Abstract: An interrupt signal is provided to an operating system executed using one or more processors of a plurality of processors. A bus attachment device receives an interrupt signal with an interrupt target ID identifying a processor assigned for use as a target processor for handling the interrupt signal. The bus attachment device translates the received interrupt target ID to a processor ID using an interrupt table entry and forwards the interrupt signal to the target processor for handling. The processor ID is used to address the target processor directly.

Abstract: Various embodiments are provided for implementing an approximation nearest neighbour (ANN) search in a computing environment are provided. An approximation nearest neighbour (ANN) of a plurality of feature vectors in hyper-planes with dynamically variable subspaces by searching an inverted index may be retrieved.

Abstract: A method can include obtaining, from a video having a first resolution, a set of frames having a second resolution. The first resolution can be higher than the second resolution. The set of frames can include a first frame and a second frame. The method can include generating a difference feature map. The method can include obtaining a third frame having the first resolution. The method can include detecting, based on the difference feature map, a first location of a first object in the third frame. The method can include cropping, from the third frame, a first cropped area. The first cropped area can be smaller than a third frame area. The method can include generating, based on a feature map and the difference feature map, a spatial attention layer. The method can include detecting, by the spatial attention layer, the first object in the first cropped area.

Abstract: In an approach, a processor groups documents into a plurality of groups based on similarity, where: documents of each group have a same document structure; and the document structure is defined by coordinates of text blocks. A processor, for each group of the plurality of groups and for each document of the respective group: retrieves a value of each text block of the respective document in accordance with a document structure of the group; and assigns to each text block of the respective document an attribute that represents the retrieved value of the text block. A processor assigns a first document of the documents to an entity of a database that matches the first document based on the group of text block values and the assigned attributes of the document.

Abstract: A method and a computer program product are used generating an index of a scoring payload dataset. Correlation coefficients for correlations between input data values and output data values of the machine learning model provided by the scoring payload datasets as well as performance data values of the processes provided by process datasets are calculated. Features of which feature values are used as input data values are ranked according to their importance using the correlation coefficients. For the features of a set of highest-ranking features feature value sets with feature values of the respective features are selected from the scoring payload datasets and a database index of the selected feature value sets is generated.

Abstract: An example operation may include one or more of generating a snapshot of a state of a permissioned blockchain, generating a unique identifier of the state snapshot that distinguishes the state snapshot from other state snapshots of the permissioned blockchain, storing the state snapshot in a data store, and storing proof of the state snapshot including the unique identifier and a storage location of the state snapshot on a public blockchain.

Abstract: Building a first layer model of a three-layer model based on attributes that are sensitive features is provided. A first dimension reduction of sensitive features removes each sensitive feature having an indicator that it is present in a patch and does not contribute to one or more of three probabilities. A second dimension reduction of insensitive features is performed using vectorizing and using one-hot encoding. The remaining insensitive features are main features. One or more second layer models of the three-layer model is built based on the main features. The third layer model is built based on a verification dataset and the first layer model. Regression test coverage is recommended based on prediction result of the third layer model, and wherein regression tests are selected. The training dataset is updated based on probability calculations of the first layer model.

Abstract: The disclosed embodiments include a method for performing financial fraud assessment that includes creating a machine learning model based on features used to identify financial fraud risk; receiving financial information associated with customer accounts; establishing communities for the customer accounts; creating a baseline set of the features for each of the communities; receiving new financial information associated with customer accounts; updating the communities for the customer accounts based on the new financial information; extracting an updated set of the features for each of the communities; and determining a difference between the baseline set of the features and the updated set of the features for each of the communities; and using the machine learning model to determine financial fraud risk for each of the communities based on the difference between the baseline set of the features and the updated set of the features for each of the communities.

Abstract: In an approach to improve query optimization in a database management system, embodiments identify opportunities for improvement in a cardinality estimate using a workload feedback process using a query feedback performed during query compilation. Embodiments identify correlations and relationships based on the structure of the query feedback and the runtime feedback performed, and collects data from the execution of a query to identify errors in estimates of the query optimizer. Further, embodiments submit the query feedback and the runtime feedback to a machine learning engine to update a set of models. Additionally, embodiments update a set of models based on the submitted query feedback and runtime feedback, and output a new, updated, or re-trained model based on collected data from the execution of the query to identify the errors in estimates of the query optimizer, the submitted query feedback and the runtime feedback, or a trained generated mode.

Abstract: Embodiments are directed to a method of manufacturing the printed circuit board. The PCB is a multi-layer component, including a dielectric material and an intermediate or second layer adjacently positioned with respect to the dielectric material. The intermediate layer or second layer includes a conductor and fiberglass strands, with the fiberglass strands having an associated orientation. When assembled, the fiberglass and the conductor have a matching orientation and separation distance from a source to a destination.

Abstract: Embodiments for implementing enhanced ensemble model diversity and learning by a processor. One or more data sets may be created by combining one or more clusters of data points of a minority class with selected data points of a majority class. One or more ensemble models may be created from the one or more data sets using a supervised machine learning operation. An occurrence of an event may be predicted using the one or more ensemble models.

Abstract: Operating system deactivation of write protection for a storage block is provided absent quiescing of processors in a multi-processor computing environment. The process includes receiving an address translation protection exception interrupt resulting from an attempted write access by a processor to a storage block, and determining by the operating system whether write protection for the storage block is active. Based on write protection for the storage block not being active, the operating system issues an instruction to clear or modify translation lookaside buffer entries of the processor associated with the storage block, absent waiting for an action by another processor of multiple processors of the computing environment, to facilitate write access to the storage block proceeding at the processor.

Abstract: Prioritizing crawled data in a document store for reprocess operations. Reprocessing occurs upon a triggering change to configurations. Prioritization is based on the status of the crawled data with respect to an ACL. During reprocessing, the crawled data is reprocessed in an order defined by assigned priority levels.

Abstract: A computer-implemented method for providing interpretable predictions from a machine learning model includes receiving a data structure that represents a hierarchical structure of a set of features (X) used by one or more predictive models to generate a set of predictions (Y). An interpretability model is built corresponding to the predictive models, by assigning an interpretability to each prediction Yi based on the hierarchical structure. Assigning the interpretability includes decomposing X into a plurality of partitions Xj using the hierarchical structure, wherein X=U1NXj, N being the number of partitions. Further, each partition is decomposed into a plurality of sub-partitions using the hierarchical structure until atomic sub-partitions are obtained. A score is computed for each partition as a function of the predicted scores of the sub-partitions, wherein the predicted scores represent interactions between the sub-partitions. Further, an interpretation of a prediction is outputted.

Abstract: Computer-implemented methods for optimized compute resource addition and removal in a distributed storage platform. In a case of a newly added compute resource being connected to a storage subsystem shared by compute resources in the distributed storage platform, the distributed storage platform formulates a redistribution plan to redistribute a subset of a global address space of the storage subsystem to a newly added logical volume in the storage subsystem. In a case of a removed compute resource being disconnected from the storage subsystem, the distributed storage platform formulates a redistribution plan to redistribute respective logical blocks in a logical volume for the removed compute resource to respective remaining logical volumes for respective remaining compute resources in the distributed storage platform. The distributed storage platform executes the redistribution plan to reassign data block ownerships on one or more physical memory devices in the storage subsystem.

Abstract: A method, the method comprising retrieving a sound intensity map for a venue, wherein the sound intensity map is divided up into a plurality of regions, wherein the sound intensity map predicts a sound quality for each region during a current event. Receiving data from a plurality of IOT enabled operated aerial vehicles, where each IOT enabled operated aerial vehicle of the plurality of IOT enabled operated aerial vehicles travels around different regions of the plurality of regions, wherein each IOT enabled operated aerial vehicle collects data during the event. Comparing the received data to the sound intensity map to determine the region where an audio component of a venue audio needs to be adjusted. Determining the adjustment required for the audio component and adjusting the audio equipment.

Abstract: A system and method for launching parallel processes on a server configured to process a number of parallel processes. A request is received from a parallel application to start a number of parallel processes. In response to this request a launcher creates a surrogate. The surrogate inherits communications channels from the launcher. The surrogate then executes activities related to the launch of the parallel processes, and then launches the parallel processes. The parallel processes are launched and the surrogate is terminated.

Abstract: Provided is a technique for matching different user representations of a person in a plurality of computer systems may be provided. The technique includes collecting information sets about user representations from a plurality of computer systems; normalizing the information sets to a unified format; grouping the information sets in the unified format into indexing buckets based on a user name using a non-phonetic algorithm; determining a similarity score for each pair of information sets in each of the indexing buckets; classifying each information set pair into a set of classes based on the similarity scores, wherein the set of classes comprise at least matches and non-matches; and using a data structure for merging information of information set pairs classified as matches.

Abstract: A piezo-junction device may be provided. The piezo-junction device comprises a piezoelectric element comprising two electrodes and piezoelectric material in-between, and a semiconductor junction device adjacent to the piezoelectric element such that one of the two electrodes of the piezoelectric element is in contact with the semiconductor junction device connecting the semiconductor junction device and the piezoelectric element electrically in series. Thereby, the semiconductor junction device and the piezoelectric element are together positioned in a fixed mechanical clamp such that the piezoelectric element with an applied electrical field applies strain to the semiconductor junction device causing a change in Fermi levels of the semiconductor junction device.

Abstract: A method, a computer program product, and a computer system identifies a last person of a queue. The method includes receiving an image of the queue where the image includes a plurality of individuals comprising the queue. The method includes determining positions and facing directions of the individuals comprising the queue. The method includes identifying the last person of the queue based on a vector field analysis according to the positions and the facing directions of the individuals comprising the queue. The method includes generating instructions to join the queue based on the identified last person of the queue. The instructions include a modified image indicating the last person of the queue in the image.