Identification and information acquisition of high-value construction solid waste combined millimeter-wave radar and convolutional neural networks.

The accumulation of construction solid waste (CSW) leads to the waste of land resources and environmental pollution, becoming a significant social problem. Identifying the amount of high-value CSW is essential for assessing the value of accumulated CSW and formulating appropriate recycling strategies. With the development of machine learning technology, CSW recognition techniques combining image acquisition devices and convolutional neural networks have been widely applied.

Study of the Properties and Modification Mechanism of SBS-Modified Asphalt by Dry Process.

SBS (styrene-butadiene-styrene block copolymer) is a thermoplastic elastomer with properties most similar to rubber. SBS asphalt modifier is mainly composed of a styrene-butadiene-styrene block copolymer with a certain amount of additives and stabilizers. SBS-modified asphalt binder has always been the most commonly used pavement material both domestically and internationally.

Multi-Task Segmentation and Classification Network for Artery/Vein Classification in Retina Fundus.

Automatic classification of arteries and veins (A/V) in fundus images has gained considerable attention from researchers due to its potential to detect vascular abnormalities and facilitate the diagnosis of some systemic diseases. However, the variability in vessel structures and the marginal distinction between arteries and veins poses challenges to accurate A/V classification. This paper proposes a novel Multi-task Segmentation and Classification Network (MSC-Net) that utilizes the vessel features extracted by a specific module to improve A/V classification and alleviate the aforementioned limitations.

An Extension Network of Dendritic Neurons.

Deep learning (DL) has achieved breakthrough successes in various tasks, owing to its layer-by-layer information processing and sufficient model complexity. However, DL suffers from the issues of both redundant model complexity and low interpretability, which are mainly because of its oversimplified basic McCulloch-Pitts neuron unit. A widely recognized biologically plausible dendritic neuron model (DNM) has demonstrated its effectiveness in alleviating the aforementioned issues, but it can only solve binary classification tasks, which significantly limits its applicability.

Particle Swarm Optimization-Based Approach for Optic Disc Segmentation.

Fundus segmentation is an important step in the diagnosis of ophthalmic diseases, especially glaucoma. A modified particle swarm optimization algorithm for optic disc segmentation is proposed, considering the fact that the current public fundus datasets do not have enough images and are unevenly distributed. The particle swarm optimization algorithm has been proved to be a good tool to deal with various extreme value problems, which requires little data and does not require pre-training.

Quantifying Hole-Edge Crack of Bolt Joints by Using an Embedding Triangle Eddy Current Sensing Film.

Hole-edge crack quantification of bolt joints is critical for monitoring and estimating structural integrity of aircraft. The paper proposes a new triangle eddy current sensor array for the purpose of increasing the level of quantifying hole-edge crack parameters, especially, the crack angle. The new senor array consists of triangular coils instead of planar rectangular coils.

Improving Flame Retardancy of Epoxy Resin Nanocomposites by Carbon Nanotubes Grafted CuAl-Layered Double Hydroxide Hybrid.

To solve the issues of the poor dispersion performance of the inorganic flame retardant filler in epoxy resin (EP) matrix, the three-dimensional (3D) hybrid carbon nanotubes-copper aluminum (sodium dodecyl sulfate)-layered double hydroxide (CNTs-OLDH) is designed and synthesized by co-precipitation. The results indicate that the CNTs-OLDH hybrid with 3D-structure is successfully fabricated and well dispersed in EP matrix. The thermostability of EP/CNTs-OLDH nanocomposites is raised and the residue is obviously increased.

Reasonable thickness design of expressway pavement structures based on gray relation analysis of subgrade soil improvement.

During the design of pavement structures, determining a reasonable thickness for pavement layers is critical. When an expressway is to be built in an area with a poor soil foundation, a reasonable subgrade treatment will make the pavement more durable. However, determining the optimal thickness of subgrade treatment is a difficult task for designers.

Identification and Compensation Technique of Non-Uniform Temperature Field for Lamb Wave-and Multiple Sensors-Based Damage Detection.

Lamb wave-based damage detection for large-scale composites is one of the most prosperous structural health monitoring technologies for aircraft structures. However, the temperature has a significant effect on the amplitude and phase of the Lamb wave signal so that temperature compensation is always the focus problem. Especially, it is difficult to identify the damage in the aircraft structures when the temperature is not uniform.

Analysis of Adhesive Characteristics of Asphalt Based on Atomic Force Microscopy and Molecular Dynamics Simulation.

Asphalt binder is a very important building material in infrastructure construction; it is commonly mixed with mineral aggregate and used to produce asphalt concrete. Owing to the large differences in physical and chemical properties between asphalt and aggregate, adhesive bonds play an important role in determining the performance of asphalt concrete. Although many types of adhesive bonding mechanisms have been proposed to explain the interaction forces between asphalt binder and mineral aggregate, few have been confirmed and characterized.

Modelling and laboratory studies on the adhesion fatigue performance for thin-film asphalt and aggregate system.

Adhesion between asphalt and aggregate plays an important role in the performance of asphalt mixtures. A low-frequency adhesion fatigue test was proposed in this paper to study the effect of environment on the asphalt-aggregate adhesion system. The stress-based fatigue model had been utilized to describe the fatigue behavior of thin-film asphalt and aggregate system.