Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies

The year 2020 saw the covid-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world have been faced with the challenge of protecting public health while keeping the economy running to the greatest extent possible. Epidemiological models provide insight into the spread of these types of diseases and predict the e_ects of possible intervention policies. However, to date, even the most data-driven intervention policies rely on heuristics. In this paper, we study how reinforcement learning (RL) and Bayesian inference can be used to optimize mitigation policies that minimize economic impact without overwhelming hospital capacity. Our main contributions are (1) a novel agent-based pandemic simulator which, unlike traditional models, is able to model _ne-grained interactions among people at speci_c locations in a community; (2) an RL- based methodology for optimizing _ne-grained mitigation policies within this simulator; and (3) a Hidden Markov Model for predicting infected individuals based on partial observations regarding test results, presence of symptoms, and past physical contacts

Исследование влияния технологического процесса изготовления обмоток на дефектность корпусной изоляции асинхронных двигателей

В работе проведено исследование влияния колебаний режимов работы статорообмоточных станков WST-660 и пазоизолировочных станков ИПС-3 на дефектность корпусной изоляции. Получены математические модели дефектообразования в корпусной изоляции обмотки с учетом режимов работы технологического оборудования и качества материала корпусной изоляции в состоянии поставки. Установлено, что изменением режимов работы технологического оборудования можно добиться требуемого качества корпусной изоляции при максимальной производительности оборудования

Wind Field of a Nonmesocyclone Anticyclonic Tornado Crossing the Hong Kong International Airport

A nonmesocyclone tornado traversed the Hong Kong International Airport on September 6, 2004 directly impacting a surface weather station. This allowed for 1-second 10-meter above ground level (AGL) wind observations through the core of the tornado. Integration of these 10-meter AGL wind data with Ground-Based Velocity Track (GBVTD) wind retrievals derived from LIDAR data provided a time history of the three-dimensional wind field of the tornado. These data indicate a progressive decrease in radial inflow with time and little to no radial inflow near the time the tornado crosses the surface weather station. Anemometer observations suggest that the tangential winds approximate a modified-Rankine vortex outside the radius of maximum winds, suggesting that frictionally induced radial inflow was confined below 10 m AGL. The radial-height distribution of angular momentum depicts an increase in low-level angular momentum just prior to the tornado reaching its maximum intensity

The Use of Software Agents for Autonomous Control of a DC Space Power System

In order to enable manned deep-space missions, the spacecraft must be controlled autonomously using on-board algorithms. A control architecture is proposed to enable this autonomous operation for an spacecraft electric power system and then implemented using a highly distributed network of software agents. These agents collaborate and compete with each other in order to implement each of the control functions. A subset of this control architecture is tested against a steadystate power system simulation and found to be able to solve a constrained optimization problem with competing objectives using only local information

Some Economics of Market-Based Distributed Scheduling

Market mechanisms solve distributed scheduling problems by allocating the scheduled resources according to market prices. We model distributed scheduling as a discrete resource allocation problem, and demonstrate the applicability of economic analysis to this framework. Drawing on results from the literature, we discuss the existence of equilibrium prices for some general classes of scheduling problems, and the quality of equilibrium solutions. We then present two protocols for implementing market solutions, and analyze their computational and economic properties.http://deepblue.lib.umich.edu/bitstream/2027.42/60422/1/mb-scheduling-extended.pd

Observational and Modeling Analysis of Land–Atmopshere Coupling over Adjacent Irrigated and Rainfed Cropland during the GRAINEX Field Campaign

The Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 to investigate Land-Atmosphere (L-A) coupling just prior to and through the growing season across adjacent, but distinctly unique, soil moisture regimes (contrasting irrigated and rainfed fields). GRAINEX was uniquely designed for the development and analysis of an extensive observational dataset for comprehensive process studies of L-A coupling, by focusing on irrigated and rainfed croplands in a ~100 x 100 km domain in southeastern Nebraska. Observation platforms included multiple NCAR EOL Integrated Surface Flux Systems and Integrated Sounding Systems, NCAR CSWR Doppler Radar on Wheels, 1200 radiosonde balloon launches from 5 sites, the NASA GREX airborne L-Band radiometer, and 75 University of Alabama-Huntsville Environmental Monitoring Economic Monitoring Sensor Hubs (EMESH mesonet stations). An integrated observational and modeling approach to advance knowledge of L-A coupling processes and precipitation impacts in regions of heterogeneous soil moisture will be presented. Specifically, through observation of land surface states, surface fluxes, near surface meteorology, and properties of the atmospheric column, an examination of the diurnal planetary boundary layer evolving characteristics will be presented. Results from a hierarchy of modeling platforms (e.g. single column, large-eddy, and mesoscale simulations) will also be presented to complement the observational findings. The modeling effort will generate high spatiotemporal resolution datasets to: 1) generate a multi-physics ensemble to test the robustness and potentially advance physical parameterizations in high resolution weather and climate models, 2) comparison of prescribed forcing from observations and those from offline land surface model simulations and high resolution operational analyses, 3) determine the ability of model simulations to reproduce observed boundary layer evolution, with particular attention to the processes that compose the L-A coupling chain and metrics (e.g. mixing ratio diagrams), and 4) in combination with observations, isolate the impacts of soil moisture heterogeneity on planetary boundary layer characteristics, cloud development, precipitation, mesoscale circulation patters and boundary layer development. Initial results from the observational and modeling analysis will be presented