Abstract: A system and method for managing network traffic in a distributed environment. the system including: a plurality of logic modules configured to determine policy data related to bandwidth management and at least one split criteria for a basis for shaping network traffic; a control processor associated with each one of the plurality of logic modules, each control processor configured to determine data associated with each of a plurality of traffic flows at the associated logic module and to coordinate traffic actions over the plurality of logic modules; a packet processor associated with each control processor and configured to determine a traffic action based on each traffic flow and received policy data; and at least two shaper objects configured to receive a split of the traffic flows and enforce the determined traffic action on their respective traffic flow.

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A computer-implemented method, system and computer program product for efficient resource utilization. A workflow of manufacturing a product using various machines at each plant of an organization is created, where the workflow illustrates which machines are utilized to produce the product using one or more raw materials. A production rate for the product at each plant manufacturing the product is predicted based on the workflow. An amount of a raw material required by a first plant to produce the product is determined based on the predicted production rate for the product at the first plant. An amount of the raw material is then routed to the first plant from one or more other plants based on minimizing the system inventory carrying cost and minimizing the system transportation cost if the first plant needs an additional amount of the raw material to realize the predicted production rate for the product.

Abstract: A computer method for identifying product in a distributor's inventory system that fulfills a product request made via a natural language query. the natural language query is received as a product request including multiple words in sequential order. The words are vectorized into word-vectors that are concatenated and used to generate a query embedding. The query embedding is processed utilizing a trained product category classifier that predicts which product category the requested product belongs. Forward and backward sequence vectors are generated from the sequentially ordered words of the query that are concatenated and processed using a trained model specific to the predicted product category. The sequence vectors represent positional relationships between the words of the natural language query. Thereafter, the system identifies product attribute(s) embodied in the natural language query that each correspond to a predetermined key-characteristic of the category.

Abstract: A computer implemented method for identifying substitute products for a target product via a distributor's product management computer system, the method includes: receiving, at a distributor's product management computer system, data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated therewith; processing the received data through a machine-learning-produced algorithm and thereby generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transforming the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm;

Abstract: Techniques for determining a location of a mobile device are provided. An example of a method according to the disclosure includes determining, on the mobile device, beam identification information for one or more radio beams, transmitting, with the mobile device, the beam identification information to a network node, receiving, at the mobile device, positioning reference signal beam information for one or more positioning reference signals, generating, with the mobile device, one or more receive beams based on the positioning reference signal beam information, obtaining, with the mobile device, at least one measurement from at least one of the one or more positioning reference signals, and facilitating location determination of the mobile device at a location-capable device based at least in part on the at least one measurement.

Abstract: Techniques are provided which may be implemented using various methods and/or apparatuses in a mobile device to determine signal measurements on a plurality of frequencies and to provide signal measurements for position calculation on a location server or on the mobile device. Techniques are provided which may be implemented using various methods and/or apparatuses on a mobile device to concurrently scan for signals across two or more frequencies while optimizing sending and/or utilizing signal measurements made at higher frequency bands or signal measurements of signals sent from devices at a shorter range.

Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant.

Abstract: A system and method for improving driver situation awareness prediction using human visual sensory and memory mechanism that includes receiving data associated with a driving scene of a vehicle and an eye gaze of a driver of the vehicle. The system and method also include analyzing the data and extracting features associated with objects located within the driving scene and determining a situational awareness score that is associated with a situational awareness of the driver with respect to each of the objects located within the driving scene. The system and method further include communicating control signals to electronically control at least one system of the vehicle based on the situational awareness score that is associated with each of the objects located within the driving scene.

Abstract: A method, computer systems and program product to import non-compliant container images is provided. A processor receives a non-compliant container image, wherein the container image is not compliant with a target computing environment. A processor extracts a one or more embeddings from the non-compliant container image. A processor compares the one or more embeddings from the non-compliant container image to a plurality of one or more embeddings from an image catalog. A processor identifies a similar image from the image catalog based on the comparison of layer embeddings from the non-compliant container image and the similar image. A processor deploys the similar image in the target computing environment.

Abstract: Techniques are described herein that are capable of performing transfer-learning for structured data with regard to journeys defined by sets of actions. A first deep neural network (DNN) for a first journey is trained using structured data. Weights of nodes in the first DNN are transferred to nodes in a second DNN for a second journey using transfer-learning. An embedding layer replaces a final layer of the first DNN in the second DNN to provide an output with a same number of nodes as a pre-final layer of the first DNN. Weights of the nodes in the embedding layer are initialized based at least on a probability that a new feature of the second journey co-occurs with each feature in the structured data. A softmax function is applied on a final layer of the second DNN to indicate possible next actions of the second journey.

Abstract: A data processing system for machine-learning driven data analysis implements obtaining digital healthcare service provider information associated with one or more digital healthcare service providers and query parameters information from a user searching for digital healthcare service providers that may provide digital healthcare services to employees of the user. The system analyzes query parameter information using a first machine learning model to obtain category information. The system analyzes the category information and the digital health service provider information to predict digital healthcare service providers that provide services that the user may be interested in provided to the employees. These predictions are provided to the user as digital healthcare service recommendations.

Abstract: A louver blade for a louver assembly includes a first section, a second section extending from the first section and including a crest of the louver blade, an extension extending from the second section to form a recess between the extension and the second section, and a protrusion extending from the second section toward the extension and configured to facilitate retention of the particles within the recess. The extension is configured guide particles into the recess in an installed configuration of the louver blade with the louver assembly.

Abstract: Indexing a data corpus to a set of multidimensional points, including: generating a set of points in a multidimensional space; identifying, for each sample in a plurality of samples in a data corpus, a nearest point in the set of points; and generating an index mapping each sample with the nearest point in the set of points.

Abstract: A computer system includes processor hardware configured to execute instructions that include joining at least a portion of multiple call transcription data entries with at least a portion of multiple agent call log data entries according to timestamps associated with the entries to generate a set of joined call data entries, and validating the joined call data entry by determining whether a transcribed entity name matches with entity identifier information associated with the agent call log data entry. The instructions include preprocessing the joined call data entry according to word confidence score data entries associated with the call transcription data entry to generate preprocessed text, performing natural language processing vectorization on the preprocessed text to generate an input vector, and supplying the input vector to an unsupervised machine learning model to assign an output topic classification of the model to the joined call data entry associated with the input vector.

Abstract: In one embodiment, a memory device includes a memory core and input receivers to receive commands and data. The memory device also includes a register to store a value that indicates whether a subset of the input receivers are powered down in response to a control signal. A memory controller transmits commands and data to the memory device. The memory controller also transmits the value to indicate whether a subset of the input receivers of the memory device are powered down in response to the control signal. In addition, in response to a self-fresh command, the memory device defers entry into a self-refresh operation until receipt of the control signal that is received after receiving the self-refresh command.

Abstract: A mobile charging station for transporting and recharging multiple UAVs (unmanned aerial vehicles), typically small UAVs, with the charging station, itself, being in the form of a carrier UAV. By transporting smaller passenger UAVs in, or on, the larger carrier UAV: (i) the smaller UAVs effectively have a longer range because they can be taken part, or even most, of the way to a target destination by riding in, or on, the larger carrier UAV; (ii) the passenger UAVs can have their electrical batteries re-charged; (ii) the passenger UAVs can have their batteries replaced; and/or (iv) the passenger UAVs can have their hydrogen fuel cells recharged with hydrogen (for examples, by replacement of the fuel cell or by pumping hydrogen into the existing fuel cell.

Abstract: This disclosure provides systems, methods, and devices for wireless communication that support reselection procedures for power saving in industrial internet of things (IIoT) operations. In a first aspect, a method of wireless communication includes a user equipment (UE) setting a reselection flag to a no-reselection state either by default or in response to a source cell signal-to-noise ratio (SNR) exceeding a predetermined maximum SNR. The UE can set the flag to the allow-reselection state in response to the target cell SNR range exceeding the source cell SNR range or the source cell SNR being below a predetermined minimum SNR. The UE may then either reselect to the target cell when appropriate or maintain service on the source cell based on the state of the reselection flag. Other aspects and features are also claimed and described.

Abstract: A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.