Abstract: A method and/or use of restoring blood flow in neurovasculature by removing thrombus in a plurality of human patients experiencing ischemic stroke using a revascularization device as either a first-line device or a second-line device.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which provides a terrain segmentation and classification tool for synthetic aperture radar (SAR) imagery. The server accurately segments and classifies terrain types in SAR imagery and automatically adapts to new radar sensors data. The server receives a first SAR imagery and trains an autoencoder based on the first SAR imagery to generate learned representations of the first SAR imagery. The server trains a classifier based on labeled data of the first SAR imagery data to recognize terrain types from the learned representations of the first SAR imagery. The server receives a terrain query for a second SAR imagery. The server translates the second imagery data into the first imagery data and classifies the second SAR imagery terrain types using the classifier trained for the first SAR imagery. By reusing the original classifier, the server improves system efficiency.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprise a processor, which provides runtime enforcement of data flow integrity. The processor accesses the application binary file from the disk to execute an application and translates the application binary into intermediate representation. The processor applies the logic of data flow integrity controls to the intermediate representation. Specifically, the processor identifies the vulnerable code in the intermediate representation. The processor applies data flow integrity controls to the vulnerable code. The processor adds simple instrumentation that only changes the application's behavior when unauthorized data tampering occurs while preserving the application's normal behavior. When certain operations may cause unauthorized data tampering, the processor takes proper measures to stop the operations. The processor translates the intermediate representation back to a machine code and replaces the original binary with the machine code.

Abstract: For each respective virtual machine (VM) of a plurality of VMs, a distributed computing system generates a unique Application Binary Interface (ABI) for an operating system for the respective VM, compiles a software application to use the unique ABI, and installs the operating system and the compiled software application on the respective VM. A dispatcher node dispatches, to one or more VMs of the plurality of VMs that provide a service and are in the active mode, request messages for the service. Furthermore, a first host device may determine, in response to software in the first VM invoking a system call in a manner inconsistent with the unique ABI for the operating system of the first VM, that a failover event has occurred. Responsive to the failover event, the distributed computing system fails over from the first VM to a second VM.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which provides a terrain segmentation and classification tool for synthetic aperture radar (SAR) imagery. The server accurately segments and classifies terrain types in SAR imagery and automatically adapts to new radar sensors data. The server receives a first SAR imagery and trains an autoencoder based on the first SAR imagery to generate learned representations of the first SAR imagery. The server trains a classifier based on labeled data of the first SAR imagery data to recognize terrain types from the learned representations of the first SAR imagery. The server receives a terrain query for a second SAR imagery. The server translates the second imagery data into the first imagery data and classifies the second SAR imagery terrain types using the classifier trained for the first SAR imagery. By reusing the original classifier, the server improves system efficiency.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprise a processor, which provides runtime enforcement of data flow integrity. The processor accesses the application binary file from the disk to execute an application and translates the application binary into intermediate representation. The processor applies the logic of data flow integrity controls to the intermediate representation. Specifically, the processor identifies the vulnerable code in the intermediate representation. The processor applies data flow integrity controls to the vulnerable code. The processor adds simple instrumentation that only changes the application's behavior when unauthorized data tampering occurs while preserving the application's normal behavior. When certain operations may cause unauthorized data tampering, the processor takes proper measures to stop the operations. The processor translates the intermediate representation back to a machine code and replaces the original binary with the machine code.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which provides a terrain segmentation and classification tool for synthetic aperture radar (SAR) imagery. The server accurately segments and classifies terrain types in SAR imagery and automatically adapts to new radar sensors data. The server receives a first SAR imagery and trains an autoencoder based on the first SAR imagery to generate learned representations of the first SAR imagery. The server trains a classifier based on labeled data of the first SAR imagery data to recognize terrain types from the learned representations of the first SAR imagery. The server receives a terrain query for a second SAR imagery. The server translates the second imagery data into the first imagery data and classifies the second SAR imagery terrain types using the classifier trained for the first SAR imagery. By reusing the original classifier, the server improves system efficiency.

Abstract: For each respective virtual machine (VM) of a plurality of VMs, a distributed computing system generates a unique Application Binary Interface (ABI) for an operating system for the respective VM, compiles a software application to use the unique ABI, and installs the operating system and the compiled software application on the respective VM. A dispatcher node dispatches, to one or more VMs of the plurality of VMs that provide a service and are in the active mode, request messages for the service. Furthermore, a first host device may determine, in response to software in the first VM invoking a system call in a manner inconsistent with the unique ABI for the operating system of the first VM, that a failover event has occurred. Responsive to the failover event, the distributed computing system fails over from the first VM to a second VM.

Abstract: For each respective virtual machine (VM) of a plurality of VMs, a distributed computing system generates a unique Application Binary Interface (ABI) for an operating system for the respective VM, compiles a software application to use the unique ABI, and installs the operating system and the compiled software application on the respective VM. A dispatcher node dispatches, to one or more VMs of the plurality of VMs that provide a service and are in the active mode, request messages for the service. Furthermore, a first host device may determine, in response to software in the first VM invoking a system call in a manner inconsistent with the unique ABI for the operating system of the first VM, that a failover event has occurred. Responsive to the failover event, the distributed computing system fails over from the first VM to a second VM.

Abstract: An example method includes providing, by a computing system, first randomized configuration information, generating, by the computing system and based on the first randomized configuration information, a first unique instance of a software component, providing second randomized configuration information, wherein the second randomized configuration information is different from the first randomized configuration information, and generating, based on the second randomized configuration information, a second unique instance of the software component that is executable on the runtime computing system.

Abstract: An example method includes providing, by a computing system, first randomized configuration information, generating, by the computing system and based on the first randomized configuration information, a first unique instance of a software component, providing second randomized configuration information, wherein the second randomized configuration information is different from the first randomized configuration information, and generating, based on the second randomized configuration information, a second unique instance of the software component that is executable on the runtime computing system.

Abstract: An example method includes providing, by a computing system, first randomized configuration information, generating, by the computing system and based on the first randomized configuration information, a first unique instance of a software component, providing second randomized configuration information, wherein the second randomized configuration information is different from the first randomized configuration information, and generating, based on the second randomized configuration information, a second unique instance of the software component that is executable on the runtime computing system.

Abstract: An example method includes providing, by a computing system, first randomized configuration information, generating, by the computing system and based on the first randomized configuration information, a first unique instance of a software component, providing second randomized configuration information, wherein the second randomized configuration information is different from the first randomized configuration information, and generating, based on the second randomized configuration information, a second unique instance of the software component that is executable on the runtime computing system.

Abstract: An example method includes providing, by a computing system, first randomized configuration information, generating, by the computing system and based on the first randomized configuration information, a first unique instance of a software component, providing second randomized configuration information, wherein the second randomized configuration information is different from the first randomized configuration information, and generating, based on the second randomized configuration information, a second unique instance of the software component that is executable on the runtime computing system.

Abstract: In general, the techniques of this disclosure describe a method that includes receiving, by a computing device, a user interaction for identifying one or more undesired features of a software program to be removed. The software program is provisioned on the computing device as a software binary. The method further including identifying, by the computing device, one or more execution paths of the software binary that implement the one or more undesired features. Identifying the one or more execution paths includes outputting an indication directing the user to interact with the one or more undesired features, generating undesired feature information of an execution log, and determining the one or more execution paths using the execution log. The method further includes removing, by the computing device, the one or more execution paths to generate a modified software binary.