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Conference on Lasers and Electro-Optics (CLEO)

作者： Diego Tami Douglas A. A. Ohlberg Jhonattan C. Ramirez Cássio Gonçalves Do Rego Gilberto Medeiros-Ribeiro Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Brazil Microscopy Center Universidade Federal de Minas Gerais Brazil Department of Electronic Engineering Universidade Federal de Minas Gerais Brazil Computer Science Department Universidade Federal de Minas Gerais Brazil

In this work, we analyzed numerically a multiscale nanosystem based on sMIM on TBG. Spontaneous formation of a water-meniscus by the approximation between the tip-sample concentrates the microwave fields, reaching res... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Microscopy Masers Lasers and electrooptics Laser modes Numerical models Impedance Electrooptical waveguides

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A spatiotemporal multi-scale computational model for FDG PET imaging at different stages of tumor growth and angiogenesis

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SCIENTIFIC REPORTS 2022年第1期12卷 1-16页

作者： Kashkooli, Farshad Moradi Abazari, Mohammad Amin Soltani, M. Ghazani, Mehran Akbarpour Rahmim, Arman Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering School of Optometry and Vision Science Faculty of Science University of Waterloo Waterloo Canada Advanced Bioengineering Initiative Center Multidisciplinary International Complex K. N. Toosi University of Technology Tehran Iran Centre for Biotechnology and Bioengineering (CBB) University of Waterloo Waterloo ON Canada Faculty of Mechanical Engineering University of Tabriz Tabriz Iran Department of Integrative Oncology BC Cancer Research Institute Vancouver BC Canada Department of Physics and Astronomy University of British Columbia Vancouver BC Canada Department of Radiology University of British Columbia Vancouver BC Canada

A deeper understanding of the tumor microenvironment (TME) and its role in metabolic activity at different stages of vascularized tumors can provide useful insights into cancer progression and better support clinical assessments. In this study, a robust and comprehensive multi-scale computational model for spatiotemporal transport of F-18 fluorodeoxyglucose (FDG) is developed to incorporate important aspects of the TME, spanning subcellular-, cellular-, and tissue-level scales. Our mathematical model includes biophysiological details, such as radiopharmaceutical transport within interstitial space via convection and diffusion mechanisms, radiopharmaceutical exchange between intracellular and extracellular matrices by glucose transporters, cellular uptake of radiopharmaceutical, as well as its intracellular phosphorylation by the enzyme. Further, to examine the effects of tumor size by varying microvascular densities (MVDs) on FDG dynamics, four different capillary networks are generated by angiogenesis modeling. Results demonstrate that as tumor grows, its MVD increases, and hence, the spatiotemporal distribution of total FDG uptake by tumor tissue changes towards a more homogenous distribution. In addition, spatiotemporal distributions in tumor with lower MVD have relatively smaller magnitudes, due to the lower diffusion rate of FDG as well as lower local intravenous FDG release. Since mean standardized uptake value (SUVmean) differs at various stages of microvascular networks with different tumor sizes, it may be meaningful to normalize the measured values by tumor size and the MVD prior to routine clinical reporting. Overall, the present framework has the potential for more accurate investigation of biological phenomena within TME towards personalized medicine.

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Modern extreme value statistics for Utopian extremes

arXiv

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arXiv 2023年

作者： Richards, Jordan Alotaibi, Noura Cisneros, Daniela Gong, Yan Guerrero, Matheus B. Redondo, Paolo Shao, Xuanjie School of Mathematics University of Edinburgh United Kingdom Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Harvard School of Public Health BostonMA United States Department of Mathematics California State University FullertonCA United States

Capturing the extremal behaviour of data often requires bespoke marginal and dependence models which are grounded in rigorous asymptotic theory, and hence provide reliable extrapolation into the upper tails of the data-generating distribution. We present a toolbox of four methodological frameworks, motivated by modern extreme value theory, that can be used to accurately estimate extreme exceedance probabilities or the corresponding level in either a univariate or multivariate setting. Our frameworks were used to facilitate the winning contribution of Team Yalla to the EVA (2023) Conference Data Challenge, which was organised for the 13th International Conference on Extreme Value Analysis. This competition comprised seven teams competing across four separate sub-challenges, with each requiring the modelling of data simulated from known, yet highly complex, statistical distributions, and extrapolation far beyond the range of the available samples in order to predict probabilities of extreme events. Data were constructed to be representative of real environmental data, sampled from the fantasy country of "Utopia". © 2023, CC BY.

关键词： Extrapolation

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Giant long-range dipole-dipole interactions in a plasmonic lattice

Giant long-range dipole-dipole interactions in a plasmonic l...

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Frontiers in Optics + Laser science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Boddeti, Ashwin K. Guan, Jun Sentz, Tyler Juarez, Xitali Newman, Ward Cortes, Cristian Odom, Teri W. Jacob, Zubin School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Intel Corporation BeavertonOR97007 United States Center for Nanoscale Materials Argonne National Laboratory LemontIL60439 United States Graduate Program in Applied Physics Department of Materials Science and Engineering Department of Chemistry Northwestern University EvanstonIL60208 United States

We observe long-range dipole-dipole interactions in a plasmonic lattice. Fluorescence lifetime measurements show density-dependent non-exponential decay dynamics over 800nm mean nearest-neighbour separation distances ... 详细信息

ISBN: (纸本)9781557528209

关键词： Plasmonics

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Temperature-dependent THz transients emitted by optically excited FeNi/Pt spintronic emitters

Temperature-dependent THz transients emitted by optically ex...

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International Conference on Infrared and Millimeter Waves

作者： Jing Cheng Daniel E. Bürgler Roman Adam Ivan Komissarov Debamitra Chaktraborty Genyu Chen Roman Sobolewski Materials Science Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA Research Centre Jülich Peter Grünberg Institute Jülich Germany Department of Electrical and Computer Engineering University of Rochester Rochester New York USA

We conducted a study on the temperature dependence of THz transients emitted from FeNi/Pt spintronic emitters excited by femtosecond optical pulses. The results indicate that the emitted THz radiation strength is governed by the temperature-dependent magnetization changes within the FeNi layer system. We observed a very good agreement between the magnetization and THz amplitude temperature dependences below the 0.8 T/Tc ratio. Our findings highlight the importance of considering temperature effects in THz spintronic emitters for improving their signal strength and efficiency.

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Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupling under Extreme Spatial Confinement

Terahertz Landau Polaritons in Nano-slots: Ultrastrong Coupl...

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International Conference on Infrared and Millimeter Waves

作者： Dasom Kim Sunghwan Kim Dukhyung Lee Shuang Liang Fuyang Tay Michael J. Manfra Dai-Sik Kim Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Physics Long-wavelength Nanotechnology Laboratory and Quantum Photonics Institute Ulsan National Institute of Science and Technology (UNIST) Ulsan South Korea Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Department of Material Science and NanoEngineering Rice University Houston TX USA

We report ultrastrong coupling of the cyclotron resonance of a two-dimensional electron gas in a GaAs quantum well to terahertz cavity photons under extreme confinement to the nanometer scale. This was realized by an array of nano-slots fabricated close to the quantum well layer on the GaAs substrate. Our terahertz magnetospectroscopic measurements revealed two polariton branches as a function of applied magnetic field. While the photon-like part of the two polariton branches was clearly observed, the matter-like part was generally elusive. Our electromagnetic simulations quantitatively reproduce our observation for the upper-polariton branch. However, for the lower-polariton branch, our simulations predict a pronounced resonance, which was absent in experimental spectra. This discrepancy may be a consequence of the breakdown of the dipole approximation in this extreme confinement situation.

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Smart Residential Parking

Smart Residential Parking

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International Conference on Informatics and Computational sciences (ICICoS)

作者： Suhartono Jung-Lung Chiang Maria Mahardini Sakanti C. Bambang Dwi Kuncoro Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan R.O.C Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan R.O.C Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan R.O.C

ISBN: (数字)9798350375886

ISBN: (纸本)9798350375893

This research aims to create a smart residential system that will improve parking management in residential areas using mini-server technology. Another aim is to provide a safe and effective smart parking solution for residential areas with limited capacity. This research method uses mini-server technology and control to create smart system ideas. Apart from that, this research also uses servo motor technology, proximity sensors, cameras, and IoT applications for smart parking management. The result is the creation of intelligent residential parking management, which uses a Raspberry Pi 5 Model B as a server and control to improve the parking management system in residential areas, and the use of number plate recognition technology to be applied to Smart City. This further research offers a new perspective on creating intelligent parking solutions using two input validation parameters simultaneously, namely facial and license plate recognition

关键词： Smart cities Automated parking Servers Security Internet of Things Usability Servomotors

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Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services

TechRxiv

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TechRxiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Huang, Huawei Mao, Shiwen School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore School of Software Engineering Sun Yat-Sen University Zhuhai China Department of Electrical and Computer Engineering Auburn University Auburn United States

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which deploys AIGC models in wireless edge networks to ensure broad AIGC services accessibility for Metaverse users. Nonetheless, an important aspect of providing personalized user experiences requires carefully selecting AIGC Service Providers (ASPs) capable of effectively executing user tasks, which is complicated by environmental uncertainty and variability. Addressing this gap in current research, we introduce the AI-Generated Optimal Decision (AGOD) algorithm, a diffusion model-based approach for generating the optimal ASP selection decisions. Integrating AGOD with Deep Reinforcement Learning (DRL), we develop the Deep Diffusion Soft Actor-Critic (D2SAC) algorithm, enhancing the efficiency and effectiveness of ASP selection. Our comprehensive experiments demonstrate that D2SAC outperforms seven leading DRL algorithms. Furthermore, the proposed AGOD algorithm has the potential for extension to various optimization problems in wireless networks, positioning it as a promising approach for future research on AIGC-driven services. The implementation of our proposed method is available at: https://***/Lizonghang/AGOD. © 2023, CC BY.

关键词： Reinforcement learning

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Low power In Memory Computation with Reciprocal Ferromagnet/Topological Insulator Heterostructures

arXiv

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arXiv 2022年

作者： Vakili, Hamed Ganguly, Samiran de Coster, George J. Neupane, Mahesh R. Ghosh, Avik W. Department of Physics University of Virginia CharlottesvilleVA22904 United States Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States Department of Electrical and Computer Engineering Virginia Commonwealth University RichmondVA23284 United States DEVCOM Army Research Laboratory 2800 Powder Mill Rd AdelphiMD20783 United States Materials Science and Engineering Program University of California RiversideCA92521 United States

The surface state of a 3D topological insulator (3DTI) is a spin-momentum locked conductive state, whose large spin hall angle can be used for the energy-efficient spin orbit torque based switching of an overlying ferromagnet (FM). Conversely, the gated switching of the magnetization of a separate FM in or out of the TI surface plane, can turn on and off the TI surface current. By exploiting this reciprocal behaviour, we can use two FM/3DTI heterostructures to design an integrated 1-Transistor 1-magnetic tunnel junction random access memory unit (1T1MTJ RAM) for an ultra low power Processing-in-Memory (PiM) architecture. Our calculation involves combining the Fokker-Planck equation with the Non-equilibrium Green Function (NEGF) based flow of conduction electrons and Landau-Lifshitz-Gilbert (LLG) based dynamics of magnetization. Our combined approach allows us to connect device performance metrics with underlying material parameters, which can guide proposed experimental and fabrication efforts. © 2022, CC BY-NC-SA.

关键词： Magnetization

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AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Forged content shared widely on social media platforms is a major social problem that requires increased regulation and poses new challenges to the research community. The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous work on detecting AI-generated fake videos only utilizes visual modality or audio modality. While there are some methods in the literature that exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multi-modal datasets of deepfake videos involving acoustic and visual manipulations. Moreover, these existing methods are mostly based on CNN and suffer from low detection accuracy. Inspired by the recent success of Transformer in various fields, to address the challenges posed by deepfake technology, in this paper, we propose an Audio-Visual Transformer-based Ensemble Network (AVTENet) framework that considers both acoustic manipulation and visual manipulation to achieve effective video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multi-modal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that our best model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. © 2023, CC BY.

关键词： Statistical tests

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