A system to assess the current, or future workload of a pilot and automatically providing annunciation when needed to the pilot, as well as to resources that support the pilot. The system may automatically, and without pilot involvement, assess the workload for the pilot based on incoming events and abnormal scenarios. The predicted incoming events may be related to operation data, such as navigation information, weather, traffic avoidance, and so on. The system may also detect abnormal scenarios, such as engine warnings, fuel or other aircraft issues. The system may determine whether the predicted incoming events or the abnormal scenario satisfies one or more pre-defined criteria. Based on the event satisfying one or more criteria, the system may output an annunciation to either the pilot, resources that support the pilot, such as an additional pilot and air traffic control (ATC).

The present disclosure provides a vehicle passenger flow statistical method, including: acquiring, by a server, door opening time and door closing time of a vehicle during any one door opening and closing process of door opening and closing processes in a pending statistical period; acquiring, by the server, a first set of images and a second set of images in a carriage of the vehicle according to the door opening time and the door closing time; and acquiring, by the server, the number of on-board people and the number of off-board people during the door opening and closing process according to the first set of images and the second set of images. The present disclosure can improve efficiency and accuracy of passenger flow statistics according to which an operation plan of the vehicle may be optimized timely and effectively.

In some embodiments, the disclosure is directed to a system that predicts the carbon footprint of an industrial process. In some embodiments, the system is configured to monitor the amount of energy used in one or more process steps in an industrial process. In some embodiments, the system is configured to determine a carbon intensity for each of the one or more process steps. In some embodiments, the system is configured to generate a report including the carbon intensity. In some embodiments, the system is configured to determine the effect different raw material have on each of the one or more processing steps. In some embodiments, the system is configured to generate an optimum blend of raw materials that reduces the carbon intensity of one or more steps. In some embodiments, the system is configured to generate a blend of source fuels that reduces the industrial facilities overall carbon footprint.

Techniques are described for providing customizable sign-on functionality, such as via an access manager system that provides single sign-on functionality and other functionality to other services for use with those services’ users. The access manager system may maintain various sign-on and other account information for various users, and provide single sign-on functionality for those users using that maintained information on behalf of multiple unrelated services with which those users interact. The access manager may allow a variety of types of customizations to single sign-on functionality and/or other functionality available from the access manager, such as on a per-service basis via configuration by an operator of the service, such as co-branding customizations, customizations of information to be gathered from users, customizations of authority that may be delegated to other services to act on behalf of users, etc., and with the customizations that are available being determined specifically for that service.

An exemplary method provides matching natural gas subsurface production to contractual quantities or demand. A demand for hydrocarbons and an unconstrained supply from multiple reservoirs according to one or more unconstrained subsurface supply parameters are determined. A constrained supply is calculated according to parameterized constraints associated with wells, facilities, and processing systems of the unconstrained subsurface supply parameters according to a selected model option. Hydrocarbons quantities in the constrained supply are matched with the demand for hydrocarbons.

From a first set of natural language documents describing a demand for a movable physical item, a set of demand features is extracted. From a second set of natural language documents describing a supply of the movable physical item, a set of supply features is extracted. A correlation quantifying a relationship between the set of demand features and the set of supply features is computed. Using the correlation and the correlation trend, an attraction between the set of demand features and the set of supply features is modeled as a gravitational force. Using a routing determined according to the attraction, the movable physical item is caused to be transported.

Automated supply chain management techniques are disclosed. For example, a method comprises the following steps. The method obtains a demand for a given number of an item associated with a manufacturing order. The method obtains a set of classifications for a set of suppliers based on historical data corresponding to each of the suppliers, and obtains a criticality indicator for the demand. The method generates an allocation for the demand across at least a subset of the set of suppliers based on the set of classifications and the criticality indicator, wherein each of the suppliers in the subset is allocated a given proportion of the demand in accordance with the generated allocation.

A non-iterative revising tool is provided, which interfaces with a WFM service running on one or more WFM hosts. The non-iterative revising tool can configure a client computing device to export timetable records and staffing forecast records from a WFM service; non-iteratively revise, for a referent employee, task assignments of timetable records to fulfill forecast workload volumes of a primary task type according to conditions not implemented by conventional WFM services; and import revised timetable records into the WFM service after work task assignments have been at least partially aligned with forecast workload volumes based on an alignment objective. The non-iterative revising tool and the WFM services configuring client computing devices and WFM hosts in conjunction allows numerous data records to be exported from WFM hosts running the WFM services, revised over a single pass by client computing devices running the non-iterative revising tool, and imported back to the WFM hosts running the WFM services, in just minutes.

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.

A system for incremental solution of the shift design and assignment problem comprises an interface configured to receive an incremental change and an existing schedule. The system comprises a processor to determine whether labor demand has changed; in response to labor demand having been changed, generate an updated set of shift candidates; determine a new cost function; restart a solver using the updated set of shift candidates, the existing schedule, the incremental change, and the new cost function, wherein the solver comprises a mixed integer programming (MIP) solver, and wherein the MIP solver determines simultaneously a subset of the shift candidates selected in the final schedule and a set of shift assignments of which worker is assigned to which selected shift candidate of the subset of shift candidates.