Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at a client computer, a driver script file; creating, by the driver script file, a use-case specific directory; creating, by the driver script file, an application parameters file; retrieving, by the driver script file, a core configuration script file; determining, by the core configuration script file, a required database driver; retrieving, by the core configuration script file, the required database driver; retrieving, by the core configuration script file, a database driver configuration file for the required database driver; populating, by the core configuration script file, the database driver configuration file with a plurality of entries, wherein the plurality of entries in the database driver configuration file comprise entries based on a user input; and validating, by the core configuration script file, a connection defined by the database driver configuration file.

Abstract: Monitoring of animals in a herd has various challenges. A method and a system for monitoring and measuring the behavior of a plurality of animals in a herd chamber is provided. The disclosure provides a method to develop a model to identify the animal interactions between a given set of herds of two or more animals. The system uses image, RFID sensors, animal phenotyping information such as species, breed, age and reproduction cycle information to generate an animal profile. This profile is used to quantify the interaction into an aggression score to the animals in the given herd. The aggression score over a given duration can help herd manager to put the animals with similar aggression score together. This will also help analyze the temporal aspects of the aggression score for a given animal and take preventive measures.

Abstract: A method, computer program product, and computing system for processing workload data associated with processing a plurality of requests for an artificial intelligence (AI) model on a processing unit. A maximum number of key-value (KV) cache blocks available for the workload data is determined by simulating the workload data using a simulation engine. A token utilization for the workload data is determined based upon, at least in part, the maximum number of KV cache blocks available for the workload data. Processing unit resources are allocated for the processing unit based upon, at least in part, the token utilization.

Abstract: A compressed fluid source assembly may comprise: a pressure cylinder configured to receive a compressed fluid source therein; and a surface acoustic wave (SAW) sensor coupled to an external surface of the pressure cylinder.

Abstract: An apparatus comprising a network interface controller comprising a queue for messages for a thread executing on a host computing system, wherein the queue is dedicated to the thread; and circuitry to send a notification to the host computing system to resume execution of the thread when a monitoring rule for the queue has been triggered.

Abstract: Hybrid and adaptive cooling systems are described. A method comprises selecting a cooling system type from a set of cooling system types of a hybrid cooling system to cool an electronic component of an electronic device, generating a control directive to activate a cooling component of the cooling system type, and performing thermal management of the electronic component of the electronic device using the cooling component of the cooling system type. Other embodiments are described and claimed.

Abstract: Methods and apparatus are provided herein. For example, a method for maintaining a power conversion system can include transmitting, to a computing apparatus in operable communication with the power conversion system, an alert message indicating non-working microinverters and which of the non-working microinverters are under warranty and eligible for replacement; receiving, from the computing apparatus, a request for replacement for the non-working microinverters; and transmitting, to the computing apparatus, an acknowledgment message indicating that the request has been successfully received and replacements for the non-working microinverters are being shipped.

Abstract: A female Luer fitting disinfection device comprises a container comprising a bottom surface, a side wall, and an open end; a porous foam insert disposed within the container, the porous foam insert comprising a central region. A plug is positioned within the central region, the plug sized and shaped to fit within a lumen of the female Luer fitting, and a liquid disinfectant is in the container and absorbed within the porous foam insert. A sealing web covering the open end of the container. A method of disinfecting a female Luer fitting is also provided.

Abstract: There is disclosed in one example an application-specific integrated circuit (ASIC), including: an artificial intelligence (AI) circuit; and circuitry to: identify a flow, the flow including traffic diverted from a core cloud service of a network to be serviced by an edge node closer to an edge of the network than to the core of the network; receive telemetry related to the flow, the telemetry including fine-grained and flow-level network monitoring data for the flow; operate the AI circuit to predict, from the telemetry, a future service-level demand for the edge node; and cause a service parameter of the edge node to be tuned according to the prediction.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to estimate workload complexity. An example apparatus includes processor circuitry to perform at least one of first, second, or third operations to instantiate payload interface circuitry to extract workload objective information and service level agreement (SLA) criteria corresponding to a workload, and acceleration circuitry to select a pre-processing model based on (a) the workload objective information and (b) feedback corresponding to workload performance metrics of at least one prior workload execution iteration, execute the pre-processing model to calculate a complexity metric corresponding to the workload, and select candidate resources based on the complexity metric.

Abstract: A method comprises collecting usage data for a plurality of automated resources integrated in a platform, computing a utilization score for one or more automated resources of the plurality of automated resources based at least in part on the usage data, and predicting a future utilization for the one or more automated resources using one or more machine learning algorithms. Integration of the one or more automated resources in the platform is controlled based at least in part on one or more of the utilization score and the future utilization.

Abstract: The present disclosure provides a composition comprising a histone deacetylase (HDAC) inhibitor and an immune checkpoint inhibitor and methods for using the same in treating cancer.

Abstract: Provided herein is an instrument delivery device including an instrument, a housing having a proximal end and a distal end and defining an inner volume configured to movably receive the instrument, a coupling device positioned at the distal end of the housing and including a lock configured to couple the housing to a proximal connector of the catheter assembly, and an advancement member configured to move relative to the housing to move the instrument between a first position and a second position. A scrubbing cap is engaged with the lock that includes a scrubbing insert, a housing having a connector portion configured to engage with the lock, a holder portion configured to retain the scrubbing insert therein, and a seal that seals the scrubbing insert within the holder portion. The scrubbing cap is engaged with the lock so as to be removable from the instrument delivery device.

Abstract: Examples described herein provide a method for drilling a wellbore by a wellbore operation system into a subsurface of the earth. The wellbore operation system includes a bottom hole assembly. The method includes conveying the bottom hole assembly into the wellbore. The method further includes selecting a well plan for the wellbore. The method further includes measuring well data by at least one sensor in the wellbore operation system while the bottom hole assembly is in the wellbore. The method further includes generating, by a processing device, a steering proposal based at least in part on the well plan and the well data. The method further includes drilling, with the wellbore operation system, at least a portion of the wellbore based at least in part on the steering proposal.

Abstract: Technologies for accelerated key caching in an edge hierarchy include multiple edge appliance devices organized in tiers. An edge appliance device receives a request for a key, such as a private key. The edge appliance device determines whether the key is included in a local key cache and, if not, requests the key from an edge appliance device included in an inner tier of the edge hierarchy. The edge appliance device may request the key from an edge appliance device included in a peer tier of the edge hierarchy. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys in the key cache for eviction. The edge appliance device may activate per-tenant accelerated logic to identify one or more keys for pre-fetching. Those functions of the edge appliance device may be performed by an accelerator such as an FPGA. Other embodiments are described and claimed.

Abstract: State of art techniques mostly rely of computationally intensive, time consuming Neural Networks. Embodiments provide a method and system for identification and classification of different grain and adulterant types for grain grading analysis. The method analyzes input image of grain sample of elements to determine morphological features of elements, using dynamically determined calibration factor from reference object in the image. Variation in perimeter of elements is used to perform classification of elements into target grain size, low size adulterants and higher size adulterants. The aspect ratio of target grain determines grain variety and adulterants determine adulteration percentage. Elements are classified into grain colored and non-grain colored adulterants. Grain colored adulterants are further classified as Grain Like Impurities and non-GLI, using predefined ranges of standard deviation of perimeter metric.

Abstract: Examples described herein relate to a network device apparatus that includes a packet processing circuitry configured to determine if target data associated with a memory access request is stored in a different device than that identified in the memory access request and based on the target data associated with the memory access request identified as stored in a different device than that identified in the memory access request, cause transmission of the memory access request to the different device. In some examples, the memory access request comprises an identifier of a requester of the memory access request and the identifier comprises a Process Address Space identifier (PASID) and wherein the configuration that a redirection operation is permitted to be performed for a memory access request is based at least on the identifier.

Abstract: Technologies for fulfilling service requests in an edge architecture include an edge gateway device to receive a request from an edge device or an intermediate tier device of an edge network to perform a function of a service by an entity hosting the service. The edge gateway device is to identify one or more input data to fulfill the request by the service and request the one or more input data from an edge resource identified to provide the input data. The edge gateway device is to provide the input data to the entity associated with the request.

Abstract: An architecture to perform resource management among multiple network nodes and associated resources is disclosed. Example resource management techniques include those relating to: proactive reservation of edge computing resources; deadline-driven resource allocation; speculative edge QoS pre-allocation; and automatic QoS migration across edge computing nodes.

Abstract: Example edge gateway circuitry to schedule service requests in a network computing system includes: gateway-level hardware queue manager circuitry to: parse the service requests based on service parameters in the service requests; and schedule the service requests in a queue based on the service parameters, the service requests received from client devices; and hardware queue manager communication interface circuitry to send ones of the service requests from the queue to rack-level hardware queue manager circuitry in a physical rack, the ones of the service requests corresponding to functions as a service provided by resources in the physical rack.