126 resultados para Ford, John, 1586-ca. 1640.


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In this paper new online adaptive hidden Markov model (HMM) state estimation schemes are developed, based on extended least squares (ELS) concepts and recursive prediction error (RPE) methods. The best of the new schemes exploit the idempotent nature of Markov chains and work with a least squares prediction error index, using a posterior estimates, more suited to Markov models then traditionally used in identification of linear systems.

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This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

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This paper investigates demodulation of differentially phase modulated signals DPMS using optimal HMM filters. The optimal HMM filter presented in the paper is computationally of order N3 per time instant, where N is the number of message symbols. Previously, optimal HMM filters have been of computational order N4 per time instant. Also, suboptimal HMM filters have be proposed of computation order N2 per time instant. The approach presented in this paper uses two coupled HMM filters and exploits knowledge of ...

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In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

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In this paper, we propose a risk-sensitive approach to parameter estimation for hidden Markov models (HMMs). The parameter estimation approach considered exploits estimation of various functions of the state, based on model estimates. We propose certain practical suboptimal risk-sensitive filters to estimate the various functions of the state during transients, rather than optimal risk-neutral filters as in earlier studies. The estimates are asymptotically optimal, if asymptotically risk neutral, and can give significantly improved transient performance, which is a very desirable objective for certain engineering applications. To demonstrate the improvement in estimation simulation studies are presented that compare parameter estimation based on risk-sensitive filters with estimation based on risk-neutral filters.

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In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

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The mineral meliphanite (Ca,Na)2Be[(Si,Al)2O6(F,OH)] is a crystalline sodium calcium beryllium silicate which has the potential to be used as piezoelectric material and for other ferroelectric applications. The mineral has been characterized by a combination of scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) and vibrational spectroscopy. EDS analysis shows a material with high concentrations of Si and Ca and low amounts of Na, Al and F. Beryllium was not detected. Raman bands at 1016 and 1050 cm−1 are assigned to the SiO and AlOH stretching vibrations of three dimensional siloxane units. The infrared spectrum of meliphanite is very broad in comparison with the Raman spectrum. Raman bands at 472 and 510 cm−1 are assigned to OSiO bending modes. Raman spectroscopy identifies bands in the OH stretching region. Raman spectroscopy with complimentary infrared spectroscopy enables the characterization of the silicate mineral meliphanite.

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Samples of marble from Chillagoe, North Queensland have been analyzed using scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS) and Raman spectroscopy. Chemical analyses provide evidence for the presence of minerals other than limestone and calcite in the marble, including silicate minerals. Some of these analyses correspond to silicate minerals. The Raman spectra of these crystals were obtained and the Raman spectrum corresponds to that of allanite from the Arizona State University data base (RRUFF) data base. The combination of SEM with EDS and Raman spectroscopy enables the characterization of the mineral allanite in the Chillagoe marble.

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Heteroleptic complexes of the type \[RuL2L′](PF6)2 (L, L′ = combinations of 1,10-phenanthroline (phen) and 2,2′-bipyridine (bipy)) were found to cocrystallize with \[Ni(phen)3](PF6)2 to produce cocrystals of \[Ni(phen)3]x\[RuL2L′]1–x(PF6)2. In this report we show that the ability of the complexes to cocrystallize is influenced by the number of common ligands between complexes in solution. Supramolecular selection is a phenomenon caused by molecular recognition through which cocrystals can grow from the same solution but contain different ratios of the molecular components. It was found that systems where L = phen displayed less supramolecular selection than systems where L = bipy. With increasing supramolecular selection, the composition of cocrystals was found to vary significantly from the initial relative concentration in the cocrystallizing solution, and therefore it was increasingly difficult to control the final composition of the resultant cocrystals. Consequently, modulation of concentration-dependent properties such as phase was also found to be less predictable with increasing supramolecular selection. Notwithstanding the complication afforded by the presence of supramolecular selection, our results reaffirm the robustness of the \[M(phen)3](PF6)2 structure because it was maintained even when ca. 90% of the complexes in the cocrystals were \[Ru(phen)(bipy)2](PF6)2, which in its pure form is not isomorphous with \[M(phen)3](PF6)2. Experiments between complexes without common ligands, i.e., \[Ru(bipy)3](PF6)2 cocrystallized with \[Ni(phen)3](PF6)2, were found to approach the limit to which molecular recognition processes can be confused into cocrystallizing different molecules to form single cocrystals. For these systems the result was the formation of block-shaped crystals skewered by a needle-shaped crystals.

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The Archean Hollandaire volcanogenic massive sulfide deposit is a felsic–siliciclastic VMS deposit located in the Murchison Domain of the Youanmi Terrane, Yilgarn Craton, Western Australia. It is hosted in a succession of turbidites, mudstones and coherent rhyodacite sills and has been metamorphosed to upper greenschist/lower amphibolite facies and includes a pervasive S1 deformational fabric. The coherent rhyodacitic sills are interpreted as syndepositional based on geochemical similarities with well-known VMS-associated felsic rocks and similar foliations to the metasediments. We offer several explanations for the absence of textural evidence (e.g. breccias) for syn-depositional origins: 1) the subaqueous sediments were dehydrated by long-lived magmatism such that no pore-water remained to drive quench fragmentation; 2) pore-space occlusion by burial and/or, 3) alteration overprinting and obscuring of primary breccias at contact margins. Mineralisation occurs by sub-seafloor replacement of original host rocks in two ore bodies, Hollandaire Main (~125 x >500 m and ~8 m thick) and Hollandaire West (~100 x 470 m and ~5 m thick), and occurs in three main textural styles, massive sulfides, which are exclusively hosted in turbidites and mudstones, and stringer and disseminated sulfides, which are also hosted in coherent rhyodacite. Most sulfides have textures consistent with remobilisation and recrystallisation. Hydrothermal metamorphism has altered the hangingwall and footwall to similar degrees, with significant gains in Mg, Mn and K and losses in Na, Ca and Sr. Garnet and staurolite porphyryoblasts also exhibit a footprint around mineralisation, extending up to 30 m both above and below the ore zone. High precision thermal ionisation mass spectrometry of zircons extracted from the coherent rhyodacite yield an age of 2759.5 ± 0.9 Ma, which along with geochemical comparisons, places the succession within the 2760–2735 Ma Greensleeves Formation of the Polelle Group of the Murchison Supergroup. Geochemical and geochronological evidence link the coherent rhyodacite sills to the Peter Well Granodiorite pluton ~2 km to the W, which acted as the heat engine driving hydrothermal circulation during VMS mineralisation. This study highlights the importance of both: detailed physical volcanological studies from which an accurate assessment of timing relationships, particularly the possibility of intrusions dismembering ore horizons, can be made; and identifying synvolcanic plutons and other similar suites, for VMS exploration targets in the Youanmi Terrane and worldwide.

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The distinguished Australian architect surveys his career and examines how his architectural theories are expressed in his designs.

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A modified inorganic bentonite (Na/Al) based on purified Ca-bentonite was prepared through exchanging Al and Na ions in the interlayer space of Ca-bentonite. The structural properties of purified and modified bentonites were characterized by XRD and SEM analysis. Batch experiments were performed for the adsorption of ammonium nitrogen and different experimental conditions were studied in order to investigate the optimum adsorption conditions. Comparative experiments were also carried out for natural Ca-bentonite (RB), unmodified purified bentonite (PB) and modified purified bentonite (MB). Through the thermodynamic analysis, the ammonium nitrogen adsorption process can be spontaneous, the standard heat was −41.46kJmol −1 , and the adsorption process based on ion exchange adsorption. The ammonium nitrogen adsorption capacity of MB (46.904mg/g) was improved compared to raw bentonite (RB) (26.631mg/g), which was among the highest values of ammonium nitrogen adsorption compared with other adsorbents according to the literatures. The described process provides a potential pathway for the removal of ammonium nitrogen at low concentrations encountered in most natural waters.

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Depolymerization of purified organosolv eucalyptus wood lignin by the heterogeneous catalysts, cobalt polyphosphate (CoP2O6) and calcium phosphate (β-CaP2O6) was investigated. A total syringol yield of 16.7% was achieved with β-CaP2O6 in a methanol/water (50/50, wt/wt) solvent system after depolymerization at 300 ºC for 1 h, showing selectivity of the catalyst.

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Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10−4, Bonferroni corrected), of which six reached P < 5 × 10−8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.