Abstract: A system and method for efficiently determining a diagnostic protocol used by a vehicle under service and instantiating service appropriately. The diagnostic protocol is checked for expected electrical behaviors exhibited at the pins of a diagnostic port of a vehicle. If the expected behaviors are observed, a first protocol is designated for use. If the expected behaviors are not observed, other protocols are test for appropriate designation.

Abstract: Battery arrays are provided for traction battery packs. An exemplary battery array may include a first cell stack subassembly including a first split dividing wall member, and a second cell stack subassembly including a second split dividing wall member. The first split dividing wall member and the second split dividing wall member cooperate to establish a dividing wall assembly between the first cell stack subassembly and the second cell stack subassembly. The dividing wall assembly can function to both provide the necessary tensile structure for maintaining battery cell compression and thermally isolate the adjacent cell stack subassemblies from one another.

Abstract: Placing an event into a particular cluster can allow various inferences about the event. A new payment transaction that looks similar to a previously identified cluster of mostly fraudulent payment transactions, for example, may be higher risk. The present disclosure includes structural data improvements to the way that online clustering of events (which may include web events and not just payment transactions) occurs. A new event can be classified into a particular segment very quickly using feature table searching, which can allow for better decision making when a short timeframe is required (e.g. transaction processing, online advertising, etc.).

Abstract: A system is disclosed that includes an image sensor, a depth sensor, and at least one processor. The image sensor acquires images within a first field-of-view. The depth sensor includes a plurality of photosensitive cells that acquires distance information within a second field-of-view. The second field-of-view at least partially overlaps the first field-of-view. The at least one processor is programmed to transition from a first mode of operation to a second mode of operation in response to satisfaction of a specified criteria based on object information associated with the distance information for an object within the second field-of-view.

Abstract: Methods, systems, and media for secure authentication of users using one or more biometric recognition systems are provided. In some embodiments, the method comprises: receiving an indication that a biometric identifier is to be used to authenticate a user to a service; receiving (i) the biometric identifier of the user from a capture device and (ii) knowledge-based secondary information associated with the user from an input device; determining a Voronoi cell identifier that corresponds to the biometric identifier; calculating a hash of the Voronoi cell identifier and the knowledge-based secondary information; transmitting the hash to a server device for verification; in response to transmitting the hash to the server device, receiving a response indicating whether the hash matches a previously stored hash that was stored in the server device; and determining whether to automatically authenticate the user to the service based on the response from the server device.

Abstract: Secure methods, systems, and media for generating and verifying user credentials are provided. In some embodiments, the method comprises: receiving, from a user device, a request for access to a service that requires valid user credentials; determining an aspect of the user credentials that is to be satisfied to grant access to the requested service; transmitting, to the user device, a request for information related to the aspect of the user credential; receiving, from the user device, information related to the aspect of the user credential, wherein the information has been signed using a key associated with the user device; verifying the key used to sign the information by the user device; in response to verifying the key used to sign the information, determining whether the aspect of the user credential has been satisfied based on the received information; and, in response to determining that the aspect of the user credential has been satisfied, granting access to the service.

Abstract: An analyzer system for in vitro diagnostics includes a sample handler module having a robot arm that delivers samples from drawers into carriers on a linear synchronous motor automation track. Samples are delivered via the automation track to individual track sections associated with individual analyzer modules. Analyzer modules aspirate sample portions directly from the sample carriers and perform analysis thereon.

Abstract: Identity systems, methods, and media for auditing and notifying users concerning verifiable claims are provided.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may provide a computer code instruction set to a machine to execute the task to facilitate an improvement in the operation of the value chain network.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained on a training data set of a set of value chain network entities operating data to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of at least one value chain entity of the set of value chain network entities. A VCN process may determine a task to be completed for the value chain network based upon, at least in part, on an output of the set of AI-based learning models. A VCN process may execute the task to facilitate an improvement in the value chain network.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may configure a robotic process automation system to execute the task to facilitate an improvement in the value chain network.

Abstract: A VCN process may receive, by a computing device, information associated with a set of value chain network entities of a value chain network, the information generated by at least one of a set of sensors of the set of value chain network entities, a set of IoT devices configured to collect data relating to the set of value chain network entities, or a set of APIs configured to publish data relating to the set of value chain network entities. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models. A VCN process may determine a potential risk in the value chain based upon, at least in part, an output of the AI-based learning classification. A VCN process may execute an action to mitigate the potential risk in the value chain network.

Abstract: A VCN process may receive, by a computing device, information associated with a set of value chain network entities of a value chain network, the information generated by at least one of: a set of sensors of the set of value chain network entities, a set of IoT devices configured to collect data relating to the set of value chain network entities, or a set of APIs configured to publish data relating to the set of value chain network entities. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models. A VCN process may determine a procurement action to be taken in the value chain network based upon, at least in part, an output of the set of AI-based learning models. A VCN process may execute the procurement action.

Abstract: A VCN process may receive information associated with a set of value chain network entities. A VCN process may provide the information to a first set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the first set of AI-based learning models is trained to generate a prediction of future demand for an item. A VCN process may provide the information to a second set of AI-based learning models, wherein at least one member of the second set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of at least one value chain entity. A VCN process may determine a potential risk in the value chain network associated with the at least one value chain network entity based upon, at least in part, an output of the AI-based learning models.

Abstract: A VCN process may receive, by a value chain network digital twin, information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained to determine a task to be completed for the value chain network. A VCN process may provide at least one of an instruction for executing the task in the value chain network digital twin and a recommendation for executing the task in the value chain network digital twin.

Abstract: An analyzer system for in vitro diagnostics includes a sample handler module having a robot arm that delivers samples from drawers into carriers on a linear synchronous motor automation track. Samples are delivered via the automation track to individual track sections associated with individual analyzer modules. Analyzer modules aspirate sample portions directly from the sample carriers and perform analysis thereon.

Abstract: Methods, systems, and media for recovering identity information in verifiable claims-based systems are provided.

Abstract: Methods, systems, and media for secure authentication of users using one or more biometric recognition systems are provided. In some embodiments, the method comprises: receiving an indication that a biometric identifier is to be used to authenticate a user to a service; receiving (i) the biometric identifier of the user from a capture device and (ii) knowledge-based secondary information associated with the user from an input device; determining a Voronoi cell identifier that corresponds to the biometric identifier; calculating a hash of the Voronoi cell identifier and the knowledge-based secondary information; transmitting the hash to a server device for verification; in response to transmitting the hash to the server device, receiving a response indicating whether the hash matches a previously stored hash that was stored in the server device; and determining whether to automatically authenticate the user to the service based on the response from the server device.

Abstract: Secure methods, systems, and media for generating and verifying user credentials are provided. In some embodiments, the method comprises: receiving, from a user device, a request for access to a service that requires valid user credentials; determining an aspect of the user credentials that is to be satisfied to grant access to the requested service; transmitting, to the user device, a request for information related to the aspect of the user credential; receiving, from the user device, information related to the aspect of the user credential, wherein the information has been signed using a key associated with the user device; verifying the key used to sign the information by the user device; in response to verifying the key used to sign the information, determining whether the aspect of the user credential has been satisfied based on the received information; and, in response to determining that the aspect of the user credential has been satisfied, granting access to the service.

Abstract: Methods, systems, and media for secure authentication of users using one or more biometric recognition systems are provided. In some embodiments, the method comprises: receiving an indication that a biometric identifier is to be used to authenticate a user to a service; receiving (i) the biometric identifier of the user from a capture device and (ii) knowledge-based secondary information associated with the user from an input device; determining a Voronoi cell identifier that corresponds to the biometric identifier; calculating a hash of the Voronoi cell identifier and the knowledge-based secondary information; transmitting the hash to a server device for verification; in response to transmitting the hash to the server device, receiving a response indicating whether the hash matches a previously stored hash that was stored in the server device; and determining whether to automatically authenticate the user to the service based on the response from the server device.