Abstract: The present disclosure relates to development of a self-service artificial intelligence platform by integrating data-based model with physics-based model and vice-versa to generate real-time recommendations and control actions. Further, the present disclosure provides the system and method for at least one of data collection and preparation, developing a hybrid system/control model, and developing a physics-based model driven by data-based model and vice versa to generate real-time recommendations and control actions.

Abstract: A data storage device and method for host-determined proactive block clearance are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to receive a command from a host that specifies a parameter of an upcoming burst mode; and in response to receiving the command, proactively perform a garbage collection operation according to the parameter to create available storage space in the memory to store data from the host during the upcoming burst mode. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.

Abstract: A method for dynamically replicating data in a disaggregated distributed storage system includes receiving, by a processor, a request from a controller to replicate data; dynamically selecting, by the processor, a storage node for replicating the data from among a plurality of storage nodes, based on one or more replication parameters associated with each storage node of the plurality of storage nodes, wherein the one or more replication parameters include at least one of a flash factor corresponding to the each storage node, and a latency between the controller and the each storage node; and providing, by the processor, information about the selected storage node to the controller for replicating the data.

Abstract: A method for identifying fraudulent cryptographic currency transactions using a deep neural network includes: receiving, by a receiver of a processing server, a source dataset, the source dataset including labeled source data associated with a plurality of source features and being associated with a source domain; receiving, by the receiver of the processing server, a target dataset, the target dataset including unlabeled target data associated with a plurality of target features and being associated with a target domain; combining, by a processor of the processing server, at least a subset of the plurality of source features and at least a subset of the plurality of target features into a combined data layer; training, by the processor of the processing server, a deep neural network using a domain adaptation algorithm and the combined data layer to identify a set of final features.

Abstract: According to one embodiment, a method for generating a cardiac map is disclosed. The method comprises during cardiac mapping in which a mapping catheter is inserted into a heart, receiving a plurality of recordings from the mapping catheter, each recording includes a voltage, and the spatial coordinates of a recording site within the heart indicative of an electrode position of the mapping catheter at the time of acquisition of said voltage, constructing a three-dimensional surface of the heart based on the spatial coordinates of each recording site, performing surface analysis to determine off-surface points in the plurality of recordings where each off-surface point corresponds to a recording from the plurality of recordings which does not lie on the three-dimensional surface, and selectively moving at least some of the off-surface points to the three-dimensional surface based on a predefined threshold.

Abstract: Provided is a system for predicting a response of a user in a multi-user environment. The system includes a display engine configured to display a user interface (UI) on a display screen for inputting a message corresponding to received messages from one or more contacts, a first processing engine configured to generate a list of correlated candidate messages associated with an input message using received messages, a second processing engine configured to predict a set of correlated candidate messages relevant to the input message from the list of correlated candidate messages, and a third processing engine configured to generate a priority list of candidate messages including the predicted set of correlated candidate messages. The display engine displays, on the display screen, at least one of one or more appropriate candidate messages based on a priority associated with the appropriate candidate messages in the generated priority list of candidate messages.

Abstract: An apparatus for the generation of an impedance model of a biological chamber is disclosed. The apparatus includes a catheter assembly comprising a plurality of electrodes arranged into one or more constraint pairs. The apparatus includes a processor and a memory communicatively connected to the processor. The memory instructs the processor to receive tank data. The memory instructs the processor to generate a plurality of relative configurations of the plurality of electrodes as a function of the tank data using a compliant configuration generator. The memory instructs the processor to record voltage data from the plurality of electrodes within a biological chamber as a function of the plurality of relative configurations. The memory instructs the processor to map a plurality of impedance metrics for each relative configuration as a function of the voltage data. The memory instructs the processor to generate an impedance model as a function of the map.

Abstract: A system includes a server device which receives a charter service request from a user device is provided herein. The vehicle charter service request includes information about the request including a specified pickup location, one or more specified stop locations, and a specified destination location. The server device may provide a graphical user interface for the one or more vehicle types which are selectable for providing the vehicle charter service. The server device creates an optimized route for the charter service based on the specified pickup location, one or more specified stop locations, and a specified destination location. The server device may further provide a map and real time tracking for a vehicle providing the charter service.

Abstract: A system and method include a server device which transmits a list of passengers for a vehicle route. The list of passengers may include profiles for each one of the passengers. The server device may further receive a unique identification for a passenger boarding a vehicle and compare the unique identification to the list of passengers for the vehicle route. The server device may further identify the passenger boarding the vehicle as being on board the vehicle in the profile for that passenger. The server device may further receive vehicle status information from the vehicle and transmit driver navigational information to a driver device. The server device may further transmit real time tracking data to a user device, including a map with an indicator of a current location of the vehicle.

Abstract: A system and method include a server device which identifies a plurality of stops for a vehicle among a fleet of vehicles. The server device also identifies stop locations for each one of the plurality of stops and a side of a street for each one of the plurality of stops. Once identified, the server devices generates an optimized route for service by the vehicle to service each one of the stop based on an optimized stop order for each one of the plurality of stops based on the stop locations being disposed only on the identified side of the street for each one of the plurality of stop locations. The optimized route may be provided to a driver device while the route and time of arrival information may be provided to a user.

Abstract: A system and method that includes a ride requestor device, a driver device, a server device, and a user device is disclosed. The ride requestor device provides rider information and stop location information for a plurality of riders. The driver device provides location information, navigation information, and stop timing information for a particular vehicle in a fleet of vehicles. The server device includes an artificial intelligence engine which generates and optimizes a plurality of routes for service by the fleet of vehicles to provide a ride to each one of the plurality of riders.

Abstract: A system and method include a device associated with a user. The device may identify to a server computer a route to be reassigned from a first vehicle to a second vehicle among a fleet of vehicles. The server device may include an artificial intelligence engine which compares the route to be reassigned to a plurality of route groups associated with one of the administrator and the ride requestor. The server device may further identify one or more route groups which are able to service the route to be reassigned based on the artificial intelligence engine. The server device may transmit a graphical representation of one or more of the plurality of route groups which is proximally available in terms of location and time, as determined by the artificial intelligence engine to service the route to be reassigned with a color coded indicator. The server device reassigns the route.

Abstract: A graphical user interface and a system are provided which include a route identification interface element which specifies a new route for a vehicle, a plurality of route type buttons, a vehicle type interface, a stop order interface, a map, a control button, and an assignment button. The stop order interface identifies one or more stops for a vehicle in a fleet of vehicles. The map identifies the new route and the one or more stops graphically on the graphical user interface. The control button provides a utilization view for the one or more vehicles in the fleet of vehicles from which a vehicle from the one or more vehicles in the fleet of vehicles that are available can be assigned to the new route.

Abstract: Providing overload protection may include receiving, from a first NRF of two or more NRFs, a load metric and comparing the load metric to a threshold. Additionally, when the load metric is above the threshold, providing NRF overload protection may include sending a Network Function (NF) Discovery (NFD) message to a second NRF instead of the first NRF and sending a heartbeat signal to the first NRF.

Abstract: Described herein is an apparatus and method for predicting Pulsed Field Ablation (PFA) durability. An apparatus may include at least a processor; and a memory communicatively connected to the at least processor, wherein the memory contains instructions configuring the at least processor to receive a training dataset comprising a plurality of example PFA device parameters correlated to a plurality of example PFA outcomes; train a PFA durability machine learning model using the training dataset; receive a PFA device parameter; and generate a PFA durability datum as a function of the PFA device parameter using a trained PFA durability machine learning model.

Abstract: Described herein is a method of improving the inhibitory profile of Streptococcus salivarius comprising formulating the S. salivarius in a composition comprising an effective amount of a supplemental saccharide. Also described herein are compositions comprising Streptococcus salivarius and supplemental saccharide, methods of inhibiting microorganisms using such compositions, therapeutic formulations comprising such compositions, and methods of treating or preventing diseases using such compositions and therapeutic formulations.

Abstract: Data transformation and data quality checking is provided by reading data from a source datastore and storing the data into memory, performing in-memory processing of the data stored in memory, where the data is maintained in-memory for performance of the in-memory processing thereof, and where the in-memory processing includes performing one or more transformations on the data stored in memory, in which the data stored in memory is transformed and stored back into the memory and applying one or more data quality rules to the data stored in-memory, and based on performing the in-memory processing of the data stored and maintained in memory for the in-memory processing, loading to a target datastore at least some of the data processed by the in-memory processing.

Abstract: Various embodiments described herein relate to an asset discovery engine with a deep vulnerabilities scanner with respect to assets in an industrial network. In an embodiment, a request to perform an asset vulnerability assessment of one or more assets within a network is received, the request comprising an asset descriptor describing the one or more assets. In response to the request, aggregated asset property data associated with the one or more assets is obtained based on the asset descriptor. Furthermore, the asset vulnerability assessment is performed based on the aggregated asset property data and asset vulnerability signature data stored in an asset vulnerability signature repository. In response to determining that the asset vulnerability assessment satisfies a defined criterion, one or more actions associated with the network are performed.

Abstract: A method for a graphical user interface (GUI) of a computer system is provided. The method comprises displaying within a first portion the GUI, an electro-anatomical map of the heart, said electro-anatomical map comprising a plurality of measurement points within the heart for which data was collected; displaying a plurality of markers, each representing a respective one of said measurement points spatially in relation to the geometry of the heart within said first portion; determining, by a processor, user-selection of a particular measurement point within the heart through selection of its associated marker; responsive to said user-selection of the particular measurement point, retrieving at least one metric associated with said measurement point; and displaying in a second portion of the GUI, each retrieved metric associated with a particular measurement point within the heart.

Abstract: A system and method include providing a list of children to be picked up by a vehicle at a particular stop along a route to a driver device. The provided list is displayed as part of a graphical user interface which includes a plurality of pick up options for each child in the list of children. The options include a picked up interface button, a no show interface button and a canceled button. The graphical user interface provides a picture and identification of each child. The server device transmits a message to a user device with confirmation that a child has been picked up. The server device also provides a list of children to be dropped off by the vehicle via a graphical user interface that also provides drop off options for each child in the list of children including a dropped off button or an on hold button.