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The dielectric properties of materials (complex permittivity) can be deduced from the admittance measured at the discontinuity plane of a coaxial open‐ended probe. This implies the implementation of an inversion procedure. The purpose of this paper is to develop a new non‐iterative inversion methodology in the field of microwave characterization allowing reducing the computation cost comparatively to iterative procedures.

The inversion methodology combines the support vector machine (SVM) technique and the finite element method (FEM). The SVM are used as inverse models. They show good approximation and generalization capabilities. FEM allows the generation of the data sets required by the SVM parameter adjustment. A data set is constituted of input (complex admittance and frequency) and output (complex permittivity) pairs.

The results show the applicability of SVM to solve microwave inverse problems instead of using traditional iterative inversion methods which can be very time‐consuming. The experimental results demonstrate the accuracy which can be provided by the SVM technique.

The paper allows extending the capability of microwave characterization cells developed at Laboratoire de Génie Électrique de Paris.

A new inversion method is developed and applied to microwave characterization. This new concept introduces SVM in the context of microwave characterization. SVM results and iterative inversion procedure results are compared in order to evaluate the effectiveness of the developed technique.

The principle of microwave characterization of dielectric materials using open-ended coaxial line probe is to link the dielectric properties of the sample under test to the measurements of the probe admittance (Y(f) = G(f)+ jB(f )). The purpose of this paper is to develop an alternative inversion tool able to predict the evolution of the complex permittivity (ε = ε′ – jε″) on a broad band frequency (f from 1 MHz to 1.8 GHz).

The inverse problem is solved using adaptive network based fuzzy inference system (ANFIS) which needs the creation of a database for its learning. Unfortunately, train ANFIS using f, G and B as inputs has given unsatisfying results. Therefore, an inputs selection procedure is used to select the three optimal inputs from new inputs, created mathematically from original ones, using the Jang method.

Inversion results of measurements give, after training, in real time the complex permittivity of solid and liquid samples with a very good accuracy which prove the applicability of ANFIS to solve inverse problems in microwave characterization.

The originality of this paper consists on the use of ANFIS with input selection procedure based on the Jang method to solve the inverse problem where the three optimal inputs are selected from 26 new inputs created mathematically from original ones (f, G and B).

In this chapter, the authors will examine turnover in Turkey. In the first section, the authors will briefly describe the legal, institutional, and cultural context with a particular emphasis on their implications for employment conditions and turnover in Turkey. In the second section, the authors will review the academic literature on turnover that originated from Turkey. The authors divide the reviewed studies into two groups: generalizability studies, which are primarily replications of the mainstream literature with no focus on any specific characteristics of Turkey, and contextual studies, which emphasized the role of the economic, legal, or cultural background in formulating or interpreting their research. In the final section, the authors will discuss the findings of the review vis-á-vis the mainstream literature as well as practical implications and conclude with potential future research directions in the Turkish context.

The present study connects the literature on sustainable HRM with that on employability to investigate the relationship between sustainability-oriented human resource actions and organizational outcomes. More specifically, this study explores how training for employability affects the employer–employee relationship and employee retention. Furthermore, this study considers competitive intensity as a potential moderator in these relationships.

The analyses draw on the fourth European Company Survey (ECS 2019) with a sample of 21?869 firms with more than ten employees. Two separate logistic regression models were used to test the hypothesis.

The results show that training for employability contributes to improving the employer–employee relationship and that competitive intensity positively shapes this relationship. Contextually, training for employability reduces the overall employee retention of the firm.

Although this study supports the potential win–win nature of employability support, especially for companies that operate in competitive markets and an uncertain environment, it also highlights the existence of paradoxical sustainability tensions that should be managed by employers.

A framework for reliable modeling of high-frequency structures by nested kriging with an improved sampling procedure is developed and extensively validated. A comprehensive benchmarking including conventional kriging and previously reported design of experiments technique is provided. The proposed technique is also demonstrated in solving parameter optimization task.

The keystone of the proposed approach is to focus the modeling process on a small region of the parameter space (constrained domain containing high-quality designs with respect to the selected performance figures) instead of adopting traditional, hyper-cube-like domain defined by the lower and upper parameter bounds. A specific geometry of the domain is explored to improve a uniformity of the training data set. In consequence, the predictive power of the model is improved.

Building the model in a constrained domain allows for a considerable reduction of a training data set size without a necessity to either narrow down the parameter ranges or to reduce the parameter space dimensionality. Improving uniformity of training data set allocation permits further reduction of the computational cost of setting up the model. The proposed technique can be used to expedite the parameter optimization and enables locating good initial designs in a straightforward manner.

The developed framework opens new possibilities inaccurate surrogate modeling of high-frequency structures described by a large number of geometry and/or material parameters. Further extensions can be investigated such as the inclusion of the sensitivity data into the model or exploration of the particular geometry of the model domain to further reduce the computational overhead of training data acquisition.

The efficiency of the proposed method has been demonstrated for modeling and parameter optimization of high-frequency structures. It has also been shown to outperform conventional kriging and previous constrained modeling approaches. To the authors’ knowledge, this approach to formulate and handle the modeling process is novel and permits the establishment of accurate surrogates in highly dimensional spaces and covering wide ranges of parameters.

Prompted by the enlarging skills gap between the university graduate and the desired employee in Mauritius, the Charles Telfair Institute embarked its students on the #NuKapav project for an authentic work integrated learning (WIL) experience which endeavours to fight for the societal inclusion of Persons with Disabilities. The purpose of this paper is to examine the impact of this service-learning project on the students from professional, civic engagement and social justice perspectives.

This research used a focus group methodology, allowing the 23 students who participated on the #NuKapav project to share their experiences.

This paper recommends that universities in Mauritius and other regional countries consider incorporating service-learning into their WIL programmes to reinforce graduate employability skills and encourage good citizenship through lasting allegiance to community causes.

The higher education system in Mauritius operates within a broader context facing constant mutations influenced by socio-economic and political factors. As such, research on service-learning cannot be conducted in isolation but should instead include the perspective of various stakeholders on both the demand and supply side of community learning projects. The main limitation of this research relates to its focus on capturing student participants’ perspective alone. Further research is, therefore, recommended to examine how other stakeholders, including employees, employers and community service project supervisors, value service-learning for a more comprehensive view.

The main contribution of this paper is the examination of how service-learning can help equip graduates with crucial career skills, while bringing an enduring mind-set shift in the future workforce for sustained commitment to social change and inclusion.

Drawing upon self-determination theory, this study investigates the direct and indirect impact of health-promoting leadership on employee engagement via workplace relational civility and explores the moderating effect of employability on these factors.

The authors collected a total of 723 matched and valid responses from nurses in Guangxi, China. Data regarding health-promoting leadership, workplace relational civility, employability and employee engagement were gathered using a survey administered in two waves, 1 week apart. The authors utilised structural equation modelling and linear regression to test the model.

This study reveals that health-promoting leadership has both direct and indirect positive effects on nurses' engagement through workplace relational civility. Furthermore, the authors found that employability negatively moderates the impact of workplace relational civility on nurses' engagement but does not moderate the impact of health-promoting leadership on nurses' engagement.

This is one of the few studies that have examined the effects of health-promoting leadership within the nursing industry. The authors confirm the importance of health-promoting leadership and workplace relationship civility on employee engagement. In addition, this study demonstrates the moderating role of employability in employment relationships.

The purpose of this paper is to advance two seemingly conflicting paths from perceived employability to employee performance. Both paths start from the idea that feeling employable makes employees more independent from their employer. Framed positively, independence implies the perception of being in control, and perceived control may promote employee performance. Framed negatively, independence implies reduced attachment to the organization, while such ties drive employee performance. Innovative features in this study are threefold. First, the authors introduce perceived justice as a moderator. Second, the authors distinguish between perceived quantitative and qualitative employability: this relates to seeing “other” vs “better” job opportunities. Third, the authors include a range of performance indicators: task performance, organizational citizenship behavior and counterproductive work behavior.

Survey data were collected within one Belgian public-sector organization (n=1,500 employees) and analyzed using structural equation modeling.

Perceived control mediated the relationship between perceived employability and employee performance, yet only upon high perceived justice. Affective organizational commitment mediated the relationship between perceived employability and employee performance, regardless of perceived justice. Those relationships were positive for quantitative perceived employability and negative for qualitative perceived employability.

Perceived employability relates positively to employee performance, especially upon high perceived justice. Yet this relationship is bounded to which job alternatives are perceived, just “other” or instead “better.”

This study aims to explore the serial mediation effect of perceived internal employability and affective commitment in the relationship between the organisational practices of competences development and turnover intentions.

The methodology was quantitative and is based on a survey with a sample of 313 participants, all of whom were employed in several organisations located in Portugal.

A significant and negative effect of organisational practices of competences development, perceived internal employability and affective commitment on turnover intentions was verified. A total serial mediation effect was also found from perceived internal employability and affective commitment in the relationship between organisational practices of competences development (i.e., training, individualised support and functional rotation) and turnover intentions.

These practices should be developed by leaders of organisations in order that employees feel that the organisation is investing in their development, which can lead to an increase in their emotional attachment towards the organisation and consequently increase their desire to stay in the organisation.

This study makes two important contributions. First, it confirms the existence of a significant and negative relationship between perceived internal employability and turnover intentions. Second, it proves the existence of a total serial mediation effect of perceived internal employability and affective commitment in the relationship between organisational practices of competences development and turnover intentions.

Eddy current testing (ECT) is a nondestructive testing method for the detection of flaws that uses electromagnetic induction to find defects in conductive materials. In this method, eddy currents are generated in a conductive material by a changing magnetic field. A defect is detected when there is a disruption in the flow of the eddy current. The purpose of this paper is to develop a new noniterative inversion methodology for detecting degradation (defect characterization) such as cracking, corrosion and erosion from the measurement of the impedance variations.

The methodology is based on multi-output support vector machines (SVM) combined with the adaptive database schema design method (SDM). The forward problem was solved numerically using finite element method (FEM), with its accuracy experimentally verified. The multi-output SVM is a statistical learning method that has good generalization capability and learning performance. FEM is used to create the adaptive database required to train the multi-output SVM and the genetic algorithm is used to tune the parameters of multi-output SVM model.

The results show the applicability of multi-output SVM to solve eddy current inverse problems instead of using traditional iterative inversion methods which can be very time-consuming. With the experimental results the authors demonstrate the accuracy which can be provided by the multi-output SVM technique.

The work allows extending the capability of the experimentation ECT defect characterization system developed at LGEP.

A new inversion method is developed and applied to ECT defect characterization. This new concept introduces multi-output SVM in the context of ECT. The real data together with estimated one obtained by multi-output SVM model are compared in order to evaluate the effectiveness of the developed technique.