Abstract: The present disclosure describes a technology platform for creating and updating records of resources in a ledger. To create a record, a tenant organization may prepare a record to write to the ledger that may be flagged as temporary. Metadata may be added to the record, which flags the record as temporary. The metadata may comprise a unique code and an identification of a user that can approve the temporary record. The unique code and the identification may be sent, by the technology platform, to a device associated with one or more approving devices. Upon receiving the code and the identification of the transaction, the device may sign the unique code and invoke a routine based on the identification. The routine may fetch the temporary record. The device may compare the unique code to a code stored in the metadata of the temporary record. Upon valid verification of the unique code, the device may indicate authorization of the write.

Abstract: The present disclosure describes a technology platform for creating and updating records of resources in a ledger. To create a record, a tenant organization may prepare a record to write to the ledger that may be flagged as temporary. Metadata may be added to the record, which flags the record as temporary. The metadata may comprise a unique code and an identification of a user that can approve the temporary record. The unique code and the identification may be sent, by the technology platform, to a device associated with one or more approving devices. Upon receiving the code and the identification of the transaction, the device may sign the unique code and invoke a routine based on the identification. The routine may fetch the temporary record. The device may compare the unique code to a code stored in the metadata of the temporary record. Upon valid verification of the unique code, the device may indicate authorization of the write.

Abstract: The present disclosure is directed to a method of detecting anomalous behaviors based on a temporal profile. The method can include collecting, by a control system comprising a processor and memory, a set of network data communicated by a plurality of network nodes over a network during a time duration. The method can include identifying, by the control system, one or more seasonalities from the set of network data. The method can include generating, by the control system, a temporal profile based on the one or more identified seasonalities. The method can include detecting, by the control system and based on the temporal profile, an anomalous behavior performed by one of the plurality of network nodes. The method can include identifying, by the control system and based on the temporal profile, a root cause for the anomalous behavior.

Abstract: The present disclosure describes techniques for generating a digital twin to represent the chemical properties, elemental properties, elemental components, parametric components, and/or molecular components for a resource. A sample of a resource may be obtained and analyzed to identify one or more molecular descriptors contained in the resource. Further analysis of the one or more molecular descriptors and/or the resource may identify gaps in the data and/or information about the resource. Using machine-learning models and a chemistry knowledgebase, the gaps in the data and/or information about the resource may be filled. Further, the machine-learning models described herein may be used to generate a digital twin of the resource that represents the resource in a digital form such that the resource may be tracked accurately throughout its lifecycle, including how the resource may change due to environmental conditions, storage conditions, and/or custodial changes.

Abstract: The present disclosure is directed to a method of detecting anomalous behaviors based on a temporal profile. The method can include collecting, by a control system comprising a processor and memory, a set of network data communicated by a plurality of network nodes over a network during a time duration. The method can include identifying, by the control system, one or more seasonalities from the set of network data. The method can include generating, by the control system, a temporal profile based on the one or more identified seasonalities. The method can include detecting, by the control system and based on the temporal profile, an anomalous behavior performed by one of the plurality of network nodes. The method can include identifying, by the control system and based on the temporal profile, a root cause for the anomalous behavior.

Abstract: The present disclosure describes a technology platform for creating and updating records of resources in a ledger. To create a record, a tenant organization may prepare a record to write to the ledger that may be flagged as temporary. Metadata may be added to the record, which flags the record as temporary. The metadata may comprise a unique code and an identification of a user that can approve the temporary record. The unique code and the identification may be sent, by the technology platform, to a device associated with one or more approving devices. Upon receiving the code and the identification of the transaction, the device may sign the unique code and invoke a routine based on the identification. The routine may fetch the temporary record. The device may compare the unique code to a code stored in the metadata of the temporary record. Upon valid verification of the unique code, the device may indicate authorization of the write.

Abstract: The present disclosure is directed to a method of identifying an infected network node. The method includes identifying a first network node as infected. The method includes collecting a first set of network data from the first network node including anomalous activities performed by the first network node. The method includes generating an anomalous behavior model using the first set of network data. The method includes collecting a second set of network data from a second network node including anomalous activities performed by the second network node. The method includes comparing the second set of data to the generated anomalous behavior model. The method includes determining, from the comparison, that a similarity between first characteristics and second characteristics exceeds a predefined threshold. The method includes ascertaining, based on the determination, the second network node as an infected network node.

Abstract: The present disclosure is directed to a method of detecting anomalous behaviors based on a temporal profile. The method can include collecting, by a control system comprising a processor and memory, a set of network data communicated by a plurality of network nodes over a network during a time duration. The method can include identifying, by the control system, one or more seasonalities from the set of network data. The method can include generating, by the control system, a temporal profile based on the one or more identified seasonalities. The method can include detecting, by the control system and based on the temporal profile, an anomalous behavior performed by one of the plurality of network nodes. The method can include identifying, by the control system and based on the temporal profile, a root cause for the anomalous behavior.

Abstract: Systems and methods directed to improve the responsiveness of an application's UI and improve a user's experience are disclosed. In particular, the systems and methods implement layout and rendering of UI components in a mobile application as two independent steps: layout and mount. During the layout step, attributes related to a layout are identified. For example, during the layout step, a list of UI components in each container, and their respective sizes and positions are identified. The layout result is then used in the mount step to create an actual view hierarchy to be rendered on screen once the component becomes visible. As result of this decoupling of layout operations from the rendering operations, the CPU-intensive measure and layout operations can be moved to the background thread, saving milliseconds.

Abstract: The present disclosure is directed to a method of identifying an infected network node. The method includes identifying a first network node as infected. The method includes collecting a first set of network data from the first network node including anomalous activities performed by the first network node. The method includes generating an anomalous behavior model using the first set of network data. The method includes collecting a second set of network data from a second network node including anomalous activities performed by the second network node. The method includes comparing the second set of data to the generated anomalous behavior model. The method includes determining, from the comparison, that a similarity between first characteristics and second characteristics exceeds a predefined threshold. The method includes ascertaining, based on the determination, the second network node as an infected network node.

Abstract: Systems and methods directed to improve the responsiveness of an application's UI and improve a user's experience are disclosed. In particular, the systems and methods implement layout and rendering of UI components in a mobile application as two independent steps: layout and mount. During the layout step, attributes related to a layout are identified. For example, during the layout step, a list of UI components in each container, and their respective sizes and positions are identified. The layout result is then used in the mount step to create an actual view hierarchy to be rendered on screen once the component becomes visible. As result of this decoupling of layout operations from the rendering operations, the CPU-intensive measure and layout operations can be moved to the background thread, saving milliseconds.