Abstract: Embodiments are disclosed for a method. The method includes determining that a thief thread attempted a work steal from a garbage collection (GC) owner queue. Additionally, the method includes determining that a number of tasks in the GC owner queue meets a predetermined threshold. Further, the method includes determining that the GC owner queue comprises a heavy-weight task. The method also includes moving the heavy-weight task to a top position of the GC owner queue.

Abstract: A system, methods and software for administering and managing experiential learning opportunities (ELOs) are disclosed. The system generally includes a database server storing a relational database containing ELO placement data and records and having an interface configured to communicate with a university computer having a student information database thereon, website server, configured to host an ELO website through which users interact with the relational database, and a memory in the website server, storing a content management system (CMS) that comprises modules and a data pool stored in/on storage nodes on the website server. The modules include a forms module for users to enter ELO data and submit ELO requests, ELO proposals, waivers and agreements, and a timelog module to collect and store timelog data and manage the timelog approval process.

Abstract: A system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to perform steps of a method for processing a large file. The system may receive record data comprising a plurality of records having an identification value in a common field having a data format. The system may determine a plurality of focus values based on the data format and create a plurality of virtual processing units based on the plurality of focus values. Each of the plurality of virtual processing units may process a sub-group of the plurality of records that corresponds to the focus value associated with the respective virtual processing unit.

Abstract: The present disclosure provides a method, system, and device for generating and managing archived data. To illustrate, an archive request including an indication of a first set of files is received from an entity device. Archive information is generated based on the first set of files and stored at a first storage location and the first set of files are transmitted to an archival storage location. After the storage at the archival storage location, the archive information is accessed from the first storage location based on a retrieval request from the entity device and a request is transmitted to the archival storage location based on the archive information. The first set of files are received from the archival storage location and stored at a second storage location. A notification is sent to the entity device indicating the first set of files are available at the second storage location.

Abstract: A data processing method includes receiving data from a plurality of sources, generating a knowledge graph, and identifying potentially ambiguous particular nodes. For each of the particular nodes a semantic neighborhood is constructed including the particular node and a plurality of nodes within a particular degree of separation from the particular node, the particular node is omitted from the semantic neighborhood, a plurality of groups of connected nodes are determined in the semantic neighborhood, a plurality of instances of the particular node are defined, a plurality of substitute nodes are generated based on the plurality of instances, and each of the plurality of groups of connected nodes are connected to one of the plurality of substitute nodes to update the knowledge graph. A query is received via a network. Query results are retrieved out of the updated knowledge graph, and the query results are rendered accessible.

Abstract: Systems, methods, and devices for generating a transactional change tracking summary for a database. A method includes executing a transaction on a table of a database, wherein the table includes a micro-partition and the transaction is executed on the micro-partition. The method includes, in response to the transaction being fully executed, generating a change tracking entry comprising an indication of one or modifications made to the table by the transaction. The method includes storing the change tracking entry in a change tracking stream, wherein the change tracking stream includes one or more sequential change tracking entries that each correspond to a different transaction that is fully executed on the table.

Abstract: A system includes: a memory operable to store a predictive model; a first processor communicatively coupled to the memory, the first processor operable to execute the predictive model to perform operations including generating knowledge score metrics based on a set of attributes for individuals included in a specified population, where the knowledge score metrics quantify a prediction of a capability of an individual for performing metadata labeling; a second processor communicatively coupled to the memory and the first processor, the second processor is operable to perform operations including comparing the knowledge score metrics to a specified threshold, and identifying attributes of individuals from a specified population having knowledge score metrics exceeding the specified threshold as attributes of individuals capable of performing metadata labeling.

Abstract: A method for processing video data is performed by a data processing unit (DPU). The method includes obtaining, by the DPU, video data; processing the video data to obtain video data chunks and video processing engine outcomes; generating compliance metadata based on the video data chunks and the video processing engine outcomes; associating the compliance metadata with the video data chunks; and storing the compliance metadata and the video data chunks in appropriate storages based on the compliance metadata.

Abstract: Source namespace and file copying: a namespace service receives request to copy namespace to destination, identifies namespace update for file in namespace, and communicates namespace update for file to destination. An access object service receives request to copy file to destination and identifies group identifier for fingerprints group corresponding to sequential segments in file. The access object service communicates request for fingerprints group to deduplication service associated with group identifier range including group identifier. The deduplication service communicates fingerprints group, retrieved from fingerprint storage, to access object service, which communicates fingerprints group and identifier to destination. The access object service communicates request for file segments, corresponding to fingerprints missing in destination, from destination to deduplication service.

Abstract: In general, the invention relates to a method for performing backup operations. The method includes generating a backup on backup storage system, locking the backup for a retention span, generating a backup archive log image using archive log files for the backup, and locking the backup archive log image for a second retention span.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: A system for detecting errors in task workflows from a real time video feed records. The video feed that shows a plurality of steps being performed to accomplish a plurality of tasks through an automation process system. The system splits the video feed into a plurality of video recordings which are valid breakpoints determined through cognitive Machine Learning Engine, where each video recording shows a single task. For each task from among the plurality of tasks, the system determines whether the task fails and the exact point of failure for that task. If the system determines that the task fails, the system determines a particular step where the task fails. The system flags the particular step as a failed step. The system reports the flagged step for troubleshooting.

Abstract: A host system can be queried to determine whether new data has been received based on a first time interval. After completion of the first time interval, a determination can be made as to whether the new data has been received and whether a portion of the new data was not stored. In response to the portion of the new data not being stored, the host system can be queried to determine whether subsequent data has been received based on a second time interval where the second time interval is different from first time interval.

Abstract: A system for providing context tree based on data model is disclosed. The system comprises an interface, a processor, and a memory. The interface is configured to receive a data model entry point, and to receive one or more context filters. The processor is configured to determine context tree data based on the one or more context filters and the data model entry point from any context tree provider that has appropriate context tree information. The memory is coupled to the processor and is configured to provide the processor with instructions.

Abstract: Various examples are provided related to identification of protected information elements associated with unique entities in data files present in data file collections associated with enterprise IT networks. The unique entities can be associated with one or more entity identifications in one or more data files. Computer-generated identification of entity identifications and protected information elements can be conducted, in part, by at least some human review. Information generated accordingly to the disclosed methodology can be used to generate plans for a time and number of human reviewers needed to review data files. Information generated from the processes herein can be configured as user notifications, reports, dashboards, machine learning for subsequent data file analyses, and notifications of unique entities having protected information elements present in one or more data files.

Abstract: A lock is applied automatically without any user involvement, to each of one or more data objects stored by the data processing system. Each of the one or more locks prevent deletion, by any user, of the one or more data objects within a predetermined time frame. A cloud garbage collector marks the one or more data objects for a) deletion, or b) for lock extension, the garbage collector scheduled to run periodically at a period that is less than the predetermined time frame. The deletion or the lock extension is executed for the one or more data objects, based on marks by the garbage collector. Other embodiments are described and claimed.

Abstract: Embodiments for automatic visualization and explanation of feature learning output for predictive modeling in a computing environment by a processor. A degree of importance score may be assigned to one or more features from a relational database according to the machine learning model. A visualization graph of one or more join paths and the one or more features with the degree of importance score to predict a target variable may be generated.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Methods, systems, and devices for data separation for garbage collection are described. A control component coupled to the memory array may identify a source block for a garbage collection procedure. In some cases, a first set of pages of the source block may be identified as a first type associated with a first access frequency and a second set of pages of the source block ay be identified as a second type associated with a second access frequency. Once the pages are identified as either the first type or the second type, the first set of pages may be transferred to a first destination block, and the second set of pages may be transferred to a second destination block as part of the garbage collection procedure.

Abstract: In a pipeline of operations having a terminating operation and a source operation, a builder is built corresponding to the terminating operation. The builder may also correspond to one or more intermediate operations. A database query is generated corresponding to the builder and is sent to a database or a data source for efficient access to the database.