Daoming Wang, Youfu Hou, Zuzhi Tian and Qingrui Meng
This study aims to reveal the temperature rise characteristic of magnetorheological (MR) fluid in a multi-disc MR clutch under slip condition, including the temperature…
Abstract
Purpose
This study aims to reveal the temperature rise characteristic of magnetorheological (MR) fluid in a multi-disc MR clutch under slip condition, including the temperature distribution regularity and the impact factors.
Design/methodology/approach
Three-dimensional transient heat conduction equation for the MR fluid in the working gap was derived based on the heat transfer theory. Then, numerical simulation was conducted to analyze the temperature field of MR fluid. Furthermore, an experimental study was performed to explore the temperature distribution of the MR fluid in radial and circumferential directions, as well as the effects of disc groove, slip power and gap size on temperature rise characteristic of the MR fluid.
Findings
The results show that temperature appears to be largest in the center of the working gap and the temperature difference increases with the slip time. However, the temperature field in a circumferential direction is basically the same, but it presents slightly lower in the groove area. The temperature of the MR fluid increases linearly with the slip time and the rise rate increases with the slip power. Moreover, the temperature rise value decreases with the increase of gap size.
Originality/value
In this paper, the temperature gradients, both in radial and circumferential directions, are experimentally measured going beyond the estimation by computer simulations. In addition, the factors that influence the temperature rise characteristic of MR fluid were fully analyzed. The results could provide a reliable basis for the development of cooling technology for high-power MR devices.
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With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the…
Abstract
Purpose
With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.
Design/methodology/approach
This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.
Findings
China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.
Originality/value
This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.
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Hadi Sadoghi Yazdi, Reza Pourreza and Mehri Sadoghi Yazdi
The purpose of this paper is to present a new method for solving parametric programming problems; a new scheme of constraints fuzzification. In the proposed approach, constraints…
Abstract
Purpose
The purpose of this paper is to present a new method for solving parametric programming problems; a new scheme of constraints fuzzification. In the proposed approach, constraints are learned based on deductive learning.
Design/methodology/approach
Adaptive neural‐fuzzy inference system (ANFIS) is used for constraint learning by generating input and output membership functions and suitable fuzzy rules.
Findings
The experimental results show the ability of the proposed approach to model the set of constraints and solve parametric programming. Some notes in the proposed method are clustering of similar constraints, constraints generalization and converting crisp set of constraints to a trained system with fuzzy output. Finally, this idea for modeling of constraint in the support vector machine (SVM) classifier is used and shows that this approach can obtain a soft margin in the SVM.
Originality/value
Properties of the new scheme such as global view of constraints, constraints generalization, clustering of similar constraints, creation of real fuzzy constraints, study of constraint strength and increasing the degree of importance to constraints are different aspects of the proposed method.
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Yongrong Xin, Xiuping Zuo and Qingping Huang
The implementation of the national education and lifelong education should break through the traditional learning mode in the digital era. A seamless learning environment is the…
Abstract
Purpose
The implementation of the national education and lifelong education should break through the traditional learning mode in the digital era. A seamless learning environment is the intelligent form of deep integration of digital learning environment and physical learning environment. The development and construction of seamless learning space and platform is a new trend of international mobile learning research and practice. So, the purpose of this paper is to build a seamless learning platform of the open education system by expanding and improving the connotation and extension of seamless learning, based on the theories of mobile learning, ubiquitous learning and open education, combining with the characteristics of the big data era.
Design/methodology/approach
A seamless learning platform model will be constructed through constructing five modules including resource integration module, requirement module, management module, teacher integration module, and carrier module, using interdisciplinary research methods (combined with economics), functional analysis, model methods and exploratory research methods. Finally, this paper attempts to realize the application of a seamless learning platform in open education through the strategic path of public-private partnership (PPP).
Findings
Seamless learning platform model given by this paper can effectively eliminate the problem of information asymmetry between learner-demander and educational manager through the effective management of carrier fusion module. Furthermore, it can effectively integrate the learning resources and teachers of the open education system and social individual education system, and provide high-quality shared learning resources and diverse stratification teachers to students and social workers through PPP project cooperation ways.
Originality/value
There are many papers on the study of open education and resource construction. However, few papers have studied how to effectively integrate and optimize various existing scattered online resources, including various system courses, teachers and platform systems. The paper provides an effective way to solve the above sub-problems and the realization path/model reference for the effective and accurate promotion of lifelong sustainable learning for all.
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The purpose of this paper is to examine the moderating effect of networking ties on the relationship between customer orientation and firm performance.
Abstract
Purpose
The purpose of this paper is to examine the moderating effect of networking ties on the relationship between customer orientation and firm performance.
Design/methodology/approach
This study adopted a survey approach to collect data from 251 respondents in the Mangaung Metropolitan Municipality in the Free State province, South Africa. Scales for data collection were operationalised from prior studies. A hierarchical regression analysis was used to examine the moderating effect of networking ties on the relationship between customer orientation and firm performance.
Findings
The results showed that customer orientation had a significant positive association with firm performance, thus supporting the existing calls for examining the unique contributions of customer orientation to firm performance. Furthermore, this study hypothesised that business, political, and social network ties positively moderated this association. However, the results showed that only business and social network ties had a positive and significant moderating effect, with the influence of customer orientation on firm performance being more pronounced for firms with high as opposed to low business and social network ties. Nevertheless, all the three types of network ties showed a positive and significant direct relationship with firm performance, thus supporting the consolidated literature on the positive impact of network ties on firm performance.
Practical implications
The practical implications are twofold. First, it encourages business owners to develop a customer-oriented approach as a key strategic objective in their pursuit for optimal business performance. Second, business owners and managers should increasingly exploit their business and social network ties to accumulate vital resources for effectively exploiting their customer-oriented capabilities as a means to improve their performance.
Originality/value
Even though customer orientation is a valuable internal strategic capability, its benefit on firm performance might be limited in small and medium enterprises (SMEs) when the businesses are unable to respond quickly to customer needs. This is more common when the SME is faced with resource limitations required for exploiting the new market opportunities. However, this study showed that SMEs can mitigate this issue by depending on their business and social network ties for valuable resources to effectively exploit opportunities that emerge from identified customer needs.
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Ra'ed Masa'deh, Bader Yousef Obeidat and Ali Tarhini
Knowledge sharing adoption has been considered as a significant practice for organizations. However, there is a modest empirical confirmation to indicate how these organizations…
Abstract
Purpose
Knowledge sharing adoption has been considered as a significant practice for organizations. However, there is a modest empirical confirmation to indicate how these organizations value the richness of their knowledge capabilities. The purpose of this paper is to investigate both transformational and transactional leadership styles that influence employees’ knowledge sharing practices, and the impact of the latter on job performance, and then on firm performance.
Design/methodology/approach
Data collected from 179 employees at the higher council of youth in Jordan were empirically tested using structural equation modelling.
Findings
The findings revealed that both transformational and transactional leadership styles have significant impact on job performance, and the latter on firm performance. Also, it was found that transactional leadership impacted knowledge sharing, whereas transformational leadership did not.
Originality/value
This research proposes a new approach to understand knowledge sharing adoption, and outlines some theoretical and managerial implications of the findings.
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A. Garg, K. Tai and M.M. Savalani
The empirical modelling of major rapid prototyping (RP) processes such as fused deposition modelling (FDM), selective laser sintering (SLS) and stereolithography (SL) has…
Abstract
Purpose
The empirical modelling of major rapid prototyping (RP) processes such as fused deposition modelling (FDM), selective laser sintering (SLS) and stereolithography (SL) has attracted the attention of researchers in view of their contribution to the overall cost of the product. Empirical modelling techniques such as artificial neural network (ANN) and regression analysis have been paid considerable attention. In this paper, a powerful modelling technique using genetic programming (GP) for modelling the FDM process is introduced and the issues related to the empirical modelling of RP processes are discussed. The present work aims to investigate the performance of various potential empirical modelling techniques so that the choice of an appropriate modelling technique for a given RP process can be made. The paper aims to discuss these issues.
Design/methodology/approach
Apart from the study of applications of empirical modelling techniques on RP processes, a multigene GP is applied to predict the compressive strength of a FDM part based on five given input process parameters. The parameter setting for GP is determined using trial and experimental runs. The performance of the GP model is compared to those of neural networks and regression analysis.
Findings
The GP approach provides a model in the form of a mathematical equation reflecting the relationship between the compressive strength and five given input parameters. The performance of ANN is found to be better than those of GP and regression, showing the effectiveness of ANN in predicting the performance characteristics of the FDM part. The GP is able to identify the significant input parameters that comply with those of an earlier study. The distinct advantages of GP as compared to ANN and regression are highlighted. Several vital issues related to the empirical modelling of RP processes are also highlighted in the end.
Originality/value
For the first time, a review of the application of empirical modelling techniques on RP processes is undertaken and a new GP method for modelling the FDM process is introduced. The performance of potential empirical modelling techniques for modelling RP processes is evaluated. This is an important step in modernising the era of empirical modelling of RP processes.
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Guotai Chi and Bin Meng
The purpose of this paper is to propose a debt rating index system for small industrial enterprises that significantly distinguishes the default state. This debt rating system is…
Abstract
Purpose
The purpose of this paper is to propose a debt rating index system for small industrial enterprises that significantly distinguishes the default state. This debt rating system is constructed using the F-test and correlation analysis method, with the small industrial enterprise loans of a Chinese commercial bank as the data sample. This study establishes the weighting principle for the debt scoring model: “the more significant the default state, the larger is the weight.” The debt rating system for small industrial enterprises is constructed based on the standard “the higher the debt rating, the lower is the loss given default.”
Design/methodology/approach
In this study, the authors selected indexes that pass the homogeneity of variance test based on the principle that a greater deviation of the default sample’s mean from the whole sample’s mean leads to greater significance in distinguishing the default samples from the non-default samples. The authors removed correlated indexes based on the results of the correlation analysis and constructed a debt rating index system for small industrial enterprises that included 23 indexes.
Findings
Among the 23 indexes, the weights of 12 quantitative indexes add up to 0.547, while the weights of the remaining 11 qualitative indexes add up to 0.453. That is, in the debt rating of the small industry enterprises, the financial indexes are not capable of reflecting all the debt situations, and the qualitative indexes play a more important role in debt rating. The weights of indexes “X17 Outstanding loans to all assets ratio” and “X59 Date of the enterprise establishment” are 0.146 and 0.133, respectively; both these are greater than 0.1, and the indexes are ranked first and second, respectively. The weights of indexes “X6 EBIT-to- current liabilities ratio,” “X13 Ratio of capital to fixed” and “X78 Legal dispute number” are between 0.07 and 0.09, these indexes are ranked third to fifth. The weights of indexes “X3 Quick ratio” and “X50 Per capital year-end savings balance of Urban and rural residents” are both 0.013, and these are the lowest ranked indexes.
Originality/value
The data of index i are divided into two categories: default and non-default. A greater deviation in the mean of the default sample from that of the whole sample leads to greater deviation from the non-default sample’s mean as well; thus, the index can easily distinguish the default and the non-default samples. Following this line of thought, the authors select indexes that pass the F-test for the debt rating system that identifies whether or not the sample is default. This avoids the disadvantages of the existing research in which the standard for selecting the index has nothing to do with the default state; further, this presents a new way of debt rating. When the correlation coefficient of two indexes is greater than 0.8, the index with the smaller F-value is removed because of its weaker prediction capacity. This avoids the mistake of eliminating an index that has strong ability to distinguish default and non-default samples. The greater the deviation of the default sample’s mean from the whole sample’s mean, the greater is the capability of the index to distinguish the default state. According to this rule, the authors assign a larger weight to the index that exhibits the ability to identify the default state. This is different from the existing index system, which does not take into account the ability to identify the default state.