Provided are a legal information processing system, method, and non-transitory computer-readable storage medium storing program which enable the acquisition of useful information anticipating trends in the revision of legislation, regulations, or standards. This legal information processing system sets one or more key persons who are involved in legislation, regulations, or standards, collects at least public information which is created by the key person or in the publication of which the key person is involved, and predicts a trend in the revision of legislation, regulations, standards on the basis of the content of the collected information.

A motorized lifting and transfer chair includes a base having a front portion and an opposing rear portion, where the rear portion has a pair of foot rests. The chair also includes a plurality of wheels mounted to the base configured to be selectively locked, and a vertical post assembly secured proximate to the rear portion of the base and extending upwards from the base. In addition, the chair includes a seating platform cantilevered from the vertical post assembly, where the seating platform comprises two portions with an aperture formed along two adjacent edges of the two portions and the two portions are configured to swing open and closed about the vertical post assembly. The chair includes a motorized device that raises and lowers the seating platform, and a latch is configured to secure the two portions of the seating platform closed.

By accurately predicting industrial aging processes (IAP), such as the slow deactivation of a catalyst in a chemical plant, it is possible to schedule maintenance events further in advance, thereby ensuring a cost-efficient and reliable operation of the plant. So far, these degradation processes were usually described by mechanistic models or simple empirical prediction models. In order to accurately predict IAP, data-driven models are proposed, comparing some traditional stateless models (linear and kernel ridge regression, as well as feed-forward neural networks) to more complex stateful recurrent neural networks (echo state networks and long short-term memory networks). Additionally, variations of the stateful models are discussed. In particular, stateful models using mechanistical pre-knowledge about the degradation dynamics (hybrid models). Stateful models and their variations may be more suitable for generating near perfect predictions when they are trained on a large enough dataset, while hybrid models may be more suitable for generalizing better given smaller datasets with changing conditions.

A method of defining a deployment specification for one or more infrastructure components as part of a transmission network for a utility service in a defined geographic region includes receiving a deployment specification for each of a plurality of deployment options, each received specification including a location and type of one or more infrastructure components for deployment in the region, each type of infrastructure component having associated infrastructure characteristics, and each location having associated location characteristics. The method further includes receiving environmental characteristics for the region; executing a classifier, for each deployment specification, based on one or more of the infrastructure characteristics, the location characteristics, and the environmental characteristics to forecast a measure of susceptibility of infrastructure deployed in accordance with the specification to one or more operational impediments of the infrastructure in use; and selecting a deployment specification based on the forecast susceptibilities.

The exemplary embodiments disclose a method, a computer program product, and a computer system for managing environment change. The exemplary embodiments may include determining a plurality of change and risk models for a plurality of computing environments, generating a plurality of association rules based on the plurality of change and risk models, and generating a joint association rule by combining at least two of the plurality of association rules, wherein the joint association rule indicates, from the three dimensions, an association relationship between changes and risk events over at least a part of the time series.

A system for predicting and prescribing actions for impacting policymaking outcomes may include at least one processor configured to access first information scraped from the Internet to identify, for a particular pending policy, information about a plurality of policymakers slated to make a determination on the pending policy. The processor may parse the scraped first information to determine an initial prediction relating to an outcome of the pending policy. The processor may access second information to identify an action likely to change at least one of the initial prediction and the propensity of at least one policymaker, to thereby generate a subsequent prediction corresponding to an increase in a likelihood of achieving the desired outcome. The processor may display to the system user a recommendation to take the action in order to increase the likelihood of achieving the desired outcome.

Methods, apparatus, systems, and computer program products are disclosed for utilizing specially configured machine learning models to generate incremental currency value(s) associated with one or more target merchant data objects. Some embodiments, based on one or more market record sets, identify an actual electronic currency value for a total merchant data object set, and include a counterfactual model configured to generate a counterfactual electronic currency value for use in determining a counterfactual incremental electronic currency impact, and in some embodiments for ranking other models. Embodiments, additionally or alternatively, include an incrementality-trained ensemble model for generating a predictive incremental electronic currency impact. The incrementality-trained ensemble model may be trained to predict based on the rankings of the outputs of the counterfactual model. Embodiments may further rank target merchant data objects and perform one or more additional actions, including assigning the target merchant data objects to sales account data structures for management.

In an example, a cloud service management node includes a knowledge base having a plurality of billing rules for a cloud computing environment, a processor, and a memory coupled to the processor. The memory may include a discount predictor module to receive an actual bill related to consumption of a cloud service in the cloud computing environment. Further, the discount predictor module may determine a variation between the actual bill and an expected cost from a public rate card by comparing the actual bill with the expected cost. Furthermore, the discount predictor module may evaluate the plurality of billing rules to predict a discount type and a discount associated with the discount type that matches the variation between the actual bill and the expected cost from the public rate card. Further, the discount predictor module may output the discount type and the discount on an interactive user interface.

The present invention comprises a novel innovation and strategic management software application consisting of an automated method and system for receiving business information and data from a user describing the business products, services and strategy and finances to translate to generated systems, processes and enhanced outcomes. Utilizing artificial intelligence and machine learning for language processing, automated systems render business innovation and strategy models, position business, products and services and performs the management of these. Management of services and processes are communicated through the software application. Communication of project status, tasks and performance are indicated alongside other communications such as audio, visual/video text, and data intelligence which are transferable between internal and external users or team members in the application. Curated education, customized analytics, and insights promote a robust system for information retrieval for users of the application that together provide enhanced competitive competencies.

A system is provided for an artificial intelligence engine adapted to identify robotic process automation' opportunities based on return on investment (ROI) potential for automation. The system includes a processor and a computer readable medium configured to perform operations comprising receiving an event log of a plurality of user actions, splitting the plurality of user actions into a plurality of user action sentences, determining a sequence of user actions in the plurality of user action sentences based on a recurrence for the sequence in the plurality of user action sentences, determining a score for the sequence based on a time duration in which the user completes the sequence and based on types of the plurality of user actions in the sequence, and filtering the sequence with a plurality of other sequences.