Abstract: In some implementations, a device may obtain historical information associated with user engagement with one or more historical communications associated with a user account. The device may train a machine learning model, using the historical information, to predict at least one of preferred communication channels, preferred communication timings, or preferred communication content associated with the user account. The device may determine that a communication associated with the user account is to be transmitted. The device may obtain, from the machine learning model and by the device, recommendation information including at least one of a recommended timing, a recommended communication channel, or a recommended content of the communication based on providing information associated with the user account to the machine learning model. The device may generate the communication according to the recommendation information.

Abstract: Disclosed herein are systems and methods for interacting with a consumer ledger. The systems and methods include: receiving a copy of the consumer ledger from one of a plurality of miners; adding a transaction to the consumer ledger; and transmitting the consumer ledger to the plurality of miners for conformation.

Abstract: Gross energy load can be determined by combining periodic net load statistics, such as provided by a power utility or energy agency, with on-site power generation, such as photovoltaic power generation, as produced over the same time period. The gross energy load provides an indication upon which other types of energy investment choices can be evaluated. These choices can include traditional energy efficiencies, such as implementing electrical efficiency measures, which includes cutting down on and avoiding wasteful energy use and switching to energy efficient fixtures, and improving the thermal efficiency and performance of a building. The choices can also include non-traditional energy efficiencies, such as replacing a gasoline-powered vehicle with an electric vehicle, fuel switching from a water heater fueled by natural gas to a heat pump water heater, and fuel switching from space heating fueled by natural gas to a heat pump space heater.

Abstract: A system for generating task schedules using an electronic device includes: a processor, the processor comprising neural networks; a memory coupled to the processor; a scheduler coupled to the processor, the scheduler is configured to: receive: a total work database configured to contain items representing work packages; a resources database configured to contain items representing resources required to fulfill items in the work packages; a constraints database configured to contain items representing constraints to fulfilling items in the work packages; and a scheduling objective database configured to designate a prime objective that is to be achieved by the optimum task schedule; provide a trained reinforcement learning engine for optimizing the task schedule based on inputs from the databases; and generate an optimum work package schedule to sequence the work packages using the trained reinforcement learning engine, wherein the optimum work package schedule maximizes the one or more prime objectives.

Abstract: The disclosure includes implementations for providing a recommendation to a driver of a second DSRC-equipped vehicle. The recommendation may describe an estimate of how long it would take the second DSRC-equipped vehicle to receive a roadside service from a drive-through business. A method according to some implementations may include receiving, by the second DSRC-equipped vehicle, a Dedicated Short Range Communication message (“DSRC message”) that includes path history data. The path history data may describe a path of a first DSRC-equipped vehicle over a plurality of different times while the first DSRC-equipped vehicle is located in a queue of the drive-through business. The method may include determining delay time data for the second DSRC-equipped vehicle based on the path history data for the first DSRC-equipped vehicle. The delay time data may describe the estimate. The method may include providing the recommendation to the driver. The recommendation may include the estimate.

Abstract: Disclosed are systems and methods for facilitating identification of risk across risk silos in an organization. Machine learning utilizes risk identification data from two or more silos to identify risk associated with electronic change requests provided to the system. Regulatory/compliance results are submitted to a blockchain for immutable recordation of compliance status.

Abstract: The invention is directed towards an apparatus and method for generating an action validation protocol. A processor is configured to receiver user data relating to an action datum. The processor is configured to select an action datum validator. The action datum is transmitted to the action datum validator where an action datum label is selected. Once an action datum validator selects an action label, the action is further categorized. If the action datum has not been completed, it will be sent back to the action datum identifier.

Abstract: Sharing content includes verifying occurrence of an event, determining participants of the event, gathering related content generated by the participants, where the related content corresponds to the event, and disseminating the related content to the participants. The event may be a business meeting. Verifying occurrence of an event may include determining scheduled participants, scheduled location, and scheduled time of the event using an electronic calendar of one of the scheduled participants. Participants may include the scheduled participants and other participants that are not listed in the electronic calendar where the other participants attend the event. Verifying occurrence of an event may also include confirming that at least an event organizer is at the scheduled location at the scheduled time and there is at least one other one of the participants. The content may include documents, photos, scanned images, audio clips, video clips, typed notes, and/or handwritten notes.

Abstract: A method, computer program product, and a system where a processor(s) generates a digital wardrobe for each user of a set of users. The processor(s) obtains a prospective theme(s) for a given event and a list of participants comprising a portion of the set of users. The processor(s) identify preferences, in the digital wardrobes of the portion of the set of users, relevant to each of the one or more prospective themes for the given event. The processor(s) determine, based on analyzing the relevant preferences in the digital wardrobes of the portion of the set of users, if a consensus exists in the relevant preferences of the portion of the set of users, where the consensus represents a given prospective theme, where the respective relevant preferences for the given prospective theme are aligned across the portion of the set of users. Based on determining that the consensus exists, the processor(s) generates an event theme for the given event, wherein the event theme is the consensus.

Abstract: A system and method that monitors conditions at a location and monitors and detects events in images to determine if there is a recognized event and if so, the recognized event is assigned a concern level and a workflow is transmitted to one or more qualified individuals based on the recognized event and the concern level of the recognized event.

Abstract: Methods, systems, and media for providing direct and hybrid data acquisition approaches are provided.

Abstract: An intelligent scheduler system implemented by one or more computer for objectively selecting interviewers for an interview of a candidate for a job opening at an organization. The one or more computers includes a storage device and a processing device to generate a calibrated job profile, generate an enriched talent profile of the candidate, identify, based on the calibrated job profile and the enriched talent profile, an aspect of the candidate to be evaluated during the interview, execute a deep neural network comprising an input layer to receive the aspect, the enriched talent profile of the candidate, and the enriched talent profiles of the potential interviewers, and an output layer to output match scores each indicating an effective measure of a corresponding one of the potential interviewers for evaluating the aspect during the interview, and determine, based on the match scores, qualified interviewers from the potential interviewers.

Abstract: Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for performance evaluation and training. A computing platform may automatically determine, based on audio transcription files, a model for dynamic performance evaluation and training, which may be dynamically updated as additional audio transcription files are received. The computing platform may receive and analyze an additional audio transcription file using natural language processing and the model, which may result in proficiency scores. Based on the proficiency scores, the computing platform may calculate an overall proficiency score and identify areas for improvement associated with the first individual. Based on the areas for improvement, the computing platform may determine performance feedback tailored to the individual and may send, to a user device associated with the individual, the performance feedback.

Abstract: Systems, methods, and apparatuses for completing an action requested by a customer are described herein. A requested action is received from the customer. A customer task for completion of the requested action to be performed by the customer is identified. An interaction board is generated that is accessible by the customer and accessible an employee associated with a provider. The interaction board is displayable via a graphical user interface and includes the customer task. An indication is received from the customer that the customer task has been completed prior to a customer interaction. The interaction board is updated to indicate that the customer task has been completed prior to the customer interaction. Information associated with the requested action is received from a customer device during the customer interaction. The interaction board is updated to include the information received from the customer device during the customer interaction.

Abstract: Systems and methods are directed to optimizing survey parameters using machine learning. A network system monitors user activity of a plurality of users with respect to an application and provides a notification to users of the plurality of users that satisfy a trigger condition for providing the notification. The network system obtains feedback corresponding to the notification, whereby the feedback indicates whether each of the users accepted, rejected, or ignored the notification. A machine learning model is then trained using input data obtained from the feedback to optimize on one or more parameters used by the network system in providing a future notification. Based on the machine learning model, the future notification is presented to a further set of users using the one or more optimized parameters.

Abstract: A method for staffing a commercial vehicle with a driver includes sending to a server, by a dispatch computing device associated with a job dispatcher, a job order to staff a commercial vehicle with a driver. The method includes receiving, from a driver computing device associated with the driver, an identification of the driver and one or more driver qualifications. The method includes verifying, by the server, the one or more driver qualifications in response to receiving the identification of the driver and the one or more driver qualifications. The method includes receiving, from the driver computing device, a request to be assigned to the job order. The method includes assigning, by the dispatch computing device, the job order to the driver by accepting the request received from the driver computing device.

Abstract: An intelligent prediction system includes one or more processors, one or more memory components, and machine-readable instructions that cause the intelligent prediction system to: receive text data comprising a plurality of speaker turn segments of a transcription of a conversation, each speaker turn segment of the plurality of speaker turn segments representative of a turn in the conversation, the plurality of speaker turn segments collectively representative of the conversation up to a point of time, generate a point in time bind probability based on a speaker turn segment bind probability of a speaker turn segment at the point in time and memory data associated with the plurality of segments up to the point in time, and generate a speaker turn segment impact score at the point in time by subtracting an immediately preceding point in time bind probability from the point in time bind probability.

Abstract: A SOW management system provides centralized management of SOWs during the entire SOW life cycle, from creation through final approval. The SOW management system includes a search tool that allows users to easily retrieve and manage existing SOWs, and SOW template management functionality that allows users to manage different types of SOW templates that are used to create SOWs. The SOW management system also provides user management, including managing user roles, and tracks changes in SOWs throughout the SOW life cycle. This allows users to create and collaborate on SOWs using a centralized system, instead of the conventional approach of manually tracking changes via email. The SOW management system includes the capability to integrate data from third-party systems and to export data to those systems.

Abstract: A method for verifying regenerative management practices in agricultural parcels includes: determining a regenerative carbon footprint value for a parcel that comprises a difference of a regenerative carbon footprint and a baseline carbon footprint, where the baseline carbon footprint is derived by calculating greenhouse gas emissions based on simulating crops under current management practices, and where the regenerative carbon footprint is derived by calculating greenhouse gas emissions based on simulating crops under regenerative management practices corresponding to a plan proposed by a grower; approving and publishing carbon credits according to the plan; for key dates corresponding to each of the regenerative management practices, processing remotely sensed images against corresponding crop curves to determine compliance/noncompliance indicators corresponding to the key dates; and storing the compliance/noncompliance indicators database, and determining at a verification date compliance with the plan.

Abstract: Disclosed embodiments may provide a framework to implement an omnichannel relevance analysis system. In response to a request to obtain an omnichannel relevance for a product, the system identifies a set of relevancy attributes and domain priorities and obtains product data sets associated with a set of platforms through which the product is made available. Using these product data sets, the system generates an omnichannel relevance index to indicate a position of the product in relation to sets of other products made available within the set of platforms.