Search results

Many cities of various types are distributed in the large area of mountainous regions in China. In these cities, there are acute contradictions between man and earth. Considering that the space growth mode of mountainous cities is widely different from that of flatland cities, the fractal method was adopted in the research aimed at demarcating the urban growth boundary of mountainous cities. The fractal features of the investigated mountainous cities in space were figured out via inference from their function, dimension, region, grade, and environment, and the fractal mode and conceptual framework of urban growth boundary of Qin-Ba mountainous region were constructed according to some concepts and methods such as fractal dimension, fractal network, and fractal order. In the research, the traditional urban growth boundary form-was decomposed into scattered points (point form), paths (linear form), and patches (plane form) to form the fractal theory units for the research of urban growth boundary, and the leading idea, procedure, and control method for “fractal demarcation of urban growth boundary” were established to provide strategies for demarcation of urban space growth boundary of Qin-Ba mountainous region.

With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

The purpose of this paper is to test an innovative model for exploring the direct and indirect relationships between principals’ cognitive complexity (CC), schools’ absorptive capacity (ACAP), a teacher’s affective commitment and a teacher’s intent to leave.

Data were collected from a survey of 1,664 teachers at 107 Arab elementary schools, randomly selected from the database of the Israeli educational system. To test the proposed model, multilevel structural equation modeling was conducted.

The analysis confirmed that schools’ ACAP and a teacher’s affective commitment are prominent mediators between principals’ CC and a teacher’s intent to leave.

Understanding the factors that contribute to a teacher’s intent to leave could help school principals and policy makers retain effective teachers in today’s schools.

This study adds to the body of research directed at identifying school principals’ characteristics, as well as work-related factors, which may decrease a teacher’s intent to leave and are amenable to leadership intervention.

A smart city is a potential solution to the problems caused by the unprecedented speed of urbanization. However, the increasing availability of big data is a challenge for transforming a city into a smart one. Conventional statistics and econometric methods may not work well with big data. One promising direction is to leverage advanced machine learning tools in analyzing big data about cities. In this paper, the authors propose a model to learn region embedding. The learned embedding can be used for more accurate prediction by representing discrete variables as continuous vectors that encode the meaning of a region.

The authors use the random walk and skip-gram methods to learn embedding and update the preliminary embedding generated by graph convolutional network (GCN). The authors apply this model to a real-world dataset from Manhattan, New York, and use the learned embedding for crime event prediction.

This study’s results show that the proposed model can learn multi-dimensional city data more accurately. Thus, it facilitates cities to transform themselves into smarter ones that are more sustainable and efficient.

The authors propose an embedding model that can learn multi-dimensional city data for improving predictive analytics and urban operations. This model can learn more dimensions of city data, reduce the amount of computation and leverage distributed computing for smart city development and transformation.

This study aims to optimize the structure of gold-sputtered U-shaped plastic fiber sensors.

A group of U-shaped Au-sputtered plastic optical fiber sensing probes with polishing angles of 45°, 90° and 135° is prepared.

The experimental results show that the spectral response and sensitivity of the sensor at 45°polishing angle is twice that of the sensor at 90°.

Due to the limitations of laboratory temperature and equipment, the overall effect has not reached the ideal, but the expected effect has been obvious. Experiments also optimize the sensor.

Optical fiber sensing has always been an indispensable part of various fields.

Sensor optimization is of great help to the progress of technology and the development of science and technology.

The authors have no conflicts of interest to disclose.

The purpose of this paper is to draw on triadic reciprocal determinism and social exchange theory to examine how “induced-type” and “compulsory-type” union participation influence union commitment and job involvement, and how union participation in the west differs from that in China. It also examines whether the role of both organizational justice and employee participation climate (EPC) functions in the Chinese context.

Cross-sectional data are collected from 694 employees in 46 non-publicly owned enterprises, both Chinese and foreign, in the Pearl River Delta region of China. A multi-level moderated mediation test is used to examine the model of this research.

Union participation is positively related to organizational justice, union commitment and job involvement. In addition, organizational justice acts as the mediator among union participation, union commitment and job involvement. Specifically, the mediating role of organizational justice between union participation and union commitment, and between union participation and job involvement, is stronger in high-EPC contexts than low-EPC contexts.

Instead of examining the impacts of attitudes on union participation, as per most studies in the western context, this research examines the impacts of union participation in the Chinese context on attitudes, including union commitment and job involvement. It also reveals the role of both organizational justice and EPC in the process through which union participation influences union commitment and job involvement.

The purpose of this paper is to prepare the Mn‐Si‐Fe‐Cu‐Al alloy explosion suppression materials, and determine the corrosion behavior of aluminum alloy explosion suppression materials in HCl and NaOH solutions. The different mechanism of corrosion was discussed.

In this paper, Mn‐Si‐Fe‐Cu‐Al alloy explosion suppression materials were prepared, and the electrochemical behavior of the EAESM was studied. The corrosion parameters were calculated and the mechanism of the corrosion process was discussed. The corrosion behavior was characterized by immersion tests and SEM at room temperature.

Mn‐Si‐Fe‐Cu‐Al alloy explosion suppression materials have been prepared. SEM, the polarization curves showed that materials have corrosion resistance. The best content of Al alloy is Mn 0.880%, Si 0.135%, Fe 0.383% and Cu 0.0835%.

The results of this investigation show that adding alloying elements can form new strengthening phases that influence the corrosion resistance of alloys.

Tongue diagnosis is a standard expert technique of traditional Chinese medicine (TCM). Computerized tongue diagnosis promises to automate the process of tongue diagnosis yet the tongue images segmentation upon which it depends is made difficult by the fact that the tongue is non‐rigid and varies greatly in size, shape, color, and texture. This paper presents a novel medical sensor system for TCM tongue diagnosis, which makes use of hyperspectral imaging technology.

The tongue image capturing sensor device for Chinese medical is based on the theory of the pushbroom hyperspectral imager. The paper illustrates its advantages by detecting the tongue contour in the hyperspectral images.

The experiments from 1,522 clinical tongue images show the validity of the system.

In this paper, the authors propose to use hyperspectral technology for tongue diagnosis for the first time in the literature and obtain promising results.

The novel sensor for tongue image capture gives a new method for tongue imformation collection. This system gives a new approach for tongue information collection.

This conceptual paper explores a novel model explaining teachers' perceptions of their effective leader through the lens of implicit leadership theory (ILT), using the concepts of school principals' sense-making and cognitive complexity (CC).

The sense-making framework and CC theory were used to explain ILT, which focuses on individuals' perceptions of leaders' prototypical and anti-prototypical attributes.

The theoretical model suggests that school principals as sense-makers with high levels of CC will be perceived by teachers as effective in terms of leadership prototypes, whereas teachers' perceptions of principals with low levels of CC will be related to leadership anti-prototypes.

This paper suggests a model for a multidimensional understanding of the relationship between principals' sense-making and CC and their influence on teachers' perceptions of an effective leader.

Opening avenues for future research into employee perceptions of different leadership characteristics, this model emphasizes the cognitive aspects of school principals within implicit leadership theories. This theoretical model should be further examined empirically, and other types of CC, such as social and behavioral aspects, or affective complexity and self-complexity, should be considered.

The purpose of current study was to investigate the impact of supervisor support on Knowledge Sharing Behavior through psychological well-being, psychological ownership, and Alturism. The study also took mindfulness as first path moderator in the relation to supervisor support and psychological well-being, and psychological ownership.

Positivism research philosophy followed by the deductive approach is followed to meet the objectives of the current study. A total of 219 employees from the telecom sector were identified as the respondents of the study. A purposive sampling technique was used to collect the data through self-administrated questionnaires. Exploratory and confirmatory factor analyses were used through AMOS to generate the results and test hypotheses.

The results suggested that supervisor support significantly contributes to the achievement of the knowledge-sharing behavior of employees with the chain of mediation, i.e. psychological well-being, ownership and altruism. Similarly, the moderating role of mindfulness is significant in the relationship between supervisor support and psychological well-being.

Although a number of researchers have studied the link between supervisor support and other employees related attitudinal and behavioral outcomes, few have explored the roles of psychological ownership, well-being and altruism in the relationship of knowledge sharing behavior. This study thus posits a novel sequential mediation and moderation mechanism, based on the social exchange theory, through which supervisor support is translated into knowledge sharing behavior.