Abstract: Using a first dataset of labeled data, a model is trained by adjusting a feature extractor parameter, a classifier parameter, and a discriminator parameter of the model. Using the discriminator parameter and a parametric function of the feature extractor parameter, a plurality of samples of a dataset of unlabeled data is scored. A subset of the scored plurality of samples is selected for labeling. Responsive to receiving a label of each of the selected subset of the scored plurality of samples, the first dataset of labeled data is augmented with the selected subset of the scored plurality of samples and the label of each of the selected subset of the scored plurality of samples. Using the augmented dataset of labeled data, the model is retrained. The retraining comprises further adjusting the feature extractor parameter, the classifier parameter, and the discriminator parameter of the model.

Abstract: An embodiment includes detecting query data associated with a query, where the query data comprises an active feature and a passive attribute used in a machine learning model, and where the machine learning model is trained to output a predicted result based at least in part on the active feature. The embodiment generates, using a first trained neural network, a digital image based at least in part on the passive attribute, and generates, from the machine learning model, outcome narrative data indicative of an explanation of the predicted result and based at least in part on the active feature. The embodiment then generates, using an image generator, a graphical explanation of the predicted result, the graphical explanation being based at least in part on the outcome narrative data and the digital image.

Abstract: A computer-implemented method, system and computer program product for optimizing a flow of data within transform, load (ETL) data processing pipelines. Database columns from a source database that are to be transformed as well as not transformed in the data processing stages of a processing segment of an ETL data processing pipeline are identified. Those database columns that are to be transformed are grouped into a processing schema. Transformations are then performed on the database columns of the processing schema. Those database columns that are not to be transformed are grouped into a non-processing schema. A large object data type (LOB) is then created to reference the non-processing schema. An identifier is created and inserted in the data processing stages to identify the LOB in replace of the database columns that are not to be transformed thereby avoiding the copying of the database columns that are not to be transformed.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can dynamically generate audio for one or more images associated with a location based on contextual information that satisfies a request. Embodiments of the present invention can embed the generated audio into the one or more images. Embodiments of the present invention can then display the one or more images with the embedded audio on a user device.

Abstract: Embodiments for a single user truck loader. A platform is configured to receive placement of a load. Wheels are disposed at locations of the platform. A dolly mechanism is disposed in a cavity formed in the platform. Sidewalls of the platform house the cavity. The cavity of the platform is configured to receive a lift deck of a lifting mechanism.

Abstract: Provided are techniques for mode-specific search query processing. A current search query is received from a user, where the user has a user profile, and where the user profile has a public portion and a private portion. A query mode and a query context for the current search query are determined. In response to determining that the query mode is a guided mode, the current search query is rewritten based on the query context, the private portion of the user profile of the user, and the public portion of each corresponding user profile of each of one or more search influencers to generate a first rewritten search query; the first rewritten search query is executed to generate first search results; and the first search results are returned.

Abstract: Described aspects include a system for optimizing performance of a functional circuit unit, a method of optimizing performance of a functional circuit unit, and a computer program product. In one embodiment, the system may include a functional circuit unit having an associated cooling device and power converter, one or more sensors for the functional circuit unit, the one or more sensors including a power sensor and a temperature sensor, and a first machine learning model. The first machine learning model may be adapted to receive temperature data and power data from the one or more sensors, and to generate control signals for the cooling device and the power converter to optimize performance of the functional circuit unit.

Abstract: An apparatus includes a first plate, a second plate, a third plate, a ferroelectric dielectric, and a paraelectric dielectric. The ferroelectric dielectric is between the first plate and the second plate such that the first plate, the ferroelectric dielectric, and the second plate form a first capacitor. The paraelectric dielectric is between the second plate and the third plate such that the second plate, the paraelectric dielectric, and the third plate form a second capacitor.

Abstract: An information handling system and method for translating virtual addresses to real addresses including a processor for processing data; memory devices for storing the data; and a memory controller configured to control accesses to the memory devices, where the processor is configured, in response to a request to translate a first virtual address to a second physical address, to send from the processor to the memory controller a page directory base and a plurality of memory offsets. The memory controller is configured to: read from the memory devices a first level page directory table using the page directory base and a first level memory offset; combine the first level page directory table with a second level memory offset; and read from the memory devices a second level page directory table using the first level page directory table and the second level memory offset.

Abstract: A computer-implemented method according to one embodiment includes receiving a plurality of linguistic expressions (LEs); changing one or more conditions of the plurality of linguistic expressions to create an updated plurality of linguistic expressions, utilizing a visual exploration framework (VEF) that visually presents to a user each of the plurality of linguistic expressions; and including the updated plurality of linguistic expressions in a model used to classify input sentences. According to another embodiment, a computer-implemented method includes receiving (i) a set of linguistic expressions (LEs) and (ii) a set of labeled data as input, where the LEs are logical combinations of predicates learned from the labeled data, and each data point in the labeled data comprises a piece of text and ground-truth labels; presenting the LEs in a visual exploration framework; and allowing a user to sort, filter, subset, and select LEs based on different criteria, utilizing the framework.

Abstract: A system, method, and computer program product for implementing digital script modification is provided. The method includes generating image sequences associated with textual content of a digital story. Multiple contextual dimensions are identified within the textual content and a group of dimensions are selected. The image sequences in combination with the group of dimensions are expanding or contracted and image sequences are altered based on detected interactions with the group of dimensions. Dimensions are extracted from the group of dimensions during presentation of the digital story and a scriptwriter is enabled to modify the dimensions. The image sequences are modified and a hardware interface device is enabled to interact with various image sequences and alter the multiple contextual dimensions. The textual content of the digital story is dynamically altered.

Abstract: A computer answers a question using a data table. The computer receives a user question and a target table containing a target cell corresponding to a target answer for the user question, with the target cell corresponding to a target column and a target row. The computer generates, a first classifier to provide column correlation values reflecting the probability that a given column is the target column. The computer generates a second classifier that provides row correlation values reflecting the probability that a given row is the target row. The computer applies the first classifier to the target table to determine a column correlation value for each column. The computer applies the second classifier to the target table to determine a row correlation value for each row. The computer suggests, as the target cell, a cell having elevated column and row correlation values relative to other target table cells.

Abstract: An apparatus for thermal interface material detection includes a heat dissipating device stack up that includes a heat dissipating device, a thermal interface material, a heat generating component, and a printed circuit board. The heat dissipating device is disposed on the thermal interface material, the thermal interface material is disposed on the heat generating component, and the heat generating component is disposed on the printed circuit board. A channel in a body of the heat dissipating device includes an embedded conductive probe, where a first end of the embedded conductive probe leads to a lower surface of the body of the heat dissipating device and a second end of the embedded conductive probe leads to an upper surface of the body of the heat dissipating device.

Abstract: A node of the computing environment obtains an exclusive fetch request of a cache line shared by, at least, the node and a manager node of the computing environment. The exclusive fetch request includes a state indication regarding processing of the exclusive fetch request by the manager node. The node processes the exclusive fetch request, based on the state indication included with the exclusive fetch request regarding processing of the exclusive fetch request by the manager node.

Abstract: In an approach for predicting an optimal system upgrade, a processor detects an upgrade is available for a system of a first user computing device. A processor gathers a set of live data from an environment of the first user computing device using a process mining software. A processor compares the set of live data to a set of historical data stored in a knowledge corpus to identify a second user computing device similar to the first user computing device. Responsive to identifying the second user computing device, a processor performs a pattern recognition to generate one or more critical recommendations associated with the upgrade for the system of the first user computing device. A processor schedules the upgrade for the system of the first user computing device during a period of time, wherein the period of time is scheduled consistent with the one or more critical recommendations.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations that include generating a key pair and encrypting a data credential with a public key to make a data credential secret. The operations may further include storing the data credential secret in a cluster on a host and deploying a workload on the cluster. The operations may also include establishing an empty bundle in the host and generating a pod trusted execution environment.

Abstract: An artificial intelligence (AI) interaction method, system, and computer program product include selecting an artificial intelligence model to respond to a query to generating a response to the query using the selected artificial intelligence model, and receiving the response to the query from the selected artificial intelligence model.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate sparse depth completion with semantic mesh deformation optimization in an augmented reality environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a depth completion component that generates a first depth map from an image and sparse depth samples. The computer executable components further comprise a semantic mesh deformation component that performs a semantic mesh deformation process, using the sparse depth samples, to generate a second depth map comprising a defined image accuracy.

Abstract: A method for minimizing data transfer and storage utilization on cloud object storage systems is disclosed. In one embodiment, such a method replicates a file from a production system to a cloud object storage system. The method determines whether a number of hard links associated with the file is greater than one. In the event the number is greater than one, the method creates, on the cloud object storage system, a special object for the file and associates the file with the special object. Upon creating a hard link on the production system in association with the file, the method replicates the hard link from the production system to the cloud object storage system without replicating data associated with the file. A metadata reference to the special object is added to the hard link on the cloud object storage system. A corresponding system and computer program product are also disclosed.

Abstract: Embodiments include in response to monitoring a processor during operation, detecting a first number of throttling amounts in the processor, determining that the first number of throttling amounts fulfills a first condition regarding a throttling amounts threshold, and modifying a voltage level of the processor by a first amount. Embodiments include in response to modifying the voltage level of the processor by the first amount, detecting a second number of throttling amounts in the processor, determining that the second number of throttling amounts fulfills a second condition regarding the throttling amounts threshold, and modifying the voltage level of the processor by a second amount.