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The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of “situational awareness evaluation warning active control,” a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China’s railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.

The engineering education accreditation (EEA) is a principal quality assurance mechanism. However, at many education institutions, the most labor-intensive work of EEA process is accomplished manually. Without the support of computer and information technology, the EEA process leads to high labor intensity, low work efficiency and poor management level. The purpose of this paper is to build a complex network model and realize an information management system of talent training program for supporting the EEA process.

Based on polychromatic graph (PG), this paper builds a network model of talent training program for engineering specialty. The related information and data are organized and processed in this network model. From the bidirections of top-down and bottom-up, the user requirements are retrieved automatically in logic layer. Together with the specialty of mechanical engineering, the proposed PG-based network modeling method is applied and the corresponding information management system is realized.

The study results show that the PG-based network modeling method takes full advantages of the strong simulation ability of PG to model the complex network system and has some unique merits in formal expression of problem, efficient processing of information and lightweight realization of system. Further, the information management system of talent training program can reduce the tedious human labor and improve the management level of EEA process dramatically.

This paper proposes a PG-based network modeling method, in which the nodes and the edges can be painted by some unified colors to describe the different kinds of activities and the various types of interactions. Theoretically, this modeling method does not distinguish the activities, the interactions and their properties in graphic symbol and the problem size is diminished about a half. Furthermore, this paper provides an effective experience and idea to the education institutions for implementing the engineering education accreditation, increasing the education management efficiency and promoting the talent training quality.

The Web 3D virtual display technology for personalized clothing based on Unity3D is studied in this paper. The framework of the technology is described. The development steps including personalized clothing design and modeling, interaction and virtual display technology based on Unity3D are given out. The purpose of this paper is to provide a feasible technical route and support for the virtual display for the customized products.

The paper opted for an exploratory study using the open-ended approach of grounded theory, including the Web 3D virtual display technology for personalized clothing based on Unity3D.

A feasible technical route for the virtual display of the customized products is provides in this paper.

This paper fulfills a software and has practical use.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China.

This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen.

The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications.

This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

This paper aims to develop an efficient numerical method for nonlinear transient heat conduction problems with local radiation boundary conditions and nonlinear heat sources.

Based on the physical characteristic of the transient heat conduction and the distribution characteristic of the Green’s function, a quasi-superposition principle is presented for the transient heat conduction problems with local nonlinearities. Then, an efficient method is developed, which indicates that the solution of the original nonlinear problem can be derived by solving some nonlinear problems with small structures and a linear problem with the original structure. These problems are independent of each other and can be solved simultaneously by the parallel computing technique.

Within a small time step, the nonlinear thermal loads can only induce significant temperature responses of the regions near the positions of the nonlinear thermal loads, whereas the temperature responses of the remaining regions are very close to zero. According to the above physical characteristic, the original nonlinear problem can be transformed into some nonlinear problems with small structures and a linear problem with the original structure.

An efficient and accurate numerical method is presented for transient heat conduction problems with local nonlinearities, and some numerical examples demonstrate the high efficiency and accuracy of the proposed method.

With rising environmental concerns, recent years have witnessed a significant surge of academic and corporate interest in green supply chain coordination (GSCC). This is evident from the rise in channel coordination literature focused toward the elimination of sub-optimal in the green supply chain (GSC). This paper seeks to summarize the model-based research on coordination in GSCs with the help of a framework developed specifically for this paper. The purpose of this paper is to present an in-depth analysis of the widely used models in the area.

A review of literature is presented in this paper to examine the underlying concepts peculiar to GSCC. A classification framework is developed to present an exhaustive survey of commonly used concepts.

Around 90 percent of the papers on GSCC come from game theory (GT) application, which explicitly utilizes coordination through contracts. The review concludes prospective area of research in GSCC. The study posits that there exists a potential of creating a more rational and efficient coordination strategies to improve GSC’s operational performance, with the view of the optimum distribution of resources and better environmental management.

To the best of authors’ knowledge, this is the first state-of-the-art review of GSCC literature focused primarily on mathematical model-based literature. This review identifies various methodological and content-oriented characteristics of GSCC. The paper also opens avenues of future research.

The purpose of this chapter is to evaluate and discuss the factors that underpin tourists' perceptions of anti-COVID-19 practices in tourist accommodations and destinations, as well as in tourists' experience, satisfaction and behaviour, in order to make recommendations for managers at hotels and tourist destinations.

A survey at tourist accommodations in the Canary Islands was conducted to collect data, and 431 questionnaires were part of the final analysis. The data were analysed with the SPSS27 statistical processing software. Various multivariate techniques such as correlation analysis and factor analysis were used to analyse the data.

The results reveal that anti-COVID-19 practices at the accommodation are the most important for tourists to feel safe in their visit to the destination. The most important factors in the tourists' experience during the pandemic are those related to communication and behaviour. Satisfaction after COVID-19 is perceived higher if places or items for cleaning and disinfestation are provided to tourists and rooms are naturally ventilated, while intentions to visit after COVID-19 are highest to visit local destinations.

The results of the research will support scholars and practitioners to recognise the importance of factors that influence anti-COVID-19 practices, tourists' experience, satisfaction and behaviour during the pandemic. In addition, the research offers policy recommendations for maximum benefits for the tourism industry in the Canary Islands and others tourist destinations.

The chapter was an original primary and exploratory study that surveyed tourists to determine their perceptions of anti-COVID-19 practices, experience, satisfaction and behaviour during the pandemic. The results reveal the most important factors in the construction of the analysed variables, and may be used as a starting point for further hospitality marketing research.

Additive manufacturing (AM) or solid freeform fabrication (SFF) technique is extensively used to produce intrinsic 3D structures with high accuracy. Its significant contributions in the field of tissue engineering (TE) have significantly increased in the recent years. TE is used to regenerate or repair impaired tissues which are caused by trauma, disease and injury in human body. There are a number of novel materials such as polymers, ceramics and composites, which possess immense potential for production of scaffolds. However, the major challenge is in developing those bioactive and patient-specific scaffolds, which have a required controlled design like pore architecture with good interconnectivity, optimized porosity and microstructure. Such design not only supports cell proliferation but also promotes good adhesion and differentiation. However, the traditional techniques fail to fulfill all the required specific properties in tissue scaffold. The purpose of this study is to report the review on AM techniques for the fabrication of TE scaffolds.

The present review paper provides a detailed analysis of the widely used AM techniques to construct tissue scaffolds using stereolithography (SLA), selective laser sintering (SLS), fused deposition modeling (FDM), binder jetting (BJ) and advanced or hybrid additive manufacturing methods.

Subsequently, this study also focuses on understanding the concepts of TE scaffolds and their characteristics, working principle of scaffolds fabrication process. Besides this, mechanical properties, characteristics of microstructure, in vitro and in vivo analysis of the fabricated scaffolds have also been discussed in detail.

The review paper highlights the way forward in the area of additive manufacturing applications in TE field by following a systematic review methodology.