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Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.

ACM arranges points in the axis of the membership adaptively. Through the adaptive collocation procedure, ACM can arrange more points in the axis of the membership where the membership function changes sharply and fewer points in the axis of the membership where the membership function changes slowly. At each point arranged in the axis of the membership, the level-cut strategy is used to obtain the cut-level interval of the uncertain variables; besides, the vertex method and the Chebyshev interval uncertainty analysis method are used to conduct the cut-level interval uncertainty analysis.

The proposed ACM has a high accuracy without too much additional computational efforts.

A novel ACM is developed for the structural fuzzy uncertainty analysis.

To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

This study clarifies how intra-organizational social capital (IOSC) and unit-organizational ambidexterity (UOA), using resource-based view and dynamic capability theory, together support organizational value creation. While there is research in strategic human resource management (SHRM) exploring the role of resources and its uses, there remains limited understanding of how resources are linked and their effective utilization in the service sector. This study aims to examine the mediating process linking employee-experienced service-oriented high-performance work systems (SHPWS) experienced by employees and service performance by integrating IOSC and UOA.

This study uses time lagged data from managers and employees of different branches of Chinese state-owned banks. To test the proposed hypotheses, path analysis was applied.

The path analysis results reveal that employee-experienced SHPWS is an important antecedent of service performance. Moreover, IOSC (as resources) and UOA (uses) strongly mediate the theorized relationship.

This study attempts to refine theory and practice with clearer, more insightful and coherent means to better understand and help unpack the ‘black box’ between SHPWS-performance relationships through a new linkage model.

The paper tests the overconfidence bias and volatility on the Ghana Stock Exchange (GSE) during the pre-Covid-19 pandemic and Covid-19 pandemic period.

The study employs pairwise Granger causality to test the presence of overconfidence bias on the Ghana stock market as well as GARCH (1,1) and GJR-GARCH (1, 1) models to understand whether overconfidence bias contributed to volatility during pre-Covid-19 pandemic and Covid-19 pandemic period. The pre-Covid-19 pandemic period spans from January, 2019 to December, 2019, and Covid-19 pandemic period spans from January, 2020 to December, 2020.

The paper finds a unidirectional Granger causality running from weekly market returns to weekly trading volume during the Covid-19 pandemic period. These results indicate the presence of overconfidence bias on the Ghana stock market during the Covid-19 pandemic period. Finally, the conditional variance estimation results showed that excessive trading of overconfident market players significantly contributes to the weekly volatility observed during the Covid-19 pandemic period.

The empirical findings demonstrate that market participants on the GSE exhibit conditional irrationality in their investment decisions during the Covid-19 pandemic period. This implies investors overreact to private information and underreact to available public information and as a result become overconfident in their investment decisions.

Findings from this paper show that there is evidence of overconfidence bias among market players on the GSE. Therefore, investors, financial advisors and other market players should be educated on overconfidence bias and its negative effect on their investment decisions so as to minimize it, especially during the pandemic period.

This study is a maiden one that underscores investors’ overconfidence bias in the wake of a pandemic in the Ghanaian stock market. It is a precursor to the overconfidence bias discourse and encourages the testing of other behavioral biases aside what is understudied during the Covid-19 pandemic period in Ghana.

The purpose of this paper is to understand compression garment in the area of medical industry, compression garments were used initially for patients with circulatory problems. External pressure was created by compression garments on the body surface which prevents blood clots, leg swelling and improves venous hemodynamics.

Compression rehabilitation is a significant element in the effective management of lower limb problems of people associated with venous, lymphatic, fat disorders like lipoedema.

Compression garments have been attributed primarily for the increase in blood flow, improvement in recovery, reduction in muscle vibration that increase stability, improvement in thermoregulation, decrease in muscle pain, elimination of blood lactate and creatine kinase after exercise.

Compression garments are extraordinary clothes that contain elastomeric yarns or fibers that are responsible for applying significant mechanical pressure on the required body surface for compressing, stabilizing and supporting underlying tissues.

The purpose of this study is to extend previous research by using a longitudinal design to examine the differential contribution of brand understanding (BU) drivers at various moments in the early tenure of service employees. Employee BU is a prerequisite of brand promise delivery among service employees. Previous studies, using cross-sectional samples, established that brand-oriented recruitment, training and leadership are significant BU drivers.

A three-wave survey was collected from a 105-member panel of recent hires at a restaurant chain that displayed a strong brand culture and adopted internal brand management (IBM) practices. Structural equation models with carryover effects were estimated to measure the impact of BU drivers on Day 1, as well as at four and seven months of tenure. In addition, a latent growth model of BU was estimated using random coefficients modeling.

Results show a significant positive effect of IBM practices on BU at each point in time; however, despite this, by the seven month milestone, BU is still not fully developed.

As with most organizational longitudinal studies, there was sample attrition because of the high turnover that characterizes the restaurant industry. This attrition is not believed to be correlated with the variables measured in the study.

Managers seeking a differentiated customer experience should not assume new hires attain a good understanding of the service brand even after the first seven months of tenure. Hence, brand training and leadership should extend well beyond this time frame.

This study is the first, as per the authors’ understanding, to use a longitudinal design to model BU as a dynamic variable because it befits the learning trajectories of new employees.

The purpose of this paper is to promote the corrosion resistance of the 5083-111H aluminum alloy by laser cleaning.

Laser with 2 ns pulse width was adopted in this project and the corrosion resistance of cleaned samples was tested by copper-accelerated salt spray (CASS). The surface morphology, elemental composition and distribution were then characterized by SEM. Moreover, surface morphology, elemental composition and distribution were also tested.

Results suggested a higher corrosion resistance was successfully obtained by laser cleaning. Compared with samples cleaned by 2000 grit sandpaper, mechanical cleaning resulted in a 53% larger height difference between the peak and valley. The content of the oxygen is 8.85% on the surface cleaned mechanically and the distribution is dependent on the distribution of aluminum whereas that of the laser cleaning sample is 24.41% and the distribution existed even in the Al-poor area.

In this project, the 2-ns laser cleaning was proved to have the capability to remove the oxide layer on the aluminum alloy surface while retaining an excellent corrosion resistance and smooth surface. Meanwhile, a thorough elemental distribution and smaller grain size lead to a smaller difference in elemental concentration. This retards the diffusion of oxygen into the substrate and hence increases the corrosion resistance of the surface.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.