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To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM).

By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam.

Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models.

The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields.

An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.

The meshfree node-based smoothed point interpolation method (NS-PIM) is extended to the forward and inversion analysis of a high gravelly soil core rock-fill dam during construction periods.

As one member of the meshfree methods, the NS-PIM has the advantages of “softer” stiffness and adaptability to large deformations which is quite indispensable for the stability analysis of rock-fill dams. In this work, the present method contains a reconstruction procedure to deal with the existence or nonexistence of the construction layers. After verifying the validity of the NS-PIM method for nonlinear elastic model during construction period, the convergence features of the NS-PIM and FEM methods are further investigated with different mesh schemes. Furthermore, the NS-PIM and FEM methods are applied for the forward analysis of a high gravelly soil core rock-fill dam and the convergence features under complex stress conditions are also studied using the rock-fill dam model. Finally, the NS-PIM method is used to calculate the Duncan–Chang parameters of the deep overburden under the high gravelly soil core rock-fill dam based on the back-propagation neural network method.

The results show that: the NS-PIM solution for construction analysis still possesses the property of upper bound solution even under complex stress conditions and can provide comparatively more conservative results for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution; the inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction period and the calculated results show good agreement with the measured displacement values and it is feasible to apply the NS-PIM to the forward and inversion analysis of high rock-fill dams on deep overburden during construction periods.

In further study, the feasibility of three-dimensional problems, elastic–plastic problems, contact problems and multipoint inversion can still be probed in the NS-PIM solution for the forward and inversion analysis of high rock-fill dams on deep overburden.

This paper introduced a method for the forward and inversion analysis of high rock-fill dams during construction period using the NS-PIM solution. The property of upper bound solution ensures that the NS-PIM can provide more conservative results for safety evaluation. The inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction periods.

First, the analysis from forward to inversion for high rock-fill dams during construction period using the NS-PIM solution is accomplished in this work. A procedure dealing with the existence or nonexistence of the construction layers is also developed for the construction analysis. Second, it is confirmed in this work that the NS-PIM still possesses the property of upper bound solution even under complex stress conditions (the forward analysis of high rock-fill dams during construction period). Thus, more conservative results can be provided for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution. Third, the calculated material parameters of the deep overburden in this work can be used for further studies of the high rock-fill dam.

The purpose of this paper is to present an analytical model and simulation for cylindrical gate all around MOSFTEs including quantum effects.

To incorporating the impact of quantum effects, the authors have used variational method for solving the Poisson and Schrodinger equations. The accuracy of the results obtained using this model is verified by comparing them with simulation results.

This model is developed to provide an analytical expression for inversion charge distribution function for all regions of device operation. This expression is used to calculate the other important parameters like inversion charge centroid, threshold voltage, inversion charge, gate capacitance and drain current. The calculated expressions for the above parameters are simple and accurate. The validity of this model was checked for the devices with different dimensions and bias voltages.

Simulation based on the compact physical models reduces the cost of developing a sophisticated fabrication technology and shortens the time-to-market. They may also be utilized to explore innovative device structures.

This paper presents, for the first time, a compact quantum analytical model for cylindrical surrounding gate MOSFETs which predicts the device characteristics reasonably well over the entire range of device operation (above threshold as well as sub-threshold region).

The purpose of this paper is to apply the Steady State Kalman Filter for temperature measurements of tissues via magnetic resonance thermometry. Instead of using classical direct inversion, a methodology is proposed that couples the magnetic resonance thermometry with the bioheat transfer problem and the local temperatures can be identified through the solution of a state estimation problem.

Heat transfer in the tissues is given by Pennes’ bioheat transfer model, while the Proton Resonance Frequency (PRF)-Shift technique is used for the magnetic resonance thermometry. The problem of measuring the transient temperature field of tissues is recast as a state estimation problem and is solved through the Steady-State Kalman filter. Noisy synthetic measurements are used for testing the proposed methodology.

The proposed approach is more accurate for recovering the local transient temperatures from the noisy PRF-Shift measurements than the direct data inversion. The methodology used here can be applied in real time due to the reduced computational cost. Idealized test cases are examined that include the actual geometry of a forearm.

The solution of the state estimation problem recovers the temperature variations in the region more accurately than the direct inversion. Besides that, the estimation of the temperature field in the region was possible with the solution of the state estimation problem via the Steady-State Kalman filter, but not with the direct inversion.

The recursive equations of the Steady-State Kalman filter can be calculated in computational times smaller than the supposed physical times, thus demonstrating that the present approach can be used for real-time applications, such as in control of the heating source in the hyperthermia treatment of cancer.

The original and novel contributions of the manuscript include: formulation of the PRF-Shift thermometry as a state estimation problem, which results in reduced uncertainties of the temperature variation as compared to the classical direct inversion; estimation of the actual temperature in the region with the solution of the state estimation problem, which is not possible with the direct inversion that is limited to the identification of the temperature variation; solution of the state estimation problem with the Steady-State Kalman filter, which allows for fast computations and real-time calculations.

Looks at the interrelationship between resonance, probability and feedback and describes how we can control and direct them – the very essence of cybernetics – by using musical science to explain their causes and effects.

The purpose of this paper is to present the progress and trends of the literature on art as an investment and to outline potential research lines to be developed.

This work gathers, analyses and critically discusses the attributes of investments in art in general, and in Latin American art in particular.

Most studies report that art (art in general, and Latin American in particular) has offered relatively low but positive real returns, which have tended to be below those offered by stocks and similar to those realized by bonds. Art has a low correlation with other investments.

The literature on the attributes of Latin American art as an investment is limited and new research would help to close the knowledge gap with respect to this segment of the art market as it continues to grow.

Similarly to the research carried out into other segments of the art market, studies on Latin American art suggest that the works of art are worth more, ceteris paribus: the more renowned the artist, the larger the work, whether they were executed in oil, and if they were auctioned at Sotheby’s or Christie’s. The paper also details a series of practical implications for those who participate in the art market.

To the best of the authors’ knowledge, this is the first exhaustive review of the literature on the attributes of Latin American art as an investment. The findings of this study are useful for academics, art collectors, auction houses, gallerists and others who take part in the arts market.

Presentar los avances y las tendencias de la literatura sobre el arte como inversión, y delinear líneas de investigación a ser desarrolladas.

Este trabajo reúne, analiza y discute críticamente los atributos de inversión del arte, en general, y latinoamericano, en particular.

La mayoría de los estudios reportan que el arte (tanto el arte, en general, como el arte latinoamericano, en particular) ha ofrecido rendimientos reales positivos, aunque relativamente bajos, los cuales tienden a ser inferiores de los de las acciones y a ser similares a los de los bonos. El arte tiene una baja correlación con otras inversiones.

La literatura sobre los atributos del arte latinoamericano como inversión es limitada. Es de esperar que nuevas investigaciones permitan ir cerrando la brecha del conocimiento con respecto a esta parte del mercado del arte a la par que éste continúe creciendo.

Los estudios de arte latinoamericano sugieren, similar a las investigaciones sobre otros segmentos del mercado del arte, que las obras de arte valen más, ceteris paribus: cuando el artista es más reputado, a medida que el área de las obras es mayor, si han sido ejecutadas en óleo, y cuando son subastadas en las casas de subastas Sotheby’s o Christie’s. En el trabajo se detallan, además, una serie de implicaciones prácticas para los participantes del mercado de arte.

Hasta donde se ha podido comprobar, esta es la primera revisión exhaustiva acerca de los atributos del arte latinoamericano como inversión. Los resultados de esta investigación son de utilidad para: académicos, coleccionistas de arte, casas de subastas, galeristas, y demás participantes en el mercado del arte.

This paper attempts to establish the grey GM(0,N) estimation model of the soil organic matter content spectral inversion under the uncertainties between soil organic matter contents and spectral characteristics and the theory of grey system.

At first, based on the uncertainty of the relationship between the soil organic matter content and spectral characteristics, using the ordered grey accumulation generation and grey GM(0, N) model to establish hyper‐spectral grey estimation model of soil organic matter content. Second, the presented model is used to estimate soil organic matter of Hengshan County in Shanxi province in the last part of the paper.

The results are convincing: not only that soil organic matter content spectral inversion grey GM(0, N) model based on the ordered grey accumulation generation theory is valid, but also the model's prediction accuracy is higher, with the sample's average prediction accuracy being 93.662 per cent.

The method exposed in the paper can be used on soil organic matter content hyper‐spectral inversion and even for other similar forecast problems.

The paper succeeds in realising both prediction pattern and application of soil organic matter content hyper‐spectral inversion by using the newest developed theories: grey GM(0, N) model based on the ordered grey accumulation generation.

In the present study we introduce a new recursive matrix inversion (RMI) algorithm for a distributed memory computer. The RMI algorithm was designed to meet the requirements of high performance flexible software for implementing different parallel optimization algorithms. Special consideration has been taken to ensure the usability and portability of the algorithm. The results we present show that a significant improvement in performance is attainable over the LU‐factorization algorithm included in the LAPACK library.

The purpose of this paper is to establish the grey‐weighted relationship prediction pattern of the soil organic matter content spectral inversion under the uncertainties between soil organic matter contents and spectral characteristics and the theory of grey system.

At first, according to grey‐weighted distance, a new grey relationship model is presented. Second, in order to make full use of the information of grey relationship sequences, the maximum grey relationship discrimination principle is improved and then the soil organic matter content spectral inversion pattern is put forward based on weighted grey recognition theory. A numeric example of Hengshan County in Shanxi Province is also computed in the last part of the paper.

The results are convincing: not only that soil organic matter content spectral inversion pattern based on the weighted grey recognition theory is valid, but also the model's prediction accuracy is higher; the sample's average prediction accuracy is 94.917 per cent.

The method exposed in the paper can be used at soil organic matter content hyper‐spectral inversion and even for other similar forecast problems.

The paper succeeds in realising both prediction pattern and application of soil organic matter content hyper‐spectral inversion by using the newest developed theories: weighted grey recognition theory.

By generalizing the equation of state of the conduction electron gas in a semiconductor to include a dependence not only on electron density but also on the density gradient we show that the standard diffusion‐drift description can be extended to describe much of the quantum mechanical behavior exhibited by strong inversion layers.