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This paper aims to present an investigation on flight quality analysis and design of tilt-rotor aircraft combined with corresponding flight quality specifications.

From the perspective of modal characteristics of tilt-rotor aircraft, it focuses on the analysis of the change rules of the longitudinal short-term motion mode, lateral roll convergence mode, spiral mode and Dutch roll mode. Then, the flight quality design research is carried out using the explicit model tracking control method. The quantitative relationship between flight quality requirements and explicit model is established. Accordingly, the closed-loop flight quality of XV-15 tilt-rotor aircraft is evaluated.

The stability of spiral mode is the result of the interaction of various aerodynamic derivatives and spiral instability occurs in helicopter mode. The other motion modes are stable in full flight mode and meet the requirements of level 1 specified in ADS-33E-PRF and MIL-F-8785C flight quality specifications. There is a quantitative relationship between flight quality requirements and explicit model, and the flight quality of tilt-rotor aircraft is improved through the explicit model tracking control method.

The presented analysis results showed the influence of motion modes and flight quality and the effectiveness of explicit model tracking control method in flight quality improvement, which could be considered as new information for further flight quality design of tilt-rotor aircraft.

The originality of the paper lies in the proposed design and analysis method of the flight quality of tilt-rotor aircraft from the direction of the influence of its aerodynamic derivatives and motion modes.

The purpose of this paper is to identify the drivers of manufacturing transformation and upgrading and examine their influencing paths and effects. The study also dynamically evaluates and compares the achievements of the manufacturing transformation and upgrading of various economies.

This paper establishes the mechanism model of manufacturing transformation and upgrading based on the partial least squares approach to structural equation modeling. With the help of a mechanism model, the study carries out empirical analysis using panel data from the G20 for 2005–2015.

Innovation, measured by innovation input and innovation output, has the largest positive effect on manufacturing transformation and upgrading. Economic development has a negative direct effect, as well as positive indirect effects. Its total effect is positive but small. Economic openness has no significantly direct effect, but has significantly positive indirect effects. Its total effect is significantly positive, but is the smallest among drivers. Developed economies have relatively higher but decreasing achievements, whereas emerging economies have lower but increasing achievements and maintain the catch-up trend toward developed economies.

Few macro empirical studies examine the drivers and achievements of manufacturing transformation and upgrading. A need has arisen for evidence-based research and policies to guide governments in their efforts to promote manufacturing transformation and upgrading. This may be the first macro-level study to empirically analyze the drivers of manufacturing transformation and upgrading, and their influencing paths as well as achievements.

This paper aims to explore the intention of consumers to visit green hotels in China through the theory of planned behavior (TPB) extended by adding perceived consumer effectiveness and environmental concern.

The TPB model is used as the basic theoretical framework but is extended by adding two critical variables. Data is collected from 324 respondents by using a self-administered questionnaire survey and analyzed with the assistance of structural equation modeling.

The empirical results show that perceived consumer effectiveness and environmental concern have positive effects on the attitude and the intention of consumers to visit green hotels, and that perceived consumer effectiveness has the largest effect. However, in China, the impact of environmental concern on the intention of consumers to visit green hotels is relatively limited, and the subjective norm has a strong effect. In addition, this research verifies the usefulness of the extended TPB model in understanding the intention of consumers in green hotels industry in China. This is evidenced by a comparison of the initial TPB model with the extended TPB model where the explanatory power has improved from 65 to 68 per cent.

This research contributes to TPB theory by addressing certain gaps in the literature regarding the intention of consumers to visit green hotels in China. Furthermore, considering the limitations of the TPB model, two pro-social variables, namely, perceived consumer effectiveness and environmental concern, are incorporated into the TPB model to better understand the intention of consumers to visit green hotels. Also, this research addresses the gap that studies on the role of perceived consumer effectiveness are limited in the tourism and hospitality management literature. The results indicate that perceived consumer effectiveness has the largest influence on the intention of consumers to visit green hotels.

The purpose of this paper is to apply an extended technology acceptance model to examine the medical data analyst’s intention to use medical big data processing technique.

Questionnaire survey method was used to collect data from 293 medical data analysts and analyzed with the assistance of structural equation modeling.

The results indicate that the perceived usefulness, social influence and attitude are important to the intention to use medical big data processing technique, and the direct effect of perceived usefulness on intention to use is greater than social influence and attitude. The perceived usefulness is influenced by perceived ease of use. Attitude is influenced by perceived usefulness, and attitude acts as a mediator between perceived usefulness and usage intention. Unexpectedly, attitude is not influenced by perceived ease of use and social influence.

This research examines the medical data analyst’s intention to use medical big data processing technique and provides several implications for using medical big data processing technique.

The purpose of this paper is to observe consumers’ attitudes toward and intentions to purchase green products on social media and to explore the relationships among social media marketing, perceived consumer effectiveness (PCE), product knowledge, subjective norms, perceived behavioral control, price consciousness and attitudes toward and intentions to purchase green products. In addition, this research attempts to further understand these relationships in different consumer groups.

A questionnaire survey method was used to collect data from consumers in China. The Amos 22.0 software package was used to conduct the data analysis.

The empirical results suggest that attitude, subjective norms and perceived behavioral control positively affect purchase intentions, while price consciousness negatively affects purchase intentions. Product knowledge positively affects consumers’ attitudes and purchase intentions, and PCE positively affects consumers’ attitudes. As expected, social media marketing positively affects subjective norms, product knowledge and PCE and negatively affects price consciousness. However, there is no significant relationship between PCE and purchase intentions. According to the results of multigroup structural equation modeling analysis, the effects differ significantly among different consumer groups.

This study enriches the research about the factors that influence consumers’ purchases of green products in emerging countries in the social media marketing context.

Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.

The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.

Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.

The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.

The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.

The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.

A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.

This paper aims at the problem of surrounding rock excavation damage zone of tunneling in the rich water region, this paper aims to propose a new seepage-stress-damage coupling model and studied the numerical algorithm. This reflects the characteristics of rock damage evolution, accompanied by plastic flow deformation and multi-field interaction.

First of all, rock elastoplastic damage constitutive model based on the Drucker–Prager criterion is established, the fully implicit return mapping algorithm is adopted to realize the numerical solution. Second, based on the relation between damage variation and permeability coefficient, the rock stress-seepage-damage model and multi-field coupling solving iterative method are presented. Finally, using the C++ language compiled the corresponding programs and simulated tunnel engineering in the rich water region.

Results show that difference evolution-based back analysis inversed damage parameters well, at the same time the established coupling model and calculating program have more advantages than general conventional methods. Multiple field coupling effects should be more considered for the design of tunnel support.

The proposed method provides an effective numerical simulation method for the construction of the tunnel and other geotechnical engineering involved underground water problems.

Aircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.

The vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.

The vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.

The proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.