Abstract: A traceability system for a bulk commodity supply chain is provided. The system includes a tracking device, a location determination subsystem, and at least one computing device having at least one processor. The location determination subsystem is configured to determine positional information of the tracking device while placed in a bulk commodity traveling along the bulk commodity supply chain. The processor receives the positional information from the location subsystem, extracts positional values from the positional information, and processes the positional values to identify motion primitives. A modeling tool is applied to the identified motion primitives to produce a positional path of the tracking device, which is output, for example, via a user interface. The positional path represents travel of the bulk commodity along the supply chain.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed. An example apparatus includes interface circuitry to receive an analog signal. The example apparatus also includes sequencer circuitry to: determine whether the apparatus is to operate in a single transfer state or a multiple transfer state; access a configuration from a control register in a plurality of control registers; initiate a conversion of the analog signal to a digital value based on the configuration; and write the digital value to a result register in a plurality of result registers based on the determination.

Abstract: A system described herein may monitor a set of local Key Performance Indicators (“KPIs”) associated with an edge computing device. The local KPIs may not be provided to a central orchestrator that is communicatively coupled to multiple edge computing devices. The system may monitor application KPIs associated applications implemented by the edge computing device, which may be provided to the central orchestrator. The orchestration models may include conditions associated with the set of local KPIs, and orchestration actions to perform with respect to the particular edge computing based on the conditions. The system may perform orchestration actions on the particular edge computing device based on the monitored local KPIs and application KPIs. The central orchestrator may identify that the application KPIs are below a threshold and perform a second set of orchestration actions with respect to the edge computing device, or one or more other edge computing devices.

Abstract: A controller for selectively displaying information from raster charts is disclosed. The controller is configured to: retrieve raster data; assign a different priority level to each of a plurality of types of raster data; cause raster data having a predetermined priority level to be displayed with first augmentation information and prevent from being displayed raster data not having the first predetermined priority level, wherein the first augmentation information comprises database data retrieved from a database and is assigned a first predetermined augmentation information priority level; generate a hidden layer of second augmentation information comprising database data from the database that is correlated to a geographical location of the displayed raster data and assigned a second predetermined augmentation information priority level; and cause the hidden layer of second augmentation information to be displayed over a portion of the displayed raster data when the geographical location is selected.

Abstract: The prediction system of strip chew collects and stores first data and second data as adaptive model construction data. The first data indicates the occurrence or non-occurrence of the strip chew in an object rolling path and the occurrence point of the strip chew. The second data includes information on a preceding rolling path and attribute information on an object strip. The system constructs an adaptive model using the stored adaptive model construction data, and stores the constructed adaptive model as an adapted model. The system collects prediction data similar to the second data. Then, the system inputs the prediction data to the adapted model to predict the occurrence or non-occurrence of the strip chew in the object rolling path and all or some of the occurrence points of the strip chew before the prediction object strip reaches the object rolling path.

Abstract: Technologies are shown for storing data from a data object in a distributed application architecture and reassembling the data object from the stored data. A first set of data from the data object is stored on a distributed file system, and a second set of data from the data object is stored on a blockchain. In response to a request for the data object, a script from the blockchain is executed to generate a reassembled data object by: obtaining, from the blockchain, metadata to reassemble the data object, obtaining the second set of data from the blockchain and the first set of data from the distributed file system, and generating the reassembled data object using the first set of data and the second set of data based on the metadata.

Abstract: In various examples, machine learning of encoding parameter values for a network is performed using a video encoder. Feedback associated with streaming video encoded by a video encoder over a network may be applied to an MLM(s). Using such feedback, the MLM(s) may predict a value(s) of an encoding parameter(s). The video encoder may then use the value to encode subsequent video data for the streaming. By using the video encoder in training, the MLM(s) may learn based on actual encoded parameter values of the video encoder. The MLM(s) may be trained via reinforcement learning based on video encoded by the video encoder. A rewards metric(s) may be used to train the MLM(s) using data generated or applied to the physical network in which the MLM(s) is to be deployed and/or a simulation thereof. Penalty metric(s) (e.g., the quantity of dropped frames) may also be used to train the MLM(s).

Abstract: The present invention may include a computing device that receives root data, where the root data comprises a plurality of datasets. The computing device determines a context of each dataset within the plurality of datasets. The computing device identifies one or more users based on monitoring behavior of the one or more users related to each dataset. The computing device appends metadata associated with each dataset within the plurality of datasets with the determined context and the one or more identified users and setts access restrictions to each dataset in the metadata based on the context and the one or more identified users.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for managing energy use in a vehicle. For instance, the method may include receiving forecasted data from a first external source, receiving real-time data corresponding to at least one weather parameter at a first location at a first time, and continuously determining whether to perform an adjustment to a control parameter of the vehicle by using a machine learning model that is based on the forecasted data for the at least one weather parameter, the real-time data for the at least one weather parameter, a battery condition of the vehicle, and/or an estimated amount of energy consumed by traveling along a first navigation path.

Abstract: A light detection and ranging (LIDAR) system to generate a baseband signal in the time domain from the return signal, where the baseband signal includes frequencies corresponding to LIDAR target ranges; and a signal processing system coupled with the optical processing system to measure energy of the baseband signal in the frequency domain, to compare the energy to an estimate of LIDAR system noise, and to determine a likelihood that an signal peak in the frequency domain indicates a detected target.

Abstract: A user equipment (UE) is configured to deactivate/activate a point-to-multipoint (PTM) link of a multicast radio bearer (MRB). The UE receives, from a base station of a wireless network, a multicast radio bearer (MRB) configuration, wherein the MRB includes configuration of a split MRB including a point to multipoint (PTM) link and a point to point (PTP) link, deactivates or activates the PTM link based on the MRB configuration, reestablishes a radio link control (RLC) associated with the PTM link and recovers a packet data convergence protocol (PDCP).

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving information regarding a customer to onboard to a managed service and determining one or more relevant features from the information regarding the customer, the one or more relevant features correlated with historical onboarding times. The method also includes determining, using a machine learning (ML) model, an expected time to onboard the customer to the managed service based on the one or more relevant features.

Abstract: Disclosed herein are methods, systems, and processes to provide coherency across disjoint caches in clustered environments. It is determined whether a data object is owned by an owner node, where the owner node is one of multiple nodes of a cluster. If the owner node for the data object is identified by the determining, a request is sent to the owner node for the data object. However, if the owner node for the data object is not identified by the determining, selects a node in the cluster is selected as the owner node, and the request for the data object is sent to the owner node.

Abstract: A framework for generating reasons for imaging studies. An extractor, including a reinforcement learning agent, is trained to select one or more relevant sentences from the training histories of present illness. An abstractor is further pre-trained to generate one or more reasons for study from the one or more relevant sentences. An entity linking system is pre-trained using medical text corpora to map one or more mentions in the one or more reasons for study to one or more standardized medical entities for predicting one or more diagnoses. The reinforcement learning agent may then be re-trained using one or more rewards generated by the entity linking system. One or more reasons for study may be generated from a current history of present illness using the trained extractor, abstractor and entity linking system.

Abstract: A method for content-aware type-on-path generation is implemented via a computing system including a processor. The method includes surfacing an image via a graphics GUI of a graphics application and detecting one or more salient objects within the image using a CNN model. The method also includes generating a contour map for each detected salient object and generating a path along the contours of each salient object by applying a defined offset to the corresponding contour map. The method further includes applying input text characters as type-on-path along the generated path based at least on user input received via the graphics GUI.

Abstract: Methods and apparatus to maintain a state of a fluid in a system are disclosed. An example system includes a pump including a primary inlet, a primary outlet, and a secondary inlet, at least one injector including a first inlet, a second inlet, and at least one outlet, a third conduit coupled to a first conduit upstream of the primary inlet and coupled to the at least one injector at the first inlet to deliver the fluid, a fourth conduit coupled to a second conduit downstream of the primary outlet and coupled to the at least one injector at the second inlet to deliver the fluid, and a fifth conduit coupled to the at least one injector at the at least one outlet to receive the fluid and coupled to the pump at the secondary inlet.

Abstract: Rare earth element containing catalysts for dehydrogenating paraffins and the methods of making the catalysts are disclosed. A rare earth modified alumina support in eta-alumina form, theta-alumina form, or combinations thereof is impregnated with chromium-containing solution. The chromium-impregnated support is then subjected to calcination processes. The produced catalyst contains the rare earth element, chromium, and alumina. The crush strength of the produced catalyst is greater than 0.4 daN/mm.

Abstract: Systems and methods for enhancing virality for a content item are disclosed herein. A content item is uploaded to a content sharing platform over a communication network. Feedback on the content item is received from the content sharing platform over the communication network. Based on the feedback, a virality score for the content item is determined and a determination is made as to whether the virality score meets a virality criterion. In response to a determination that the virality score does not meet the virality criterion, a virality enhancement technique is selected from a virality enhancement database, the content item is modified by applying the virality enhancement technique to the content item, and the modified content item is uploaded to the content sharing platform over the communication network.

Abstract: A vehicle lamp assembly includes a light source that emits light, a side marker lamp having a lens, and a frustum reflector that guides light from the light source to the lens of the side marker lamp. A vehicle lighting method includes emitting light from a light source into a frustum reflector, redirecting the light within the frustum reflector, and illuminating a side marker lamp using the light redirected within the frustum reflector.

Abstract: Mechanisms are provided for generating electronic data interchange mapping source code. A source code generator, comprising a machine learning trained neural network computer model, receives input data comprising a source document data structure in a first format and a destination document data structure in a second format, different from the first format. The source code generator processes the input data to generate a source code sequence output vector. A source code is generated that maps contents of source documents in the first format to contents of destination documents in the second format based on the source code sequence output vector. The source code is output to a computing device for execution on other source documents that utilize the first format to thereby automatically generate corresponding destination documents in the second format.