Abstract: Methods, systems, and computer program products for context-based response generation are provided herein. A method includes: obtaining conversation logs comprising agent responses matched to contexts and a set of designated responses that are not matched to the contexts; replacing at least a portion of the agent responses with the designated responses to form modified conversation logs; training a first model, using the modified conversation logs, to output a designated response in the set for a given context and a second model, using the historical conversation logs, to output one of the agent responses for a given context; identifying one or more new responses based at least in part on the output of the second machine learning model for a particular one of the contexts; and retraining the first machine learning model based at least in part on the one or more new responses.

Abstract: An object-detection system for an automated vehicle includes an object-detector, a receiver, and a controller. The object-detector detects detectable-objects proximate to a host-vehicle. The receiver receives an indication of an object-presence from other-transmitters proximate to the host-vehicle. The controller is in communication with the object-detector and the receiver. The controller is configured to operate the host-vehicle to avoid interference with a hidden-object when the hidden-object is not detected by the object-detector and the object-presence is indicated by at least two instances of the other-transmitters.

Abstract: A system for content sharing and methods for making and using the same. The content sharing system enables a smooth and easy exchange of electronic data.

Abstract: Processing methods may be performed to form an airgap spacer on a semiconductor substrate. The methods may include forming a spacer structure including a first material and a second material different from the first material. The methods may include forming a source/drain structure. The source/drain structure may be offset from the second material of the spacer structure by at least one other material. The methods may also include etching the second material from the spacer structure to form the airgap. The source/drain structure may be unexposed to etchant materials during the etching.

Abstract: A request to retrieve data from a memory device of a memory sub-system can be received from a machine learning (ML) framework executing on a host system, where the data comprises a plurality of logical partitions. A set of parallel I/O threads can be initiated to retrieve the data from the memory device, where each I/O thread of the set of parallel I/O threads retrieves a different portion of the data from a different corresponding logical partition and stores the different portion of the data in a I/O buffer of a set of I/O buffers corresponding to the set of I/O threads in parallel. The different portion of the data can be successively provided from each I/O buffer to the ML framework, where the set of parallel I/O threads is to continually retrieve the data from the memory device until all of the data from the logical partitions has been provided to the ML framework.

Abstract: In order to avoid writing duplicates of blocks of data into a storage platform, any virtual disk within the storage platform may have a de-duplication feature enabled. Or, all virtual disks have this feature enabled. For virtual disks with de-duplication enabled, a unique message digest is calculated for every block of data written to that virtual disk. Upon a write, these message digests are consulted in order to determine if a particular block of data has already been written, if so, it is not written again, and if not, it is written. All de-duplication virtual disks are written to a single system virtual disk within the storage platform. De-duplication occurs over the entire storage platform and over all its virtual disks because all message digests are consulted before a write is performed for any virtual disk. A read for a de-duplication virtual desk reads from the system virtual disk.

Abstract: Systems, methods, and computer-readable storage media for object detection and classification, and particularly produce detection and classification. A system configured according to this disclosure can receiving, at a processor, an image of an item. The system can then perform, across multiple pre-trained neural networks, feature detection on the image, resulting in feature maps of the image. These feature maps can be concatenated and combined, then input into an additional neural network for feature detection on the combined feature map, resulting in tiered neural network features. The system then classifies, via the processor, the item based on the tiered neural network features.

Abstract: A dual-modulated QR code (DMQR code) is in the format of a conventional QR code but uses elongated markers instead of black squares in the code modules. The positions of the markers within the DMQR code represent a nonconfidential primary message, and the orientations of the markers within the modules of the DMQR code represent a confidential secondary message.

Abstract: Some embodiments of the invention provide a method for collecting metric values relating to operations of a set of one or more resources executing on host computers in a datacenter. In some embodiments, the method hierarchically collects and analyzes samples, with a first set of samples collected and analyzed in the data plane, and a second set of samples collected and analyzed in the control plane by aggregating the samples collected in the data plane. In some embodiments, the data plane includes host computers on which sample collecting engines (e.g., service engines) execute, while the control plane includes a set of one or more servers that obtains sample data collected by the host computers, and aggregates and analyzes this data.

Abstract: In some embodiments, apparatuses, systems, and methods are provided herein useful to assessing products. In some embodiments, an enclosure for use in assessing products comprises a housing including a door configured to allow placement of a product within the housing, a product holding surface located within the housing allowing pictures to be taken through the product holding surface and configured to support the product, a first image capture device configured to capture an image of the product from a first perspective, a second image capture device configured to capture an image of the product from a second perspective, and wherein the image of the product from the second perspective is captured through the product holding surface, and a lighting element, wherein the lighting element is located within the housing, and wherein the lighting element is configured to provide lighting within the housing.

Abstract: A device may receive, from a user device, a request to establish a voice call. The device may determine that one of a plurality of endpoints is to be involved in the voice call with the user device. The device may transmit send-only invites to the plurality of endpoints. The device may receive, from a first endpoint of the plurality of endpoints, a receive-only response. The device may transmit a send-receive invite to the first endpoint, wherein the send-receive invite identifies a selected communication protocol as a communication protocol for the voice call. The device may transmit a send-receive acceptance to the user device. The send-receive acceptance may identify the communication protocol for the voice call, and upon the user device receiving the send-receive acceptance, the voice call can be established between the user device and the first endpoint.

Abstract: A method and apparatus for providing Web advertisements to online users is disclosed. A balanced set of negative data points and positive data points is derived from a log of Ad impressions and used to train a classifier. In response to an Ad request signal, a plurality of Ads is retrieved from a database. The Ad request signal indicates a request to provide an Ad for a slot available on a Web page associated with a website. The signal is provided in relation to an access of the Web page by an online user and includes information related to the online user. A choice of an Ad is predicted based on the information related to the online user and the plurality of Ads. The Ad is provided to a Web server to cause display of the Ad on the slot when the Web page is displayed to the online user.

Abstract: A GraphQL server stores schemas for GraphQL APIs in a schema store, the schemas defining operations, types and fields of the APIs. Field resolvers are associated with the fields of the APIs to specify which of the data source is to be used to fulfill an API query request. When an event is detected that makes changes to a schema of any of the data sources, the schema store is accessed and an old field name is automatically replaced with a new field name in both the retrieved schemas and the field resolvers mapped to the retrieved schemas. Responsive to receiving an API request, it is determined whether the request has any field names that do not match the corresponding schema, and if so, the old field name is replaced with the new field name in the request.

Abstract: Provided are systems, methods, and computer-readable medium for a simulation platform that can generate simulated activity data for testing a security monitoring and control system. In various examples, the simulation platform can parse the activity data from a cloud service to generate a template, where each entry in the template describes an action and the fields associated with the action. The simulation platform can further generate a configuration that describes a test scenario. The simulation platform can use the configuration and the template to generate the particular action, including randomizing some or all of the fields of the action. When input into the security monitoring and control system, the system can operate on the simulated activity data in the same way as when the system ingests live activity data.

Abstract: A floorplan modelling method and system. The floorplan modelling method includes receiving 2D images of each corner of an interior space from a camera, generating a corresponding camera position and camera orientation in a 3D coordinate system in the interior space for each 2D image, generating a depth map for each 2D image to estimate depth for each pixel, generating a corresponding edge map for each 2D image, and generating a 3D point cloud for each 2D image using the corresponding depth map and parameters of the camera. The floorplan modelling method includes transforming the 3D point clouds with the corresponding edge map into a 2D space in the 3D coordinate system of the camera, regularizing the 3D point clouds into 2D boundary lines, and generating a 2D plan of the interior space from the boundary lines.

Abstract: Fluidic multiwell bioreactors are provided as a microphysiological platform for in vitro investigation of multi-organ crosstalks for an extended period of time of at least weeks and months. The disclosed platform is featured with one or more improvements over existing bioreactors, including on-board pumping for pneumatically driven fluid flow, a redesigned spillway for self-leveling from source to sink, a non-contact built-in fluid level sensing device, precise control on fluid flow profile and partitioning, and facile reconfigurations such as daisy chaining and multilayer stacking. The platform supports the culture of multiple organs in a microphysiological, interacted systems, suitable for a wide range of biomedical applications including systemic toxicity studies and physiology-based pharmacokinetic and pharmacodynamic predictions. A process to fabricate the disclosed bioreactors is also provided.

Abstract: An ion conductive layer can include a hygroscopic ion conductive material, such as a halide-based material. In an embodiment, the ion conductive layer can include an organic material, ammonium halide, or a combination thereof.

Abstract: Systems and methods for automated code analysis and tagging are disclosed. In one embodiment, a method for automated code analysis and tagging may include: (1) receiving, by a code annotation computer program executed by a computer processor, a training code snippet from a training codebase; (2) parsing, by the code annotation computer program, the training code snippet into a data structure; (3) quantifying, by the code annotation computer program, the data structure, (4) parsing, by the code annotation computer program, a docstring associated with the training code snippet into a plurality of keywords; (5) quantifying, by the code annotation computer program, the plurality of keywords; and (6) training, by the code annotation computer program, a code annotation model based on a similarity between the quantified data structure and a smoothing parameter for a Dirichlet prior smoothing estimate.

Abstract: One or more systems and/or methods for product similarity detection and recommendation are provided. Users may view articles and/or other content that includes images depicting products that may be of interest to the users. These images are processed using image processing functionality such as computer vision to identify the products depicted by the images. A vector embedding model is used to generate product vector representations of the products. Catalog items that are available from a catalog to supplement the articles and other content may be processed to generate catalog item vector representations. When content (an article) with an image depicting a product is to be displayed to the user, similarity between a product vector representation of the product and the catalog item vector representations is determined in order to identify and display catalog items depicting products that are similar to the product depicted by the image in the content.

Abstract: An analytics system identifies interventions for individual samples from a set of samples with a mixture of interventions. Given a causal graph, a set of baseline samples, and a set of samples with interventions, a set of intervention tuples is determined that represents the mixture of interventions for the set of samples with interventions. Each intervention tuple in the set of intervention tuples identifies an intervention and a mixing coefficient representing a percentage of samples with the intervention. An iterative process is used in which a set of intervention tuples is determined for N variables and then lifted to a set of intervention tuples for N+1 variables until all variables from the causal graph have been considered, providing a final set of intervention tuples. The final set of intervention tuples is used to match individual samples from the set of samples with interventions to interventions.