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This paper aims to elaborate on the characteristics of vernacular architecture, particularly the architecture of the Turkish eastern Black Sea region, through a case study in the area; and to attract the attention of architects and researchers on the unique characters of the region. Another aim of the paper is to examine the contribution of vernacular architecture to sustainability through its design methods and principles, which have been developed throughout centuries.

This paper presents a single case study on the architecture of the Turkish eastern Black Sea region through 14 unique samples from Senoz (Büyükdere) Valley. The case study is preceded by theoretical research on vernacular architecture, its characteristics and its contribution to sustainable architecture.

The case study carried out in the Senoz Valley revealed that the region's vernacular architecture is still living. However, it has lost its importance in the past. Outcomes of the case study indicate that the unique character of the architecture in the valley needs to be protected and sustained, so that future generations can also benefit from its special design features.

Senoz Valley is a settlement located near the city of Rize in the eastern Black Sea region of Turkey. Vernacular architecture reflects the characteristics of the region and contains unique features in construction and planning. According to these special features, the architecture of Senoz valley deserves a place in the literature of vernacular architecture.

While the COVID-19 outbreak affects all aspects of life in the world, there is also a global impact in the field of education. Within the scope of the measures to control the epidemic, distance education was started shortly after the starting of the spring semester in all primary and secondary schools and universities. In this process, architectural design courses, which are one of the most fundamental courses of architectural education, started to be held in online studios. The purpose of this paper is to investigate the evaluations of architecture students about the online design studio courses carried out during the COVID-19 outbreak.

This research used a qualitative approach to evaluate the ideas of first, second, third and fourth grade students of architectural design studios in the host university. A questionnaire was directed to students in order to see their opinions about the online design studio education.

Results shows that students think the most prominent benefit of online studios appears in the use of digital tools. Another important result is that if they are equipped with the necessary tools and given the chance to realize themselves, students can work efficiently even in the distance education process.

This study is important in terms of learning the expectations of students from the online process and to identify important issues that should be considered for the next semesters. In addition, this study will serve as a basis for comparative evaluation of architectural education during and after the epidemic. In this context, the study will shed light on future academic research.

Sustainability, especially in terms of development and growth, has been in the agenda of the world community for several decades. However, apparently not all the aspects of sustainability are given equal importance. Ecologic and economic components of sustainability have been in the focal point of many theoretical and practical works, as the social aspect has been mostly left out of emphasis. The purpose of this paper is to examine the social aspects of sustainability and its relation to architecture, with respect to the strong connection between the society and the built environment.

The core of the paper consists of a case study conducted at a design studio course for third-year architecture students whereas the outcomes of the student works on the design problem are evaluated as examples for design approaches to reflect the effects of the built environment on social sustainability. The case study is supported with a literature review and examination of existing approaches to similar subjects regarding social sustainability.

The findings resulted in a better understanding of social sustainability in architectural education which is reflected on the built environment through several architectural strategies.

This paper contributes to the literature by providing a holistic understanding of sustainability including its social aspects and creating an awareness for the importance of social sustainability in architectural education.

The existence of retail spaces lies far back in history. However, retail design as an academic field of work is relatively recent and available for development. The common points and differences between commercial spaces and retail spaces, as well as the relationship between private and public spaces, require academic attention from a retail perspective. The purpose of this paper is to contribute to the academic knowledge on retail design by interpreting retail spaces according to their relationship with their surroundings and their way of defining borders.

The focal point of the paper lies on a case study based on built examples of retail spaces in Turkey. An actual perspective, along with the historical background of retail design, provides the theoretical framework of the study, as the term “border” is being interpreted according to encountered restrictions and intentions throughout the retail design process.

The case study conducted in the scope of this paper has shown that borders are an important component in retail design and they are affected by various factors like the limitations of the surroundings and atmospheric tools such as colours, lighting, sound or scent.

Although there are existing studies on retail design from various perspectives, the interpretation of retail spaces in relationship with their borders is missing in academic literature. This paper provides a definition of borders in retail design including the elements that describe them and the knowledge of borders according to different corporate tendencies.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on architectural education (AE) was investigated, and a framework was proposed to reduce the impacts' negative consequences.

Systematic literature review, bibliometric and content analyses were combined to gain an in-depth understanding of the effects of the pandemic on AE and projections for its future. Relevant documents were extracted from the Web of Science (WoS) database. Bibliometric connections in the context of AE and COVID-19 pandemic were explored using text-mining and content analysis was performed.

The challenges, development tendencies and collaboration networks in AE during the pandemic were quantitatively and qualitatively analyzed. The most influential articles, journals, authors and countries/regions were highlighted using a bibliometric analysis. The analysis of keyword tendencies and clusters indicates that new concepts have emerged in AE research during the pandemic involving online, in-person and hybrid education. Using content analysis of 57 subtopics, 39 (18) were categorized as having negative (positive) effects. A comprehensive mitigation framework was designed to reduce the impact of the pandemic on AE.

The study findings can enable practitioners to construct effective solutions to COVID-19- and other disaster-related problems regarding AE. The implications, obstacles and mitigation framework presented can help identify gaps in the literature and guide further research.

This paper presents the first bibliometric and content analysis of AE and COVID-19 pandemic-related studies published from January 2020 to June 2022 to highlight several research directions and academic development within the field.

Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.

This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.

The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

During the past several years, research and studies in the field of solar energy have been continuously increased. One of the substantial applications of solar energy is related to industrial utilization for the drying process by efficient heat transfer methods. This study aims to upgrade the overall performance of an indirect solar dryer using a solar absorber extension tube (SET) equipped with ball-type turbulators.

In this work, three various SETs including hollow (SET Type 1), 6-balls (SET Type 2) and 10-balls (SET Type 3), have been simulated using Fluent software to evaluate heat transfer characteristics and flow structure along the air passage. Then, the modified solar drying system has been manufactured and tested at different configurations.

The findings indicated that adding a SET improved the performance notably. According to the results, using turbulators in the tube has a positive effect on heat transfer. The highest overall thermal efficiency was found in the range of 51.47%–64.71% for the system with SET Type 3. The maximum efficiency increment of the system was found as 19% with the use of SET. Also, the average specific moisture extraction rate, which is a significant factor to survey the effectiveness of the dehumidification system was found between 0.20 and 0.38 kg kWh⁻¹.

In the present study, a novel SET has been developed to upgrade the performance of the solar dehumidifier. This new approach makes it possible to improve both thermal and drying performances.

This study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.

A thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.

The following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.

The findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.

There are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.

The current study examined employment rates and predictors of employment among Syrian refugees currently living in Lebanon and Jordan. This paper argues that men and women refugees have different experiences seeking out employment after resettlement due to patriarchal structures and attitudes toward women that are present in the Arab Middle East. The goals of this paper were a) to examine employment rates among Syrian refugees, b) to examine predictors of employment among male and female refugees, and c) to examine refugee status as a moderator of the relationship between attitudes toward women and employment status.

Nationally representative data from the Arab Barometer on 600 refugees and 1400 native-born individuals living in Lebanon and Jordan from 2016–2017 were used.

Native-born individuals living in Lebanon and Jordan were 2.16 times more likely to be employed than refugees. Men living in Lebanon and Jordan were 7.83 times more likely to be employed than women. Finally, refugee status moderated the relationship between attitudes toward women's rights and roles and employment. Among native-born women, a positive attitude toward women's rights and roles predicted employment status, whereas this positive relationship was not found for women refugees. Among refugee men, a positive attitude toward women's rights and roles was linked to a lower likelihood of holding a job.

These findings suggest that agencies supporting refugees should communicate realistic expectations about employment during resettlement and should address the challenges that women refugees face when seeking employment.

This study is the first study to identify attitudes toward women's rights and roles as a predictor of employment among refugee populations and highlights the unique struggles that refugee women face.