发帖
雷达卡
摘要翻译：
病毒和细菌等病原体在人类生活中起着至关重要的作用，因为它们会引起传染病，从而导致流行病。最近的冠状病毒肺炎2019疫情表明，采取戴口罩等有效预防措施对减少人类死亡和疫情副作用至关重要。因此，必须准确地模拟传染病的传播，传染病的最重要传播途径之一是空气传播。文献中的传播模型是由不同学科的研究人员在不同的尺度上独立提出的。因此，有必要合并所有这些研究尝试。为此，我们提出了一种通信工程方法，将流行病学、生物学、医学和流体力学等不同学科融于同一锅中，以模拟空气传播的病原体在人类之间的传播。在该方法中，我们引入了移动人类ad hoc网络（MoHANETs）的概念。该概念利用了机载传输驱动的人类群体与移动ad hoc网络的相似性，并使用分子通信作为使能范式。本文的目的是提出一个统一的通信工程框架，并突出未来研究方向的传染病传播模型通过空气传播病原体在人与人之间的传播。本文首先综述了空气中病原菌的传播机制。然后，给出了具有分层结构的MoHANET。在这些层中，通过空气散发携带病原体的飞沫的传染性人体和接触这些飞沫的人体分别被认为是发射者和接收者。此外，还对该方法的实验方法进行了评述和讨论。
---
英文标题：
《Mobile Human Ad Hoc Networks: A Communication Engineering Viewpoint on
Interhuman Airborne Pathogen Transmission》
---
作者：
Fatih Gulec and Baris Atakan
---
最新提交年份：
2020
---
分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
--
一级分类：Computer Science 计算机科学
二级分类：Social and Information Networks 社会和信息网络
分类描述：Covers the design, analysis, and modeling of social and information networks, including their applications for on-line information access, communication, and interaction, and their roles as datasets in the exploration of questions in these and other domains, including connections to the social and biological sciences. Analysis and modeling of such networks includes topics in ACM Subject classes F.2, G.2, G.3, H.2, and I.2; applications in computing include topics in H.3, H.4, and H.5; and applications at the interface of computing and other disciplines include topics in J.1--J.7. Papers on computer communication systems and network protocols (e.g. TCP/IP) are generally a closer fit to the Networking and Internet Architecture (cs.NI) category.
涵盖社会和信息网络的设计、分析和建模，包括它们在联机信息访问、通信和交互方面的应用，以及它们作为数据集在这些领域和其他领域的问题探索中的作用，包括与社会和生物科学的联系。这类网络的分析和建模包括ACM学科类F.2、G.2、G.3、H.2和I.2的主题；计算应用包括H.3、H.4和H.5中的主题；计算和其他学科接口的应用程序包括J.1-J.7中的主题。关于计算机通信系统和网络协议（例如TCP/IP）的论文通常更适合网络和因特网体系结构（CS.NI）类别。
--
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
--
---
英文摘要：
Pathogens such as viruses and bacteria play a vital role in human life, since they cause infectious diseases which can lead to epidemics. Recent coronavirus disease 2019 epidemic has shown that taking effective prevention measures such as wearing masks are important to reduce the human deaths and side effects of the epidemic. It is therefore requisite to accurately model the spread of infectious diseases whose one of the most crucial routes of transmission is airborne transmission. The transmission models in the literature are proposed independently from each other, at different scales and by the researchers from various disciplines. Thus, there is a need to merge all these research attempts. To this end, we propose a communication engineering approach that melts different disciplines such as epidemiology, biology, medicine, and fluid dynamics in the same pot to model airborne pathogen transmission among humans. In this approach, we introduce the concept of mobile human ad hoc networks (MoHANETs). This concept exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. The aim of this article is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases among humans through airborne pathogen transmission. In this article, we first review the airborne pathogen transmission mechanisms. Then, the MoHANET is given with a layered structure. In these layers, the infectious human emitting pathogen-laden droplets through air and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Moreover, the experimental methods for the proposed approach are reviewed and discussed.
---
PDF链接：
https://arxiv.org/pdf/2011.00884
京公网安备 11010802022788号
