Abstract: A method of using an Artificial Intelligence (AI) self-governing infrastructure design, is provided. The method provides an AI-aware, self-governing, infrastructure design which prompts the design to requisition constituent components required for a build-out of the design. In response to the prompting, the method may include using the design to initiate a plurality of tickets. The plurality of tickets procures constituent components and confirms that the initiated tickets are sufficient to place the design in a condition of viability. Following the fulfillment of the tickets, the infrastructure self-certifies operability and seeks end-user acceptance of the operability of the build-out. The design is maintained as decision-making capable, and further configured to selectively receive human intervention. The human intervention enables design customization.

Abstract: The present disclosure details systems, computer program products, and methods for machine engine analysis of network interaction data to identify conflicts. This involves the activation of an intelligence engine that connects to a backend data engine to access a database of conflict of interest (COI) datasets. The intelligence engine analyzes incoming applicant data and the COI datasets to identify potential conflicts. The identified conflicts are validated using stochastic metrics via a rules engine. A quantifiable probability metric is calculated, representing the probability of conflict from both organizational and individual perspectives. Based on the potential conflict of interest, a recommendation is generated that aligns with the calculated probability. The system then provides recommendations via API or on a user interface that is communicatively coupled to the processor.

Abstract: Embodiments of the present invention provide an approach for authenticating video data utilizing a contextual identifier. Specifically, a set of video data including contextual identifiers is captured. A respective cryptographic signature for each frame of the set of video data is generated utilizing metadata of the respective frame. Each frame of the set of video data and the respective cryptographic signature are stored on a blockchain, and the set of video data is authenticated utilizing the respective cryptographic signatures stored on the blockchain.

Abstract: Techniques are provided for optimizing the power consumption of a data storage device included in a battery-operated device. The battery-operated device (e.g., portable devices like wearable devices, smartwatches, and mobile phones) can access certain data stored on the data storage device more frequently when the device operates on battery power as compared to when the device does not operate on battery power. Techniques are provided for identifying and classifying data into different classifications, for example, power sensitive data and non-power sensitive data. Then the device can optimize the battery power consumption of the data storage device by storing or relocating data stored at the data storage device based on the classification of the data.

Abstract: Arrangements for detecting unauthorized activity based on input method analysis and monitoring are provided. In some aspects, identity information associated with a user may be received and be stored. An input may be received from a computing device of the user. An input pattern of the received input may be determined. Using a machine learning model, the input pattern of the received input may be compared to input patterns of humans and input patterns of machines. Based on the comparison, it may be determined whether the user is a human user or a non-human user. Responsive to determining that the user is a non-human user, a request may be transmitted to the user to provide increased authentication credentials. Responsive to determining that the user is a human user, an identity of the user may be verified by comparing the input pattern of the received input to the stored identity information.

Abstract: Techniques are described for orchestrating a cohort deployment in a computing network comprising a plurality of computing nodes implementing a virtualized computing network managed by an orchestrator. The cohort deployment is managed by a deployment broker configured to coordinate the cohort deployment. The cohort deployment includes multiple deployments, where the cohort deployment comprises a parent deployment and a spawned deployment that includes a dependency on the parent deployment.

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: Example methods and systems are directed to a managed inventory. A database may store information regarding items owned by a user. The information regarding an item may include a quantity owned and one or more triggering events. Based on the occurrence of a triggering event, an order for the item may be placed without user intervention. Data to the database may be provided by one or more sensors. Triggering events may be defined in terms of sensor data. The triggering event may be defined by a user or through machine learning. The order may be placed using a predetermined modality or a dynamically-determined modality based on one or more criteria, such as price, shipping speed, and the urgency of the order.

Abstract: According to a technique of code development, a plurality of subsystem power profiles for a corresponding plurality of subsystems of a host platform in a production data processing environment are received. Each of the subsystem power profiles specifies power consumption of a corresponding one of the plurality of subsystems across a range of workload traffic intensities. Based on the plurality of power profiles, source code and/or software architecture of the source code is power-optimized in a development data processing environment such that, in the production data processing environment, power consumption per unit of performance of an executable program derived from the source code is improved.

Abstract: A first forwarding VM may execute in a first availability zone and have a first IP address. Similarly, a second forwarding VM may execute in a second availability zone and have a second IP address. The first and second IP addresses may be recorded with a cloud DNS web service of a cloud provider such that both receive requests from applications directed to a particular DNS name acting as a single endpoint. A service cluster may include a master VM node and a standby VM node. An IPtable in each forwarding VM may forward a request having a port value to a cluster port value associated with the master VM node. Upon a failure of the master VM node, the current standby VM node may be promoted to execute in master mode and the IPtables may be updated to now forward requests having the port value to a cluster port value associated with the newly promoted master VM node (which was previously the standby VM node).

Abstract: Methods, systems, and apparatuses for storage device pool management based on storage device logical to physical (L2P) table information are provided. One such data storage system includes data storage devices each including a non-volatile memory; and a storage management device configured to receive L2P table information from at least two of the data storage devices; receive host data from a host device to be stored in one or more of the data storage devices; select, based on the L2P table information from the at plurality of data storage devices and the size of the host data, a target data storage device from the plurality of data storage devices; and send the host data to the target data storage device.

Abstract: An example embodiment includes determining, from a set of entries stored in a memory, a set of performed actions; identifying clusters of similar actions within the set of performed actions based on multidimensional vector embeddings of the performed actions, wherein each of the performed actions is a member of one of the clusters, and wherein each of the clusters contains at least one of the performed actions; determining a sequence for the clusters based on orderings of the performed actions within the set of entries and the membership of the performed actions within the clusters; and providing for display, on a user interface, representations of the performed actions within the clusters, wherein the representations of the performed actions are ordered according to the determined sequence for the clusters.

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: A MEMS sensor includes a through hole to allow communication with an external environment, such as to send or receive acoustic signals or to be exposed to the ambient environment. In addition to the information that is being measured, light energy may also enter the environment of the sensor via the through hole, causing short-term or long-term effects on measurements or system components. A light mitigating structure is formed on or attached to a lid of the MEMS die to absorb or selectively reflect the received light in a manner that limits effects on the measurements or interest and system components.

Abstract: A liquid radiation curable composition comprising component a) 20 to 60 weight percent of one or more reactive oligomer(s) containing at least two urethane and/or urea linkages in the backbone and at least two ethylenic unsaturated group(s) which can form polymeric crosslink networks with the other components in the composition in the presence of radicals, anions, nucleophiles or combinations thereof, with a weight average molecular weight (Mw) of greater than 3000 g/mol and glass transition temperature Tg of the cured reactive oligomer(s) itself is greater than 25° C.

Abstract: A UE may calculate an allocation of a transmission power for a first uplink transmission on a first uplink channel and at least one second uplink transmission on at least one second uplink channel, the transmission power being allocated in each symbol of a plurality of symbols in a slot. The UE may detect a transmission power change in the allocation of the transmission power in the slot for at least one of the first uplink transmission or the at least one second uplink transmission. The UE may determine whether to adjust the allocation of the transmission power for the at least one of the first uplink transmission or the at least one second uplink transmission to eliminate the transmission power change in the slot for the at least one of the first uplink transmission or the at least one second uplink transmission.

Abstract: Methods and apparatus configured to obtain a decision-point value, and send, for a logical channel group (LCG) having a quantity of data pending an uplink transmission, a long buffer status report in response to the decision-point value exceeding a threshold value, or a short buffer status report in response to the decision-point value being equal to or less than the threshold value are disclosed. The decision-point value may be a buffer status report-type determinative value, which may be based on a peak power envelope of a wireless communication device, a data transmission rate historically obtained by the wireless communication device, a number of component carriers available for a complete upload of a buffer holding data, a cost function, an amount of data associated with the LCG that is pending the uplink transmission, a type of the wireless communication device, or a latency of communications of the wireless communication device.

Abstract: Aspects of the disclosure relate to improved techniques for managing a data storage device (DSD) pool, and in particular the selecting of DSDs based on commands distribution and latencies among the command queues in the DSDs. In some aspects, a DSD may have multiple queues that enable the DSD to perform certain commands (e.g., write commands and/or read commands) in parallel. Thus, such DSD has various head-of-line blocking latencies based on which queue the command is directed to. A storage management device can reduce the command latency of the DSDs, for example, based on queue information (e.g., head-of-line blocking, parallel queue utilization, etc.) learned from the DSDs.

Abstract: Aspects directed toward data storage management are provided. A storage management device is connected to data storage devices (DSDs) that form a virtual storage pool (VSP), where the storage management device is configured to increase the overall performance of the VSP, as well as the lifespans of the individual DSDs. The storage management device can be configured to learn about the over-provisioning (OP) information of each DSD and strategically select the DSD to send write commands or data based on the OP information. The storage management device can be configured to borrow spare OP capacity from a DSD and use the borrowed capacity to expend the exported/logical capacity of the DSD.

Abstract: A liquid, radiation curable composition with a viscosity of 4000 cps or lower comprising component a) 20 to 60 weight percent of one or more oligomer(s), pre-polymer(s) or polymer(s) containing a plurality of ester linkages in the backbone, at least one or more urethane groups and at least two ethylenic unsaturated groups which can form polymeric crosslink networks with the other components in the composition in the presence of radicals, anions, nucleophiles or combination thereof, component b) 30 to 90 weight percent of one or more monomer(s) containing one ethylenic unsaturated group capable of forming polymeric crosslink networks with the other components in the composition in presence of radicals, anions, nucleophiles or combination thereof, component c) 0.