Abstract: A method for storing metadata and a configuration schema for each of a plurality of capabilities, and storing a plurality of catalogs, each catalog identifying the metadata and configuration schema associated with at least one of the plurality of capabilities. The method also includes receiving a request for implementation of one of the plurality of capabilities on a pluggable system, and associating, by a lifecycle manager and based on a catalog of the plurality of catalogs related to the request, the metadata and configuration schema related to the requested one of the plurality of capabilities with a domain specific capabilities controller compatible with the pluggable system.

Abstract: By analyzing first configuration data of a set of sensors, a first configuration of the set of sensors is measured. A set of permutations of the first configuration is generated. For each permutation in the set of permutations, a corresponding set of virtual sensor data is generated. Using an analysis on each set of virtual sensor data and a set of real sensor data obtained using the first configuration, a corresponding analysis result is caused to be determined. Using the quality measure, a configuration producing a highest quality analysis result is determined. A contextual situation and the configuration are stored as a sensor configuration rule. By analyzing second configuration data of the set of sensors, a second configuration of the set of sensors is measured. The second configuration is adjusted according to the configuration specified in the sensor configuration rule.

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: One or more systems, devices, or methods of use provided herein relate to a process of long-range coupling qubits in a quantum computing device with energy loss protection. A system can comprise a first transmon coupler capable of selectively coupling a first tunable coupler qubit to a first fluxonium qubit; a second transmon coupler capable of selectively coupling a second tunable coupler qubit to a second fluxonium qubit. Additionally, in one or more embodiments, the system can include a long-range coupler capable of selectively coupling the first fluxonium qubit to the second fluxonium qubit. The first transmon coupler can be coupled to a first B mode of the first tunable coupler qubit, and the second transmon coupler can be coupled to a second B mode of the second tunable coupler qubit.

Abstract: A computer-implemented method for automatically pairing two devices is disclosed. The computer-implemented method includes detecting a first type of movement from a first device. The computer-implemented method further includes determining that the first device is located within a threshold distance of a second device when the first type of movement from the first device is detected. The computer-implemented method further includes determining whether an auto-pairing policy matches the first type of movement from the first device and the threshold distance between the first and second devices. The computer-implemented method further includes, responsive to determining that the auto-pairing policy matches the first type of movement from the first device and the threshold distance between the first and second devices, automatically pairing the first device and the second device.

Abstract: One or more systems, devices, and/or methods provided herein relate to a process for in-process radio frequency (RF) signal quality analysis and amplitude adjustment of one or more RF devices. In one or more embodiments, the RF device can comprise a portion of a quantum computing system, such as of readout electronics thereof, and thus amplitude adjustment can be at a waveform generator that generates pulses to affect one or more qubits of a quantum logic circuit of the quantum computing system. Generally, an electronic device can comprise an RF tap connected to an RF signal component of a first RF signal chain, and an analysis component connected to the RF tap, the analysis component configured to convert an RF signal from the RF signal component and to compare a conversion result thereof to an expected power output that is based on historical data for a second RF signal chain.

Abstract: Configurable sensor units and sensor apparatus are provided. A configurable sensor unit comprises a sensor device for generating an electrical signal, dependent on a stimulus sensed by the device, in a circuit, and a programmable non-volatile memory element operable in the circuit as a load resistor for the sensor device, whereby resistance of the load resistor depends on a programmed state of the memory element. The sensor unit has an output for providing an output signal dependent on the aforementioned electrical signal and programmed state. Sensor apparatus may comprise a plurality of these configurable sensor units. Such sensor apparatus may be configured to perform in-sensor compute operations for neural network architectures. Further sensor apparatus comprises a configurable sensor unit and a controller for programming the memory element of the sensor unit to a programmed state dependent on an operating requirement for the sensor unit.

Abstract: A mechanism is provided in a data processing system for displaying cyber threat data in a narrative format. The mechanism receives a cyber threat information file that comprises cyber threat data in a serialized format. The mechanism generates a tree data structure representing relationships between objects in the cyber threat data and generates a user interface presenting the cyber threat data in a narrative format based on the tree data structure. The mechanism presents the user interface to an analyst.

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: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to data drift detection in an edge device. A system can comprise a memory configured to store computer executable components; and a processor configured to execute the computer executable components stored in the memory, wherein the computer executable components can comprise a verification component that can verify accuracy of a first model and accuracy of a second model to detect data drift associated with an edge device that is deployed without network connectivity; a computation component that can compute at least a first ratio based on the accuracy of the first model and the accuracy of the second model; and an analysis component that can use the at least the first ratio to determine whether performance degradation of at least one of the first model or the second model is a function of the data drift.

Abstract: Embodiments of the invention are directed to data replication in an active-active databases having a source site and a target site. Aspects include creating a subscription activation message in a capture address space, the subscription activation message having a timestamp after a latest committed timestamp of the active-active databases and transmitting the subscription activation message to a subscription activation module of the target site of the active-active databases. Based on a determination that one or more tables associated with the subscription activation message are inactive, aspects also include repairing the one or more tables. Based on a determination that all tables associated with the subscription activation message are active, aspects include initiate replication of the capture address space from the source site to the target site with a timestamp of the latest committed timestamp.

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: A method, a computer program product, and a computer system generate a realtime viewer of content in a user interface for cloud storage environments. The method includes receiving an input selecting a data unit stored with a cloud storage service. The method includes transmitting a sensory representation to a user device. The sensory representation is shown on the user interface of the user device. The sensory representation is generated prior to the input is received. The sensory representation is output to a user utilizing the user device such that the user is capable of ascertaining a content of the data unit without the user requesting the data unit.

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: A stream of tuples is processed by a stream application. The stream application includes a plurality of processing elements that operate on one or more compute nodes, each processing element includes one or more stream operators. One or more databases that are capable of communicating with the stream application are monitored during the processing of the stream of tuples. A potential performance condition of a first database of the one or more databases is detected based on the monitoring. An output adjustment is performed, in response to the potential performance condition.

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: 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: 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: 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: 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.