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This paper is devoted to the evaluation of the T-stress for a hypocycloid hole in an infinite plate. The remote tractions are applied for the infinite plate containing the hypocycloid hole. After using the conformal mapping, an elasticity solution is obtained, and the T-stress at the cusp tip can be abstracted from this solution. The paper aims to discuss these issues.

Conformal mapping technique is used for solving the T-stress problem for a hypocycloid cusp hole problem.

The present study proves that the cusp configuration has a significant influence to the value of T-stress at cusp crack tip.

A closed form solution for the T-stress in cusp crack is first obtained in the submission.

The purpose of this paper is to introduce a significant modification of the sensitivity maps calculation process using electric field distribution analysis. A sensitivity matrix is typically a crucial part of a deterministic image reconstruction process in a three-dimensional capacitance tomography (3D ECT) and strictly decides about a final image quality. Commonly used sensitivity matrix computation methods mostly provide acceptable results and additionally allow to perform a recalculation of sensitivity maps according to the changing permittivity distribution.

The new “tunnel-based” algorithm is proposed which traces the surfaces constructed along the electric field lines. The new solution is developed and tested using experimental data.

To fully validate the new technique both linear and non-linear image reconstruction processes were performed and the criteria of image error estimation were discussed. This paper discusses some preliminary results of the image reconstruction process using the new proposed algorithm. As a result of this research, an increased accuracy of the new method is proved.

The presented results of image reconstruction with new sensitivity matrix in comparison with the classic matrix proved that the new solution is able to improve the convergence and stability of image reconstruction process for 3D ECT imaging.

Crude oil separation is an important process in the oil industry. To make efficient use of the separators, it is important to know their internal behaviour, and to measure the levels of multi‐interfaces between different materials, such as gas‐foam, foam‐oil, oil‐emulsion, emulsion‐water and water‐solids. To develop a multi‐interface level sensor.

Multi‐modality sensor with segmented capacitance and electromagnetic sensing elements. Some key issues are addressed, including the effect of salt content in water on measurement.

Working with gas/oil/saline water, the simulation and experimental results show that the newly designed sensor is promising.

First time to present this multi‐modality sensor, which can cope with current problems with saline water.

Different from manufacturing resources allocation problems, the prices and amounts of limited public service resources could not be changed with the consumers’ requirements and social fairness is the most important objective for improving allocation efficiency. To measure social fairness reasonably, the purpose of this paper is fourfold: first, divide social fairness into longitudinal comparative fairness and crosswise comparative fairness, therefore providing their calculation formula and describing the comprehensive fair degree by using the interval numbers. Second, the comparison regulations of interval numbers are given and the corresponding features are also described. Third, an extension of VIKOR method is put forward for evaluating social fairness of different allocation alternatives with interval numbers. Finally, a numerical example illustrates the proposed method and clarifies the main results developed in the paper.

In this paper, the author depicts the social fair degree as an interval number, and thus proposes the comparison method between any two interval numbers. Based on the basis procedure of the VIKOR method, the paper proposes an extension of the fuzzy VIKOR method with the interval numbers to rank and select the compromise allocation alternatives. Finally, a numerical example illustrates the practicability of the proposed method.

The comparison of interval numbers is very important when the author evaluates the decision alternatives. Through analyzing the present comparison methods, the paper proposes the simple method of comparing the interval numbers, which can obtain the same results with the above two methods. The fuzzy VIKOR method, a popular multi-criteria decision-making method, focusses on ranking and selecting from a set of alternatives in a fuzzy environment. For the fuzzy value, the paper also proposes the extension of the VIKOR method to perform an evaluation and get the compromise alternatives.

According to the huge customers’ requirement, how to improve their social fair degree has become the focus in public service resources allocation, where the social fair degree may be a comprehensive concept which includes the fair degree compared with all the other allocation alternatives and the fair degree compared with the other small group under the same allocation alternative. In the paper, the author defines the above two types of fair degree and then depicts the comprehensive fair degree as their integration, which will be interval numbers.

Internet technology allows millions of people to find high quality medical resources online, with the result that personal healthcare and medical services have become one of the fastest growing markets in China. Data relating to healthcare search behavior may provide insights that could lead to better provision of healthcare services. However, discrepancies often arise between terminologies derived from professional medical domain knowledge and the more colloquial terms that users adopt when searching for information about ailments. This can make it difficult to match healthcare queries with doctors’ keywords in online medical searches. The paper aims to discuss these issues.

To help address this problem, the authors propose a transfer learning using latent factor graph (TLLFG), which can learn the descriptions of ailments used in internet searches and match them to the most appropriate formal medical keywords.

Experiments show that the TLLFG outperforms competing algorithms in incorporating both medical domain knowledge and patient-doctor Q&A data from online services into a unified latent layer capable of bridging the gap between lay enquiries and professionally expressed information sources, and make more accurate analysis of online users’ symptom descriptions. The authors conclude with a brief discussion of some of the ways in which the model may support online applications and connect offline medical services.

The authors used an online medical searching application to verify the proposed model. The model can bridge users’ long-tailed description with doctors’ formal medical keywords. Online experiments show that TLLFG can significantly improve the searching experience of both users and medical service providers compared with traditional machine learning methods. The research provides a helpful example of the use of domain knowledge to optimize searching or recommendation experiences.

The authors use transfer learning to map online users’ long-tail queries onto medical domain knowledge, significantly improving the relevance of queries and keywords in a search system reliant on sponsored links.

The purpose of this paper is to explore gas/liquid two-phase flow is widely existed in industrial fields, especially in chemical engineering. Electrical resistance tomography (ERT) is considered to be one of the most promising techniques to monitor the transient flow process because of its advantages such as fast respond speed and cross-section imaging. However, maintaining high resolution in space together with low cost is still challenging for two-phase flow imaging because of the ill-conditioning of ERT inverse problem.

In this paper, a sparse reconstruction (SR) method based on the learned dictionary has been proposed for ERT, to accurately monitor the transient flow process of gas/liquid two-phase flow in a pipeline. The high-level representation of the conductivity distributions for typical flow regimes can be extracted based on denoising the deep extreme learning machine (DDELM) model, which is used as prior information for dictionary learning.

The results from simulation and dynamic experiments indicate that the proposed algorithm efficiently improves the quality of reconstructed images as compared to some typical algorithms such as Landweber and SR-discrete fourier transformation/discrete cosine transformation. Furthermore, the SR-DDELM has also used to estimate the important parameters of the chemical process, a case in point is the volume flow rate. Therefore, the SR-DDELM is considered an ideal candidate for online monitor the gas/liquid two-phase flow.

This paper fulfills a novel approach to effectively monitor the gas/liquid two-phase flow in pipelines. One deep learning model and one adaptive dictionary are trained via the same prior conductivity, respectively. The model is used to extract high-level representation. The dictionary is used to represent the features of the flow process. SR and extraction of high-level representation are performed iteratively. The new method can obviously improve the monitoring accuracy and save calculation time.

This paper analyzes the effect that is generated in the dynamic response of a Commonwealth Advisory Aeronautical Council building for different types of power spectra. This article also compares synthetic wind method (SWM) results with wind tunnel tests and other numerical approaches.

One of the main methodologies developed in Brazil, the SWM, is employed to determine the dynamic wind loads. The Davenport, Lumley and Panowski, Harris, von Karman and Kaimal model are used in SWM to generate the resonant harmonics. Lateral pressures are calculated by the wind speed deflection profile for 30, 35, 40 and 45 m/s. The structure is processed in Autodesk Robot Structural Analysis with numerical analysis in FEM by the Hilber–Hughes–Taylor method. To corroborate the synthetic wind with experimental results, displacement curves are developed for wind tunnel experimental results, Davenport method, Eurocode and NBR 6123, together with the SWM.

Results show that for 30 m/s, the lowest convergence of the power spectra models was presented and that the greatest difference found was below 10%. In addition, it was shown that Eurocode 1-4 can lead to oversizing, while NBR 6123 can lead to undersizing, compared with the experimental results. Finally, results by the Davenport method, wind tunnel test and synthetic wind showed good accuracy.

By carrying out this comparative analysis, this work presents an important contribution in the field of calculating the dynamic response of tall buildings. Studies with these comparisons to corroborate the SWM had not yet been carried out.

To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system theory. The purpose of this paper is to make full use of the difference of data distribution and avoid the marginal data being ignored.

Based upon the grey distribution characteristics of small sample data, the definition about a new concept of grey relational similarity measure comes into being. At the same time, the concept of sample weight is proposed according to the grey relational similarity measure. Based on the new definition of grey weight, the grey point estimation and grey confidence interval are studied. Then the improved Bootstrap resampling is designed by uniform distribution and randomness as an important supplement of the grey estimation. In addition, the accuracy of grey bilateral and unilateral confidence intervals is introduced by using the new grey relational similarity measure approach.

The new small sample evaluation method can realize the effective expansion and enrichment of data and avoid the excessive concentration of data. This method is an organic fusion of grey estimation and improved Bootstrap method. Several examples are used to demonstrate the feasibility and validity of the proposed methods to illustrate the credibility of some simulation data, which has no need to know the probability distribution of small samples.

This research has completed the combination of grey estimation and improved Bootstrap, which makes more reasonable use of the value of different data than the unimproved method.

No carbon gas is released into the atmosphere in electricity production with wind energy. Therefore, this type of energy is significantly environmentally friendly. On the other hand, thanks to wind energy investments, a country can produce its own energy. This reduces the country’s foreign dependency on energy. Due to these positive aspects, increasing wind energy investments is very important for both the social and economic development of the country. The aim of this study is to define the most appropriate government support to improve wind energy investments. In this context, four different criteria are defined in this regard by making a detailed literature review. In the analysis process, fuzzy AHP methodology is considered. Within this framework, the comparative evaluations of three different experts are obtained. The findings indicate that providing loans with low-interest rate is the most appropriate government support for the wind energy investors. Additionally, it is also defined that tax deduction is another important issue for this purpose. However, it is also identified that appropriate location supply and purchase guarantee of the product produced have lower importance in comparison with the others. It is strongly recommended that governments should provide loans to the wind energy investors. This strategy can minimize the problem of high initial cost so that it can be much easier to attract the attention of the investors.

The purpose of this paper is to investigate the mechanical behavior and propagation of cracks of numerical granite samples through the Brazilian split test and to provide a reference for predicting the behavior of real granite samples.

The numerical models of granite containing two fissures are established using the parallel bond model (PBM) and the smooth joint model (SJM) in PFC2D. The peak stresses, number of cracks and anisotropic ratios are obtained to study the influence of the mineral composition and the angle of inclination of rock bridge on the strength, failure mode and deformation characteristics.

The numerical results obtained show that the mineral composition has a marginal influence on the peak stress. When the angle of inclination of rock bridge β increases, the peak stress drops to its minimum value at β = 90° and then gradually increases to a relatively low level. The behavior of cracks falls into three categories based on the distribution of cracks. By analyzing the stress–strain curve and the process of crack propagation for sample No. 4 with β = 60°, it is found that the process of failure can be divided into four stages and tensile cracks dominate. The anisotropic ratios of peak stress and a number of cracks obtained show that the peak stress is low anisotropic and the number of cracks is medium anisotropic.

This paper presents a numerical simulation method to analyze mechanical behavior and propagation of cracks under different conditions. The proposed method and the results obtained are useful for predicting the behavior of real granite samples in laboratory and engineering projects.