Azure SQL Edge, a robust Internet of Things (IoT) database for edge computing, combines capabilities such as data streaming and time series with built-in machine learning and graph features. Extend the industry-leading Microsoft SQL engine to edge devices for consistent performance and security across your entire data estate, from cloud to edge. Develop your applications once and deploy them anywhere across the edge, your on-premises datacenter, or Azure.

Detect anomalies and apply business logic at the edge using the built-in machine learning capabilities. Choose from popular machine learning languages and convert them using the Open Neural Network Exchange (ONNX) to process time-series, graph, and other types of data. Deploy your cloud-trained models onto edge servers, gateways, and devices to perform real-time analytics on streaming data.


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Use the same high-performing, secure engine as SQL Server and Azure SQL Database to meet the demands of edge computing. Get flexible high availability and disaster recovery using Kubernetes or other container orchestration, and help protect data on your edge devices using industry-leading security tools such as transparent data encryption, data masking, and Always Encrypted.

Install and manage Azure SQL Edge on all your edge devices without a large team of database administrators. Create and deploy the container from a single management portal, and update the container and data schema based on your security-management and business needs.

Use a single container for your local streaming, storage, and machine learning. Because the surface area is the same as SQL Database and SQL Server running on premises, Azure SQL Edge extends a consistent application development and management experience to the edge. Develop once and run your applications wherever you need them.

Azure SQL Edge does all that and also includes the capabilities of SQL Database for storage, processing, and analysis of data at the edge. Use Azure SQL Edge in a disconnected, semi-connected, or rarely connected deployment where local storage and analytics are important.

AWS Snowball Edge now supports Windows operating systems, including Windows Server 2012 R2, Windows Server 2016, and Windows Server 2019. Previously, you were able to run instances on Snowball devices using either the Ubuntu or CentOS Linux operating systems. Now, with support for Windows, you can run your Windows-based workloads at the edge on Snowball Edge Compute Optimized and Snowball Edge Storage Optimized devices.

For the past week my microsoft edge has been generating a .log file. I noticed it in my av log during a random check. But, the thing that has me perplexed is the log time updates every thirty minutes or so. Example, I check the log at 6 am ... it would say the log was done at 5:30 am. If I check back at 6:30 the time would change to 6am.

The application was upgraded to 64 bits. The installation path changed to C:\Program Files\Docker\Docker. Users might need to close any Powershell/Cmd windows that were already open before the update to get the new PATH. In some cases, users may need to log off and on again.

The application was upgraded to 64 bits. The installation path changed to C:\Program Files\Docker\Docker. If users have PowerShell/Cmd windows already open before the update, they might need to close them to catch the new PATH. In some cases, users need to log off and on again.

Most web browsers include a feature to block pop-up windows. While this may eliminate unwanted or bothersome pop-up windows, the feature sometimes can impede the functionality of legitimate or useful websites.

Some popular Penn-affiliated websites requiring pop-ups include U@Penn and the Penn Online Directory.


Follow the instructions below to configure your web browser to allow pop-up windows for your selected websites.

Note: If you have installed third party applications to block pop-ups (examples include the Google, MSN, and Yahoo! toolbars), be sure to consult the vendor documentation to allow pop-up windows for desired websites.

When a website attempts to launch a new pop-up window, you may see dialog boxes alerting you of pop-up windows that have been blocked. Follow the instructions below to allow pop-up windows on a per-website basis.

To image the distribution of a specific element in a specimen with an energy filtering TEM, the element-unspecific background under the core-edge has to be subtracted. The most commonly used procedure is the three-window power-law method leading to considerable systematic errors for low-energy core-edges. Here a new method is described which can be considered as a generalized difference method. Characteristic examples for element detection in biological specimens using this method are shown. The background under the core-edge can be described by one or two pre-edge windows as a polynome of third order. This function can be deduced from specimen areas that are not known to contain the element or from a second specimen used as a standard. Control experiments showed that background subtraction for on-overlapping core-edges in the low-loss region (50-200 eV) needs two pre-edge images, whereas at higher-energy losses (> 300 eV) only one pre-edge image is necessary. With the method described, objective elemental mapping becomes possible even for edges at 50-100 eV. This was proven for the M2,3-edge of iron at 60 eV. The detection of phosphorous was possible with a signal-to-noise ratio five times higher than when using the three-window method. Preliminary data showed that it should be possible to detect calcium with only one image before the edge.

A new concept for the mounting of spherical sector windows has been experimentally evaluated under short-term, long-term, and cyclic pressure loadings. The new mounting concept requires that the spherical sector windows be provided with square edges instead of conical edges. The horizontal bearing surface of the square edge carries the axial and the vertical bearing surface the radial thrust of the spherical sector window. Experimental evaluation of the new mounting concept has shown that the spherical windows with square edges are subjected to larger flexure moments than similar windows with conical edges. However, the short-term critical pressures of spherical sector windows with square edges and included angle 75 deg <  < 180 deg were found to be only 10 percent less than those of similar windows with conical edges. For spherical sectors with  < 75 deg the square edge mounting provides significantly higher short-term implosion pressures than conical edge mountings. Based on the short-term critical pressures, strains, stresses, and cyclic fatigue data generated by this study, the spherical shell sector windows with square edge mounting are considered acceptable for service in manned submersibles, habitats, or diving bells. e24fc04721

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