Search results

This study aims to obtain the more precise decision map to fuse the source images by Coefficient significance method. In the area of multifocus image fusion, the better decision map is very important the fusion results. In the processing of distinguishing the well-focus part with blur part in an image, the edge between the parts is more difficult to be processed. Coefficient significance is very effective in generating the better decision map to fuse the multifocus images.

The energy of Laplacian is used in the approximation coefficients of redundant discrete wavelet transform. On the other side, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient.

Due to the shift-variance of the redundant discrete wavelet and the effectiveness of fusion rule, the presented fusion method is superior to the region energy in harmonic cosine wavelet domain, pixel significance with the cross bilateral filter and multiscale geometry analysis method of Ripplet transform.

In redundant discrete wavelet domain, the coefficient significance based on statistic property of covariance is proposed to merge the detail coefficient of source images.

The more precise decision map is important to generate better-fused image. Guided filter can preserve edge information effectively. The purpose of his study is to use guided filter to form the precise decision map and highly informatively fused image.

The dual tree complex wavelet transform is adopted to decompose the source images into high frequency and low frequency coefficients. Sum of modified Laplacian method is introduced as the focus metric in dual tree complex wavelet coefficients. The guided filter is guided by the dual tree complex wavelet coefficient when the sum of modified Laplacian is used as the input image. The output image of guided filter is used to produce the decision map to fuse dual tree complex wavelet coefficient of source images.

The sum of modified Laplacian of dual tree complex wavelet coefficient can be used as the guided image in guided filter to generate better decision map. Comparison with the other state-of-the-art methods illustrates that the proposed approach is more effective in fusing the multifocus images both visual performance and objective evaluation.

The sum of modified Laplacian of dual tree complex wavelet coefficient is introduced to be used as the guided image in guided filter to generate better decision map. This method is fast and effect to fuse the source images. Comparison with the other state-of-the-art methods illustrates that the proposed approach is more effective in fusing the multifocus images both visual performance and objective evaluation.

The normal operation of a rotor system is generally vulnerable to misalignment between gas foil bearing (GFB) and rotor. However, most theoretical and experimental researches about the characteristics of GFBs have ignored this phenomenon. Therefore, the main purpose of this paper is to evaluate the static and dynamic performance of GFBs considering misalignment.

The shaft is allowed to misalign in two directions. Then the variations of bearing load, friction force, restoring moment, stiffness and damping coefficients are thoroughly explored. The hydrodynamic pressure on the gas film is modeled with compressible Reynolds equation, and the deformation of the flexible bearing is calculated with finite element method. Small perturbation method is used to obtain the displacement and moment dynamic coefficients.

The film thickness and pressure distribution distort when misalignments appear. The inclination of GFBs can enhance the restoring moment to withstand the imposed misalignment. Furthermore, the simulation phenomenon demonstrates the misalignment around load direction should be avoided as much as possible, while a small value misalignment around another direction is allowed.

The value of this paper is the exploration of the influence of misalignments on the static and dynamic performance of the Generation II journal GFB.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0418/

With the ascendance of information technology, particularly through the internet, external information sources and their impacts can be readily transferred to influence the performance of financial markets within a short period of time. The purpose of this paper is to investigate how incidents affect stock prices and volatility using vector error correction and autoregressive-generalized auto regressive conditional Heteroskedasticity models, respectively.

To characterize the investors’ responses to incidents, the authors introduce indices derived using search volumes from Google Trends and the Baidu Index.

The empirical results indicate that an outbreak of disasters can increase volatility temporarily, and exert significant negative effects on stock prices in a relatively long time. In addition, indices derived from different search engines show differentiation, with the Google Trends search index mainly representing international investors and appearing more significant and persistent.

This study contributes to the existing literature by incorporating open-source data to analyze how catastrophic events affect financial markets and effect persistence.

This chapter aims to provide a descriptive analysis and a theoretical interpretation of the challenges for international expansion of four large multinationals of each of the BRIC countries (JBS from Brazil, VimpelCom from Russia, Tata Motors from India, and Lenovo from China).

This study employs a qualitative approach, following a multiple-case study methodology, by analyzing four prominent cases of the internationalization of BRIC multinationals.

The internationalization process of the studied BRIC multinationals was influenced by the type of inputs and resources that each company had in their home country and the search for needed resources in other firms abroad that may have helped them to complement their business assets. The international expansion of these firms have been characterized by overcoming of several obstacles through the possession of firm-specific advantages, mainly composed of managerial capabilities, expertise, and knowledge about the markets and their companies.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.

Following a brief introduction of titanium (Ti) alloys, this paper considers the near-α group of Ti alloys, which are the most popular high-temperature Ti alloys developed for a high-temperature application, particularly in compressor disc and blades in aero-engines. The paper is relied on literature within the past decade to discuss phase stability and microstructural effect of alloying elements, plastic deformation and reinforcements used in the development of these alloys.

The near-a Ti alloys show high potential for high-temperature applications, and many researchers have explored the incorporation of TiC, TiB SiC, Y₂O₃, La₂O₃ and Al₂O₃ reinforcements for improved mechanical properties. Rolling, extrusion, forging and some severe plastic deformation (SPD) techniques, as well as heat treatment methods, have also been explored extensively. There is, however, a paucity of information on SiC, Y₂O₃ and carbon nanotube reinforcements and their combinations for improved mechanical properties. Information on some SPD techniques such as cyclic extrusion compression, multiaxial compression/forging and repeated corrugation and straightening for this class of alloys is also limited.

This paper provides a topical, technical insight into developments in near-a Ti alloys using literature from within the past decade. It also outlines the future developments of this class of Ti alloys.

The purpose of this study is to prepare ZnFe₂O₄ nanospheres, sheet MoS₂ and three ZnFe₂O₄@MoS₂ core-shell composites with various shell thicknesses, and add them to the base oil for friction and wear tests to simulate the wear conditions of hybrid bearings.

Through the characterization and analysis of the morphology of wear scars and the elemental composition of friction films, the tribological behavior and wear mechanism of sample materials as lubricant additives were investigated and the effects of shell thickness and sample concentration on the tribological properties of core–shell composite lubricant additives were discussed.

The findings demonstrate that each of the five sample materials can, to varying degrees, enhance the lubricating qualities of the base oil and that the core–shell nanocomposite sample lubricant additive has superior lubricating properties to those of ZnFe₂O₄ and MoS₂ alone, among them ZnFe₂O₄@MoS₂-2 core–shell composites with moderate shell thickness performed most ideally. In addition, the optimal concentration of the ZnFe₂O₄@MoS₂ lubricant additive was 0.5 Wt.%, and a concentration that was too high led to particle deposition and affected the friction effect.

In this work, ZnFe₂O₄@MoS₂ core–shell composites were synthesized for the first time using ZnFe₂O₄ as the carrier and the lubrication mechanism of core–shell composites and single materials were compared and studied, which illustrated the advantages of core–shell composite lubricant additives. At the same time, the influence of different shell thicknesses on the lubricant additives of core–shell composites was studied.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0367/

The aim of this paper is to quantify the impact of transboundary air pollutants, particularly those related to urban traffic, on health outcomes. The importance of focusing on the health implications of transboundary pollution is due to the fact that these emissions originate from another jurisdiction, thus constituting international negative externalities. Thus, by isolating and quantifying the impact of these transboundary air pollutants on domestic health outcomes, the authors can understand more clearly the extent of these externalities, identify their ramifications for health and emphasise the importance of cross-country cooperation in the fight against air pollution.

The authors employ panel data regression analysis to look at the relationship between emissions of transboundary air pollution and mortality rates from various respiratory diseases among a sample of 40 European countries, over the period 2003–2014. In turn, the authors use annual data on transboundary emissions of sulphur oxides (SOx), nitrogen oxides (NOx) and fine particulate matter (PM_2.5), together with detailed data on the per capita incidence of various respiratory diseases, including lung cancer, asthma and chronic obstructive pulmonary disease (COPD). The authors consider a number of different regression equation specifications and control for potential confounders like the quality of healthcare and economic prosperity within each country.

The results show that transboundary emissions of PM_2.5 are positively and significantly related to mortality rates from asthma in our sample of countries. Quantitatively, a 10% increase in PM_2.5 transboundary emissions per capita from neighbouring countries is associated with a 1.4% increase in the asthma mortality rate within the recipient country or roughly 200 deaths by asthma per year across our sample.

These findings have important policy implications for cross-country cooperation and regulation in the field of pollution abatement and control, particularly since all the countries under consideration form a part of the UN's Convention on Long-Range Transboundary Air Pollution (CLRTAP), a transnational cooperative agreement aimed at curtailing such pollutants on an international level.