Integral sliding mode control for offshore steel jacket platforms

This paper is concerned with robust integral sliding mode control for an offshore steel jacket platforms subject to nonlinear wave-induced force and parameter perturbations. A robust integral sliding mode controller is designed to stabilize the dynamic model of the offshore steel jacket platform. It is shown through simulation results that the robust integral sliding mode control scheme can reduce the internal oscillations of the offshore steel jacket platform dramatically; and the performance of the offshore steel jacket platform under the robust integral sliding mode control scheme is better than the ones under the nonlinear control scheme and the dynamic output feedback control scheme.     

A four-neutrino mixing scheme for observed neutrino data

It has been observed that simultaneous explanation of the solar and atmospheric neutrino deficits and the reported evidence for oscillation from the Los Alamos Liquid Scintillator Detector (LSND) requires at least one extra neutrino species in addition to the three known ones. The extra neutrino must be sterile with respect to the known weak interactions. We present a new mass matrix for these four neutrinos in which the LSND effect and the atmospheric neutrino deficit are governed by only one parameter. We investigate the phenomenological implications of such a mass matrix ansatz and suggest possible ways to understand it in gauge theories.     

A high-fidelity memory scheme for quantum data buses

A novel quantum memory scheme is proposed for quantum data buses in scalable quantum computers by using adjustable interaction. Our investigation focuses on a hybrid quantum system including coupled flux qubits and a nitrogen–vacancy center ensemble. In our scheme, the transmission and storage(retrieval) of quantum state are performed in two separated steps, which can be controlled by adjusting the coupling strength between the computing unit and the quantum memory. The scheme can be used not only to reduce the time of quantum state transmission, but also to increase the robustness of the system with respect to detuning caused by magnetic noises. In comparison with the previous memory scheme, about 80% of the transmission time is saved. Moreover, it is exemplified that in our scheme the fidelity could achieve 0.99 even when there exists detuning, while the one in the previous scheme is 0.75.     

On the physical interpretation of statistical data from black-box systems

In this paper we explore the physical interpretation of statistical data collected from complex black-box systems. Given the output statistics of a black-box system, and considering a class of relevant Markov dynamics which are physically meaningful, we reverse-engineer the Markov dynamics to obtain an equilibrium distribution that coincides with the output statistics observed. This reverse-engineering scheme provides us with a conceptual physical interpretation of the black-box system investigated. Five specific reverse-engineering methodologies are developed, based on the following dynamics: Langevin, geometric Langevin, diffusion, growth-collapse, and decay-surge. In turn, these methodologies yield physical interpretations of the black-box system in terms of conceptual intrinsic forces, temperatures, and instabilities. The application of these methodologies is exemplified in the context of the distribution of wealth and income in human societies, which are outputs of the complex black-box system called “the economy”.     

On the interpretation of magnetization data for antiferromagnetic nanoparticles

We have investigated the influence of anisotropy on the magnetization curves of antiferromagnetic nanoparticles. We show that if such curves are analyzed in a conventional way, i.e. using a Langevin function in combination with a linear term, this usually results in good quality fits, but with an apparent temperature dependence of parameters such as the magnetic moment per particle and the antiferromagnetic susceptibility. In order to avoid the problems associated with anisotropy as well as volume/moment distributions we propose that the initial susceptibility is used when analyzing the temperature dependence of the magnetic moment.     

A high order multivariate approximation scheme for scattered data sets

We present a high order multivariate approximation scheme for scattered data sets. Each data point is represented as a Taylor series, and the high order derivatives in the Taylor series are treated as random variables. The approximation coefficients are then chosen to minimize an objective function at each point by solving an equality constrained least squares. The approximation is an interpolation when the data points are given as exact, or a nonlinear regression function when nonzero measurement errors are associated with the data points. Using this formulation, the gradient information on each data point can be used to significantly reduce the approximation error. All parameters of the approximation scheme can be computed automatically from the data points. An uncertainty bound of the approximation function is also produced by the scheme. Numerical experiments demonstrate that although this method is more computationally intensive than traditional methods, it produces more accurate approximation functions.     

Aspects of using the factor analysis for XPS data interpretation

In this work, the use of factor analysis to chemical state quantification of XPS data is studied. First, the theory of the method is reviewed with a special emphasis on the issues related to XPS data analysis. In particular, we concentrate on the transformation of the abstract components into physically meaningful ones in the case where reliable reference spectra are not available. We have observed that in the commonly used iterative target transformation factor analysis (ITTFA), in which a delta peak serves as the initial guess, the shape of the obtained component depends strongly on the position of the delta peak and on the minimum allowed intensity level. We propose an approach in which these parameters are varied in order to generate different representations for each component of the data. With simulated model data we show that if the variation is done with a sufficiently small step size, the correct representation will be generated. We also show that in the case of two-component data the iteration of the components is not necessary because a position can be found where a delta peak directly transforms into the correct component without unphysical features. Besides the model data, the proposed method is applied to experimental 2p photoelectron spectra of iron and chromium oxides.     

Enhanced visualization methods for interpretation of wind tunnel data

Journal of Visualization -     

A scheme for data encryption and transmission using temporal correlation-based spectral switches

We present a method for data encoding in terms of spectral shifts in the source spectra. The spectral switching of polychromatic light due to temporal correlation, around the intensity minima in a Michelson Interferometer (MI) has been utilized for this purpose. The potential application of the encoding method for free space communication is described in detail. The advantages of this method are compared with the proposed schemes of data communication using spectral switches. The experimental constraints of this method are also discussed.     

A three-dimensional vibroacoustic model for the prediction of underwater noise from offshore pile driving

Steel monopiles are nowadays widely used as foundations for a large number of offshore structures. The installation procedure commonly involves a pile driving process which can last up to several hours depending upon pile dimensions, soil conditions and input energy of the hydraulic hammer. In impact pile driving, a hydraulic hammer delivers a series of hammer blows at the head of the pile that drive the pile into the sediment. Each hammer strike results in pile vibrations that emit strong impulsive sounds into the water column which can be harmful for the marine ecosystem. With today's increasing concern regarding the environmental impact of such operations, engineering tools which will be able to provide reliable predictions of the underwater noise levels are required. In this study, a linear semi-analytical formulation of the coupled vibroacoustics of a complete pile–water–soil interaction model is addressed. The pile is described by a high order thin shell theory whereas both water and soil are modelled as three-dimensional continua. Results obtained with the developed model indicate that the near-field response in the water column consists mainly of pressure conical waves generated by the supersonic compressional waves in the pile excited by the impact hammer. The soil response is dominated by shear waves with almost vertical polarization. The Scholte waves are also generated at the water–seabed interface which can produce pressure fluctuations in the water column that are particularly significant close to the sea floor. The effects of soil elasticity and pile size are thoroughly investigated and their influence on the generated pressure levels is highlighted. The results are also compared with those ones of a similar model in which the soil is treated as an equivalent acoustic fluid. It is shown that the latter approximation can yield inaccurate results at low frequencies especially for harder soil sediments.     

On the interpretation of heavy-ion sub-barrier fusion data

We study the well-known deviation of measured fusion cross-sections below the barrier from predictions of one-dimensional tunnelling models. A simple parametrisation of measured excitation functions is discussed which allows to identify a smooth general trend depending only on gross nuclear properties. The parametrisation is substantiated by quantum mechanically exact calculations in a two-dimensional tunnelling model. Various possibilities for the geometrical interpretation of the second degree of freedom are discussed. Neck formation is identified as the most probable degree of freedom effecting the overall behavior of sub-barrier fusion.     

Replica-exchange Monte Carlo scheme for bayesian data analysis

We develop a sampling algorithm to explore the probability densities arising in Bayesian data analysis problems. Our algorithm is a multiparameter generalization of a replica-exchange Monte Carlo scheme. The strategy relies on gradual weighing of experimental data and on Tsallis generalized statistics. We demonstrate the effectiveness of the method on nuclear magnetic resonance data for a folded protein.     

The level scheme of143Nd and a unified-model interpretation

The structure of the nucleus¹⁴³Nd is studied using the¹⁴²Nd(d, p) reaction at a bombarding energy of 16.07 MeV. More than 80 levels are observed below 4.4 MeV excitation. Using DWBA calculationsl-values and spectroscopic factors are deduced for 50 levels. Detailed calculations using a unified-model and the macroscopic-microscopic Strutinsky method are performed in order to describe the negative and positive parity states. A very good agreement with the experimental data is found.     

Three flavour oscillation interpretation of neutrino data

I consider the mixing of the three active neutrino flavours and obtain the constraints on the parameters of this mixing from the solar, atmospheric and reactor neutrino data.     

A new interpretation for orthofermions

In this article we introduce a simple physical model which realizes the algebra of orthofermions. The model is constructed from a cylinder which can be filled with some balls. The creation and annihilation operators of orthofermions are related to the creation and annihilation operators of balls in certain positions in the cylinder. Relationship between this model and topological symmetries in quantum mechanics is investigated.     

Impact parameter interpretation of proton-proton scattering from a critical review of all ISR data

This paper contains a critical review of all the data produced at the ISR on proton-proton elastic scattering and total cross sections. This coherent and complete set of data is used to compute the impact parameter distribution of the proton-proton inelastic overlap integral. This impact parameter analysis has smaller errors than any other previously made, and confirms the good agreement with the geometrical scaling model while strongly disagreeing with models based on factorizing eikonals. For the first time we find indications of a second contribution to the peripheral rising of the proton-proton cross section in a region around 2.2 fm.     

A novel approach for crowd video monitoring of subway platforms

Crowd monitoring in a dense crowd scene has become an important and challenging topic in the field of video surveillance system. This paper proposes a novel crowd monitoring approach for subway platforms to address requirements in rail traffic management. Firstly, an improvement for Mixture Gaussian background modeling is presented to segment the crowd. In the process of feature extraction, the concept of the weighted area is proposed to solve the problem of the perspective of images. To deal with the issue of the occlusion between individuals, an improved gradient feature is developed in this paper. And then, Adaptive Boost classifier with the feature weighted area and the improved gradient is used to estimate the crowd density. Finally, the crowd is counted by the method of linear regression. The experimental results show that the proposed approach is feasible and effective for crowd monitoring in real subway platforms.     

A rational interpretation of the dirac equation for the electron

Rationalization of the interpretation of the Dirac equation for the electron lies beyond the conventional scope of quantum mechanics. This difficulty motivates a revision of the system of quantum mechanics through which the indeterministic trait is eliminated from the system.