Search results

The paper proposed a fast procedure for solving the reliability-based robust design optimization (RBRDO) by modifying the RBRDO formulation and transforming it into a series of RBRDO subproblems. Then for each subproblem, the objective function, constraint function and reliability index are approximated using Taylor series expansion, and their approximate forms depend on the deterministic design vector rather than the random vector and the uncertain estimation in the inner loop of RBRDO can be avoided. In this way, it can greatly reduce the evaluation number of performance function. Lastly, the trust region method is used to manage the above sequential RBRDO subproblems for convergence.

As is known, RBRDO is nested optimization, where the outer loop updates the design vector and the inner loop estimate the uncertainties. When solving the RBRDO, a large evaluation number of performance functions are needed. Aiming at this issue, the paper proposed a fast integrated procedure for solving the RBRDO by reducing the evaluation number for the performance functions. First, it transforms the original RBRDO problem into a series of RBRDO subproblems. In each subproblem, the objective function, constraint function and reliability index caused are approximated using simple explicit functions that solely depend on the deterministic design vector rather than the random vector. In this way, the need for extensive sampling simulation in the inner loop is greatly reduced. As a result, the evaluation number for performance functions is significantly reduced, leading to a substantial reduction in computation cost. The trust region method is then employed to handle the sequential RBRDO subproblems, ensuring convergence to the optimal solutions. Finally, the engineering test and the application are presented to illustrate the effectiveness and efficiency of the proposed methods.

The paper proposes a fast procedure of solving the RBRDO can greatly reduce the evaluation number of performance function within the RBRDO and the computation cost can be saved greatly, which makes it suitable for engineering applications.

The standard deviation of the original objective function of the RBRDO is replaced by the mean and the reliability index of the original objective function, which are further approximated by using Taylor series expansion and their approximate forms depend on the deterministic design vector rather than the random vector. Moreover, the constraint functions are also approximated by using Taylor series expansion. In this way, the uncertainty estimation of the performance functions (i.e. the mean of the objective function, the constraint functions) and the reliability index of the objective function are avoided within the inner loop of the RBRDO.

The purpose of this paper is to exploit a new and robust method to forecast the long-term extreme dynamic responses for wave energy converters (WECs).

A new adaptive binned kernel density estimation (KDE) methodology is first proposed in this paper.

By examining the calculation results the authors has found that in the tail region the proposed new adaptive binned KDE distribution curve becomes very smooth and fits quite well with the histogram of the measured ocean wave dataset at the National Data Buoy Center (NDBC) station 46,059. Carefully studying the calculation results also reveals that the 50-year extreme power-take-off heaving force value forecasted based on the environmental contour derived using the new method is 3572600N, which is much larger than the value 2709100N forecasted via the Rosenblatt-inverse second-order reliability method (ISORM) contour method.

The proposed method overcomes the disadvantages of all the existing nonparametric and parametric methods for predicting the tail region probability density values of the sea state parameters.

It is concluded that the proposed new adaptive binned KDE method is robust and can forecast well the 50-year extreme dynamic responses for WECs.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

It has long been recognized that overwhelmed employees of bureaucratic organizations use a variety of strategies to cope with demand for their services, often at the expense of their clients. One such strategy involves discouraging clients from taking action by making references to complex bureaucratic procedures and routines. While the public management literature has a well-developed research program focusing on the mobilization of such administrative burdens, organization theory seems to be lagging behind in the analysis of that type of misconduct. In this chapter, we explain how references to the representational dimension of routines can be used to discourage clients from taking action, what are the boundary conditions of such a strategy, and its possible consequences for clients.

The main purpose of the study is to determine the mediating role of trait anxiety in the relationship between hotel managers’ perceptions of digital competence in the Cappadocia Region and their perceptions of job insecurity.

In this study, which is based on quantitative research, a cross-sectional design was used. The seven-item digital competence scale, four-item job insecurity scale and 20-item trait anxiety scale were used to measure the level of digital competence, job insecurity and trait anxiety of hotel managers. The convenience sampling method was used in the research, and 337 questionnaires were completed by senior and junior managers who agreed to participate in the research. To test the mediating role of trait anxiety, Andrew F. Hayes’ views on the contemporary approach were taken as a basis.

The analysis results showed that digital competence had the opposite effect on job insecurity. Similarly, digital competence had the opposite effect on the level of trait anxiety. The level of trait anxiety affected the perception of job insecurity in a linear direction. As a result of the bootstrapping test, it was found that the indirect effect of trait anxiety on the relationship between digital competence and job insecurity was significant.

The study was unable to collect data from hotels that were closed during the COVID-19 pandemic due to restrictions. Therefore, one of the limitations of the study was that it did not reach the entire population. Another limitation of the study was that the questionnaires were addressed to hotel managers in the Cappadocia Region.

Hotel managers’ digital skills are considered to contribute to the tourism industry by organizing and determining business strategies, work processes and employee skills. In addition, when hiring hotel managers, it is essential to ensure that they have certain skills such as compatibility with the digital age, openness to innovation and the ability to adapt the employees working in their team to the age, which helps to improve the competitiveness of the hotel industry with the world and ensure the continuity of this situation.

The research addressed the variables of digital competence, job insecurity and trait anxiety and collected data from hotel managers in the Cappadocia Region using a survey technique. There were few studies that addressed these variables, and the mediating effect of trait anxiety was revealed based on the contemporary approach.

The purpose of this paper is to explore teacher candidates’ response to young adult literature (prose and comics) featuring fat identified protagonists. The paper considers the textual and embodied resources readers use and reject when imagining and interpreting a character’s body. This paper explores how readers’ meaning making was influenced when reading prose versus comics. This paper adds to a corpus of scholarship about the relationships between young adult literature, comics, bodies and reader response theory.

At the time of the study, participants were enrolled in a teacher education program at a Midwestern University, meeting monthly for a voluntary book club dedicated to reading and discussing young adult literature. To examine readers’ responses to comics and prose featuring fat-identified protagonists, the author used descriptive qualitative methodologies to conduct a thematic analysis of meeting transcripts, written participant reflections and researcher memos. Analysis was grounded in theories of reader response, critical fat studies and multimodality.

Analyses indicated many readers reject textual clues indicating a character’s body size and weight were different from their own. Readers read their bodies into the stories, regarding them as self-help narratives instead of radical counternarratives. Some readers were not able to read against their assumptions of thinness (and whiteness) until prompted by the researcher and other participants.

Although many reader response scholars have demonstrated readers’ tendencies toward personal identification in the face of racial and class differences, there is less research regarding classroom practices around the entanglement of physical bodies, body image and texts. Analyzing reader’s responses to the constructions of fat bodies in prose versus comics may help English Language Arts (ELA) educators and students identify and deconstruct ideologies of thin-thinking and fatphobia. This study, which demonstrates thin readers’ tendencies to overidentify with protagonists, suggests ELA classrooms might encourage readers to engage in critical literacies that support them in reading both with and against their identities.

Following the COVID-19 pandemic, the issues related to job insecurity became even more prominent than before. This paper sets out to identify the determinants of job insecurity in the context of the COVID-19 pandemic among Romanian workers, a topic than was scarcely addressed in previous studies.

Based on a representative sample at the national level (N = 744), the authors performed a multilinear regression analysis that pinpoints the factors predicting job insecurity.

This study findings indicate that high-skilled workers employed on permanent arrangements, having higher workloads, who had received organizational support, and managed to harmonize work demands with family responsibilities experience the lowest levels of job insecurity. In this study, teleworking does not influence the level of job insecurity. Gender (being male), working in the public sector and approving the political management of the COVID-19 pandemic also count in securing the feelings employees have about their job.

Besides filling a geographical gap in the literature, another innovative contribution of the paper is the emphasis on the importance for the employees of how public authorities manage the public health crisis. Also, this study explores the workload as a factor of job insecurity which was unaddressed previously. Implications for research and practice are emphasized.

Governments globally are adopting e-Government services to streamline administrative processes and meet citizens' expectations. This study investigates e-Government service quality from citizens' perspectives in 50 Greek municipalities, using the technology acceptance model (TAM) and cognitive theory.

The data from 707 respondents across 50 Greek municipalities are analyzed using structural equation modeling (SEM), ANOVA and moderation analysis. The study assesses the relationships between key factors and citizens' intentions to use e-Government services, examining the impact of demographics and the digital divide.

The study reveals that perceived attractiveness (PA), perceived usefulness (PU), perceived ease of use (PEOU) and awareness (AWA) significantly influence citizens' behavioral intentions (BINTs) toward municipal e-Government services. Interestingly, PEOU negatively impacts users' intentions, suggesting dissatisfaction with portal attractiveness and utility. The study explores the influence of demographic variables and the digital divide on citizens' BINTs, highlighting economic activity and income as crucial determinants.

The study emphasizes the significance of user-friendly design, PU, PEOU and AWA campaigns for the development of effective e-Government platforms. Strategies to address the digital divide and promote citizen engagement are essential for enhancing user experience, service utility and AWA, ultimately fostering a positive attitude toward e-Government.

Addressing demographic differences ensures inclusive e-Government systems, while bridging the digital divide promotes equitable service delivery and citizen engagement.

This research provides insights into factors influencing citizens' BINTs toward e-Government services. The study's examination of demographic attributes and the digital divide enhances understanding, contributing to the development of citizen-centric e-Government services and supporting inclusive digital transformations.