Abstract: Various computing technologies for various reverse engineering platforms capable of outputting, including creating or generating, a human readable and high level source code, such as C, Fortran, LISP, or BASIC, from various binary files, such as application binaries, executable binaries, or data binaries, in an original language as developed pre-compilation. For example, some of such reverse engineering platforms can be programmed to disassemble binary files from different process architectures, identify various code optimizations as compiler introduced, reverse or unwind various compiler optimizations (de-optimize), and generate a human readable and high-level source code from de-optimized data.

Abstract: Various computing technologies for various reverse engineering platforms capable of outputting, including creating or generating, a human readable and high level source code, such as C, Fortran, LISP, or BASIC, from various binary files, such as application binaries, executable binaries, or data binaries, in an original language as developed pre-compilation. For example, some of such reverse engineering platforms can be programmed to disassemble binary files from different process architectures, identify various code optimizations as compiler introduced, reverse or unwind various compiler optimizations (de-optimize), and generate a human readable and high-level source code from de-optimized data.

Abstract: Described herein are various computing technologies for various reverse engineering platforms capable of outputting a human readable and high level source code from various binary files in its original language, as developed before compilation. For example, a computer-implemented method includes generating, by a computer, an intermediate representation having machine-readable data representing assembly language for a binary file; detecting, by the computer, a set of one or more structural features by executing a convolutional neural network on the intermediate representation, the set of one or more structural features having one or more optimizations; identifying, by the computer, a set of one or more code transformations corresponding to the one or more optimizations detected in the set of one or more structural features; and generating, by the computer, one or more source code files representing the binary file according to the set of one or more code transformations.

Abstract: The present disclosure relates to a method and system for configuring a surgical tool during surgery. A laser scanner generates sensor data and a processor determines spatial data indicative of a position of the anatomical feature and of a position of a tool interface that is fixed in relation to the anatomical feature based on the sensor data. The processor also determines a first desired spatial configuration of the surgical tool in relation to the tool interface based on the spatial data and a second desired spatial configuration of the surgical tool in relation to the anatomical feature. The outcome is more accurate and less complex than other methods, such as methods that are based on reference to the absolute positions of the anatomical feature and the surgical tool within an operation theatre.

Abstract: Described herein are various computing technologies for various reverse engineering platforms capable of outputting (e.g., creating, generating) a human readable and high level source code (e.g., C formatted text, Fortran formatted text, LISP formatted text, BASIC formatted text) from various binary files (e.g., application binary file, executable binary file, data binary file) in its original language, as developed before compilation. For example, some of such reverse engineering platforms can be programmed to disassemble binary files from different process architectures, identify various code optimizations as compiler introduced, reverse or unwind various compiler optimizations (de-optimize), and generate a human readable and high-level source code from de-optimized data. These techniques can be technically beneficial for design recovery purposes (e.g., security auditing, digital rights management, driver engineering).

Abstract: The present disclosure relates to a method and system for configuring a surgical tool during surgery. A laser scanner generates sensor data and a processor determines spatial data indicative of a position of the anatomical feature and of a position of a tool interface that is fixed in relation to the anatomical feature based on the sensor data. The processor also determines a first desired spatial configuration of the surgical tool in relation to the tool interface based on the spatial data and a second desired spatial configuration of the surgical tool in relation to the anatomical feature. The outcome is more accurate and less complex than other methods, such as methods that are based on reference to the absolute positions of the anatomical feature and the surgical tool within an operation theatre.

Abstract: Mass spectrometry is used to identify a protein of interest. The protein is first ionized then fragmented into protein product ion. Masses of the observed product ions are compared to product ion masses calculated in silico for database protein sequences to identify product ion matches within a predetermined mass tolerance. An algorithm that weights the product ion to matches based upon one or more factors such as product ion abundance, favored cleavage sites, product ion type, precursor ion charge state and polarity is used to score the possible matches to database proteins in order to identify the protein of interest. The invention represents a “top down” approach and is particularly well-suited for identification of a protein in a complex mixture.