system), a fully featured statistical and parameter scanning framework, and additional tools for implementing and using hierarchical models.

  5. Modeling of stage-discharge relationship for Gharraf River, southern Iraq using backpropagation artificial neural networks, M5 decision trees, and Takagi-Sugeno inference system technique: a comparative study

    NASA Astrophysics Data System (ADS)

    Al-Abadi, Alaa M.

    2016-11-01

    The potential of using three different data-driven techniques namely, multilayer perceptron with backpropagation artificial neural network (MLP), M5 decision tree model, and Takagi-Sugeno (TS) inference system for mimic stage-discharge relationship at Gharraf River system, southern Iraq has been investigated and discussed in this study. The study used the available stage and discharge data for predicting discharge using different combinations of stage, antecedent stages, and antecedent discharge values. The models' results were compared using root mean squared error (RMSE) and coefficient of determination ( R 2) error statistics. The results of the comparison in testing stage reveal that M5 and Takagi-Sugeno techniques have certain advantages for setting up stage-discharge than multilayer perceptron artificial neural network. Although the performance of TS inference system was very close to that for M5 model in terms of R 2, the M5 method has the lowest RMSE (8.10 m3/s). The study implies that both M5 and TS inference systems are promising tool for identifying stage-discharge relationship in the study area.

  6. Towards Context Sensitive Information Inference.

    ERIC Educational Resources Information Center

    Song, D.; Bruza, P. D.

    2003-01-01

    Discusses information inference from a psychologistic stance and proposes an information inference mechanism that makes inferences via computations of information flow through an approximation of a conceptual space. Highlights include cognitive economics of information processing; context sensitivity; and query models for information retrieval.…

  7. Multimodel inference and adaptive management

    USGS Publications Warehouse

    Rehme, S.E.; Powell, L.A.; Allen, C.R.

    2011-01-01

    Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

  8. Validate High Stakes Inferences by Designing Good Experiments, Not Audit Items: A Comment on "Self-Monitoring Assessments Educational Accountability Systems"

    ERIC Educational Resources Information Center

    Briggs, Derek C.

    2010-01-01

    The use of large-scale assessments for making high stakes inferences about students and the schools in which they are situated is premised on the assumption that tests are sensitive to good instruction. An increase in the quality of classroom instruction should cause, on the average, an increase in test scores. In work with a number of colleagues…

  9. Validate High Stakes Inferences by Designing Good Experiments, Not Audit Items: A Comment on "Self-Monitoring Assessments Educational Accountability Systems"

    ERIC Educational Resources Information Center

    Briggs, Derek C.

    2010-01-01

    The use of large-scale assessments for making high stakes inferences about students and the schools in which they are situated is premised on the assumption that tests are sensitive to good instruction. An increase in the quality of classroom instruction should cause, on the average, an increase in test scores. In work with a number of colleagues…

  10. Visual Inference Programming

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter

    2002-01-01

    The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

  11. Visual Inference Programming

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter

    2002-01-01

    The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

  12. Nanotechnology and statistical inference

    NASA Astrophysics Data System (ADS)

    Vesely, Sara; Vesely, Leonardo; Vesely, Alessandro

    2017-08-01

    We discuss some problems that arise when applying statistical inference to data with the aim of disclosing new func-tionalities. A predictive model analyzes the data taken from experiments on a specific material to assess the likelihood that another product, with similar structure and properties, will exhibit the same functionality. It doesn't have much predictive power if vari-ability occurs as a consequence of a specific, non-linear behavior. We exemplify our discussion on some experiments with biased dice.

  13. Quantum Inference on Bayesian Networks

    NASA Astrophysics Data System (ADS)

    Yoder, Theodore; Low, Guang Hao; Chuang, Isaac

    2014-03-01

    Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.

  14. Symbolic inference of xenobiotic metabolism.

    PubMed

    McShan, D C; Updadhayaya, M; Shah, I

    2004-01-01

    We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds.

  15. SYMBOLIC INFERENCE OF XENOBIOTIC METABOLISM

    PubMed Central

    MCSHAN, D.C.; UPDADHAYAYA, M.; SHAH, I.

    2009-01-01

    We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds. PMID:14992532

  16. Multisensory oddity detection as bayesian inference.

    PubMed

    Hospedales, Timothy; Vijayakumar, Sethu

    2009-01-01

    A key goal for the perceptual system is to optimally combine information from all the senses that may be available in order to develop the most accurate and unified picture possible of the outside world. The contemporary theoretical framework of ideal observer maximum likelihood integration (MLI) has been highly successful in modelling how the human brain combines information from a variety of different sensory modalities. However, in various recent experiments involving multisensory stimuli of uncertain correspondence, MLI breaks down as a successful model of sensory combination. Within the paradigm of direct stimulus estimation, perceptual models which use Bayesian inference to resolve correspondence have recently been shown to generalize successfully to these cases where MLI fails. This approach has been known variously as model inference, causal inference or structure inference. In this paper, we examine causal uncertainty in another important class of multi-sensory perception paradigm--that of oddity detection and demonstrate how a Bayesian ideal observer also treats oddity detection as a structure inference problem. We validate this approach by showing that it provides an intuitive and quantitative explanation of an important pair of multi-sensory oddity detection experiments--involving cues across and within modalities--for which MLI previously failed dramatically, allowing a novel unifying treatment of within and cross modal multisensory perception. Our successful application of structure inference models to the new 'oddity detection' paradigm, and the resultant unified explanation of across and within modality cases provide further evidence to suggest that structure inference may be a commonly evolved principle for combining perceptual information in the brain.

  17. Moment inference from tomograms

    USGS Publications Warehouse

    Day-Lewis, F. D.; Chen, Y.; Singha, K.

    2007-01-01

    Time-lapse geophysical tomography can provide valuable qualitative insights into hydrologic transport phenomena associated with aquifer dynamics, tracer experiments, and engineered remediation. Increasingly, tomograms are used to infer the spatial and/or temporal moments of solute plumes; these moments provide quantitative information about transport processes (e.g., advection, dispersion, and rate-limited mass transfer) and controlling parameters (e.g., permeability, dispersivity, and rate coefficients). The reliability of moments calculated from tomograms is, however, poorly understood because classic approaches to image appraisal (e.g., the model resolution matrix) are not directly applicable to moment inference. Here, we present a semi-analytical approach to construct a moment resolution matrix based on (1) the classic model resolution matrix and (2) image reconstruction from orthogonal moments. Numerical results for radar and electrical-resistivity imaging of solute plumes demonstrate that moment values calculated from tomograms depend strongly on plume location within the tomogram, survey geometry, regularization criteria, and measurement error. Copyright 2007 by the American Geophysical Union.

  18. Circular inferences in schizophrenia.

    PubMed

    Jardri, Renaud; Denève, Sophie

    2013-11-01

    A considerable number of recent experimental and computational studies suggest that subtle impairments of excitatory to inhibitory balance or regulation are involved in many neurological and psychiatric conditions. The current paper aims to relate, specifically and quantitatively, excitatory to inhibitory imbalance with psychotic symptoms in schizophrenia. Considering that the brain constructs hierarchical causal models of the external world, we show that the failure to maintain the excitatory to inhibitory balance results in hallucinations as well as in the formation and subsequent consolidation of delusional beliefs. Indeed, the consequence of excitatory to inhibitory imbalance in a hierarchical neural network is equated to a pathological form of causal inference called 'circular belief propagation'. In circular belief propagation, bottom-up sensory information and top-down predictions are reverberated, i.e. prior beliefs are misinterpreted as sensory observations and vice versa. As a result, these predictions are counted multiple times. Circular inference explains the emergence of erroneous percepts, the patient's overconfidence when facing probabilistic choices, the learning of 'unshakable' causal relationships between unrelated events and a paradoxical immunity to perceptual illusions, which are all known to be associated with schizophrenia.

  19. Inferring Horizontal Gene Transfer

    PubMed Central

    Lassalle, Florent; Dessimoz, Christophe

    2015-01-01

    Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages [1]. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events. PMID:26020646

  20. Matrix Factorization for Transcriptional Regulatory Network Inference

    PubMed Central

    Ochs, Michael F.; Fertig, Elana J.

    2013-01-01

    Inference of Transcriptional Regulatory Networks (TRNs) provides insight into the mechanisms driving biological systems, especially mammalian development and disease. Many techniques have been developed for TRN estimation from indirect biochemical measurements. Although successful when initially tested in model organisms, these regulatory models often fail when applied to data from multicellular organisms where multiple regulation and gene reuse increase dramatically. Non-negative matrix factorization techniques were initially introduced to find non-orthogonal patterns in data, making them ideal techniques for inference in cases of multiple regulation. We review these techniques and their application to TRN analysis. PMID:25364782

  1. Gene-network inference by message passing

    NASA Astrophysics Data System (ADS)

    Braunstein, A.; Pagnani, A.; Weigt, M.; Zecchina, R.

    2008-01-01

    The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.

  2. Reliability of the Granger causality inference

    NASA Astrophysics Data System (ADS)

    Zhou, Douglas; Zhang, Yaoyu; Xiao, Yanyang; Cai, David

    2014-04-01

    How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result.

  3. Computational inference of neural information flow networks.

    PubMed

    Smith, V Anne; Yu, Jing; Smulders, Tom V; Hartemink, Alexander J; Jarvis, Erich D

    2006-11-24

    Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.

  4. Bayesian inference in geomagnetism

    NASA Technical Reports Server (NTRS)

    Backus, George E.

    1988-01-01

    The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.

  5. BIE: Bayesian Inference Engine

    NASA Astrophysics Data System (ADS)

    Weinberg, Martin D.

    2013-12-01

    The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates heta distributed according to P( heta|D) so moments are trivially obtained by summing of the ensemble of variates.

  6. Continental basalts record the crust-mantle interaction in oceanic subduction channel: A geochemical case study from eastern China

    NASA Astrophysics Data System (ADS)

    Xu, Zheng; Zheng, Yong-Fei

    2017-09-01

    Continental basalts, erupted in either flood or rift mode, usually show oceanic island basalts (OIB)-like geochemical compositions. Although their depletion in Sr-Nd isotope compositions is normally ascribed to contributions from the asthenospheric mantle, their enrichment in large ion lithophile elements (LILE) and light rare earth elements (LREE) is generally associated with variable enrichments in the Sr-Nd isotope compositions. This indicates significant contributions from crustal components such as igneous oceanic crust, lower continental crust and seafloor sediment. Nevertheless, these crustal components were not incorporated into the mantle sources of continental basalts in the form of solidus rocks. Instead they were processed into metasomatic agents through low-degree partial melting in order to have the geochemical fractionation of the largest extent to achieve the enrichment of LILE and LREE in the metasomatic agents. Therefore, the mantle sources of continental basalts were generated by metasomatic reaction of the depleted mid-ocean ridge basalts (MORB) mantle with hydrous felsic melts. Nevertheless, mass balance considerations indicate differential contributions from the mantle and crustal components to the basalts. While the depleted MORB mantle predominates the budget of major elements, the crustal components predominate the budget of melt-mobile incompatible trace elements and their pertinent radiogenic isotopes. These considerations are verified by model calculations that are composed of four steps in an ancient oceanic subduction channel: (1) dehydration of the subducting crustal rocks at subarc depths, (2) anataxis of the dehydrated rocks at postarc depths, (3) metasomatic reaction of the depleted MORB mantle peridotite with the felsic melts to generate ultramafic metasomatites in the lower part of the mantle wedge, and (4) partial melting of the metasomatites for basaltic magmatism. The composition of metasomatites is quantitatively dictated by the crustal metasomatism through melt-peridotite reaction at the slab-mantle interface in oceanic subduction channels. Continental basalts of Mesozoic to Cenozoic ages from eastern China are used as a case example to illustrate the above petrogenetic mechanism. Subduction of the paleo-Pacific oceanic slab beneath the eastern edge of Eurasian continent in the Early Mesozoic would have transferred the crustal signatures into the mantle sources of these basalts. This process would be associated with rollback of the subducting slab at that time, whereas the partial melting of metasomatites takes place mainly in the Late Mesozoic to Cenozoic to produce the continental basalts. Therefore, OIB-like continental basalts are also the product of subduction-zone magmatism though they occur in intraplate settings.

  7. Subduction-zone crust-mantle interaction is a common mechanism for the origin of oceanic arc and island basalts

    NASA Astrophysics Data System (ADS)

    Zheng, Y. F.; Zhao, Z. F.

    2014-12-01

    We present a generalized model for the origin of oceanic arc basalts (OAB) and oceanic island basalts (OIB). This is realized by an integrated study of their major-trace element and stable-radiogenic isotope compositions. Many continental basalts are geochemically indistinguishable from common OIB, a fact that requires part of the upper mantle to have been a common reservoir beneath both oceans and continents. In addition, this reservoir must have been isolated from the convective asthenosphere for preservation of geochemical anomalies. Common OAB and OIB show consistent enrichment of LILE and LREE relative to normal MORB. On the primitive mantle-normalized spidergram, however, OAB are characterized by negative Nb and Ta anomalies but a positive Pb anomaly, whereas OIB show positive or no Nb and Ta anomalies but a negative Pb anomaly. Such differences are attributed to the difference in the property of metasomatic agents (aqueous solutions, hydrous melts and supercritical fluids) derived from subducting crustal rocks. The metasomatic agents are highly enriched in fluid/melt-mobile incompatible trace elements such as LILE and LREE, transferring enriched components from the crustal rocks to the mantle sources of OAB and OIB. The stability of rutile in the subducting crustal rocks dictates the abundance of Nb and Ta in the metasomatic agents. Lead is preferentially partitioned into the metasomatic agents when released at subarc depths, whereas dehydrated Pb-poor restites were subducted to greater depths. This explains the positive Pb anomaly in OAB but the negative Pb anomaly in OIB. We accept the assumption that normal MORB are derived from partial melting of the normal asthenospheric mantle, a common reservoir of isotopic depletion. We extend the chemical reaction at the slab-mantle interface in subduction channel from subarc depths to those above the mantle transition zone, generating metasomatic ultramafic rocks (metasomes) in the upper mantle. The reaction at subarc depths produces serpentinized to chloritized peridotites, serving as the source of OAB; the reaction at greater depths produces pyroxene-rich peridotites, pyroxenite and hornblendite, serving as the source of OIB. These metasomes have low solidii and thus are more susceptible to partial melting than the peridotite at the same P-T conditions.

  8. Crust-mantle decoupling in the Alps, Carpathians, Dinarides and Hellenides - the next targets of AlpArray?

    NASA Astrophysics Data System (ADS)

    Handy, Mark R.; Kissling, Eduard; Spakman, Wim; Ustaszewski, Kamil; Le Breton, Eline; Giese, Joerg

    2017-04-01

    The junctions of the Alps, Carpathians, Dinarides and Hellenides have disparate subsurface and surface structures that indicate decoupling of the crust and lithospheric mantle during Adria-Europe convergence. The complexity of subsurface structures at these orogenic junctions make them inviting targets for the next generation of integrated seismological-structural studies. Travel-time and receiver-function tomography at the Alps-Carpathians junction suggest that the NE-dipping "Lippitsch" positive anomaly beneath the Eastern Alps may connect eastward to a subvertical positive anomaly reaching down to the Mantle Transition Zone beneath the Pannonian Basin. The length of this slab-like anomaly exceeds known Neogene shortening in the overlying crust which is masked by Miocene Pannonian upper-plate extension. This suggests that either Neogene N-S shortening in the eastern Alps, western Carpathians and northern Dinarides has been underestimated and/or that this anomaly is an amalgam of subduction of both European and Adriatic lithospheres; these may have melded during a Miocene switch in subduction polarity beneath the eastern Alps. Neogene crustal deformation north of the Periadriatic Fault in the Tauern Window (Austria) involved north-directed crustal wedging and eastward orogenic escape, whereas south of this fault deformation involved large (≤ 130°) clockwise block rotations, S-directed thrusting and overturned Eocene Dinaric thrusts (Medvenica mountains, northern Croatia). Most global P-wave tomographic models indicate no Adriatic slab anomaly in the northern Dinarides and only a short (≤ 150 km long) NE-dipping anomaly in the southern Dinarides. The short length probably reflects the obliquity of Neogene Adria-Europe convergence, whereas the lack of an anomaly may be due to thermal erosion during asthenospheric flow since late Paleogene slab delamination or breakoff. At the Dinarides-Hellenides junction, the NE-dipping Adriatic slab has retreated SW-ward since this breakoff event, as indicated in cross sections by offset between the slab anomaly and the Sava suture. This junction is marked by orogen-parallel and -normal extension, and clockwise block rotation localized along a normal fault oriented transverse to the orogen (Shkoder-Peja Normal Fault, SPNF). Faulting has been active since mid-Miocene time according to clastics in the hangingwall of the SPNF, earthquake focal mechanisms and GPS motion vectors. The junction has been interpreted as a hinge zone at the NW end of the Hellenic arc that links arc-parallel extension to Adriatic subduction during radial expansion of the SW-retreating Hellenides.

  9. Bayes factors and multimodel inference

    USGS Publications Warehouse

    Link, W.A.; Barker, R.J.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

    2009-01-01

    Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

  10. The research on high speed underwater target recognition based on fuzzy logic inference

    NASA Astrophysics Data System (ADS)

    Jiang, Xiang-Dong; Yang, De-Sen; Shi, Sheng-Guo; Li, Si-Chun

    2006-06-01

    The underwater target recognition is a key technology in acoustic confrontation and underwater defence. In this article, a recognition system based of fuzzy logic inference (FLI) is set up. This system is mainly composed of three parts: the fuzzy input module, the fuzzy logic inference module with a set of inference rules and the de-fuzzy output module. The inference result shows the recognition system is effective in most conditions.

  11. Multi-attribute utility function or statistical inference models: a comparison of health state valuation models using the HUI2 health state classification system.

    PubMed

    Stevens, Katherine; McCabe, Christopher; Brazier, John; Roberts, Jennifer

    2007-09-01

    A key issue in health state valuation modelling is the choice of functional form. The two most frequently used preference based instruments adopt different approaches; one based on multi-attribute utility theory (MAUT), the other on statistical analysis. There has been no comparison of these alternative approaches in the context of health economics. We report a comparison of these approaches for the health utilities index mark 2. The statistical inference model predicts more accurately than the one based on MAUT. We discuss possible explanations for the differences in performance, the importance of the findings, and implications for future research.

  12. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  13. Improving Inferences from Multiple Methods.

    ERIC Educational Resources Information Center

    Shotland, R. Lance; Mark, Melvin M.

    1987-01-01

    Multiple evaluation methods (MEMs) can cause an inferential challenge, although there are strategies to strengthen inferences. Practical and theoretical issues involved in the use by social scientists of MEMs, three potential problems in drawing inferences from MEMs, and short- and long-term strategies for alleviating these problems are outlined.…

  14. Feature Inference Learning and Eyetracking

    ERIC Educational Resources Information Center

    Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

    2009-01-01

    Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

  15. Learning to Observe "and" Infer

    ERIC Educational Resources Information Center

    Hanuscin, Deborah L.; Park Rogers, Meredith A.

    2008-01-01

    Researchers describe the need for students to have multiple opportunities and social interaction to learn about the differences between observation and inference and their role in developing scientific explanations (Harlen 2001; Simpson 2000). Helping children develop their skills of observation and inference in science while emphasizing the…

  16. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  17. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  18. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  19. Improving Inferences from Multiple Methods.

    ERIC Educational Resources Information Center

    Shotland, R. Lance; Mark, Melvin M.

    1987-01-01

    Multiple evaluation methods (MEMs) can cause an inferential challenge, although there are strategies to strengthen inferences. Practical and theoretical issues involved in the use by social scientists of MEMs, three potential problems in drawing inferences from MEMs, and short- and long-term strategies for alleviating these problems are outlined.…

  20. Double jeopardy in inferring cognitive processes.

    PubMed

    Fific, Mario

    2014-01-01

    Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes from the construction of inadequate research designs possessing a low diagnostic accuracy of cognitive processes. For that reason we introduced the systems factorial technology (SFT), which has primarily been designed to make inferences about underlying processing order (serial, parallel, coactive), stopping rule (terminating, exhaustive), and process dependency. SFT proposes that the minimal research design complexity to learn about n number of cognitive processes should be equal to 2 (n) . In addition, SFT proposes that (a) each cognitive process should be controlled by a separate experimental factor, and (b) The saliency levels of all factors should be combined in a full factorial design. In the current study, the author cross combined the levels of jeopardies in a 2 × 2 analysis, leading to four different analysis conditions. The results indicate a decline in the diagnostic accuracy of inferences made about cognitive processes due to the presence of each jeopardy in isolation and when combined. The results warrant the development of more individual subject analyses and the utilization of full-factorial (SFT) experimental designs.

  1. Efficient Bayesian inference for ARFIMA processes

    NASA Astrophysics Data System (ADS)

    Graves, T.; Gramacy, R. B.; Franzke, C. L. E.; Watkins, N. W.

    2015-03-01

    Many geophysical quantities, like atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long-range dependence (LRD). LRD means that these quantities experience non-trivial temporal memory, which potentially enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LRD. In this paper we present a modern and systematic approach to the inference of LRD. Rather than Mandelbrot's fractional Gaussian noise, we use the more flexible Autoregressive Fractional Integrated Moving Average (ARFIMA) model which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LRD, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g. short memory effects) can be integrated over in order to focus on long memory parameters, and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data, with favorable comparison to the standard estimators.

  2. Inverse Ising inference with correlated samples

    NASA Astrophysics Data System (ADS)

    Obermayer, Benedikt; Levine, Erel

    2014-12-01

    Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially, the parameters of the least constrained statistical model are learned from the observed correlations such that direct interactions can be separated from indirect correlations. Among many other applications, this approach has been helpful for protein structure prediction, because residues which interact in the 3D structure often show correlated substitutions in a multiple sequence alignment. In this context, samples used for inference are not independent but share an evolutionary history on a phylogenetic tree. Here, we discuss the effects of correlations between samples on global inference. Such correlations could arise due to phylogeny but also via other slow dynamical processes. We present a simple analytical model to address the resulting inference biases, and develop an exact method accounting for background correlations in alignment data by combining phylogenetic modeling with an adaptive cluster expansion algorithm. We find that popular reweighting schemes are only marginally effective at removing phylogenetic bias, suggest a rescaling strategy that yields better results, and provide evidence that our conclusions carry over to the frequently used mean-field approach to the inverse Ising problem.

  3. Double jeopardy in inferring cognitive processes

    PubMed Central

    Fific, Mario

    2014-01-01

    Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes from the construction of inadequate research designs possessing a low diagnostic accuracy of cognitive processes. For that reason we introduced the systems factorial technology (SFT), which has primarily been designed to make inferences about underlying processing order (serial, parallel, coactive), stopping rule (terminating, exhaustive), and process dependency. SFT proposes that the minimal research design complexity to learn about n number of cognitive processes should be equal to 2n. In addition, SFT proposes that (a) each cognitive process should be controlled by a separate experimental factor, and (b) The saliency levels of all factors should be combined in a full factorial design. In the current study, the author cross combined the levels of jeopardies in a 2 × 2 analysis, leading to four different analysis conditions. The results indicate a decline in the diagnostic accuracy of inferences made about cognitive processes due to the presence of each jeopardy in isolation and when combined. The results warrant the development of more individual subject analyses and the utilization of full-factorial (SFT) experimental designs. PMID:25374545

  4. Quantum-Like Representation of Non-Bayesian Inference

    NASA Astrophysics Data System (ADS)

    Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

    2013-01-01

    This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

  5. The empirical accuracy of uncertain inference models

    NASA Technical Reports Server (NTRS)

    Vaughan, David S.; Yadrick, Robert M.; Perrin, Bruce M.; Wise, Ben P.

    1987-01-01

    Uncertainty is a pervasive feature of the domains in which expert systems are designed to function. Research design to test uncertain inference methods for accuracy and robustness, in accordance with standard engineering practice is reviewed. Several studies were conducted to assess how well various methods perform on problems constructed so that correct answers are known, and to find out what underlying features of a problem cause strong or weak performance. For each method studied, situations were identified in which performance deteriorates dramatically. Over a broad range of problems, some well known methods do only about as well as a simple linear regression model, and often much worse than a simple independence probability model. The results indicate that some commercially available expert system shells should be used with caution, because the uncertain inference models that they implement can yield rather inaccurate results.

  6. Inferring handedness from lithic evidence.

    PubMed

    Rugg, G; Mullane, M

    2001-07-01

    Until recently research into the origins of human handedness has been hampered by the lack of valid techniques for inferring handedness in pre-modern populations. A method developed by Toth for inferring handedness from lithic evidence, based on orientation of the cortex on lithic flakes, has produced promising results. However, this method is limited in applicability and has a variable signal to noise ratio. The authors describe a separate method, based on the orientation of the cone of percussion in lithic flakes, for inferring handedness from the lithic evidence. This method complements the cortex method. Some preliminary experimental evidence is presented which indicates that handedness can be inferred from lithic evidence using the cone of percussion method. Suggestions for further research are made.

  7. Bayesian Inference of Galaxy Morphology

    NASA Astrophysics Data System (ADS)

    Yoon, Ilsang; Weinberg, M.; Katz, N.

    2011-01-01

    Reliable inference on galaxy morphology from quantitative analysis of ensemble galaxy images is challenging but essential ingredient in studying galaxy formation and evolution, utilizing current and forthcoming large scale surveys. To put galaxy image decomposition problem in broader context of statistical inference problem and derive a rigorous statistical confidence levels of the inference, I developed a novel galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes) that exploits recent developments in Bayesian computation to provide full posterior probability distributions and reliable confidence intervals for all parameters. I will highlight the significant improvements in galaxy image decomposition using GALPHAT, over the conventional model fitting algorithms and introduce the GALPHAT potential to infer the statistical distribution of galaxy morphological structures, using ensemble posteriors of galaxy morphological parameters from the entire galaxy population that one studies.

  8. Insights on the injection mechanisms inferred from AMS fabrics of sand injectites in a turbiditic system, the exemple of Bevon area of the SE Basin (France).

    NASA Astrophysics Data System (ADS)

    Robion, Philippe; Mehl, Caroline

    2016-04-01

    We propose to investigate the set up mechanisms of sands injection in the case of dykes injected in host marls of Aptian-Albian age in the Vocontian basin (SE France). Several models have been proposed for a downward injection of the dyke in the Bevons area and we guess that AMS fabric investigations can be used to infer the flow direction. 144 drill cores distributed on 14 sites were sampled, among which 8 sites in the injectites and 6 sites in the host rocks. The studied dykes are generally of a few decimeters thick and are setting up in both in vertical or oblique position with respect to the subhorizontal bedding of the host rocks. There were sampled from one side to the other in order to track the flow direction by identification of imbricated fabric. Magnetic mineralogy, i.e. unblocking temperature inferred from IRM 3 axes demagnetization, indicates that the ferromagnetics s.l. mineralogy is dominated by an assemblage of magnetite (unblocking temperature Tub=580°C) and pyrrhotite (Tub=325°C). Magnetic susceptibility is low, typical for siliciclastic rocks, ranging from 4x10-5 up to 1.7x10-4 SI. Degree of magnetic anisotropy is likely representative of AMS measurements in sedimentary rocks with weak values, below than 5 %. In marly host rocks magnetic mineralogy is dominated by pyrrhotite associated with magnetite and both the magnetic susceptibility and degree of anisotropy are slightly lower than for injectites. Regarding magnetic fabric axes distribution, despite some dispersion, the results show that minimum axes of AMS (K3) are parallel to the dyke plane, and maximum axes (K1) are roughly in horizontal position. In marly host rocks, the magnetic fabric is related to tectonic shortening. We interpret that the host rocks have recorded the regional tectonic imprint while the magnetic fabric of the injectites are related to early sedimentary processes. The mechanism of set up proposed to explain the magnetic fabric in the Bevon injectites is a step

  9. Bayesian Inference: with ecological applications

    USGS Publications Warehouse

    Link, William A.; Barker, Richard J.

    2010-01-01

    This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

  10. Statistical Inference: The Big Picture.

    PubMed

    Kass, Robert E

    2011-02-01

    Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice, labelled here statistical pragmatism, serves as a foundation for inference. Statistical pragmatism is inclusive and emphasizes the assumptions that connect statistical models with observed data. I argue that introductory courses often mis-characterize the process of statistical inference and I propose an alternative "big picture" depiction.

  11. Active inference, communication and hermeneutics☆

    PubMed Central

    Friston, Karl J.; Frith, Christopher D.

    2015-01-01

    Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others – during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions – both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then – in principle – they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. PMID:25957007

  12. Active inference, communication and hermeneutics.

    PubMed

    Friston, Karl J; Frith, Christopher D

    2015-07-01

    Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. Causal inference and developmental psychology.

    PubMed

    Foster, E Michael

    2010-11-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference-tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development.

  14. Abductive inference and delusional belief.

    PubMed

    Coltheart, Max; Menzies, Peter; Sutton, John

    2010-01-01

    Delusional beliefs have sometimes been considered as rational inferences from abnormal experiences. We explore this idea in more detail, making the following points. First, the abnormalities of cognition that initially prompt the entertaining of a delusional belief are not always conscious and since we prefer to restrict the term "experience" to consciousness we refer to "abnormal data" rather than "abnormal experience". Second, we argue that in relation to many delusions (we consider seven) one can clearly identify what the abnormal cognitive data are which prompted the delusion and what the neuropsychological impairment is which is responsible for the occurrence of these data; but one can equally clearly point to cases where this impairment is present but delusion is not. So the impairment is not sufficient for delusion to occur: a second cognitive impairment, one that affects the ability to evaluate beliefs, must also be present. Third (and this is the main thrust of our paper), we consider in detail what the nature of the inference is that leads from the abnormal data to the belief. This is not deductive inference and it is not inference by enumerative induction; it is abductive inference. We offer a Bayesian account of abductive inference and apply it to the explanation of delusional belief.

  15. Optimal inference with suboptimal models: Addiction and active Bayesian inference

    PubMed Central

    Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl

    2015-01-01

    When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321

  16. Active inference and robot control: a case study

    PubMed Central

    Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

    2016-01-01

    Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours. PMID:27683002

  17. Active inference and robot control: a case study.

    PubMed

    Pio-Lopez, Léo; Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

    2016-09-01

    Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours.

  18. Functional neuroanatomy of intuitive physical inference

    PubMed Central

    Mikhael, John G.; Tenenbaum, Joshua B.; Kanwisher, Nancy

    2016-01-01

    To engage with the world—to understand the scene in front of us, plan actions, and predict what will happen next—we must have an intuitive grasp of the world’s physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events—a “physics engine” in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general “multiple demand” system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action. PMID:27503892

  19. Functional neuroanatomy of intuitive physical inference.

    PubMed

    Fischer, Jason; Mikhael, John G; Tenenbaum, Joshua B; Kanwisher, Nancy

    2016-08-23

    To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.

  20. Consistency and Plausible Inference,

    DTIC Science & Technology

    1982-10-01

    the Pros- po(:tor Consultant System for Mineral Exploration ," Expert 5,ystems in the Mi cro Electronic Age £I). Michie, ed.), Edinburgh University...Press, 11979. . Duda, R.O., P.E. Hart, K. Konolige, and R. Reboh, A Computer-Based Consultant for Mineral Exploration , SRI International, 19,9. 8. Garvey

  1. Physics of Inference

    NASA Astrophysics Data System (ADS)

    Toroczkai, Zoltan

    Jaynes's maximum entropy method provides a family of principled models that allow the prediction of a system's properties as constrained by empirical data (observables). However, their use is often hindered by the degeneracy problem characterized by spontaneous symmetry breaking, where predictions fail. Here we show that degeneracy appears when the corresponding density of states function is not log-concave, which is typically the consequence of nonlinear relationships between the constraining observables. We illustrate this phenomenon on several examples, including from complex networks, combinatorics and classical spin systems (e.g., Blume-Emery-Griffiths lattice-spin models). Exploiting these nonlinear relationships we then propose a solution to the degeneracy problem for a large class of systems via transformations that render the density of states function log-concave. The effectiveness of the method is demonstrated on real-world network data. Finally, we discuss the implications of these findings on the relationship between the geometrical properties of the density of states function and phase transitions in spin systems. Supported in part by Grant No. FA9550-12-1-0405 from AFOSR/DARPA and by Grant No. HDTRA 1-09-1-0039 from DTRA.

  2. Statistical inference and string theory

    NASA Astrophysics Data System (ADS)

    Heckman, Jonathan J.

    2015-09-01

    In this paper, we expose some surprising connections between string theory and statistical inference. We consider a large collective of agents sweeping out a family of nearby statistical models for an M-dimensional manifold of statistical fitting parameters. When the agents making nearby inferences align along a d-dimensional grid, we find that the pooled probability that the collective reaches a correct inference is the partition function of a nonlinear sigma model in d dimensions. Stability under perturbations to the original inference scheme requires the agents of the collective to distribute along two dimensions. Conformal invariance of the sigma model corresponds to the condition of a stable inference scheme, directly leading to the Einstein field equations for classical gravity. By summing over all possible arrangements of the agents in the collective, we reach a string theory. We also use this perspective to quantify how much an observer can hope to learn about the internal geometry of a superstring compactification. Finally, we present some brief speculative remarks on applications to the AdS/CFT correspondence and Lorentzian signature space-times.

  3. The state of the atmosphere as inferred from the FGGE satellite observing systems during SOP-1. [special observing period (SOP-1) of First Global Atmospheric Research Program Global Experiment (FGGE)

    NASA Technical Reports Server (NTRS)

    Halem, M.; Kalnay-Rivas, E.; Baker, W. E.; Atlas, R.

    1981-01-01

    The statistical properties, and coverage, of satellite temperature sounding data are described. Tropical regions are observed every two days, extratropics from one to four times a day. Oceans are covered two to three times a day. Asynoptic coverage is comparable to the U.S. rawinsonde network twice daily coverage. Lack of ground truth for data sparse areas makes accuracy difficult to assess. The rms differences of layer mean temperatures obtained from collocating rawinsonde observations with satellite temperature profiles in space and time differ from rms differences of layer mean satellite temperature soundings. The FGGE satellite systems can infer the three dimensional motion field and improve the representation of the large scale state of the atmosphere.

  4. The state of the atmosphere as inferred from the FGGE satellite observing systems during SOP-1. [special observing period (SOP-1) of First Global Atmospheric Research Program Global Experiment (FGGE)

    NASA Technical Reports Server (NTRS)

    Halem, M.; Kalnay-Rivas, E.; Baker, W. E.; Atlas, R.

    1981-01-01

    The statistical properties, and coverage, of satellite temperature sounding data are described. Tropical regions are observed every two days, extratropics from one to four times a day. Oceans are covered two to three times a day. Asynoptic coverage is comparable to the U.S. rawinsonde network twice daily coverage. Lack of ground truth for data sparse areas makes accuracy difficult to assess. The rms differences of layer mean temperatures obtained from collocating rawinsonde observations with satellite temperature profiles in space and time differ from rms differences of layer mean satellite temperature soundings. The FGGE satellite systems can infer the three dimensional motion field and improve the representation of the large scale state of the atmosphere.

  5. The association forecasting of 13 variants within seven asthma susceptibility genes on 3 serum IgE groups in Taiwanese population by integrating of adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods.

    PubMed

    Wang, Cheng-Hang; Liu, Baw-Jhiune; Wu, Lawrence Shih-Hsin

    2012-02-01

    Asthma is one of the most common chronic diseases in children. It is caused by complicated coactions between various genetic factors and environmental allergens. The study aims to integrate the concept of implementing adaptive neuro-fuzzy inference system (ANFIS) and classification analysis methods for forecasting the association of asthma susceptibility genes on 3 serum IgE groups. The ANFIS model was trained and tested with data sets obtained from 425 asthmatic subjects and 483 non-asthma subjects from the Taiwanese population. We assessed 13 single-nucleotide polymorphisms (SNPs) in seven well-known asthma susceptibility genes; firstly, the proposed ANFIS model learned to reduce input features from the 13 SNPs. And secondly, the classification will be used to classify the serum IgE groups from the simulated SNPs results. The performance of the ANFIS model, classification accuracies and the results confirmed that the integration of ANFIS and classified analysis has potential in association discovery.

  6. Locative inferences in medical texts.

    PubMed

    Mayer, P S; Bailey, G H; Mayer, R J; Hillis, A; Dvoracek, J E

    1987-06-01

    Medical research relies on epidemiological studies conducted on a large set of clinical records that have been collected from physicians recording individual patient observations. These clinical records are recorded for the purpose of individual care of the patient with little consideration for their use by a biostatistician interested in studying a disease over a large population. Natural language processing of clinical records for epidemiological studies must deal with temporal, locative, and conceptual issues. This makes text understanding and data extraction of clinical records an excellent area for applied research. While much has been done in making temporal or conceptual inferences in medical texts, parallel work in locative inferences has not been done. This paper examines the locative inferences as well as the integration of temporal, locative, and conceptual issues in the clinical record understanding domain by presenting an application that utilizes two key concepts in its parsing strategy--a knowledge-based parsing strategy and a minimal lexicon.

  7. Optimal fuzzy inference for short-term load forecasting

    SciTech Connect

    Mori, Hiroyuki; Kobayashi, Hidenori

    1996-02-01

    This paper proposes an optimal fuzzy inference method for short-term load forecasting. The proposed method constructs an optimal structure of the simplified fuzzy inference that minimizes model errors and the number of the membership functions to grasp nonlinear behavior of power system short-term loads. The model is identified by simulated annealing and the steepest descent method. The proposed method is demonstrated in examples.

  8. Development of Statistical Methods Using Predictive Inference and Entropy.

    DTIC Science & Technology

    1986-03-01

    Inference and Entopy APPENDIX B: Achieab Accuracy in Parametric Estimation of B-I Multivariate spectra ii LWl OF MIUMU AND TABLES FIGURES PAGE Figre1...1986e). "Achievable Accuracy in Parametric Estimation of Multivariate Spec- tra’. Draft. Larimore, WE. (1983a). ’Predictive inference, sufficiency... PARAMETRIC ESTIMATION OF MULTIVARIATE SPECTRA By Wallace E. Larimore Scientific Systems Inc., Cambridge, Massachusetts, U.SA. Research Sponsored by the

  9. Causal inference in biology networks with integrated belief propagation.

    PubMed

    Chang, Rui; Karr, Jonathan R; Schadt, Eric E

    2015-01-01

    Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

  10. Perception, illusions and Bayesian inference.

    PubMed

    Nour, Matthew M; Nour, Joseph M

    2015-01-01

    Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.

  11. Inferring Trust Based on Similarity with TILLIT

    NASA Astrophysics Data System (ADS)

    Tavakolifard, Mozhgan; Herrmann, Peter; Knapskog, Svein J.

    A network of people having established trust relations and a model for propagation of related trust scores are fundamental building blocks in many of today’s most successful e-commerce and recommendation systems. However, the web of trust is often too sparse to predict trust values between non-familiar people with high accuracy. Trust inferences are transitive associations among users in the context of an underlying social network and may provide additional information to alleviate the consequences of the sparsity and possible cold-start problems. Such approaches are helpful, provided that a complete trust path exists between the two users. An alternative approach to the problem is advocated in this paper. Based on collaborative filtering one can exploit the like-mindedness resp. similarity of individuals to infer trust to yet unknown parties which increases the trust relations in the web. For instance, if one knows that with respect to a specific property, two parties are trusted alike by a large number of different trusters, one can assume that they are similar. Thus, if one has a certain degree of trust to the one party, one can safely assume a very similar trustworthiness of the other one. In an attempt to provide high quality recommendations and proper initial trust values even when no complete trust propagation path or user profile exists, we propose TILLIT — a model based on combination of trust inferences and user similarity. The similarity is derived from the structure of the trust graph and users’ trust behavior as opposed to other collaborative-filtering based approaches which use ratings of items or user’s profile. We describe an algorithm realizing the approach based on a combination of trust inferences and user similarity, and validate the algorithm using a real large-scale data-set.

  12. Algorithm Optimally Orders Forward-Chaining Inference Rules

    NASA Technical Reports Server (NTRS)

    James, Mark

    2008-01-01

    People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally deve