Abstract: The cost of data-mining is estimated where data-mining services are delivered via a distributed computing system environment. System requirements are estimated for a particular data-mining task for an input data set having specified properties. Estimating system requirements includes applying a partial learning tool to operate on sample data from the input data set.

Abstract: Embodiments for testing embedded systems and their applications in an Internet of Things (IoT) environment by a processor, denoted as a Hardware-in-the-Loop as a Service (HiLaaS). In a simulated environment, one or more simulated entities and one or more real entities in a networked system may be tested in real-time according to received control parameters, for a price. The price is estimated by the system, based on other parameters, and offered to the user to accept or reject. Alternatively, the user may specify the price, the system estimates control parameters, and the user can accept or reject the control parameters. One or more properties of the one or more entities, the network system, or combination thereof may be estimated based on the testing of the one or more simulated entities, when the price and control parameters are accepted.

Abstract: Techniques are described that facilitate disruption control in complex schedules comprising a plurality of interdependent tasks. In one embodiment, a computer-implemented method comprises forecasting, by a device operatively coupled to a processor, probability distributions of time delays added to respective tasks of a complex schedule using a stochastic model for the respective tasks, current delay information associated with the respective tasks, and one or more defined mitigating actions that reduce or eliminate time delay attributed to a delay component of the stochastic model. The method further comprises, determining, by the device, loss information regarding losses, wherein losses can include costs attributed to the time delays and costs related to the one or more defined mitigating actions. The method can further comprise determining, by the device, a recommendation regarding implementation of the one or more defined mitigating actions based on the loss information.

Abstract: Embodiments describing an approach for managing multiple concurrent dialogs between a user and a plurality of devices and services based on a multi-modal dialog broker, embodiments comprise receiving instructions from at least one of: one or more users, the one or more devices, or the one or more services. Managing the instructions from the at least one of: one or more users, the one or more devices, or the one or more services. Obtaining one or more dialog variants. Determining a preferred dialog variant, in which responsive to determining the preferred dialog variant, executing the preferred dialog variant, and outputting the preferred dialog variant.

Abstract: Techniques for autonomously optimizing traffic flow amongst one or more traffic junctions are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a piece-wise sinusoidal representation of traffic arrival at a first traffic junction.

Abstract: Techniques for autonomously optimizing traffic flow amongst one or more traffic junctions are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a piece-wise sinusoidal representation of traffic arrival at a first traffic junction. The computer-implemented method can also comprise determining, by the system, an offset a parameter of one or more traffic junctions based on the piece-wise sinusoidal representation and a polynomial objective.

Abstract: A system and method for cognitive risk mitigation are presented. Embodiments comprise journey prediction, parsing of data sources, risk assessment and mitigation, and natural-language user interaction by a cognitive processor. Data is gathered from a plurality of data sources and analyzed in the context of one or more of the user's intention(s). A dialogue with the user, in natural language, aims to provide and select one or more suggestions relating to the one or more user intention(s) such that the risk(s) relating to the one or more user's intention(s) is reduced. During the dialogue, cognitive reasoning may be performed, wherein the cognitive reasoning includes the ability to justify each suggestion and the ability to infer information from the interaction such as, for example, data obtained in a dialogue may inform subsequent inferences. The embodiments may use speech synthesis and speech recognition in an interactive spoken dialogue.

Abstract: Techniques for autonomously optimizing traffic flow amongst one or more traffic junctions are provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a piece-wise sinusoidal representation of traffic arrival at a first traffic junction. The computer-implemented method can also comprise determining, by the system, an offset a parameter of one or more traffic junctions based on the piece-wise sinusoidal representation and a polynomial objective.

Abstract: A method includes establishing a cost for consumption of a given resource by a given resource consumer for a designated period of time, the cost comprising a fixed cost for consumption of the given resource up to a threshold consumption level for the designated time period and an additional cost associated with consumption of the given resource exceeding the threshold consumption level for the designated period of time, monitoring consumption of the given resource by the given resource consumer, determining whether resource consumption by the given resource consumer is projected to exceed the threshold consumption level over the designated time period, generating an alert responsive to determining that resource consumption by the given resource consumer is projected to exceed the threshold consumption level over the designated time period, and providing the alert for presentation via a user interface of a user device associated with the given resource consumer.

Abstract: A mechanism is provided for optimization of mixed-criticality systems. A plurality of strategies is received that are in a fixed order of criticality. For each strategy in the plurality of strategies, a multivariate objective function and a multivariate constraint in a multivariate decision variable is obtained. A number of strategies of the plurality of strategies that are feasible in combination are maximized. A solution that is feasible for the number of strategies that are feasible in combination is generated such that the objective of a least-critical strategy that is feasible in combination with the other strategies in the number of strategies is optimized.

Abstract: A method includes establishing a cost for consumption of a given resource by a given resource consumer for a designated period of time, the cost comprising a fixed cost for consumption of the given resource up to a threshold consumption level for the designated time period and an additional cost associated with consumption of the given resource exceeding the threshold consumption level for the designated period of time, monitoring consumption of the given resource by the given resource consumer, determining whether resource consumption by the given resource consumer is projected to exceed the threshold consumption level over the designated time period, generating an alert responsive to determining that resource consumption by the given resource consumer is projected to exceed the threshold consumption level over the designated time period, and providing the alert for presentation via a user interface of a user device associated with the given resource consumer.

Abstract: A yield management system, method, and non-transitory recording medium for an event, including modeling demand for tickets for the event to create a demand model, analyzing data comprising recent consumer purchases of the tickets for the event and recent advertising for the same event, and adjusting decision variables, comprising advertising spending for the event, the split thereof to various media, and the price of tickets, based on the data and the demand model.

Abstract: The cost of data-mining is estimated where data-mining services are delivered via a distributed computing system environment. System requirements are estimated for a particular data-mining task for an input data set having specified properties. Estimating system requirements includes applying a partial learning tool to operate on sample data from the input data set.

Abstract: The cost of data-mining is estimated where data-mining services are delivered via a distributed computing system environment. System requirements are estimated for a particular data-mining task for an input data set having specified properties. Estimating system requirements includes applying a partial learning tool to operate on sample data from the input data set.

Abstract: A mechanism is provided for synchronization of concurrent optimization and forecasting. A change between current forecast input data most recently received from a forecasting mechanism and forecast input data used in a current iterative execution of a mechanism for solving optimization problems is estimated with respect to the objective function employed in the optimization problem. A threshold is estimated by evaluating the progress of the mechanism for solving optimization problems in a current execution. A determination is made as to whether the change is greater than or equal to the threshold. Responsive to the change being greater than or equal to the threshold, further computation by the mechanism for solving optimization problems is canceled, restarted, or rescheduled. Responsive to the change being less than the threshold, computation by the sensitivity-aware scheduler is allowed to continue.

Abstract: A mechanism is provided for synchronization of concurrent optimization and forecasting. A change between current forecast input data most recently received from a forecasting mechanism and forecast input data used in a current iterative execution of a mechanism for solving optimization problems is estimated with respect to the objective function employed in the optimization problem. A threshold is estimated by evaluating the progress of the mechanism for solving optimization problems in a current execution. A determination is made as to whether the change is greater than or equal to the threshold. Responsive to the change being greater than or equal to the threshold, further computation by the mechanism for solving optimization problems is canceled, restarted, or rescheduled. Responsive to the change being less than the threshold, computation by the sensitivity-aware scheduler is allowed to continue.

Abstract: A method for forecasting time delays added to a scheduled start time and a scheduled end time of a task includes generating a stochastic model of the task and resources affecting the task, the stochastic model includes a reactionary delay component that is a function of previous task end times and a root cause delay component that is an independent random process at a specific time. The method further includes: calculating a probability distribution of time delays added to the scheduled start time as a combination of the reactionary delay component and the root cause delay component using the stochastic model to provide a probability distribution of start times; and calculating a probability distribution of time delays added to the scheduled end time as a combination of the reactionary delay component and the root cause delay component using the stochastic model to provide a probability distribution of end times.

Abstract: A method for forecasting time delays added to a scheduled start time and a scheduled end time of a task includes generating a stochastic model of the task and resources affecting the task, the stochastic model includes a reactionary delay component that is a function of previous task end times and a root cause delay component that is an independent random process at a specific time. The method further includes: calculating a probability distribution of time delays added to the scheduled start time as a combination of the reactionary delay component and the root cause delay component using the stochastic model to provide a probability distribution of start times; and calculating a probability distribution of time delays added to the scheduled end time as a combination of the reactionary delay component and the root cause delay component using the stochastic model to provide a probability distribution of end times.

Abstract: In order to modulate consumer usage of service categories for accessing a resource, an electronic service menu is first transmitted by a computer system. The electronic service menu includes a cost indicator and a benefit indicator for each of the service categories. Subsequent to the transmission of the electronic service menu, consumer usage data about each of the service categories is tracked. The consumer usage data is then analyzed. Based on this analysis, the service capacity of at least one of the service categories is adjusted. Also based on the analysis, a revised electronic service menu is transmitted by the computer system. The revised electronic service menu includes at least one revised cost indicator and at least one revised benefit indicator.

Abstract: A mechanism is provided for optimization of mixed-criticality systems. A plurality of strategies is received that are in a fixed order of criticality. For each strategy in the plurality of strategies, a multivariate objective function and a multivariate constraint in a multivariate decision variable is obtained. A number of strategies of the plurality of strategies that are feasible in combination are maximized. A solution that is feasible for the number of strategies that are feasible in combination is generated such that the objective of a least-critical strategy that is feasible in combination with the other strategies in the number of strategies is optimized.