Influencing Factors Study of the Contemporary Spatial Expansion of Wuhan

2013 ◽  
Vol 357-360 ◽  
pp. 1911-1917
Author(s):  
Xia Li
Keyword(s):  
Data Analysis ◽  
Urban Space ◽  
Industrial Structure ◽  
Academic Research ◽  
Influence Factors ◽  
Urban Land Use ◽  
Transitional Period ◽  
Impact Factors ◽  
Systematic Research ◽  
Spatial Expansion

The rapid urban development of Chinas city during the transitional period has received extensive academic research and policy attention. This study inquired into the process, features and impact factors of spatial expansion in Wuhan during the transitional period. This study conducted a systematic research of the transitional urban space and using data analysis to explore the spatial logic and inherent laws underlying the spatial expansion of Wuhan. Based on data analysis via SPSS, three primary components closely related to urban land use change are identified. Corresponding influence factors under the spatial expansion are explored. Economic development, urbanization level, industrial structure, the foreign investment and other indicators drive the spatial expansion of Wuhan, and it is urgent to optimize the current space framework of the downtown areas for the creation of a sustainable and effective urban space form. This study also indicates the new trends of spatial expansion and relevant recommendations for the future development of Wuhan.

The Research of the Power Mechanism in the Coastal City Spatial Expansion in Period of Rapid Urbanization - Take Qingdao as an Example

2012 ◽  
Vol 253-255 ◽  
pp. 157-161
Author(s):  
Hong En Zhang ◽  
Xu Chong ◽  
Nie Tong
Keyword(s):  
Urban Space ◽  
Industrial Structure ◽  
Land Policy ◽  
Spatial Expansion ◽  
Rapid Urbanization ◽  
Coastal City ◽  
Dynamic Factors ◽  
City Space ◽  
Internal Reason ◽  
The City

Since reforming and opening-up policy, the internal reason of fast urbanization caused the restructuring of the city space. But the affects of unique marine resource in coastal city in the urban spatial expansion process can not be neglected. From the perspective of dynamic factors take Qingdao as an example, in this essay, the research would be done to discuss about the coastal city's influence on the expansion of urban space in port economy , the industrial structure, land policy, living factors and other aspects.

scholarly journals Application of the Cosine Gray Model Based on System Cloud in the Forecast of Higher Education Scale

2015 ◽  
Vol 10 (8) ◽  
pp. 16
Author(s):  
Chao Ge ◽  
Cun Li
Keyword(s):  
Higher Education ◽  
Industrial Structure ◽  
Influence Factors ◽  
Impact Factors ◽  
Forecasting Model ◽  
Education Development ◽  
Teaching Resources ◽  
Level Of Economic Development ◽  
The Government ◽  
Higher Education In China

The scale of higher education is an essential link in the process of the formulation of education planning and reasonable allocation of teaching resources. At the same time, it also provides the required basis and support for the government to formulate educational planning and policy. The scale of higher education development is influenced not only by the level of economic development and industrial structure, but also by the total population and the living standards of residents. We take these elements as the influence factors, which contain noise information. Because the scale of higher education and its impact factors have complex nonlinear relationship, the traditional forecasting method cannot describe their changing trends, which leads to the low accuracy of prediction. In order to solve the above problems, this paper bases on the traditional GM (1,1) model to judge the number of students in the future, and uses the weakening buffer operator to amend the historical data. Secondly, this paper analyzes the structure of the system cloud gray forecasting model, and demonstrates its integral generation principle. We propose a new method for the cosine gray forecasting model which is based on the system cloud SCOS-GM (1, 1), and prove the effectiveness of SCOS-GM (1, 1) model by the residual test. Finally, the SCOS-GM (1, 1) model is utilized to predict the scale of higher education in China during the period of 2012-2014. The results show that the scale of higher education will demonstrate a gradual upward trend in the next few years.

Industrial Structure and Party Competition in the New Deal: A Reply to Webber

1991 ◽  
Vol 34 (4) ◽  
pp. 493-526 ◽  
Author(s):  
Thomas Ferguson
Keyword(s):  
Data Analysis ◽  
Political Parties ◽  
New Deal ◽  
Industrial Structure ◽  
Statistical Design ◽  
Party Competition ◽  
Investment Theory ◽  
New Material ◽  
Capital Intensive ◽  
The New Deal

This paper is a response to Webber's (1991) critique of Thomas Ferguson's (1983, 1984, 1986) essays on the New Deal and his “investment theory” of political parties. It argues that Webber's evidence is invalid and that his statistical design is conceptually flawed. The sample is defective: it includes many people it should not and it excludes others who should have been reckoned in, notably many Texas oilmen. His procedure for ascertaining corporate partisanship is inadequate, since, among other problems, it excludes large payments made to the 1936 Democratic campaign by firms such as Standard Oil of New Jersey and General Electric. The campaign finance data he relies upon are also far less complete than he implies. An entirely new data analysis is presented, incorporating not only Webber's data, but much new material from archives. The results confirm Ferguson's central thesis about the 1936 election: contributions to the Democrats in 1936 do indeed come from firms that are more internationally-oriented and capital-intensive than those contributing to the Republicans.

Describing Ship-Design

2013 ◽  
Author(s):  
Ties van Bruinessen ◽  
Hans Hopman ◽  
Frido Smulders
Keyword(s):  
Industrial Structure ◽  
Complex Structure ◽  
Academic Research ◽  
Design Strategy ◽  
Ship Design ◽  
Design Strategies ◽  
Complex Interactions ◽  
Blank Sheet ◽  
Offshore Industry ◽  
Engineering Practices

The majority of European ship-design industry concentrates on the development of complex, one-off ‘specials’ for the offshore industry, like dredgers, drill ships, pipe-laying ships, et cetera. This industry is complex, not just in terms of the industrial structure but also in the terms of the object. To control the complexity the industry uses large and expansive knowledge basis that support the design, engineering and manufacturing activities. Within academic research the focus is close to practice and dominantly aims at developing knowledge and tools that supports engineering practices. As these strategies are aimed at controlling the complexity, they leave very little room for more innovative developments. On the other side of the spectrum there is a ship-design practice that does allow radical ship design: design and engineering from a blank sheet of paper. Not surprising that these projects are laborious and expensive. The space in between these two design strategies seems unaddressed in literature. The literature on the design of complex structures appears to be scarce, even though this is an area where European ship-design industry is heavily involved. The research this paper reports on aims to develop a design strategy for complex ships in between incremental and radical innovation. We interviewed stakeholders from ship industry, looked into the design literature to describe the present situation and finally performed case-studies in other fields of application for inspiration. Based on these studies we illustrate an alternative design strategy that leaves more space for innovation without the requirement to start from scratch. The approach focuses on the complex interactions between the different levels of decomposition in a complex structure such as a ship.

scholarly journals Archiving South African digital research data: How ready are we?

2016 ◽  
Vol Volume 112 (Number 7/8) ◽  
Author(s):  
Margaret M. Koopman ◽  
Karin de Jager ◽  
◽  
Keyword(s):  
Data Management ◽  
South African ◽  
Academic Research ◽  
Research Data ◽  
Digital Data ◽  
Systematic Research ◽  
Data Archiving ◽  
Research Data Management ◽  
The University ◽  
Digital Research

Abstract Digital data archiving and research data management have become increasingly important for institutions in South Africa, particularly after the announcement by the National Research Foundation, one of the principal South African academic research funders, recommending these actions for the research that they fund. A case study undertaken during the latter half of 2014, among the biological sciences researchers at a South African university, explored the state of data management and archiving at this institution and the readiness of researchers to engage with sharing their digital research data through repositories. It was found that while some researchers were already engaged with digital data archiving in repositories, neither researchers nor the university had implemented systematic research data management.

scholarly journals How to Maintain a Sustainable Environment? A Spatial Evolution of Urban Atmospheric Pollution and Impact Factors in China

2019 ◽  
Vol 11 (16) ◽  
pp. 4376
Author(s):  
Mingze Li ◽  
Yuan Huang ◽  
Mingdan Han
Keyword(s):  
Industrial Structure ◽  
Negative Relationship ◽  
Urban Pollution ◽  
Atmospheric Pollutants ◽  
Impact Factors ◽  
Spatial Evolution ◽  
Spatial Error ◽  
Spatial Lag Model ◽  
Spatial Panel Data ◽  
Per Capita

Urban pollution has significantly contributed to the spread of diseases and global warming. The analysis of spatial distribution characteristics of atmospheric pollutants is crucial for making sustainable industrial policy, and environmentally friendly urban planning. In this paper, GeoDa software is used to analyze how sulfur dioxide (SO2), nitrogen oxides (NOx), and smoke dust (DUS) are spatially distributed in various provinces of China. Then, global spatial correlation test and cluster analysis are carried out to obtain the spatial evolution characteristics of three pollutants. Afterward, the spatial panel data model is applied to explore the factors that affect the spatial evolution of SO2, NOx and smoke dust (DUS) nationwide. MATLAB is used to estimate the Spatial Lag Model (SLM) and the Spatial Error Model (SEM) of the three pollutants, respectively. According to our analysis, SEM is more applicable for SO2 and NOx, whereas SLM is optimal for smoke dust (DUS). The results show that foreign direct investment (FDI), industrial structure, and urbanization aggravate environmental pollution, while per capita gross domestic products (per capita GDP) has a negative relationship with the cluster of pollutants. The study concludes by informing public policy makers on environment friendly policies for a more sustainable development.

scholarly journals Regional Patch Detection of Road Traffic Network

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Xia Zhu ◽  
Weidong Song ◽  
Lin Gao
Keyword(s):  
Complex Network ◽  
Road Traffic ◽  
Geographic Distance ◽  
Influence Factors ◽  
Impact Factors ◽  
Traffic Network ◽  
The Road ◽  
Key Points ◽  
Path Distance ◽  
Shortest Path Distance

Road traffic network (RTN) structure plays an important role in the field of complex network analysis. In this paper, we propose a regional patch detection method from RTN via community detection of complex network. Firstly, the refined Adapted PageRank algorithm, which combines with the influence factors of the location property weight, the geographic distance weight and the road level weight, is used to calculate the candidate ranking results of key nodes in the RTN. Secondly, the ranking result and the shortest path distance as two significant impact factors are used to select the key points of the RTN, and then the Adapted K-Means algorithm is applied to regional patch detection of the RTN. Finally, based on the experimental data of Zhangwu road traffic network, the analysis results are as follows: Zhangwu is divided into 9 functional structures with key node locations as the core. Regional patch structure is divided according to key points, and the RTN is actually divided into nine small functional communities. Nine functional regional patches constitute a new network structure, maintaining connectivity between the regional patches can improve the overall efficiency of the RTN.

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