Abstract: Online estimation of area-level inertia can be used for frequency stability control in low-inertia power systems. This disclosure provides an area-level inertia online estimation method considering inter-area equivalent frequency dynamics. The disclosed method only needs one phasor measurement unit placed at any bus within each area. The inter-area equivalent frequency dynamics model for the multi-area power system is developed, which is employed to estimate area-level inertia under the small disturbance situation. Then, the area-level inertia estimation model boils down to a nonlinear parameter identification problem. The other boundary conditions of the disclosed method are derived by parameter identifiability.

Abstract: The system and method described herein may be used to make a binary determination of whether to initiate an in-trip audit of self-scans in a self-checkout system. For example, the system may receive one or more audit parameters that are used to calculate an audit score. The audit score may be compared to a predefined audit threshold to determine, during a shopping trip, whether to initiate the in-trip audit. After or in combination with making the binary determination, the system may make a probabilistic determination of whether to initiate an audit based on historical audit points associated with the shopper. The audit points are incremented or decremented based on prior audits and other characteristics of the shopper.

Abstract: Embodiments are disclosed to detect whether an interaction has occurred between a customer and one or more store employees. By analyzing a how long a communication device used by the customer was within a threshold range of one or more devices worn by store employees, an interaction between the customer and one or more store employees may be identified. Employees whom the customer interacted with may be identified by processing transmission parameters broadcasted by the devices worn by the store employees. Thus, all employees in which a customer interacted with while visiting a store may be identified. The customer may be asked for feedback via the communication device upon detection that a customer has completed a transaction and/or left the store. Using the solicited feedback provided by the customer, various types of reports may be generated.

Abstract: A system for automatically checking seat dimension accuracy for a vehicle may include a storage unit configured to store therein seat design data at a time of designing an actually produced seat and seat scan data obtained by scanning the actually produced seat, a controller configured to determine whether the actually produced seat has been produced to match predesigned dimensions using the seat design data and the seat scan data stored in the storage unit, and an output unit configured to automatically output a result of determination by the controller in a specific form. The system and a method for checking seat dimension accuracy for a vehicle can automatically check whether an actually produced seat has been accurately produced to match designed seat dimensions through automatic comparison of scan data of the actually produced seat with seat design data, and automatically generate a checking result report.

Abstract: Disclosed is a method for commissioning a magneto-inductive flow measuring device having means for producing a magnetic field and at least one measuring electrode pair for sensing a potential difference in a medium. The method includes a settling of the means during a settling time for stabilizing the magnetic field. During the settling time a first voltage time function is applied to the means, wherein after the settling time a measuring time begins, wherein during the measuring time a second voltage time function is applied to the means, wherein the settling time is divided into first time intervals, each of which has a duration, wherein the measuring time is divided into second time intervals, each of which has a duration, wherein an average value of all first interval durations is always less than an average value of all second interval durations.

Abstract: Systems and methods which provide a motion sensor data-driven framework for sports action recognition and/or assessment using a wearable sensor are described. A motion sensor data-driven system may provide real-time kinematical analysis to athletes engaged in active competition or training sessions under typical competition or training conditions. Analysis of motion sensor data provided according to embodiments may operate to recognize instances of one or more particular sports actions performed by an athlete and/or assess the skill of the athlete from analysis of one or more sports actions. A motion sensor data processing platform of embodiments of a motion sensor data-driven system may comprise a processor-based system configured to receive and analyze data regarding the movement of an athlete's limb reported by a wearable sensor device comprising a micro inertial measurement unit configuration for capturing and reporting data regarding the movement of an athlete's limb.

Abstract: A sentiment analysis computing system includes a storage medium and a processing system. Sentiment input is received from audience members viewing a streamed/webcasted event. The received input is stored to the storage medium. A time slice of the webcasted event is determined and sentiment inputs that are within that time slice are obtained. A sentiment value is calculated for the determined time slice based on aggregated sentiment values. The calculated sentiment value for the time slice is then output by the sentiment analysis computing system.

Abstract: A system for measuring the orientation angle of automotive collision avoidance sensors. An adaptive spacer is supported to conformably interengage the collision avoidance sensor module of a vehicle being repaired. The adaptive spacer extends outwardly from the sensor module and the orientation angle of the sensor module is transposed by the adaptive spacer to form an angular guideline on an underlying calibration board, mat or other surface. The angle between the angular guideline and a base guideline parallel to the center line of the vehicle and the angular guideline is measured to provide the orientation angle of the vehicle's sensor module.

Abstract: A method of automatically generating baggage driver staffing recommendations including receiving a first set of flight parameters for a first flight, creating a first predictive staffing model for the first flight by simulating missed bag quantities for a range of driver quantities using a first computer-implemented machine learning model and the first set of flight parameters, and automatically generating a first recommended driver quantity predicted to result in a quantity of missed bags using the first predictive staffing model and a threshold quantity of missed bags. The missed bag quantities are simulated using a simulator, the first computer-implemented machine learning model is configured to relate driver quantities and flight parameters to expected missed bag quantities, and the first predictive staffing model relates predicted quantities of missed bags to quantities of staffed drivers.

Abstract: A computer-implemented method for managing crop harvesting activities is implemented by a harvest advisor computing device in communication with a memory. The method includes receiving an initial date of a crop within a field, receiving an initial moisture value associated with the crop and the initial date, and receiving a target harvest moisture value associated with the crop. The method also includes receiving field condition data associated with the field. The method further includes computing, by the harvest advisor, a target harvest date for the crop based at least in part on the initial date, the initial moisture value, the field condition data, and the target harvest moisture value, and displaying the target harvest date for the crop to the grower for harvest planning. The target harvest date indicates a date at which the crop will have a present moisture value approximately equal to the target harvest moisture value.

Abstract: A computer system and computer-implemented method for retail merchandise planning, including promotional product selection, price optimization and planning. According to one or more embodiments, the computer system for generating an electronic retail plan for a retailer comprises, a data staging module configured to input retail sensory data from one or more computer systems associated with the retailer; a data processing module configured to pre-process the inputted retail sensory data; a data warehouse module configured to store the inputted retail sensory data and the pre-processed retail sensory data; a state model module configured to generate a retailer state model for modeling operation of the retailer based on the retail sensory data; a calibration module configured to calibrate the state model module according to one or more control parameters; and an output module for generating an electronic retail plan for the retailer based on the retailer state model.

Abstract: A method to provide multi-objective recommendations. The method includes receiving user input indicating a plurality of objectives, where each of the plurality of objectives indicates a desired goal for a field of interest, receiving user input indicating a plurality of actionable fields, receiving user input indicating selection of one of a plurality of records in a data set, determining, based on applying an evolutionary algorithm, one or more candidate changes to values of the plurality of actionable fields of the selected record, determining, for each of the one or more candidate changes, a multi-objective score for that candidate change, selecting one or more of the one or more candidate changes to recommend to a user based on the multi-objective scores of the one or more candidate changes, and providing, for display to the user, the selected one or more candidate changes as recommended changes.

Abstract: A system is provided for providing real-time actionable feedback. The system comprises: a server in communication with a plurality of client devices, which server comprises a first module configured to process clinical care data using a machine learning algorithm trained model to identify: (i) performance metrics that impact a clinical care outcome in a selected field, and (ii) one or more actions that influence the performance metrics and are actionable to a selected clinical care provider; a second module for generating a real-time measurement of the one or more performance metrics of the selected clinical care provider; and a third module configured to dynamically display on the graphical user interface of a client device of the selected clinical care provider: (i) the real-time measurement of the one or more performance metrics of the selected clinical care provider, and (ii) an adjustment of the one or more actions.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate employing a probabilistic model to generate a continuous disease status index based on observational data are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a model component that employs a probabilistic model to generate probability distributions of disease states of a disease of an entity based on observational data of the entity. The computer executable components can further comprise an index component that generates a disease status index of the disease based on the probability distributions of the disease states.

Abstract: A method of managing the adaptive dispatching of a taxi includes receiving a request for a taxi, the received request being from a passenger; scoring a taxi driver based on at least one of an acceptance rate for assignment, a rejection rate for assignment, an idle rate, and a frequency of job acceptance; scoring the passenger based on at least one of a cancellation rate, a booking frequency, an abandonment rate, and a blacklist factor; matching the passenger to a taxi driver based on the taxi driver score and the passenger score; assigning a passenger to a taxi driver based on one of a conditional historical acceptance rate and a stochastic assignment of either chance constraints or a conditional value at risk; and dispatching the taxi driver to the passenger.

Abstract: Computing systems, methods and management tools for scheduling, optimizing and completing a dynamically adjustable workflow process. The computing systems, methods and management tools being capable of evaluating the availability of resources available for completing the workflow process and ascertaining the reliability of the resources in order to pre-generate a workflow process schedule. The computing systems, methods and management tools are further able to communicate with the assigned resources to incrementally negotiate and receive approval for proposed improvements to the pre-generated workflow schedule prior to implementation of the workflow schedule in order to optimize the cycle time of the process and increase probability of successfully completing the workflow process. The computing systems, methods and management tools may dynamically track the due dates for completing particular tasks and generate amended workflow process schedules in the event a failure occurs.

Abstract: A punch item management tool may be provided that coordinates and guides the process of taking a punch item from creation to completion. As one possibility, the punch item management tool may coordinate and guide the interactions between a creator of a punch item, a punch item manager for the punch item, and one or more assignees that are expected to perform work on the punch item. As another possibility, the punch item management tool may coordinate and guide the interactions between an individual serving the dual role of creator and punch item manager for a punch item and one or more assignees that are expected to perform work on the punch item. In either case, the punch item management tool may provide a user interface including various views through which these individuals may interact with one or more punch items.

Abstract: A method for workforce scheduling by a computer system is provided. The method includes receiving a first workforce schedule describing initial assignments of a plurality of workers to a plurality of shifts, each shift comprising one or more work activities, each work activity comprising an activity and a time interval, and storing the first workforce schedule in a memory. The method also includes receiving a cell size associated with each activity, and determining a quantity of workers in each work activity associated with each activity in the first workforce schedule. The method further includes determining cell size violations by dividing the quantity of workers assigned to each work activity by the cell size for the activity associated with the work activity. The method also includes modifying the first workforce schedule to minimize cell size violations, resulting in a second workforce schedule, and storing the second workforce schedule in the memory.

Abstract: An embodiment includes extracting a capability from a dataset representative of a project description of a proposed project using a first machine learning process to form a cluster representative of the capability. The embodiment assigns the capability to a first node of a business operations graph based on a classification result of the capability by a second machine learning process. The embodiment generates a visual indicator based, at least in part, on the assigning of the capability to the first node. The embodiment generates the visual indicator by a process comprising generating a first visual indicator of the capability being assigned to the first node, and a second visual indicator of a development sequence for the capability relative to another capability from the project description based at least in part on an association from the business operations graph between the first node and a second node of the graph.

Abstract: A method for computer modeling a retail environment includes: calculating a space elasticity for an item of an item category in a retail store, using a constrained linear regression model; calculating a cross-space elasticity for the item of the item category in the retail store, using a multiple regression model; generating a number for horizontal facings for the item of the item category in the retail store, using a non-linear multiple-constraint mixed integer optimization model, based on the space elasticity of the item and the cross-space elasticity of the item; and generating an electronic planogram of the item category for the retail store, based on the number of the horizontal facings of the item.