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The purpose of this research is to improve the understanding of what constitutes a successful thesis proposal (TP) and as such enhance the quality of the TP writing in architecture, planning and related disciplines.

Based on extended personal experience and a review of relevant literature, the authors proposed a conception of a successful TP comprising 13 standard components. The conception provides specific definition/s, attributes and success rules for each component. The conception was applied for 15 years on several batches of Saudi graduate students. The implications of the conception were assessed by a students' opinion survey. An expert inquiry of experienced academics from architectural schools in nine countries was applied to validate and improve the conception.

Assessment of the proposed conception demonstrated several positive implications on students' knowledge, performance and outputs which illustrates its applicability in real life. Experts' validation of the conception and constructive remarks have enabled further improvements on the definitions, attributes and success rules of the TP components.

The proposed TP conception with its 13 components is limited to standard problem-solving research and will differ in the case of other types such as hypothesis-based research.

The proposed conception is a useful directive and evaluative tool for writing and assessing thesis proposals for graduate students, academic advisors and examiners.

The research contributes to improving the quality of thesis production process among the academic community in the built environment fields.

The paper is meant to alleviate the confusion and hardship caused by the absence of a consensus on what constitutes a successful TP in the fields of architecture, urban planning and related disciplines.

The purpose of this paper is to investigate the role of partnership in integrating the corporate social responsibility (CSR) of project stakeholders towards better housing affordability.

A research methodology, consisted of literature review and field studies, is designed to accomplish four objectives. First, to provide a comprehensive literature review of the concepts of affordable housing, project stakeholders, CSR and partnership; second, to present and synthesis the results of relevant field studies examined the experiences of CSR and partnership among selected construction firms and the Government of South Africa (SA) in affordable housing projects; third, to develop a CSR‐partnership model (and its action plan) that integrates the CSR of project stakeholders to achieve greater housing affordability; finally, to draw some conclusions and recommendations to improve the practice of CSR and partnership among government authorities and construction professionals.

Affordable housing is one of the greatest challenges that face countries around the globe, especially developing countries. The complexity of the problem hinders governments, alone, from achieving their plans for sustainable development. Project stakeholders must have social responsibilities towards supporting government initiatives for affordable housing development. The five‐domain CSR‐partnership model developed by the authors will help integrating the CSR of project stakeholders as an approach for developing affordable housing project.

Because of the conceptual nature of the proposed model, it has to be tested and validated to ensure its capability to integrate the CSR of project stakeholders as an innovative approach for overcoming the difficulties facing governments in providing housing for the poor.

The conducted review provides better understanding of the issue related to the practice of social responsibilities and partnership of project stakeholders, both worldwide and in SA. Through its five domains (government, society, economy, law, and technology), the proposed CSR‐partnership model and its action plan are expected to serve as a foundation for optimising the partnership of project stakeholders with government authorities towards better housing affordability. This ideology has received scant attention in construction literature. The developed model represents a synthesis that is novel and creative in thought and adds value to the knowledge in a manner that has not previously occurred.

This paper aims to present an optimal variable speed drive of a doubly fed induction motor (DFIM) with minimum losses and reduced inverter capacity. The operation with minimum losses ensures that the DFIM develops the required load torque at desired speed with maximum energy saving. Moreover, the control of rotor voltage ensures the reduced inverter capacity. The water cycle algorithm (WCA) as one of meta-heuristic optimization techniques is used to estimate the optimal rotor voltages to drive the DFIM with minimum losses. The results of WCA are confirmed with other well-known and reliable optimization method such as particle swarm optimization along with classical method.

The DFIM is an efficient alternative solution of synchronous motor (SM) because of its speed is synchronized with both stator and rotor frequencies regardless the load torque. As a result, the speed of variable speed drive associated with DFIM can be controlled through a rotor inverter with reduced capacity rather than SM. The output voltage of rotor inverter is controlled to develop the demanded output power with minimum motor losses.

A complete DFIM drive model is developed under MATLAB/SIMULINK environment using d-q dynamic model to verify the strength and significance of the proposed controller. An experimental setup using a 300 W three-phase wound rotor induction motor is established to validate the mathematical models and theoretical results. The motor performances with proposed rotor voltage control (minimum losses) are compared with conventional method of constant voltage to frequency ratio (V/f constant). It is found that the proposed WCA based on controller achieves significant reductions in motor losses, input power and rotor inverter power.

The paper presents an efficient method to maximize the energy saving of DFIM with a reduced inverter capacity using WCA.

Early childhood teachers play a significant role in building children’s success in their first years of school. Therefore, a healthy early childhood workforce in a healthy working environment is an essential aspect of effective early childhood services. This paper aims to explore the extent to which psychological hardiness can be considered as a mediator variable between exposure to workplace bullying and job anxiety among early childhood teachers.

A homogeneous sample comprised of 200 early childhood teachers. For data collection, the researcher used the workplace bullying scale, the psychological hardiness scale and the job anxiety scale among early childhood teachers (prepared by the researcher).

The findings indicated that psychological hardiness mediates the relationship between exposure to workplace bullying and job anxiety among early childhood teachers.

The research result highlighted the necessity of providing counseling programs for early childhood teachers helping them eliminate work stress that affects their job performance. In addition, the kindergarten administration must concentrate on how to effectively communicate and cooperate with early childhood teachers in light of regulations, policies and laws to defeat the spread of workplace bullying. The results of this research contributed to the existing literature by examining the relationship between the research variables, particularly in the early childhood education context.

Describes Poetry in the Branches, a multi‐layered, replicable program model, devised by Poets House, New York, to foster the link between librarians, the public and the living tradition of poetry. Provides a comprehensive list of titles of contemporary poetry collections by single authors and anthologies.

This paper aims to propose a system for defect detection in constructed elements that is able to indicate deformity positions. It also evaluates the defects in finishing materials of constructed building elements to support the subjective visual quality investigation of the aesthetics of an architectural work.

This strategy depends on defect features analysis that evaluates the defect value in digital images using digital image processing methods. The research uses the three-dimensional (3D) modeling techniques and image processing algorithms to generate a system that is able to perform some of the monitoring activities by computers. Based on the collected site scans, a 3D model is created for the building. Then, several images can be exported from the 3D model to investigate a specific element. Different image denoizing techniques are compared such as mean filter, median filter, Wiener filter and Split–Bregman iterations. The most efficient technique is implemented in the system. Then, the following six different methods are used for image segmentation to separate the concerned object from the background; color segmentation, region growing segmentation, histogram segmentation, local standard deviation segmentation, adaptive threshold segmentation and mean-shift cluster segmentation.

The proposed system is able to detect the cracks and defected areas in finishing works and calculate the percentage of the defected area compared to the total captured area in the photo with high accuracy.

The proposed system increases the precision of decision-making by decreasing the contribution of human subjective judgment. Investigation of different finishing surfaces is applied to validate the proposed system.

The current research study aims to examine the application feasibility and impact of artificial intelligence (AI) among higher educational institutions (HEIs) in talent acquisitions (TA).

A systematic sampling method was adopted to collect the responses from the 385 staff working across the various levels of management in HEIs in metropolitan cities in India. JAMOVI & SmartPLS 4 were applied to validate the hypothesis by performing the simple percentage analysis and structural equation modelling. The demographic and construct variables considered were adoption, actual usage, perceived usefulness, perceived ease of use and talent management.

The key indicators of perceived usefulness are productivity, perceived ease of use, adaptability, candidate experience with the adoption of AI, frequency in decision-making in its actual usage and career path of development in the HEIs. These are the most influential items impacting the application of AI in TA.

AI has the potential to revolutionize TA in HEIs in the form of enhanced efficiency, improved candidate experience, more objective hiring decisions, talent analytics and risk automation. However, they facilitate resume screening, candidate sourcing, applicant tracking, interviewing and predictive analytics for attrition.