Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing self qualification of cloud based applications. One of the methods includes analyzing, by a self-qualified process (SQP), a set of risks for a cloud based software platform, wherein each risk comprises a set of features that are being evaluated according to a risk definition; performing, by the SQP, one or more tests related to one or more risks of the set of risks; and based on an outcome of each of the tests, generating a measure of a qualification state for the cloud based software platform, wherein the measure of the qualification state is used to determine self-qualification of the software platform.

The present technology pertains to a method and system for assessing risks associated with facilities, based on using natural language processing. For example, a method can include receiving a natural language input comprising at least one raw text document associated with a facility and generating a plurality of segmented sentences from the raw text documents. The plurality of segmented sentences can be provided as inputs to a machine learning model trained to classify an input segmented sentence over a pre-defined lexicon of pharmaceutical terminology. Each segmented sentence can be classified into one or more classes given by the pre-defined lexicon of pharmaceutical terminology. A secondary classification can be performed for each classified segmented sentence to generate a production issue label based on an analysis of the classified segmented sentence. From the secondary classifications for the classified segmented sentences, at least one production category score for the facility can be generated.

A sales talent development support system includes: a storage that stores sales task information, sales skill information, and sales result expectation value in association with each other; a salesperson information reception unit, which receives an input of execution task information and a sales result achievement value; a sales result determination unit, which determines whether the sales result achievement value has reached the sales result expectation value; an execution task determination unit, which determines whether the execution task information satisfies the sales task information needed to achieve the sales result expectation value that is compared; a sales skill identification unit, which identifies sales skills needed to execute lacked sales tasks; and a sales skill presentation unit, which presents the sales skills specified by the sales skill identification unit.

A computerized-method for identifying and utilizing effectiveness of agent handling multiple concurrent multi-channel interactions is provided herein. The computerized-method includes operating of a Multiple Multi-Channel Effectiveness (MME) module. The MME module includes: (a) operating an interaction module to retrieve one or more concurrent interactions of an agent from the data storage of interactions, according to a time range; (b) calculating an MME score for the agent based on metadata of the one or more concurrent interactions which defines the ability of the agent to handle multiple concurrent multi-channel interactions simultaneously; (c) storing the calculated MME score in the data storage of agents; and (d) sending the MME score to the one or more applications to take one or more follow-up actions based on the MME score.

Computer implemented reconstruction of compliance mapping due to an update in a regulation in the compliance mapping by a computing device includes comparing a first version of a regulation in the compliance mapping to a second, updated version of the first regulation. A change in the second version with respect to the first version is identified. The change may be an added control description, a deleted control description, or an updated control description. Upon determining that the change is an updated control description, the updated control description is analyzed to determine a type of update. The mapping of the regulation is reconstructed based on the change and, if the change is an updated control description, the type of update, using at least one of natural language processing and/or machine learning. The risk of the reconstructed mapping is assessed, and a service owner is notified about the risk of the changes.

An automated system for making quality measure submissions. In one embodiment, the system includes: a data input system; a data output system; a database of descriptive data items; a processor in communication with the data input system, the data output system and the database, and comprising a rules engine to traverse a hierarchical tree of denominator and numerator questions, using patient input and data items from the database of descriptive data items. In one embodiment, the invention relates to an automated review system for providing a multiple measure review of care including: a provider input device for inputting patient data; a patient database; a rules engine in communication with the patient database and traversing a plurality of denominator and numerator rules, using provider input patient data and patient data from the database to generate, from multiple encounters and multiple measures, the review of care subsequent to each visit.

Disclosed are a method and device for managing a project by using cost payment time point settings. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Disclosed are a method and device for managing a project by using data filtering. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Disclosed are a method and device for managing a project by using a data pointer. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

The information processing apparatus, the information processing method, and the program include at least one processor configured to acquire, in at least one piece of processing of the process, at least one piece of information of chemical information or physical information of an object to be processed and a processed object at two points at which elapses of processing times between before the processing and after the processing are different from each other, acquire a calculation value of a difference between numerical values at the two points that are obtained from the information, and set the difference as an explanatory variable, set the quality of the product as an objective variable, and predict the quality of the product based on the calculation value by using a trained model obtained by performing machine learning based on a known data set of the explanatory variable and the objective variable.