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This paper aims to compare different dynamical models, cavitation procedures and numerical methods to simulate hydrodynamic lubricated bearings of internal combustion engines.

Two dynamical models are considered for the main bearing of combustion engines. The first is a fluid-structure interaction multi-body dynamics coupled with lubricated bearings, where the equilibrium and Reynolds equations are solved together. The second model finds the equilibrium position of the bearing subjected to previously calculated dynamical loads. The Traditional p-? procedure and Giacopini’s model described in Giacopini et al. (2010) are adopted for cavitation purposes. The influence of the finite difference and finite element numerical methods is investigated.

Simulations were carried out considering small-, mid- and large-sized engines and the dynamical models differed mainly in predicting the journal orbits. Finite element method with Giacopini’s cavitation model had improved numeric stability for the three engines.

The dynamic models do not consider the flexibility of the components of the main mechanism of combustion engines which may overestimate the oil pressure and journal orbits.

It can help researchers and engineers to decide which combination of methods is best suited for their needs and the implications associated with each one.

The used methods may help engineers to design better and more efficient combustion engines.

This paper helps practitioners to understand the effects of different methods on the results. Additionally, depending on the engine, one approach can be more effective than the other.

Mobile health (mHealth) technologies, in particular, have been sought after and advocated as a means of dealing with the pandemic situation. Despite the obvious advantages of mHealth, which include monitoring and exchanging health information via mobile applications, mHealth adoption has yet to take off exponentially. Expanding on the unified theory of acceptance and use of technology (UTAUT) model, this study aims to better comprehend consumers’ receptivity to mHealth even after the pandemic has subsided.

Through purposive sampling, data were collected from a sample of 345 mobile phone users and analysed using partial least squares structural equation modelling (PLS-SEM) and artificial neural networks (ANN) capture both linear and nonlinear relationships.

Effort expectancy, performance expectancy, social influence, pandemic fear and trustworthiness positively influenced mHealth adoption intention, with the model demonstrating high predictive power from both the PLSpredict and ANN assessments.

The importance–performance map analysis (IPMA) results showed that social influence had great importance for mHealth uptake, but demonstrated low performance.

Referrals are an alternative that policymakers and mHealth service providers should think about to increase uptake. Overall, this study provides theoretical and practical insights that contribute to the advancement of digital healthcare, aligning with the pursuit of Sustainable Development Goal 3 (SDG 3) (good health and well-being).

This study has clarified both linear and nonlinear relationships among the factors influencing intentions to adopt mHealth. The findings from both PLS and ANN were juxtaposed, demonstrating consistent findings.

Sustainable development concern, coupled with changes in the talent landscape, has led to a heightened focus on green human resource management (GHRM). Drawing on attribution theory and conservation of resources theory, this study examined GHRM, leader–member exchange (LMX) and core self-evaluations (CSE) in relation to work engagement together with human resource management (HRM) performance attributions as a mediator.

Partial least squares structural equation modelling (PLS-SEM) was used to analyse the data collected from 110 respondents working in ISO 14001 certified organisations in Malaysia.

Results revealed that GHRM and LMX were positively related to HRM performance attributions that were intended to improve employee performance. However, CSE was not found to be related to HRM performance attributions. Consequently, HRM performance attributions were positively related to work engagement. Furthermore, GHRM and LMX had positive indirect effects on work engagement through HRM performance attributions as a mediator.

Since the data collected were from Malaysia only, it limits the generalisability of the results to other regions.

The findings suggest that organisations should adopt GHRM and train its leaders to forge stronger social bonds with their subordinates to elicit higher work engagement by positively influencing employee attributions on the motives of HRM practices.

This study contributes to the acknowledged gap on GHRM and HRM attributions by examining the non-green employee outcomes of GHRM and the antecedents of HRM performance attributions. This study also contributes by integrating attribution theory with conservation of resources theory to provide the mediation mechanism in linking GHRM and LMX towards higher work engagement through HRM performance attributions as a mediator; thus empirically illustrating the resource gain spirals.

This chapter tries to shed some light on the relationship between cultural patterns and country-specific public sector reform profiles. For a comparison, the British and German cases seem to be particularly appealing as they arguably represent two distinct approaches in public sector reform (see also Schröter & Wollmann, 1997; Schröter & Wollmann, 2000). It has become part and parcel of the conventional public management wisdom that the UK stands out for its vigorously pursued market-orientation and the emphasis on the explicitly “managerial” side of the new public management (“freedom to manage”) (see also Schröter, 2006), while few commentators seem to dispute that recent public sector reform programs in Germany have been of only modest range – more concerned with “maintaining” (Pollitt & Bouckaert, 2004) established features of the administrative system and fine-tuning the internal bureaucratic machinery of the state apparatus. At this point, our discussion does not take issue with that stereotypical depiction of national reform styles (see Schröter, 2001); rather it tackles a potentially powerful approach of interpreting the conspicuous policy variance: the linkage between traditional political and administrative cultures and national reform strategies.

One of the challenging issues in computer vision and pattern recognition is face image recognition. Several studies based on face recognition were introduced in the past decades, but it has few classification issues in terms of poor performances. Hence, the authors proposed a novel model for face recognition.

The proposed method consists of four major sections such as data acquisition, segmentation, feature extraction and recognition. Initially, the images are transferred into grayscale images, and they pose issues that are eliminated by resizing the input images. The contrast limited adaptive histogram equalization (CLAHE) utilizes the image preprocessing step, thereby eliminating unwanted noise and improving the image contrast level. Second, the active contour and level set-based segmentation (ALS) with neural network (NN) or ALS with NN algorithm is used for facial image segmentation. Next, the four major kinds of feature descriptors are dominant color structure descriptors, scale-invariant feature transform descriptors, improved center-symmetric local binary patterns (ICSLBP) and histograms of gradients (HOG) are based on clour and texture features. Finally, the support vector machine (SVM) with modified random forest (MRF) model for facial image recognition.

Experimentally, the proposed method performance is evaluated using different kinds of evaluation criterions such as accuracy, similarity index, dice similarity coefficient, precision, recall and F-score results. However, the proposed method offers superior recognition performances than other state-of-art methods. Further face recognition was analyzed with the metrics such as accuracy, precision, recall and F-score and attained 99.2, 96, 98 and 96%, respectively.

The good facial recognition method is proposed in this research work to overcome threat to privacy, violation of rights and provide better security of data.

In this paper, we first develop the concepts of authentic leaders, authentic leadership, and authentic leader development. We suggest a definition of authentic leaders, which is based on the leader’s self-concept: his or her self-knowledge, self-concept clarity, self-concordance, and person-role merger, and on the extent to which the leader’s self-concept is expressed in his or her behavior. Following, we offer a life-story approach to the development of authentic leaders. We argue that authentic leadership rests heavily on the self-relevant meanings the leader attaches to his or her life experiences, and these meanings are captured in the leader’s life-story. We suggest that self-knowledge, self-concept clarity, and person-role merger are derived from the life-story. Therefore, the construction of a life-story is a major element in the development of authentic leaders. We further argue that the life-story provides followers with a major source of information on which to base their judgments about the leader’s authenticity. We conclude by drawing some practical implications from this approach and presenting suggestions for further research.

In this chapter, we integrate recent theories on followers’ self-concept and transformational leadership theory in order to develop a conceptual framework for understanding the exceptional and diverse effects transformational leaders may have on their followers. We propose that transformational leaders may influence two levels of followers’ self-concept: the relational and the collective self thus fostering personal identification with the leader and social identification with the organizational unit. Specific leader behaviors that prime different aspects of followers’ self-concepts are identified, and their possible effects on different aspects of followers’ perceptions and behaviors are discussed.