Prefabricated construction (PC) has attracted wide spread attention as a model of sustainable development for the construction industry of the future. Although the PC has many advantages, it is still ...at an initial stage in China. Based on the current conditions in China, this study focuses on the interrelationships of factors affecting PC promotion. Firstly, through a comprehensive review of relevant literatures and expert recommendations, 5 factors were identified: policy factor, technical factor, management factor, market factor and cost factor. Next, the data were collected through a questionnaire survey, and the questionnaire data were processed using SPSS 24.0 and AMOS 22.0. The overall relationships of each factor were quantitatively analyzed with Structural Equation Modeling (SEM). The results show that the policy factor plays a dominant role, while the management factor and market factors are also significant. This study also provides decision makers with relevant information about the factors involved, which will be helpful in devising appropriate strategies for the wider adoption of PC.
In this study, a modified accelerated corrosion method based on the traditional galvanic method was adopted to generate non-uniform corrosion of reinforcement. The flexural performance of corroded RC ...beams was experimentally investigated, aiming to study the influence of longitudinal reinforcements corrosion induced by two different accelerated corrosion methods on the degradation of flexural capacity of RC beams. The corrosion-induced and load-induced cracking behaviors, as well as the degradation of flexural performance of beam specimens corroded by these two different methods were studied. The test results showed that the longitudinal reinforcements subjected to the modified accelerated corrosion method demonstrates a considerably higher circumferential and longitudinal non-uniformity, while the traditional accelerated corrosion method induces a rather uniform corrosion. For the corrosion-induced crack, the non-uniform reinforcement corrosion induced by the modified accelerated corrosion method was closer to the one after exposure to the natural environment. The non-uniformity of corrosion aggravates the propagation of both corrosion-induced and load-induced cracks, leading to the change of flexural failure mode. And the uniform corrosion induced by the traditional accelerated corrosion method underestimates the degradation of shear capacity of RC beam, especially in the cases of corrosion degree no less than 15%.
As vertical crowdfunding platforms (e.g., cultural and creative crowdfunding) are gradually gaining widespread attention, it is vital to explore the determinants specific to their success. For this ...reason, drawing on the signal theory (i.e., combining project cultural background, peer review valence, and face information disclosure), we develop an econometric model to examine the success determinants of cultural and creative crowdfunding (CCCF) projects. A data set with 2877 real CCCF projects obtained from Modian.com is used for analysis. The Natural Language Processing (NLP) approach is used to calculate the sentiment and information entropy of reviews in crowdfunding projects, and an open-source image processing library is used to identify face information. Moreover, an instrumental variable is considered to address endogeneity problems. The empirical results show that cultural background and peer review valence in CCCF projects positively influence crowdfunding success, while initiators' real face information disclosure negatively influences crowdfunding success. Furthermore, the information entropy of peer reviews negatively moderates the influence of peer review valence on crowdfunding success. This research provides a new perspective, i.e., latent features in CCCF, to explore success determinants. In addition, this study contributes to guiding the CCCF platforms in developing appropriate strategies and helps to improve the initiator's chances of successful fundraising.
•An econometric model is used to explore special success determinants of CCCF projects based on signal theory.•Natural language processing and computer vision techniques are applied to measure variables.•Cultural background, peer review valence, and initiators' face will affect the crowdfunding success.
Precast components manufacturer generally operates under limited production capacity and produces products of one order which may delay another. This paper develops a precast component order ...acceptance and scheduling model that aims to maximize the total profit in a stochastic multiple orders environment. In that model, the increasing of the overall profit of the precast component manufacturer is achieved by using a heuristic algorithm and a dynamic order acceptance heuristic. Results of numerical examples indicate the proposed model realizes the increasing total profit in most cases comparing to accept all of the orders. Besides, this study tested three order acceptance criteria and found that the profit-based criterion is to be more stable in terms of maximum total profit. This approach is anticipated to provide support to precast component manufacturers when faced with multiple orders in long-term production.
PurposeThe safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex ...construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.Design/methodology/approachThis model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.FindingsThe experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.Originality/valueThis study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.
Purpose
Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of ...reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.
Design/methodology/approach
The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.
Findings
The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.
Originality/value
The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.
The contradiction between the indoor environment and building energy consumption has been controversial. The design of building envelope involves many parameters such as window size and exterior wall ...material. These parameters have significant influence on building energy-saving design and indoor environment. In this paper, nondominant sorting genetic algorithm-II (NSGA-II) is utilized to calculate winter heat consumption, indoor total lighting energy consumption, and thermal comfort. The Pareto method is used to select the compromise solution and effective value of each building parameter. Different from other studies, we add more architectural design variables into the model calculation, which can bring architects more detailed energy-saving design content.
Although the increasing mobile technology applies in our daily lives, there remain questions that clearly illustrate the experience inspired by the mobile technology environment. It is theoretically ...and practically meaningful to systematically reveal how mobile technology generates users' virtual experience and, subsequently, the behavioral response. To fill the gaps, drawing on the Stimulus-Organism-Response model, this paper regards flow as the core experience based on the features of the mobile users' experience. The framework is that mobile technology will promote users' virtual experience, and in turn, affect their behavioral response. This study uses online survey data from 452 respondents. We employ the structural equation model based on the partial least squares method and further mediation analysis by the Sobel test to validate the research hypotheses. Our results show that the mobile technology environment has a significantly positive effect on users' purchase intention/return mediated by the virtual experience. However, the direct relationship between ubiquity and flow, as well as telepresence and intention to purchase/return, are not significant. Finally, a few theoretical and managerial contributions are also discussed.
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