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Construction Materials

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Real-time construction demolition waste detection using state-of-the-art deep learning methods; single-stage vs two-stage detectors.

Waste management (New York, N.Y.)
Central to the development of a successful waste sorting robot lies an accurate and fast object detection system. This study assesses the performance of the most representative deep-learning models for the real-time localisation and classification of...

The impact of thermal insulating materials in heat loss control in smart green buildings using experimental and swarm intelligent analysis.

Environmental science and pollution research international
The efficacy of saving energy standards depends on the ability to anticipate the heat loss of buildings. Environmentally friendly materials, also known as eco-friendly or sustainable materials, have a minimal negative impact on the environment throug...

Improved U-net network asphalt pavement crack detection method.

PloS one
Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow ...

Artificial neural network, machine learning modelling of compressive strength of recycled coarse aggregate based self-compacting concrete.

PloS one
This research study aims to understand the application of Artificial Neural Networks (ANNs) to forecast the Self-Compacting Recycled Coarse Aggregate Concrete (SCRCAC) compressive strength. From different literature, 602 available data sets from SCRC...

Study on design optimization of GFRP tubular column composite structure based on machine learning method.

PloS one
Circular reinforced concrete wound glass fiber reinforced polymer (GFRP) columns and reinforced concrete filled GFRP columns are extensively utilized in civil engineering practice. Various factors influence the performance of these two types of GFRP ...

Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild.

Journal of environmental management
The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting process...

Sensor-based characterization of construction and demolition waste at high occupancy densities using synthetic training data and deep learning.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Sensor-based monitoring of construction and demolition waste (CDW) streams plays an important role in recycling (RC). Extracted knowledge about the composition of a material stream helps identifying RC paths, optimizing processing plants and form the...

Predicting concrete strength early age using a combination of machine learning and electromechanical impedance with nano-enhanced sensors.

Environmental research
To ensure the structural integrity of concrete and prevent unanticipated fracturing, real-time monitoring of early-age concrete's strength development is essential, mainly through advanced techniques such as nano-enhanced sensors. The piezoelectric-b...

Deep learning-based prediction of compressive strength of eco-friendly geopolymer concrete.

Environmental science and pollution research international
The greenhouse gases cause global warming on Earth. The cement production industry is one of the largest sectors producing greenhouse gases. The geopolymer is produced with synthesized by the reaction of an alkaline solution and the waste materials s...