Abstract: The present disclosure involves systems, software, and computer implemented methods for intelligent document processing in enterprise resource planning. One example method includes automatically determining that a document file is ready to be processed in an ERP (Enterprise Resource Planning) system. The document file is automatically processed and a request is sent to the ERP system to automatically create or update ERP data in the ERP system based on the document file. Status information is received from the ERP system regarding the request to create or update ERP data in the ERP system. The status information received from the ERP system is logged and information indicating that the document file has been processed in the ERP system is automatically recorded.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.

Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.

Abstract: A process for invoking a robot from an application may include launching the application from a computing system to invoke a robot link embedded within the application. The process may also include initiating from the application a port discovery process to identify a port, port details, and a token. The process may further include generating by the application a randomized code and invoking a consent application requesting approval from a user of the computing system to invoke the robot from the application. The process may also include registering the randomized code with a local listener module and passing user information and the token to a global listener module. The process may further include receiving from the global listener module the token and port identification, allowing the application to authenticate itself with, and communicate with, the robot, thereby completing the robot invoking process.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.

Abstract: A system and method provide an automation solution for guiding a contact center agent during a communication session by providing contextual in-line assistance. Robotic process automation (RPA) is used for automating workflows and processes with robots that capture information from multiple applications of a contact center system and generate contextual guidance for the contact center agent via callout activities during the communication session.

Abstract: One or more robots may be invoked from one or more applications for robotic process automation (RPA). A process for invoking a robot from an application may include launching the application from a computing system to invoke a robot link embedded within the application. The process may also include initiating from the application a port discovery process to identify a port, port details, and a token. The process may further include generating by the application a randomized code and invoking a consent application requesting approval from a user of the computing system to invoke the robot from the application. The process may also include registering the randomized code with a local listener module and passing user information and the token to a global listener module. The process may further include receiving from the global listener module the token and port identification, allowing the application to authenticate itself with, and communicate with, the robot, thereby completing the robot invoking process.

Abstract: One or more robots may be invoked from one or more applications for robotic process automation (RPA). A process for invoking a robot from an application may include launching the application from a computing system to invoke a robot link embedded within the application. The process may also include initiating from the application a port discovery process to identify a port, port details, and a token. The process may further include generating by the application a randomized code and invoking a consent application requesting approval from a user of the computing system to invoke the robot from the application. The process may also include registering the randomized code with a local listener module and passing user information and the token to a global listener module. The process may further include receiving from the global listener module the token and port identification, allowing the application to authenticate itself with, and communicate with, the robot, thereby completing the robot invoking process.

Abstract: Described embodiments provide systems and methods for hosted resource configuration, with intelligent personalization of a user's workspace experienced based on the user's available time. The system analyzes the user's schedule, location, and work habits, and prioritizes and maps tasks to available time slots, enabling the system to be more efficient, with less time identifying and selecting next tasks. The system may identify a period of time in which a user can perform a task associated with a hosted application; may identify at least one task associated with the hosted application, the at least one task including a duration within that of the identified period of time, and may provide, to a client device of the user, content of the hosted application based on the identified at least one task, the content enabling the user to accomplish the at least one task within the identified period of time.

Abstract: Disclosed is a system and method for optimizing cooling efficiency of a data center is disclosed. The system may comprise an importing module, a Computational fluid dynamics (CFD) modeling module, a scope determination module, a metrics computation module, an identification module and a recommendation module. The importing module may be configured to import data associated to the data center. The CFD modeling module may be configured to leverage an external CFD Analysis tool in order to develop a CFD model of the data center. The scope determination module may be configured to determine a scope for optimizing the cooling efficiency of the data center. The metrics computation module may be configured to compute metrics based upon the data. The identification module may be configured to identify inefficiency and a cause producing the inefficiency. The recommendation module may be configured to facilitate optimizing cooling efficiency of the data center.

Abstract: In some examples, embedded designer implementation may include, upon receiving an indication of actuation of a second designer launch element that is included in a first designer, launching a second designer inline from the first designer. Further, embedded designer implementation may include, upon receiving an indication of actuation of a first designer return element that is included in the second designer, returning to the first designer inline from the second designer. The first designer and the second designer may include a configurable component. Further, embedded designer implementation may include utilizing a common portion of the memory for the configurable component.

Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.

Abstract: According to some aspects of this disclosure a roadside assistance application programming interface (API) may allow any type of application, internet of things device, voice recognition device, and others to provide roadside assistance functionality. According to some aspects of this disclosure a device may communicate with sensors or an on-board diagnostics system of a vehicle and retrieve vehicle data. The device may recommend a service based on the vehicle data. The device may send a request for roadside assistance. The device may be used to enroll a user as a member of a roadside assistance benefits program. The above mentioned steps may all be performed via a single application running on the device. According to some aspects of this disclosure a device may process a roadside assistance request and determine a roadside assistance service provider to send to a user that requested roadside assistance.

Abstract: A method for providing notifications is provided. The method includes a tangible user interface (TUI) element the receives an input from a computing device coupled to the TUI element. The input is indicative of an outcome corresponding to a functionality of an application on the computing device. Based on the outcome, the TUI element determines at least one illumination pattern from a plurality of pre-stored illumination patterns. Thereafter, the TUI element generates an output based on the at least one determined illumination pattern.

Abstract: Example embodiments of the present invention relate to a method, a system, and a computer program product for disease outbreak prediction analytics. The method includes calculating a respective correlation value for each outbreak attribute pair among a set of outbreak attributes for a data set regarding a disease and assigning a weight value for each outbreak attribute according to the correlation values. A risk value for the disease then may be determined according to the weight values.

Abstract: In some examples, embedded designer implementation may include, upon receiving an indication of actuation of a second designer launch element that is included in a first designer, launching a second designer inline from the first designer. Further, embedded designer implementation may include, upon receiving an indication of actuation of a first designer return element that is included in the second designer, returning to the first designer inline from the second designer. The first designer and the second designer may include a configurable component. Further, embedded designer implementation may include utilizing a common portion of the memory for the configurable component.

Abstract: Binding a security token to a client token binder, such as a trusted platform module, is provided. A bound security token can only be used on the client on which it was obtained. A secret binding key (kbind) is established between the client and an STS. The client derives a key (kmac) from kbind, signs a security token request with kmac, and instructs the STS to bind the requested security token to kbind. The STS validates the request by deriving kmac using a client-provided nonce and kbind to MAC the message and compare the MAC values. If the request is validated, the STS generates a response comprising the requested security token, derives two keys from kbind: one to sign the response and one to encrypt the response, and sends the response to the client. Only a device comprising kbind is enabled to use the bound security token, providing increased security.

Abstract: Disclosed is a system and method for facilitating optimizing cooling efficiency of a data center. The method may comprise receiving a layout of the data center. The method may comprise computing co-ordinates of each equipment of a plurality of equipments associated with the data center. Further, the method may comprise segregating the layout into a plurality of cells. The method may comprise capturing preliminary data associated with the data center. Further, the method may comprise determining a state value of the data center based upon the preliminary data. The method may comprise capturing CFD data and, selectively, thermal assessment data. Further, the method may comprise facilitating the optimization of the cooling efficiency of the data center by using an external analysis tool capable of performing Computational Fluid Dynamics (CFD) analysis or thermal assessment followed by the Computational Fluid Dynamics (CFD) analysis using the CFD data and the thermal assessment data.

Abstract: A method for providing notifications is provided. The method includes a tangible user interface (TUI) element the receives an input from a computing device coupled to the TUI element. The input is indicative of an outcome corresponding to a functionality of an application on the computing device. Based on the outcome, the TUI element determines at least one illumination pattern from a plurality of pre-stored illumination patterns. Thereafter, the TUI element generates an output based on the at least one determined illumination pattern.