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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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Spin-orbit-locked hyperbolic polariton vortices carrying reconfigurable topological charges

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eLight 2022年第1期2卷 143-153页

作者： Mingsong Wang Guangwei Hu Saroj Chand Michele Cotrufo Yohannes Abate Kenji Watanabe Takashi Taniguchi Gabriele Grosso Cheng‑Wei Qiu Andrea Alù Photonics Initiative Advanced Science Research CenterCity University of New YorkNew York CityNY 10031USA Department of Electrical and Computer Engineering National University of SingaporeSingapore 116083Singapore Department of Physics and Astronomy The University of GeorgiaAthensGA 30602USA Research Center for Functional Materials National Institute for Materials ScienceTsukubaIbaraki 305‑0044Japan International Center for Materials Nanoarchitectonics National Institute for Materials ScienceTsukubaIbaraki 305‑0044Japan Physics Program Graduate CenterCity University of New YorkNew YorkNY 10016USA

The topological features of optical vortices have been opening opportunities for free-space and on-chip photonic technologies,e.g.,for multiplexed optical communications and robust information *** a parallel but disjoint effort,polar anisotropic van der Waals nanomaterials supporting hyperbolic phonon polaritons(HP2s)have been leveraged to drastically boost light-matter *** far HP2 studies have been mainly focusing on the control of their amplitude and scale *** we report the generation and observation of mid-infrared hyperbolic polariton vortices(HP2Vs)associated with reconfigurable topological ***-shaped gold disks coated with a flake of hexagonal boron nitride are exploited to tailor spin-orbit interactions and realise deeply subwavelength *** complex interplay between excitation spin,spiral geometry and HP2 dispersion enables robust reconfigurability of the associated topological *** results reveal unique opportunities to extend the application of HP2s into topological photonics,quantum information processing by integrating these phenomena with single-photon emitters,robust on-chip optical applications,sensing and nanoparticle manipulation.

关键词： Hyperbolic polariton vortex Light-matter interactions Spin-orbit interaction Topological charge Reconfigurability

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Pulsed Terahertz Time Domain Spectroscopy for Evaluating Treatment Efficacy: Initial Validation in Monitoring Pancreatic Ductal Adenocarcinoma

Pulsed Terahertz Time Domain Spectroscopy for Evaluating Tre...

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International Conference on Infrared and Millimeter Waves

作者： Debamitra Chakraborty Bradley N. Mills Jing Cheng Ivan Komissarov Scott A. Gerber Roman Sobolewski Materials Science Graduate Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA Department of Surgery University of Rochester Medical Center Rochester New York USA Department of Electrical and Computer Engineering University of Rochester Rochester New York USA

Pancreatic Ductal Adenocarcinoma (PDAC) is a highly invasive malignancy with limited curative effectiveness. Here, we report the viability of using pulsed Terahertz (THz) time domain spectroscopy (THz TDS) to monitor the efficacy of Stereotactic Body Radiation Therapy (SBRT) in treating PDAC in murine models. Our study shows that THz imaging can provide reliable and reproducible results to differentiate the changes in untreated and SBRT-treated PDAC tissue using THz refractive index and absorption coefficient as mapping parameters with statistical significance. Hence the study highlights that pulsed THz-TDS can be used as a technique to monitor tumor responses to immunotherapy, providing a comprehensive assessment of the tumor’s reaction to the treatment.

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Asynchronous Multi-Task Learning Based on One Stage YOLOR Algorithm

Asynchronous Multi-Task Learning Based on One Stage YOLOR Al...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Cheng-Fu Liou Tsung-Han Lee Jiun-In Guo Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Pervasive Artificial Intelligence Research Labs (PAIR Labs) Wistron-NCTU Embedded Artificial Intelligence Research Center Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan

The You Only Learn One Representation (YOLOR) approach is an object detector that can encode implicit knowledge and explicit knowledge of multiple tasks simultaneously. However, the requirement of jointly feeding data is not a friendly setting for an edge device due to the high computational cost. A better strategy is to learn the concept of the new task on the device individually, one by one, without access to the old data. In other words, the model has to deal with multiple tasks asynchronously. In this work, we extend the multi-purpose network YOLOR to asynchronous multi-task learning to learn domain invariant features, which focus on capturing the relatedness between the weight of the previous task and data of the subsequent task. Further, as the number of tasks gradually increases, we accumulate significant weights by introducing task-specific masks and expert modules; the former can automatically identify important filters to prevent modification caused by new tasks, and the latter address the kernel space misalignment problem to perform multi-task feature selection. We experimentally demonstrate that the proposed training strategy significantly outperforms the traditional solution in learning multiple tasks at different times on a public dataset, which supports that the proposed approach is more competitive for resource-limited edge devices.

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Snapshot hyperspectral imaging using a random phase mask and spectral filter array

Snapshot hyperspectral imaging using a random phase mask and...

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Computational Optical Sensing and Imaging, COSI 2020 - Part of Imaging and Applied Optics Congress 2020

作者： Monakhova, Kristina Yanny, Kyrollos Waller, Laura Department of Electrical Engineering and Computer Sciences University of California Berkeley United States UCB/UCSF Joint Graduate Program in Bioengineering University of California Berkeley United States

We introduce a snapshot hyperspectral imager that uses a random phase mask, repeated spectral filter array, and compressive recovery to achieve high spatial and spectral resolution in a small form factor. © 2020 ... 详细信息

ISBN: (纸本)9781557528209

关键词： Hyperspectral imaging

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Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions with Applications

arXiv

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arXiv 2024年

作者： Iguchi, Yuga Jasra, Ajay Maama, Mohamed Beskos, Alexandros Department of Statistical Science University College London LondonWC1E 6BT United Kingdom School of Data Science The Chinese University of Hong Kong Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we present a new antithetic multilevel Monte Carlo (MLMC) method for the estimation of expectations with respect to laws of diffusion processes that can be elliptic or hypo-elliptic. In particular, we consider the case where one has to resort to time discretization of the diffusion and numerical simulation of such schemes. Motivated by recent developments, we introduce a new MLMC estimator of expectations, which does not require simulation of intractable Lévy areas but has a weak error of order 2 and achieves the optimal computational complexity. We then show how this approach can be used in the context of the filtering problem associated to partially observed diffusions with discrete time observations. We illustrate with numerical simulations that our new approaches provide efficiency gains for several problems relative to some existing methods. © 2024, CC BY.

关键词： Diffusion

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A Security Testbed for Networked DES Control Systems

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IFAC-PapersOnLine 2022年第28期55卷 128-134页

作者： Michel R.C. Alves Karen Rudie Patrícia N. Pena Graduate Program in Electrical Engineering - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil Department of Electrical and Computer Engineering and Ingenuity Labs Research Institute Queen's university Kingston Ontario K7L 3N6 Canada Department of Electronics Engineering - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil

In this paper we present an implementation scheme for a networked control system where the coordination between devices is done by supervisory control theory. The system is intended to be used as a testbed for DES security-related techniques. We provide some examples of attacks whose effect can be evaluated using the proposed setup. The hardware and software are based on low-cost devices and can be modified to suit different control systems. The details of the implementation are available on a free online repository.

关键词： Discrete-Event Systems Supervisory control Deception attacks Networked Control

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A weighted multivariate fuzzy time series method for multiple output high-dimensional time series forecasting in IoT applications

A weighted multivariate fuzzy time series method for multipl...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Hugo Vinicius Bitencourt Patrícia de Oliveira Lucas Omid Orang Petrônio Silva Frederico Gadelha Guimarães Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Instituto Federal do Norte de Minas Gerais Salinas MG Brazil Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Instituto Federal do Norte de Minas Gerais Januária MG Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple factors and criteria that demand forecasting these time series. This paper introduces MO-WMVFTS, a novel multiple-input multiple-output (MIMO) fuzzy time series (FTS) method for tackling this complex scenario. MO-WMVFTS is a hybrid forecasting method that fuses weighted multivariate FTS (WMVFTS) with embedding transformations, designed for IoT applications. To assess the performance of the proposed method, it was applied to the prediction of energy consumption in smart homes and air quality in smart cities. Here, three real-world datasets are used to assess the validity of our proposed approach, and the results obtained are highly competitive when compared to other existing methods.

关键词： Smart buildings Smart cities Soft sensors Time series analysis Smart homes Predictive models Internet of Things Forecasting Streams MIMO communication

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Adaptive Environment-Aware Robotic Arm Reaching Based on a Bio-Inspired Neurodynamical Computational Framework

arXiv

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arXiv 2024年

作者： Chatziparaschis, Dimitrios Zhong, Shan Christopoulos, Vasileios Karydis, Konstantinos Dept. of Electrical and Computer Engineering Univ. of California Riverside 900 University Avenue RiversideCA92521 United States Neuroscience graduate program Univ. of California Riverside 900 University Avenue RiversideCA92521 United States Dept. of Bioengineering Univ. of California Riverside 900 University Avenue RiversideCA92521 United States

Bio-inspired robotic systems are capable of adaptive learning, scalable control, and efficient information processing. Enabling real-time decision-making for such systems is critical to respond to dynamic changes in the environment. We focus on dynamic target tracking in open areas using a robotic six-degree-of-freedom manipulator with a bird-eye view camera for visual feedback, and by deploying the Neurodynamical Computational Framework (NeuCF). NeuCF is a recently developed bio-inspired model for target tracking based on Dynamic Neural Fields (DNFs) and Stochastic Optimal Control (SOC) theory. It has been trained for reaching actions on a planar surface toward localized visual beacons, and it can re-target or generate stop signals on the fly based on changes in the environment (e.g., a new target has emerged, or an existing one has been removed). We evaluated our system over various target-reaching scenarios. In all experiments, NeuCF had high end-effector positional accuracy, generated smooth trajectories, and provided reduced path lengths compared with a baseline cubic polynomial trajectory generator. In all, the developed system offers a robust and dynamic-aware robotic manipulation approach that affords real-time decision-making. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Hot Carrier Injection Reliability of Fabricated N- and P-Type Multi FinFETs with Different TiN Stacks

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ECS Journal of Solid State Science and Technology 2023年第3期12卷 035007-035007页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Hsu, Heng-Tung Chen, Ke-Horng Lin, Wen-Chin Yu, Tien-Han Chou, Hung-Ting Godwin Raj, D. Godfrey, D. International College of Semiconductor Technology National Yang Ming Chiao Tung University Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan National Applied Research Laboratories Taiwan Institute of Microelectronics National Cheng Kung University Taiwan National Chung-Shan Institute of Science and Technology Taoyuan Taiwan Dept of ECE Amal Jyothi College of Engineering Kerala India Dept of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India

Device degradation due to hot carrier injection (HCI) in multi-fin 20 nm and 10 nm N- and P-type FinFET devices are thoroughly analyzed. To further understand the HCI reliability of the four FinFET devices, the device is fabricated with a standard Vt base and low Vt base gate stacks with different work functions. It is evident that: (i) The standard Vt device sustains lower effective stress bias due to the difference in threshold voltage, resulting in a more stable threshold voltage than the low Vt base device, and (ii) the transconductance of the single N- and P-type FinFET is more severely degraded than the multi-fin N- and P-type FinFET, mainly because multi N- and P-type Finfet has coupe effect, which effectively reduces the impact of HCI. © 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited

关键词： FinFET

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