The present invention generally relates to the field of automated functional testing, and, more particularly, to a method and system for validation of calculation code against calculation specification. Currently the validation is done manually which is time consuming and effort intensive. Embodiments of present disclosure provide an automated method of validation by generating a schema from the calculation specification, retrieving data based on the schema, executing the intermediate calculations, and comparing the result with the output from the calculation code. The method requires minimal manual input and is a fast, simple, resilient and low-code/no-code technique that can be extended to support any type of calculation code and calculation specifications with minimal or no change.

The overall quality of a workforce is analyzed, scored and presented using an analysis engine that performs a multi-domain analysis on enterprise data. The analysis engine presents key information about the performance of a workforce across a range of hardware devices so as to inform different users in their unique contexts and roles within a business organization as to workforce performance. The analysis engine associates a customizable performance profile with each workforce member. Each performance profile is comprised of a plurality of performance measures. Each performance measure in turn, represents a performance metric that measures some aspect of the job duties performed by the associated workforce member, e.g., an industrial vehicle operator. The scores are aggregated into an overall performance profile score. To compute the scores, data is considered across multiple domains, e.g., by collecting and analyzing data from industrial vehicle data systems, warehouse management systems, labor management systems, etc.

Methods, systems, and computer-readable media are provided for building a score plan for a healthcare organization, its providers, its payers, and/or its patients and presenting the results of the score plan on one or more score card user interfaces. Score cards graphically display an entity's progress towards meeting quality measure objectives. The score cards provide information on percentage completion of one or more quality measure objectives by the entity and/or quality measure objectives that may be difficult for the entity to achieve.

A system for generating product label changes is described. The system includes a product labeling platform executable on a network enabled computing device and a database of at least one selectable master label and at least one selectable jurisdiction label associated with a labeled product. The platform associates at least one selected descriptor from a first pre-defined descriptor set to each change made to a selected master label, and further associates at least one selected descriptor from a second pre-defined descriptor set to each change made to a selected jurisdiction label. The platform further associates a report including the selected descriptors from the first and second pre-defined descriptor sets with the changed label. A system for generating and managing product labels for a product across multiple jurisdictions is also disclosed. Methods including a computer-implemented method of updating a product label and a computer-implemented method of generating and managing product labels for a product across a plurality of jurisdictions are also disclosed.

Embodiments of work stations for use in a medical dose preparation management system are disclosed. A work station may include a camera stand. The camera stand may include a housing enclosing a camera and one or more light sources therein. As such, the camera and light sources may be directed at a medical dose preparation staging region to capture medical dose preparation images of the medical dose preparation staging region. The camera stand may include an adjustable support positionable in a plurality of positions to dispose the camera and light source relative to the medical dose preparation staging region. The work stations may facilitate improved image quality and record work flows carried out at the work station for preparation verification.

The information processing device 1C mainly includes the biological information acquisition unit 30C, the state coincidence determination unit 35C, and the meeting score calculation unit 37C. The biological information acquisition unit 30C is configured to acquire biological information Ib of multiple participants in a meeting. The state coincidence determination unit 35C is configured to determine, based on the biological information Ib, whether or not there is a state coincidence among the multiple participants in the meeting and generate the state coincidence information Im relating to the state coincidence. The meeting score calculation unit 37C is configured to calculate, based on the state coincidence information Im, a meeting score Sc indicating an evaluation of a quality of the meeting according to a purpose of the meeting.

A remote driving taxi system provides a mobility service using remote driving taxis that are driven by remote drivers. Management information indicates assignment states between the remote driving taxis and the remote drivers. The remote driving taxi system executes an assignment process based on the management information, in response to a request from a user. Specifically, the remote driving taxi system selects one of unassigned taxis to each of which the remote driver has not been assigned, as a first remote driving taxi that provides the service to the user. Further, the remote driving taxi system selects one of remote drivers each of which has not been assigned to the remote driving taxi, as a first remote driver that provides the service to the user. Then, the remote driving taxi system assigns the first remote driver to the first remote driving taxi.

Described herein are systems and methods for agricultural data analysis. In one embodiment, a computer system for monitoring field operations includes a database for storing agricultural data including yield and field data and at least one processing unit that is coupled to the database. The at least one processing unit is configured to execute instructions to monitor field operations, to store agricultural data, to automatically determine whether at least one correlation between different variables or parameters of the agricultural data exceeds a threshold, and to perform analysis of the agricultural data to identify a category of man-made issues or other issues that have potentially caused the correlation when at least one correlation occurs between different variables or parameters of the agricultural data.

Systems and methods to provide training content to equipment operators and determine the success of the training content. Sensor data is captured during a user’s operation of the equipment. The sensor data is analyzed to detect an event in the operation of the equipment. In response to detecting an event, training content for the event is selected and presented to the user. If the user does not consume the training content, the content is re-presented to the user. If the user consumed the training content, but a reoccurrence of the event is detected in additional sensor data, then the training content is labeled as being unsuccessful at training the user to avoid the event. In response to the training content being unsuccessful at training the user, additional training content may be provided to the user or a modification to the equipment may be suggested.

A computerized-method for determining an agent-proficiency when addressing concurrent customer sessions via one or more channel types and utilization thereof is provided herein. The computerized-method includes operating a Concurrent-Sessions-Handling-Agent-Proficiency (CSHAP) module. The CSHAP-module includes: (a) operating an interactions-module to retrieve one or more interactions and metadata thereof of the agent; (b) for each interaction, determining if the interaction has been handled with concurrent interactions; (c) for each determined interaction as handled with concurrent interactions, checking in the metadata if the interaction has one or more defocused-events; (d) calculating a CSHAP-score for the agent based on one or more attributes from the metadata of the interaction to provide an indication as to an ability of the agent to address concurrent customer sessions; (e) storing the calculated CSHAP-score in a data-store; and (f) sending the CSHAP-score to one or more applications, to take one or more follow-up actions based on the CSHAP-score.