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This paper aims to present the spherical entropy image (SEI), a novel global descriptor for the scan registration of three-dimensional (3D) point clouds. This paper also introduces a global feature-less scan registration strategy based on SEI. It is advantageous for 3D data processing in the scenarios such as mobile robotics and reverse engineering.

The descriptor works through representing the scan by a spherical function named SEI, whose properties allow to decompose the six-dimensional transformation into 3D rotation and 3D translation. The 3D rotation is estimated by the generalized convolution theorem based on the spherical Fourier transform of SEI. Then, the translation recovery is determined by phase only matched filtering.

No explicit features and planar segments should be contained in the input data of the method. The experimental results illustrate the parameter independence, high reliability and efficiency of the novel algorithm in registration of feature-less scans.

A novel global descriptor (SEI) for the scan registration of 3D point clouds is presented. It inherits both descriptive power of signature-based methods and robustness of histogram-based methods. A high reliability and efficiency registration method of scans based on SEI is also demonstrated.

The purpose of this paper is to explore the variation law between the clay microstructure and macro external force by using soil scanning electron microscope (SEM) images.

First, SEM images of clay were pre-processed by MATLAB, and quantitative statistical parameters such as directional probability entropy, fractal dimension and shape factor are extracted. Second, the distribution force model was proposed, considering that the microscopic parameters of soil particles were independent of each other, and the distribution coefficient was determined according to the analytic hierarchy process (AHP). Then, the fitted formula of quantitative statistical parameters based on the distribution force model was obtained by taking the macroscopic distribution force as independent variable and the microscopic parameters of soil particles as dependent variable. Finally, the correctness of corresponding fitting formula was verified.

The results showed that the change of external consolidation pressure has great influence on the directional probability entropy and fractal dimension, while the shape factor reflecting the regular degree of soil particle shape is less sensitive to the consolidation pressure. The fitting formula has high accuracy, and mostly the R value can reach more than 0.9. All the data have passed the test, which proves that the distribution force model proposed in this paper is rational.

The model can be used to connect the macroscopic stress of soil with the micro-structure deformation of soil particles through mathematical formula, which can provide reference for engineering practice.

The purpose of this paper is to develop an efficient online monitoring system. It can improve the welding quality through the real‐time analysis of the welding image information.

In this paper, a set‐variable precision rough set (VPRS) modeling method was improved and the prediction model of back‐side bead width dynamic response for robotic arc welding process is proposed. Back‐side width based on the vision sensor in the compound controller is used. Meantime, a compound intelligent controller is designed with the wire‐feeding rate compensation.

The dynamical information of the top‐side weld pool can be captured in real‐time. Moreover, VPRS prediction model could provide the back‐side bead width of the weld, which integrated with the fuzzy neural network controller. Therefore, more uniform weld penetration can be achieved with the variation of the assembling gap.

The monitor system requires that the information of the weld pool and the front gap can be extracted precisely. Moreover, the front assembling gap should be limited in a certain interval [0∼3 mm]. This puts forward high request to image processing algorithm and the assembling of the work‐piece.

This monitor system is applicable to the manufacturing of the spherical head petals in rocket storage tank.

The paper demonstrates that the compound intelligent controller based on the VPRS prediction is possible and effective. The experiments show that the real‐time and precision requirements for monitoring and control of weld quality can be satisfied by using this online control system during welding process.

There is a double crisis in modern science and in particular in physics and mechanics. Among others Einstein and Stephane Lupasco, in the 1930s, warned about this crisis. The Quantum Theory cannot be reconciled with the Relativity Theory. Specifically there is a gap (cleavage) between micro – and macro‐physics and mechanics. Parallel or beneath there is also a second crisis derived from a discontinuity (again a cleavage) between classical and modern science, that is between two previous revolutions. A new research programme of a simultaneous equilibrium versus disequilibrium approach, initially applied in economics has now been extended to include natural sciences. It is the question of a new, more comprehensive methodology which is actually a sui generis synthesis between classical and modern heritage. The rigorous application of the new research programme leads to the organisation of an Orientation Table, that is, a methodological map of all possible combinations (systems). The Table shows, without any exaggeration, a few revolutionary results. For instance, with the help of the Table, modern science or the second revolution (Einstein, Bohr, Heisenberg) does not appear contradictory but rather complementary to classical science or the first revolution (Newton, Lavoisier). The Kuhnian thesis to the contrary is disproved and the second crisis is solved. With the help of the Universal Hypothesis of Duality (the basis of the Orientation Table), matter and energy, at the micro – and macro‐level, appear in a double form (the Principle of Duality): stable (equilibrium) particles and unstable (disequilibrium) waves. The strong interactions from modern physics are associated with the law of gravitation (attraction) or stable equilibrium which governs stable matter and energy. The weak interactions are associated with the law of disgravitation (dispersion or repulsion) including entropy or unstable equilibrium which governs unstable matter and energy. In this way the first crisis is also solved.

Attempts to prove, in this second chapter of the author’s monograph, that with a new research programme, it is possible to build a methodological bridge between economics and all other natural sciences and the scientists should address this challenge. Reviews basic principles that govern nature, including Einstein’s findings along with such luminaries as Copernicus, Newton, Galileo and Jeans. Concludes that the future is safe, as a new generation of scientists is now emerging in the East and the West, and that the new methodology should provide enough space for new roads, ideas and interpretations, which may occur in the future. Closes by saying a new spirit should be initiated in economics and transplanted into natural sciences.

Nowadays, most methods of illusion garment evaluation are based on the subjective evaluation of experienced practitioners, which consumes time and the results are too subjective to be accurate enough. It is necessary to explore a method that can quantify professional experience into objective indicators to evaluate the sensory comfort of the optical illusion skirt quickly and accurately. The purpose of this paper is to propose a method to objectively evaluate the sensory comfort of optical illusion skirt patterns by combining texture feature extraction and prediction model construction.

Firstly, 10 optical illusion sample skirts are produced, and 10 experimental images are collected for each sample skirt. Then a Likert five-level evaluation scale is designed to obtain the sensory comfort level of each skirt through the questionnaire survey. Synchronously, the coarseness, contrast, directionality, line-likeness, regularity and roughness of the sample image are calculated based on Tamura texture feature algorithm, and the mean, contrast and entropy are extracted of the image transformed by Gabor wavelet. Both are set as objective parameters. Two final indicators T1 and T2 are refined from the objective parameters previously obtained to construct the predictive model of the subjective comfort of the visual illusion skirt. The linear regression model and the MLP neural network model are constructed.

Results show that the accuracy of the linear regression model is 92%, and prediction accuracy of the MLP neural network model is 97.9%. It is feasible to use Tamura texture features, Gabor wavelet transform and MLP neural network methods to objectively predict the sensory comfort of visual illusion skirt images.

Compared with the existing uncertain and non-reproducible subjective evaluation of optical illusion clothing based on experienced experts. The main advantage of the authors' method is that this method can objectively obtain evaluation parameters, quickly and accurately obtain evaluation grades without repeated evaluation by experienced experts. It is a method of objectively quantifying the experience of experts.

The main purpose of this work is to arrive at a three-dimensional (3D) numerical solution on mixed convection in a cubic cavity with a longitudinally located triangular fin in different sides.

The 3D governing equations are solved via finite volume technique by writing a code in FORTRAN platform. The governing parameters are chosen as Richardson number, 0.01 ≤ Ri ≤ 10 and thermal conductivity ratio 0.01 ≤ Rc ≤ 100 for fixed parameters of Pr = 0.7 and Re = 100. Two cases are considered for a lid-driven wall from left to right (V+) and right to left (V−).

It is observed that entropy generation due to heat transfer becomes dominant onto entropy generation because of fluid friction. The most important parameter is the direction of the moving lid, and lower values are obtained when the lid moves from right to left.

The main originality of this work is to arrive at a solution of a 3D problem of mixed convection and entropy generation for lid-driven cavity with conductive triangular fin attachments.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.