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As an important indicator of the quality of life of individuals, residential environments are continuing to evolve, due to the rapidly changing production–consumption relations. However, in this evolving process, the effect of the differentiated residential environments on the individuals' residential satisfaction remains unclear. This paper aims to measure the effects of the varying residential environments on the overall quality of urban life (QoUL) in Kayseri, one of the most developed cities in Central Anatolia.

It is based on empirical data on the quality of life in the different residential environments of Kayseri. The research method used stratified purposeful sampling, and the household survey data were analyzed using factor analysis, multiple regression and ANOVA statistical methods.

The most influential factors on the overall QoUL of individuals living in different Kayseri residential neighborhoods were satisfaction with neighborhood and city-level urban services, neighborhood relations and belonging factor groups. The critical finding obtained in this study is that residential satisfaction in low-rise and compact form housing areas in Kayseri is higher compared to residential satisfaction in high-rise neighborhoods. This result reveals that the high-rise building typology that is dominant in Turkey's big cities should be seriously questioned, and urban development policies should be re-evaluated.

The study was designed to produce baseline data so that future changes in residential conditions as perceived by the residents of Kayseri could be monitored to support decisions for residential areas.

Comparative case studies, particularly on low-rise versus high-rise environments, are scarce. As a result, this research contributes to the field of comparative studies on residential environments.

Compared to low-rise and mid-rise buildings, commercial high-rise buildings have severe maintenance management deficiencies due to the complex nature of the structure and building services incorporated. Previous studies have shown that implementing lean in maintenance is a recognised prominent strategy to enhance maintenance performance. Thus, this study aims to investigate how lean maintenance can be applied to improve maintenance management in commercial high-rise buildings in Sri Lanka.

This study adopted a case study method. Three commercial high-rise buildings were selected to conduct the empirical study. An expert survey is also conducted to validate the findings.

The findings of the study revealed that out of the eight cardinal types of lean maintenance waste, six are rooted in the selected cases: (i) excessive preventive maintenance, (ii) waiting (maintenance resources, tools, procuring of additional supplies and documentation and permits), (iii) transportation due to centralised maintenance, (iv) poor inventory management, (v) poor information handling and (vi) poor utilisation of labour. Then the study revealed strategies to eradicate identified lean maintenance wastes.

The findings of this study can be used to guide maintenance practitioners in implementing lean maintenance in Sri Lankan commercial high-rise buildings. Furthermore, the proposed strategies can be directly applied to mitigate identified maintenance wastes.

This paper provides information on how high-rise commercial buildings in Sri Lanka can enhance their maintenance management by mitigating lean maintenance wastes.

Based on the weak seismic performance and low ductility of coupled shear walls, engineered cementitious composites (ECC) is utilized to strengthen it to solve the deformation problem in tall buildings more effectively and study its mechanical properties more deeply.

The properties of reinforced concrete coupled shear wall (RCCSW) and reinforced ECC coupled shear wall (RECSW) have been studied by numerical simulation, which is in good agreement with the experimental results. The reliability of the finite element model is verified. On this basis, a detailed parameter study is carried out, including the strength and reinforcement ratio of longitudinal rebar, the placement height of ECC in the wall limb and the position of ECC connecting beams. The study indexes include failure mode and the skeleton curve.

The results suggest that the bearing capacity of RECSW is significantly affected by the ratio of longitudinal rebar. When the ratio of longitudinal rebar increases from 0.47% to 3.35%, the bearing capacity of RECSW increases from 250 kN to 303 kN, an increase of 21%. The strength of longitudinal rebar has little influence on the bearing capacity of RECSW. When the strength of the longitudinal rebar increases, the bearing capacity of RECSW increases little. The failure mode of RECSW can be improved by lowering the casting height of the ECC beam in a certain range.

In this paper, ECC is used to strengthen the coupled shear wall, and the accuracy of the finite element model is verified from the failure mode and skeleton curve. On this basis, the casting height of the ECC casting wall limb, the strength and reinforcement ratio of longitudinal rebar and the position of the ECC beam are studied in detail.

This account becomes both a theoretical and a methodological exploration of walking with the law; as such the purpose of the paper is to demonstrate how we migh walk in order to attend to how the law makes the built environment possible, how it shapes and creates places to be lived in, visited and experienced and how the law manifests in human encounters and interactions in the everyday life of the city.

In this study, the authors combine a walking narrative approach with an open-ended interview to raise awareness of the law’s hidden presence in the urban environment. The authors explore the city of Sheffield, in Yorkshire, in the North of England, to learn about its past, regeneration and future development by combining the appreciation of the built environment, as experienced by the senses and movement, with a guided tour.

This study highlights the interconnectivity of law and place both objectively and subjectively: the authors discuss sensorial experiences of law, and also elaborate on the normativity of law, as manifested in the regulation and the making of urban places in Sheffield.

The originality lies in the combination of methods used to appreciate the manifestation of law in the built environment, comprising interview, autoethnographic elements and walking (multisensory experience).

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

When it comes to discovering the leaders of the future, how can hiring organizations build a more sensitive talent radar to pick up signals of early-stage talent? What do upcoming leaders need to do to appear on that radar? What kind of search strategy is needed to find the exceptional candidate? Based on dozens of interviews with talent development specialists, we present 11 characteristics that emerge as keys to success. We present a case that illustrates why executive search is high stakes-game of responsible positions, and examine why talent alone is no guarantee of success.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018) and in English (online) by the Amrop Partnership (2021) as “Destination Boardroom 2: The Talent Radar.”

Given the distinct and unique climates in these countries, research conducted in other parts of the world may not be directly applicable. Therefore, it is crucial to conduct research tailored to the specific climatic conditions of Australia and New Zealand to ensure accuracy and relevance.

Given population growth, urban expansions and predicted climate change, researchers should provide a deeper understanding of microclimatic conditions and outdoor thermal comfort in Australia and New Zealand. The study’s objectives can be classified into three categories: (1) to analyze previous research works on urban microclimate and outdoor thermal comfort in Australia and New Zealand; (2) to highlight the gaps in urban microclimate studies and (3) to provide a summary of recommendations for the neglected but critical aspects of urban microclimate.

The findings of this study indicate that, despite the various climate challenges in these countries, there has been limited investigation. According to the selected papers, Melbourne has the highest number of microclimatic studies among various cities. It is a significant area for past researchers to examine people’s thermal perceptions in residential areas during the summer through field measurements and surveys. An obvious gap in previous research is investigating the impacts of various urban contexts on microclimatic conditions through software simulations over the course of a year and considering the predicted future climate changes in these countries.

This paper aims to review existing studies in these countries, provide a foundation for future research, identify research gaps and highlight areas requiring further investigation.

Despite the quantity of collaborations, the vocational network of the housing production in Ankara during its first five years (1923–1928) remains dispersed. The aim of this study is to identify all the actors of housing production and their collaborations which shaped Ankara's urban development as the new capital city.

The study engages with the literature and archival documents to identify the actors of the housing production, i.e. architects, master-builders, public institutions, private companies, contractors and entrepreneurs, and their resultant vocational network in the housing production in Ankara during 1923–1928.

Due to different agendas, such as speculation, financial interests or patriotism, the construction industry in Ankara had become an arena where many paths intersected, forming an intertwined vocational network. The profession of contractor became popular, and local architects, engineers and even individuals of various other professions began to work as mediators for foreign companies and public institutions, which required support especially in large-scale projects.

The dispersed information revealed that the actors of the housing production remained mostly anonymous, or only the famous architects were commemorated; however, others could be found within the lines of the established literature on Ankara and/or in archival documents. This research not only focuses on “salient” actors but also highlights the “silent” actors of the housing production and prepares charts to clarify the vocational network in Ankara during its first five years to contribute to the future studies on Ankara and its housing.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.