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Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA

Health Data science 2021年第1期2021卷 78-87页

作者： Raj Dandekar Emma Wang George Barbastathis Chris Rackauckas Department of Computational Science and Engineering Massachusetts Institute of TechnologyCambridgeUSA MA 02139 Department of Electrical Engineering and Computer Sciences Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 138602 Department of Applied Mathematics Massachusetts Institute of TechnologyCambridgeMA 02139USA

In the wake of the rapid surge in the COVID-19-infected cases seen in Southern and West-Central USA in the period of June-July 2020,there is an urgent need to develop robust,data-driven models to quantify the effect which early reopening had on the infected case count *** particular,it is imperative to address the question:How many infected cases could have been prevented,had the worst affected states not reopened early?To address this question,we have developed a novel COVID-19 model by augmenting the classical SIR epidemiological model with a neural network *** model decomposes the contribution of quarantine strength to the infection time series,allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in *** show that the upsurge in the infected cases seen in these states is strongly corelated with a drop in the quarantine/lockdown strength diagnosed by our ***,our results demonstrate that in the event of a stricter lockdown without early reopening,the number of active infected cases recorded on 14 July could have been reduced by more than 40%in all states considered,with the actual number of infections reduced being more than 100,000 for the states of Florida and *** we continue our fight against COVID-19,our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution,for any region under consideration.

关键词： COV neural Central

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Robust Beamforming Design for RSMA-Integrated Full-Duplex Communications: Energy and Spectral Efficiency Trade-off

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Allu, Raviteja Katwe, Mayur Singh, Keshav Cotton, Simon L. Li, Chih-Peng Duong, Trung Q. National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan National Institute of Technology Department of Electronics and Communication Engineering Chhattisgarh Raipur492010 India Queen's University Belfast Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom Memorial University Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada

In this paper, we investigate an unconventional full-duplex (FD) integrated rate-splitting multiple access (RSMA) scheme for improved spectral efficiency (SE) and energy efficiency (EE) performance when compared to the conventional power-domain schemes. In particular, we focus on improving the energy efficiency (EE) and spectral efficiency (SE) trade-off for the multiple users subject to robust beamforming design and smart inter-user interference mitigation under imperfect channel state information (CSI). We formulate a multi-objective optimization (MOO) problem, specifically aiming to jointly maximize EE and SE within the FD-RSMA system by jointly optimizing the resource allocation subject to the limits on transmit power and minimum rate, under the assumption of a CSI error model with a bound. Initially, the MOO problem is converted into a single objective optimization (SOO) problem using the weighted sum method, with a trade-off parameter. An iterative algorithm is employed, utilizing successive convex approximation and the S-procedure to achieve near-optimal resource allocation for the transformed SOO problem, with a particular emphasis on effective interference management. Simulation results highlight the effectiveness of the FD-RSMA scheme, demonstrating its superiority over the multi-user FD space division multiple access by 16.93 % and non-orthogonal multiple access scheme by 76.04 %. © 2017 IEEE.

关键词： Spectrum efficiency

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Simulation of Hybrid TWDM-PON with broadband AWG in topology 23

Simulation of Hybrid TWDM-PON with broadband AWG in topology

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23rd Slovak-Czech-Polish Optical Conference on Wave and Quantum Aspects of Contemporary Optics

作者： Šiška, Petr Látal, Jan Hejduk, Stanislav Seyringer, Dana Dohnal, Fadi Chovan, Jozef Uherek, František Štípal, Jiří Trubák, Kamil Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava 17. listopadu 2172/15 Ostrava-Poruba708 00 Czech Republic Research Centre for Microtechnology Vorarlberg University of Applied Sciences Hochschulstraße 1 Dornbirn6850 Austria Slovak Centre of Scientific and Technical Information International Laser Centre Ilkovičova 3 Bratislava841 04 Slovakia Institute of Electronics and Photonics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovičova 3 Bratislava812 19 Slovakia

ISBN: (数字)9781510688094

ISBN: (纸本)9781510688087

This work deals with the study of implementation possibilities of broadband optical multiplexer/demultiplexer in the form of AWG (Arrayed Waveguide Gratings) in TWDM-PON topology (Time and Wavelength Division Multiplexing Passive Optical Network) by norm G.989.1 as a key component of the hybrid network. The functionality possibilities of the TWDM-PON system are observed where the goal of AWG design is to support also wavelengths different from standard wavelengths used for TWDM-PON in C-band (Conventional) ranges from 1530 nm to 1565nm and L-band (Long-wavelength, 1565-1625nm) bands. This should allow for older communication systems (for example EPON (Ethernet Passive Optical Network) given by norm IEEE 802.3ah and GPON (Gigabit-capable Passive Optical Network) by norm ITU-T G.984) to be operating concurrently over ODN (optical distribution network) without mutual disturbance with newer xPON communication systems. The network topology operating in this manner makes efficient use of passive infrastructure, including reducing the cost of construction (CAPEx) or operation (OPEx) while creating hybrid types of optical networks. © 2025 SPIE.

关键词： Arrayed waveguide gratings

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Characterizations of Second-order Nonlinear Optical Susceptibility for ϵ-phase Gallium Oxide

Characterizations of Second-order Nonlinear Optical Suscepti...

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2022 Compound Semiconductor Week, CSW 2022

作者： Zhou, Jingan Zhao, Xuan Xu, Rui Fu, Kai Li, Tao Xu, Mingfei He, Ziyi Robinson, Jacob T. Zhu, Hanyu Zhang, Xiaodong Zhao, Yuji Rice University Department of Electrical and Computer Engineering HoustonTX77005 United States Rice University Smalley-Curl Institute Applied Physics Graduate Program HoustonTX77005 United States Rice University Department of Materials Science and NanoEngineering HoustonTX77005 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85287 United States Suzhou Institute of Nano-tech and Nano-bionics CAS Key Laboratory of Nanodevices and Applications Suzhou215123 China

ISBN: (数字)9781665453400

ISBN: (纸本)9781665453400

In this work, we report the second-order nonlinear optical susceptibility χ(2) for epsilon phase Gallium Oxide (ϵ-Ga2O3) thin film on sapphire. ϵ-Ga2O3 exhibits hexagonal P63mc space group symmetry, which is a non-centrosymmetric structure with non-zero second order susceptibility. By focusing a pulsed laser beam on to a polished ϵ-Ga2O3 thin film, we collected the generated second harmonic photons with an ultra-sensitive femtowatt photodetector, obtaining effective second-order nonlinear optical susceptibility of χ(2) = 4.89×10-3 pm/V at wavelength of 800 nm. Two different measurement systems collecting reflected and transmitted photons were applied separately to make the result more convincing. The wavelength dependence from 790 nm to 900 nm and polarization dependence from TM mode to TE mode were measured as well. These results will be helpful for the design and fabrication of Ga2O3 based integrated photonics platform in the infrared-visible spectral range. © 2022 IEEE.

关键词： Gallium compounds

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GPT-Based Automated Induction: Vulnerability Detection in Medical Software

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Deng, Liangjun Lei, Hang Khan, Fazlullah Srivastava, Gautam Chen, Jingxue Haque, Mainul University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China University of Nottingham Ningbo China School of Computer Science and the Next-Generation Internet of Everything Laboratory Faculty of Science and Engineering Zhejiang Ningbo315104 China Lovely Professional University Division of Research and Development Phagwara India Chandigarh University University Centre of Research and Development Mohali India Brandon University Department of Math and Computer Science BrandonMBR7A 6A9 Canada China Medical University Research Centre for Interneural Computing Taichung40402 Taiwan Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact & Outcome Punjab Rajpura140401 India University of Nottingham Ningbo China Department of Mathematics Faculty of Science and Engineering Zhejiang Ningbo315104 China

Integrating Natural Language Processing (NLP) with Generative Pre-trained Transformer (GPT) models plays a pivotal role in enhancing the accuracy and efficiency of healthcare software, which is essential for patient safety and providing high-quality care. The precision of healthcare software is fundamental to protecting the well-being of the patient. In addition, it can ensure the delivery of superior care, maintain the integrity of healthcare systems, and promote trust and cost-effectiveness. It is necessary to emphasize the importance of software reliability in its development and deployment. Symbolic execution serves as a vital technology in automated vulnerability detection. However, symbolic execution often faces problems such as path explosion, which seriously affects efficiency. Although there have been several studies to reduce the number of computational paths in symbolic execution, this problem remains a major obstacle. Therefore, more efficient solutions are urgently needed to ensure the software security. This paper proposes a large-scale language model(LLM) induction method mitigating path explosion applied to symbolic execution engines. In contrast to traditional symbolic execution engines, which often result in timeout or out-of-memory detection, our approach achieves the task of detecting vulnerabilities in seconds. Furthermore, our proposal improves the scalability of symbolic execution, allowing more extensive and complex programs to be analyzed without significant increases in computational resources or time. This scalability is crucial to tackling modern software systems and improving the efficiency and effectiveness of automated defect verification in healthcare software. © 2025 IEEE. All rights reserved,

关键词： Scalability

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Enhancing IoT Intelligence: A Transformer-based Reinforcement Learning Methodology

arXiv

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arXiv 2024年

作者： Rjoub, Gaith Islam, Saidul Bentahar, Jamal Almaiah, Mohammed Amin Alrawashdeh, Rana Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Department of Computer Science Khalifa University Abu Dhabi United Arab Emirates King Abdullah II School of Information Technology The University of Jordan Amman Jordan Faculty of Information Technology Applied Science Private University Amman Jordan Department of Information and Computer Science King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

The proliferation of the Internet of Things (IoT) has led to an explosion of data generated by interconnected devices, presenting both opportunities and challenges for intelligent decision-making in complex environments. Traditional Reinforcement Learning (RL) approaches often struggle to fully harness this data due to their limited ability to process and interpret the intricate patterns and dependencies inherent in IoT applications. This paper introduces a novel framework that integrates transformer architectures with Proximal Policy Optimization (PPO) to address these challenges. By leveraging the self-attention mechanism of transformers, our approach enhances RL agents’ capacity for understanding and acting within dynamic IoT environments, leading to improved decision-making processes. We demonstrate the effectiveness of our method across various IoT scenarios, from smart home automation to industrial control systems, showing marked improvements in decision-making efficiency and adaptability. Our contributions include a detailed exploration of the transformer’s role in processing heterogeneous IoT data, a comprehensive evaluation of the framework’s performance in diverse environments, and a benchmark against traditional RL methods. The results indicate significant advancements in enabling RL agents to navigate the complexities of IoT ecosystems, highlighting the potential of our approach to revolutionize intelligent automation and decision-making in the IoT landscape. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Laminar and transiently disordered dynamics of magnetic-skyrmion pipe flow

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Physical Review B 2023年第14期108卷 144428-144428页

作者： Xichao Zhang Jing Xia Oleg A. Tretiakov Motohiko Ezawa Guoping Zhao Yan Zhou Xiaoxi Liu Masahito Mochizuki Department of Applied Physics Waseda University Okubo Shinjuku-ku Tokyo 169-8555 Japan Department of Electrical and Computer Engineering Shinshu University 4-17-1 Wakasato Nagano 380-8553 Japan School of Physics The University of New South Wales Sydney New South Wales 2052 Australia Department of Applied Physics The University of Tokyo 7-3-1 Hongo Tokyo 113-8656 Japan College of Physics and Electronic Engineering Sichuan Normal University Chengdu 610068 China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Guangdong 518172 China

The world is full of fluids that flow. The fluid nature of flowing skyrmionic quasiparticles is of fundamental physical interest and plays an essential role in the transport of many skyrmions. Here, we report the laminar and transiently disordered dynamic behaviors of many magnetic skyrmions flowing in a pipe channel. The skyrmion flow driven by a uniform current may show a lattice structural transition. The skyrmion flow driven by a nonuniform current shows a dynamically varying lattice structure. A large uniform current could result in the compression of skyrmions toward the channel edge, leading to the transition of the skyrmion pipe flow into an open-channel flow with a free surface. Namely, the width of the skyrmion flow could be adjusted by the driving current. Skyrmions on the free surface may form a single shear layer adjacent to the main skyrmion flow. In addition, although we focus on the skyrmion flow dynamics in a clean pipe channel without any pinning or defect effect, we also show that variation of the magnetic anisotropy in the pipe channel could lead to more complicated skyrmion flow dynamics and path lines. Our results reveal the fluid nature of skyrmionic quasiparticles, which may motivate future research on the complex flow physics of magnetic textures.

关键词： Channel flow Dynamical phase transitions Laminar flows Magnetism Skyrmions Spintronics Transport phenomena Turbulence Interfaces Nanostructures Micromagnetic modeling

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Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenera...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Mateusz Daniol Daria Hemmerling Jakub Sikora Pawel Jemiolo Marek Wodzinski Magdalena Wojcik-Pedziwiatr Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Kraków Krakow Poland Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland Department of Neurology Andrzej Frycz Modrzewski Krakow University Krakow Poland

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Parkinson’s disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to capture eye-tracking signals through Mixed Reality technology for the evaluation of neurodegenerative diseases. Additionally, we introduce a pipeline for extracting clinically relevant features from eye-gaze analysis, describing the capabilities of the proposed system from a medical perspective. The study involved a cohort of healthy control individuals and patients suffering from Parkinson’s disease, showcasing the feasibility and potential of the proposed technology for non-intrusive monitoring of eye movement patterns for the diagnosis of neurodegenerative *** relevance— Developing a non-invasive biomarker for Parkinson’ s disease is urgently needed to accurately detect the disease’s onset. This would allow for the timely introduction of neuroprotective treatment at the earliest stage and enable the continuous monitoring of intervention outcomes. The ability to detect subtle changes in eye movements allows for early diagnosis, offering a critical window for intervention before more pronounced symptoms emerge. Eye tracking provides objective and quantifiable biomarkers, ensuring reliable assessments of disease progression and cognitive function. The eye gaze analysis using Mixed Reality glasses is wireless, facilitating convenient assessments in both home and hospital settings. The approach offers the advantage of utilizing hardware that requires no additional specialized attachments, enabling examinations through personal eyewear

关键词： Wireless communication Tracking Pipelines Mixed reality Gaze tracking Feature extraction Reliability Monitoring Medical diagnostic imaging Diseases

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Analysis and Prediction of Wear Characteristics of Sustainable Metal Matrix Composites Using Machine Learning with Decision Making Algorithm

Analysis and Prediction of Wear Characteristics of Sustainab...

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Smart Electronics and Communication (ICOSEC), International Conference on

作者： Vaishali N. Agme Ashish Rushali Pant Mulagundla Sridevi A. Suman M. Vijaya Sekhar Babu Department of Applied Science Bharati Vidyapeeth College of Engineering Navi Mumbai Maharashtra India Department of CSE Koneru Lakshmaiah Education Foundation (KLEF) - KL Deemed University Vaddeswaram Andhra Pradesh India ME Dehradun R/S Graphic Era Deemed To Be University Dehradun India Department of Computer Science and Engineering CVR College of Engineering Mangalpalli (V) Ibrahimpatnam (M) Telangana India Department of Mathematics Audisankara College of Engineering and Technology Gudur Tirupati Andhra Pradesh India Department of Mechanical Engineering GIET Engineering College Rajamahendravaram Andhra Pradesh India

The goal of this research was to analyse and predict the wear characteristics of sustainable metal matrix composites using machine learning with a decision-making algorithm. The study used Al 7072 alloy with nano-particle SiC as an alloying element, which was added in three different compositions (0.3 %, 0.6%, and 0.9 % ) through stir casting. The experiment was based on the Taguchi L27 orthogonal array and an Artificial Neural Network (ANN) was utilised as a machine learning approach to predict the responses with 100% accuracy. The input parameters were composition (C), load (R), and rotation speed (S), while the responses were the Specific wear rate (Spr) and friction coefficient (Fc), which were optimised using the Taguchi combined optimisation technique. The results showed that the ANN approach was effective in predicting the wear characteristics of the sustainable metal matrix composites and the Taguchi combined optimisation technique improved the wear resistance and friction coefficient. This study provides a valuable contribution to the field of sustainable materials, as the findings can be used to improve the design and production of sustainable metal matrix composites with improved wear characteristics, which can lead to a reduction in energy consumption and environmental impact.

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FraMark: A Blockchain Marketplace for a 5G Network Management using Fractional NFTs 7

FraMark: A Blockchain Marketplace for a 5G Network Managemen...

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7th World Symposium on Communication engineering, WSCE 2024

作者： Michoulis, George Tsourdinis, Kyros Niotis, George Kyranou, Konstantinos Fountoukidis, Eleutherios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis Psannis, Konstantinos E. Goudos, Sotirios K. Sidroco Holdings Ltd R&D Dpt. Thessaloniki Greece Sidroco Holdings Ltd R&D Dpt. Nicosia Cyprus Democritus University of Thrace Dpt. of Computer Science Kavala Greece University of Western Macedonia Dpt. of Electrical & Computer Engineering Kozani Greece Kingston University London Kingston Upon Thames Dpt. of Networks and Digital Media Surrey United Kingdom University of Macedonia Department of Applied Informatics Thessaloniki Greece ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9798331542825

This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework's claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management. © 2024 IEEE.

关键词： 5G mobile communication systems

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