Abstract: Media playback may be controlled or adapted using behavioral player adaptation. The user and the user's physical environment are monitored via sensors. Sensor data representative of relevant user behavior and physical properties of the environment where the user is located is collected, aggregated, and pre-processed to determine the state of parameters of the sensed environment that may be relevant. The pre-processed sensor data is examined to determine the state of user model parameters. Machine learning may be used for the data examination; a neural network is used to learn the key parameters from the pre-processed data that then are used for media playback adaptation and/or control.

Abstract: The present description refers to a computer implemented method, computer program product, and computer system to determine a plurality of electric charging schedules for one or more electric vehicles, determine, for each of the electric charging schedules, a plurality of charging objective values, assign a weight to each of the charging objective values, wherein one set of weights is used for the plurality of electric charging schedules, calculate a fitness value for each of the electric charging schedules based on the plurality of charging objective values for each respective electric charging schedule and the set of weights, identify the electric charging schedule having a highest fitness value, and select the electric charging schedule having the highest fitness value for charging one or more electric vehicles.

Abstract: The present description refers to a computer implemented method, computer program product, and computer system to determine a plurality of electric charging schedules for one or more electric vehicles, determine, for each of the electric charging schedules, a plurality of charging objective values, assign a weight to each of the charging objective values, wherein one set of weights is used for the plurality of electric charging schedules, calculate a fitness value for each of the electric charging schedules based on the plurality of charging objective values for each respective electric charging schedule and the set of weights, identify the electric charging schedule having a highest fitness value, and select the electric charging schedule having the highest fitness value for charging one or more electric vehicles.

Abstract: Methods and related systems for evaluating pattern-based constraints on business process models provide specifications for business process models, related structural patterns, and constraints on structural patterns so that instances of structural patterns can be identified in models and constraints on these instances can be evaluated. Model elements may include tasks that correspond to prescribed activities, events that correspond to states of the model, and gateways that control process flow between model elements. Identifying instances of structural patterns within models may include assigning classes or textual labels to model elements and then employing a search query or production rule to search over the model elements for instances of the structural patterns.