Abstract: Examples described herein relate to a timing source. In some examples, the timing source generates a clock signal by synchronization with a second clock signal from a crystal source and subsequent synchronization with a third clock signal. In some examples, the third clock signal is synchronized to timing signals received in Ethernet packets. In some examples, the crystal source is to provide the second clock signal to the circuitry via the interface.

Abstract: In some embodiments, a processor may receive a claim, where the claim relates to an event. The processor may identify characteristics of the claim. The processor may determine, using an AI model, an alert reason based on a similarity of the characteristics of the claim to characteristics of one or more other claims. The processor may generate an alert notification, and the processor may output the alert notification to a user.

Abstract: Examples described herein relate to a first central processing unit (CPU) node to generate time stamp counter (TSC) values based on a first clock signal and a second CPU node to generate TSC values based on a second clock signal. In some examples, the first CPU node is to determine at least one network timer time stamp based on the TSC values based on the first clock signal and the second CPU node is to determine at least one network timer time stamp based on the TSC values based on the second clock signal. In some examples, determine at least one network timer time stamp based on the TSC values based on the first clock signal is based on (i) a relationship between the first clock signal and a device main timer and (ii) a relationship between a network timer source and the network interface device main timer.

Abstract: A method for load balancing in an Open Radio Access Network (O-RAN) system having an overloaded serving cell of a first base station includes: determining, by at least the first base station, radio-resource-usage efficiency of each one of a subset of user equipments (UEs) in the overloaded serving cell; determining, by at least the first base station, from the subset of UEs a list of candidate UEs for handover from the overloaded serving cell to a non-overloaded neighboring cell, based on one of i) per-UE average physical resource block (PRB) usage over a specified time period, or ii) per-UE average of measurements involving modulation-and-coding-scheme over a specified time period; and handing over, by the first base station, at least a selected number of UEs from the list of candidate UEs to the non-overloaded neighboring cell to implement load balancing.

Abstract: A computer-implemented method for treating a medical condition via a digital therapeutic platform, the method including receiving one or more user inputs, generating a script at a script generator, based on the one or more user inputs, determining therapeutic digital content by applying the script as an input to a therapeutic machine learning platform, receiving the therapeutic digital content via at least one of a therapeutic content database or a content generator, identifying a user platform to output the therapeutic digital content, modifying the therapeutic digital content for output via the user platform, providing the therapeutic digital content via the user platform, receiving feedback based on user consumption of the therapeutic digital content via the user platform and adjusting at least one of the script generator or the therapeutic machine learning platform based on the feedback.

Abstract: With MR-DC, UE is connected to both MCG and SCG. When an MCG handover failure occurs, there is a defined method to categorize the handover failures and take corrective actions, however, for SCG handover failures, there are no defined categorizations and corresponding corrective actions currently available. The current method facilitates identification and categorization of SCG handover failures to be categorized as too early, too late and wrong cell handovers. By fine-tuning the handover parameters (based on the SCG handover failure type) SCG handover failure rates would be reduced significantly.

Abstract: A computer-implemented system, method and/or computer program product to monitor changes in business risk of a targeted entity includes retrieving one or more industry classifications for one or more core businesses of the targeted entity; receiving news feeds related to the one or more industry classifications; detecting and extracting negative news related to the core businesses of the targeted entity from the news feeds; calculating an industry confidence score based upon the negative news; determining if the industry confidence score is greater than an industry confidence threshold; calculating, in response to the industry confidence score being larger than the industry confidence threshold, an entity confidence score for the targeted entity based upon negative news; and generating, in response to the entity confidence score being larger than an entity confidence threshold, an alert report for the targeted entity.

Abstract: In an approach to facilitate contactless remote shopping assistance, a computer-implemented method includes one or more processors configured for receiving first order data from a user device corresponding to an order of items to be retrieved from a parking lot of a retail entity proximate to a retail entity location, transmitting the first order data to the retail entity, and assigning the order to a mobility device stationed at the retail entity. The method further includes transmitting order retrieval instructions to the mobility device causing the mobility device to navigate the retail to secure the items, receiving an indication that the mobility device secured the items, and transmitting order delivery instructions to the mobility device. The method further includes receiving a second indication that the mobility device transported the items to the parking lot and placed the items in a vehicle associated with a user of the user device.

Abstract: Methods and apparatus for data plane control of network time sync protocol in multi-host systems. A network interface controller (NIC) is configured to implement a network data plane that is associated with a software-based control plane implemented in the multi-host system. The NIC includes a primary timer and secondary timers at distributed endpoints such as network ports. The NIC receives network time packets having network timestamps and employs a secondary timer to associate a local timestamp with the packets. The network and local timestamps are compared by a network intellectual property block (network IP) in the data plane datapath to adjust the primary and secondary timer(s) to match the network time. The network IP uses a 2-bit wire protocol to increment and/or decrement the primary and secondary timer(s) that enables the timers to be adjusted with a nanosecond granularity.

Abstract: A computer-implemented method for treating a medical condition via a digital therapeutic platform, the method including receiving one or more user inputs, generating a script at a script generator, based on the one or more user inputs, determining therapeutic digital content by applying the script as an input to a therapeutic machine learning platform, receiving the therapeutic digital content via at least one of a therapeutic content database or a content generator, identifying a user platform to output the therapeutic digital content, modifying the therapeutic digital content for output via the user platform, providing the therapeutic digital content via the user platform, receiving feedback based on user consumption of the therapeutic digital content via the user platform and adjusting at least one of the script generator or the therapeutic machine learning platform based on the feedback.

Abstract: Examples described herein relate to a first central processing unit (CPU) node to generate time stamp counter (TSC) values based on a first clock signal and a second CPU node to generate TSC values based on a second clock signal. In some examples, the first CPU node is to determine at least one network timer time stamp based on the TSC values based on the first clock signal and the second CPU node is to determine at least one network timer time stamp based on the TSC values based on the second clock signal. In some examples, determine at least one network timer time stamp based on the TSC values based on the first clock signal is based on (i) a relationship between the first clock signal and a network interface device main timer and (ii) a relationship between a network timer source and the network interface device main timer.

Abstract: Described are implementations of base station Control Plane (CU-CP) of a gNB-CU or an eNB-CU-CP configured to request a Distributed Unit (DU) to remove a System Information Block 1 (SIB1) or broadcast a minimal SIB1 for a network gateway—and Automatic Neighbor Relation (ANR) or a 4G Mobility Management Entity/Serving Gateway (MME/S-GW). At a disconnection of the network gateway, the CU Control Plane of the base station sends a request to the DU of the base station to remove the SIB1, or to broadcast a minimal transmission of the SIB1.

Abstract: A computer-implemented method, computer program product, and/or computing system for determining unexpected data includes: running for a given claim a machine learning term prediction model with first and second term types to predict third type terms in a specific domain that uses a machine learning term embedding model that has learned the correlation between term types in the specific domain; determining cohesiveness between the predicted third type terms and the actual third type terms from the given claim; determining a value score between the predicted third type terms and the actual third type; and running a machine learning propensity model using the value score determined for the given claim and context data for the given claim to determine if the given claim is unexpected.

Abstract: Described are systems and methods for updating a UL split threshold for a 4G leg and 5G leg for a number of split Data Radio Bearers (DRBs) using a Near-Real Time RIC or 5G Central Unit. A Near-Real Time RIC or 5G Central Unit subscribes to receive UL split threshold parameters from a gNB or eNB E2 node to determine whether to change the values of UL split threshold parameters for UL split DRBs. If so, the UL split threshold parameters are updated at the E2 node and communicated to the UE.

Abstract: Exploratory network analysis aided by an artificial intelligence recommender includes determining one or more current activities in response to detecting one or more processor-executable instructions input to a computer system by a user. A best next activity is predicted in response to matching the one or more current activities with an electronically stored pattern of activities. The predicting is performed using a machine learning model trained with knowledge components generated from patterns of past activities. A recommendation based on the best next activity is output, the recommendation recommending to the user one or more additional processor-executable instructions to input to the computer system.

Abstract: A computer-implemented system, method and computer program product for detecting fraud. The system and method receives data representing transacting parties where a party transacts with another party to define a relationship therebetween. The received data is incorporated into a relationship network graph comprising nodes that capture data about transacting parties and corresponding information associated with each transaction. A risk model is run that is configured to determine a risk weight for the relation between nodes associated with the transacting parties based on the data captured in the relationship network graph. Then there is determined a degree of a party's association score based on risk scores of nodes associated with the party and a defined relationship with another suspicious party. The system then dynamically updates the risk weight of the relation based on the party's association score.

Abstract: A computer-implemented method to generate a hotspot confidence score for a hotspot in a network graph includes, receiving input data, wherein the input data includes a plurality of messages, each message containing a set of message data. The method further includes generating, based on the plurality of messages, a network graph. The method also includes identifying, in the network graph, a first hotspot. The method includes compiling a set of hotspot characteristics for the first hotspot. The method further includes receiving, in response to identifying the first hotspot, a first user feedback. The method also includes, generating, by a learning model, a hotspot confidence score for the first hotspot; and outputting the hotspot confidence score.

Abstract: In an approach for detecting non-obvious relationships between entities from visual data sources, a processor calculates a co-occurrence frequency score for an entity pair from visual data. A processor calculates a distance proximity score for the entity pair from the visual data. A processor determines an event type in the visual data. A processor determines a timeline relationship in the visual data. A processor calculates a relationship score based on the co-occurrence frequency score, the distance proximity score, the event type, and the timeline relationship. A processor detects a relationship between the entity pair based on the relationship score.

Abstract: Novel tools and techniques are provided for implementing an imaging discovery utility for augmenting clinical image management. In some embodiments, in response to receiving a request for a first medical image file(s) from a requesting device, a non-relational (“NoSQL”) data management system (“DMS”) may access a NoSQL database containing, inter alia, a plurality of medical image files that are mirrored copies of a plurality of medical image files stored in a relational (“SQL”) database, the medical image files each being organized in an image-centric hierarchy with image data being at a top level and patient information associated with the image data being at a lower level. Based on a successful search of the NoSQL database based on search terms in the request, the NoSQL DMS may identify a corresponding second medical image(s) in the SQL database, and may retrieve and send (to the requesting device) the identified second medical image(s).

Abstract: Aspects of the present disclosure relate to identifying and quantifying relationships between entities. Data sources can be queried to receive data regarding a party. Entities can be extracted from the data to receive a set of entities, wherein the party is a first entity of the set of entities. An ontological structure can be built that interrelates entities within the set of entities. An initial relationship strength can be determined between the first entity and a second entity based on co-occurrence between the first and second entities, wherein the second entity is a second party. A relationship score can be calculated between the first and second entities based on the initial relationship strength and at least one additional factor.