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This study aims to use resonant surface acoustic wave (SAW) sensors, which have advantages in the harsh application environments, to measure different physical parameters such as temperature, pressure and force. For SAW sensors, the locality in measurement resolution by the effective time is poor, it cannot give the detailed results of SAW echoes.

To promote the application of SAW sensor, this paper proposes a convex program-based super-resolution measurement method to recover the missing spectral line and enhance frequency resolution.

The proposed method reduces the reliance on effective time and improves the measurement resolution of SAW sensors. The performance was validated by experiments.

The limited resolution capability restricts the benefit of SAW technology in harsh environments. The proposed method shed light on SAW measurement resolution increase, exploiting its full potential and leading to commercial applications.

This paper aims to present an context evaluation and frequency measurement method for surface acoustic wave (SAW) resonant sensor.

This method is based on a signal subspace construction, which, along with assembling optional value set, provides the results.

The method can assess the application context and improve the resolution and accuracy of the passive wireless SAW resonator sensor system.

Passive wireless SAW resonators have been used as sensor elements for different physical parameters such as temperature, pressure and force in a number of industrial and medical applications. Various wireless channel environments introduce different application contexts.

This paper aims to propose a noise-robust method to estimate the frequency of the reflective echo to reduce the negative effects of noise and improve the accuracy and resolution of a resonant surface acoustic wave (SAW) sensor.

The proposed approach exploits the singular value decomposition to obtain the frequency information of a SAW response signal and overcome the noise influences.

Compared with the commonly used Fourier transform (FT) method, the accuracy and resolution improvement of the proposed method used in the SAW sensor is validated.

The system using the proposed method delivers lesser standard deviation, that is, delivers higher performance than the conventional system using the fast FT method.

This paper aims to develop a novel type of bionic underwater robot (BUR) with multi-flexible caudal fins. With the coordinate movement of multi-caudal fins, BUR will combine the undulation propulsion mode of carangiform fish and jet propulsion mode of jellyfish together organically. The use of Computational Fluid Dynamics (CFD) and experimental method helps to reveal the effect of caudal fin stiffness and motion parameters on its hydrodynamic forces.

First, the prototype of BUR was given by mimicking the shape and propulsion mechanism of both carangiform fish and jellyfish. Besides, the kinematics models in both undulation and jet propulsion modes were established. Then, the effects of caudal fin stiffness on its hydrodynamic forces were investigated based on the CFD method. Finally, an experimental set-up was developed to test and verify the effects of the caudal fin stiffness on its hydrodynamic forces under different caudal fin actuation frequency and amplitude.

The results of this paper demonstrate that BUR with multi-flexible caudal fins combines the hydrodynamic characteristics of undulation and jet propulsion modes. In addition, the caudal fin with medium stiffness can generate larger thrust force and reduce the reactive power.

This paper implies that robotic fish can be equipped with both undulation and jet propulsion modes to optimize the swimming performance in the future.

This paper provides a BUR with multi-propulsion modes, which has the merits of high propulsion efficiency, high acceleration performance and overcome the head shaken problem effectively.

This study aims to analyze management innovations developed by a homegrown Chinese hotel company aimed at sustaining its growth and reveals some unorthodox management practices in the lodging industry in China.

A theoretical sampling process was used to choose 7 Days Inn as a single case study. Semi-structured in-depth personal interviews of 15 informants with varying responsibilities were conducted to obtain organization-specific insights. Content analysis of the transcripts was performed to analyze interview data. Secondary data and interviews of managers in competing hotels were also used to support the findings.

This study identified seven major innovative management practices developed by 7 Days Inn. Most of these innovations arose from the company’s idiosyncratic collective mindset. The company created a different approach to thinking about the basic issues regarding business and management – including managerial roles, mistakes and change – that constituted the cornerstones of its management innovations.

Owing to the limitations of case method, the findings may not be generalizable to other Chinese hotel companies.

As little is known about innovative management practices by homegrown hotel companies in China, this study sheds new light on a creative and distinctive management system in the Chinese hotel industry. Introducing management styles that differ significantly from those of Western companies will benefit both management researchers and practitioners.

This study extends previous findings in management innovation by uncovering indigenous innovation influenced by traditional Chinese cultural values in China’s hospitality industry.