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The aim of this paper is to develop a new method to predict the potential shrinkage of plain‐knitted fabric.

The presented method is based on deformable curve. The delivered plain‐knitted fabric is represented as a deformable parametric curve, and the relaxed fabric can be reached by minimizing the energy of the curve. Compared to the delivered‐knitted fabric, the length and width shrinkage percentages can be calculated accordingly.

The new method is more convenient than the traditional trial and error method, and need less‐input parameters than the STARFISH technique. Experimental results show that this method is feasible.

This paper presents a new method for shrinkage prediction of plain‐knitted fabric based on deformable curve and energy minimum. The work can be linked with shrinkage control in textile industry.

In the event of a DC short-circuit fault in a flexible DC power grid, the high peak value of the fault current puts forward more stringent requirements on the DC circuit breaker. The existing fault current cutoff mainly focuses on changing the topology structure. To suppress the development of fault current and reduce the investment cost of the DC grid, this paper aims to propose a dual-loop active current-limiting control based on energy difference.

Firstly, the equivalent circuit at fault is established, and the parameters related to the fault current are analyzed. Then, the relationship between the output voltage change of the bridge arm and the difference between the AC and DC energy is deduced. Finally, the experimental results are discussed on the real-time simulation platform Opal-RT.

The proposed current-limiting measures can greatly reduce the fault current, reduce the breaking current of the circuit breaker and increase the capacitor voltage during the fault period, which is beneficial to the stability of the AC system. It is verified that the proposed method is also applicable to a certain high-resistance fault.

This paper applies the method of AC fault to DC fault and deduces the relationship between energy difference and voltage variation corresponding to different step lengths based on digital simulation. In addition, two variables are used as control structure parameters to reduce the probability of system misoperation.

This study focuses on the Critical Success Factors (CSF) for developing sustainable entrepreneurship in the Pakistani telecommunication industry. Despite the efforts made by governments and stakeholders to stimulate sustainable entrepreneurship initiatives, contributions in the telecommunications sector are lacking. Therefore, this study has the major objective of identifying a transformation path for these firms. This is done by providing a theoretical framework for sustainable entrepreneurship in the telecommunications industry, focusing on managerial and operational practices that should be modified according to a set of CSFs identified by experts in Pakistani firms.

This article proposes a novel Multiple Attribute Decision Making (MADM) approach based on Grey Systems Theory (GST) and Best-Worst Method (BWM) while unveiling endogenous relationships among current managerial/operational practices and the CSFs for sustainable entrepreneurship in the telecommunications industry.

CSFs for achieving sustainable entrepreneurship in the Pakistani telecommunications industry were found to rely on a tripod, based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing digital illiteracy, targeting poor communities, helping the young in structuring start-ups.

This article contributes to the MADM research stream by proposing a novel use of the BWM technique based on GST to promote sustainable entrepreneurship CSFs in Pakistani telecommunications firms.

Outside the US and Europe, to establish a good government requires more than Western-style democracy. Adopting universal suffrage fully from the Western model is no longer a panacea to reach the ultimate goal of good governance in the East, i.e., to keep promoting socio-economic renovation can be noted as a prerequisite to have further meaningful political advancement in an Asian polity. The purpose of this paper is to explain how to establish a good but authoritarian government in the East.

Given the good of comparative historical analysis, Lee Kuan Yew in Singapore and Deng Xiaoping in China are selected as both cases for “method of agreement.” Further including “argument based on the contrary” to form a context for macro-historical analysis, this paper outlines two characteristics of the duo’s authoritarian leadership, namely, Ideologies and Policy-making; and Political Modernization, and hence provides a more balanced reevaluation of their governance.

Apart from noting how these two Asian giants more or less contributed to their good but authoritarian governments for long in the twentieth century, such a word of authoritarianism to the duo was quite positive to help legitimize their governance, which was far different from many negative views of the Western world.

As theories put forward by Western academics could not entirely justify modernization among Asian societies in the twentieth century, this paper attempts to answer one question: Does the meaning of authoritarianism remain unchanged in the discourse of the East and the West?

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.