Search results

The synthetic application and interaction of/between the internet, Internet of Things, cloud computing, big data, Industry 4.0 and other new patterns and new technologies shall breed future Web-based industrial operation system and social operation management patterns, manifesting as a crowd cyber eco-system composed of multiple interconnected intelligent agents (enterprises, individuals and governmental agencies) and its dynamic behaviors. This paper aims to explore the basic principles and laws of such a system and its behavior.

The authors propose the concepts of crowd science and engineering (CSE) and expound its main content, thus forming a research framework of theories and methodologies of crowd science.

CSE is expected to substantially promote the formation and development of crowd science and thus lay a foundation for the advancement of Web-based industrial operation system and social operation management patterns.

This paper is the first one to propose the concepts of CSE, which lights the beacon for the future research in this area.

With the development of intelligent technology, deep learning has made significant progress and has been widely used in various fields. Deep learning is data-driven, and its training process requires a large amount of data to improve model performance. However, labeled data is expensive and not readily available.

To address the above problem, researchers have integrated semi-supervised and deep learning, using a limited number of labeled data and many unlabeled data to train models. In this paper, Generative Adversarial Networks (GANs) are analyzed as an entry point. Firstly, we discuss the current research on GANs in image super-resolution applications, including supervised, unsupervised, and semi-supervised learning approaches. Secondly, based on semi-supervised learning, different optimization methods are introduced as an example of image classification. Eventually, experimental comparisons and analyses of existing semi-supervised optimization methods based on GANs will be performed.

Following the analysis of the selected studies, we summarize the problems that existed during the research process and propose future research directions.

This paper reviews and analyzes research on generative adversarial networks for image super-resolution and classification from various learning approaches. The comparative analysis of experimental results on current semi-supervised GAN optimizations is performed to provide a reference for further research.

This paper aims to examine the role of the Chinese People’s Political Consultative Conference (CPPCC), a political advisory body in China, in addressing environmental challenges.

This study uses 457 CPPCC environmental proposals across 160 cities for the period of 2013 to 2015 and a mediation effect model to examine the effect of CPPCC environmental proposals on environmental quality.

This study shows that CPPCC environmental proposals improve environmental quality; and the relationship between CPPCC environmental proposals and environmental quality is partially mediated by enforcement of environmental laws and regulations only although the proposals positively influence both law enforcement and environmental public budget expenditures.

Future research may examine how the interaction between the government and other important stakeholders such as non-governmental organizations can help improve environmental quality. In addition, future research may examine whether other policy tools such as pollution tax and fees, environmental subsidies, and emissions trading can play a role in dealing with environmental issues.

This study provides evidence that supports CPPCC members to take an even more active role in public governance by engaging with both the government and the public.

The CPPCC’s participation in public governance helps the government respond to critical issues more effectively. The government should pay close attention to CPPCC proposals when making public policies. Furthermore, the government probably needs to review its policies in relation to environmental expenditures.

This study is the first to examine the role of the CPPCC, a political advisory body, in addressing environmental challenges through functioning as a bridge between government and the public, whereas the extant literature has predominantly focused on the role of government, market and the public.

The purpose of this paper is to analyse the impact of high-speed railway (HSR) on industrial pollution emissions using the data for 285 prefecture-level cities in China from 2004 to 2016.

The research method used in this paper is the multi-period difference-in-differences (DID) model, which is an effective policy effect assessment method. To further address the issue of endogeneity, the DID integrated with the propensity score matching (PSM-DID) approach is employed to eliminate the potential self-selection bias.

The results show that the HSR has significantly reduced industrial pollution emissions, which is validated by several robustness tests. Compared with peripheral cities, HSR exerts a greater impact on industrial pollution emissions in central cities. In addition, the mechanism test reveals that the optimised allocation of inter-city industries is an important channel for HSR to mitigate industrial pollution emissions, and this is closely related to the location of HSR stations.

Previous studies have paid more attention to evaluating the economic effects of HSR, however, most of these studies overlook its environmental effects. Consequently, the impact of HSR on industrial pollution emissions is led by using multi-period DID models in this paper, in which the environmental effects are measured. The results of this paper can provide a reference for the pollution reduction policies and also the coordinated development of economic growth and environmental quality.

Rural credit cooperatives (RCCs) have long dominated China’s rural credit market and met most of agricultural credit demands while the existing literature seldom examines their contribution to agricultural sector. The purpose of this paper is to provide empirical evidence on the contribution of RCCs to agricultural growth, using China’s provincial panel data from 1997 to 2014.

Both static fixed effects models and two-step generalized method of moment dynamic panel data models, which control the endogeneity, are employed to identify the causality from RCC credit to agricultural growth in China.

The results show that the credit from RCCs increases the agricultural output significantly. A 1 percent increase in RCC credit leads to agricultural growth of about 0.08 percent, which is robust to various empirical specifications. Further study shows that the contribution of RCC credit to agricultural growth decreases from the most developed eastern region to the least developed western region and increases over time.

The results imply that RCC credit is critical in financing agricultural activities by relaxing rural credit constraints and intense competition strengthens the contribution of RCCs to agricultural growth by improving managerial efficiency and developing diversified financial products to meet better rural credit demands.

To the authors’ knowledge, this is first empirical study on the effect of RCC credit on agricultural growth despite of many on the role of financial development in agricultural growth.

People's socializing behavior in social networking services (SNS) presents dramatically different features, forming differentiated online social interaction patterns (DOSIP) in SNS. This study aims to explore the relationships between users' multidimensional psychological needs and multiple social interaction patterns in SNS.

Based on Maslow's hierarchy of needs and use and gratifications (U&G) theory, the authors develop the research model to examine the effects of psychological needs on DOSIP. A survey is used to collect the data of SNS users' social interaction. The authors adopt structural equation modeling–neural network (SEM-NN) integrated method to examine the research model.

Need to belong, need for self-esteem, need for social contact, need for emotional expression, need for cognition, and need for external-esteem have significant influences on both active and passive social interactions respectively.

Based on the categorization of DOSIP into six types in terms of the level of activity and disclosure of social interaction, the authors construct an integrated research model of multidimensional psychological needs to multiple social interaction patterns, and validate the antecedents of DOSIP from the perspective of psychological needs.

The purpose of this study is to regard winter heating as a quasi-natural experiment to identify the possible causal effects of winter heating on population mobility. However, there are scant research studies examining the effect of atmospheric quality on population mobility. There also exists some relevant research studies on the relationship between population mobility and environmental degradation (Lu et al., 2018; Reis et al., 2018; Shen et al., 2018), and these studies exist still some deficiencies.

The notorious atmospheric quality problems caused by coal-fired heating in winter of northern China have an aroused widespread concern. However, the quantitative study on the effects on population mobility of winter heating is still rare. In this study, the authors regard the winter heating as a quasi-natural experiment, based on the of daily panel data of 58 cities of Tencent location Big Data in China from August 13 to December 30 in 2016 and August 16 to December 30 in 2017, and examine the impacts of winter heating on population mobility by utilizing a regression discontinuity method.

The findings are as follows, in general, winter heating significantly aggravates regional population mobility, but the impacts on population mobility among different cities are heterogeneous. Specifically, the effects of winter heating on population mobility is greater for cities with relatively good air quality, and the effects is also more obvious for big and medium-sized cities than that in small cities. In addition, different robustness tests, including continuity test, different bandwidth tests and alternative empirical model, are adopted to ensure the reliability of the conclusion. Finally, the authors put forward corresponding policy suggestions from the three dimensions of government, enterprises and residents.

First, regarding winter heating as a quasi-natural experiment, a regression discontinuity design method is introduced to investigate the relationship between winter heating and population mobility, which is helpful to avoid the estimation error caused by endogeneity. Second, the authors use the passenger travel “big data” based on the website of Tencent Location Big Data, which can effectively capture the daily characteristics of China's population mobility. Third, this study discusses the population mobility from the perspective of winter heating and researches population mobility before and after winter heating, which is helpful in enriching the research on population mobility.

The purpose of this paper is to provide the historical background of genealogical records and analyze the value of Chinese genealogical research through the study of names and genealogical resources.

The paper examines the historical evolution and value of Chinese genealogical records, with the focus on researching the Islamic Chinese names used by the people living in Guilin. The highlight of this paper includes the analysis and evolution of the Islamic Chinese names commonly adopted by the local people in Guilin. It concludes with the recommendations on emphasizing and making the best use of genealogical records to enhance the research value of Chinese overseas studies.

The paper covers the history of Islam and describes how the religion was introduced into China, as well as Muslims' ethnicity and identity. It also places focus on the importance of building a research collection in Asian history and Chinese genealogy.

This research study has a strong subject focus on Chinese genealogy, Asian history, and Islamic Chinese surnames. It is a narrow field that few researchers have delved into.

The results of this study will assist students, researchers, and the general public in tracing the origin of their surnames and developing their interest in the social and historical value of Chinese local history and genealogies.

The study of Chinese surnames is, by itself, a particular field for researching the social and political implications of contemporary Chinese society during the time the family members lived.

Very little research has been done in the area of Chinese local history and genealogy. The paper would be of value to researchers such as historians, sociologists, ethnologists and archaeologists, as well as students and anyone interested in researching a surname origin, its history and evolution.

During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every update during this process is very time consuming. To improve efficiency, it is necessary to circumvent the computer-aided design modeling stage when possible and directly modify the meshes to save valuable time. The purpose of this paper is to develop a method for mesh modifications.

In contrast to existing studies, which focus on one or a class of modifications, this paper comprehensively studies mesh union, mesh gluing, mesh cutting and mesh partitioning. To improve the efficiency of the method, the paper presents a fast and effective surface mesh remeshing algorithm based on a ball-packing method and controls the remeshing regions with a size field.

Examples and results show that the proposed mesh modification method is efficient and effective. The proposed method can be also applied to meshes with different material properties, which is very different with previous work that is only suitable for the meshes with same material property.

This paper proposes an efficient and comprehensive tetrahedral mesh modification method, through which engineers can directly modify meshes instead of models and save time.