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Finite Elements FE based on the Reissner’s Mixed Variational Theorem RMVT, for the analysis of multilayered plates subjected to magneto‐electro‐elastic MEE fields, are developed in this work. Accurate description of the various field variables has been provided by employing a variable kinematic model which is based on the Carrera’s Unified Formulation CUF. Displacements, transverse shear/normal stresses, magnetic and electric potentials have been chosen as independent unknowns. Interlaminar continuity of mechanical variables is “a priori” guaranteed by the RMVT application. Layer‐wise plate elements with linear up to fourth order distribution in the thickness direction have been compared. FE governing equations, according to CUF, are presented in terms of fundamental nuclei whose form is not affected by kinematic assumptions. Results show the effectiveness of the proposed elements, the superiority of mixed FEs with respect to the classical ones, as well as their capability, by choosing appropriate kinematics, to accurately trace the static response of laminated plates subject to magneto‐electro‐elastic fields.

Finite elements for the analysis of multilayered plates subjected to magneto‐electro‐elastic fields are developed in this work. An accurate description of the various field variables has been provided by employing a variable kinematic model which is based on the Unified Formulation, UF. Displacements, magnetic and electric potential have been chosen as independent unknowns. Equivalent single layer and layer‐wise descriptions have been accounted for. Plate models with linear up to fourth‐order distribution in the thickness direction have been compared. The extension of the principle of virtual displacements to magneto‐electro‐elastic continua has been employed to derive finite elements governing equations. According to UF these equations are presented in terms of fundamental nuclei whose form is not affected by kinematic assumptions. Results show the effectiveness of the proposed elements as well as their capability, by choosing appropriate kinematics, to accurately trace the static response of laminated plates subject to magneto‐electro‐elastic fields.

This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.

A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.

The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.

The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.

In this paper, we show that workers’ performance in firms is conditioned by a set of informational factors and expectations about the future. We also demonstrate that any corporate action that successfully raises workers’ employment expectations will translate into performance gains. In the current uncertain context, firms can raise productivity by offering higher‐value jobs that provide workers with greater opportunities to improve their employability. In this sense, high‐performance work organizations can play an important role.

The research about the concept of Halal tourism has emerged recently. It becomes the vital factor in determining the tourists's satisfaction or their loyalty. Thus, this concept needs to be developed in certain areas because it still not acknowledged. The purpose of this study is to align the theoretical foundations of Halal tourism to conventional tourism paradigms. It investigates the value of Muslim tourists' perception in the context of Malaysian tourist destination. The six variables of Muslim tourist perceived value (MTPV) are examined such as quality, price, emotional, social, physical and non-physical attributes. The respondents of the research are a total of 205 Muslim tourists in Langkawi, Malaysia during October 2021 (Langkawi Tourism Bubble). The results indicated four (4) variables have impacts on tourist satisfaction. Practical implications will impact towards cognitive, affective and Islamic (i.e. Halal) values on tourist satisfaction. It was examined as one of the priotitize destination experience on tourist satisfaction. The findings provide Malaysian tourism with significant managerial implications. It also impacted the Halal tourism as a new approach specifically in the post COVID-19 era. Hence, in improving Muslim tourist satisfaction, destination marketers should consider the Halal tourism. Tour agencies also should scrutinize the product and services value including destination attributes that they offer. The destination's competitiveness will be strengthened with the right destination attraction, facilities, accommodation and activities that suit Muslim tourists.

This study aims to explore the ways in which young people and prison staff (Prison Officers) within a youth custodial establishment experience empathy. Previous research tends to view empathy as a stable trait and one which people can develop through individual-centred therapy. There has been little consideration of the impact of relationship factors and context in relation to empathy experience and expression. The current study aims to address this by exploring the role of the custodial context in shaping empathy, including the potential impact of relationships, environmental factors and culture.

A qualitative approach was used to enable breadth and depth in the exploration of this area. Individual, semi-structured interviews were carried out with a purposive sample of three young people and three Prison Officers. Data was analysed using inductive thematic analysis informed by the guidelines of Braun and Clarke (2006) and King and Horrocks (2010).

Constructed themes included “constructions of empathy”, “recipe for empathy”, “institutional investment”, “the value of empathy” and “doing empathy”. Together, they provide detailed insight into the interplay of personal and wider contextual factors influencing the experience of empathy in a custodial setting. The findings suggest that the way in which young people and staff experience empathy in the custodial environment is unique. The findings suggest that empathy takes place within the context of relationships and is influenced by the nature of those relationships, along with the wider social context within which it occurs.

The findings of the current study support a move away from understanding empathy as an individual personality trait and instead viewing it as a dynamic experience that is changeable based upon the relationship and the context within which it occurs. The findings suggest that interventions aiming to develop empathy should look beyond the level of the individual and the relationship and focus upon developing environments that are supportive of empathy.

This study provides unique insights into the subjective experience of empathy in a custodial setting, presenting as one of the first to take a more holistic approach to understand this phenomenon.

Changing career patterns and the erosion of job security have led to a growing emphasis on employability as a basis for career and employment success. The written and psychological contracts between employer and employer have become more transactional and less relational, and loyalty is no longer a guarantee of ongoing employment. Individuals are thus expected to take primary responsibility for their own employability rather than relying on the organisation to direct and maintain their careers. The purpose of this paper is to identify and examine the assumptions underpinning the concept of employability and evaluate the extent to which employability has been adopted as a new covenant in the employment relationship.

Through a review of relevant literature the paper discusses current research on careers and employability and examines the available evidence regarding its adoption as a basis for contemporary employment relationships.

The paper finds that the transfer of responsibility for employability from organisation to individual has not been widespread. There is still an expectation that organisations will manage careers through job‐specific training and development. Employability has primarily benefited employees with highly developed or high‐demand skills. Employability is not a guarantee of finding suitable employment.

Employers can assist their employees by clarifying changes to the psychological contract, highlighting the benefits of career self‐management, and providing training and development in generic employability skills.

The paper questions underlying assumptions about employability and explores issues of relevance to human resource managers, policy‐makers, employers and employees.

Today’s successful restaurant manager needs to possess a diversity of talents, abilities, and skills. Presents profiles of successful managerial recruits for quick service, midscale and upscale restaurants in the US. Factor analysis was used to reduce the number of attributes and traits that were identified for being a successful manager in the restaurant industry. Seventy‐two success attributes and traits were reduced to 12 identifiable components. The components’ relationships with the demographic factors were then studied using Chi‐square tests. Profiles for being a successful manager in quick service, midscale and upscale restaurants were developed.

The purpose of this paper is to deal with the anomaly detection problem in multi-unmanned aerial vehicles (UAVs) formation that can be transformed to identify some unknown parameters; a more general nonlinear dynamical model for each UAV is considered to include two terms. Due to an unknown parameter corresponding to the normal or abnormal state for each UAV, the bias-compensated approach is proposed to obtain the unbiased parameter estimation. Meanwhile, the biased error and accuracy analysis are also given in case of strict statistical description of the uncertainty or white noise. To relax this strict statistical description on external noise, an analytic center approach is proposed to identify the unknown parameters in presence of bounded noise, such that two inner and outer ellipsoidal approximations are constructed to include the membership set. To be precise, this paper is regarded as one extension and summary for the author’s previous research on the anomaly detection in multi-UAV formation. Finally, one simulation example is given to confirm the theoretical results.

Firstly, one extended nonlinear relation is constructed to embody the mutual relationship of UAVs. Secondly, to obtain the unbiased parameter estimations, the bias-compensated approach is applied to achieve it under the condition of white noise. Thirdly, in case of unknown but bounded noise, an analytic center approach is proposed to deal with this special case. Without loss of generality, the author thinks this paper can be used as one extension and summary for research on multi-UAVs formation anomaly detection.

An anomaly detection problem in multi-UAVs formation can be transformed into a problem of nonlinear system identification, and in modeling the nonlinear dynamical model for each UAV, two terms are considered simultaneously to embody the mutual relationships with other nearest UAV.

To the best knowledge of the authors, this problem of the anomaly detection problem in multi-UAVs formation is proposed by the authors’ previous work, and the problem of multi-UAVs formation anomaly detection can be transferred into one problem of parameter identification. In case of unknown but bounded noise, an analytic center approach is proposed to identify the unknown parameters, which correspond to achieve the goal of the anomaly detection.

The purpose of this paper considers optimal input signal design for flutter model parameters identification, as input signal is the first step during the whole identification process. According to the constructed flutter stochastic model with observed noises, separable least squares identification and set membership identification are proposed to identify those unknown model parameters for statistical noise and unknown but bounded noise, respectively. The common trace operation with respect to the asymptotic variance matrix is minimized to solve the power spectral for the optimal input signal in the framework of statistical noise. Moreover, for the unknown bout bounded noise, the radius of information, corresponding to the established parameter uncertainty interval, is minimized to give the optimal input signal.

First, model identification for aircraft flutter is reviewed as one problem of parameter identification and this aircraft flutter model corresponds to one stochastic model, whose input signal and output are corrupted by external noises. Second, for aircraft flutter statistical model with statistical noise, separable least squares identification is proposed to identify the unknown model parameters, then the optimal input signal is designed to satisfy one given performance function. Third, for aircraft flutter model with unknown but bounded noise, set membership identification is proposed to solve the parameter set for each unknown model parameter. Then, the optimal input signal is designed by applying the idea of the radius of information with unknown but bounded noise.

This aircraft flutter model corresponds to one stochastic model, whose input signal and output are corrupted by external noises. Then identification strategy and optimal input signal design are studied for aircraft flutter model parameter identification with statistical noise and unknown but bounded noise, respectively.

To the best knowledge of the authors, this problem of the model parameter identification for aircraft flutter was proposed by their previous work, and they proposed many identification strategies to identify these model parameters. This paper proposes two novel identification strategies and opens a new subject about optimal input signal design for statistical noise and unknown noise, respectively.