Abstract: An adaptive support garment integrating directional fabrics to assist in providing adaptive support to select portions of the garment is discussed herein. The adaptive support garment can include a first directional fabric, a second directional fabric, and a tension device. The first directional fabric includes first directional fibers, and the first directional fabric can be coupled to a fixed portion of the adaptive support garment. The second directional fabric includes second directional fibers, and the second directional fabric can be coupled to a movable control structure portion of the adaptive support garment. The tension device can be coupled to the movable control structure and configured to apply a tension in a first direction on the movable control structure. In operation, the first directional fibers can engage with the second directional fibers to resist movement in a second direction opposite the first direction.

Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: A visual effects system includes a first display, wherein the first display includes a polarized filter on or in the first display, and a second display, wherein the second display is not polarized. The visual effects system also includes a beam splitter positioned to enable a guest to view the first display through the beam splitter and a reflection of the second display via the beam splitter.

Abstract: The disclosed technology includes an air moving system for a stringing apparatus. The air moving system can comprise an energy bank, an electric air moving device in electrical communication with the energy bank and configured to output a supply of air to cause a cable to move along a duct and at least one controller. The at least one controller can be configured to determine a speed of the cable moving along the duct and control the output of the supply of air of the electric air moving device to control the speed of the cable based at least in part on the determined speed of the cable.

Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.

Abstract: Systems and methods for detecting anomalies in antenna systems (e.g., air traffic control surveillance systems), include a processor receiving antenna status information. A variational autoencoder receives and optimizes the antenna status information and determines whether it qualifies as an anomaly. Optimized antenna status information is compared to either non-anomalous or anomalous antenna status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the antenna status information by generating a plurality of probabilistic models of the antenna status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the antenna status information prior to optimization.

Abstract: Systems and methods for detecting anomalies in aviation data communication systems (e.g., air traffic control surveillance systems), include a processor receiving device status information. A variational autoencoder receives and optimizes the device status information and determines whether it qualifies as an anomaly. Optimized device status information is compared to either non-anomalous or anomalous device status data in a latent space of the variational autoencoder. The latent space preferably includes an n-D point scatter plot and hidden vector values. The processor optimizes the device status information by generating a plurality of probabilistic models of the device status information and determining which of the plurality of models is optimal. A game theoretic optimization is applied to the plurality of models, and the best model is used to generate the n-D point scatter plot in latent space. An image gradient sobel edge detector preprocesses the device status information prior to optimization.

Abstract: A code segment executing on a compute instance may be identified as suspicious based on runtime behavior or similar behavioral analysis or the like. In order to ensure the identification and use of the most up-to-date identification and remediation tools, the compute instance may defer various remediation steps for an interval, during which the compute instance may wait for data updates from a threat management system. After the interval has passed, the compute instance may use any updated data or tools in order to address the code segment that triggered the initial malware detection.

Abstract: The present disclosure includes a combination composition comprising UBP and fermentation collected from Burkholderia sp. where the combination provides significantly improved insecticidal and/or plant growth promoting properties when applied to plants and/or seeds.

Abstract: A system includes a persistent storage and a data transfer manager. The persistent storage stores sending entity storage resources and receiving entity storage resources. The data transfer manager obtains a data transfer request for data in the sending entity storage resources. In response to obtaining the data transfer request, the data transfer manager obtains a sending entity schema associated with the data; determines a current storage location of the data using the obtained sending entity schema; determines a future storage location for a copy of the data in the receiving entity storage resources; stores a copy of the data at the determined future storage location; adapts the sending entity schema based on the determined future storage location; and modifies a receiving entity schema based on the adapted sending entity schema.

Abstract: A code segment executing on a compute instance may be identified as suspicious based on runtime behavior or similar behavioral analysis or the like. In order to ensure the identification and use of the most up-to-date identification and remediation tools, the compute instance may defer various remediation steps for an interval, during which the compute instance may wait for data updates from a threat management system. After the interval has passed, the compute instance may use any updated data or tools in order to address the code segment that triggered the initial malware detection.

Abstract: An apparatus in one embodiment comprises an ingestion manager, a plurality of ingestion engines associated with the ingestion manager, and an analytics platform configured to receive data from the ingestion engines under the control of the ingestion manager. The ingestion manager is configured to interact with one or more of the ingestion engines in conjunction with providing data to a given one of a plurality of analytics workspaces of the analytics platform. For example, the analytics workspaces of the analytics platform are illustratively configured to receive data from respective potentially disjoint subsets of the ingestion engines under the control of the ingestion manager. Additionally or alternatively, the ingestion manager may be configured to implement data-as-a-service functionality for one or more of the analytics workspaces of the analytics platform.

Abstract: A code segment executing on a compute instance may be identified as suspicious based on runtime behavior or similar behavioral analysis or the like. In order to ensure the identification and use of the most up-to-date identification and remediation tools, the compute instance may defer various remediation steps for an interval, during which the compute instance may wait for data updates from a threat management system. After the interval has passed, the compute instance may use any updated data or tools in order to address the code segment that triggered the initial malware detection.

Abstract: A computing device includes a persistent storage and a processor. The persistent storage includes an asset. The processor obtains a computation request for the asset, instantiates an executable entity based on a computation prototype and a manifest associated with the asset, performs the computation request using the instantiated executable entity and metadata specified by the manifest associated with the asset to obtain a computation result; and provides the obtained computation result.

Abstract: A code segment executing on a compute instance may be identified as suspicious based on runtime behavior or similar behavioral analysis or the like. In order to ensure the identification and use of the most up-to-date identification and remediation tools, the compute instance may defer various remediation steps for an interval, during which the compute instance may wait for data updates from a threat management system. After the interval has passed, the compute instance may use any updated data or tools in order to address the code segment that triggered the initial malware detection.

Abstract: A registration framework is disclosed that allows assets to be registered with an analytics platform. When an asset is ingested into the analytics platform, the registration framework operates to register the asset in an asset roster. The asset roster identifies the asset and stores information about the asset. The registration framework can then be used by users to discover assets. Assets may also be deployed by the registration framework to workspaces.

Abstract: A tool for automatic pre-detection of potential software product impact according to a statement placed in a software development system, and for automatically recommending for resolutions which accesses a repository of information containing a history of changes and effects of the changes for a software project; using a received a statement in natural language to perform a natural language search of the repository; according to the findings of the search of the repository, using a machine learning model to compose an impact prediction regarding the received statement relative to the findings; and automatically placing an advisory notice regarding to the impact prediction into the software development system, wherein the advisory notice is associated with the received statement.

Abstract: A tool for automatic pre-detection of potential software product impact according to a statement placed in a software development system, and for automatically recommending for resolutions which accesses a repository of information containing a history of changes and effects of the changes for a software project; using a received a statement in natural language to perform a natural language search of the repository; according to the findings of the search of the repository, using a machine learning model to compose an impact prediction regarding the received statement relative to the findings; and automatically placing an advisory notice regarding to the impact prediction into the software development system, wherein the advisory notice is associated with the received statement.

Abstract: A system includes a persistent storage and a data transfer manager. The persistent storage stores sending entity storage resources and receiving entity storage resources. The data transfer manager obtains a data transfer request for data in the sending entity storage resources. In response to obtaining the data transfer request, the data transfer manager obtains a sending entity schema associated with the data; determines a current storage location of the data using the obtained sending entity schema; determines a future storage location for a copy of the data in the receiving entity storage resources; stores a copy of the data at the determined future storage location; adapts the sending entity schema based on the determined future storage location; and modifies a receiving entity schema based on the adapted sending entity schema.