Abstract: Systems and methods for assessing, tracking and improving security maturity of an organization are provided. Described is a system for assessing security maturity of an organization. The system receives a list of data sources located across multiple jurisdictions for the organization, collects data sources/data using custom rules from a plurality of data sources of the list of data sources, determine criticality score for each of the plurality of data sources, calculates data source coverage and asset collection coverage, determines use case coverage, and determines security maturity score using a maturity score model. The maturity score model is a logistic equation which is a function of the data source coverage, the asset collection coverage, the criticality score associated with each of the plurality of data sources, the use case coverage, asset coverage by each the plurality of data sources.

Abstract: Methods and systems for improved collection and evaluation of audit responses for healthcare sites are provided. In one embodiment, a method is provided that includes receiving responses associated with an audit of a healthcare site. A deficiency score and a total score may be calculated based on the responses. The deficiency scores may be calculated based on a quantity of responses indicating a deficient status and/or an improvement required status. The total score may be calculated based on a total quantity of the responses and a quantity of the responses that indicate an inapplicable status. The risk score may then be calculated based on the deficiency score.

Abstract: A system for managing performance of a service establishment, the service establishment having multiple servers and multiple customers. Each server has a server queue with zero or more customers. Servers take orders from customers when they reach the head of the server's queue. The system includes: an order input interface for obtaining orders from the servers as the servers take orders from the customers; one or more digital video cameras positioned and configured to capture video of the server queues; a public view monitor viewable by the customers; a management monitor viewable by one or more managers of the service establishment; and a customer tracking processor. The customer tracking processor is configured to: receive video of server queues; identify customers in the video data; track customer progress in the server queues; and calculate and display expected wait times of the server queues on the public view monitor.

Abstract: A system and method of combining table management software and customer experience skills by generating profiles of patrons, servers, and restaurants and using machine learning algorithms on those profiles to build more intimate relationships between patrons, food service establishments, and food service professionals. Trait matching provides optimized matchmaking between patrons and servers who share certain commonalities while also balancing the table management operations. Machine learning algorithms may be used to identify patterns of commonality that would not otherwise be recognized. This system allows patrons to choose servers at an establishment over a plurality of electronic devices by using the cluster analysis results. It provides servers more lateral work experience between participating restaurants, and restaurants more power to operate smoothly and build highly cohesive teams.

Abstract: A system and method for real-time operational predictive scoring of components and services of an information technology system (ITS) for forecasting and assessing performance of the components of the ITS are provided. A data pipeline is configured to collect and store, in real-time, multiple time series signals corresponding to health, performance, and functionality of each of the components of the ITS. An operational predictive score (OPS) engine of a scoring module calculates an OPS for each of the time series signals. An OPS roll-up module of the scoring module calculates an OPS for each of the components and services in the ITS by aggregating the OPS for the individual time series signals. An alerting engine to notify operational issues and provide root cause analysis using OPS score decomposition. A visualization layer for OPS based analytics.

Abstract: Provided are an index value calculator to calculate an index value obtained by quantifying a degree of status for evaluation items, a teamwork evaluator to evaluate a teamwork based on the index value, a support content determiner to select target persons to be supported including the members of the team based on the evaluation result of the teamwork and determine support contents in accordance with the target persons to be supported, and a presentation information generator to generate presentation information for presenting the determined support contents for each of the output devices corresponding to the selected target persons to be supported, and the teamwork evaluator evaluates the teamwork using an evaluation logic configured by combining logical formulas for comparing a threshold value set for evaluation items with the calculated index value.

Abstract: A messaging system may receive a plurality of messages in a conversation maintained by a messaging service. It may be determined that a first message sent from a first messaging application associated with a first user comprises information identifying a second user. The messaging system may receive information indicative of a date associated with the first message. At least one database may store an association among at least the first message, the second user, and the date. The messaging system may send information indicative of the date still being active in the at least one database to a second messaging application associated with the second user.

Abstract: An embodiment of the present invention is directed to a market data hub. The innovative system comprises a processing engine that manages contributed content and allows for custom analytics, alerting, reporting, machine learning interfaces, etc., while preserving entitlements controls specific to participants. Moreover, the system disseminates market data to downstream consumers and syndicated entities that are entitled to view the market data.

Abstract: Systems and methods of improving AI governance are disclosed. One or more sub-contexts associated with a plurality of users are generated from one or more data sources. The one or more sub-contexts represent one or more changes in data that are relevant to assessing one or more risks associated with the plurality of users. One or more sub-contexts are provided as training data to a plurality of models. Each of the models is associated with a confidence score. A probabilistic assessment of the one or more risks associated with the plurality of users is generated based on an application of the plurality of models to additional data pertaining to the plurality of users received in real time. The probabilistic assessment is presented in a dashboard user interface, the dashboard user interface having user interface elements configured to provide insight into how the probabilistic assessment was generated.

Abstract: Computer implemented sales prediction system collects data relating to events of visitors showing an interest in a client company from plural data sources, an organization module which organizes collected data into different event types and separates collected event counts in each event type between non-recent and recent events occurring within a predetermined time period, a first processing module which periodically calculates weighting for each event type based on recent and non-recent events for the event type compared to totals for other selected event types, a second processing module which periodically calculates sales prediction scores for each visitor and companies with which visitors are associated based on accumulated event data and weighting, and a reporting and data extract module which is configured to detect variation in sales prediction scores over time to identify spikes which can predict upcoming sales and to provide predicted sales information and leads to the client company.

Abstract: A method may be used to predict a business' category by analyzing the business' vendors. A neural network architecture may be trained via supervised learning to predict categories for businesses based on listed vendors. The neural network may be used to classify uncategorized businesses within an accounting software database. A list of factors associated with a business' success may be generated by analyzing, aggregating and ranking factors determined to be relevant to a business based on its categorization. The factors associated with the business' success may be related to the products and/or services offered by the business and the format of which those products and/or services are offered by the business. The factors may also be related to the products and/or services purchased by the business from a vendor and the format of which those products and/or services are purchased from the vendor.

Abstract: A dynamic supply chain planning system for analysis of historical lead time data that uses machine learning algorithms to forecast future lead times based on historical lead time data, weather data and financial data related to locations and dates within the supply chain.

Abstract: Systems and methods for providing distance-based indicators for electric vehicles are provided. In one embodiment, a method includes generating a dynamic task list, having a plurality of tasks associated with a vehicle location of a vehicle, in response to a parking event. Each task of the plurality of tasks has a task period. The method also includes determining a charge period for the vehicle at a charging station based on one or more vehicle charging parameters. The method further includes calculating a user return period based on a return distance between a user and the vehicle. The method yet further includes displaying a timing indicator with one or more of the plurality of tasks on the dynamic task list based on the task period and the user return period.

Abstract: The present disclosure relates to a method for determining optimal process flow (107) for a process performed by users (101) in a computing system. The method comprises receiving plurality of keystroke level events for each of plurality of process flows associated with the process, performed by plurality of users (101). Further, the method comprises determining one or more subtasks (105) for each of the plurality of process flows (102). A subtask comprises a set of events occurring together in the plurality of keystroke level events (103). Furthermore, the method comprises grouping one or more process flows from the plurality of process flows (102) to form one or more clusters (106), based on the one or more subtasks (105). Each cluster comprises the one or more process flows with similar subtasks. Thereafter, the method comprises determining an optimal process flow (107) in each cluster.

Abstract: Methods and systems determine at least one production constraint for a material loading system and a material processing system; estimate an effect of entropy on a cycle time of a material conveying system to produce a future cycle time estimate; estimate an effect of entropy on a material processing time to produce a future material processing time estimate; predict whether a delay will occur during the operation of the material loading, material conveying, and material processing systems; estimate a duration of the predicted delay; determine a loading system capacity and a conveying system capacity required to meet the defined production target based on the production constraint and estimates of the future cycle time, the future material processing time, and the duration of the predicted delay; and deploy one or more material loading and conveying systems to meet the determined loading and conveying system capacities.

Abstract: Methods of deploying shovels and haul trucks to meet a defined production target may include: Determining at least one production constraint for a shovel and a material processing system; estimating an effect of entropy on a cycle time of the haul trucks to produce a future cycle time estimate; estimating an effect of entropy on a material processing time of the material processing system to produce a future material processing time estimate; predicting whether a delay will occur during the operation of the shovel, the haul trucks, and the material processing system; estimating a duration of the predicted delay; determining a number of shovels and a number of haul trucks required to meet the defined production target based on the determined production constraint, the future cycle time estimate, the future material processing time estimate, and the duration of the predicted delay; and deploying the determined number of shovels and the determined number of haul trucks.

Abstract: Provided is a system, method, and computer program product for predicting product temperatures. The system includes at least one processor programmed or configured to collect, from temperature probes, temperature data of the plurality of different perishable products during a time period, collect, from at least one environmental sensor, environmental data of the at least one environment during the time period, generate a machine-learning model based on the temperature data and the environmental data, collect second environmental data from the at least one environmental sensor and/or from a separate data source while at least one package of at least one perishable product is in the at least one environment, and generate a predicted temperature of the at least one perishable product based on inputting the second environmental data into the machine-learning model.

Abstract: Lead to recognition time delay data, leads and sales data, and lead distance data for leads arriving at a system within a time range can be used to determine a time variable close rate and a distance adjustment thereof which, in turn, can be used to generate a predicted close rate for each lead. Using the predicted close rate for each lead, an address drive distance for each lead, and dealer-level discount information, a logistic regression model can be trained to generate a score for each combination of a dealer, make, and zip code. Each score indicates a probability of closing a sale between a lead in the zip code and the dealer in the combination. Scores thus generated can be used by a computing facility in recommending dealers to a consumer in the zip code who has expressed an interest in purchasing a vehicle of the same make.

Abstract: In one embodiment, a method for accounting for equity transactions for an incorporated legal entity in an interactive computer system is disclosed, comprising: identifying a stock option grant document stored as an electronic document on an interactive computer system, the electronic document stored in association with an electronic record of the incorporated legal entity; identifying a stock option grant in the stock option grant document, stored as core record metadata within the stock option grant document; determining a number of granted stock options using the stock option grant stored as core record metadata; subtracting the number of granted options from a stock option grant user account associated with both a user and the incorporated legal entity; and subtracting the number of granted options from an outstanding shares account associated with the incorporated legal entity, in conjunction with a stock option exercise document and as a number of granted shares.

Abstract: An improved approach to creating a plan for a well. A user receives an initial well plan for a planned well and uses the initial well plan as a starting point for alternate well plans. This is done by creating a copy of the initial well plan, allowing the various uses to make changes to the initial well plan, and executing various automatic validation routines on the alternate designs. These validation routines can provide estimated times and costs to complete the planned well use the alternate well plan. The approach can also involved displaying the estimated times and costs of the different candidate well plans. The user can then select one of the candidate well plans as the master well plan. As replanning is done during the operations, this replanning information, along with the actual executed actions, is captured and stored.