A computer implemented method for determining the veracity of a completed task for validating the completed task towards the progression of a goal is disclosed. The completed task is a medical procedure performed by a first party. The goal is to compile a predetermined number of completed tasks required by a third party. The method includes receiving and storing registration data from a first party, second party, and third party. The method receives medical case information from the first party. The method causes an SMS message to be sent to the second party for soliciting approval of the case data. If an approval is received, then the method generates a validated medical case record. The method stores the validated medical case record to the blockchain and mints a token associated with the validated medical case. The method tracks the progression towards the goal based on validated medical cases.

A system and method are provided for automatically correlating geologic tops. The system receives well logs from different well bores and each of the picks is added to a priority queue ordered by each pick's quality measure. User selected picks are assigned the highest level of quality measure. The system performs correlation by selecting a window of well log data about a pick selected from the top of the priority queue and then finding the best optimal match with a corresponding window in a neighboring wellbore.

A system for recommending a maximum quantity of work in process, in which one or more processors of a distributed storage device are configured to execute: acquiring at least part of production data stored in the distributed storage device, the production data includes quantity records and cycle time records of a production line in time periods, and the cycle time record of each time period includes a cycle time at each process station of the production line in said each time period; clustering the quantity records to obtain a plurality of initial classifications, each initial classification includes at least one quantity record; determining a portion of the initial classifications as preferred classifications; determining the maximum quantity of work in process at each process station; and a display device is configured to display the maximum quantity of work in process at each process station determined by an analysis device.

In one aspect, a device agnostic system for providing a fully connected worker risk assessment is disclosed. The system includes an interface and data model for capturing and interpreting one or more variables associated with a worker's body motion and non-body motion related data. The system further includes a processor for aggregating, assessing, and interpreting the one or more input variables to perform a fully connected worker risk assessment based on not only the worker's movement, but also non-movement related data. The processor further provides an output based on the processed one or more input variables to provide a fully connected risk assessment and solutions relating to the same.

Methods, apparatus, and processor-readable storage media for providing an automated services exchange are described herein. An example computer-implemented method includes obtaining provider requests from one or more service providers, wherein each of the provider requests comprises an indication of at least one type of service provided by the corresponding service provider and attributes associated with the at least one type of the service; processing the provider requests, wherein the processing for a respective one of the provider requests comprises generating a corresponding set of metrics associated with the at least one type of service and the attributes of the respective provider request; and matching a given one of the provider requests to at least one consumer request based at least in part on: the processing and constraints identified in the at least one consumer request with respect to at least a portion of the attributes of the given provider request.

Methods and systems are presented herein for assessing risk associated with a vendor providing services and/or other products to a financial institution, for preparation of associated risk assessment reports or vendor oversight reports, and for maintenance of a plurality of risk assessment reports or oversight reports associated with a plurality of vendors.

The present disclosure provides a consistency evaluation method for a traditional extraction process and a modern extraction process of a traditional Chinese medicine (TCM) compound preparation. In the present disclosure, the reference correlation degree is calculated based on the relative deviation. The reference correlation degree is within a threshold interval of [−∞, 1]. If the relative deviation is 0, the reference correlation degree is 100%, and at the moment, the quality of a modern extraction sample is completely consistent with that of a reference sample. Thus, compared with the relative deviation, the reference correlation degree can represent a quality difference between the modern extraction sample and the reference sample more intuitively and clearly. Comprehensive evaluation conducted in combination of a subjective weighting method and an objective weighting method reflects the subjective will of a decision maker, but does not depart from actual data, making a final weighting result more persuasive.

An information processing device includes a communication unit and a control unit. The control unit selects at least one instant message as a selected message from one or more instant messages transmitted and received between terminal devices including a first terminal device. The control unit selects the selected message based on at least one of pick-up time and drop-off time of a vehicle picking up and dropping off a first user of the first terminal device. The control unit determines evaluation of a service provided in the vehicle based on the selected message.

An automated method for improving application developers' cybersecurity competencies is provided. The method includes: breaking each application of a set of computer applications into one or more pieces each piece being developed by a corresponding one of a plurality of application developers; associating each piece of each application with its corresponding application developer; performing cybersecurity assessment testing on the set of computer applications in order to generate cybersecurity assessment results for the set of computer applications; building a cybersecurity competency profile for each application developer using the generated cybersecurity assessment results attributed to corresponding pieces associated with the application developer; grouping the application developers into at least two groups using unsupervised machine learning on the built cybersecurity competency profiles; and choosing, for each application developer based on the corresponding groups to which the application developer belongs, a subset of training courses to improve the cybersecurity competency of the application developer.

A computerized-method for identifying nonadherence to contact-center practice rules is provided herein. The computerized-method includes operating a data-analyzer module. The said data-analyzer module includes: (i) retrieving a set of rules; (ii) monitoring activities of each user via one or more product-applications by receiving a stream of data related to the activities from the one or more applications. The stream of data may include details of the monitored activities; (iii) comparing details of the monitored activities with each rule in the set of rules to identify one or more activities that are breaching a rule from the set of rules; (iv) for each activity of a related-user from the identified one or more activities: (a) notifying the related-user about a guideline-breaching via a computerized-device of the related-user; and (b) updating the data store of exceptions with the details of the activity that breached the rule from the set of rules.