Abstract: A cyber-security analysis method uses machine learning (ML) technology to classify cyber-threat indicators, for example, as malicious or benign, by generating a threat score. The method includes receiving, at a compute device, a cyber-threat indicator (IUE) and associated verdicts from a set of sources. Augmenting the verdicts associated with the IUE with verdicts associated with at least one related indicator having a defined relationship with the IUE. The relationship between the IUE and the at least one related indicator can be operational, e g., based on an administrative domain, or functional, e.g., based on a protocol specification. The cyber-threat score is generated for the IUE based on the ML model and the combined verdicts of the IUE and the at least one related indicator.

Abstract: A ground cable may comprise a plurality of strands. Inner core strands of the cable may be surrounded by an adjacent outermost layer or wrap of outer wrap strands. The outer wrap of strands may comprise at least one indicator strand, which may comprise an indicator finish on a portion of its surface. A characteristic of the indicator finish may change when exposed to a current level that exceeds an electrical fault threshold.

Abstract: Example embodiments of the present disclosure provide for an example method including maintaining a current version info list including version info tuples for software layers. The example method includes, upon receipt of a request for a registered version key, performing a comparison algorithm to authenticate a requested version info list including a number of version info tuples associated with software layers. The tuples can include a security version number (SVN) and a security context string for each software layer. The requested version info list can be authenticated using the comparison algorithm to determine that the requested version info list includes version info tuples with higher SVNs than the current version info list. Responsive to authenticating the requested version info list, the method include providing a portion of the requested version info list as input into a key derivation function (KDF) and obtaining a device requested version key as output.

Abstract: A computer-implemented method, computer program product and computing system for maintaining a non-public content repository; and analyzing user-generated content to identify related content included within the non-public content repository.

Abstract: A blood pressure monitoring device includes a wrist strap, a case, and a display. The strap portion is adapted to fasten the device to the wrist without occluding blood flow. At least one sensor modality is arranged within the case for obtaining sensor data from an artery in the wrist. In a preferred embodiment photoplethysmography sensors are incorporated in the case to generate PPG waveform data. A processor within the case is operable to compute mean arterial pressure, and optionally diastolic and systolic blood pressure based on extracted and computed features of the sensor data. Related methods and systems are also described.

Abstract: A remote monitoring system for monitoring inventory, process, and product life-cycle data is disclosed. Data may be collected from the remote monitoring system. The data can include information on raw material components, source information, production or storage location and movement, production or storage temperature, production or storage barometric pressure, packaging, distribution, sales, or combinations thereof.

Abstract: A communication interface includes a first and second interface module to provide for point-to-point transmission of signalling to a second or third node respectively and receipt of signalling from the second node or third node respectively via one or more first terminals. The first and second interface modules include one or more second terminals to communicatively couple a first processor and the first or second interface module. At least one interface-to-interface connection couples the first interface module and the second interface module. A routing module reads a data frame and, based on whether or not an identifier present in a routing field of the data frame matches one or more predetermined identifiers, provides for forwarding of the data frame to the first processor or to the interface-to-interface connection for retransmission by the other of the first interface module and the second interface module.

Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to detect anomalous post-authentication behavior/state change(s) with respect to a workload identity. For example, audit logs that specify actions performed with respect to the workload identity of a platform-based identity service, a causing state change(s), while another identity is authenticated with the platform-based identity service, are analyzed. The audit log(s) are analyzed via a model for anomaly prediction based on actions. The model generates an anomaly score indicating a probability whether a particular sequence of the actions is indicative of anomalous behavior/state change(s). A determination is made that an anomalous behavior has occurred based on the anomaly score, and when anomalous behavior has occurred, a mitigation action may be performed that mitigates the anomalous behavior.

Abstract: A method for synchronization of translation audio data includes receiving a live audio signal corresponding to a live event having spoken words in an original language. The method also includes translating the live audio signal to a first translated language and a second translated language and producing a first translated audio signal based on the first translated language and a second translated audio signal based on the second translated language. A first segment of the first translated audio signal having a first duration and a first segment of the second translated audio signal having a second duration that is longer than the first duration. The method also includes processing the first segment of the first translated audio signal into a processed first segment having a duration equal to the second duration and transmitting the processed first segment to a first mobile computing device at the live event.

Abstract: A blower includes a housing including an inlet and an outlet, a bearing-housing structure provided to the housing and adapted to rotatably support a rotor, a motor provided to the bearing-housing structure and adapted to drive the rotor, and an impeller provided to the rotor. The bearing-housing structure includes a bearing shaft having a bearing surface that rotatably supports the rotor. The bearing shaft provides only a single bearing of the non-ball bearing type for the rotor.

Abstract: Aspects of the disclosure provide various methods relating to enclaves. For instance, a method of authentication for an enclave entity with a second entity may include receiving, by one or more processors of a host computing device of the enclave entity, a request and an assertion of identity for the second entity, the assertion including identity information for the second identity; using an assertion verifier of the enclave entity to determine whether the assertion is valid; when the assertion is valid, extracting the identity information; authenticating the second entity using an access control list for the enclave entity to determine whether the identity information meets expectations of the access control list; when the identity information meets the expectations of the access control list, completing the request.

Abstract: Apparatus and methods are disclosed for implementing a copilot as a network of microservices including specialized large language models (LLMs) or other trained machine learning (ML) tools. The microservice network architecture supports flexible, customizable, or dynamically determinable dataflow. Compared to much larger competing LLMs, comparable or superior performance is achieved for certain tasks, while significantly reducing hardware requirements and computation time. Disclosed examples incorporate microservices for expansion, retrieval, embedding, and evaluation, in addition to one or more core microservices. Optionally, intermodal I/O, multiple data repositories, competency qualification, or human feedback can be supported. Multiple core microservices can support varying client authorizations or cognitive functions. The disclosed architecture supports any major LLM use case and can be deployed on a single compute node with a single GPU.

Abstract: A portable dual chamber auto-injector configured to store a dry opioid antagonist medicament separately from a liquid component, wherein a user actuated mixing system comprising a movable component to create a fluidic pathway between the first and second chambers and release a portion of energy from a pre-stored energy to drive a displacement mechanism into the first chamber and displace the liquid component into the second chamber and solubilize the opioid antagonist. A needle assembly in fluid communication with the second chamber can be used to transfer the solubilized opioid antagonist.

Abstract: A flow generator includes a housing, a blower structured to generate a flow of pressurized breathable air, and a suspension device to support the blower within the housing and provide a pressure seal between low and high pressure sides of the blower. The suspension device includes a bellows-like portion provided along the perimeter of the blower to absorb shock applied at least radially to the blower and one or more cones provided along upper and/or lower sides of the blower to absorb shock applied at least axially to the blower.

Abstract: Embodiments of the present disclosure related to systems and methods of determining, computing, or simulating crop yield for a growing season. In certain embodiments, the model begins with a yield potential reflective of environmental limitations for a particular field which assumes that the grower has chosen a crop variety that is appropriate for their growing season and has managed their farm optimally. An end-of-season yield is predicted by accounting for environmental stressors, which are applied to the starting yield potential as penalties, in certain embodiments, the crop yield model simulates post-, in-, and end-of-season yield potentials by classifying major categories of plant stressors. These stressors are used to track and penalize yield potential using a dynamic set of inputs. The crop yield model works in conjunction with a crop phenology model to facilitate identification of historical averages for various phenological states of the crop development.

Abstract: Embodiments of the present disclosure related to systems and methods of a field-scale crop phenology model for simulating/computing plant development stages of a crop. The field-scale crop phenology model is used to simulate plant development stages during a growing season. Knowledge of plant stages, especially as a forecast, helps the timing of chemical applications as well as other crop-dependent management decisions. Together with a user's field location, planting date, and varietal information, the crop phenology model serves as a robust field-scale decision-making tool. In certain embodiments, the phenology model can be run under three different scenarios: historical, preseason, or in-season. Using a blend of different weather data inputs, the phenology model can generate phenology results based on the desired scenario of a user.

Abstract: A method for wireless capture of real-time audio and video at a live event using a mobile computing device includes receiving a data representation of a live audio signal corresponding to the live event via a wireless network. The method also includes processing the data representation of the live audio signal into a live audio stream. The method also includes initiating a video capture corresponding to the live event. The method also includes producing, concurrent with the video capture, a shareable video corresponding to the live event based on the captured video and the live audio stream.

Abstract: A cyber-security analysis method uses machine learning (ML) technology to classify cyber-threat indicators, for example, as malicious or benign, by generating a threat score. The method includes receiving, at a compute device, a data set including cyber-threat indicators and verdicts serving as votes from each source in the set of sources. Each of the votes is associated with one of the cyber-threat indicators. An ML model is trained based on at least one of agreements among the sets of votes, and disagreements among the sets of votes to produce a trained ML model. In response to receiving a new cyber-threat indicator, votes are identified for each source from a subset of the sources, to define a second set of votes. The cyber-threat score is generated for the new cyber-threat indicator based on the trained ML model and the second set of votes.

Abstract: A method for filling a pod is provided. A pod is provided and has a housing defining a plurality of serving chambers arranged in an annular array and surrounding a drive hub. Data is received that is indicative of a customized nutritional supplement for the pod to a controller of an automated filling station. The customized nutritional supplement is filled into at least one of the plurality of serving chambers of the pod via the automated filling station by controlling a plurality of hoppers of the filling station to dispense the customized supplement into the plurality of serving chambers of the pod. Each hopper contains a corresponding ingredient available for the customized supplement.

Abstract: A mixing device configured to hold two containers, each having a separate medicament component disposed therein. A fluidic channel is provided that upon creating fluidic communication with each container once seals about each container are opened. Then a transfer mechanism can transfer the medicament components from one container to the other container until ready to be delivered or transferred through the fluidic channel through a delivery assembly.