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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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Implicit Neural Representations for Deconvolving SAS Images

Implicit Neural Representations for Deconvolving SAS Images

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OCEANS

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

ISBN: (纸本)9781665427883

Synthetic aperture sonar (SAS) image resolution is constrained by waveform bandwidth and array geometry. Specifically, the waveform bandwidth determines a point spread function (PSF) that blurs the locations of point scatterers in the scene. In theory, deconvolving the reconstructed SAS image with the scene PSF restores the original distribution of scatterers and yields sharper reconstructions. However, deconvolution is an ill-posed operation that is highly sensitive to noise. In this work, we leverage implicit neural representations (INRs), shown to be strong priors for the natural image space, to deconvolve SAS images. Importantly, our method does not require training data, as we perform our deconvolution through an analysis-by-synthesis optimization in a self-supervised fashion. We validate our method on simulated SAS data created with a point scattering model and real data captured with an in-air circular SAS. This work is an important first step towards applying neural networks for SAS image deconvolution.

关键词： Deconvolution Oceans Neural networks Training data Scattering Bandwidth Image restoration

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Assisted Multi-Frame Approach for Super-Resolution in UAV Photogrammetric Images

Assisted Multi-Frame Approach for Super-Resolution in UAV Ph...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Daniel Zanotta Vinicius Sales Ademir Marques Andre Luiz Durante Spigolon Luiz Gonzaga Maurício Roberto Veronez Vizlab — X-Reality and GeoInformatics Lab UNISINOS - São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil PETROBRAS - Petrobras Research and Development Center (CENPES) RJ Brazil

Improvement in spatial resolution of remote sensing images will always be a hot-topic since the sharpening of image objects is mandatory for many appications. Even thought image instruments have received great improvements in the recent years, super-resolution techniques are welcome to increase even more the level of quality of the data for further interpretations. In this paper we present a multi-frame super-resolution approach that uses a set of UAV images acquired at the same spot, but with slight different perspectives caused by random fluctuations. The small off-sets between consecutive pixels of the low spatial resolution images are considered at subpixel level to feed an arithmetic system of equations able to produce high resolution pixels, which are the unknowns of the system. The results are soundness and could show visual enhancement. However, further developments is need to in deep undertanding and possible advancement of the designed approach.

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Implicit Neural Representations for Deconvolving SAS Images

arXiv

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arXiv 2021年

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

关键词： Optical transfer function

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An Efficient Three-Factor Authenticated Key Agreement Technique Using FCM Under HC-IoT Architectures

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Computers, Materials & Continua 2022年第7期72卷 1373-1389页

作者： Chandrashekhar Meshram Agbotiname Lucky Imoize Sajjad Shaukat Jamal Parkash Tambare Adel R.Alharbi Iqtadar Hussain Department of Post Graduate Studies and Research in Mathematics Jayawanti Haksar Government Post-Graduation CollegeCollege of Chhindwara UniversityBetul460001M.P.India Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr University44801BochumGermany Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia Water Resources&Applied Mathematics Research Lab Nagpur440027India College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar

The Human-Centered Internet of Things(HC-IoT)is fast becoming a hotbed of security and privacy *** users can establish a common session key through a trusted server over an open communication channel using a three-party authenticated key *** of the early authenticated key agreement systems relied on pairing,hashing,or modular exponentiation processes that are computationally intensive and *** order to address this problem,this paper offers a new three-party authenticated key agreement technique based on fractional chaotic *** new scheme uses fractional chaotic maps and supports the dynamic sensing of HC-IoT devices in the network architecture without a password *** projected security scheme utilized a hash function,which works well for the resource-limited HC-IoT *** results show that our new technique is resistant to password guessing attacks since it does not use a ***,our approach provides users with comprehensive privacy protection,ensuring that a user forgery attack causes no ***,our new technique offers better security features than the techniques currently available in the literature.

关键词： Three-party authenticated key agreement anonymity fractional chaotic maps Chebyshev polynomial password table human-centered internet of things(HC-IoT)

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Sound non-reciprocity based on synthetic magnetism

arXiv

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arXiv 2022年

作者： Chen, Zhaoxian Li, Zhengwei Weng, Jingkai Liang, Bin Lu, Yanqing Cheng, Jianchun Alù, Andrea Collaborative Innovation Center of Advanced Microstructures Key Laboratory of Modern Acoustics MOE Institute of Acoustics Department of Physics Nanjing University Nanjing210093 China College of Engineering and Applied Sciences Nanjing University Nanjing210093 China Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Synthetic magnetism has been recently realized using spatiotemporal modulation patterns, producing non-reciprocal steering of charge-neutral particles such as photons and phonons. Here, we design and experimentally demonstrate a non-reciprocal acoustic system composed of three compact cavities interlinked with both dynamic and static couplings, in which phase-correlated modulations induce a synthetic magnetic flux that breaks time-reversal symmetry. Within the rotating wave approximation, the transport properties of the system are controlled to efficiently realize large non-reciprocal acoustic transport. By optimizing the coupling strengths and modulation phases, we achieve frequency-preserved unidirectional transport with 45-dB isolation ratio and 0.85 forward transmission. Our results open to the realization of acoustic nonreciprocal technologies with high efficiency and large isolation, and offer a route towards Floquet topological insulators for sound. Copyright © 2022, The Authors. All rights reserved.

关键词： Magnetism

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Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin

Enhancing Sustainable Development Goals Through Future Vapor...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Surendra Maharjan Wenzhao Li Shahryar Fazli Hani Sewilam Hesham El-Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Earth Systems Science and Data Solutions Lab Chapman University Orange CA USA The Center for Applied Research on the Environment and Sustainability The American University in Cairo Cairo Egypt Department of Engineering Hydrology RWTH Aachen University Aachen Germany Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 to 2060 under two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. The study's findings on the implications of rising VPD levels in the Nile River Basin (NRB), particularly under the SSP 5-8.5 scenario, highlight a critical challenge for the region's agricultural productivity and food security. The increased VPD, indicative of drier conditions, leads to a moisture deficit for crops, potentially reducing agricultural yields. This scenario poses a significant threat to food security, as lower crop yields can result in food shortages and higher food prices, adversely affecting vulnerable populations. The study underscores the necessity of integrating VPD insights into agricultural and water resource management strategies to uphold food security against climatic variations in support of the SDGs.

关键词： Productivity Climate change Precipitation Food security Agriculture Rivers Sustainable development

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Spatial hearing and virtual auditory display 49

Spatial hearing and virtual auditory display

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49th International Congress and Exposition on Noise Control Engineering, INTER-NOISE 2020

作者： Xie, Bosun Vigeant, Michelle C. South China University of Technology Acoustic Lab. School of Physics and Optoeletronics Wushan Road 381 Guangzhou510641 China Pennsylvania State University Graduate Program in Acoustics College of Engineering 201 Applied Science Bldg. University ParkPA16802 United States

ISBN: (纸本)9788994021362

Spatial hearing refers to the subjective perceptions of the spatial attributes of sound and is one of the important functions of human hearing. Based on the principles of spatial hearing, virtual auditory displays simulate the binaural signals in various acoustic environments and then create desired spatial auditory events via headphone or sometimes loudspeaker presentations. HRTF-based (head-related transfer functions) binaural synthesis is the core of virtual auditory displays over headphones. As a special spatial sound technique, virtual auditory displays are not only applicable to conventional audio reproduction, but also to a wide field of research areas and engineering applications, such as multimedia, virtual reality, communication, and acoustic environment assessments. During the past two or three decades, virtual auditory displays have become a hot topic in the field of acoustics and signal processing. This presentation first outlines the principles of spatial hearing, and then comprehensively reviews the principles, progresses, and applications of virtual auditory displays, including some recent works from the authors' research groups. Finally, the presentation will conclude with some prospective future works. © Proceedings of 2020 International Congress on Noise Control Engineering, INTER-NOISE 2020. All rights reserved.

关键词： Loudspeakers

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Cyclodextrin-modified layered double hydroxide thin-film nanocomposite desalination membrane for boron removal

Cyclodextrin-modified layered double hydroxide thin-film nan...

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2023 AIChE Annual Meeting

作者： Ee, Liang Ying Zhao, Qipeng Gao, Jie Lim, Chit Kai Xue, Kai Chin, Sze Yuet Li, Sam Fong Yau Chung, Tai-Shung Chen, Shing Bor Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore 4 Engineering Drive 4 Singapore117585 Singapore Department of Chemistry College of Humanities and Sciences National University of Singapore 3 Science Drive 3 Singapore117543 Singapore Chemical Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Centre of High Field NMR Spectroscopy and Imaging School of Physical and Mathematical Sciences College of Science Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore NUS Environmental Research Institute National University of Singapore T-Lab Building 5A Engineering Drive 1 Singapore117411 Singapore Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei106335 Taiwan

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Observations of spatial coherence from a multibeam sub-bottom profiler

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Proceedings of Meetings on acoustics 2024年第1期54卷

作者： Laura Brownstead Jason Philtron Chad Smith Daniel C. Brown Graduate Program in Acoustics The Pennsylvania State University University Park PA Applied Research Laboratory The Pennsylvania State University University Park PA 16802 USA lgb5113@psu.edu Applied Research Laboratory The Pennsylvania State University University Park 16802 PA USA jhb186@psu.edu cms561@psu.edu dcb19@psu.edu

Sonar data from the Kongsberg SBP-29 (with a 64-channel receive array) aboard R/V Sally Ride is analyzed to judge the value of spatial coherence of signals reflected from the ocean floor. The multibeam sub-bottom profiler collected five days of sonar test data off the coast of Southern California over a variety of sediment types and marine geologies. The spatial coherence of measured signals is sensitive to different bottom types and to sediment layering deep below the ocean floor. Navigational data also permits comparison of sonar data to existing bathymetric maps of the ensonified floor. The flexibility of the transmit and receive arrays permit detailed study of potentially informative seafloor features and landmarks. The findings of primary interest are interpreted in the context of a Normal fit to characterize the spatial coherence of scattered signals and future work is reported based on statistical analysis of the fitted data.

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