Abstract: A deep learning (DL) network is proposed to mitigate artifacts in simultaneous multi-slice (SMS) magnetic resonance imaging (MRI) data. For example, unaliased images generated from SMS aliased images can exhibit leakage artifacts due to inaccuracies in the receive-coil sensitives used during sensitivity encoding (SENSE) processing. To mitigate leakage artifacts, the DL network learns to correct the receive-coil sensitives before SENSE processing, and/or learns to detect and subtract the artifacts from the unaliased images after SENSE processing. The DL network can also be trained to denoise the unaliased images.

Abstract: An icemaker for a refrigerated appliance is provided herein. The icemaker includes an ice tray having a plurality of ice-forming compartments. Each of the ice-forming compartments includes sidewalls and a base that defines an internal freezing chamber. A duct system has upper and lower baffles. The upper baffle directs chilled air above the ice tray and the lower baffle directs chilled air below the ice tray. A deflector is operably coupled with the upper baffle. The deflector has a transition portion offset from a body portion. A diverter is disposed between the deflector and the ice tray. The diverter defines a plurality of variously sized slots therein.

Abstract: A predictive queue control and allocation system includes a queue and a queue control server communicatively coupled to the queue. The queue includes a first and second allocation of queue locations. The queue stores a plurality of resources. The queue control server includes an interface and a queue control engine implemented by a processor. The interface monitors the plurality of resources before the plurality of resources are stored in the queue. The queue control engine predicts that one or more conditions indicate that a queue overflow will occur in the first allocation of queue locations. The queue control engine prioritizes the plurality of resources being received by the queue. The queue control engine may apply a machine learning technique to the plurality of resources. The queue control engine transfers the plurality of resources prioritized by the machine learning technique.

Abstract: A method of building a service subscriber life-cycle data store by an application stored in a non-transitory memory of a computer system and executable by a processor of the computer system. The method comprises periodically reading wireless communication subscriber account logs from a log data store, parsing each of the logs to identify a subscriber associated with that subscriber account log, a time, and an account log type, analyzing the parsed account logs in time sequence order and based on the account log type to identify a plurality of subscriber life-cycle events, for each life-cycle event building a subscriber life-cycle entry comprising a date and time, a subscriber identity, and an identity of a subscriber life-cycle event, where each subscriber life-cycle entry corresponds to a plurality of subscriber account logs, and storing the subscriber life-cycle entry in a subscriber life-cycle data store.

Abstract: A drone docking system is disclosed that is connected to a drone. The drone docking system has a positioning member that connects to the drone and is configured to rotate the angle of the drone from a generally horizontal position to a generally vertical position. Connected to the positioning member is a charging member, which in one embodiment has a charging prong. The charging member is configured to connect to a power source, such as one located on existing infrastructure, e.g., a street light. A connection member is connected to the charging member. The connection member engages existing infrastructure to hold the drone in place. In one arrangement, the connection member has a pair of arcuate arms that receive, retain, and hold onto the existing infrastructure. In one example, the pair of arcuate arms are spring biased to apply a gripping pressure on the existing infrastructure.

Abstract: Described herein is a system for providing complete global mobility, operation and execution anytime, anywhere, anyplace and by any user; the system using Augmented Reality-Mixed Reality for creating live Hologram Projections (digital twins) of all available Physical Assets including assets such as humans in real world complete with monitoring, visualization, communication, operations and execution capabilities; the system incorporating Data Infused Holograms with Artificial Intelligence (Ai) Powered Descriptive, Predictive, Prescriptive and Cognitive (Fully Autonomous) Analytics and operative capabilities for Global Healthcare Ecosystems; each Hologram of the physical assets having infinite data points as required.

Abstract: A predictive queue control and allocation system includes a queue and a queue control server communicatively coupled to the queue. The queue includes a first and second allocation of queue locations. The queue stores a plurality of resources. The queue control server includes an interface and a queue control engine implemented by a processor. The interface monitors the plurality of resources before the plurality of resources are stored in the queue. The queue control engine predicts that one or more conditions indicate that a queue overflow will occur in the first allocation of queue locations. The queue control engine prioritizes the plurality of resources being received by the queue. The queue control engine may apply a machine learning technique to the plurality of resources. The queue control engine transfers the plurality of resources prioritized by the machine learning technique.

Abstract: A method of migrating a data store of wireless communication subscriber data from a source data store system to a target data store system. The method comprises receiving a provisioning request by a computer system, looking up and revising a data entry in the source data store system based on the provisioning request, copying and creating a reference to the revised data entry in the target data store system, and changing the reference in the source data store system to reference empty memory by the computer system. A second portion of data migration comprising creating a list of data entries, softlocking each data entry, reading and copying each data entry to the target data store system, creating a reference to the data entry, changing the reference in the source data store system to reference empty memory, and releasing the softlock by the computer system.

Abstract: Described herein is a method and system providing complete global maritime mobility, operation and execution of any kind, anywhere, at any place by an authorised user, the system comprising live hologram projections “Digital Assets” of all on field “Physical Assets” including humans; and the system using Augmented Reality-Mixed Reality for creating live “Digital Twins” referred to as Hologram Projections of all available physical assets including humans in real world complete with monitoring, visualisation, communication, operations and execution capabilities; the system incorporating Data Infused Holograms with Artificial Intelligence Powered Descriptive, Predictive, Prescriptive and Cognitive (Fully Autonomous) Analytics and operative capabilities for Global Maritime World; each hologram of a physical asset having infinite data points as required.

Abstract: A method and system providing complete global defence mobility, operation and execution of any kind, anywhere, at any place by an authorised user, the system comprising live hologram projections “Digital Assets” of all on field “Physical Assets”; each hologram of a physical asset having infinite data points as required; and the system creating live “Digital Twins” of all available physical assets including humans in real world complete with monitoring, visualisation, communication, operations and execution capabilities incorporating Artificial Intelligence Powered Descriptive, Predictive, Prescriptive and Cognitive (Fully Autonomous) Analytics and operative capabilities for Global Defence World.

Abstract: Described herein is a method and application platform system based on a block chain technology and created using blockchain technology and related software coding, programming languages, android technology, iOS technology, and/or azure cloud platform; the platform is incorporating multiple sub-platforms, such as BlockVOTE, BlockBOARD, BlockDRIVE, BlockAML, BlockLOAN, BlockPASSPORT and BlockVISA; and is supportive on any platforms/modes such as mobile phones, smart phones, tablets, computers, kiosks, digitals, screens, Virtual Reality supportive, Augmented Reality supportive and Mixed Reality; and incorporates block chain based encrypted digital verifications and transactions with Artificial Intelligence Instant Analytics. The platform can be accessible anytime, anywhere and by any user.

Abstract: A mechanism is provided in a computing device configured with instructions executing on a processor of the computing device to implement a ground truth generation system for quality assessment scoring of articles in a corpus. The ground truth generation system receives recommendations of a set of recommended articles from subject matter experts. The ground truth generation system identifies a set of non-recommended articles. A topic clustering component within the ground truth generation system performs topic clustering on a combination of the set of recommended articles and the set of non-recommended articles to form a set of topic clusters containing recommended articles and non-recommended articles. The ground truth generation system identifies a first number of recommended articles and a second number of non-recommended articles in each of the set of topic clusters to form a quality assessment training set.

Abstract: Magnetic resonance imaging (MRI) systems and methods to determine and/or correct slice leakage and/or residual aliasing in the image domain in accelerated MRI imaging. Some implementations process one slice of MRI image domain data by input to a sensitivity encoding (SENSE) un-aliasing matrix built from predetermined RF signal reception sensitivity maps, thereby producing SENSE-decoded MRI image domain data for one pass-through image slice and at least one extra slice, and determine inter-slice leakage and/or in-plane residual aliasing based on content of the at least one extra output slice from the SENSE-decoded MRI image domain data. Some implementations correct slice leakage in reconstructed images by generating a fractional leakage matrix of inter-slice leakage measurements, and by multiplying the inverted fractional leakage matrix with uncorrected reconstructed images.

Abstract: A magnetic resonance imaging system includes an array radiofrequency coil and processing circuitry operatively linked to the array radiofrequency coil and configured to receive output signals from the array radiofrequency coil commensurate with a simultaneous multi-slice magnetic imaging characterized by simultaneous multi-slice parameters, estimate distorted regions of the image volume using either data obtained via a pre-scan or a pre-computed model, minimize overlap of the distorted regions with image voxels representing tissue to obtain optimized values of the simultaneous multi-slice parameters, configuring and executing the simultaneous multi-slice imaging sequence based on the optimized values of the simultaneous multi-slice parameters, and reconstruct simultaneous multi-slice images with minimized artifacts.

Abstract: A cache repair tool includes an interface, a monitoring engine, and a purging engine. The interface receives a request to repair a cache. The request includes a maximum size threshold less than a total storage capacity of the cache. The request includes an identification of a data type. The monitoring engine determines an available capacity of the cache. The monitoring engine determines that the available capacity is less than or equal to the maximum size threshold. The purging engine purges data of the identified data type from the cache in response to the determination that the determined size exceeds the maximum size threshold.

Abstract: Magnetic resonance imaging (MRI) systems and methods determine slice leakage and/or residual aliasing in the image domain in accelerated MRI imaging. Implementations process one slice of MRI image domain data by input to a sensitivity encoding (SENSE) un-aliasing matrix built from predetermined RF signal reception sensitivity maps, thereby producing as matrix output SENSE-decoded MRI image domain data for one pass through image slice and at least one extra slice, and determine inter-slice leakage and/or in-plane residual aliasing based on content of the at least one extra output slice from the SENSE-decoded MRI image domain data.

Abstract: An icemaker for a refrigerated appliance is provided. The icemaker includes an ice tray having a plurality of ice-forming compartments and a duct for directing chilled air operably coupled with a diverter. The diverter includes a base having first and second sides and defining a plurality of variously sized slots. A centerline of the base is aligned with a centerline of the ice tray. At least one spacing portion extends between two of the plurality of variously sized slots. A plurality of fins extend away from a top surface of the base.

Abstract: An icemaker for a refrigerated appliance is provided herein. The icemaker includes an ice tray having a plurality of ice-forming compartments. Each of the ice-forming compartments includes sidewalls and a base that defines an internal freezing chamber. A duct system has upper and lower baffles. The upper baffle directs chilled air above the ice tray and the lower baffle directs chilled air below the ice tray. A deflector is operably coupled with the upper baffle. The deflector has a transition portion offset from a body portion. A diverter is disposed between the deflector and the ice tray. The diverter defines a plurality of variously sized slots therein.

Abstract: A predictive queue control and allocation system includes a queue and a queue control server communicatively coupled to the queue. The queue includes a first and second allocation of queue locations. The queue stores a plurality of resources. The queue control server includes an interface and a queue control engine implemented by a processor. The interface monitors the plurality of resources before the plurality of resources are stored in the queue. The queue control engine predicts that one or more conditions indicate that a queue overflow will occur in the first allocation of queue locations. The queue control engine prioritizes the plurality of resources being received by the queue. The queue control engine may apply a machine learning technique to the plurality of resources. The queue control engine transfers the plurality of resources prioritized by the machine learning technique.

Abstract: An apparatus includes an interface, a capacity engine, a monitoring engine, and a purging engine. The interface receives a request to repair a cache. The capacity engine monitors a cache to determine a first amount of data the cache receives in a first predetermined amount of time. The capacity engine determines a second amount of data indicating an estimated amount of data the cache will receive in a second predetermined amount of time. The capacity engine determines a size of the cache and a maximum size threshold using the second amount of data. The monitoring engine determines an available capacity of the cache and that the available capacity is less than or equal to the maximum size threshold. The purging engine purges data from the cache.