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The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.

An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.

Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.

Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.

The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and three-dimensional (3D) point cloud maps.

A fusion method using multiple algorithms was proposed. For 2D raster maps, this method uses accelerated robust feature detection to extract feature points of multi-raster maps, and then feature points are matched using a two-step algorithm of minimum Euclidean distance and adjacent feature relation. Finally, the random sample consensus algorithm was used for redundant feature fusion. On the basis of 2D raster map fusion, the method of coordinate alignment is used for 3D point cloud map fusion.

To verify the effectiveness of the algorithm, the segmentation mapping method (2D raster map) and the actual robot mapping method (2D raster map and 3D point cloud map) were used for experimental verification. The experiments demonstrated the stability and reliability of the proposed algorithm.

This algorithm uses a new visual method with coordinate alignment to process the raster map, which can effectively solve the problem of the demand for the initial relative position of robots in traditional methods and be more adaptable to the fusion of 3D maps. In addition, the original data of the map can come from different types of robots, which greatly improves the universality of the algorithm.

Aiming at the problems of weak generalization of robot imitation learning methods and higher accuracy requirements of low-level detectors, this study aims to propose an imitation learning method based on structural grammar.

The paper proposes a hybrid training model based on artificial immune algorithm and the Baum–Welch algorithm to extract the action information of the demonstration activity to form the {action-object} sequence and extract the symbol description of the scene to form the symbol primitives sequence. Then, probabilistic context-free grammar is used to characterize and manipulate these sequences to form a grammar space. Minimum description length criteria are used to evaluate the quality of the grammar in the grammar space, and the improved beam search algorithm is used to find the optimal grammar.

It is found that the obtained general structure can parse the symbol primitive sequence containing noise and obtain the correct sequence, thereby guiding the robot to perform more complex and higher-order demonstration tasks.

Using this strategy, the robot completes the fourth-order Hanoi tower task has been verified.

An imitation learning method for robots based on structural grammar is first proposed. The experimental results show that the method has strong generalization ability and good anti-interference performance.

To improve robustness of a dairy supply chain (SC) against corruption, the purpose of this paper is to propose a systemic model of a corruption impacted dairy SC, exposing relationships among SC operations, risks and the impact of corruption.

Cases from the dairy industry in New Zealand (NZ) are used for thematic analysis of interview data collected from participants at senior levels of NZ dairy firms. Based on these and other inputs from literature, a systemic model is built subsequently.

Mitigating certain risks can significantly alleviate the impact of corruption, an external factor, on supply chain performance (SCP). The causal loop diagram (CLD) developed here brings out the modifying effect of corruption on dairy risks and SCP.

The illustration of the CLD helps business managers better understand the interactions among risk variables and explains the systemic reasons for SC vulnerability.

This is the first paper to construct a holistic system to comprehensively reveal the interactions of supply chain risks (SCRs) and the impact of corruption. Also, by utilizing SCR interactions, this study indicates a pathway to mitigate the negative effects of corruption through improving dairy SC robustness.

The purpose of this paper is to empirically demonstrate an effective method for assessing how servicescape attributes shape consumer well-being and to highlight the value of importance-performance analysis (IPA) within a services context.

This study surveyed frequent visitors to a travel destination to determine their perceived importance of and satisfaction with servicescape attributes. The responses were analyzed using a series of importance-performance analyses to determine the impact of each servicescape attribute on consumer well-being.

Key servicescape attributes contributing to the well-being of frequent visitors to a destination were identified. For example, weather; friendly residents; restaurants; and interaction with locals were identified as attributes with a “high impact” on well-being, although weather and friendly residents were satisfiers and restaurants and interaction with locals were identified as dissatisfiers. In total, 23 servicescape attributes were plotted on a matrix depicting each attribute’s range and type of impact.

This study provides practitioners with an idea of which servicescape attributes are important in improving well-being and illustrates how IPA may be used to identify attributes of any transformative service. Additionally, the analysis helps managers prioritize servicescape attributes for a more ideal allocation of scarce resources. These findings should be applicable to various contexts.

This paper is the only known study to examine effects of servicescape attributes on consumer well-being and one of few to use the modified IPA in a services context.

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.

This article aims to examine the role of boundaryless career orientation in influencing Internet professionals' strategies toward workplace problems in China's Internet companies, which feature prominent problems including excessive overwork. It addresses one question: how do Chinese Internet professionals make grievance strategies?

This article draws on qualitative data based on semi-structured, in-depth interviews with 134 employees from 6 representative Chinese Internet companies. The data were collected during 2018-2021 and analyzed with a grounded theory approach.

This article highlights the role of boundaryless career orientation in explaining Chinese Internet professionals' strategies toward workplace grievances. The author develops a comprehensive model to illustrate how boundaryless career orientation influences four grievance strategies namely, strategic compliance, exit, dissent expression and resistance that correspond to four different motives to advance the professionals' boundaryless career: learning, transferring, relieving and resolving. Internet professionals choose different grievance strategies based on how each option can benefit their boundaryless career goals.

This article is one of the first to bring in boundaryless career orientation as a key factor in explaining Chinese Internet professionals' grievance strategies. It provides a fuller picture than previous studies by showing wide varieties of professionals' grievance behaviors. The finding of high-level boundaryless career orientation among Internet professionals offers insights on how companies can improve employment relations by improving career management practices.

The purpose of this paper is to propose a type of hybrid bearing lubricated with supercritical carbon dioxide (S-CO₂) and to investigate the stiffness and damping characteristics of the bearing under hydrostatic status.

Established a test rig for radial bearings lubricated with S-CO₂ and used it to measure the dynamic coefficients by recording the relative and absolute displacements of bearing. Test bearing is mounted on a nonrotating, stiff shaft. Using static loading experiments to obtain structural stiffness. The dynamic coefficient regularities of the test bearing under hydrostatic status were revealed through dynamic loading experiments.

Experiment results indicate that test bearing displayed increased stiffness when subjected to high excitation frequencies and low excitation forces, as well as elevated damping when exposed to low excitation frequencies and low excitation forces. Additionally, an increase in either environmental pressure or hydrostatic recess pressure can elevate the dynamic coefficient. The effect of temperature on the dynamic coefficient is more pronounced around the critical temperature of S-CO₂.

Designed a type of hybrid bearing for use in the Brayton cycle that is lubricated with S-CO₂ and uses hydrostatic lubrication during start-stop and hydrodynamic lubrication during high-speed operation. The hybrid bearing reduces the wear and friction power consumption of gas bearing. However, few experimental analyses have been conducted by researchers in this field.