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Point cloud compression (PCC) is a key enabler for various 3-D applications, owing to the universality of the point cloud format. Ideally, 3D point clouds endeavor to depict object/scene surfaces that are continuous. Practically, as a set…
Application of performance-based design (PBD) in earthquake geotechnical design codes has been gaining attention for the past decade. Strong vibrations (e.g., earthquake loading) may generate an uplift or a partial separation of shallow…
Model compression and acceleration are attracting increasing attentions due to the demand for embedded devices and mobile applications. Research on efficient convolutional neural networks (CNNs) aims at removing feature redundancy by…
The rapid progress on MgB2 superconductor since its discovery[1] has made this material a strong competitor to low and high temperature superconductors (HTS) for applications with a great potential to catch the niche market such as in…
The mechanical response of interpenetrating phase composites (IPCs) with stochastic spinodal topologies is investigated experimentally and numerically. Model polymeric systems are fabricated by Polyjet multi-material printing, with the…
When carbon dioxide (CO2) is injected into an aquifer or a depleted geological reservoir, its dissolution into solution results in acidification of the pore waters. As a consequence, the pore waters become more reactive, which leads to…
Currently, density-based clustering algorithms are widely applied because they can detect clusters with arbitrary shapes. However, they perform poorly in measuring global density, determining reasonable cluster centers or structures,…
Deep convolutional neural networks (CNNs) with a large number of parameters require intensive computational resources, and thus are hard to be deployed in resource-constrained platforms. Decomposition-based methods, therefore, have been…
Bone drilling is a universal surgical procedure commonly used for internal fracture fixation, implant placement, or reconstructive surgery in orthopedics and dentistry. The increased temperature during such treatment increases the risk of…
This paper investigates the optimization of 2D and 3D composite structures using machine learning (ML) techniques, focusing on fracture toughness and crack propagation in the Double Cantilever Beam (DCB) test. By exploring the intricate…
Equipment used for site investigation activities like drill rigs are typically large and heavy to provide sufficient reaction mass to overcome the soil's penetration resistance. The need for large and heavy equipment creates challenges for…
Resource-efficient and high-precision approximate synthesis of quantum circuits expressed in the Clifford+T gate set is vital for Fault-Tolerant quantum computing. Efficient optimal methods are known for single-qubit RZ unitaries, otherwise…
Computational homogenization is the gold standard for concurrent multi-scale simulations (e.g., FE2) in scale-bridging applications. Experimental and synthetic material microstructures are often represented by 3D image data. The…
Since its inception, Benders Decomposition (BD) has been successfully applied to a wide range of large-scale mixed-integer (linear) problems. The key element of BD is the derivation of Benders cuts, which are often not unique. In this…
Point clouds are a basic data type that is increasingly of interest as 3D content becomes more ubiquitous. Applications using point clouds include virtual, augmented, and mixed reality and autonomous driving. We propose a more efficient…
A major drawback of modern neural OpenIE systems and benchmarks is that they prioritize high coverage of information in extractions over compactness of their constituents. This severely limits the usefulness of OpenIE extractions in many…
Fibres of ultralong and aligned carbon nanotubes (CNT) have axial properties above reference engineering materials, proving to be exceptional materials for application in structural composites, energy storage and other devices. For CNT…
This article provides an overview of the modeling of the effective thermomechanical properties of the multifunctional carbon nanotube (CNT) reinforced hybrid composites for advanced structural applications. The novel constructional feature…
Deep learning is increasingly being used to perform machine vision tasks such as classification, object detection, and segmentation on 3D point cloud data. However, deep learning inference is computationally expensive. The limited…
The susceptibility to delamination is one of the main concerns in fiber reinforced polymer composites (FRPs). This work demonstrates improvements of 60% in Mode-I fracture toughness after integration of thin (~30 micron), continuous veils…