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The purpose of this paper is to make research on causing mechanism of meteorological disaster as well as the components of meteorological disaster system and their semantic relationships. It has important practical significance due to the urgent need of further providing support for pre-assessment of influences of disastrous weather/climate events and promoting the level of emergency management.

This paper analyses the occurrence regulations and components of meteorological disasters and proposes the concept of meta-action. Ontology modelling method is adopted to describe the components and relationships among different parts comprising meteorological disaster system, and semantic web rule language is selected to identify the implicit relationships among the domain knowledge explicitly defined in ontology model. Besides, a case is studied to elaborate how to provide logic and semantic information support for comprehensive risk assessment of disastrous weather/climate events based on rule-based ontology reasoning method. It proves that ontology modelling and reasoning method is effective in providing decision makings.

This paper provides deep analyses about causing mechanisms of meteorological disasters, and implements information fusion of the components of meteorological disaster system and acquisition of potential semantic relations among ontology components and their individuals.

In this paper, on the basis of analysing the disaster-causing mechanisms, the meteorological disaster ontology (MDO) model is proposed by using the ontology modelling and reasoning method. MDO can be applied to provide decision makings for meteorological departments.

The purpose of this paper is to address the urgent need for guiding the construction of information systems for disease surveillance and early warning, given the latest efforts of the report system of public health information over China.

A system framework for disease surveillance and early warning, based on disease clustering test and cluster detection techniques, geographical information system, network and communication is conceived. Through geographical surveillance analysis of severe acute respiratory syndrome occurring in Beijing in 2003, an application example of the framework is illustrated.

Through approaches such as integrating spatial‐time clustering test and cluster detection algorithms, spatial visualization, computer network, wireless communication, it is feasible to build a systematic, automatic, real‐time surveillance and early warning system for prevention and control of disease.

The present study provides an underlying framework for the development of disease surveillance and early warning system enabling data acquisition, data analysis and alarm publishing.

The framework integrates report system of public health information, GIS and disease clustering test and cluster detection techniques into an application, which will significantly enhance the resilience of healthcare facilities. It is supposed to be implemented in near future and provides fundamental support for nation‐wide disease surveillance and early warning.

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

Examines China’s population movement since the 1980s. The analysis tackles two types of migration: permanent with corresponding transfers of the household registration, and temporary without such transfers. The study finds that, while the reform has brought about a proliferation of temporary migrants, numbers of permanent migrants have been rather stable. Of temporary migrants, an increasing proportion has been made up by urban residents. Temporary migrants as a whole are more likely to conduct inter‐provincial migration than their permanent counterparts. Coastal provinces and a few northwest provinces have been the favored destinations for temporary migrants. Cities, especially large cities, are preferred by both permanent and temporary migrants. The attraction of towns has been weak and tended to decline. The findings suggest that the reform has not led to a significant change in the formality of permanent migration. The large‐city oriented flow of the overall migration has been contrary to the state urbanization strategy which prioritizes the development of small cities and towns.

The purpose of this paper is to study the evolution of Chinese industrial relations after the market reform of 1978, while basing its arguments and conclusion on analysis of the interactions of key actors in the labour arena in China. The significant phenomena in the evolution of industrial relations are the coming of transnational capital and the emergence of self‐organising protests by migrant workers.

The paper uses a case study approach.

The Labour Contract Law and the local political economy experience strong effects from TNCs and other business players. Meanwhile, globalisation has introduced the civil society movement to China, which has given rise to an increasing number of NGOs working for labour rights. Tight financial and technical connections between grassroots NGOs and international donor organisations make it possible for bottom‐up labour activities to counteract the unilateral influence of the state and market over the Chinese workforce. Since the ACFTU, the official trade union umbrella, has many institutional constraints to undertake a thorough transition towards labour in the near future, workers' representation is diversified.

One implication for further theoretical studies is that tripartism cannot fully disclose the reality of Chinese labour, and that labour representation derives from both unions and self‐organisation of workers, such as NGOs, which opens more room for the entrenchment of the grassroots labour movement to sustain the balance of power among the state, ACFTU, firms, international market forces and individual workers in the long term.