Abstract: A signal representing a sound can be received. A machine learning model can be run to identify that the sound triggers a reaction in a user hearing the sound. A preventive action can be automatically activated to mitigate the reaction. The user's reactions can be monitored. Responsive to determining that the user's reaction has been mitigated or suppressed, the preventive action can be deactivated. The machine learning model can be retrained using at least the signal as new training data.

Abstract: Systems and methods to facilitate sleep are described. In on example, a cognitive alarm clock system for children learns sleep patterns and activities towards recommending sleep schedules and teaching independence. The system may detect the cognitive state of a child based on voice or cry pattern recognition, a time of day or night, scheduled activities, and social context, among other factors. The system may initiate actions to facilitate sleep in response to the cognitive factors. For example, the system may adjust lighting or push back a wakeup time. In another example, the system may use the cognitive analysis to teach children good sleeping habits by making recommendations to facilitate a good night's rest and encourage independence.

Abstract: Systems and methods to facilitate sleep are described. In on example, a cognitive alarm clock system for children learns sleep patterns and activities towards recommending sleep schedules and teaching independence. The system may detect the cognitive state of a child based on voice or cry pattern recognition, a time of day or night, scheduled activities, and social context, among other factors. The system may initiate actions to facilitate sleep in response to the cognitive factors. For example, the system may adjust lighting or push back a wakeup time. In another example, the system may use the cognitive analysis to teach children good sleeping habits by making recommendations to facilitate a good night's rest and encourage independence.

Abstract: An image file is to be posted on a social media web site is automatically detected, the image file containing at least an image of a first individual with a background image depicting a location determined to be unsafe. A risk level associated with the location is determined. Based on the risk level, an action is automatically activated, which prevents at least a second individual from taking a photograph of the second individual at the location.

Abstract: Methods, systems, and computer program products are provided. Aspects include determining characteristic data associated with a physical environment, based on the characteristic, determining an elastic map for the physical environment, wherein the elastic map comprises a graph comprising a set of nodes and a set of edges, wherein each edge connects two nodes and a set of configurable parameters that define an elastic coupling for each edge, determining an initial physical configuration of the set of nodes in the physical environment based on the elastic map, causing a set of mobile sensors to establish the initial configuration in the physical environment, simulating a mobile sensor elastic coupling between each mobile sensor based on the elastic energy function for each edge, collecting an environmental data point associated with the physical environment, and adjusting a configuration of the set of mobile sensors based on the environmental data point.

Abstract: The present invention is a system and method that generates a Table of Contents (TOC) customized to the user knowledge about the concept(s) in the user query and the specific context and preferences of the user. The invention identifies search concepts within the search queries, receives search results, and splits the search results into one or more result segments. In a preferred embodiment, a correlation strength between concepts in one or more of the result segments and the user search query, along with reference to the user knowledge, context, and/or preferences determine which result segments are selected in sequenced to form the TOC.

Abstract: An operation performed with a computer cursor on a graphical user interface (GUI) can be detected, which operation copies content pointed to by the computer cursor into a memory buffer. An analysis can be performed to determine a risk associated with the operation. Based on the analysis, a change in a GUI element of the GUI can be made or caused.

Abstract: An emergency vehicle that is displaying emergency lights detects an approaching vehicle, and assesses road conditions, intensity of the emergency lights at the approaching vehicle, a response of the approaching vehicle to the emergency lights, and a state variable related to a driver of the approaching vehicle. The emergency vehicle then obtains a likelihood value that the approaching vehicle will initiate an accident, by supplying information about the road conditions, the intensity of the emergency lights at the approaching vehicle, the response of the approaching vehicle, and the state variable as inputs to a neural network trained to correlate accidents to such information. In response to the likelihood value exceeding a threshold value, the emergency vehicle modifies the emergency lights.

Abstract: Context associated with content may be received. An additional content may be generated for insertion into the content. The additional content can be created to be within the context associated with the content and based on a likely responsiveness of the user to the additional content, the additional content referring to an item. The additional content preserves continuity and/or semantics in the context of the content.

Abstract: A natural language processing system for analyzing speech includes a computer processing device configured to receive recorded speech of a person. The computer processing device constructs a baseline speech model of the person, the baseline speech model of the person including a property of speech based on a personal attribute of the person, compares current recorded speech of the person to the baseline speech model of the person to determine a deviation of the property of speech therebetween, and determines if the deviation of the property of speech meets a threshold of the property of speech that is defined for a disorder.

Abstract: Methods and systems for crop grading and crop management. One or more images of crops are obtained and one or more crop related features are at least one of identified or extracted from the one or more images. A crop health status is determined based on the one or more crop related features, an environmental context, a growth stage of the crop, and a farm cohort by using a computerized deep learning system to perform an automated growth stage analysis. One or more actions are at least one of recommended, triggered, and performed.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Abstract: A set of learner data associated with a learner is received. The set of learner data includes at least a real-time data stream, e.g., derived from instrumentation, in a social network enabled digital learning environment. Based on the set of learner data, at least one learning improvement strategy is determined for improving the learner's learning capability. Atomic level mentorship activities are generated. Each atomic level mentorship activity is targeted with a specific skill and knowledge item and having an estimated duration period. At least one mentorship is identified from at least one social network platform. An initial incentive structure comprising at least an amount of payment and payment modality is created. The atomic level mentorship activities with the initial incentive structure are presented.

Abstract: An emergency vehicle that is displaying emergency lights detects an approaching vehicle, and assesses road conditions, intensity of the emergency lights at the approaching vehicle, a response of the approaching vehicle to the emergency lights, and a state variable related to a driver of the approaching vehicle. The emergency vehicle then obtains a likelihood value that the approaching vehicle will initiate an accident, by supplying information about the road conditions, the intensity of the emergency lights at the approaching vehicle, the response of the approaching vehicle, and the state variable as inputs to a neural network trained to correlate accidents to such information. In response to the likelihood value exceeding a threshold value, the emergency vehicle modifies the emergency lights.

Abstract: A system, method, and computer program product for verifying signatures. The system includes at least one processing component, at least one memory component, and a reference storage comprising a set of reference signatures. The system also includes a model generator configured to generate a signature model based on the set of reference signatures. Further, the system includes a verification component configured to receive a signature, and determine whether the signature is valid.

Abstract: Method, system, and computer product for operating a self-driving vehicle (SDV). The SDV receives information from a calendar entry of a passenger's schedule about an event at a destination location to which the SDV is to drive the passenger to. The SDV sensors detect one or more behaviors or cognitive states of the passenger while in the vehicle. The SDV determines an optimal arrival time at the destination location based on the user's schedule information and the user's behavior or cognitive state; and further alters the driving speed or route taken by the SDV based on the determined optimal arrival time and an estimated travel time. The reshaping of the SDV driving characteristics is based on calendar information received including: an event meeting time, event topic, attendees, event importance. A detected passenger behavior can include talking on a phone, reading, or being in a tired, sleeping, agitated or nervous state.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Abstract: Embodiments of the present invention describe predictively reconstructing a physical event using augmented reality. Embodiments describe, identifying relative states of objects located in a physical event area by using video analysis to analyze collected video feeds from the physical event area before and after a physical event involving at least one of the objects, creating a knowledge corpus including the video analysis and the collected video feeds associated with the physical event and historical information, and capturing data, by a computing device, of the physical event area.

Abstract: A method for enhancing speech performance includes communicating, via an input/output (I/O) device, speech data of a patient with speech problems, segmenting the speech data, generating one or more feature vectors based on at least the segmented speech data, determining whether the one or more feature vectors match with one or more recognition objects pre-trained using clinical data of one or more other patients, determining a speech disorder based on a matched result between the one or more feature vectors and the one or more recognition objects, and communicating, via the I/O device, one or more ameliorative actions for mitigating the determined speech disorder.

Abstract: A social media control method, system, and computer program product, include detecting a contextual meaning of a content of a third-party post on a user's social media account, classifying the content into user-defined categories based on an overlap between the contextual meaning and the user-defined categories, identifying an undesired piece of information from the content, identifying a trusted online friend within a social media circle of the user, and providing a one-time access control to the identified trusted online friend to rectify the undesired content in the third-party post.