Faculty of Design and Creative Technologies (Te Ara Auaha)

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https://hdl.handle.net/10292/10758
The Faculty of Design and Creative Technologies (Te Ara Auaha) is comprised of four school; Colab, the School of Art and Design, the School of Communication Studies and the School of Engineering, Computer and Mathematical Sciences. It also has Institutes, Centres and Labs across the Arts and Sciences in a mix that blends the traditional and the new, praxis and theory.

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Browsing Faculty of Design and Creative Technologies (Te Ara Auaha) by Subject "0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics"

Now showing 1 - 5 of 5
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    A Highly Stretchable Strain-based Sensing Sheet for the Integrated Structural Health Monitoring
    (IOP Publishing, 2024-06-28) Zhang;, Hui; Beskhyroun, Sherif
    In this study, a flexible strain sensing system that can be applied to full-scale reinforced concrete frame structures is presented. In order to fulfil the criteria for strain detection that are posed by various structural components, the flexible strain gauge is offered in two distinct configurations: one full bridge and one double half bridge. A strain configuration selector is built on the basis of this information. The selector is designed to enable the system to flexibly switch strain modes for measuring axial or bending strain without adjusting the installation location of strain sensors. The first section of this study focuses mostly on elaborating on the methodology behind the development of a flexible strain system. This method was primarily designed with the aim of detecting the abnormalities in the strain field that are brought on by structural damage in order to accomplish the goal of local detection. The creation of a strain configuration selector also enables the conversion between two different strain measures whenever it is necessary without requiring the sensor installation to be moved to a new position, which helps to significantly reduce the amount of cost associated with sensor deployment. The performance of the flexible strain sensing system as well as its sensitivity were evaluated by doing the cyclic load testing on a full-scale RC frame. Both half-bridge and full-bridge strain gauges are installed in the critical components, such as beams and columns. In addition, 14 linear variable displacement transducers (LVDTS) were placed on the RC frame in order to monitor variations in displacement and deformation. The findings of the experiments indicate that the flexible strain sensor exhibits a high degree of sensitivity, and it is therefore suitable for integration into a structural health monitoring (SHM) system for the purpose of tracing the strain caused by localised structural damage. Additionally, it is able to monitor the strain trend on the complete scale of the frame model. In future work, the flexible strain system will be modified and enhanced by using wireless technology for data transmission in order to build a wirelessly integrated structural health monitoring (SHM) system.
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    A Linear Relation between the Color Stretch sBV and the Rising Color Slope s0*(B−V) of Type Ia Supernovae
    (American Astronomical Society, 2023-04-05) Chen, Ping; Dong, Subo; Ashall, Chris; Benetti, S; Bersier, D; Bose, S; Brimacombe, Joseph; Brink, Thomas G; Buckley, David AH; Cappellaro, Enrico; Christie, Grant W; Elias-Rosa, N; Filippenko, Alexei V; Gromadzki, Mariusz; Holoien, Thomas W-S; Hu, Shaoming; Kochanek, CS; Koff, Robert; Kollmeier, Juna A; Lundqvist, P; Mattila, S; Milne, Peter A; Muñoz, JA; Mutel, Robert; Natusch, Tim; Nicolas, Joel; Pastorello, A; Prentice, Simon; Prieto, JL; Roth, Tyler; Shappee, BJ; Stone, Geoffrey; Stanek, KZ; Stritzinger, MD; Thompson, Todd A; Tomasella, Lina; Villanueva, Steven
    Using data from the Complete Nearby (redshift zhost < 0.02) sample of Type Ia Supernovae (CNIa0.02), we find a linear relation between two parameters derived from the B − V color curves of Type Ia supernovae: the color stretch sBV and the rising color slope ${s}_{0}^{* }(B-V)$ after the peak, and this relation applies to the full range of sBV. The sBV parameter is known to be tightly correlated with the peak luminosity, especially for fast decliners (dim Type Ia supernovae), and the luminosity correlation with sBV is markedly better than with the classic light-curve width parameters such as Δm15(B). Thus, our new linear relation can be used to infer peak luminosity from ${s}_{0}^{* }$. Unlike sBV (or Δm15(B)), the measurement of ${s}_{0}^{* }(B-V)$ does not rely on a well-determined time of light-curve peak or color maximum, making it less demanding on the light-curve coverage than past approaches.
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    Anomaly Detection in Text Data Sets Using Character-Level Representation
    (Institute of Physics (IoP), 2021-04-28) Mohaghegh, Mahsa; Abdurakhmanov, Amantay
    This paper proposes a character-level representation of unsupervised text data sets for anomaly detection problems. An empirical examination of the character-level text representation was conducted to demonstrate the ability to separate outlying and normal records using an ensemble of multiple classic numerical anomaly classifiers. Experimental results obtained on two different data sets confirmed the applicability of the developed unsupervised model to detect outlying instances in various real-world scenarios, providing the opportunity to quickly assess a large amount of textual data in terms of information consistency and conformity without knowledge of the data content itself.
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    Automated Biometric Identification using Dorsal Hand Images and Convolutional Neural Networks
    (Institute of Physics (IoP), 2021-04-01) Mohaghegh, Mahsa; Ash, Payne
    The identification of perpetrators, present in Child Sexual Abuse Imagery (CSAI), is a significant challenge due to the use of anonymisation techniques that mask their identities. Consequently, researchers have investigated the use of uncommon biometric identifiers such as knuckle patterns, palmprints and the dorsal side of the hand. This research proposes a Convolutional Neural Network (CNN) based, fully automated approach to biometric identification using dorsal hand images. The identification performance of three different CNN architectures, AlexNet, ResNet50 and ResNet152, is experimentally determined against two similar datasets, the 11k Hands and IITD dorsal hand databases. A transfer learning approach is used and the final output layers of the CNNs are modified to match the number of classes present in the datasets. The results showed that ResNet CNNs achieved identification accuracies greater than 99.9% on both datasets, whereas the AlexNet CNN achieved between 80.1% and 93.7%. These results demonstrate that it is feasible to use deep, off-the-shelf CNNs, such as ResNets, for automated biometric identification using dorsal hand images. This highlights the potential of using dorsal hand images to identify perpetrators of child sexual abuse from CSAI.
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    Inverse MultiView. II. Microarcsecond Trigonometric Parallaxes for Southern Hemisphere 6.7GHz Methanol Masers G232.62+00.99 and G323.74–00.26
    (American Astronomical Society, 2023-07-28) Hyland, LJ; Reid, MJ; Orosz, G; Ellingsen, SP; Weston, SD; Kumar, J; Dodson, R; Rioja, MJ; Hankey, WJ; Yates-Jones, PM; Natusch, T; Gulyaev, S; Menten, KM; Brunthaler, A
    We present the first results from the Southern Hemisphere Parallax Interferometric Radio Astrometry Legacy Survey: 10 μas accurate parallaxes and proper motions for two Southern Hemisphere 6.7 GHz methanol masers obtained using the inverse MultiView calibration method. Using an array of radio telescopes in Australia and New Zealand, we measured trigonometric parallaxes and proper motions for the masers associated with the star formation region G232.62+00.99 of π = 0.610 ± 0.011 mas, μx = −2.266 ± 0.021 mas yr−1, and μy = 2.249 ± 0.049 mas yr−1, which implies its distance to be d = 1.637 ± 0.029 kpc. These measurements represent an improvement in accuracy by more than a factor of 3 over the previous measurements obtained through Very Long Baseline Array observations of the 12 GHz methanol masers associated with this region. We also measure the trigonometric parallax and proper motion for G323.74–00.26 as π = 0.364 ± 0.009 mas, μx = −3.239 ± 0.025 mas yr−1, and μy = − 3.976 ± 0.039 mas yr−1, which implies a distance of d = 2.747 ± 0.068 kpc. These are the most accurate measurements of trigonometric parallax obtained for 6.7 GHz class II methanol masers to date. We confirm that G232.62+00.99 is in the Local Arm and find that G323.74–00.26 is in the Scutum–Centaurus arm. We also investigate the structure and internal dynamics of both masers.
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