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The purpose of this paper is to mainly center on the touchless interaction between humans and robots in the real world. The accuracy of hand pose identification and stable operation in a non-stationary environment is the main challenge, especially in multiple sensors conditions. To guarantee the human-machine interaction system’s performance with a high recognition rate and lower computational time, an adaptive sensor fusion labeling framework should be considered in surgery robot teleoperation.

In this paper, a hand pose estimation model is proposed consisting of automatic labeling and classified based on a deep convolutional neural networks (DCNN) structure. Subsequently, an adaptive sensor fusion methodology is proposed for hand pose estimation with two leap motions. The sensor fusion system is implemented to process depth data and electromyography signals capturing from Myo Armband and leap motion, respectively. The developed adaptive methodology can perform stable and continuous hand position estimation even when a single sensor is unable to detect a hand.

The proposed adaptive sensor fusion method is verified with various experiments in six degrees of freedom in space. The results showed that the clustering model acquires the highest clustering accuracy (96.31%) than other methods, which can be regarded as real gestures. Moreover, the DCNN classifier gets the highest performance (88.47% accuracy and lowest computational time) than other methods.

This study can provide theoretical and engineering guidance for hand pose recognition in surgery robot teleoperation and design a new deep learning model for accuracy enhancement.

Due to significant differences between urban and rural areas in terms of geographical environment, building scale, resident culture, social organization and other aspects, the post-disaster recovery and reconstruction models for both exhibit substantial variation. This study identifies critical strategic issues that must be addressed in housing reconstruction in the context of different social structures of urban–rural “integration” and urban–rural “dualization” to achieve the goal of “building back better” in the future.

By taking the experience of the 5.12 Wenchuan earthquake and the Taiwan 9.21 earthquake as a reference, this study provides a thematic analysis and systematic summary of the entire process of post-disaster housing reconstruction.

A successful housing reconstruction process should actively engage disaster-affected populations through participatory institutional design. Providing a diverse housing reconstruction model can coordinate the interests of the government, the market and affected individuals, promoting harmony of residential, productive and ecological functions. However, it can also lead to the division of existing communities.

This research relies on existing literature, government publications, academic studies and news reports, which may carry inherent biases or omissions. Future research can benefit from conducting more extensive and long-term post-reconstruction surveys to assess the sustained impact of recovery efforts while also considering additional data sources to ensure comprehensive and unbiased analyses.

With the support of post-disaster reconstruction policies, diverse changes in land use can lead to urban and rural spatial pattern reform and sustainable regional development, providing a reference for formulating optimal strategies.

This study carries significant societal implications by addressing critical strategic issues in housing reconstruction within varying urban–rural social structures. It highlights the importance of engaging affected populations through participatory design and harmonizing government, market and individual interests. The research introduces strategies for activating rural construction land quotas and creating new funding sources, promoting sustainable regional development. Its findings contribute to post-disaster reconstruction models, offering valuable insights for policymakers and stakeholders, ultimately leading to more effective and inclusive recovery efforts and benefiting disaster-prone areas worldwide.

This research primarily investigates the market circulation patterns of urban and rural land under different social structures, delves into the strategies for sources of housing reconstruction funding, along with an assessment of their effectiveness.

The purpose of this paper is to investigate relationships of urban seismic resilience assessment indicators.

To achieve this aim, construction of the urban seismic resilience assessment indicators system was conducted and 20 indicators covering five dimensions, namely building and lifeline infrastructure, environment, society, economy and institution were identified. Following this, this study used evidence fusion theory and intuitionistic fuzzy sets to process the information from experts then developed the fuzzy total interpretive structure model.

A total of 20 urban seismic resilience assessment indicators are reconstructed into a hierarchical and visual system structure including five levels. Indicators in the bottom level including debris flow risk, landslide risk, earthquake experience and demographic characteristics are fundamental indicators that significantly impact other indicators. Indicators in the top level including open space, gas system and public security are direct indicators influenced more by other indicators. Other indicators are in middle levels. Results of MICMAC analysis visually categorize these indicators into independent indicators, linkage indicators, autonomous indicators and dependent indicators according to driving power and dependence.

This paper attempts to explore relationships of urban seismic resilience assessment indicators with the interpretive structural model method. Additionally, Fuzzy total interpretive structure model is developed combined with evidence fusion theory and intuitionistic fuzzy sets, which is the extension of total interpretive structure model. Research results can assist the analytic network process method in assessing urban seismic resilience in future research.

The aim of this paper is to review the recent corporate social responsibility (CSR) literature in China, which has the world's largest developing economy. Through discussions and critical review, the objective is to suggest future directions for CSR research in this country.

The paper starts with a review of recent CSR literature in the mainland, followed by an in‐depth critique of two major Chinese CSR studies conducted by the Chinese Academy of Social Sciences.

In China, much of the CSR literature is conceptual, descriptive, or argumentative in nature. Proper research methodologies are not systematically applied in some studies, and supporting theories are lacking. Besides, self‐developed indicator systems, rather than internationally adopted systems, are used as the mainstream measurement tools in research focusing on CSR performance evaluation. In general, CSR research in China has just got started and has a long way to go.

Recent reviews of CSR literature have concentrated on emerging economies, particularly Bangladesh, India, Indonesia, Malaysia, and so on. This paper is one of the first reviews of CSR studies in mainland China. It contributes to understanding the development of Chinese CSR research. After the review and discourse, several research questions are suggested for future research.