In systems for interpreting the predictions of a machine learning model with the help of a surrogate model, feature vectors of inputs to the machine learning model can be grouped based on locality sensitive hashes or other hashes that reflect similarity between the feature vectors in matching hash values. For a given prediction to be interpreted and the corresponding input feature vector, a suitable training dataset for the surrogate model can then be obtained at low computational cost by hashing the input feature vector and retrieving stored feature vectors with matching hash values, along with their respective predictions.

The present disclosure relates to systems and methods for automatically assisting physical activities. The system may include a body condition monitoring unit, and an autonomous companion unit. The body condition monitoring unit may obtain body condition data of a user. The autonomous companion unit may be automatically move alongside the user and guide the user. The autonomous companion unit may include a transporting subunit, a plurality of sensors, and a controller subunit. The transporting subunit may be enable the movement of the autonomous companion unit. The plurality of sensors may obtain surroundings data associated with the autonomous companion unit. The controller subunit may control the transporting subunit to move the autonomous companion unit according to a target movement plan. The target movement plan may include a target route and a target speed profile, which are based on a preliminary movement plan, the surroundings data, and the body condition data.

Disclosed herein are an apparatus and a method for detecting a vulnerability to a nonvolatile memory attack. The apparatus for detecting a vulnerability to a nonvolatile memory attack includes memory for storing at least one program, and a processor for executing the program, wherein the program includes a fuzzer unit for sending a fuzzing message to fuzzing target software, a nonvolatile memory write control unit for, when a request to write data to a nonvolatile memory is received from the fuzzing target software, transferring nonvolatile memory write data to an attack vulnerability detection unit, and the attack vulnerability detection unit for, when the nonvolatile memory write data is received from the nonvolatile memory write control unit, searching for a vulnerability to a nonvolatile memory attack based on a result of determining whether the nonvolatile memory write data is normal based on a model pre-trained in a normal state.

A system (1) for estimating the brain blood volume and/or brain blood flow and/or depth of anesthesia of a patient, comprises at least one excitation electrode (110E) to be placed on the head (20) of a patient (2) for applying an excitation signal, at least one sensing electrode (110S) to be placed on the head (20) of the patient (2) for sensing a measurement signal caused by the excitation signal, and a processor device (12) for processing said measurement signal (VC) sensed by the at least one sensing electrode (110S) for determining an output indicative of the brain blood volume and/or the brain blood flow. Herein, the processor device (12) is constituted to reduce noise in the measurement signal (VC) by applying a non-linear noise-reduction algorithm. In this way a system for estimating the brain blood volume and/or the brain blood flow of a patient is provided which may lead to an increased accuracy and hence more exact estimates.

A system (1) for estimating the brain blood volume and/or brain blood flow and/or depth of anesthesia of a patient, comprises at least one excitation electrode (110E) to be placed on the head (20) of a patient (2) for applying an excitation signal, at least one sensing electrode (110S) to be placed on the head (20) of the patient (2) for sensing a measurement signal caused by the excitation signal, and a processor device (12) for processing said measurement signal (VC) sensed by the at least one sensing electrode (110S) for determining an output indicative of the brain blood volume and/or the brain blood flow. Herein, the processor device (12) is constituted to reduce noise in the measurement signal (VC) by applying a non-linear noise-reduction algorithm. In this way a system for estimating the brain blood volume and/or the brain blood flow of a patient is provided which may lead to an increased accuracy and hence more exact estimates.

A method and system for intelligently provisioning resources in storage systems. Specifically, the method and system disclosed herein entail throttling the allocation of resources aiding in the performance of background service tasks on a backup storage system. That is, throughout a predicted span of a background service task, resources may be dynamically allocated towards the performance of the background service task at discrete time intervals within the predicted span, thereby improving overall system utilization.

A method and system for intelligently provisioning resources in storage systems. Specifically, the method and system disclosed herein entail throttling the allocation of resources aiding in the performance of background service tasks on a backup storage system. That is, throughout a predicted span of a background service task, resources may be dynamically allocated towards the performance of the background service task at discrete time intervals within the predicted span, thereby improving overall system utilization.

Systems and methods for editing a media composition from media assets are provided. An editing device receives a media asset associated with a scene to be rendered in a media composition. The editing device receives a script including script elements that index script sections associated with the scene and metadata. The editing device edits the media composition with segments of the media asset based on a comparison of the segments, the script elements, and the metadata.

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive mapping operations with respect to a ground-truth database table. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive mapping operations utilizing a hierarchical string matching machine learning framework using at least one or more of an exact match model, a probabilistic match model, a disjoint match model, and an embedding-based match model.

A method and a system for extracting information from a subpoena document are provided. The method includes: receiving a subpoena document; extracting raw text included in the subpoena document; identifying, based on the extracted raw text, entities that are named in the subpoena document; determining, based on the extracted raw text, first information that relates to a scope period, a law enforcement agency, and/or an investigative agent associated with the subpoena document; retrieving second information that relates to the identified entities from a customer database; and outputting a subset of the determined first information and a subset of the obtained second information. The method may also include using a weighted fuzzy name match algorithm to match the identified entities with the second information.