Abstract: In various embodiments, methods, systems, and vehicle apparatuses are provided. A method for determining a trusted context of operation by an in-vehicle Network Intrusion Detection System (NIDS) for learning of a vehicle platform, including executing the NIDS to monitor a set of Electronic Control Units (ECUs) and vehicle state elements by receiving a set of vehicle derived inputs about a vehicle's operating state; in response to a determination about the vehicle's operating state, identifying the trusted window during which learning about network topology and whitelisted messages contained in a vehicle platform is allowable; creating a vehicle-specific configuration containing a list of networks of topologies and whitelisted messages in use by the ECUs in the vehicle platform, and preventing misconfiguring of at least one network in the list of network topologies and whitelisted messages of the vehicle-specific configuration in the vehicle platform outside the trusted window.

Abstract: A biometric information authentication device includes a control unit, wherein, when a first biometric authentication is successfully completed based on biometric information acquired from an operator and registered biometric information preliminarily registered by a registered person and an operation for registering new registered biological information is subsequently performed, the control unit permits registration upon a successful second biometric authentication based on biometric information acquired again and the registered biometric information preliminarily registered by the registered person.

Abstract: A method and a system for providing a shared state module that acts as a common interface for facilitating data sharing among microservice front-end modules that are being used in conjunction with one another within a single application are provided. The method includes: receiving an input that includes information that relates to a set of microservice modules to be utilized for constructing an application; uploading each of the set of microservice modules and a shared state module that is configured to facilitate data sharing; transmitting, to each of the set of microservice modules, an instruction that provides access to the shared state module; and when a particular microservice module requests a subset of data that is accessible via the shared state module, causing the requested subset of data to be received by the particular microservice module.

Abstract: A hardware client and corresponding method employ an object-oriented memory device. The hardware client generates an object-oriented message associated with an object of an object class. The object class includes at least one data member and at least one method. The hardware client transmits the object-oriented message generated to the object-oriented memory device via a hardware communications interface. The hardware communications interface couples the hardware client to the object-oriented memory device. The object is instantiated or to-be instantiated in at least one physical memory of the object-oriented memory device according to the object class. The at least one method enables the object-oriented memory device to access the at least one data member for the hardware client.

Abstract: Methods are provided for improving performance of a computing system used to model potential crop yield. In one example embodiment, a computer-implemented method includes generating a model of potential crop yield, as a function of planting date and relative maturity based, at least in part, on one or more relative maturity maps, one or more planting date maps, and one or more actual production history maps, and storing the model in a memory of the server computer system. The method also includes receiving, via an interface at a field manager computing device, a selection of a particular field and computing, from the model of potential crop yield, a potential yield for the particular field based, at least in part, on a planting date for the particular field, a relative maturity value, and values representing actual production history for the particular field.

Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for determining optimized solutions to input problems in a containerized, cloud-based (e.g., serverless) manner. In one embodiment, an example method is provided. The method comprises: receiving a problem type of an input problem originating from a client computing entity; mapping the problem type to one or more selected solver types; generating one or more container instances of one or more compute containers, each compute container corresponding to a selected solver type; generating a problem output using the one or more container instances; and providing the problem output comprising a solution to the input problem to the client computing entity.

Abstract: An authentication method includes: receiving a command of an upper host; parsing an option parameter in the command; determining a value of a fingerprint authentication identifier in the option parameter, and if the value is a first preset value, prompting a user to input a fingerprint and verifying the fingerprint input to obtain a user operation verification result; if the value is a second preset value, prompting the user to press a key and verifying the key pressed to obtain a user operation verification result; determining the user operation verification result, and if the user operation verification result is success, setting an authentication mode confirmation identifier, obtaining client data from the command, generating data to be signed, signing the data to be signed to generate a signature result, sending the signature result to the upper host; if the user operation verification result is failure, reporting an error.

Abstract: A method for accessing Redfish data that is compliant with Redfish® specification, and that is stored in a board baseboard management controller (BMC) of a computer device is provided. The method includes: executing a unified extensible firmware interface (UEFI) application to transmit a data request to the BMC through a host interface using a representational state transfer (REST) protocol; when it is determined that Redfish data that corresponds with a URL included in the data request has been received, performing data transformation on the Redfish data to obtain transformed data; and generating and presenting the transformed data on a graphic interface.

Abstract: Embodiments included herein generally relate to processing data samples. More particularly, embodiments relate to processing a plurality of data samples using a multi-agent ring-buffer and a plurality of agents configured to communicate with the ring-buffer to process each of the plurality of data samples.

Abstract: Systems and methods for data anomaly detection include recommending one or more algorithms from a set of algorithms to process received time series data, wherein the one or more algorithms are recommended based at least in part on a type of workload for processing the received time series data. Assisted parameter tuning is provided for a detected anomaly alert and calibration, and the received time series data is processed based on a user selected algorithm that is parameter tuned.

Abstract: Systems, computer-implemented methods, and computer program products that can facilitate refinement of a predicted event based on explainability data are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an interpreter component that identifies a probable cause of a predicted event based on explainability data. The computer executable components can further comprise an enrichment component that executes a diagnostic analysis based on the probable cause.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving a new application programming interface (API) specification and extracting one or more keywords from the new API specification. The method also includes identifying, using a trained machine learning (ML) model, one or more existing API specifications that are similar to the new API specification based on the one or more keywords from the new API specification and, responsive to the identification, outputting information regarding the one or more existing API specifications that are similar to the new API specification.

Abstract: Systems and methods for automated notification and resolution of trigger events are disclosed. According to one embodiment, a method for automated notification and resolution of trigger events may include: (1) monitoring, by a backend computer program, an account for a trigger condition; (2) generating, by the backend computer program, a voice notification for the trigger condition; (3) communicating, by the backend computer program, the voice notification to an electronic device associated with the account and a link to a network location to resolve the trigger condition; (4) presenting, by the backend computer program and at the network location to resolve the trigger condition, one or more resolution options; (5) receiving, by the backend computer program and at the network location to resolve the trigger condition, a selection of one of the one or more resolution options; and (6) executing, by the backend computer program, the selected resolution option.

Abstract: In an example embodiment, a graphical user interface-based software tool is provided that uses integrated process information and information of a technical infrastructure to provide automatically-analyze integrations. The tool displays a list of integrations available with one or more corresponding software products linked to the first process by the linkage, each integration in the list of integrations identifying a separate software product with a separate application program interface (API) from the first software product.

Abstract: In a general aspect, a method for determining a location of motion detected by wireless communication devices in a wireless communication network includes obtaining motion data associated with a first time frame. The motion data includes a set of motion indicator values. The method also includes generating a first probability vector based on the set of motion indicator values and obtaining a second probability vector generated from motion data associated with a prior time frame. The method additionally includes obtaining a transition probability matrix that includes transition values and non-transition values. The method further includes determining, by operation of a data processing apparatus, a location of the motion detected from the wireless signals exchanged during the first time frame.

Abstract: A distributed, web-services based storage system. A system may include a web services interface configured to receive, according to a web services protocol, a given client request for access to a given data object, the request including a key value corresponding to the object. The system may also include storage nodes configured to store replicas of the objects, where each replica is accessible via a respective unique locator value, and a keymap instance configured to store a respective keymap entry for each object. For the given object, the respective keymap entry includes the key value and each locator value corresponding to replicas of the object. A coordinator may receive the given client request from the web services interface, responsively access the keymap instance to identify locator values corresponding to the key value and, for a particular locator value, retrieve a corresponding replica from a corresponding storage node.

Abstract: A system, device, method, and datastack for managing applications that manage operation of assets are provided. In the method, data is shared between the applications. The method includes generating, by a first application of the applications, one or more metadata stacks associated with one or more assets. The one or more metadata stacks include at least one metadata string generated based on operation of the one or more assets. Access to the one or more metadata stacks is enabled. A second application of the applications is capable of accessing the one or more metadata stacks and datapoints associated with the one or more metadata stacks.

Abstract: Embodiments described herein are generally directed to the use of sidecars to perform dynamic Application Programming Interface (API) contract generation and conversion. In an example, a first call by a first microservice to a first API of a second microservice is intercepted by a first sidecar of the first microservice. The first API is of a first API type of multiple API types and is specified by a first contract. An API type of the multiple API types is selected by the first sidecar. Responsive to determining the selected API type differs from the first API type, based on the first contract, a second contract is generated by the first sidecar specifying a second API of the selected API type; and a second sidecar of the second microservice is caused to generate the second API and internally connect the second API to the first API based on the second contract.

Abstract: A method, apparatus, system, and computer program product provide the ability to dynamically generate a digital building information model. Design data for various designs is received. The design data for each design is encoded into a graph. A knowledge base is maintained and defines a model of design intent while processing and storing the graph. First user input of a goal or constraint is received. The knowledge base generates solutions based on the input. Second user input based on the solutions is received and used to iteratively train the knowledge base. The solutions are then output.

Abstract: A message limit value to be used in enqueuing one or more messages on a queue of a device of the computing environment is obtained. The message limit value indicates whether an extended maximum message length is supported by the device. The extended maximum message length is different from a default maximum message length supported by the device. Based on determining that the extended maximum message length is supported and that the obtained message limit value has a defined relationship with a select value, at least one message of an extended length is enqueued on the queue of the device.