Abstract: A computer implemented method processes log events. A computer system determines dependence and independence of training log events. The computer system clusters the training log events with determined dependence and independence to form clustered training log events. The computer system generates an event association model using the clustered training log events. The computer system clusters the log events using the event association model.

Abstract: Embodiments for intelligent mitigation of concentration conflicts by a processor. A concentration level of a user required for one or more primary activities may be determined from one or more data sources. A distraction level indicating a possible impact to the concentration level caused by one or more secondary objects may be determined. One or more actions may be provided to mitigate the possible impact to the concentration level.

Abstract: In a method for improving speech analysis between devices, a processor receives a speech input comprising audio from a speech recognition platform. A processor segments the speech input into input vectors. A processor maps the input vectors to a profile. A processor calculates affinity coefficients between each input vector and the profile. A processor aggregates the input vectors and affinity coefficients in a user profile. A processor implements the user profile in a speech recognition program.

Abstract: Provided are a computer program product, system, and method for training and using a machine learning module to determine locales and augmented reality representations of information on locales to render in an augmented reality display. A determination is made of qualifying locales accessible to a visiting user during a user available time from a current location. Values for locale features of the qualifying locales and values of user features in a user profile of the visiting user are provided as input to a locale attraction machine learning module to determine local attraction scores for the qualifying locales. A determination is made of qualifying locales based on locale attraction scores of the qualifying locales to transmit to the visiting user computing device to cause an augmented reality display to render augmented reality representations of information on the qualifying locales.

Abstract: Embodiments for implementing intelligent audio composition guidance for a video by a processor. One or more acoustic characteristics used in a plurality of video segments may be identified, from a corpus, as having similar acoustic, linguistic, and visual characteristics of a selected video segment.

Abstract: An embodiment includes analyzing a first digital image using a first trained neural network that classifies the first image as having a first context based on a plurality of characteristics of the first image. The embodiment generates a data structure that associates first and second elements depicted in the first image based on an affinity detected between the first and second elements in the first context. The embodiment executes a querying process that searches for information requested by a user, and detects that a search result from the querying process conveys a second context that is different from the first context. The embodiment identifies a third element in the data structure having an affinity with the first element in the second context. The embodiment renders a machine-generated image that is generated using a second trained neural network and depicts the first element and the third element in the second context.

Abstract: According to one embodiment, a method, computer system, and computer program product for three-dimensional printing is provided. The embodiment may include analyzing data of a user. The data is collected while the user is performing an activity. The embodiment may include deriving a user behavior model (UBM) of the user based on the analysis of the data. The embodiment may include calculating a relative comfort coefficient (RCC) of the user for the activity based on attributes of the UBM. The embodiment may include predicting adjustments to the attributes of the UBM which result in the RCC exceeding a threshold value. The predicted adjustments are derived using a convolutional neural network classifier. The embodiment may include defining one or more parameters of a tangible component of an object utilized by the user when performing the activity based on the predicted adjustments.

Abstract: In an approach for monitoring a user's in-flight activity and/or a pattern of movement of a user and warning the user of an in-flight activity or a pattern of movement that could lead to a potential short-term or long-term injury, a processor monitors a body movement and a posture of a user through an application of micro-location analysis enabled by a mesh network of 5G sensors over a period of time. A processor determines whether the body movement and the posture detected can lead to an activity or a series of activities that can result in a potential injury. Responsive to determining a pre-set threshold of risk has been reached, a processor issues a real time alert to the user to warn of the potential injury.

Abstract: The present invention may include a computer receives one or more communications and data from a sensor. The computer determines an activity of a user based on the received data, wherein the activity is determined by a trained neural network. The computer calculates a stress coefficient based on the activity and the data. The computer generates a cognitive notifications choreographer model from the stress coefficient and one or more communications and causes a communication software to reply to the one or more communications based on the cognitive notifications choreographer model determining the stress coefficient above a threshold value.

Abstract: A computer-implemented method includes: monitoring, by a computing device, information regarding a user's real-world environment; detecting, by the computing device and based on the monitoring, when the user's real-world environment includes patterns that are correlated with a study topic; and providing, by the computing device, information regarding the study topic for display in a user device based on the detecting.

Abstract: According to one embodiment, a method, computer system, and computer program product for customizing a mixed reality experience based on the experiential state of users in a queue to join the mixed reality experience or immersed in the mixed reality experience is provided. The present invention may include modeling the experiential state of the at least one user participating in the mixed-reality experience; modeling one or more relationships between the experiential state of the at least one user and one or more physical or virtual experience parameters comprising the mixed-reality experience; based on the one or more modeled relationships, predicting one or more alterations to the one or more physical or virtual experience parameters to enhance the experiential state of the at least one user; and operating a mixed reality system to perform one or more remedial actions to execute the one or more predicted alterations.

Abstract: A processor may monitor frequency data related to a user metric of a user during a measurement window. The user metric may relate to the user's use of a computer implemented environment. The processor may simplify the frequency data related to the user metric, resulting in a set of simplified frequency data. The processor may input the set of simplified frequency data into a neural network. The neural network may determine a likelihood of a negative user experience for the user. The processor may alter a parameter of the first user environment based on the likelihood.

Abstract: One or more computer processors generate a network fractal based on one or more predicted network conditions for a network that includes a change in user density, user device latency, and network throughput, wherein the network fractal is a deployment template comprised of a plurality of nodes. The one or more computer processors select a configuration of network infrastructure devices placed at each node in the plurality of nodes comprised in the generated network fractal. The one or more computer processors modify the network utilizing the generated network fractal and the selected configuration of network infrastructure devices. The one or more computer processors deploy the modified network.

Abstract: In a method for improving speech analysis between devices, a processor receives a speech input comprising audio from a speech recognition platform. A processor segments the speech input into input vectors. A processor maps the input vectors to a profile. A processor calculates affinity coefficients between each input vector and the profile. A processor aggregates the input vectors and affinity coefficients in a user profile. A processor implements the user profile in a speech recognition program.

Abstract: By executing a natural language processing model on a set of natural language text describing a first engagement, a set of characteristics of the first engagement is generated. By executing the natural language processing model on a set of natural language text describing a future engagement, a set of characteristics of the future engagement is generated. The first engagement is determined to be above a threshold similarity with the future engagement. Using the skillset used in performing the first engagement, a required skillset of the future engagement is forecasted. By executing the natural language processing model on a set of natural language text describing a current skillset, a set of characteristics of the current skillset is generated. Using the required skillset of the future engagement and the set of characteristics of the current skillset, a learning path is generated.

Abstract: An embodiment includes determining an experiential state of a first user participating in a mixed-reality experience. The embodiment also includes creating a first driver model that maps a relationship between the experiential state of the first user and a parameter of the mixed-reality experience. The embodiment also includes aggregating the first driver model with a plurality of driver models associated with experiential states and parameters of respective other users. The embodiment also includes creating a first cohort experience model using the aggregated driver models. The embodiment also includes deriving a first cohort experience parameter for the first cohort experience model. The embodiment also includes initiating an automated remedial action for participants in the mixed-reality system being associated with the first cohort experience model and the first cohort experience parameter.

Abstract: One or more computer processors generate a network fractal based on one or more predicted network conditions for a network that includes a change in user density, user device latency, and network throughput, wherein the network fractal is a deployment template comprised of a plurality of nodes. The one or more computer processors select a configuration of network infrastructure devices placed at each node in the plurality of nodes comprised in the generated network fractal. The one or more computer processors modify the network utilizing the generated network fractal and the selected configuration of network infrastructure devices. The one or more computer processors deploy the modified network.

Abstract: By executing a natural language processing model on a set of natural language text describing a first engagement, a set of characteristics of the first engagement is generated. By executing the natural language processing model on a set of natural language text describing a future engagement, a set of characteristics of the future engagement is generated. The first engagement is determined to be above a threshold similarity with the future engagement. Using the skillset used in performing the first engagement, a required skillset of the future engagement is forecasted. By executing the natural language processing model on a set of natural language text describing a current skillset, a set of characteristics of the current skillset is generated. Using the required skillset of the future engagement and the set of characteristics of the current skillset, a learning path is generated.

Abstract: A method, computer system, and a computer program product for product safety is provided. The present invention may include scanning a product inventory. The present invention may include classifying one or more products within the product inventory based on an expiration evaluation. The present invention may include applying a price discount or a display modification notification based on a classification of the one or more products.

Abstract: A method, computer system, and a computer program product for product safety is provided. The present invention may include scanning a product inventory. The present invention may include classifying one or more products within the product inventory based on an expiration evaluation. The present invention may include applying a price discount or a display modification notification based on a classification of the one or more products.