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This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors.

First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm.

The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers.

In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm.

With the increasing importance of e-commerce to the economy and people's lives, user-generated content, such as electronic word-of-mouth (eWOM) represented by online reviews, has exploded. On one hand, it is of great significance for review consumers (readers) to identify high-quality ones from a large number of existing reviews to assist their purchase decision. On the other hand, how to use appropriate strategies to make their published reviews more concerned by others is also important to review generators (reviewers). The purpose of this study is to understand the comprehensive relationship among review characteristics, review helpfulness and receiver attention.

This study uses the online movie reviews obtained from the most popular review platform in China to conduct multiple empirical analyses.

The results show that the review helpfulness plays a mediating role between the emotional characteristics of online reviews and the receiver attention, and such a mediating role is more significant among reviewers with rich review expertise. The reviewer's expertise also moderates the impact of review emotions on review helpfulness.

This work studies eWOM receiver involvement, which can ultimately impact product sales, but seldom be investigated in eWOM domain. Therefore, this research can enrich studies on eWOM and provide valuable practical implications as well.

The purpose of this paper is to investigate the factors influencing the development of social media marketing strategy in an international context. We specifically look at the potential drivers and barriers throughout the social media marketing strategy development process and how cultural differences shape social media marketing strategy decision-making among firms in international markets.

The study is conducted with an inductive research approach involving in-depth interviews with 32 firms from Finland, China and Brazil. Using inductive data analysis, we identify both internal and external factors that drive and hinder the development of firms’ social media marketing strategies. Moreover, we explore the essential elements in social media marketing strategy development based on the key practices observed among these firms, which enables us to conduct a comparative analysis of how cultural values influence the development of social media marketing strategies.

Our findings underscore the importance of both internal (i.e. resources and capabilities) and external (i.e. market-level and country-level) factors that influence the development of social media marketing strategy. Our analysis also unveiled four key practices throughout the social media marketing strategy development process: social selling, content marketing, risk management and relationship management. Additionally, we identified three distinct mindsets regarding firms’ social media selling objectives across companies in the three countries.

The comparative approach provides novel insight into firms' international social media marketing strategy. Our proposed conceptual model shows the development process of social media marketing strategy in the international context. The research propositions highlight the role of cultural values and open up new avenues for future research.

This study aims to identify an antecedent that hinders knowledge sharing, namely, the perceived climate of Cha-xu. Based on the social exchange perspective, the authors propose a theoretical model that links the perceived climate of Cha-xu to employee knowledge sharing. This model focuses on the mediating role of two types of trust (vertical and horizontal trust) and the moderating role of task interdependence in influencing the mediation.

Using a sample of 509 Chinese employees, this study carried out a survey on an online platform. This study developed a structural equation model and tested the moderated mediation hypothesis by using Mplus 8.0.

The results showed that two types of trust act as mediators in the relationship between the perceived climate of Cha-xu and knowledge-sharing processes. The mediating effect of horizontal trust is stronger. Most significantly, findings show that this mediated relationship is contingent on the level of task interdependence.

This paper provides evidence for distinguishing vertical trust and horizontal trust in the field of knowledge management. From a managerial perspective, this study identifies traditional cultural factors for hindering knowledge-sharing processes within Chinese organizations.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.

This paper aims to present a longitudinal and visualizing study using scientometric approaches to depict the historical changes in the academic community, intellectual base and research hotspots within the business domain.

Two mapping methods are used, namely, co-citation analysis and co-occurrence analysis. Both the co-citation analysis and co-occurrence analysis in this study are conducted using CiteSpace, a Java-based scientific visualization software.

This paper detects changes in academic communities in 24 business journals chosen by the University of Texas at Dallas as leading journals (UTD24) and identifies the research hotspots such as corporate governance, organizational research and capital research. Many authors and academic communities appear in two or even three periods, which indicates the lasting academic vitality of scholars in this field. This paper determines the evolution of scholars' research interests by identifying high-frequency keywords during the entire period.

This paper reveals a systematic and holistic picture of the developmental landscape of the business domain, which can provide a potential guide for future research. Furthermore, based on empirical data and knowledge visualization, the intellectual structure and evolution of the business domain can be identified more objectively.

Rapid prototyping (RP) technology is widely used in many fields in recent years. Bone tissue engineering (TE) is an interdisciplinary field involving life sciences, engineering and materials science. Hydroxyapatite (HAp) are similar to natural bone and it has been extensively studied due to its excellent biocompatibility and osteoconductivity. This paper aims to review nanoscaled HAp-based scaffolds with high porosity fabricated by various RP methods for bone regeneration.

The review focused on the fabrication methods of HAp composite scaffolds through RP techniques. The paper summarized the evaluation of these scaffolds on the basis of their biocompatibility and biodegradability through in vitro and in vivo tests. Finally, a summary and perspectives on this active area of research are provided.

HAp composite scaffold fabricated by RP methods has been widely used in bone TE and it has been deeply studied by researchers during the past two decades. However, its brittleness and difficulty in processing have largely limited its wide application in TE. Therefore, the formability of HAp combined with biocompatible organic materials and fabrication techniques could be effectively enhanced, and it can be used in bone TE applications finally.

This review paper presented a comprehensive study of the various types of HAp composite scaffold fabricated by RP technologies and introduced their potential application in bone TE, as well as future roadmap and perspective.

At present, one of the key equipment in pillar industries is a large rotating machinery. Conducting regular health monitoring is important for ensuring safe operation of the large rotating machinery. Because vibrations sensors play an important role in the workings of the rotating machinery, measuring its vibration signal is an important task in health monitoring. This paper aims to present these.

In this work, the contact vibration sensor and the non-contact vibration sensor have been discussed. These sensors consist of two types: the electric vibration sensor and the optical fiber vibration sensor. Their applications in the large rotating machinery for the purpose of health monitoring are summarized, and their advantages and disadvantages are also presented.

Compared with the electric vibration sensor, the optical fiber vibration sensor of large rotating machinery has unique advantages in health monitoring, such as provision of immunity against electromagnetic interference, requirement of less insulation and provision of long-distance signal transmission.

Both contact vibration sensor and non-contact vibration sensor have been discussed. Among them, the electric vibration sensor and the optical fiber vibration sensor are compared. Future research direction of the vibration sensors is presented.

Dairy products are an essential part of a healthy diet, and dairy is an emerging food industry in China. Meanwhile, the dairy industry is one of the “disaster zones” with quality and safety issues occurring more frequently in its supply chain than in others. Based on qualitative research focused on consumers in the Northwest and South of China, the present study aims to understand and provide information on consumer perception of food safety in dairy products.

Nine focus group interviews were carried out from January to April 2018. Altogether, 61 participants (24 males, 37 females, aged 18–60 years) were recruited in four cities. Qualitative content analysis of the data was conducted using Nvivo version 11.4.0.

A high concern with the safety of dairy products is widespread, particularly among participants with children, who are especially worried about the safety of dairy products. High prevalence of food safety incidents causes consumers to lower their confidence in food safety, and make them pay more attention to the news about food safety incidents. Consumers tend to become less sensitive to price, focusing more on food safety and quality, while purchasing dairy products. Brand and purchase venue are the most important indicators for consumers to determine the quality of dairy products. Safety certification becomes increasingly important.

It has some limitations. The focus group interviews covered different two regions (Northwest and South of China). However, the number of focus groups was limited to nine because of budget constraints. The participants come from Northwest and South of the country, which means that the findings may not apply for another area of the country. A more representative sampling with a larger sample size would be necessary to increase the validity of the study. However, the results can serve as input for further research.

This paper explores the Chinese consumers' perception of food safety and dairy products, consumers' behaviour concerning dairy products based on focus group interviews with consumers. This study offers valuable insights to members of academia, food suppliers and policy-makers.

The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.

A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.

The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.

The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.

A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.