Abstract: A risk management method, system, and non-transitory computer readable medium, include a data analyzing circuit configured to analyze user data, site data, and equipment data to map prior behavior types to an event on a site, a relationship determining circuit configured to determine a relationship between the mapped data and the event based on behaviors exhibited by the user and an impact on a performance factor and a risk factor, and a reinforcement learning circuit configured to use reinforcement learning to learn the performance factor to the risk factor ratio to optimize an overall site productivity.

Abstract: A queue management system including a user data retrieving circuit configured to retrieve a user property of the user and a queue managing circuit configured to model the plurality of users as a non-Newtonian fluid, to analyze the user properties to assign each user an anisometric polarity parameter, and to solve an objective function for a queue property to cause the plurality of users to collectively act as the non-Newtonian fluid in the queue.

Abstract: Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.

Abstract: A method, system, and non-transitory compute readable medium for a fraud detection including a calendar reading device configured to read calendar data of a calendar for a user, a purchase detection device configured to detect an attempted purchase using a credit-card of the user, and a risk detection device configured to detect fraud by calculating a risk based on the calendar data and data related to the attempted purchase.

Abstract: A queue management system including a user data retrieving circuit configured to retrieve a user property of the user and a queue managing circuit configured to model the plurality of users as a non-Newtonian fluid, to analyze the user properties to assign each user an anisometric polarity parameter, and to solve an objective function for a queue property to cause the plurality of users to collectively act as the non-Newtonian fluid in the queue.

Abstract: A queue management method, system, and non-transitory computer readable medium, include managing a queue by modeling a plurality of users in the queue as a non-Newtonian fluid and by modeling the plurality of users as a suspension of particles in the non-Newtonian fluid based on an analysis of cognitive data of each of the plurality of users, a wearable's signals for each user of the plurality of users, and a most likely direction of a movement of each user of the plurality of users to estimate a viscosity of the plurality of users in the non-Newtonian fluid.

Abstract: A cognitive state amelioration method, system, and computer program product, include predicting a cognitive state of a user based on at least one of a plurality of inputs including a physiological state of the user, a gesture of the user, a speech pattern of the user, and an internal state status of the user received from a second user, performing an ameliorating action to treat the cognitive state of the user when the predicting predicts a negative type of the cognitive state, and learning an effectiveness of the ameliorating action for treating the negative type of the cognitive state for the predicting to predict a different cognitive state, thereby to dictate a different ameliorating action to treat the different cognitive state more effectively.

Abstract: Embodiments of the invention control a device based on physiological measurements associated with a user. A determination is made that a user has manually adjusted a controlled device. A context associated with the user is identified in response to determining that the user has manually adjusted the controlled device. A change is detected in at least one physiological measurement associated with the user in response to the controlled device being manually adjusted. A target physiological measurement associated with at least one physiological measurement is modified based on the change that has been detected. The context that has been identified is associated with the target physiological measurement that has been modified.

Abstract: Techniques for drone device control are provided. In one example, a computer-implemented method comprises establishing, by a plurality of drone devices respectively operatively coupled to processors and coordinating with one other, a defined region of a defined coordinate space of a geographic area, wherein the defined region is associated with an animal. The computer-implemented method also comprises monitoring, by the plurality of drone devices, a physical relationship between the animal and the defined region. The computer-implemented method can also comprise, in response to identifying that the physical relationship between the animal and the defined region fails to meet a criterion, performing, by the plurality of drone devices, a pattern of operations selected to alter the physical relationship between the animal and the defined region to satisfy the criterion.

Abstract: Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.

Abstract: Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.

Abstract: A queue management method, system, and non-transitory computer readable medium, include managing a queue by modeling a plurality of users in the queue as a non-Newtonian fluid and by modeling the plurality of users as a suspension of particles in the non-Newtonian fluid based on an analysis of cognitive data of each of the plurality of users, a wearable's signals for each user of the plurality of users, and a most likely direction of a movement of each user of the plurality of users to estimate a viscosity of the plurality of users in the non-Newtonian fluid.

Abstract: A queue management method, system, and non-transitory computer readable medium, include a queue management system including a device recognition circuit configured to recognize when a user device enters a queuing zone, and place a user having the user device into a queue with a plurality of users, a user data retrieving circuit configured to retrieve at least one of cognitive data and contextual data of the user, and a queue managing circuit configured to analyze the contextual data and the cognitive data to create a queue property for each user of the plurality of users in the queue based on the analyzed contextual data and the analyzed cognitive data.

Abstract: Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.

Abstract: Techniques for facilitating the autonomous presentation of a self-driving vehicle are provided. In one example, a method can include a system operatively coupled to a processor, where the system: determines a feature of a self-driving vehicle based on information regarding an entity in a pending transaction; determines a task to be performed by the self-driving vehicle based on the feature; and generates an instruction for the self-driving vehicle to perform the task.

Abstract: A restaurant management method, system, and non-transitory computer readable medium, include receiving a state of a user from user data, determining a confidence value that a restaurant change results in an improvement of the state of the user, and deploying the restaurant change when the confidence value is greater than a predetermined threshold value.

Abstract: Techniques for drone device control are provided. In one example, the technique includes monitoring, by a drone device operatively coupled to a processor and allocated to a vehicle in operation, one or more conditions associated with the vehicle. The technique also includes, in response to identifying, by the drone device, a defined condition of the one or more conditions: moving, by the drone device, to a position relative to the vehicle and determined based on the defined condition; and performing, by the drone device, an indication operation determined based on the defined condition.

Abstract: A method, system, and non-transitory compute readable medium for a fraud detection include determining, via a risk detection device, a location of a user device at a time of an attempted purchase, determining, via the risk detection device, an intended location of the user from calendar data, and updating, via the risk detection device, a likelihood of fraud based on the intended location of the user and the location of the attempted purchase.

Abstract: A method, system, and non-transitory compute readable medium for a fraud detection including a calendar reading device configured to read calendar data of a calendar for a user, a purchase detection device configured to detect an attempted purchase using a credit-card of the user, and a risk detection device configured to detect fraud by calculating a risk based on the calendar data and data related to the attempted purchase.

Abstract: Techniques for drone device control are provided. In one example, the technique includes monitoring, by a drone device operatively coupled to a processor and allocated to a vehicle in operation, one or more conditions associated with the vehicle. The technique also includes, in response to identifying, by the drone device, a defined condition of the one or more conditions: moving, by the drone device, to a position relative to the vehicle and determined based on the defined condition; and performing, by the drone device, an indication operation determined based on the defined condition.