Search results

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

The police often respond to persons who are not in direct violation of the law, but are rather undergoing behavioral crises due to mental illness or substance abuse disorders. The purpose of this study is to examine how police behavior influences civilian bystanders' emotional responses and perceptions of procedural justice (PPJ) when officers interact with these populations, which traditionally have been stigmatized in American culture.

Using a factorial vignette approach, the authors investigate whether perceived public stigma moderates the relationship between police behaviors (i.e. CIT tactics, use of force) and PPJ. The authors also investigate whether emotional reactions mediate the relationship between police behaviors and PPJ.

Regardless of suspect population (mental illness, substance use), use of force decreased participants' PPJ, and use of CIT tactics increased PPJ. These effects were consistently mediated by anger, but not by fear. Interactive effects of police behavior and perceived public stigma on PPJ were mixed.

Fear and anger may operate differently as antecedents to PPJ. Officers should note using force on persons in behavioral crisis, even if legally justifiable, seems to decrease PPJ. They should weigh this cost pragmatically, alongside other circumstances, when making discretionary decisions about physically engaging with a person in crisis.

This paper examines gender diversity in the Australian valuation industry from the perspective of valuers in senior management and leadership roles and discusses gender diversity policies and practices in their organisations. Then, it explores the initiatives that can be implemented to improve gender diversity in the Australian valuation industry.

A focus group discussion was conducted with valuers in senior management and leadership roles from selected large valuation firms and government valuation agencies in Melbourne, Australia. Data collected through the focus group discussion was combined with secondary data sourced from journals, online articles and archival materials.

The findings reveal that whilst gender diversity in the Australian valuation industry has improved over the years, females remain underrepresented. Nonetheless, whilst some valuation companies have recognised the need to address the underrepresentation of women and introduced specific gender-focussed human resource policies and practices, these initiatives are not streamlined and implemented across the industry.

The study highlights the need for closer collaboration between key stakeholders such as universities, professional associations, valuation companies and government agencies in devising strategies to attract female talents into the valuation industry.

The paper is the first empirical study to assess gender diversity in the Australian valuation industry from the perspective of valuers in management and leadership roles. The proposed policies can inform future initiatives to improve gender diversity in the valuation industry.