Abstract: Disclosed is a computer implemented method to manage queue overlap in storage systems, the method comprising, identifying, by a storage system, a plurality of queues including a first queue and a second queue. The storage system includes a plurality of cores, including a first core and a second core, and wherein the first queue is associated with a first host and the second queue is associated with a second host. The method also comprises, determining the first queue and the second queue are being processed by the first core. The method further comprises, monitoring the workload of each cores and identifying a load imbalance, wherein the loam imbalance a difference between a first workload associated with the first core, and a second workload associated with the second core. The method also comprises, notifying the second host that the load imbalance is present.

Abstract: Disclosed is an IoT enabled, portable, multiple stimuli reinforced non-nutritive Sucking Training System, Method and Device that implements a function that measures suction pressure of a non-nutritive sucking event produced by a pre-mature infant; then converts the measured pressure value using transducer to digital form; then transmits the pressure value in digital form using IoT (Internet-of-Things) controller to a server and/or to an app and/or a software installed on a smartphone device. The app and/or software installed on the smartphone device which receives the pressure measurement uses an algorithm to produce a stimulus such as music and/or haptic feedback for the pre-mature infant, to train the premature infant to suck optimally; thereby improving self-feeding capability of the premature infant.

Abstract: An approach is provided in which the approach detects a set of personal information data corresponding to a set of users in a set of training data. The approach transforms the set of training data into a set of semantically equivalent training data by replacing the set of personal information with a set of semantic equivalent data. The approach then trains a machine learning model using the set of semantically equivalent training data.

Abstract: The invention relates to Quench box assembly comprising quench pipe and quench box, to mix quench gas and vapor-liquid effluent from previous catalyst bed to achieve equilibrium temperature before entering the next bed. The quench pipe is in the form of ring having aperture while quench box consists of swirling section and a mixing chamber. The swirling section consists of inclined baffles to provide swirling action to incoming stream and the turbulence created by the swirling action increases the heat transfer rate thus requiring the smaller reactor volume to attain equilibrium temperature. The perforated plate being open from all the sides allowing the liquid to flow uniformly from all directions thus providing uniform distribution on the distributor tray. Hence, eliminates the requirement of rough liquid distributor before the distribution tray.

Abstract: A network device may receive a first data packet. The network device may determine that a level of available computing resources satisfies a threshold level. The network device may perform a secure socket layer (SSL) proxy function based on the level of available computing resources satisfying the threshold level. The network device may receive a second data packet. The network device may determine that the level of available computing resources fails to satisfy the threshold level. The network device may determine a security characteristic associated with the second data packet. The network device may determine a security rating associated with the second data packet based on the security characteristic. The network device may selectively perform the SSL proxy function based on the security rating.

Abstract: A processor may identify that a user is interacting with a device, where the interacting is identified from the user touching the device. The processor may receive tactile data associated with the user from one or more tactile sensors. The processor may extract, utilizing an AI model, one or more features of the tactile data. The processor may classify, utilizing the AI model, the tactile data as having a tactile data characteristic. The processor may output the classification to an interaction management module.

Abstract: A storage system includes a controller and block-based storage device(s) that include LSA blocks arranged as a log structured array (LSA). The controller creates a first and second LUN, each including LBA locations. The controller assigns the first LUN to a first host and the second LUN to a second host, accumulates first host data associated with a first LBA location of the first LUN, writes a block-size worth of such data to a first LSA block, and maps the first LBA location to the first LSA block. In response to receiving an ODX Copy Offload instruction, the controller determines the first host data should be migrated to a target LBA location in the second LUN, determines the first and second LUN are exclusively mappable to the same LSA, maps the target LBA location to the first LSA block, and unmaps the first LBA location from the first LSA block.

Abstract: A device may receive work item data identifying work items associated with requirements from different tools of a project and may perform data cleansing to remove and/or modify particular words from the work item data and to generate cleansed work item data. The device may perform natural language processing on the cleansed work item data to identify synonyms for words in the cleansed work item data and may replace abbreviations in the cleansed work item data with full form text to generate final work item data. The device may identify keywords in the final work item data and may process the final work item data, the synonyms, and the keywords, with a machine learning model, to identify mappings between work items of the final work item data and to determine a confidence score for the mappings. The device may perform actions based on the mappings and the confidence score.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises collecting data capable of being replicated from a computing device; detecting risks of the computing device, wherein detecting risks comprises detecting the computing device's surroundings, location, speed, and condition; initiating data replication on the computing device once the risks are determined to reach a predetermined threshold; and storing the replicated data within a cloud storage system using a 5G network.

Abstract: A computer-implemented method is used for each of two or cameras on a device, where a first camera of the two or cameras is located under a display of the device. The method further includes defining, for each camera, a best effect region on the display including a first best effect region for the first camera. The method also includes identifying, for each of one or more feeds, a feed display area including a first feed display area, where each feed display location uses a portion of the display. The method includes activating the first camera for a first feed, wherein the first feed has a first feed display area that overlaps the first best effect region.

Abstract: A computer-implemented method, system and computer program product for performing real-time monitoring of machine learning models. Real-time model state data and metadata (e.g., operating dataset) of the machine learning models located within an orchestration plane of a network are collected by agents located within the machine learning models. The portion of the collected real-time model state data and metadata that is to be provided to the user by the service orchestrator (configured to monitor the machine learning models in the service orchestration plane via the use of agents in the machine learning models) is selected and marked. The marked collected real-time model state data and metadata are then provided to the user by the service orchestrator. In this manner, real-time monitoring of the machine learning models in the orchestration plane, such as the service orchestration plane, of a broadband cellular network (e.g., fifth generation broadband cellular network) is achieved.

Abstract: A computer-implemented system and method for a transportation system comprises, using a processor associated with a service, initializing information collectors and response monitors by loading configurations, user settings, and data structures to capture device information from a plurality of devices that each run a virtual agent (VA). Fifth generation (5G) communication links are established between 5G server orchestration service instances (SOSIs) and respective VAs on the devices. Captured live status information by the SOSIs is received from various devices. A 5G dynamic ad-hoc network (DAHN) connects a user device of a user having visual impairment and a vehicle stop device, the DAHN creation being triggered by the user device entering a stop device boundary. An SOSI receives user-vehicle stop information after the connecting to the DAHN. Control information is transmitted to the vehicle device VA related to the user when the user device is located within the stop boundary.

Abstract: Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity after some customer visits to a web site of an entity and a second percentage of call propensity source data that correspond to absence of post-visit phone calls to the customer service after other customer visits to the website. A machine-learning model is trained based on a plurality of features in at least a portion of the call propensity source data to generate a trained machine-learning model. The trained machine-learning model is applied to multiple features included in at least one of corresponding website activity data and corresponding activity error data of a customer to generate a probability score that measures a likelihood of the customer calling the customer service regarding an issue that is unresolved via the website.

Abstract: A method and a system for generating data bearer mappings are provided. The method includes collecting node information from a radio access node, the node information includes resource sets operating within the radio access node. The method further includes receiving a bearer channel of a user equipment from the radio access node. The bearer channel includes a quality of service class identifier level. The method also includes connecting to the bearer channel that is transmitting data related to the user equipment and generating an insight that is based on the data and the QCI level of the user equipment. The method further includes determining a bearer mapping for the radio access nodes by analyzing node information and the insight. The bearer mapping is then transmitted to the radio access node.

Abstract: A method, system, and computer program product for managing input/output (I/O) operations in log structured arrays (LSA) is provided. The method receives a write request for a storage volume. The write request including a set of data. The method determines the set of data for a target extent of the storage volume is not copied to a target location based on a target map for a flash copy volume. An LSA is instructed to perform an internal copy-on-write (COW) for the set of data during a next IO operation for the storage volume. Based on the internal COW instruction, the method moves an internal pointer of the target location from a virtual volume to the flash copy volume.

Abstract: Methods for data visibility in nested transactions in distributed systems are performed by systems and devices. Distributed executions of queries are performed in processing systems according to isolation level protocols with unique nested transaction identifiers for data management and versioning across one or more data sets, one or more compute pools, etc., within a logical server via a single transaction manager that oversees the isolation semantics and data versioning. A distributed query processor of the systems and devices performs nested transaction versioning for distributed tasks by generating nested transaction identifiers, encoded in data rows, which are used to enforce correct data visibility. Data visibility is restricted to previously committed data from distributed transactions and tasks, and is blocked for distributed transactions and tasks that run concurrently.

Abstract: An approach is provided in which the approach receives a job request, which includes biasing parameters, from an entity operating in a distributive cognitive system. The approach evaluates the biasing parameters against a set of machine learning model bias characteristics corresponding to a set of machine learning models and selects one of the machine learning models based on the evaluating. The approach assigns the selected machine learning model to the entity to perform the job request.

Abstract: A differential can comprise a pilot clutch, a main clutch, a first ball ramp configured to act on the pilot clutch, and a second ball ramp configured to actuate the main clutch when the pilot clutch acts on the second ball ramp. An electromagnetic differential can comprise a carrier, a stator mounted on the carrier, a pilot clutch in the carrier, and a main clutch in the carrier. An electromagnetic differential can comprise a carrier and a first side gear and a second side gear in the carrier. A pilot clutch can be in the carrier surrounding a portion of the first side gear. A main clutch can be in the carrier surrounding a portion of the pilot clutch and surrounding a portion of the first side gear.

Abstract: Provided are a method, system, and computer program product in which a service orchestration layer is configured in a telecommunications network. Personalized pending user actions are transmitted to a user equipment, in response to a hold being performed over a first communications channel to the user equipment.

Abstract: In an approach to improve the field of multi-cloud environments by detecting data corruption between storage systems. Embodiments perform information tunneling on data transferring between a source storage system and a target storage system. Further, embodiments determine a checksum data of a data payload does not match an Internet Protocol (IP) packet extracted checksum and a blockchain based checksum and compare the checksum data at the target storage system with the IP packet extracted checksum and the blockchain based checksum to identify one or more checksum mismatches. Additionally, embodiments identify a corruption in a data payload based on the comparison between the checksum data at the target storage system and the IP packet extracted checksum and the blockchain based checksum, validate the corruption in the data payload, and update respective entities of identified corruption in the data payload.