A semi-analytical particle filter for identification of nonlinear oscillators

Particle filters find important applications in the problems of state and parameter estimations of dynamical systems of engineering interest. Since a typical filtering algorithm involves Monte Carlo simulations of the process equations, sample variance of the estimator is inversely proportional to the number of particles. The sample variance may be reduced if one uses a Rao-Blackwell marginalization of states and performs analytical computations as much as possible. In this work, we propose a semi-analytical particle filter, requiring no Rao-Blackwell marginalization, for state and parameter estimations of nonlinear dynamical systems with additively Gaussian process/observation noises. Through local linearizations of the nonlinear drift fields in the process/observation equations via explicit Ito-Taylor expansions, the given nonlinear system is transformed into an ensemble of locally linearized systems. Using the most recent observation, conditionally Gaussian posterior density functions of the linearized systems are analytically obtained through the Kalman filter. This information is further exploited within the particle filter algorithm for obtaining samples from the optimal posterior density of the states. The potential of the method in state/parameter estimations is demonstrated through numerical illustrations for a few nonlinear oscillators. The proposed filter is found to yield estimates with reduced sample variance and improved accuracy vis-a-vis results from a form of sequential importance sampling filter.

Nonlinear secondary whirl of an overhung rotor

Gravity critical speeds of rotors have hitherto been studied using linear analysis, and ascribed to rotor stiffness asymmetry. Here, we study an idealized asymmetric nonlinear overhung rotor model of Crandall and Brosens, spinning close to its gravity critical speed.Nonlinearities arise from finite displacements, and the rotor's staticlateral deflection under gravity is taken as small. Assuming small asymmetry and damping, slow modulations of whirl amplitudes are studied using the method of multiple scales. Inertia asymmetry appears only at second order. More interestingly, even without stiffness asymmetry, the gravity-induced resonance survives through geometric nonlinearities. The gravity resonant forcing does not influence the resonant mode at leading order, unlike the typical resonant oscillations. Nevertheless,the usual phenomena of resonances, namely saddle-node bifurcations, jump phenomena and hysteresis, are all observed. An unanticipated periodic solution branch is found. In the three-dimensional space oftwo modal coefficients and a detuning parameter, the full set of periodic solutions is found to be an imperfect version of three mutually intersecting curves: a straight line,a parabola and an ellipse.

Electrochemical reduction of hydrogen peroxide on stainless steel

Electrochemical reduction of hydrogen peroxide is studied on a sand-blasted stainless steel (SSS)electrode in an aqueous solution of NaClO4.The cyclic voltammetric reduction of H2O2 at low concentrations is characterized by a cathodic peak at -0 center dot 40 V versus standard calomel electrode(SCE).Cyclic voltammetry is studied by varying the concentration of H2O2 in the range from 0 center dot 2 mM to 20 mM and the sweep rate in the range from 2 to 100 mV s(-1)Voltammograms at concentrations of H2O2 higher than 2 mM or at high sweep rates consist of an additional current peak, which may be due to the reduction of adsorbed species formed during the reduction of H2O2. Amperometric determination of H2O2 at -0 center dot 50 V vs SCEprovides the detection limit of 5 A mu M H2O2. A plot of current density versus concentration has two segments suggesting a change in the mechanism of H2O2 reduction at concentrations of H2O2 a parts per thousand yen 2 mM. From the rotating disc electrode study, diffusion co-efficient of H2O2 and rate constant for reduction of H2O2 are evaluated.

R1SVM: A randomised nonlinear approach to large-scale anomaly detection

The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Suppression of the zero-order term in off-axis digital holography through nonlinear filtering

We present experimental validation of a new reconstruction method for off-axis digital holographic microscopy (DHM). This method effectively suppresses the object autocorrelation,namely, the zero-order term,from holographic data,thereby improving the reconstruction bandwidth of complex wavefronts. The algorithm is based on nonlinear filtering and can be applied to standard DHM setups with realistic recording conditions.We study the robustness of the technique under different experimental configurations,and quantitatively demonstrate its enhancement capabilities on phase signals.

Chemoselective reduction of azides catalyzed by molybdenum xanthate by using phenylsilane as the hydride source

A chemoselective, neutral, and efficient strategy for the reduction of azides to corresponding amines catalyzed by dioxobis(N,N,-diethyldithiocarbamato) molybdenum complex (1, MoO2[S2CNEt2](2)) in the presence of phenylsilane is discovered. This chemoselective reduction strategy tolerates a variety of reducible functional groups.

Transient response of nonlinear magneto-optic rotation in a paraffin-coated Rb vapor cell

We study resonant nonlinear magneto-optic rotation (NMOR) in a paraffin-coated Rb vapor cell as the magnetic field is swept. At low sweep rates, the nonlinear rotation appears as a narrow resonance signal with a linewidth of about ``300 mu G''(2 pi x 420 Hz). At high sweep rates, the signal shows transient response with an oscillatory decay. The decay time constant is of order 100 ms. The behavior is different for transitions starting from the lower or the upper hyperfine level of the ground state because of optical pumping effects.

A direct borohydride fuel cell employing Prussian Blue as mediated electron-transfer hydrogen peroxide reduction catalyst

A direct borohydride-hydrogen peroxide fuel cell employing carbon-supported Prussian Blue (PB) as mediated electron-transfer cathode catalyst is reported. While operating at 30 °C, the direct borohydride-hydrogen peroxide fuel cell employing carbon-supported PB cathode catalyst shows superior performance with the maximum output power density of 68 mW cm−2 at an operating voltage of 1.1 V compared to direct borohydride-hydrogen peroxide fuel cell employing the conventional gold-based cathode with the maximum output power density of 47 mW cm−2 at an operating voltage of 0.7 V. X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray Analysis (EDAX) suggest that anchoring of Cetyl-Trimethyl Ammonium Bromide (CTAB) as a surfactant moiety on carbon-supported PB affects the catalyst morphology. Polarization studies on direct borohydride-hydrogen peroxide fuel cell with carbon-supported CTAB-anchored PB cathode exhibit better performance with the maximum output power density of 50 mW cm−2 at an operating voltage of 1 V than the direct borohydride-hydrogen peroxide fuel cell with carbon-supported Prussian Blue without CTAB with the maximum output power density of 29 mW cm−2 at an operating voltage of 1 V.

A Nonlinear Approach for Re-entry Guidance of Reusable Launch Vehicles Using Model Predictive Static Programming

A nonlinear suboptimal guidance scheme is developed for the reentry phase of the reusable launch vehicles. A recently developed methodology, named as model predictive static programming (MPSP), is implemented which combines the philosophies of nonlinear model predictive control theory and approximate dynamic programming. This technique provides a finite time nonlinear suboptimal guidance law which leads to a rapid solution of the guidance history update. It does not have to suffer from computational difficulties and can be implemented online. The system dynamics is propagated through the flight corridor to the end of the reentry phase considering energy as independent variable and angle of attack as the active control variable. All the terminal constraints are satisfied. Among the path constraints, the normal load is found to be very constrictive. Hence, an extra effort has been made to keep the normal load within a specified limit and monitoring its sensitivity to the perturbation.

Virus-Specific Cytolytic Antibodies to Nonstructural Protein 1 of Japanese Encephalitis Virus Effect Reduction of Virus Output from Infected Cells

We demonstrate the presence of nonstructural protein 1 (NS1)-specific antibodies in a significant proportion of convalescent-phase human serum samples obtained from a cohort in an area where Japanese encephalitis virus (JEV) is endemic. Sera containing antibodies to NS1 but not those with antibodies to other JEV proteins, such as envelope, brought about complement-mediated lysis of JEV-infected BHK-21 cells. Target cells infected with a recombinant poxvirus expressing JEV NS1 on the cell surface confirmed the NS1 specificity of cytolytic antibodies. Mouse anti-NS1 cytolytic sera caused a complement-dependent reduction in virus output from infected human cells, demonstrating their important role in viral control. Antibodies elicited by JEV NS1 did not cross lyse West Nile virus- or dengue virus-infected cells despite immunoprecipitating the NS1 proteins of these related flaviviruses. Additionally, JEV NS1 failed to bind complement factor H, in contrast to NS1 of West Nile virus, suggesting that the NS1 proteins of different flaviviruses have distinctly different mechanisms for interacting with the host. Our results also point to an important role for JEV NS1-specific human immune responses in protection against JE and provide a strong case for inclusion of the NS1 protein in next generation of JEV vaccines.

Kinetics of photocatalytic reduction of NO by CO with Pd2+-Ion-Substituted Nano-TiO2

The objective of the present study is to develop the reaction mechanism and kinetics of photoreduction of NO by CO. For this purpose, the reactions were conducted in the presence of Pd-ion-substituted nano-TiO2, Ti1-xPdxO2-delta, which was synthesized via a solution combustion method. The photocatalytic activity was investigated with unsubstituted TiO2, 1% Pd/TiO2(imp), and Ti1-xPdxO2-delta (where x = 0.05-0.3). No appreciable NO conversion was observed over unsubstituted TiO2, although, despite competitive adsorption of NO and CO on the Pd2+ sites, there was a significant reduction of NO over Ti1-xPdxO2-delta. The kinetic model showed that the enhanced catalytic activity is due to the NO photodissociation at the oxide-ion vacancy.

Laser damage studies in nonlinear optical crystal sodium p-nitrophenolate dihydrate

We report the surface laser damage threshold in sodium p-nitrophenolate dihydrate, a nonlinear optical crystal. The experiment is performed with a pulsed Nd:YAG laser in TEM00 mode. The single shot damage thresholds are 11.16 +/- 0.28GWcm(-2) and 1.25 +/- 0.02GWcm(-2) for 1064 nm and 532 nm laser wavelengths respectively. A close correlation between the laser damage threshold and mechanical hardness is observed. A possible mechanism of laser damage is discussed.