Abstract: Provided herein are exemplary embodiments including a computer-implemented method of using artificial intelligence for automatically collecting and enriching network data for a smart campaign with autopilot features. The method includes, collecting a set of network data relevant to a smart campaign with autopilot features, applying one or more transformations to the collected set of data to create a modified set of data, generating from the modified set of data, enriched network data for a smart campaign with autopilot features, the enriched network data having content, context and event data, and using the enriched data to deploy a personalized campaign by identifying an audience, time, channel, content and goal of the communication.

Abstract: Methods and systems are provided for communication of one or more campaigns via personalized electronic messaging. An example method includes automatically creating an electronic communication personalized for each of a plurality of individual customers of a client. The automatically creating may include dynamic configuring the electronic communication for each individual customer into a single campaign for the client to optimize both relevancy for each of a plurality of individual customers and one or more desired business outcomes for the client. The dynamic configuring can include decision making using at least a business context. Performance goals of a business can comprise the business context. The decision-making can further use a user context and/or an external context. The electronic communication can be dynamically configured to include personalized recommendations and may further include personalized content and/or a personalized offer.

Abstract: Embodiments of the present disclosure provide unmanned aerial vehicle-based measurement techniques for building envelope surfaces One such method comprises acquiring, by an unmanned aerial vehicle, an air velocity measurement at an external surface of the high-rise building at a point on the external surface; acquiring, by the unmanned aerial vehicle, an external temperature at the external surface of the high-rise building at the point on the external surface; acquiring, by an infrared camera sensor of the unmanned aerial vehicle, IR measurements at the external surface of the high-rise building at the point on the external surface; and transferring, by the unmanned aerial vehicle, the IR measurements and the external air velocity and temperature measurements to a remote base station, wherein a current thermal performance of the external surface of the high-rise building is determined using the external air velocity, temperature, and IR measurements.

Abstract: A vacuum insulated glazing includes first and second spaced apart glass panes having perimeter portions defining a vacuum space between the glass panes. A vacuum valve is positioned at the perimeter portions of the glass panes and includes a valve body extending between the perimeter portions of the glass panes, and having first and second ends and a fluid conduit extending from the first end to the second end of the valve body and in fluid communication with the vacuum space. A one-way valve in the fluid conduit permits fluid flow from the vacuum space, and prevents fluid flow into the vacuum space. A suction fitting is provided for connecting the valve body to a suction device. An end seal between the perimeter portions of the glass panes is provided for hermetically sealing the vacuum space. A valve for a VIG and a method of making a VIG are also disclosed.

Abstract: Exemplary embodiments include a reinforcement learning model configured at a given point in time to receive digital data about a state of a user at the given point in time, receive digital data about an environment at the given point in time, receive digital data about a campaign at the given point in time, optimize total expected future number of positive rewards at the given point in time, and to execute an action at the given point in time. The state of the user at the given point in time may be a number of communications the user has received in a particular time period, a time since a last communication, the user's past behavior, and/or the user's engagement score from a predictive model to engage with a communication.

Abstract: Methods and corresponding systems are provided for configuring communications to customers when there are multiple campaigns scheduled in a given period. An optimal number of communications are sent prioritized according to business or performance measures where send times are spaced out in a manner that strives to attain the highest value. An example method includes determining a number of electronic communications, for a plurality of campaigns to send to the particular customer during a particular time period; determining the optimal send time during the particular time period; determining for which campaigns the particular customer is eligible; for each determined optimal time: determining a strategy including selecting an electronic communication for one of the campaigns to send to the eligible particular customer so as to maximize the value over the particular time period; and causing the selected electronic communication to be sent to the particular customer at the determined optimal time.

Abstract: Provisioning for a cloud service is provided. An instance of a provisioning object is created and initialized, and a graphical user interface (GUI) is generated. The GUI includes a home window, a configure window, an orchestrate window and a deploy window. The provisioning parameters are received from the GUI. The provisioning parameters indicate whether to deploy the software application on a local network or a remote network. A location object and a deployment object are created and initialized based on the provisioning parameters. The location object includes an on-premises object for a local network deployment or a cloud object for a remote network deployment. A command to deploy the software application is received from the GUI, and the software application is deployed to a local network or a remote network using the provisioning object, the location object and the deployment object.

Abstract: Methods and systems are provided for communication of one or more campaigns via personalized electronic messaging. An example method includes automatically creating an electronic communication personalized for each of a plurality of individual customers of a client. The automatically creating may include dynamic configuring the electronic communication for each individual customer into a single campaign for the client to optimize both relevancy for each of a plurality of individual customers and one or more desired business outcomes for the client. The dynamic configuring can include decision making using at least a business context. Performance goals of a business can comprise the business context. The decision-making can further use a user context and/or an external context. The electronic communication can be dynamically configured to include personalized recommendations and may further include personalized content and/or a personalized offer.

Abstract: Methods and corresponding systems are provided for configuring communications to customers when there are multiple campaigns scheduled in a given period. An optimal number of communications are sent prioritized according to business or performance measures where send times are spaced out in a manner that strives to attain the highest value. An example method includes determining a number of electronic communications, for a plurality of campaigns to send to the particular customer during a particular time period; determining the optimal send time during the particular time period; determining for which campaigns the particular customer is eligible; for each determined optimal time: determining a strategy including selecting an electronic communication for one of the campaigns to send to the eligible particular customer so as to maximize the value over the particular time period; and causing the selected electronic communication to be sent to the particular customer at the determined optimal time.

Abstract: Provisioning for a cloud service is provided. An instance of a provisioning object is created and initialized, and a graphical user interface (GUI) is generated. The GUI includes a home window, a configure window, an orchestrate window and a deploy window. The provisioning parameters are received from the GUI. The provisioning parameters indicate whether to deploy the software application on a local network or a remote network. A location object and a deployment object are created and initialized based on the provisioning parameters. The location object includes an on-premises object for a local network deployment or a cloud object for a remote network deployment. A command to deploy the software application is received from the GUI, and the software application is deployed to a local network or a remote network using the provisioning object, the location object and the deployment object.

Abstract: Disclosed herein are systems, methods, and software for enhancing application update processes. In an implementation, a delta file is received in a data center that hosts various instances of a service application. The delta file represents a difference between a new version of the service application and a previous version of the service application. An instance of the service application installed in the data center is removed from service temporarily in order to update it from the previous version of the service application to the new version of the service application. Upon initiating and completing an update of the instance of the service application to the new version of the service application using at least the delta file, the instance is returned to service.

Abstract: Technologies are described herein for implementing a windowed mid-tier data cache. A request is received for a data page comprising a set of data rows from a result set of a query in a database management system (“DBMS”). A determination is made whether the requested data rows exist in the mid-tier cache. If the requested rows exist in the cache, then the set of data rows is retrieved from the cache and the requested data page is returned. If the requested rows do not exist in the cache, a data chunk comprising a number of data rows from the result set larger than and encompassing the requested rows is requested from the DBMS. Upon receiving the data chunk, the data chunk is stored in the mid-tier cache, and the set of data rows are retrieved from the cache and the requested data page is returned.