The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Bracher. Enhancing Mobile Ad Hoc Network Connectivity A MECHANISM FOR ENHANCING INTERNET CONNECTIVITY FOR MOBILE AD

ABSTRACT: Mobile ad hoc networks are an emerging wireless technology which differs from other networking technologies in that they are infrastructureless, autonomous, stand-alone networks. Although these characteristics enable simple deployment, ad hoc networks are limited in terms of connectivity as communication is confined to the boundaries of the local network. Due to this constraint, plus the growing trend towards establishing an "all IP environment", efforts are being made to integrate ad hoc networks with Mobile IP in order to ultimately bridge ad hoc networks to the Internet. This paper focuses on the connectivity of ad hoc network hosts to the Internet and proposes a mechanism for extending the periods of reachability of these hosts from the viewpoint of external hosts. From the simulation tests conducted on the custom built network simulator used to implement this proposal, positive results were produced showing an overall increase in the reachability times of ad hoc network hosts plus a decrease in the percentage of packet loss of incoming packets to the ad hoc network

Towards evidence-based trust brokering

Abstract — In a global computing environment, trust management is important for entities to collaborate. Traditional access control methods cannot meet the needs of autonomous decision making with partial information. The SECURE project introduced a collaboration model using the combination of trust and risk models. This allows an entity to formulate trust according to its own observations and also by accepting recommendations from other entities. Evidence, which originates from other entities, must be gathered in a secure way to ensure that integrity is maintained. This paper introduces a trust broker model which describes how one entity can locate and retrieve evidence on another entity’s historic behavior. This evidencebased trust brokering approach provides a basic model for secure evidence gathering and is appropriate for the global computing environment. I

Detecting anomalous user activity

Systems, methods and articles for determining anomalous user activity are disclosed. Data representing a transaction activity corresponding to a plurality of user transactions can be received and user transactions can be grouped according to types of user transactions. The transaction activity can be determined to be anomalous in relation to the grouped user transactions based on a predetermined parameter