Journal of Computing in Civil Engineering
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EISSN:1943-5487|ISSN:0887-3801|Disc:The Journal of Computing in Civil Engineering serves as a resource to researchers, practitioners, and students on advances and innovative ideas in computing as applicable to the engineering profession. Many such ideas emerge from recent developments in computer science, information science, computer engineering, knowledge engineering, and other technical fields. Some examples are innovations in artificial intelligence, parallel processing, distributed computing, graphics and imaging, and information technology. The journal publishes research, implementation, and applications in cross-disciplinary areas including software, such as new programming languages, database-management systems, computer-aided design systems, and expert systems; hardware for robotics, bar coding, remote sensing, data mining, and knowledge acquisition; and strategic issues such as the management of computing resources, implementation strategies, and organizational impacts|Priority:6|Publisher:American Society of Civil Engineers|
Recent Submissions
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ANN-Powered Models for Predicting Shrinkage and Creep Properties of High-Performance Concrete Using Supplementary Cementitious Materials
(American Society of Civil Engineers, 2024)The prediction of the time-dependent behavior of high-performance concrete (HPC) structures is essential to evaluating their service life. This prediction relies on the shrinkage and creep properties of HPC. However, unlike ... -
Cost Estimation of Metro Construction Projects Using Interpretable Machine Learning
(American Society of Civil Engineers, 2024)The metro, renowned as an environmentally friendly mode of transportation due to its low energy consumption and minimal pollution, plays a crucial role in achieving sustainable urban growth. Due to the scarcity of information ... -
Style-Controlled Image Synthesis of Concrete Damages Based on Fusion of Convolutional Encoder and Attention-Enhanced Conditional Generative Adversarial Network
(American Society of Civil Engineers, 2024)Developing deep learning network models for computer vision applications in concrete damage detection is a challenging task due to the shortage of training images. To address this issue, this study proposes a novel ... -
Mapping Residential Occupancy: Understanding Sociodemographic Influences on Occupancy Patterns Using the American Time Use Survey
(American Society of Civil Engineers, 2024)Residential buildings in the US are substantial energy consumers, accounting for 39% of the country’s electricity usage and 22% of its total energy consumption. The dynamics of this consumption are intricately linked to ... -
An Intelligent Cloud-Based IoT-Enabled Multimodal Edge Sensing Device for Automated, Real-Time, Comprehensive, and Standardized Water Quality Monitoring and Assessment Process Using Multisensor Data Fusion Technologies
(American Society of Civil Engineers, 2024)Amid escalating global challenges such as population growth, pollution, and climate change, access to safe and clean water has emerged as a critical issue. It is estimated that there are 4 billion cases of water-related ... -
Novel Optical-Inspired Rain Forest for the Explainable Prediction of Geopolymer Concrete Compressive Strength
(American Society of Civil Engineers, 2024)Geopolymer concrete (GPC) is an extraordinary material for promoting sustainable development in the construction industry and reducing environmental risk. However, material properties, such as compressive strength, are ... -
Structural Material Condition Assessment through Human-in-the-Loop Incremental Semisupervised Learning from Hyperspectral Images
(American Society of Civil Engineers, 2024)Engineering materials in constructed systems in service exhibit complex patterns, including structural damage, environmental artifacts, and artificial anomalies. In recent years, machine vision methods have been extensively ... -
Smart Contract Generation and Visualization for Construction Business Process Collaboration and Automation: Upgraded Workflow Engine
(American Society of Civil Engineers, 2024)With the digital transformation of the construction industry, the need to improve construction business process collaboration and automation is increasing. However, as construction projects usually involve many stakeholders ... -
A Novel Approach for Advancing Asphalt Pavement Temperature and Flow Number Predictions Using Optical Microscope Algorithm–Least Square Moment Balanced Machine
(American Society of Civil Engineers, 2024)Asphalt pavement performance is crucial for the sustainable management of road infrastructure. However, achieving accurate predictions remains challenging due to the complex interactions among materials, environmental ... -
Automatic Pixel-Level Segmentation of Multiple Pavement Distresses and Surface Design Features with PDSNet II
(American Society of Civil Engineers, 2024)Effective distress detection and quantitative analysis play a crucial role in road maintenance and driving safety. The Pavement distress segmentation network (PDSNet) is designed to combine the pyramid scene parsing network ... -
Teleoperation-Driven and Keyframe-Based Generalizable Imitation Learning for Construction Robots
(American Society of Civil Engineers, 2024)The construction industry has long been plagued by low productivity and high injury and fatality rates. Robots have been envisioned to automate the construction process, thereby substantially improving construction ... -
A Method for Surveying Road Pavement Distress Based on Front-View Image Data Using a Lightweight Segmentation Approach
(American Society of Civil Engineers, 2024)The utilization of low-cost video data is becoming more prevalent in pavement surveys to meet the increasing demand for timely distress detection and repair. Semantic segmentation algorithms can effectively segment pavement ... -
An Efficient Explainable Convolutional Network with Visualization of Feature Maps for Enhanced Understanding of Building Facade Defects
(American Society of Civil Engineers, 2024)Over the past decade, extensive research has been conducted on employing deep learning techniques to detect visual defects in structural facades during inspection. Although these models have shown accuracy in identifying ... -
Digitization of Existing Buildings with Arbitrary Shaped Spaces from Point Clouds
(American Society of Civil Engineers, 2024)Digital twins for buildings can significantly reduce building operation costs. However, existing methods for constructing geometric digital twins fail to model the complex geometry of indoor environments. To address this ... -
Premapping of Dynamic Indoor Construction Sites Using Prior Construction Progress Video to Enhance UGV Path Planning
(American Society of Civil Engineers, 2024)Accurate mapping is crucial for the successful deployment of unmanned ground vehicles (UGVs) in navigation tasks. However, maps derived from as-designed models often lack realism and fail to reflect dynamic changes on ... -
Vision-Based Real-Time Posture Tracking for Multiple Construction Workers
(American Society of Civil Engineers, 2024)Tracking the postures of construction workers can provide precious information for safety management, occupational illness prevention, and productivity investigation. However, the posture data of construction workers is ... -
Robust Alignment of UGV Perspectives with BIM for Inspection in Indoor Environments
(American Society of Civil Engineers, 2024)Ensuring the alignment of perspectives between unmanned ground vehicles (UGVs) and Building Information Modeling (BIM) is crucial for the precise retrieval and analysis of BIM-stored information during inspection tasks. ... -
Explainable Image Captioning to Identify Ergonomic Problems and Solutions for Construction Workers
(American Society of Civil Engineers, 2024)The high occurrence of work-related musculoskeletal disorders (WMSDs) in construction remains a pressing concern, causing numerous nonfatal injuries. Preventing WMSDs necessitates the implementation of an ergonomic process, ... -
Cloud-Based Hierarchical Imitation Learning for Scalable Transfer of Construction Skills from Human Workers to Assisting Robots
(American Society of Civil Engineers, 2024)Assigning repetitive and physically demanding construction tasks to robots can alleviate human workers’ exposure to occupational injuries, which often result in significant downtime or premature retirement. However, the ... -
Instance-Based Clustering of Road Markings with Wear and Occlusion from Mobile Lidar Data
(American Society of Civil Engineers, 2024)Road markings are essential features to convey important information to various roadway users such as pedestrians, bicyclists, and motorists. Although mobile laser scanning (MLS) technology provides dense and spatially ...