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This paper aims to characterize the mineral composition of Martian surfaces based on Thermal Emission Spectrometer (TES; Mars Global Surveyor) as measured in the infrared thermal range. It presents modeling and interpreting of TES spectral data from selected Martian regions from which the atmospheric influences had been removed using radiative transfer algorithm and deconvolution algorithm. The spectra from the dark area of Cimmeria Terra and the bright Isidis Planitia were developed in Philip Christensen’s and Joshua Bandfield’s publications, where these spectra were subjected to spectral deconvolution to estimate the mineral composition of the Martian surface. The results of the analyses of these spectra were used for the modeling of dusty and non-dusty surface of Mars. As an additional source, the mineral compositions of Polish basalts and mafic rocks were used for these surfaces as well as for modeling Martian meteorites Shergottites, Nakhlites and Chassignites. Finally, the spectra for the modeling of the Hellas region were obtained from the Planetary Fourier Spectrometer (PFS) – (Mars Express) and the mineralogical compositions of basalts from the southern part of Poland were used for this purpose. The Hellas region was modeled also using simulated Martian soil samples Phyllosilicatic Mars Regolith Simulant and Sulfatic Mars Regolith Simulant, showing as a result that the composition of this selected area has a high content of sulfates. Linear spectral combination was chosen as the best modeling method. The modeling was performed using PFSLook software written in the Space Research Centre of the Polish Academy of Sciences. Additional measurements were made with an infrared spectrometer in thermal infrared spectroscopy, for comparison with the measurements of PFS and TES. The research uses a kind of modeling that successfully matches mineralogical composition to the measured spectrum from the surface of Mars, which is the main goal of the publication. This method is used for areas where sample collection is not yet possible. The areas have been chosen based on public availability of the data.

The infrared spectra of the Martian surface were modeled by applying the linear combination of the spectra of selected minerals, which then are normalized against the measured surface area with previously separated atmosphere. The minerals for modeling are selected based on the expected composition of the Martian rocks, such as basalt. The software used for this purpose was PFSLook, a program written in C++ at the Space Research Centre of the Polish Academy of Sciences, which is based on adding the spectra of minerals in the relevant percentage, resulting in a final spectrum containing 100 per cent of the minerals.

The results of this work confirmed that there is a relationship between the modeled, altered and unaltered, basaltic surface and the measured spectrum from Martian instruments. Spectral deconvolution makes it possible to interpret the measured spectra from areas that are potentially difficult to explore or to choose interesting areas to explore on site. The method is described for mid-infrared because of software availability, but it can be successfully applied to shortwave spectra in near-infrared (NIR) band for data from the currently functioning Martian spectroscopes.

This work is the only one attempting modeling the spectra of the surface of Mars with a separated atmosphere and to determine the mineralogical composition.

This paper aims to demonstrate the principle and practical applications of hyperspectral object detection, carry out the problem we now face and the possible solution. Also some challenges in this field are discussed.

First, the paper summarized the current research status of the hyperspectral techniques. Then, the paper demonstrated the development of underwater hyperspectral techniques from three major aspects, which are UHI preprocess, unmixing and applications. Finally, the paper presents a conclusion of applications of hyperspectral imaging and future research directions.

Various methods and scenarios for underwater object detection with hyperspectral imaging are compared, which include preprocessing, unmixing and classification. A summary is made to demonstrate the application scope and results of different methods, which may play an important role in the application of underwater hyperspectral object detection in the future.

This paper introduced several methods of hyperspectral image process, give out the conclusion of the advantages and disadvantages of each method, then demonstrated the challenges we face and the possible way to deal with them.

The purpose of this paper is to study the steady laminar flow of a pressure driven third‐grade fluid with heat transfer in a horizontal channel. The study serves two purposes: to correct the inaccurate results presented in Siddiqui et al., where the homotopy perturbation method was used, and to demonstrate the computational efficiency and accuracy of the spectral‐homotopy analysis methods (SHAM and MSHAM) in solving problems that arise in fluid mechanics.

Exact and approximate analytical series solutions of the non‐linear equations that govern the flow of a steady laminar flow of a third grade fluid through a horizontal channel are constructed using the homotopy analysis method and two new modifications of this method. These solutions are compared to the full numerical results. A new method for calculating the optimum value of the embedded auxiliary parameter ∼ is proposed.

The “standard” HAM and the two modifications of the HAM (the SHAM and the MSHAM) lead to faster convergence when compared to the homotopy perturbation method. The paper shows that when the same initial approximation is used, the HAM and the SHAM give identical results. Nonetheless, the advantage of the SHAM is that it eliminates the restriction of searching for solutions to the nonlinear equations in terms of prescribed solution forms that conform to the rule of solution expression and the rule of coefficient ergodicity. In addition, an alternative and more efficient implementation of the SHAM (referred to as the MSHAM) converges much faster, and for all parameter values.

The spectral modification of the homotopy analysis method is a new procedure that has been shown to work efficiently for fluid flow problems in bounded domains. It however remains to be generalized and verified for more complicated nonlinear problems.

The spectral‐HAM has already been proposed and implemented by the authors in a recent paper. This paper serves the purpose of verifying and demonstrating the utility of the new spectral modification of the HAM in solving problems that arise in fluid mechanics. The MSHAM is a further modification of the SHAM to speed up converge and to allow for convergence for a much wider range of system parameter values. The utility of these methods has not been tested and verified for systems of nonlinear equations. For this reason as much emphasis has been placed on proving the reliability and validity of the solution techniques as on the physics of the problem.

This paper aims to provide a framework of the supervised hyperspectral classification, to study the traditional flowchart of hyperspectral image (HIS) analysis and processing. HSI technology has been proposed for many years, and the applications of this technology were promoted by technical advancements.

First, the properties and current situation of hyperspectral technology are summarized. Then, this paper introduces a series of common classification approaches. In addition, a comparison of different classification approaches on real hyperspectral data is conducted. Finally, this survey presents a discussion on the classification results and points out the classification development tendency.

The core of this survey is to review of the state of the art of the classification for hyperspectral images, to study the performance and efficiency of certain implementation measures and to point out the challenges still exist.

The study categorized the supervised classification for hyperspectral images, demonstrated the comparisons among these methods and pointed out the challenges that still exist.

The dynamics of coupling between spectrum and resolvent under ε‐perturbations of operator and matrix spectra are studied both theoretically and numerically. The phenomenon of non‐trivial pseudospectra encountered in these dynamics is treated by relating information in the complex plane to the behaviour of operators and matrices. On a number of numerical results we show how an intrinsic blend of theory with symbolic and numerical computations can be used effectively for the analysis of spectral problems arising from engineering applications.

The purpose of this paper is to predict and control the composition during laser additive manufacturing, since composition control is important for parts manufactured by laser additive manufacturing. Aluminum and steel functionally graded material (FGM) were manufactured by laser metal deposition, and the composition was analyzed by means of spectral analysis simultaneously.

The laser metal deposition process was carried out on a 5 mm thick 316L plate. Spectral line intensity ratio and plasma temperature were chosen as two main spectroscopic diagnosis parameters to predict the compositional variation. Single-trace single-layer experiments and single-trace multi-layer experiments were done, respectively, to test the feasibility of the spectral diagnosis method.

Experiment results showed that with the composition of metal powder changing from steel to aluminum, the spectral intensity ratio of the characteristic spectral line is proportional to the elemental content in the plasma. When the composition of deposition layers changed, the characteristic spectrum line intensity ratio changed obviously. And the linear chemical composition analysis results confirmed the gradient composition variation of the additive manufacturing parts. The results verified the feasibility of composition analysis based on spectral information in the laser additive manufacturing process.

The composition content of aluminum and steel FGM was diagnosed by spectral information during laser metal deposition, and the relationship between spectral intensity and composition was established.

In order to overcome the uncertainty and improve the accuracy of spectral estimation, this paper aims to establish a grey fuzzy prediction model of soil organic matter content by using grey theory and fuzzy theory.

Based on the data of 121 soil samples from Zhangqiu district and Jiyang district of Jinan City, Shandong Province, firstly, the soil spectral data are transformed by spectral transformation methods, and the spectral estimation factors are selected according to the principle of maximum correlation. Then, the generalized greyness of interval grey number is used to modify the estimation factors of modeling samples and test samples to improve the correlation. Finally, the hyper-spectral prediction model of soil organic matter is established by using the fuzzy recognition theory, and the model is optimized by adjusting the fuzzy classification number, and the estimation accuracy of the model is evaluated using the mean relative error and the determination coefficient.

The results show that the generalized greyness of interval grey number can effectively improve the correlation between soil organic matter content and estimation factors, and the accuracy of the proposed model and test samples are significantly improved, where the determination coefficient R² = 0.9213 and the mean relative error (MRE) = 6.3630% of 20 test samples. The research shows that the grey fuzzy prediction model proposed in this paper is feasible and effective, and provides a new way for hyper-spectral estimation of soil organic matter content.

The research shows that the grey fuzzy prediction model proposed in this paper can not only effectively deal with the three types of uncertainties in spectral estimation, but also realize the correction of estimation factors, which is helpful to improve the accuracy of modeling estimation. The research result enriches the theory and method of soil spectral estimation, and it also provides a new idea to deal with the three kinds of uncertainty in the prediction problem by using the three kinds of uncertainty theory.

The paper succeeds in realizing both the grey fuzzy prediction model for hyper-spectral estimating soil organic matter content and effectively dealing with the randomness, fuzziness and grey uncertainty in spectral estimation.

The research is directed at development of an efficient and accurate technique for modelling incompressible free surface flows in which viscous effects may not be neglected. The paper describes the methodology, and gives illustrative results for simple geometries.

The pseudospectral matrix element method of discretisation is selected as the basis for the CFD technique adopted, because of its high spectral accuracy. It is implemented as a means of solving the Navier‐Stokes equations coupled with the modified compressibility method.

The viscous solver has been validated for the benchmark cases of uniform flow past a cylinder at a Reynolds number of 40, and 2D cavity flows. Results for sloshing of a viscous fluid in a tank have been successfully compared with those from a linearised analytical solution. Application of the method is illustrated by the results for the interaction of an impulsive wave with a surface piercing circular cylinder in a cylindrical tank.

The paper demonstrates the viability of the approach adopted. The limitation of small amplitude waves should be tackled in future work.

The results will have particular significance in the context of validating computations from more complex schemes applicable to arbitrary geometries.

The new methodology and results are of interest to the community of those developing numerical models of flow past marine structures.

The transient simulation of integrated circuit has become very expensive in terms of computer time due to increase in the number of transistors in typical simulation. Spectral technique and Chebyshev polynomials offers an efficient alternative algorithm for simulation of integrated circuits. In this paper an automatic formulation of circuit elements and transistor models, built in MOS technology, for analysis using spectral technique is presented. The algorithm is implemented and the simulation is proven to require less computer time than in the case of SPICE or ASTAP

This paper aims to estimate the corrosion rate of the carbon steel in crude oil using the electrochemical noise (EN) analysis technique.

EN measurements and electrochemical impedance (EIS) spectroscopy were employed to study the corrosion behaviour of carbon steel in crude oil and the optimum conditions of the noise analysis for estimating corrosion rate of the carbon steel are discussed. The time series noise patterns were transformed into frequency domains by fast Fourier transformation, and then their power spectrum densities (PSDs) at a frequency were determined to be compared with the corrosion rate.

The PSDs of the potential and of the current varied with changing of rotation rate of electrode and immersion time. Square roots of the PSDs for the potential difference and for the currents were in positive and almost linear correlation with the corrosion rate obtained from EIS plots. In addition, the spectral noise was negatively and linearly correlated with the corrosion rate. The relationship between the corrosion rate and the spectral noise resistance was better at lower frequencies.

It is suggested that this research is carried out for crude oils with other physical and chemical characteristics.

The PSD value at 3 mHz from the noise of the current and the spectral noise resistance at the same frequency are the optimum conditions for estimating corrosion rate in this research.

This paper arguably fills a gap in the current understanding of the interactions between corrosive species commonly found in crude feedstocks and process streams.