Deep Learning Perspectives on Efficient Image Matching in Natural Image Databases

With the proliferation of digital content, efficient image matching in natural image databases has become paramount. Traditional image matching techniques, while effective to a certain extent, face challenges in dealing with the high variability inherent in natural images. This research delves into the application of deep learning models, particularly Convolutional Neural Networks (CNNs), Siamese Networks, and Triplet Networks, to address these challenges. We introduce various techniques to enhance efficiency, such as data augmentation, transfer learning, dimensionality reduction, efficient sampling, and the amalgamation of traditional computer vision strategies with deep learning. Our experimental results, garnered from specific dataset, demonstrate significant improvements in image matching efficiency, as quantified by metrics like precision, recall, F1-Score, and matching time. The findings underscore the potential of deep learning as a transformative tool for natural image database matching, setting the stage for further research and optimization in this domain

Intrinsic Mesh Simplification

This paper presents a novel simplification method for removing vertices from an intrinsic triangulation corresponding to extrinsic vertices lying on near-developable (i.e., with limited Gaussian curvature) and general surfaces. We greedily process all intrinsic vertices with an absolute Gaussian curvature below a user selected threshold. For each vertex, we repeatedly perform local intrinsic edge flips until the vertex reaches the desired valence (three for internal vertices or two for boundary vertices) such that removal of the vertex and incident edges can be locally performed in the intrinsic triangulation. Each removed vertex's intrinsic location is tracked via (intrinsic) barycentric coordinates that are updated to reflect changes in the intrinsic triangulation. We demonstrate the robustness and effectiveness of our method on the Thingi10k dataset and analyze the effect of the curvature threshold on the solutions of PDEs

Coordinate Systems: Level Ascending Ontological Options

A major challenge faced in the deployment of collaborating unmanned vehicles is enabling the semantic interoperability of sensor data. One aspect of this, where there is significant opportunity for improvement, is characterizing the coordinate systems for sensed position data. We are involved in a proof of concept project that addresses this challenge through a foundational conceptual model using a constructional approach based upon the BORO Foundational Ontology. The model reveals the characteristics as sets of options for configuring the coordinate systems. This paper examines how these options involve, ontologically, ascending levels. It identifies two types of levels, the well-known type levels and the less well-known tuple/relation levels

From Micro- to Nano-porous Cellular Materials with Layered 2D Microstructure

A large body of work has been committed to studying the unique properties of 2D materials such as graphene, with advancements in both the material quality and scale of mechanical exfoliation and chemical vapour deposition (CVD) methods. These emergent 2D materials have recently been engineered as the cell walls in three-dimensional structures, but their superb material properties are yet to be fully realized in this new form. This thesis investigates the CVD processing of a range of catalytic templates to open new routes towards the controlled fabrication of graphitic foams and lattices. As part of a full feedback loop, mechanical characterization of these unique cellular materials was undertaken in order to examine their deformation and failure mechanisms, including capturing their behaviour in a new hierarchical model framework. These novel structures have the potential to combine the properties of structured porous materials, i.e. low density, high geometric surface area, permeability and mechanical stability, with the intrinsic properties of 2D materials such as enhanced electrical and thermal conductivity, high mechanical strength and stiffness as well as resistance to damage from extreme temperatures and chemical attack. Such high quality 2D-material based cellular structures have manifold potential applications in electrochemistry, catalysis and filtration. Herein, freestanding graphitic foams are fabricated across a range of relative densities, and their uniaxial compressive responses are measured to investigate the operative deformation and failure mechanisms that govern the mechanical response of such foams. For this purpose, a hierarchical micromechanical model is developed, which traces the deformation of the hollow cell struts to the axial stretching of the cell walls. The waviness of the multilayered graphitic wall increases the axial compliance of each cell wall, and it is established that axial straining within the cell wall occurs by interlayer shearing. Crucially, this mechanism demonstrates that the continuum properties of such foams are dictated by the weak out-of-plane shear properties of the layered cell wall material, leading to a large knockdown in the macroscopic mechanical properties of the foam. Ordered graphene gyroid lattices possessing nanoscale unit cell sizes are then fabricated and characterized through a combination of nanoindentation and a multi-scale finite element analysis (FEA) study. These structured nanolattices were found to be highly conductive and possessed a high degree of elastic recovery and strength owing to the structural efficiency afforded by the stretching-dominated cellular architecture. However, the nanoscale interlayer shearing deformation mechanism was again found to be active in the cell walls of these structures, attenuating the continuum response of the lattice. The hierarchical micromechanical model developed herein rationalizes why CVD-grown multilayer graphitic foams and lattices possess diminished continuum elastic moduli and yield strengths in comparison to the exemplary in-plane mechanical properties of 2D materials, presenting a first step towards the understanding of porous materials whose cell walls are comprised of emergent 2D materials. In addition, the direct shrinkage of commercial polymer foams and 3D printed templates is used herein to offer a very simple and low-cost method for reaching identically-shaped structures with sub-200 μm unit cell sizes. The conformal addition of different thicknesses of alumina is shown to control the level of isotropic shrinkage, reducing the shrinkage ratio from 125x to 4x after addition of 25 nm of alumina, while inducing a surface stress mismatch that drastically increases the surface roughness of the material. Furthermore, efficient graphitization was demonstrated through the use of an electrolessly deposited Nickel film, resulting in the formation of a conductive multilayer graphenic coating at temperatures below 1100°C. These processes present the flexible production of multifunctional cellular materials with sub-mm unit cells, tuneable size, roughness and conductivity. A final study investigates the preparation of a nascent 2D material, WS$_2$, through the use of a deconstructed metal organic chemical vapour deposition (MOCVD) process which allowed insight into the role of each process step. The catalytic effect of an Au substrate is unambiguously demonstrated, which allowed for a reduction in the precursor partial pressures required to nucleate and grow WS$_2$ by over an order of magnitude in comparison to competing methods. This enabled the efficient low-pressure growth of WS$_2$ films with low levels of carbon contamination. Furthermore, the reaction process developed herein exhibited a self-limiting monolayer growth behaviour with exposure cycles lasting just 10 minutes, a significant improvement over prior MOCVD processes requiring growth times in excess of 1 hour. These insights foster our understanding of the key underlying mechanisms of WS$_2$ growth for future integrated manufacturing of transition metal dichalcogenides (TMDCs) and other 2D materials.Funded by the EPSRC (EP/G037221/1) - Cambridge NanoScience through Engineering to Application Doctoral Training Centre: Assembly of Functional NanoMaterials and NanoDevices, EPSRC (EP/K016636/1) - CVD enabled Graphene Technology and Devices (GRAPHTED), ERC (279342) - In-situ metrology for the controlled growth and interfacing of nanomaterials and ERC (206409) - Multi-phase lattice materials

Taxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems

The Internet of Things (IoT) has transformed many aspects of modern manufacturing, from design to production to quality control. In particular, IoT and digital manufacturing technologies have substantially accelerated product development- cycles and manufacturers can now create products of a complexity and precision not heretofore possible. New threats to supply chain security have arisen from connecting machines to the Internet and introducing complex IoT-based systems controlling manufacturing processes. By attacking these IoT-based manufacturing systems and tampering with digital files, attackers can manipulate physical characteristics of parts and change the dimensions, shapes, or mechanical properties of the parts, which can result in parts that fail in the field. These defects increase manufacturing costs and allow silent problems to occur only under certain loads that can threaten safety and/or lives. To understand potential dangers and protect manufacturing system safety, this paper presents two taxonomies: one for classifying cyber-physical attacks against manufacturing processes and another for quality control measures for counteracting these attacks. We systematically identify and classify possible cyber-physical attacks and connect the attacks with variations in manufacturing processes and quality control measures. Our taxonomies also provide a scheme for linking emerging IoT-based manufacturing system vulnerabilities to possible attacks and quality control measures

Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis

UID/00667/2020 (UNIDEMI). J. P. Oliveira acknowledges funding by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020 Prahalada Rao acknowledges funding from the Department of Energy (DOE), Office of Science, under Grant number DE-SC0021136, and the National Science Foundation (NSF) [Grant numbers CMMI-1719388, CMMI-1920245, CMMI-1739696, CMMI-1752069, PFI-TT 2044710, ECCS 2020246] for funding his research program. This work espousing the concept of online process monitoring in WAAM was funded through the foregoing DOE Grant (Program Officer: Timothy Fitzsimmons), which partially supported the doctoral graduate work of Mr. Benjamin Bevans at University of Nebraska-Lincoln Benjamin, Aniruddha, and Ziyad Smoqi were further supported by the NSF grants CMMI 1752069 (CAREER) and ECCS 2020246. Detecting flaw formation in metal AM using in-situ sensing and graph theory-based algorithms was a major component of CMMI 1752069 (program office: Kevin Chou). Developing machine learning alogirthms for advanced manufacturing applications was the goal of ECCS 2020246 (Program officer: Donald Wunsch). The XCT work was performed at the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure under award no. ECCS: 2025298, and with support from the Nebraska Research Initiative through the Nebraska Center for Materials and Nanoscience and the Nanoengineering Research Core Facility at the University of Nebraska-Lincoln. The acquisition of the XCT scanner at University of Nebraska was funded through CMMI 1920245 (Program officer: Wendy Crone). Publisher Copyright: © 2022 The AuthorsThe goal of this work is to detect flaw formation in the wire-based directed energy deposition (W-DED) process using in-situ sensor data. The W-DED studied in this work is analogous to metal inert gas electric arc welding. The adoption of W-DED in industry is limited because the process is susceptible to stochastic and environmental disturbances that cause instabilities in the electric arc, eventually leading to flaw formation, such as porosity and suboptimal geometric integrity. Moreover, due to the large size of W-DED parts, it is difficult to detect flaws post-process using non-destructive techniques, such as X-ray computed tomography. Accordingly, the objective of this work is to detect flaw formation in W-DED parts using data acquired from an acoustic (sound) sensor installed near the electric arc. To realize this objective, we develop and apply a novel wavelet integrated graph theory approach. The approach extracts a single feature called graph Laplacian Fiedler number from the noise-contaminated acoustic sensor data, which is subsequently tracked in a statistical control chart. Using this approach, the onset of various types of flaws are detected with a false alarm rate less-than 2%. This work demonstrates the potential of using advanced data analytics for in-situ monitoring of W-DED.publishersversionpublishe

The STAR MAPS-based PiXeL detector

The PiXeL detector (PXL) for the Heavy Flavor Tracker (HFT) of the STAR experiment at RHIC is the first application of the state-of-the-art thin Monolithic Active Pixel Sensors (MAPS) technology in a collider environment. Custom built pixel sensors, their readout electronics and the detector mechanical structure are described in detail. Selected detector design aspects and production steps are presented. The detector operations during the three years of data taking (2014-2016) and the overall performance exceeding the design specifications are discussed in the conclusive sections of this paper

Investigating plasma modifications and gas-surface reactions of TiO2-based materials for photoconversion

2012 Fall.Includes bibliographical references.Plasmas offer added flexibility for chemists in creating materials with ideal properties. Normally unreactive precursors can be used to etch, deposit and modify surfaces. Plasma treatments of porous and compact TiO2 substrates were explored as a function of plasma precursor, substrate location in the plasma, applied rf power, and plasma pulsing parameters. Continuous wave O2 plasma treatments were found to reduce carbon content and increase oxygen content in the films. Experiments also reveal that Si was deposited throughout the mesoporous network and by pulsing the plasma, Si content and film damage could be eliminated. Nitrogen doping of TiO2 films (N:TiO2) was accomplished by pulsed plasmas containing a range of nitrogen precursors. N:TiO2 films were anatase-phased with up to 34% nitrogen content. Four different nitrogen binding environments were controlled and characterized. The produced N:TiO2 films displayed various colors and three possible mechanisms to explain the color changes are presented. Both O2 treated and N:TiO2 materials were tested in photocatalytic devices. Preliminary results from photocatalytic activities of plasma treated P25 TiO2 powders showed that nitrogen doping treatments hinder photocatalytic activity under UV light irradiation, but silicon deposition can improve it. N:TiO2 materials were tested in photovoltaic devices to reveal improved short-circuit current densities for some plasma-modified films. To understand the gas-phase and surface chemistry involved in producing the N:TiO2 films, NH and NH2 species in pulsed NH3 plasmas were explored by systematically varying peak plasma power and pulsing duty cycle. Results from these studies using gas phase spectroscopy techniques reveal interconnected trends of gas-phase densities and surface reactions. Gas-phase data from pulsed plasmas with two different types of plasma pulsing reveal diminished or increased densities at short pulses that are explained by plasma pulse initiation and afterglow effects. Overall this work reveals characteristics of the plasma systems explored, knowledge of the resulting materials, and control over plasma etching, deposition, and modification of TiO2 surfaces

Exploring general chemistry students' metacognitive monitoring on examinations

Includes bibliographical references.2016 Fall.To view the abstract, please see the full text of the document