Abstract: Embodiments for providing data content consumption support by a processor. Data from one or more data sources may be captured and received by one or more data capturing devices while a user is consuming the data on the one or more data sources. A domain knowledge may be automatically updated with the data. A response may be provided to one or more queries based upon information accessed from the knowledge domain.

Abstract: Various embodiments are provided for intelligent selection of time series models by one or more processors in a computing system. Time series data may be received from a user, one or more computing devices, sensors, or a combination thereof. One or more optimal time series models may be selected upon using and/or evaluating one or more recurrent neural networks models that are trained or pre-trained using simulated time series data or historical time series data, or a combination thereof for one or more predictive analytical tasks relating to the received time series data.

Abstract: Various embodiments are provided for securing machine learning models by one or more processors in a computing system. One or more hardened machine learning models that are secured against adversarial attacks are provided by applying one or more of a plurality of combinations of selected preprocessing operations from one or more machine learning models, a data set used for hardening the one or more machine learning models, a list of preprocessors, and a selected number of learners.

Abstract: A neural network has an input layer, one or more hidden layers, and an output layer. The input layer is divided into a situation context input sublayer, a background context input sublayer (in some embodiments), and an environmental input sublayer. The output layer has a selection/sequencing output sublayer and an environmental output sublayer. Each of the layers (including the sublayers) have a plurality of neurons and each of the neurons has an activation. Situation context, environmental information, and background context can be inputted into the neural network which create an output used to dynamically select and sequence selected storylines that are used to modify a story based on the sentiment, environment, and/or background of the audience.

Abstract: Embodiments for providing adversarial protection of speech in audio signals by a processor. Security defenses on one or more audio devices may be provide against automated audio analysis of audio signals by using adversarial noise.

Abstract: Techniques facilitating iterative widening search for designing chemical compounds are provided. A computer-implemented method can comprise receiving, by a system operatively coupled to a processor, an indication of a constrained structure portion of a chemical compound and a first unconstrained structure portion of the chemical compound. The method can also comprise determining, by the system, a second unconstrained structure portion for the chemical compound based on a determination that the second unconstrained structure portion satisfies a defined condition related to a difference between the first unconstrained structure portion and the second unconstrained structure portion.

Abstract: Embodiments for automatic visualization and explanation of feature learning output for predictive modeling in a computing environment by a processor. A degree of importance score may be assigned to one or more features from a relational database according to the machine learning model. A visualization graph of one or more join paths and the one or more features with the degree of importance score to predict a target variable may be generated.

Abstract: Embodiments for automatic feature learning for predictive modeling in a computing environment by a processor. A first table and a second table are joined based on an edge between the first table and the second table defined by an entity graph thereby creating a resulting joined table that is connected by a column of data. The resulting joined table is used as an input into one or more neural network operations that transform the resulting joined table to one or more features to predict a target variable.

Abstract: Embodiments for analyzing images by one or more processors are described. An image is received. An object appearing in the image is detected. A scene graph is generated for the object. At least one transformational matrix is determined for the object. The at least one transformational matrix is associated with rendering the object as the object appears in the image based on the scene graph.

Abstract: Techniques and systems for facilitating artificial intelligence for interactive preparation of electronic documents are provided. In one example, a system includes a mapping component and a document editing component. The mapping component maps data provided by a recording device into an editing action for an electronic document. The document editing component applies the editing action associated with the recording device to the electronic document to generate a modified version of the electronic document.

Abstract: Embodiments for intelligent problem solving using visual input by a processor. An interactive dialog may be initiated using the one or more IoT computing devices for receiving one or more instructions, objectives, and the contextual information to define a selected task. Visual data and contextual information associated with the visual data may be collected from one or more Internet of Things (“IoT”) computing devices. One or more solutions may be for a selected task using the visual data and contextual data.

Abstract: Embodiments for analyzing images by one or more processors are described. An image is received. An object appearing in the image is detected. A scene graph is generated for the object. At least one transformational matrix is determined for the object. The at least one transformational matrix is associated with rendering the object as the object appears in the image based on the scene graph.

Abstract: Embodiments for automatic feature learning for predictive modelling in a computing environment by a processor. A first table and a second table are joined based on an edge between the first table and the second table defined by an entity graph thereby creating a resulting joined table that is connected by a column of data. The resulting joined table is used as an input into one or more neural network operations that transform the resulting joined table to one or more features to predict a target variable.

Abstract: Embodiments for detection of energy consumption anomalies in one or more energy consumption systems in a cloud computing environment by a processor. Energy consumption anomalies associated with a selected facility, a selected object, or a combination thereof may be detected and diagnosed according to feedback and simulation data generated from a scenario-based simulation operation.

Abstract: A method is provided for determining at least one candidate reactant. One embodiment of this method includes the following steps: forming by a computer processor a graph of known reactants and known products, the graph comprising links between the known reactants and their known products, receiving by a computer processor the target compound, determining by a computer processor whether the graph includes the target compound and adding the target compound to the graph if the target compound was not previously included, forming by a computer processor a matrix representing at least a portion of the known reactants, a portion of the known products and the target compound, providing a matrix value of the graph by a computer processor for one or more candidate reactants and determining by a computer processor at least one link in the graph between the target compound and the candidate reactant based on matrix values.

Abstract: Techniques for efficient retrosynthesis analysis are provided. A computer-implemented method for determining whether a target compound can be synthesized using known pathways for similar compounds includes receiving, by a processor, target compound data including a target compound. The method further includes obtaining, by the processor, a similar compound to the target compound, along with a reaction rule for synthesizing the similar compound. The method further includes applying, by the processor, the reaction rule to the target compound to generate a set of precursors. The method further includes generating, by the processor, a notification based on the set of precursors.

Abstract: A method and system for generating a map identifying the size and location of anomalous crop health patterns of a geographic area. Predictive crop health forecasting based historical crop health images generates expected crop health images. Statistical parametric mapping is used to model differences in the expected crop health images and current crop health images to generate a statistical parametric map. Regions of anomalous crop health based on the modeled differences are identified in the statistical parametric map. The number of the identified anomalous crop health regions and the size of each of the identified anomalous crop health regions are determined. The statistical significance of the size and number of the anomalous crop health regions relative to the expected crop health is quantified. A map of anomalous crop health patterns delineates the anomalous crop health regions and the statistical significance of the size and number of anomalous crop health regions.

Abstract: Embodiments for intelligent dynamic parking for autonomous vehicles by a processor. A dynamic parking plan may be determined for an autonomous vehicle to travel from a selected location and returning to the selected location within a selected time window according to a transportation network and one or more a variable parking functions in lieu of waiting at the selected location.

Abstract: Embodiments for an intelligent directing service in an Internet of Things (IoT) computing environment by a processor. One or more objects may be identified within a defined region relative to an entity. At least a portion of an extremity of the entity may be directed to select or avoid the one or more objects according to one or more internet of things (IoT) devices.

Abstract: A method and system for generating a map identifying the size and location of anomalous crop health patterns of a geographic area. Predictive crop health forecasting based historical crop health images generates expected crop health images. Statistical parametric mapping is used to model differences in the expected crop health images and current crop health images to generate a statistical parametric map. Regions of anomalous crop health based on the modeled differences are identified in the statistical parametric map. The number of the identified anomalous crop health regions and the size of each of the identified anomalous crop health regions are determined. The statistical significance of the size and number of the anomalous crop health regions relative to the expected crop health is quantified. A map of anomalous crop health patterns delineates the anomalous crop health regions and the statistical significance of the size and number of anomalous crop health regions.