Abstract: A multi-layer compute sizing correction stack may generate prescriptive compute sizing correction tokens for controlling sizing adjustments for computing resources. The input layer of the compute sizing correction stack may generate cleansed utilization data based on historical utilization data received via network connection. A prescriptive engine layer may generate a compute sizing correction trajectory detailing adjustments to sizing for the computing resources. Based on the compute sizing correction trajectory, the prescriptive engine layer may generate the compute sizing correction tokens that that may be used to control compute sizing adjustments prescriptively.

Abstract: A remote care system may include a platform that includes one or more memory devices and one or more processors communicatively coupled to the one or more memory devices. The platform may connect and communicate bi-directionally with a plurality of devices via a gateway device. At least some of the plurality of devices may include sensors capable of gathering vitals data from a patient. The vitals data may include different types of vitals data. The platform may connect and communicate bi-directionally with another plurality of devices. The other plurality of devices may be remote to the gateway device and the at least some of the plurality of devices. The platform may support continuous and live streaming of the vitals data from the sensors. The platform may perform a set of actions on a per patient basis based on analyzing the vitals data.

Abstract: A system and method for qualitative analysis of time progressive signals, comprising: a qualitative signal analysis module, comprising at least a processor, a memory, and a long term storage device; and an output processor module comprising at least a processor a memory and a network interface has been devised. The qualitative signal analysis module retrieves signal data over time and applies pre-programmed protocols to compare multiple aspects of the signal data to derive meaningful data. The output processor module encodes data generated by the qualitative signal analysis module for use in subsequent analytical steps such as further manipulation, classification or long term storage.

Abstract: The present disclosure relates to system, method and apparatuses for determining parameter settings for a power generation system and a tangible computer readable medium therefor. In an embodiment of the present disclosure, the system comprises at least one processor; and at least one memory storing computer executable instructions. The at least one memory and the computer executable instructions are configured to, with the at least one processor, cause the system to: divide historical power related data of the power generation system into a plurality of power load segments based on typical power load values and the number of the historical power related data; identify feasible parameter ranges for each of the plurality of power load segments; and determine optimal parameter settings for each of the plurality of power load segments, based on the identified feasible parameters ranges and correlations between system energy efficiency and relative parameters of each of the plurality of power load segments.

Abstract: A device may receive information identifying a first set of instructions. The first set of instructions may identify an action to perform to test a first program. The device may identify a second set of instructions, related to testing a second program, that can be used in association with the first set of instructions. The first test may be similar to the second test. The device may identify multiple steps, of the first set of instructions, that can be combined to form a third set of instructions. The third set of instructions may be used to test the first program or a third program. The device may generate program code in a first programming language to perform the action. The first programming language may be different than a second programming language used to write the first set of instructions. The device may perform the action.

Abstract: A device may provide, to a first party, a user interface including information identifying one or more types of network functionalities for implementation, by a second party, in a network implementation. The user interface may be associated with receiving a selection of a configuration for the network implementation. The device may detect an interaction with the user interface associated with selecting the configuration for the network implementation. The configuration for the network implementation may indicate integration of a set of third party network functionalities associated with a set of third parties. The device may automatically provision a set of computing resources for the network implementation based on the configuration for the network implementation. The device may provide, to the first party, access to the network implementation based on automatically provisioning the set of computing resources.

Abstract: A system is configured to determine a conversion rate associated with a loyalty program offered by a merchant. The conversion rate may specify a monetary value allotted to a loyalty point in the loyalty program. The conversion rate, associated with the loyalty program, may change over time. The conversion rate may be determined without user input specifying the conversion rate. The system is configured to receive an instruction to lock the conversion rate for a period of time; lock the conversion rate as a locked conversion rate for the period of time based on the instruction; and permit the locked conversion rate to be used to apply a discount to a purchase during the period of time. The locked conversion rate at a time of the purchase may be different from the conversion rate offered by the loyalty program at the time of the purchase.

Abstract: An example method described herein involves receiving a first data stream and a second data stream; determining that a plurality of entities are present in the image data of the first data stream; analyzing the first data stream to determine that an entity, of the plurality of entities, is unrecognizable in the image data of the first data stream; obtaining, by the device, a common knowledge graph associated with the first data stream and the second data stream, wherein the common knowledge graph includes information regarding the plurality of entities; annotating the common knowledge graph with first corresponding recognizable characteristics of the plurality of entities in the first data stream to generate a first annotated knowledge graph; annotating the common knowledge graph with second corresponding recognizable characteristics of the plurality of entities in the second data stream to generate a second annotated knowledge graph; determining whether the entity is recognizable based on the first annotated

Abstract: A device may receive data associated with network resources. The data may be received from another device and from a system. The data may include an attribute of the network resources. The device may process the data to align the data received from the other device and from the system. The device may determine a manner in which the network resources are to be consolidated based on the attribute of the network resources. The device may perform an action based on determining the manner in which the network resources are to be consolidated. The action may be associated with consolidating the network resources.

Abstract: An automation identification diagnostic tool (AIDT) is disclosed that records and analyzes actions within a program that are taken by an agent to accomplish certain tasks. By recording the action steps to accomplish a task in a recording session data file, the AIDT is then able to analyze the recording session data file to identify steps for conversion to automated tasks.

Abstract: A device may receive project information that identifies a set of tools to be provisioned on multiple devices. The multiple devices may be used during a project. The device may process the project information to identify the set of tools based on receiving the project information. The set of tools may include different tools associated with different roles related to the project. The device may provide tool information related to installing or configuring the set of tools on the multiple devices based on processing the project information. The tool information provided to a first device of the multiple devices may relate to the first device and not to a second device of the multiple devices.

Abstract: Examples of artificial intelligence based risk and knowledge management analysis are described. In an example implementation, a data analyzer may obtain entity data pertaining to an entity associated with a risk management instrument. The entity data may include data obtained from an IoT device and/or a risk control and knowledge management database. The entity data may be processed by an intelligent risk management agent to perform a variety of risk control and knowledge management tasks, such as claim processing, notification generation, formulization of risk management instruments, and assisting agents, users, and organization. The claim processing may include, for instance, identification of a similar case from database. The notification generation may include analysis with respect to reference parameters. The formulization of risk management instrument may include analysis with respect to the entity data from multiple domains and/or various external factors.

Abstract: A method and system optimizes investments for each marketing channel of a multichannel marketing campaign. Past optimal investments are compared to current sales or profits for each marketing channel, and a new optimal investment is estimated for each marketing channel, which may be used as a marketing budget. A marketing dashboard is used to determine the new optimal investments for the marketing channels, and the new optimal investments are stored in a marketing database.

Abstract: A social collaboration workflow system embeds social collaboration functionality into the workflow process. The system identifies a location of a user device, and identifying a current activity associated with the user device based on the identified location. The system displays instructions for performing the current activity to a user interface on the user device, and displays an activity feed comprising a set of previously submitted activity feed posts that are related to the current activity to the user interface. The system determines whether the current activity has changed to a new current activity. If the current activity has changed, the system displays instructions for performing the new current activity to the user interface, and displays a new set of previously submitted activity feed posts that are related to the new current activity to the user interface.

Abstract: A device may authenticate a user for access to a plurality of target systems. The device may provide information identifying the plurality of target systems. The device may receive information associated with a request for access to one or more target systems of the plurality of target systems. The device may determine whether the request for access complies with one or more policies associated with the one or more target systems. The device may deny the request for access. Denying the request for access may include foregoing providing access to the one or more target systems. The device may receive information associated with an escalation of the request for access based on denying the request for access. The device may provide access to the one or more target systems based on the information associated with the escalation of the request for access.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reconciliation data.

Abstract: A device may receive a set of feedback files associated with a file transfer from a first device to a second device. A feedback file, of the set of feedback files, may include a timestamp corresponding to an event associated with the file transfer. The device may determine configuration information associated with the file transfer. The configuration information may include timing information, associated with the event, that identifies an expected time associated with the event. The device may determine status information associated with the file transfer. The status information may be determined based on the timestamp corresponding to the event and the timing information associated with the event. The device may provide the status information.

Abstract: A system to perform brand impact verification (BIV) for a utilization-related software application (URSA), associated with an identity and a software development process (SDP) including multiple phases. The system includes a requirements-design module to determine brand characteristics of a brand associated with the identity, and software application properties associated with the URSA. The system also includes a BIV testing engine, executed by a computer system, to identify design test procedures to produce quantitative and qualitative design test results based on the determined brand characteristics and the determined software application properties. The BIV testing engine also implements the design test procedures to generate design test results in an SDP design step of an SDP associated with the URSA. The design test procedures are implemented in the SDP in a SDP design step prior to implementing an SDP full implementation test step testing a full implementation of the URSA.

Abstract: An intelligent social feed generator system leverages existing social platforms to generate context specific social feeds having enhanced messages that facilitate context specific user actions. The system implements technical features that analyze messages on existing social platforms to determine a message context and identify responsive user actions. The system generates enhanced messages allowing the user to take such action. The system also dynamically generates an enhanced social feed based on a particular usage context, where the social feed is formed of messages that match the usage context.

Abstract: Systems and methods for identifying an adverse effect of a pharmaceutical substance are provided. A system may tokenize an electronic medical record for a plurality of tokens. The system may further generate a distance score between a first vector of a word embedding model and a second vector of the word embedding model. The first vector may correspond to a substance token and the second vector may correspond to a condition token. The system may further detect an absence of a preventative association between the substance token and the condition token in a prevention repository. The system may further generate a causal link indication indicative of a causal link between the substance token and the condition token in response to the distance score being greater than a threshold value and detection of the absence of the preventative association between the substance token and the condition token.