ORCID Profile
0000-0002-6932-2900
Current Organisations
University of South Australia
,
CSIRO
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Publisher: IEEE
Date: 04-2015
Publisher: IEEE
Date: 04-2020
Publisher: Springer Berlin Heidelberg
Date: 2002
Publisher: Elsevier BV
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 04-2020
Publisher: Wiley
Date: 11-03-2022
DOI: 10.1002/PAT.5652
Abstract: Shape memory elastomers (SMEs) are a class of intelligent materials characterized by their ability to deform and recover shapes under applied force and external stimuli. Heat and ultraviolet radiation are ex les of the most common external stimuli. With the emerging prevalence of internet of things devices and the ensuing need for smart materials and structures, SMEs provide significant opportunities to support the development of novel applications in robotics, remotely actuated systems, and packages, including those promised for the space industry. To harness the immense potential in the emerging applications of these materials, one approach is the systematic multi‐scale modeling coupled with artificial intelligence‐assisted design leading to the development of next‐generation intelligent systems. This review covers several aspects of the synthesis/materials chemistry and applications of SMEs with a view towards enabling such an approach. The synthesis procedures emphasizing dynamic covalent bond reactions are reviewed. Then, liquid crystalline elastomers are introduced as a specific elastomeric material class that exhibits excellent shape memory characteristics and distinctive transition temperatures. The utilization of advanced manufacturing methods such as additive manufacturing, three‐dimensional printing, and the emerging four‐dimensional printing technologies assisted by machine learning are detailed in producing and predicting SMEs. Finally, the current trends in the use of SMEs are summarized in areas of industrial and space engineering and biomedical applications.
Publisher: IEEE
Date: 05-2013
Publisher: IEEE
Date: 08-2015
Publisher: IEEE
Date: 2002
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 07-2023
Publisher: IEEE
Date: 12-2020
Publisher: Institution of Engineering and Technology (IET)
Date: 2012
DOI: 10.1049/EL.2012.2714
Publisher: Elsevier BV
Date: 08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2015
Publisher: IEEE
Date: 12-2013
Publisher: IEEE
Date: 02-07-2023
Publisher: IEEE
Date: 10-2018
Publisher: ACM
Date: 14-10-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2012
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2014
Publisher: Elsevier BV
Date: 09-2012
Publisher: Elsevier BV
Date: 04-2013
Publisher: Elsevier BV
Date: 03-2023
Publisher: IEEE
Date: 12-2017
Publisher: IEEE
Date: 05-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-10-2023
Publisher: Elsevier BV
Date: 08-2022
Publisher: IEEE
Date: 12-2013
Publisher: IEEE
Date: 06-2012
Publisher: Elsevier BV
Date: 06-2012
Publisher: IEEE
Date: 06-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2012
Publisher: Institution of Engineering and Technology (IET)
Date: 2012
DOI: 10.1049/EL.2012.0625
Publisher: Elsevier BV
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2015
Publisher: MDPI AG
Date: 15-11-2022
DOI: 10.3390/S22228811
Abstract: Radio frequency identification (RFID) tags are small, low-cost, wearable, and wireless sensors that can detect movement in structures, humans, or robots. In this paper, we use passive RFID tags for structural health monitoring by detecting displacements. We employ a novel process of using 3D printable embedded passive RFID tags within uniform linear arrays together with the multiple signal classification algorithm to estimate the direction of arrival using only the phase of the backscattered signals. We validate our proposed approach via data collected from real-world experiments using a unipolar RFID reader antenna and both narrowband and wideband measurements.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer Science and Business Media LLC
Date: 02-12-2021
Publisher: IEEE
Date: 19-10-2020
Publisher: IEEE
Date: 06-2014
Publisher: Elsevier BV
Date: 2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2014
Publisher: Elsevier BV
Date: 2019
Publisher: MDPI AG
Date: 12-09-2023
DOI: 10.3390/FI15090309
Publisher: IEEE
Date: 06-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Publisher: ACM
Date: 14-08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2014
Publisher: Elsevier BV
Date: 04-2023
Publisher: IEEE
Date: 05-2013
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 2017
Publisher: Informa UK Limited
Date: 31-01-2011
Publisher: MDPI AG
Date: 12-10-2018
Abstract: High-resolution hyperspectral images are in great demand but hard to acquire due to several existing fundamental and technical limitations. A practical way around this is to fuse multiple multiband images of the same scene with complementary spatial and spectral resolutions. We propose an algorithm for fusing an arbitrary number of coregistered multiband, i.e., panchromatic, multispectral, or hyperspectral, images through estimating the endmember and their abundances in the fused image. To this end, we use the forward observation and linear mixture models and formulate an appropriate maximum-likelihood estimation problem. Then, we regularize the problem via a vector total-variation penalty and the non-negativity/sum-to-one constraints on the endmember abundances and solve it using the alternating direction method of multipliers. The regularization facilitates exploiting the prior knowledge that natural images are mostly composed of piecewise smooth regions with limited abrupt changes, i.e., edges, as well as coping with potential ill-posedness of the fusion problem. Experiments with multiband images constructed from real-world hyperspectral images reveal the superior performance of the proposed algorithm in comparison with the state-of-the-art algorithms, which need to be used in tandem to fuse more than two multiband images.
Publisher: IEEE
Date: 03-2012
Publisher: Internet Society
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institution of Engineering and Technology (IET)
Date: 2011
DOI: 10.1049/EL.2011.2454
Publisher: IEEE
Date: 2002
Location: Australia
No related grants have been discovered for Reza Arablouei.