Xiumei Cai, Xi Yang and Chengmao Wu
Multi-view fuzzy clustering algorithms are not widely used in image segmentation, and many of these algorithms are lacking in robustness. The purpose of this paper is to…
Abstract
Purpose
Multi-view fuzzy clustering algorithms are not widely used in image segmentation, and many of these algorithms are lacking in robustness. The purpose of this paper is to investigate a new algorithm that can segment the image better and retain as much detailed information about the image as possible when segmenting noisy images.
Design/methodology/approach
The authors present a novel multi-view fuzzy c-means (FCM) clustering algorithm that includes an automatic view-weight learning mechanism. Firstly, this algorithm introduces a view-weight factor that can automatically adjust the weight of different views, thereby allowing each view to obtain the best possible weight. Secondly, the algorithm incorporates a weighted fuzzy factor, which serves to obtain local spatial information and local grayscale information to preserve image details as much as possible. Finally, in order to weaken the effects of noise and outliers in image segmentation, this algorithm employs the kernel distance measure instead of the Euclidean distance.
Findings
The authors added different kinds of noise to images and conducted a large number of experimental tests. The results show that the proposed algorithm performs better and is more accurate than previous multi-view fuzzy clustering algorithms in solving the problem of noisy image segmentation.
Originality/value
Most of the existing multi-view clustering algorithms are for multi-view datasets, and the multi-view fuzzy clustering algorithms are unable to eliminate noise points and outliers when dealing with noisy images. The algorithm proposed in this paper has stronger noise immunity and can better preserve the details of the original image.
Details
Keywords
Cai Li, Zhu Xiumei, Cui Qiguo and Zhao Di
This paper aims to build a theory model to examine the influencing mechanism of entrepreneurial environment on new firm performance based on network view and resource‐based view…
Abstract
Purpose
This paper aims to build a theory model to examine the influencing mechanism of entrepreneurial environment on new firm performance based on network view and resource‐based view, and then carry out empirical research.
Design/methodology/approach
Data were obtained from 112 new firms, through the use of questionnaires, in Changchun city, China.
Findings
Evidence indicates that the entrepreneurial environment has an impact on new firm performance through entrepreneurial network and resource acquisition. The results show that eight out of ten hypotheses are supported.
Practical implications
In a hostile, dynamic and complex environment, the new firm should enhance its entrepreneurial network to ensure resource acquisition and then promote performance.
Originality/value
The paper shows definitely the significance of entrepreneurial network as a bridge between external environment and resource acquisition and new firm performance. Entrepreneurial network and resource acquisition are identified as important intermediary variables, and resource combination ability as a moderating variable. This paper examines the influence of external environment on new firm performance. The research has some theoretical and managerial implications for new firms' survival and obtaining growth in highly uncertain and turbulent environments.
Details
Keywords
Xiumei Hao, Mingwei Li and Yuting Chen
This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical…
Abstract
Purpose
This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical industry as research objects and proposes a TOPSIS grey relational projection group decision method with mixed multiattributes, which is used for the ranking of the seven industries with overcapacity and provided relevant departments with a basis for decision-making.
Design/methodology/approach
First, an evaluation index system from four aspects is established. Secondly, the attributes of linguistic information are converted into two-dimensional interval numbers and triangular fuzzy numbers, and an evaluation matrix is constructed and normalized. This paper uses the AHP method to determine the subjective weights and uses the coefficient of variation method to determine the objective weights. Moreover, this paper sets up the optimization model with the largest comprehensive evaluation value to determine the combined weights. Finally, the TOPSIS grey relational projection method is proposed to calculate the closeness of grey relational projections and to rank them.
Findings
This paper analyzes the problem of overcapacity in seven industries with the TOPSIS grey relational projection method. The results show that the four industries of automobile manufacturing, textile, coal and petrochemical are all in serious overcapacity levels, while the three industries of steel, nonferrous metals and electric power are relatively in weak overcapacity level in the three years of 2016–2018. TOPSIS grey relational projection method ranks the overcapacity degree of the seven major overcapacity industries, making the relative overcapacity degree of each industry more clear and providing a reference for the government to formulate targeted policies and measures for each industry.
Practical implications
By using TOPSIS grey relational projection method to evaluate the overcapacity of the seven major overcapacity industries, on the one hand, it makes the relative overcapacity degree of each industry more clear, on the other hand, it can provides the basis for the government and decision-making departments. This helps them promote better the healthy and orderly economic development of the seven major industries and avoid resource waste caused by overcapacity.
Originality/value
This article solves the single evaluation method caused by the limited indicators in the past, combines TOPSIS and the grey relational projection method and applies it to the overcapacity evaluation of the industry, not only applies it to the evaluation of overcapacity for the first time but also involves novel problems and methods, which expands the scope of application of the model.
Details
Keywords
Abstract
Purpose
Flow force is one of the crucial factors affecting the performance of conical throttle valves. The purpose of this paper is to determine the relationship between the flow force and operating parameters of the conical throttle valve.
Design/methodology/approach
The flow force of the throttle valve can be obtained by the difference between the axial force and static pressure on the valve spool. In this paper, the internal fluid is divided into two regions and the axial force and static pressure are obtained, respectively. In addition, a two-dimensional axisymmetric simulation model and experimental test are carried out to validate the results of the flow force.
Findings
It can be seen that the theoretical, simulation and experimental results exhibit high agreement with each other and the error between them decreases with the increase in the size of the opening. The curves of pressure distribution reveal that the pressure on the spool first decreases then increases when it reaches the minimum pressure at the orifice. Additionally, the minimum pressure decreases with the increase of opening and pressure difference. The results also indicate that the increase in the size of the opening and inlet pressure has a positive effect on the flow force. However, the increase in outlet pressure has a negative effect on the flow force.
Originality/value
In this paper, the flow force calculation model of conical throttle valve is established and the influence of operating parameters on the flow force of conical throttle valve is studied.
Details
Keywords
Li Gao, Jinnan Song, Jiajuan Liang and Jianxiao Guo
This paper aims to explore the influence of founder shareholders’ resources on the allocation of control rights from the perspective of incomplete contract theory and…
Abstract
Purpose
This paper aims to explore the influence of founder shareholders’ resources on the allocation of control rights from the perspective of incomplete contract theory and resource-based theory.
Design/methodology/approach
This paper analyzes newspaper materials with NVivo11on a case of battle for corporate control in Chinese top-listed company-Vanke Group.
Findings
The research shows that human capital is the key resource and the holding proportion of financial resources directly affects the allocation of control rights. At the same time, social capital is unstable and easily broken. At last, institutional environment also affects the degree between the relationship of founder shareholders’ resources and the allocation of control rights. The influence of founder-shareholder resources on the allocation of control rights follows the path of “crisis – founder-shareholder’s resources – founder’s ability - allocation of control rights.”
Research limitations/implications
This study only selects the financial capital, human capital and social capital of Shi Wang, the founder of Vanke, as the analysis object. The study can expand the types of founder shareholder resources to verify and enrich the conclusions.
Originality/value
The current theoretical research in the literature focuses on the necessity of equity and shareholder’s resources versus the control rights. Some key factors and mechanism on the relationship have not been fully clarified. The results of this paper not only extend the combination research of social network and corporate governance, but also provide enterprise founders with references for making reasonable decisions during control battle.