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This paper aims to propose a generative design method combined with meta-heuristic algorithm for automating and optimizing the floor layout of modular buildings using typical standardized module units, which are the room module, the corridor module and the stair module.

The integrated framework involves the generative design method and optimization for modular construction. The generative rules are provided by geometric relationships and functionalities of the module units. An evaluation function of the generated floor plans is also presented by the combination of project cost and cost penalties for the geometric features. The multi-population genetic algorithm (MPGA) method is provided for the optimization of the combination of costs.

The proposed MPGA method is demonstrated fast and efficient at discovering the globally optimal solution. The results indicate that when the unit price of modules is high, the transportation distance is long, or the land cost is high, the layout cost, which related to the symmetry, the compactness and the energy is tend to be lower, making the optimal layout economical.

This paper presented an integrated framework of generative floor layout and optimization for modular construction by using typical module units. It fulfills the need for automated layout generation with repetitive units and corresponding assessment during the early design stage.

This paper aims to investigate the effect of partially blocking the cathode channel with the stair arrangement of obstacles on the performance of a proton exchange membrane fuel cell.

A numerical study is conducted by developing a three-dimensional computational fluid dynamics model.

As the angle of the stair arrangement increases, the performance of the fuel cell is reduced and the pressure drop is decreased. The use of four stair obstacles with an angle of 0.17° leads to higher power density and a lower pressure drop compared to the case with three rectangular obstacles of the same size and maximum height. The use of four stair obstacles with an angle of 0.34° results in higher power density and lower pressure drop compared to the case with two rectangular obstacles of the same size and maximum height.

Using the stair arrangement of obstacles as an innovation of the present work, in addition to improving the fuel cell’s performance, creates a lower pressure drop than the simple arrangement of obstacles.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study aims to identify the irritating aspects in the mall environment that impact shoppers with disability and explore the opportunities to design inclusive mall environments.

A mixed-methods design was used in which data collected using a survey (n = 1,434 shoppers with and without disability) were analyzed by structural equation modeling (SEM) and repeated-measures two-way ANOVA. In addition, qualitative data were obtained from critical incident technique (CIT) stories (n = 521) from shoppers with and without disability.

Mall environmental irritants evoke feelings of irritation that mediate the impacts of “inconvenient ambient conditions,” “the annoying socialscape” and “overwhelming design and atmospherics” on decreased mall-visit frequency. Compared with shoppers without disability, shoppers with disability suffer more from these irritating aspects of the mall environment, as evidenced by significantly greater high-activation unpleasant emotions. The “poor access and accessibility” category of irritants mainly affects the mall experiences of shoppers with disability.

Based on the findings, this study offers spatial-, temporal-, social-, material- and virtual-oriented recommendations for the design of inclusive retail spaces. The authors suggest that people with disability have a unique “lived experience” perspective on retail environments and that solutions should be co-created based on ongoing consultations with shoppers and employees with disability.

To the best of the authors’ knowledge, this study offers the first systematic, comprehensive comparison of the impact of environmental irritants on shoppers with and without disability and extends the literature on irritating aspects of retail environments from individual stores to malls.

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

The purpose of this paper is to identify the factor structure of safety culture construct among engineering students at university context and to examine the measurement invariance of this instrument across different socio-demographic groups in a sample of engineering students in the United Arab Emirates (UAE).

An exploratory online questionnaire was completed by 770 undergraduate and postgraduate engineering students across the UAE. Data were analyzed using a diversified multi-group and a robust and sophisticated cross-validation testing strategy. Confirmatory factor analysis (CFA) was used to test factor structures identified in previous studies. Multi-group invariance testing was conducted to determine the extent to which factor structure is comparable across groups (i.e. gender, educational and experiential background).

Three-factor model was preferred for its parsimony. The results showed that the level of safety awareness and attitude is relatively satisfactory, whereas safety behaviour is inadequate. No significant difference was showed in multi-group invariance between demographic groups.

This research is a cross-sectional study and limited to the views of engineering students (informal group). The study would benefit from both informal and formal groups in assessing safety culture at university for a robust empirical evidence. The research highlights relevant implications for policy and program development, by pointing to the need to promote safety culture and mitigate safety-related accidents among engineering students.

This paper offers insight into benefit of understanding the level of safety culture among engineering students and extend knowledge of informal group involvement in safety-related accidents at university level.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to analyse a new model to assess the sustainable behaviours, sustainable attitudes and sustainable knowledge on sport practitioners.

This paper employs a scale of 44 items divided into three different dimensions to analyse the knowledge, attitudes and behaviours towards sustainable development on 227 sport participants.

Through this study the authors have been able to obtain a reliable scale that allows us to analyse and the knowledge, attitudes and sustainable behaviours of physical and sports education practitioners.

Both psychometric properties of the initial scale and the differences between studies contexts may affect the results of the present analysis. Therefore, new studies are needed in order to analyse how sport physical activities influence sustainable behaviours among physical activity and sport practitioners.

In this work the authors present a valid and reliable tool for the study of the environmental knowledge, attitudes and behaviours of physical activity and sport practitioners.

Regarding the importance of sport in relation to sustainable development, this work is the first to adapt a scale to the context of practitioners of physical activity and sport in order to improve the understanding of how physical activity and sport affect sustainable behaviours, serving as a starting point for future research in sustainable development sports field.

In most developing countries, the delivery of construction project is still characterised by inefficiencies resulting from the use of outdated methods and techniques, which retards project performance. Hence, the call for the implementation of innovative technologies such as humanoids in the execution of construction projects as it has been proven to be very effective in other sectors while improving productivity and quality of work. Consequently, this study looks at how humanoids can be used in the construction industry and what benefits they can bring.

The study employed a quantitative approach underpinned in post-positivist philosophical view using questionnaire as the instrument for data collection. The target respondents were construction professionals, and purposive sampling was used, while a response rate of 62.5% was gotten. The methods of data analysis were mean item score, standard deviation and one-sample t-test.

The findings revealed that humanoids can be used in progress tracking, auto-documentation and inspection and surveillance of tasks in construction activities. Also, the most important benefits of using humanoids in construction work were found to be shorter delivery times, fewer injuries and more accurate work.

The outcome of the study gives professionals and relevant stakeholders in construction and other interested parties' information about the areas where humanoids can be used and their benefits in construction.

The novelty of this study is that it is a pioneering study in South Africa on humanoids' usage in the construction industry. Also, it expands the existing borderline of the conservation of construction digitalisation for enhanced project execution.

This study aims to create a more humane and responsible workplace, individuals’ gratitude and meaningfulness seem of utmost importance. This study is an effort to understand the role of gratitude intent of potential managers.

This study examines the psychological characteristic of business students in India. The researchers surveyed 333 Indian students as future managers. The collected data has been analysed with the Smart PLS 3 version to assess the formative-reflective scale by comparing model fit, measurement model and structural modelling.

The results establish that gratitude significantly affects the life satisfaction of future managers. Findings also show that materialism is negatively related to life satisfaction and meaningfulness. The importance–performance map analysis finding suggests that meaningfulness in life is a potential indicator of life satisfaction for the population studied.

Due to the limited research available on the psychological underpinnings in the Indian context, there is a massive value in examining how materialism and gratitude concurrently and distinctively predict meaning in life and the life satisfaction of future managers. This paper gives a formative explanation of the model consisted gratitude, materialism and meaningfulness in life on the life satisfaction of future managers. This study establishes the importance of meaningfulness of life in attaining life satisfaction for young managers.