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Recently, a new class of fatigue crack growth models based on elastoplastic stress‐strain histories at the crack tip region and strain‐life fatigue damage models have been proposed. The fatigue crack propagation is understood as a process of continuous crack initializations, over elementary material blocks, which may be governed by strain‐life data of the plain material. The residual stresses developed at the crack tip play a central role in these models, since they are used to assess the actual crack driving force, taking into account mean stresses and loading sequential effects. The UniGrow model fits this particular class of fatigue crack propagation models. The purpose of this paper is to propose an extension of the UniGrow model to derive probabilistic fatigue crack propagation data, in particular the derivation of the P–da/dN–ΔK–R fields.

An existing deterministic fatigue crack propagation model, based on local strain‐life data is first assessed. In particular, an alternative methodology for residual stress computation is proposed, based on elastoplastic finite element analysis, in order to overcome inconsistencies found in the analytical approximate approaches often used in literature. Then, using probabilistic strain‐life fields, a probabilistic output for the fatigue crack propagation growth rates is generated. A new probabilistic fatigue field is also proposed to take mean stress effects into account, using the Smith‐Watson‐Topper (SWT) damage parameter. The proposed models are assessed using experimental data available for two materials representative from old Portuguese bridges.

A new method to generate probabilistic fatigue crack propagation rates (P–da/dN–ΔK–R fields) is proposed and verified using puddle iron from old Portuguese bridges, usually characterized by significant scatter in fatigue properties. Also, a new probabilistic fatigue field for plain material is proposed to deal with mean stress effects.

A relation between the P–ε–N and the P–da/dN–ΔK–R fields is firstly proposed in this research. Furthermore, a new P–SWT–N field is proposed to deal with mean stress effects.

The purpose of this paper is to develop a conceptual framework which combines the strength of weak ties (SWT) concept with an innovative taxonomy for mitigating principal-agent (P-A) conflicts. The taxonomy highlights the mechanisms through which African women can overcome the obstacles faced when setting up businesses.

The paper discusses the role of “weak ties” networks in entrepreneurial activities and integrates the concept with the key parameters of the P-A paradigm. The aim is to develop a taxonomy (or scorecard) for mitigating the challenges faced by women entrepreneurs in Africa from a P-A perspective. Six P-A parameters are analysed, namely, attitudes towards risk; behaviour-based vs targets-based contracts; asymmetric information; risk-sharing; transaction costs; and verification and monitoring costs.

With the aid of the taxonomy developed in the paper, the authors analyse the channels through which “SWT” networks may impact in mitigating the problems arising from the P-A paradigm. Some implications for women entrepreneurs in Africa are highlighted.

The current conceptual study suggests that the “SWT” concept can be used by African women entrepreneurs to mitigate P-A problems. The authors argue that the original P-A taxonomy developed in the paper fills a conceptual research gap in the existing literature. Embedding the SWT concept within a P-A framework will facilitate further research not only to understand African women entrepreneurs’ attitudes (and responses) towards risk and uncertainty, but this will also facilitate greater understanding of the importance women attach to the role of incentives within their businesses.

The taxonomy presents new insights for understanding the most serious constraints that hinder women entrepreneurs in Africa. The taxonomy will be the basis for a follow-up empirical paper on selected African countries.

The originality of this study lies in the development of an innovative taxonomy which highlights the role of “SWT” social networks towards mitigating the P-A problem among African women entrepreneurs. The paper makes a significant contribution to the literature from a conceptual perspective.

This study aims to determine the reliability assessment based on the predicted fatigue life of leaf spring under random strain loading.

Random loading data were extracted from three various road conditions at 200 Hz using a strain gauge for a duration of 100 s. The fatigue life was predicted using strain-life approaches of Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models.

The leaf spring had the highest fatigue life of 1,544 cycle/block under highway data compared uphill (1,299 cycle/block) and downhill (1,008 cycle/block) data. Besides that, the statistical properties of kurtosis showed that uphill data were the highest at 3.81 resulted in the presence of high amplitude in the strain loading data. For fatigue life-based reliability assessment, the SWT model provided a narrower shape compared to the Coffin–Manson and Morrow models using the Gumbel distribution. The SWT model had the lowest mean cycle to failure of 1,250 cycle/block followed by Morrow model (1,317 cycle/block) and the Coffin–Manson model (1,429 cycle/block). The SWT model considers the mean stress effects by interpreting the strain energy density that will influence the reliability assessment.

The reliability assessment based on fatigue life prediction is conducted using the Gumbel distribution to investigate the behaviour of fatigue random loading, where most previous studies had concentrated on a Weibull distribution on random data.

Thus, this study proposes that the Gumbel distribution is suitable for analysing the reliability of random loading data in assessing with the fatigue life prediction of a heavy vehicle leaf spring.

This paper aims to provide an understanding of employee motivation from the Islamic perspective. The main objective of this paper is to understand Islamic motivation and to explore if Islamic spirituality, punishment and reward and justice motivate Muslim employees.

Qualitative research approach was used to understand and examine the views of the respondents. Semi-structured interviewing technique was adopted, and the respondents were asked to share their own thoughts and understanding for each question provided. A sample of 13 experienced academicians and practitioners from renowned private organizations and academic institutions from Malaysia and Pakistan were selected for the present study.

The study found that the conventional viewpoint of motivation varies from Islamic viewpoint in regard to motivation of employees. And significantly, Islamic spirituality, reward and punishment, and justice act more compellingly in improving employee’s motivation.

This paper clearly highlights that the Western viewpoint of employee motivation is different as compared to the Islamic perspective.

The purpose of this paper is to investigate customer‐centric corporate social responsibility (CSR) in Islamic banks of Bangladesh, Malaysia and the Arabian Gulf Region. The new framework is found from the incomplete link between managerial motivation and their actual involvement with CSR activities.

The study uses annual reports of 16 Islamic banks from three regions. Using content analysis method, the study produces an ethical identity index on eight dimensions. The average index scores are ranked to get a view of the importance given by Islamic banks to the path of social responsibility.

In this study, the customer‐centric CSR framework assumes that there are two layers of CSR involvement in Islamic banks. The upper layer assures the commitment towards Allah (SWT) by operating under Islamic Shari'ah. The bottom layer ensures the commitment towards customers, employees and society. The reports of Islamic banks show that the selected banks are too customer centric and efficiency driven. However, that efficiency is targeted at the cost of sacrificing Shari'ah norms. Their commitments to basic Islamic rules fall far behind the average.

The study uses content analysis of the annual report to identify CSR involvement of the Islamic banks. There are various issues related to CSR and corporate management that are not reported in annual reports. Moreover, disclosure norms and regulation also have an influence on reporting standards. Thus, this study is limited to what is found in the reports only.

The study contributes to the existing literature on customer‐centric CSR and customer‐centric marketing. There is evidence that the findings from this study are consistent with other studies. Islamic banks are becoming customer centric because of the competition from conventional banks. However, they must not forget the very essence of the establishment of these banks which is the spiritual freedom based upon sole submission to Allah (SWT).

Within developing countries, particularly in Africa, there is an emerging literature which highlights the unique obstacles faced by women entrepreneurs who start and develop their own businesses (De Vita, Mari, & Poggesi, 2014; Jamali, 2009; Minniti & Naude, 2010; Naude & Havenga, 2005; Nziku & Struthers, 2018). A key objective of this chapter is to critically appraise some of the conceptual approaches adopted in this literature. In so doing, the authors revisit a seminal paper first developed by Granovetter (1973) which suggested that female entrepreneurs, instead of being disadvantaged by the so-called ‘weak ties’ that bind their business networks, actually enjoy compensating benefits which Granovetter referred to as the strength of weak ties (SWT). Building on the conceptual work of Nziku and Struthers (2018) which developed an innovative taxonomy for analysing the SWT concept within a Principal-Agent (P-A) paradigm, the chapter will set out new insights which challenge some of the assumptions of the extant entrepreneurship literature. In particular, that women are inherently more risk averse in their business decision making than men. The theoretical context for this will be derived from a behavioural economics methodology first developed by Kahneman and Tversky (1979). They introduced the concept of loss aversion as a more realistic approach to attitudes towards risk on the part of entrepreneurs than risk aversion. The chapter contends that the loss aversion perspective may be more appropriate to the decision-making frame adopted by female entrepreneurs, especially in the context of Africa as well as in other developing regions of the world. The chapter will therefore suggest that such an approach can yield fresh insights on the topic of female entrepreneurship which the extant literature heretofore has not addressed, though this will have to be subsequently tested empirically.

A major key success factor regarding proficient Bayes threshold denoising refers to noise variance estimation. This paper focuses on assessing different noise variance estimations in three Bayes threshold models on two different characteristic brain lesions/tumor magnetic resonance imaging (MRIs).

Here, three Bayes threshold denoising models based on different noise variance estimations under the stationary wavelet transforms (SWT) domain are mainly assessed, compared to state-of-the-art non-local means (NLMs). Each of those three models, namely D1, GB and DR models, respectively, depends on the most detail wavelet subband at the first resolution level, on the entirely global detail subbands and on the detail subband in each direction/resolution. Explicit and implicit denoising performance are consecutively assessed by threshold denoising and segmentation identification results.

Implicit performance assessment points the first–second best accuracy, 0.9181 and 0.9048 Dice similarity coefficient (Dice), sequentially yielded by GB and DR; reliability is indicated by 45.66% Dice dropping of DR, compared against 53.38, 61.03 and 35.48% of D1 GB and NLMs, when increasing 0.2 to 0.9 noise level on brain lesions MRI. For brain tumor MRI under 0.2 noise level, it denotes the best accuracy of 0.9592 Dice, resulted by DR; however, 8.09% Dice dropping of DR, relative to 6.72%, 8.85 and 39.36% of D1, GB and NLMs is denoted. The lowest explicit and implicit denoising performances of NLMs are obviously pointed.

A future improvement of denoising performance possibly refers to creating a semi-supervised denoising conjunction model. Such model utilizes the denoised MRIs, resulted by DR and D1 thresholding model as uncorrupted image version along with the noisy MRIs, representing corrupted version ones during autoencoder training phase, to reconstruct the original clean image.

This paper should be of interest to readers in the areas of technologies of computing and information science, including data science and applications, computational health informatics, especially applied as a decision support tool for medical image processing.

In most cases, DR and D1 provide the first–second best implicit performances in terms of accuracy and reliability on both simulated, low-detail small-size region-of-interest (ROI) brain lesions and realistic, high-detail large-size ROI brain tumor MRIs.

The purpose of this paper is to employ the acoustic wave propagation method for leakage detection in pipes. The first objective is to use acoustic finite element analysis (AFEA) method to simulate acoustic wave propagation and acoustic wave reflectometry in an intact pipe and in pipes with leaks of various sizes. This is followed by the second objective which is to validate the effectiveness and the practicability of the acoustic wave method via experimental testing. The third objective involves the decomposition and de-noising of the measured acoustic waves using stationary wavelet transform (SWT). It is shown that this approach, which is used for the first time on leakage detection in pipes, can be used to identify, locate and estimate the size of a leakage defect in a pipe.

The research work was designed inline with best practices and acceptable standards. The research methodology focusses on five basic areas: literature review; experimental measurements; simulations; data analysis and writing-up of the study with clear-cut communication of the findings. The approach used was acoustic wave propagation-based method in conjunction with SWT for leakage detection in fluid-filled pipe.

First, the simulation of acoustic wave propagation and acoustic wave reflectometry in fluid-filled pipes with and without leakage have great potential in leakage detection in pipeline systems and can detect very small leaks of 1 mm diameter. Second, the measured noise-contaminated acoustic wave propagation in a fluid-filled pipe can be successfully de-noised using the SWT method in order to clearly identify and locate leakage as little as 5 mm diameter in a pipe. Third, AFEA of a fluid-filled pipe can be achieved with the simulation of only the fluid content of the pipe and without the inclusion of the pipe in the model. This eliminates contact interaction of the solid pipe walls and the fluid, and as a consequence reduces computational time and resources. Fourth, the relationship of the ratio of the leakage diameter to the ratio of the first and second secondary wave amplitudes caused by the leakage can be represented by a second-order polynomial function. Fifth, the identification of leakage in a pipe is intuitive from mere comparison of the acoustic waveforms of an intact pipe with that of a pipe with a leakage.

The research work is a novelty and was developed from the scratch. The AFEA of acoustic wave propagation and acoustic wave reflectometry in a static fluid-filled pipe, and the SWT method have been used for the first time to detect, locate and estimate the size of a leakage in a fluid-filled pipe.

The purpose of this paper is to analyse fatigue-life prediction based on a reliability assessment for coil springs of vehicle suspension systems using different road excitations under random loading.

In this study, a reliability assessment was conducted to predict the fatigue life of an automobile coil spring during different road data surfaces. Campus, urban and highway road surfaces were considered to capture fatigue load strain histories using a data acquisition system. Random loadings are applied on top of a coil spring where coil is fixed from down. Fatigue reliability was established as a system of correlated events during the service life to predict the probability of fatigue life using Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models.

Fatigue-life prediction based on a reliability assessment revealed that the Morrow model can predict a safe region of a life data point for the three road surfaces. Highway road data indicated the highest rate of reliability at 0.8 for approximately 1.69 × 10⁵ cycles for the SWT model.

Reliability assessment of the fatigue life of vehicle coil springs is vital for safe operation. The reliability analysis of a coil spring under random loading excitations can be used for fatigue-life prediction.

In practical engineering, oil filters often work under asymmetric cyclic loading. In order to improve the prediction accuracy of fatigue life of the oil filters under asymmetric cyclic loading, the effect of strain ratio and low cycle fatigue plastic deformation on fatigue life need to be considered. This paper aims to discuss the aforementioned objective.

First, strain-controlled fatigue tests with strain ratios of 0, 0.5 and −1 were carried out on the oil filter material 2A70-T6 aluminum alloy, and the test data were used to obtain strain fatigue life curves at three strain ratios. Then, based on the idea of the constant life curve method, the average value of the ratio of the strain amplitude corresponding to different strain ratios under the same partial life was defined as the strain ratio factor. Finally, the elastic-plastic factor was modified by the strain ratio factor, and a new fatigue life prediction model considering the effect of strain ratio was proposed.

The proposed model was validated, respectively, by fatigue test data of 2A70-T6 aluminum alloy, 2124-T851 aluminum alloy and oil filter and the results of the proposed model were compared with the Coffin–Manson equation, Morrow model and Smith–Watson–Topper (SWT) model, showing that the proposed model had higher applicability and accuracy.

In this work, a strain ratio factor is established based on the idea of the constant life curve method, and the strain ratio factor is used to modify the introduced elastic-plastic factor, and then a new fatigue life prediction model considering the influence of strain ratio and low cycle fatigue plastic deformation on material fatigue damage accumulation is proposed. The results show that the prediction results of the proposed model are in good agreement with the experimental data, and the proposed model has good fatigue life prediction ability considering the influence of strain ratio and lays a foundation for the fatigue life prediction of the oil filter.