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Push notification service (PNS) is an important approach to distribute personalized information to users timely and is getting more and more popular. However, users' privacy concerns are a major inhibiting factor in their continuance usage of PNS. This study investigates the effect of privacy protection functions provided by PNS sites in enhancing users' perceived fairness on the basis of justice theory to mitigate users' concerns of information privacy. The mechanism underlying such influence on users' continuance usage of PNS comprises privacy concern and privacy-control self-efficacy.

Four scenario-based surveys are conducted to test the proposed hypotheses. The authors test the research model with a sample of 360 participants by ANOVA and PLS.

Results show that the proposed privacy protection functions have direct positive effects on users' privacy-control self-efficacy, negative effects on privacy concern and indirectly affect their continuance usage of PNS. Furthermore, the interaction effects between two approaches have different impacts on users' privacy concern and privacy-control self-efficacy.

This study provides some suggestions and guidance for PNS providers to design effective privacy protection technologies.

Construction safety has been a long-term problem in the development of the construction industry. An increasing number of smart construction sites have been designed using different techniques to reduce injuries caused by construction accidents and achieve proactive risk control. However, comprehensive smart construction site safety management solutions and applications have yet to be developed. Thus, this study proposes a smart construction site framework for safety management.

A safety management system based on a cyber-physical system is proposed. The system establishes risk data synchronization mapping between the virtual construction and physical construction sites through scene reconstruction design, data awareness, data communication and data processing modules. Personnel, mechanical and other risks on site will be warned and controlled.

The results of the case study have proved the management benefits of the system. On-site workers gradually realized that they should enter the construction site based on the standard process. And the number of people close to the construction hazard areas decreased.

There are some limitations in the technology of smart construction site. The modeling speed can be faster, the data collection can be timelier, and the identification of unsafe behavior can be integrated into the system. Construction quality and efficiency issues in a virtual construction site will also be solved in further research.

In this paper, this system is actually applied in the mega project management process. More practical projects can use the management ideas and method of this paper to ensure on-site safety.

This study is among the first attempts to build a complete smart construction site based on CPS and apply it in practice. Personnel, mechanical, components, environment information will be displayed on the virtual construction site. It will greatly promote the development of the intellectualized construction industry in the future.

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under interval uncertainty can become computationally intractable because the inner level must perform robust evaluation for each design alternative delivered from the outer level. This paper aims to propose an on-line Kriging metamodel-assisted variable adjustment robust optimization (OLK-VARO) to ease the computational burden of previous VARO approach.

In OLK-VARO, Kriging metamodels are constructed for replacing robust evaluations of the design alternative delivered from the outer level, reducing the nested optimization structure of previous VARO approach into a single loop optimization structure. An on-line updating mechanism is introduced in OLK-VARO to exploit the obtained data from previous iterations.

One nonlinear numerical example and two engineering cases have been used to demonstrate the applicability and efficiency of the proposed OLK-VARO approach. Results illustrate that OLK-VARO is able to obtain comparable robust optimums as to that obtained by previous VARO, while at the same time significantly reducing computational cost.

The proposed approach exhibits great capability for practical engineering design optimization problems under interval uncertainty.

The main contribution of this paper lies in the following: an OLK-VARO approach under interval uncertainty is proposed, which can significantly ease the computational burden of previous VARO approach.

This paper aims to focus on the high-speed rotary lip seal in aircraft engines, combining its service parameters, its own structure and application conditions, to study the influence of different eccentric forms, eccentricity, rotational speed and other factors on the performance of the rotary lip seal.

A numerical simulation model for high-speed eccentric rotary lip seals has been developed based on the theory of elastic hydrodynamic lubrication. This model comprehensively considers the coupling of multiple physical fields, including interface hydrodynamics, macroscopic solid mechanics and surface microscopic contact mechanics, under the operating conditions of rotary lip seals. The model takes into account eccentricity and uses the hazardous cross-sectional method to quantitatively predict sealing performance parameters, such as leakage rate and friction force.

Eccentricity has a large impact on lip seal performance; lips are more susceptible to wear failure under static eccentricity and to leakage failure under dynamic eccentricity.

This study provides a new idea for the design of rotary lip seal considering eccentricity, which is of guiding significance for the engineering application of rotary lip seal.

This study presented the experience of improving the nucleic acid sample collection and transportation service in response to the epidemic. The main purpose is that through intelligent path planning, combined with the time scheduling of sample points, the process of obtaining results to determine the state of COVID-19 patients could be speeding up.

The research optimized the process, including finding an optimal path to traverse all sample points in the hospital area via intelligent path planning method and standardizing the operation through the time sequence scheduling of each round of support staff to collect and send samples in the hospital area, so as to ensure the shortest time in each round. And the study examines these real-time experiments through retrospective examination.

The real-time experiments' data showed that the proposed path planning and scheduling model could provide a reliable reference for improving the efficiency of hospital logistics. Testing is a very important part of diagnosis and prompt results are essential. It shows the possibility of applying the shortest-path algorithms to optimize sample collection processes in the hospital and presents the case study that gives the expected outcomes of such a process.

The value of the study lies in the abstraction of a very practical and urgent problem into a TSP. Combining the ant colony algorithm with the genetic algorithm (ACAGA), the performance of path planning is improved. Under the intervention and guidance, the efficiency of hospital regional logistics planning was greatly improved, which may be of greater benefit to critical patients who must go through fever clinic during the epidemic. By detailing how to more rapidly obtain results through engineering method, the paper contributes ideas and plans for practitioners to use. The experience and lessons learned from Tongji Hospital are expected to provide guidance for supporting service measures in national public health infrastructure management and valuable reference for the development of hospitals in other countries or regions.

This study aims to develop a bimodal nano-silver paste with improved mechanical property and reliability. Silicon carbide (SiC) particles coated with Ag were introduced in nano-silver paste to improve bonding strength between SiC and Ag particles and enhance high-temperature stability of bimodal nano-silver paste. The effect of sintering parameters such as sintering temperature, sintering time and the proportion of SiC particles on mechanical property and reliability of sintered bimodal nano-silver structure were investigated.

Sandwich structures consist of dummy chips and copper substrates with nickel and silver coating bonded by nano-silver paste were designed for shear testing. Shear strength testing was conducted to study the influence of SiC particles proportions on the mechanical property of sintered nano-silver joints. The reliability of the bimodal nano-silver paste was evaluated experimentally by means of shear test for samples subjected to thermal aging test at 150°C and humidity and temperature testing at 85°C and 85 per cent RH, respectively.

Shear strength was enhanced obviously with the increase of sintering temperature and sintering time. The maximum shear strength was achieved for nano-silver paste sintered at 260°C for 10 min. There was a negative correlation between the proportion of SiC particles and shear strength. After thermal aging testing and humidity and temperature testing for 240 h, the shear strength decreased a little. High-temperature stability and high-hydrothermal stability were improved by the addition of SiC particles.

Submicron-scale SiC particles coated with Ag were used as alternative materials to replace part of nano-silver particles to prepare bimodal nano-silver paste due to its high thermal conductivity and excellent mechanical property.

This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users perception image and users' preference.

In this paper, men's suit is composed into multiple design features under the design elements. Using the orthogonal experiment method, 16 schemes of the representative suit are designed. Through perception evaluation experiment, users' perception images and preference degree of the samples are obtained. By partial least squares (PLS) analysis method, the models between users' perception image, suit design features and users' preference are built.

The interrelationship between the three is identified by establishing PLS models between users' perception image, suit design features and users' preference. According to the coefficients of the models, the optimization schemes of men's suits considering users' perception image and preference are proposed. Verification results show that the optimization schemes are significantly better than other schemes.

The results of this paper can be used for consumer demand-oriented clothing design and provide references and methods for converting consumer's perceived needs into clothing design features.

The purpose of this paper is to evaluate some numerical integration strategies used in generalized (G)/extended finite element method (XFEM) to solve linear elastic fracture mechanics problems. A range of parameters are here analyzed, evidencing how the numerical integration error and the computational efficiency are improved when particularities from these examples are properly considered.

Numerical integration strategies were implemented in an existing computational environment that provides a finite element method and G/XFEM tools. The main parameters of the analysis are considered and the performance using such strategies is compared with standard integration results.

Known numerical integration strategies suitable for fracture mechanics analysis are studied and implemented. Results from different crack configurations are presented and discussed, highlighting the necessity of alternative integration techniques for problems with singularities and/or discontinuities.

This study presents a variety of fracture mechanics examples solved by G/XFEM in which the use of standard numerical integration with Gauss quadratures results in loss of precision. It is discussed the behaviour of subdivision of elements and mapping of integration points strategies for a range of meshes and cracks geometries, also featuring distorted elements and how they affect strain energy and stress intensity factors evaluation for both strategies.

The purpose of this paper is to evaluate the capabilities of the generalized finite element method (GFEM) under the context of the geometrically nonlinear analysis. The effect of large displacements and deformations, typical of such analysis, induces a significant distortion of the element mesh, penalizing the quality of the standard finite element method approximation. The main concern here is to identify how the enrichment strategy from GFEM, that usually makes this method less susceptible to the mesh distortion, may be used under the total and updated Lagrangian formulations.

An existing computational environment that allows linear and nonlinear analysis, has been used to implement the analysis with geometric nonlinearity by GFEM, using different polynomial enrichments.

The geometrically nonlinear analysis using total and updated Lagrangian formulations are considered in GFEM. Classical problems are numerically simulated and the accuracy and robustness of the GFEM are highlighted.

This study shows a novel study about GFEM analysis using a complete polynomial space to enrich the approximation of the geometrically nonlinear analysis adopting the total and updated Lagrangian formulations. This strategy guarantees the good precision of the analysis for higher level of mesh distortion in the case of the total Lagrangian formulation. On the other hand, in the updated Lagrangian approach, the need of updating the degrees of freedom during the incremental and iterative solution are for the first time identified and discussed here.