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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Johannes, A., et al.
(författare)
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Enhanced sputtering and incorporation of Mn in implanted GaAs and ZnO nanowires
- 2014
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Ingår i: Journal of Physics D: Applied Physics. - Bristol : IOP Publishing. - 1361-6463 .- 0022-3727. ; 47:39
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Tidskriftsartikel (refereegranskat)abstract
- We simulated and experimentally investigated the sputter yield of ZnO and GaAs nanowires, which were implanted with energetic Mn ions at room temperature. The resulting thinning of the nanowires and the dopant concentration with increasing Mn ion fluency were measured by accurate scanning electron microscopy (SEM) and nano-x-Ray Fluorescence (nanoXRF) quantification, respectively. We observed a clearly enhanced sputter yield for the irradiated nanowires compared to bulk, which is also corroborated by iradina simulations. These show a maximum if the ion range matches the nanowire diameter. As a consequence of the erosion thinning of the nanowire, the incorporation of the Mn dopants is also enhanced and increases non-linearly with increasing ion fluency.
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| 3. |
- Kumari, Renu, et al.
(författare)
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Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices
- 2023
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Ingår i: APL Materials. - Melville : American Institute of Physics (AIP). - 2166-532X. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- Computational efficiency is significantly enhanced using artificial neural network-based computing. A two-terminal memristive device is a powerful electronic device that can mimic the behavior of a biological synapse in addition to storing information and performing logic operations. This work focuses on the fabrication of a memristive device that utilizes a resistive switching layer composed of polyvinyl alcohol infused with ZnO nanoparticles. By incorporating ZnO nanoparticles into the polymer film, the fabricated memristive devices exhibit functionalities that closely resemble those of biological synapses, including short-term and long-term plasticity, paired-pulse facilitation, and spike time-dependent plasticity. These findings establish the ZnO nanoparticle-polymer nanocomposite as a highly promising material for future neuromorphic systems. © 2023 Author(s).
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| 4. |
- Mumtaz, Nadia, et al.
(författare)
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An overview of violence detection techniques : current challenges and future directions
- 2023
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Ingår i: Artificial Intelligence Review. - Dordrecht : Springer Nature. - 0269-2821 .- 1573-7462. ; 56, s. 4641-4666
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Tidskriftsartikel (refereegranskat)abstract
- The Big Video Data generated in today’s smart cities has raised concerns from its purposeful usage perspective, where surveillance cameras, among many others are the most prominent resources to contribute to the huge volumes of data, making its automated analysis adifcult task in terms of computation and preciseness. Violence detection (VD), broadly plunging under action and activity recognition domain, is used to analyze Big Video data for anomalous actions incurred due to humans. The VD literature is traditionally basedon manually engineered features, though advancements to deep learning based standalone models are developed for real-time VD analysis. This paper focuses on overview of deepsequence learning approaches along with localization strategies of the detected violence.This overview also dives into the initial image processing and machine learning-based VD literature and their possible advantages such as efciency against the current complex models. Furthermore,the datasets are discussed, to provide an analysis of the current models, explaining their pros and cons with future directions in VD domain derived from anin-depth analysis of the previous methods. © The Author(s), under exclusive licence to Springer Nature B.V. 2022.
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