Abstract: A method and system for capturing dynamic data from data fields of a product has been developed. The method includes first collecting a product data set with multiple data fields. Static data fields of the product data set are identified that contain pre-defined standardized data for multiple other data sets. Next, dynamic data fields of the data set are identified. A dynamic data field is created by a user and contains additional data that is unique and applicable only to the product data set. The static data fields and the dynamic data fields are stored separately in a database repository for later recovery.

Abstract: Generating and providing a content feed to a user that surfaces information items that are determined to be interesting or relevant to the user including content that is determined to be “distant” to the user is provided. Explicit user actions are used to discover peers who are not colleagues of the user (e.g., peers with whom the user does not share a close organizational relationship, peers with whom the user does not regularly communicate, etc.), but who the user indicates an interest in via his/her actions. These peers are categorized as elevated peers of the user, and information items associated with and trending around the elevated peers are surfaced to the user in a content feed.

Abstract: A method includes receiving a system call from an application within a container executing on an operating system, the system call comprising a synchronization operation to synchronize memory of the application to storage. The method further includes determining, by the kernel, whether a system call filtering policy associated with the container indicates that the system call is to be prevented. preventing, by the kernel, performance of the synchronization operation in view of the system call filtering policy.

Abstract: Methods and systems are provided for providing secure Ethernet transmissions. In some aspects, an autonomous vehicle system is provided and can include a first system-on-chip being configured to provide data to a second system-on-chip via an Ethernet harness, a first switch being configured to: receive the data from the first system-on-chip, and provide the data to a first transceiver for transmission to the second system-on-chip, the first switch being configured to provide first transmission data to the first transceiver and to prohibit receipt of retrieval data from the second system-on-chip, and the first transceiver configured to communicate with the second system-on-chip via the Ethernet harness.

Abstract: Techniques are described with respect to facilitating client ergonomic support. An associated method includes receiving a plurality of posture datapoints associated with multiple clients and constructing a machine learning knowledge model based upon the plurality of posture datapoints in order to identify a plurality of predefined ergonomic support design elements. The method further includes receiving client-specific posture datapoints associated with a first client and analyzing, via the machine learning knowledge model, the client-specific posture datapoints in view of the plurality of posture datapoints in order to select an initial ergonomic support design element among the plurality of predefined ergonomic support design elements. The method further includes facilitate printing of the initial ergonomic support design element for a seat component associated with the first client.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform to implement predict data constraints to validate one or more portions of a dataset, according to at least some examples. For example, a method may include predicting a subset of constraint data to validate a graph-based data arrangement, and analyzing the graph-based data arrangement against a subset of constraint data to determine an action. At least one action may include validating data in a graph-based data arrangement. Also, the method may include integrating graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation.

Abstract: A content explanation method and apparatus applied to content explanation includes identifying, by a content explanation apparatus, an emotion of the user, when identifying a negative emotion showing that the user is confused about delivered multimedia information, obtaining, by the content explanation apparatus, a target representation manner of target content in a target intelligence type, where the target content is content about which the user is confused in the multimedia information delivered to the user by an information delivery apparatus associated with the content explanation apparatus, and presenting, by the content explanation apparatus, the target content to the user in the target representation manner.

Abstract: Example systems and methods enhance user privacy by performing efficient on-device public-private computation on a combination of public and private data, such as, for example, public and private graph data. In particular, the on-device public-private computation framework described herein can enable a device associated with an entity to efficiently compute a combined output that takes into account and is explicitly based upon a combination of data that is associated with the entity and data that is associated with one or more other entities that are private connections of the entity, all without revealing to a centralized computing system a set of locally stored private data that identifies the one or more other entities that are private connections of the entity.

Abstract: Methods and systems comprising a gateway coordinator of a local system that receives a task comprising search criteria, crawls for files on a local data source of the local system, and encounters one or more files of interest. The one or more files of interest may be deNISTed and deduplicated and sent to an upload coordinator of a remote cloud facility. In one or more examples, the gateway coordinator may be a virtual machine.

Abstract: In general, embodiments of the technology relate to a method and system for implementing external content type (ECT) object types in a content management system (CMS). More specifically, embodiments of the technology relate to augmenting the object model with a new class of object type—an external content type (ECT) object type. The ECT object types are a class of object types that are used to manage object (referred to as managed external objects) that are located in external data systems.

Abstract: Implementations set forth herein relate to conditionally caching responses to automated assistant queries according to certain contextual data that may be associated with each automated assistant query. Each query can be identified based on historical interactions between a user and an automated assistant, and—depending on the query, fulfillment data can be cached according to certain contextual data that influences the query response. Depending on how the contextual data changes, a cached response stored at a client device can be discarded and/or replaced with an updated cached response. For example, a query that users commonly ask prior to leaving for work can have a corresponding assistant response that depends on features of an environment of the users. This unique assistant response can be cached, before the users provide the query, to minimize latency that can occur when network or processing bandwidth is unpredictable.

Abstract: Embodiments implement a prediction-driven, rather than a trial-driven, approach to automate database configuration parameter tuning for a database workload. This approach uses machine learning (ML) models to test performance metrics resulting from application of particular database parameters to a database workload, and does not require live trials on the DBMS managing the workload. Specifically, automatic configuration (AC) ML models are trained, using a training corpus that includes information from workloads being run by DBMSs, to predict performance metrics based on workload features and configuration parameter values. The trained AC-ML models predict performance metrics resulting from applying particular configuration parameter values to a given database workload being automatically tuned. Based on correlating changes to configuration parameter values with changes in predicted performance metrics, an optimization algorithm is used to converge to an optimal set of configuration parameters.

Abstract: According to one embodiment, a document search apparatus includes processing circuitry. The processing circuitry acquires an event text relating to an event, acquire a phenomenon expression from the event text, the phenomenon expression indicating a phenomenon of the event, acquires a synonymous expression having a meaning similar to a meaning of the phenomenon expression, and acquires at least one co-occurrence expression co-occurring with an expression selected from among the phenomenon expression and the synonymous expression. The processing circuitry performs search using the selected expression and one of the at least one co-occurrence expression as search terms to acquire a related-event document relating to the event from document information.

Abstract: An exemplary method of generating content for a user of a social networking service includes, in an application of a social networking service, receiving a classification model from a server system associated with the social networking service. The method further includes generating a collage for a user. The collage includes a set of content items stored on the client device. The method also includes, presenting the collage to the user if the collage satisfies a criterion included in the classification model. The method also includes tracking and providing user-interaction data for the collage to the server system, and receiving an updated classification model from the server system in accordance with the user-interaction data. The method also includes generating and presenting a new collage that includes a new set of content items stored on the client device, if the new collage satisfies the criterion included in the updated classification model.

Abstract: A database system includes a master server, a pair of slave servers and a main storage carrier. Each slave server is provided with a database management system (DBMS). The main storage carrier and the pair of slave servers uses the ISCSI protocol to make the pair of slave servers serving as the DBMS and the main storage carrier serving as a database (DB) connect and communicate to further make the DBMS and the DB independent and separate. The master server performs service assignment to the pair of slave servers according to a predetermined weight value. All connections of the database are directed to the slave server with a high weight value, and the other slave server with a low weight value serves as a standby.

Abstract: A software update device is provided with an update control unit that performs a software update using a new software version supplied over a network. The update control unit installs a first new software version on a first electronic control device prior to installing a second new software version on a second electronic control device, and activates the first new software version installed on the first electronic control device either after activation of the second new software version installed on the second electronic control device has started or after it is ascertained that activation of the second new software version installed on the second electronic control device has been normally completed.

Abstract: In entity transition from legacy systems to a big data distributed data platform, numerous system-based architectural gaps have surfaced. There exists a need for a bridge component for each of the architectural gaps in order to support the entity transition to the big data distributed data platform. These bridge components include a variety of frameworks that are configured to automate certain processes that are needed for the transition. These processes have only become necessary as a result of the Hadoop platform. The automated processes include a snapshot load platform. The snapshot load platform enables the addition of a new view to the historical tables. The platform includes replacing the entire table in a truncated scenario. The platform includes replacing cases in a refresh or update scenario.

Abstract: Described are platforms, systems, and methods for real-time enrichment of vertices, edges, and related data within a graph database. The platforms, systems, and methods maintain a graph database comprising a representation of a current state of an automation environment comprising a plurality of data sources, wherein the data sources are represented as vertices in the graph database and relationships between the individual data sources are represented as edges in the graph database; operate a plurality of software agents, each software agent configured to perform operations comprising: applying an algorithm to identify patterns in the graph database; and generating a specific data enrichment based on one or more identified patterns; and contribute the generated data enrichment back to the graph database.

Abstract: An example includes generating panelist-user data based on reference demographic information and self-reported demographic information, the reference demographic information and the self-reported demographic information corresponding to audience members of an audience member entity panel that are also registered users of a database proprietor, the reference demographic information from a panelist database of an audience measurement entity, and the self-reported demographic information from a user database of the database proprietor; generating a first training model and a second training model, the first training model based on a first portion of the panelist-user data, the second training model based on a second portion of the panelist-user data; selecting the first training model based on outputs of the first and second training models; and generating a third model by making an adjustment to a demographic category of the first training model, the third model to adjust third demographic information.

Abstract: A node type of a plurality of distributed nodes to which a table to be added to a distributed database should be assigned can be identified by applying a set of placement rules defined for the table. The set of placement rules can also be applied to determine whether the table should be partitioned into more than one partition. A table group name associated with the table can be obtained and used in conjunction with the node type and determination of whether to partition the table to store the table in the distributed database on at least one node of the plurality of nodes as one or more partitions.