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38th Technical Conference of the American Society for Composites, ASC 2023

作者： Jain, Sudhir Li, Carina Xiaochen Vuong, Daniel McGllick, Matthew Saifaee, Saeed Furtado, Carolina Kopp, Reed Joseph, Joshua Adjodah, Dhaval Rosini, Sebastian Sinclair, Ian Spearing, S. Mark Wardle, Brian L. Integrated Design and Management Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States MIT Media Lab Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical Engineering University of Southampton SouthamptonSO17 1BJ United Kingdom Departments of Aeronautics and Astronautics and Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States

ISBN: (纸本)9781605956916

The heterogeneity of the microstructure and the anisotropy of the mechanical properties of carbon fiber reinforced polymer composites (CFRP) are associated with complex damage mechanisms that make failure prediction highly challenging. Typical damage mechanisms for CFRP include: (i) interlaminar cracking (delamination), (ii) matrix cracking, and (iii) fiber breakage. X-ray computed tomography (CT) has been utilized recently to identify the complex damage in progressive failure of CFRP in 3D and 4D (3D spatial and 1D temporal). However, these scans contain a large amount of data (≈10 GB/mm3), which makes it challenging to extract mechanistic insights in a reasonable time frame. In previous work, we presented the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale matrix damage in CFRP. The trained CNN segments complex and sparse composite matrix damage mechanism to ≈ 99.99% agreement, with nearly 100% of human time eliminated, providing higher accuracy compared to human segmentation. In this work, we developed CNN-based method for the automated segmentation of fiber breaks using synchrotron radiation-based CT (SRCT) scans that have been human-labeled. The model employed a U-Net full CNN as the high-level encoder (feature extraction)-decoder (feature localization) structure, and VGG16 as the deep CNN backbone via the publicly available Segmentation Models GitHub repository. An unbiased evaluation was performed comparing the machine vs. the human-labeled ground truth. Finally, active learning was presented for the machine-assisted relabeling of datasets containing fiber breaks. The deep learning-based automated segmentation method demonstrated accurate identification (> 90%) of fiber breakage for CFRP. © 2023 by DEStech Publications, Inc. and American Society for Composites. All rights reserved.

关键词： Complex networks

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Our Seventh IMS Microwave Week 3MT Competition [IMS2023]

Our Seventh IMS Microwave Week 3MT Competition [IMS2023]

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作者： Hester, Jimmy G.D. Eid, Aline Bandler, John W. Kiley, Erin M. Tajik, Daniel Atheraxon AtlantaGA30308 United States Media Lab Massachusetts Institute of Technology CambridgeMA02139 United States McMaster University and Bandler Corporation HamiltonONL8S 4K1 Canada Massachusetts College of Liberal Arts North AdamsMA01247 United States Department of Electrical and Computer Engineering McMaster University HamiltonONL8S 4K1 Canada

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Spherical-Dynamic Time Warping - a New Method for Similarity-Based Remaining Useful Life Prediction

SSRN

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SSRN 2023年

作者： Li, Xiaochuan Yang, Yingjie Lin, Tianran Mba, David School of Electrical Engineering and Automation Hefei University of Technology Hefei China School of Computer Engineering and Media De Montfort University LeicesterLE1 9BH United Kingdom Faculty of Mechanical and Automotive Engineering Qingdao University of Technology Qingdao China Creative Computing Institute University of the Arts London London United Kingdom

Machinery prognostics and health management (PHM) plays a key role in the reliable and efficient operation of industrial processes. With the emerging big data era, data-driven prognostic methods which avoid considering complicated system models have attracted growing research interest. Among many data-driven models, similarity-based prediction methods have been popular due to their strong interpretability and relatively simple implementation process. Nevertheless, when quantifying the similarity between two trajectories, most existing works neglect the nonlinearity of fault evolution and degradation alignments with timing difference, which may not be sufficient to retrieve the most suitable trajectories for remaining useful life (RUL) prediction. To overcome these limitations, a Spherical-Dynamic Time Warping (Spherical-DTW) algorithm is put forward to find an optimal match between the test and training trajectories at the retrieval step. Dynamic Time Warping allows degradation alignments with timing difference through stretching or compressing the trajectories with regard to time, thereby the data in similar degradation levels can be well aligned across different units. Moreover, a newly defined nonlinear Spherical distance method is introduced and incorporated into the retrieval process to account for the nonlinearity of the damage propagation process. The significance of this study is that the newly proposed Spherical-DTW algorithm goes one step further to consider the nonlinearity of fault evolutions and allow degradation pattern alignments with timing difference when performing similarity-based prognostics. Two run-to-failure cases, involving a real-world industrial compressor failure case and a gas turbine engine failure dataset, are investigated to demonstrate the effectiveness and superiority of the proposed algorithm. © 2023, The Authors. All rights reserved.

关键词： Condition monitoring

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Manipulating quantum impurity spins via dynamical modes of nanomagnets

arXiv

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arXiv 2022年

作者： Rustagi, Avinash Kajale, Shivam Upadhyaya, Pramey Elmore Family School of Electrical And Computer Engineering Purdue University West LafayetteIN47907 United States Department of Electrical Engineering Indian Institute of Technology Maharashtra Bombay400076 India Media Arts And Sciences Massachusetts Institute of Technology CambridgeMA02142 United States

Quantum impurity (QI) spins offer promising information processing and sensing applications by harnessing up to room-temperature quantum coherence. Challenged by the requirement of designing local coherent drives and improving sensitivity to various signals for such applications, the search of hybrid systems coupling QI spins with matter excitations have garnered significant recent interest. We propose and theoretically study a hybrid system that couples spin-1 QI with the dynamical excitations of nanomagnets, which are controlled by mechanisms uncovered in classical spintronics. We show that in such systems the QI-spin decoherence, due to coupling to thermally excited modes of the nanomagnet, can be designed across a wide range by exploiting the control over nanomagnet's mode ellipticity and the chiral nature of the coupling between the QI spin and nanomagnet. On the other hand, when activated electrically via voltage-induced torques, we demonstrate that QI spins can be driven coherently with large quality factors at room temperature by leveraging inherent nonlinear precessional modes of the nanomagnet. Our results provide theoretical guidance for enabling unique quantum spintronic functionalities, such as local coherent driving of QI spins up to ambient conditions, and the design of nanomagnet-enhanced QI-based hybrid sensors. Copyright © 2022, The Authors. All rights reserved.

关键词： Nanomagnetics

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SINR: Deconvolving Circular SAS Images Using Implicit Neural Representations

arXiv

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arXiv 2022年

作者： Reed, Albert Blanford, Thomas Brown, Daniel C. Jayasuriya, Suren The School of Electrical Computer and Energy Engineering Arizona State University United States The Applied Research Laboratory United States The Applied Research Laboratory Graduate Program in Acoustics Pennsylvania State University United States The School of Arts Media and Engineering The School of Electrical Computer and Energy Engineering Arizona State University United States

Circular synthetic aperture sonars (CSAS) capture multiple observations of a scene to reconstruct high-resolution images. We can characterize resolution by modeling CSAS imaging as the convolution between a scene's underlying point scattering distribution and a system-dependent point spread function (PSF). The PSF is a function of the system bandwidth and determines a fixed degree of blurring on reconstructed imagery. In theory, deconvolution overcomes bandwidth limitations by reversing the PSF-induced blur and recovering the scene's scattering distribution. However, deconvolution is an ill-posed inverse problem and sensitive to noise. We propose an optimization method that leverages an implicit neural representation (INR) to deconvolve CSAS images. We highlight the performance of our SAS INR pipeline, which we call SINR, by implementing and comparing to existing deconvolution methods. Additionally, prior SAS deconvolution methods assume a spatially-invariant PSF, which we demonstrate yields subpar performance in practice. We provide theory and methods to account for a spatially-varying CSAS PSF, and demonstrate that doing so enables SINR to achieve superior deconvolution performance on simulated and real acoustic SAS data. We provide code (click here) to encourage reproducibility of research. © 2022, CC BY.

关键词： Optical transfer function

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Development of Educational Game for Indonesian History Lesson Focusing on Indonesia Pre-Literacy Relics 'Prehistoria' for Grade X High School Student

Development of Educational Game for Indonesian History Lesso...

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2020 International Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Nugroho, Supeno Mardi Susiki Rahman, Muhammad Daffa Abiyyu Hariadi, Mochamad Arief, Muhammad Faculty of Intelligent Electrical and Informatics Technology Sepuluh Nopember Institute of Technology Computer Engineering Department Surabaya Indonesia Tokyo University of Technology Media Science Program Graduate School of Bionics Computer and Media Sciences Tokyo Japan

ISBN: (纸本)9781728182834

The development of game technology has opened up new possibilities in learning methods through educational games. However, in Indonesia, the application of this concept is lacking. One lesson that can benefit from educational games is Indonesian History in class X, with a focus on history in the pre-literacy period. This study aims to create a puzzle-Adventure type of digital game that can help educate students about the pre-literacy period, developed with Unity, and uses WebGL as a target device while referring to Indonesia's revised 2013 national curriculum. The result of this research is the creation of a digital game that can be played on average of 254.36 seconds, with potential for educational use. A survey result shows that many of the ancient objects and some of the ages are well-recognized. However, the survey also shows many of the gameplay aspects, such as UI, gameplay features, and adventure elements, need improvements. © 2020 IEEE.

关键词： Surveys

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Enhancement of Co-located Shared VR Experiences: Representing Non-HMD Observers on Both HMD and 2D Screens

Enhancement of Co-located Shared VR Experiences: Representin...

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International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Zixuan Guo Wenge Xu Hongyu Wang Tingjie Wan Nilufar Baghaei Cheng-Hung Lo Hai-Ning Liang School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou China Department of Computer Science The University of Liverpool Liverpool UK College of Computing Birmingham City University Birmingham UK School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Department of Industrial Design Xi’an Jiaotong-Liverpool University Suzhou China Computational Media and Arts Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (数字)9798331516475

ISBN: (纸本)9798331516482

Virtual reality (VR) not only allows head-mounted display (HMD) users to immerse themselves in virtual worlds but also to share them with others. When designed correctly, this shared experience can be enjoyable. However, in typical scenarios, HMD users are isolated by their devices, and non-HMD observers lack connection with the virtual world. To address this, our research investigates visually representing observers on both HMD and 2D screens to enhance shared experiences. The study, including five representation conditions, reveals that incorporating observer representation positively impacts both HMD users and observers. For how to design and represent them, our work shows that HMD users prefer methods displaying real-world visuals, while observers exhibit diverse preferences regarding being represented with real or virtual images. We provide design guidelines tailored to both displays, offering valuable insights to enhance co-located shared VR experiences for HMD users and non-HMD observers.

关键词： Visualization Head-mounted displays Design methodology Resists Interference Observers Augmented reality

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Role of Wireless Communications in Digital Economy in the Present Context 6

Role of Wireless Communications in Digital Economy in the Pr...

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6th International Conference on Trends in Electronics and Informatics, ICOEI 2022

作者： Revathi, S. Shrivastava, Arpan Yussupova, Ardak Hidayatulloh, A. Nururrochman Saltanat, Daurbekova Mishra, Arpana Sri Ramakrishna Institute of Technology Department of Computer Science and Engineering Coimbatore India Management Devi Ahilya Vishva Vidyalaya Madhya Pradesh India Kazakh National University of Arts Department of Art Studies Nur-Sultan Kazakhstan Universitas Gadjah Mada Leadership and Policy Innovation Program Indonesia International Education Corporation Department of Construction Almaty050042 Kazakhstan Sharda University Electrical Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9781665483285

Wireless communication has connected millions of people across the world to internet to enable them to reap benefits of digital economy in present scenario. Almost all the sectors of economy including healthcare, agriculture and transportation nowadays rely largely upon wireless communications. In the present context, the sudden outbreak of Covid-19 has caused governments to impose restrictions on various activities and employees have been directed to work from their homes to ensure safety. In such a situation, wireless communication has made it possible to connect with each other via the internet. Apart from this, Smart healthcare-system has been developed through utilisation of wireless communication systems. During this pandemic situation, delivery of healthcare services in remote areas has gained huge momentum and wireless communication plays a vital role in this regard. Aim of current critical assessment is to provide an in-depth analysis of the role played by wireless communication in establishment of a well-structured digital economy in present scenario. In literature-review, different applications of wireless technology via ICT in various sectors and aspects of life have been discussed through a conceptual and a theoretical framework. The Method section of current study has provided an in-depth insight into the ways required information have been collected in this study. As found in the results and discussion section, a positive relation exists between wireless-communication and establishment of digital economy in current situation. This study has concluded that there are certain challenges associated with wireless communication;however, it has significant influence in making processes smarter and faster as compared to earlier. © 2022 IEEE.

关键词： Internet of things

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"It Feels Like Being Locked in A Cage": Understanding Blind or Low Vision Streamers' Perceptions of Content Curation Algorithms

arXiv

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arXiv 2022年

作者： Rong, Ethan Z. Zhou, Mo Morgana Lu, Zhicong Fan, Mingming Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Department of Electrical Engineering City University of Hong Kong China Department of Computer Science City University of Hong Kong China Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology China

Blind or low vision (BLV) people were recently reported to be live streamers on the online platforms that employed content curation algorithms. Recent research uncovered algorithm biases suppressing the content created by marginalized populations. However, little is known about the effects of the algorithms adopted by live streaming platforms on BLV streamers and how they, as a marginalized population, perceive the effects of the algorithms. We interviewed BLV streamers (N=19) of Douyin - a popular live stream platform in China - to understand their perceptions of algorithms, perceived challenges, and mitigation strategies. Our findings show the perceived factors contributing to disadvantages under algorithmic evaluation of BLV streamers' content (e.g., issues with filming and timely interaction with viewers) and perceived algorithmic suppression (e.g., content not amplified to sighted users but suppressed within the BLV community). Their mitigation strategies (e.g., not watching other BLV streamers' shows) tended to be passive. We discuss design considerations to design a more inclusive and fair live streaming platform. © 2022, CC BY-NC-ND.

关键词： Social networking (online)

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SkinSource: A Data-Driven Toolbox for Predicting Touch-Elicited Vibrations in the Upper Limb

SkinSource: A Data-Driven Toolbox for Predicting Touch-Elici...

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International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS)

作者： Neeli Tummala Gregory Reardon Simone Fani Dustin Goetz Matteo Bianchi Yon Visell the Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara CA USA the Media Arts and Technology Program University of California Santa Barbara Santa Barbara CA USA the School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA the Soft Robotics for Human Cooperation and Rehabilitation Lab Instituto Italiano di Tecnologia Geneva GE Italy the Department of Mechanical Engineering University of California Santa Barbara Santa Barbara CA USA the Department of Information Engineering University of Pisa PI Italy the Department of Biological Engineering University of California Santa Barbara Santa Barbara CA USA

Vibrations transmitted throughout the hand and arm during touch contact play a central role in haptic science and engineering but are challenging to model or experimentally characterize. Here, we present SkinSource, a data-driven toolbox for predicting skin vibrations across the upper limb in response to user-specified input forces. The toolbox leverages impulse response measurements that encode the physics of vibration transmission across the hands and arms of four participants and provides software tools for analyzing the predicted skin responses. We show that the SkinSource predictions closely match experimental measurements and confirm the underlying assumption of linear vibration transmission in the skin. We also demonstrate through several usage examples how SkinSource can act as a versatile computational platform for haptic research applications, such as characterizing vibrotactile transmission in the skin, engineering haptic interfaces, and investigating touch perception.

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