Abstract: A method for visualizing flow direction in a distribution network includes receiving, on a hardware device, Geographic Information System (GIS) data corresponding to the distribution network from a GIS database. The distribution network includes equipment to facilitate distribution of a commodity over a distribution area, and the GIS data includes information relating to distribution of the commodity. Commodity vectorized measurement data indicative of at least a flow direction of the commodity over the distribution area is generated based, at least in part, on a comparison of a current measurement value of the commodity to a reference measurement value of the commodity. The commodity vectorized measurement data is dynamically displayed on a geographic map display including imagery representative of the distribution network contained in the GIS data.

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for configuring and implementing application policies are provided. The disclosed technology can access application policy data associated with implementing an application policy. The application policy data can include rules associated with implementing the application policy by using organizational data associated with a plurality of applications that includes a set of extra-organizational applications that perform operations associated with a different set of extra-organizational applications. Based on the application policy data, organizational records of the organizational data that satisfy the one or more rules can be determined. The plurality of applications associated with the one or more organizational records that satisfy the one or more rules can then be accessed.

Abstract: Systems and methods are disclosed for task identification and tracking using shared conversational context. In one implementation, a first communication from a first user is received within a communication session. The first communication is processed to identify a first content element within the first communication. A second communication is received within the communication session. The second communication is processed to identify a second content element within the second communication. The first content element is associated with the second content element. Based on an association between the first content element and the second content element, a task is identified. An action is initiated with respect to the task.

Abstract: A reconfigurable workbench pipeline for robotic process automation (RPA) workflows is disclosed. Different workbench pipelines may be built for different users. For instance, a global workflow (e.g., a receipt extractor) may be built and used initially, but this workflow may not work optimally or at all for a certain user or a certain task. A machine learning (ML) model may be employed, potentially with a human-in-the-loop, to specialize the global workflow for a given task.

Abstract: A system and method for determining a candidate workflow from a cluster of similar workflows is presented. The process uses the differences classified as insertions of operators, deletions of operators, transpositions of operators and operator shifting in a parallel workflow to determine similarities in the workflow cluster and extract a candidate similar to the workflow in the comparison query. The extracted candidate workflow can then be used to suggest modifications to the workflow in the comparison query.

Abstract: Distributing and rebalancing crewless vehicles (CV) by receiving a CV demand-availability gap, identifying candidate CV to relocate to close the CV demand-availability gap, identifying a candidate transport to relocate the CV to close the CV demand-availability gap, generating a candidate CV relocation plan, optimizing an overall CV relocation plan, and executing the overall CV relocation plan.

Abstract: A learning management system may be configured to retrieve roster data from a roster database and determine from the roster data whether a pilot has a scheduled downtime during a flight or a layover time before the flight. The system may further retrieve flight data associated with the flight from the learning management system and determine a training concept associated with the flight. The system may also select a training exercise from multiple training exercises, where the training exercise is associated with the training concept. A notification may be sent to an electronic device associated with the pilot, where the notification includes an offer to perform the training exercise.

Abstract: Systems and methods may be used to generate and use a structured form representation and structured metadata. The structured form representation and structured metadata may include information relevant to a particular context and may be used to update document templates, import new documents and update document versions into software, automate data entry for document completion, update records to include new and or updated information, and provide other functionality of an information service.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating and utilizing provider device balance graphs reflecting device utilization ratio between provider devices and requester devices. In particular, in one or more embodiments, the disclosed systems determine and utilize probabilities to generate and provide provider device balance graphs based on probability distributions for device utilization ratios. The disclosed systems can apply various scaling models to address seasonality, special events, and/or differences between regions. The disclosed systems can also apply thresholds to generate device incentive graphs that more efficiently deploy provider devices across a transportation matching system.

Abstract: A system includes a memory and at least one processor to determine a location of each vehicle of a plurality of vehicles that have freight capacity, determine a distance of each vehicle to a location of each uncovered shipment of a plurality of uncovered shipments, determine an estimated time of arrival for each vehicle to arrive at the location of each uncovered shipment of the plurality of uncovered shipments, determine a particular vehicle of the plurality of vehicles having a highest score that is selected to service a particular uncovered shipment of the plurality of uncovered shipments, the highest score based on the distance, the estimated time of arrival, and a pick up time for the particular uncovered shipment, and transmit a notification to a computing device of an operator of the particular vehicle that indicates that the particular vehicle is selected to service the particular uncovered shipment.

Abstract: An electronic device for providing a user-participating-type artificial intelligence (AI) training service is provided. The electronic device may include a user input receiving unit configured to receive, from a user of the service, initial setting user inputs about an initial setting for AI training and to receive an AI training user input for requesting for the AI training. The device may further include a processor configured to provide, through a screen of the electronic device, an initial setting UI (User Interface) receiving the initial setting user inputs and an AI training UI receiving the AI training user input, and a communication unit configured to transmit, to a service providing server, data corresponding to the initial setting user inputs and the AI training user input and to receive, from the service providing server, initial setting data and/or AI training data generated based on the transmitted data.

Abstract: A computing system includes: processor(s), memory(s), storage device(s), and network interface(s) configured to communicate with data source(s) and remotely located computing device(s). The network interface(s) receives data regarding a digital product catalog representation of products from the data source(s). The processor(s): generates a respective score for the digital product catalog representation for each respective product, the score indicative of adherence of the digital product catalog representation for each respective product to at least one criterion; stores the respective score for the digital product catalog representation for each respective product using the at least one storage device; and identifies which products provide the greatest opportunity for sales improvement by improving adherence of the digital product catalog representation to the at least one criterion.

Abstract: Disclosed are systems and methods for determining developed code scores of an application. The method may include: receiving, by a processor, one or more first score tags of one or more first blocks of developed code from a user through a computing device; identifying, by the processor, patterns in the developed code based on the received one or more first score tags; applying, by the processor, the identified patterns to one or more second blocks of the developed code; and determining, by the processor, one or more second score tags for the one or more second blocks of the developed code based on the applied patterns.

Abstract: Methods of and apparatus controlling change-out inventory of an automated analyzer apparatus. The inventory control methods include receiving change-out inventory status from automated analyzer apparatus at a server, receiving an estimate of the planned workload over a specific time period at the server, analyzing with a decisioning module of the server first data of the change-out inventory status and second data of the planned workload over the specified time period, and producing a work plan itinerary as an output from the decisioning module. The work plan itinerary provides sequence instructions or commands for an operator (person and/or robotic mechanism) to follow for changing out of change-out inventory items. Inventory control apparatus configured to carry out the methods are provided, as are other aspects.

Abstract: In various embodiments, the disclosed system may be utilized in managing supply and demand chains to optimize creation and management of inventory buffer levels via machine learning. In several embodiments, optimizing inventory buffer levels may lead to minimizing costs while maximizing the availability and timeliness of product deliveries. In multiple embodiments, the disclosed system may utilize supply chain data and performance monitoring with automated machine learning and derivation of demand signatures and profiles to provide optimized creation and management of inventory buffer levels.

Abstract: A user mobile device includes a network interface, an input/output (“I/O”) device configured to exchange data with a user, the I/O device including a display device configured to present a graphical user interface to the user, an imaging device configured to generate image data; and a processing circuit. The processing circuit comprising a memory and a processor. The memory stores instructions that cause the processor to receiver user photograph data including multiple photographs of the user, determine an emotive state of the user in each of the photographs, categorize each photograph into at least a user positive emotion category and a user negative emotion category, receive spending behavior data, generate a user spending alert based on the spending behavior data including a photograph from at least one of the user positive emotion category and the user negative emotion category, and present the spending alert to the user.

Abstract: A system for value prediction for dynamic performance optimization includes a project value predictor that receives a Key Performance Indicator (KPI) and an initiative relating to an active project having a closure date. The KPI is associated with a KPI period including multiple intervals. The project value predictor operates to identify a relevant cluster of KPIs for the KPI based on historical data, forecast a future value of the KPI based on attributes/features of the KPI relative to the closure date, predict a possibility of failure of the KPI using a trained data model to pre-classify the KPI, categorize the KPI based on the future value or the pre-classification, where the KPI is categorized as failure based on the future value being less than a target KPI value after the KPI period and added to list for retraining the model based on the categorization. The system also leads to the identification and subsequent validation of Initiatives that impact the KPIs with quantification of the level of impact.

Abstract: An electronic monitoring device and system uses a wearable monitoring device in conjunction with an associated smartphone's location services to track a person's location. Cameras or biometric sensors associated with the smartphone allow incremental responses to apparent violations by requiring the wearer to check-in using a photograph, biometric data, GPS location, and other relevant information. The system optimizes compliance by tracking KPIs and using predictive analytics to adjust compliance programs as they apply to client throughout the system.

Abstract: Embodiments are disclosed for a method for machine learning model training outliers. The method includes determining multiple metric values for corresponding transactions generated by a machine learning model. The method also includes deleting multiple preliminary outliers from the transactions based on a derived cut-off value. Further, the method includes identifying an absolute goal for improving a metric of the machine learning model. Additionally, the method includes identifying multiple training outliers from the remaining transactions. The remaining transactions include the transactions remaining after deleting the preliminary outliers. Also, a metric value of the remaining transactions meets the absolute goal.

Abstract: An ordering management system for a property includes: a location module configured to determine locations of mobile devices that are located within boundaries of the property; a selection module configured to, in response to receipt of an order from a first mobile device for delivery of one or more items to a location of the first mobile device within the boundaries of the property: select one vendor at the property to supply the item(s) of the order; determine a group of the mobile devices based on the location of the first mobile device; and select a second mobile device from the group; a device communication module configured to selectively transmit, to the second mobile device, the location of the selected one vendor and the location of the first mobile device; and a vendor communication module configured to selectively transmit the order to the selected one vendor.