Abstract: An analysis of software stored and executing on one or more assets in an enterprise includes determining a hierarchy of nodes in the software and among the assets and analyzing dependencies among those nodes and assets through a static analysis of the software as it is stored as well as through a dynamic analysis of the software as it executes.

Abstract: A security analysis of software includes analyzing security risks at each level of the hierarchy of the software and aggregating identified risks within the hierarchy levels. Weights applied during aggregation assist in homogenizing risk scores originating from different types of identified security risks and provide for the ability to communicate a meaningful risk score at each level of the hierarchy.

Abstract: A governance engine is provided that receives changes identified in dependencies in an enterprise and compares those changes to rule triggers, executing an output of a rule if a trigger is implicated. Related agents may examine the identified changes for new, potentially vulnerable or otherwise disallowed dependencies.

Abstract: A security analysis of software includes analyzing security risks at each level of the hierarchy of the software and aggregating identified risks within the hierarchy levels. Weights applied during aggregation assist in homogenizing risk scores originating from different types of identified security risks and provide for the ability to communicate a meaningful risk score at each level of the hierarchy.

Abstract: An analysis of software stored and executing on one or more assets in an enterprise includes determining a hierarchy of nodes in the software and among the assets and analyzing dependencies among those nodes and assets through a static analysis of the software as it is stored as well as through a dynamic analysis of the software as it executes.

Abstract: A method includes fusing multi-modal sensor data from a plurality of sensors having different modalities. At least one region of interest is detected in the multi-modal sensor data. One or more patches of interest are detected in the multi-modal sensor data based on detecting the at least one region of interest. A model that uses a deep convolutional neural network is applied to the one or more patches of interest. Post-processing of a result of applying the model is performed to produce a post-processing result for the one or more patches of interest. A perception indication of the post-processing result is output.

Abstract: An analysis of software stored and executing on one or more assets in an enterprise includes determining a hierarchy of nodes in the software and among the assets and analyzing dependencies among those nodes and assets through a static analysis of the software as it is stored as well as through a dynamic analysis of the software as it executes.

Abstract: A method includes converting time-series data from a plurality of prognostic and health monitoring (PHM) sensors into frequency domain data. One or more portions of the frequency domain data are labeled as indicative of one or more target modes to form labeled target data. A model including a deep neural network is applied to the labeled target data. A result of applying the model is classified as one or more discretized PHM training indicators associated with the one or more target modes. The one or more discretized PHM training indicators are output.

Abstract: A security analysis of software includes analyzing security risks at each level of the hierarchy of the software and aggregating identified risks within the hierarchy levels. Weights applied during aggregation assist in homogenizing risk scores originating from different types of identified security risks and provide for the ability to communicate a meaningful risk score at each level of the hierarchy.

Abstract: A governance engine is provided that receives changes identified in dependencies in an enterprise and compares those changes to rule triggers, executing an output of a rule if a trigger is implicated. Related agents may examine the identified changes for new, potentially vulnerable or otherwise disallowed dependencies.

Abstract: An analysis of software stored and executing on one or more assets in an enterprise includes determining a hierarchy of nodes in the software and among the assets and analyzing dependencies among those nodes and assets through a static analysis of the software as it is stored as well as through a dynamic analysis of the software as it executes.

Abstract: A method includes converting time-series data from a plurality of prognostic and health monitoring (PHM) sensors into frequency domain data. One or more portions of the frequency domain data are labeled as indicative of one or more target modes to form labeled target data. A model including a deep neural network is applied to the labeled target data. A result of applying the model is classified as one or more discretized PHM training indicators associated with the one or more target modes. The one or more discretized PHM training indicators are output.

Abstract: A method includes fusing multi-modal sensor data from a plurality of sensors having different modalities. At least one region of interest is detected in the multi-modal sensor data. One or more patches of interest are detected in the multi-modal sensor data based on detecting the at least one region of interest. A model that uses a deep convolutional neural network is applied to the one or more patches of interest. Post-processing of a result of applying the model is performed to produce a post-processing result for the one or more patches of interest. A perception indication of the post-processing result is output.

Abstract: In one aspect, a method of generating a model for HVAC system control is provided. The method includes generating a model of the performance of an HVAC system, providing the generated model to at least one of an optimal control system and a diagnostic system, and automatically tuning the HVAC system using the generated model and at least one of the optimal control system and the diagnostic system.