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This study aims to track the historical development in tourism and hospitality research over the past 30 years by applying a novel interdisciplinary approach, combining both corpus linguistics and bibliometric analysis.

Most frequently discussed topics and newly emerging topics were identified by investigating 18,266 abstracts from 18 leading tourism and hospitality journals with corpus linguistics toolkit AntConc and natural language processing (NLP) tool spaCy. Trend analysis and bibliometric methods were used to determine the longitudinal changes of research topics, most highly-cited publications and authors' production.

This study revealed the evolution patterns of the identified 576 most frequently discussed topics across the four subperiods (1991–2000, 2001–2010, 2011–2015 and 2016–2020). Specifically, results showed that information technology-related topics account for the largest proportion of the identified 38 newly emerging topics from 2011. Besides, researchers are increasingly focusing on the use of more sophisticated and advanced statistical methodologies.

This study helps researchers make sensible decisions on what research topics to explore; it also helps practitioners and stakeholders make the shift and track opportunities in the field.

No other studies have employed the novel interdisciplinary approach, combining corpus linguistic tools in linguistics, NLP techniques in computer science and bibliometric analysis in library and information science, for exploring research trends in tourism and hospitality.

The paper aims to introduce the fabrication of a medium steel aircraft part by hybrid deposition and micro-rolling technology (HDMR) and illustrate its advantages, microstructure features and mechanical properties of the part.

The HDMR technology contains two procedures happening almost at the same time: the welding deposition procedure and then the micro-rolling procedure. It takes the gas metal arc welding as the heat source to melt a metal wire and deposit metal in the welding deposition procedure. The metal just deposited is rolled synchronously by a micro roller following the welding torch in micro-rolling procedure almost at the same time layer by layer. The paper presents a contrast of the grain morphology of metal parts produced respectively by HDMR and freedom arc deposition (FAD) and the mechanical properties of metal parts of the same metal from HDMR casting, forging and FAD methods.

HDMR breaks the dendrite grain of welding beads into the fine crisscross grains. The mechanical properties of metal parts are improved distinctly by the micro-rolling procedure compared to casting, forging and FAD.

In addition, the application of HDMR technology has succeeded in the fabrication of an eligible aircraft metal part, which is quite difficult to achieve using other additive manufacturing (AM) or casting technologies.

HDMR has the advantage of equiponderance manufacturing by micro-rolling compared to other AM technologies. The metal part fabricated by HDMR technology obtains the fine crisscross grains and brings hope for AM metal components with excellent mechanical properties for aircraft applications.

The wire and arc additive manufacturing (WAAM) is a promising technology, but the parts are mostly manufactured on the plane and along the vertical direction. The purpose of this paper is to propose a cylindrical slicing and manufacturing method.

For revolved parts, e.g. blades of a propeller, instead of planes, a series of cylindrical surfaces intersect with the STL model of the part. The generated slicing layers lie on the cylindrical surface, and then these spatial contours are unfolded onto the plane by the use of the cylindrical coordinate system. A deposition system based on an NC machine is established to examine deposition paths. The temperature and stress of part of two deposition orders are analyzed using the finite element method.

The scan parallel path and contour offset path are not suitable to fabricate blades directly. The hybrid of two types of paths and the hybrid of skeleton and contour offset paths are capable of forming blades without gaps. Deposition symmetrically can decrease the deformation of the propeller.

The slicing algorithm is simply implemented and practicable for any parts. The recognition of gaps and supplementary skeleton path can guarantee the full deposition of contour offset paths.

This paper aims to study the use of electrochemical noise (EN) technology in the corrosion continuous monitoring of stainless steel (SS) in an atmospheric environment.

An EN electrode was designed and fabricated to acquire the EN of 304 SS in the atmospheric environment. The statistical analysis and shot noise analysis were used to analyze the EN, and the surface morphology analysis of 304 SS was used to verify the EN analysis results.

The activation state, passive film formation and pitting corrosion of 304 SS can be clearly distinguished by the amplitude and frequency change of EN. The metastable pitting corrosion and steady-state pitting corrosion can be identified with the shot noise parameters q and fn. Under the existence of chloride ion, the stability of 304 SS passive film decreases and the steady-state corrosion pits of 304 SS are more likely to form with the reduction of thin electronic layer (TEL) pH. The critical TEL pH of 304 SS corrosion is a pH between 3 and 4.

In an atmospheric environment, the EN technology was used in the corrosion continuous monitoring of SS.

This study aims to consider active vision in low-visibility environments to reveal the factors of optical properties which affect visibility and to explore a method of obtaining different depths of fields by multimode imaging.Bad weather affects the driver’s visual range tremendously and thus has a serious impact on transport safety.

A new mechanism and a core algorithm for obtaining an excellent large field-depth image which can be used to aid safe driving is designed and implemented. In this mechanism, atmospheric extinction principle and field expansion system are researched as the basis, followed by image registration and fusion algorithm for the Infrared Extended Depth of Field (IR-EDOF) sensor.

The experimental results show that the idea we propose can work well to expand the field depth in a low-visibility road environment as a new aided safety-driving sensor.

The paper presents a new kind of active optical extension, as well as enhanced driving aids, which is an effective solution to the problem of weakening of visual ability. It is a practical engineering sensor scheme for safety driving in low-visibility road environments.

Deployment of deep neural networks on embedded devices is becoming increasingly popular because it can reduce latency and energy consumption for data communication. This paper aims to give out a method for deployment the deep neural networks on a quad-rotor aircraft for further expanding its application scope.

In this paper, a design scheme is proposed to implement the flight mission of the quad-rotor aircraft based on multi-sensor fusion. It integrates attitude acquisition module, global positioning system position acquisition module, optical flow sensor, ultrasonic sensor and Bluetooth communication module, etc. A 32-bit microcontroller is adopted as the main controller for the quad-rotor aircraft. To make the quad-rotor aircraft be more intelligent, the study also proposes a method to deploy the pre-trained deep neural networks model on the microcontroller based on the software packages of the RT-Thread internet of things operating system.

This design provides a simple and efficient design scheme to further integrate artificial intelligence (AI) algorithm for the control system design of quad-rotor aircraft.

This method provides an application example and a design reference for the implementation of AI algorithms on unmanned aerial vehicle or terminal robots.

In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal data, it has a low reconstruction error on normal data. However, when faced with complex natural images, the conventional pixel-level reconstruction becomes poor and does not show the promising results. This paper aims to provide a new method for improving the performance of novelty detection based autoencoder.

To solve the problem that conventional pixel-level reconstruction cannot effectively extract the global semantic information of the image, a novel model with the combination of attention mechanism and self-supervised learning method is proposed. First, an auxiliary task, reconstruct rotated image, is set to enable the network to learn global semantic feature information. Then, the channel attention mechanism is introduced to perform adaptive feature refinement on the intermediate feature map to optimize the correspondingly passed feature map.

Experimental results on three public data sets show that the proposed method has potential performance for novelty detection.

This study explores the ability of self-supervised learning methods and attention mechanism to extract features on a single class of images. In this way, the performance of novelty detection can be improved.

This paper aims to put forward a kind of new method of intelligent trust engineering metrics for application of mobile ad hoc network (MANET).

The new method calculates the communication trust by using the number of data packets among the nodes of MANET, predicts intelligently the trust and calculates the comprehensive trust based on the historical trust; then calculates the energy trust based on the residual energy of the nodes of MANET, calculates the direct trust based on the communication trust and energy trust. The new method calculates the recommendation trust based on the recommendation reliability; adopts the adaptive weighting to calculate the integrated direct trust by considering the direct trust with recommendation trust.

Based on the integrated direct trust and the factor of trust propagation distance, the indirect trust among the nodes of MANET is calculated. The above process can be optimized based on the dynamic machine learning presented in this study. The advantage of the new method is its intelligent ability to discover malicious nodes.

The advantage of the new method is its intelligent ability to discover malicious nodes which can partition the network by falsely reporting other nodes as misbehaving and proceeds to protect the network. The authors have done the experiments based on the tool kits such as NS3, QualNet, OMNET++ and MATLAB. The experimental results show that this study’s approach can effectively avoid the attacks of malicious nodes, and more conformable to the actual engineering application of MANET.

The purpose of this paper is to prepare a water-resistant adhesive (SA) from soy flour (SF) with less water-soluble components.

Defatted SF was suspended and stirred in water. Then, the pH of dispersion was adjusted to a predetermined value (i.e. 8, 9 or 10) by the addition of 2M sodium hydroxide (NaOH) solution. After stirring at a predetermined temperature (25°C, 35°C, 45°C) for different time (1 h, 2 h, 3 h), the 2M hydrochloric acid (HCl) solution was added in a dropwise manner into the dispersion until the pH value was adjusted to 4.5. Then, the dispersion was centrifuged at 6,000 rpm for 2 min. The obtained precipitate with less water-soluble components was used as an adhesive (SA) directly.

SA had a wet strength of 1.02 MPa when used for the fabrication of poplar plywood. Polyvinyl alcohol (PVA) solution was applied to improve the tack of SAs to wood surface and the viscosities of SAs were decreased from 10,200 cP to 4,100 cP at room temperature after the PVA addition. The soy proteins in SAs were not denatured to a large extent according to the differential scanning calorimetry and light microscopy. The remained multilevel structures of soy protein played a positive contribution to the water resistance of SAs, and the bond lines of cured SAs were much more stable than those of the cured SF and soy protein concentrate (SPC).

The fluidity and solid content of soy adhesives is much lower than formaldehyde adhesives. Further investigations are needed to improve the fluidity of soy adhesives with high solid contents.

Novel water-resistant soy adhesives were provided.

This paper aims to collect and compile the historical data of Guanfu Salt Farm, officially built by the Song Dynasty (960–1279) within modern Hong Kong territories, to reconstruct its history for the reflection of Hong Kong society of the time.

This paper is largely based on identification and analysis of historical documents, including keyword search on electronic databases and verification with the original sources, with reference to archaeological findings when necessary.

This paper reconstructs the history of Guanfu Salt Farm based on documentary sources with reference to archaeological findings. English translation of Chinese sources is also provided when necessary.

There has been an absence of systematic compilation of historical data of Hong Kong during the Song Dynasty, which are limited in quantity and scattered across different sources. This paper seeks to fill the vacuum of knowledge about pre-colonial Hong Kong, with a more comprehensive reconstruction of the history of Guanfu Salt Farm.