Abstract: An embodiment associates a virtual-meeting host designation with a first user. During the virtual meeting, the embodiment generates meeting context data that includes user characteristic data and meeting characteristic data. The embodiment uses the meeting context data to generate a predicted end time for the virtual meeting and predicts a meeting run-over condition indicative of the virtual meeting continuing past a scheduled end time by comparing the predicted end time and a scheduled end time. Responsive to predicting the meeting run-over condition, the embodiment uses the user characteristic data to generate a ranked list of other users and renders, as a display to the first user, the ranked list and an indication of the meeting run-over condition. The embodiment receives a selection of a second user as a new host of the virtual meeting and, responsive to receiving the selection, associates the host designation with the second.

Abstract: An embodiment includes configuring a grounding based application (GBA) structure comprising a plurality of layers, where the plurality of layers comprises a first layer and a second layer, the first layer having a first node that receives an input associated with a child node responsive to an input query, and the second layer having a second node that outputs a response to the input query. The embodiment also includes evaluating, using the GBA structure, a logical inference based on the input query, where the evaluating comprises generating a first truth table associated with the first node, where the generating of the first truth table comprises retaining truth values resulting from a downward inference pass on the GBA structure and discarding truth values resulting from an upward inference pass on the GBA structure. The embodiment also includes outputting, responsive to the evaluating, an output truth value representative of the logical inference.

Abstract: An embodiment defines a risk model that generates a risk score for an asset based on a plurality of factors, including a first factor that is a first factor type and a second factor that is a second factor type. The model includes a plurality of associations, including a first association that associates a first factor weight with a specified significance of the first factor, and a second association that associates a second factor weight with a time-based metric of the second factor. The embodiment includes modifying one of the plurality of associations resulting in a modified risk model, and generating, using the modified risk model, a risk score for the asset, the generating including determining the risk score for the asset based at least in part on a first factor weight value of the first factor weight and a second factor weight value of the second factor weight.

Abstract: In one general embodiment, a computer-implemented method includes receiving specification of an amount of drive space in a solid state drive (SSD) to emulate, the specified amount being less than all of the drive space of the SSD. The SSD is formatted such that only a number of blocks that provides the specified amount of drive space are made available, and the other blocks are skipped. The available blocks are distributed substantially evenly across planes of the SSD. A presented amount of drive space of the SSD corresponds to the specified amount of drive space. Parameters of the SSD that are dependent upon capacity are scaled based on the specified amount of drive space relative to an actual amount of drive space of the SSD.

Abstract: A first function of a first microservice and a second function of a second microservice are derived from data of an application using a plurality of microservices. From the first function and the second function, an embodiment determines that the first microservice and the second microservice have above a threshold similarity with each other. An embodiment determines a set of differences between the first microservice and the second microservice. New source code of the application is generated, the new source code utilizing the first microservice instead of the second microservice, the first microservice selected using the set of differences.

Abstract: Leveraging production deployments to accelerate inflight deployments in a computing environment. A component is extracted, which is identified in the production deployment. The identified, extracted component is analyzed to derive a set of data describing the identified, extracted component. A relationship between the data is built. The relationship is used to develop an enterprise-wide methodology that is utilized to accelerate development of an additional, inflight deployment by comparing the additional, inflight deployment against the developed methodology.

Abstract: Optimizing a user experience (UX) through improved efficiency of UX research includes using a processor to identify a candidate object, associated with parameters, for research. A current state of the candidate object is assessed by the processor based on the parameters. This assessment may include performing simulations, performed by the processor, on the candidate object using different combinations of the parameters. Research methods are selected, by the processor, from research method recommendations generated for the candidate object based on key performance indicators (KPIs) determined according to the assessment. Machine learning logic is executed by the processor to evaluate the research methods for the candidate object using a machine learning model, and the candidate object and/or research methods is/are modified by the processor based on output from the machine learning model.

Abstract: A method, system, and computer program product are disclosed. The method includes obtaining a configuration of dipole-line (DL) magnets and selecting a magnetic field vector to be generated. The method also includes determining, based on the configuration, orientations of the DL magnets for generating the magnetic field vector.

Abstract: The automatic computer transfer of data between applications can include detecting a first application is accessed on a device, and a second application is accessed on the device in a predetermined amount of time. It is determined that text typed in the first application matches text from the second application. It is further determined when remaining text from the second application does not match the text typed in the first application. It is further Text from the second application for the first application is suggested based on the determined remaining text from the second application. The suggested text from the second application for the first application is sent to a display to autofill into the first application.

Abstract: Embodiments of the present disclosure describe an approach for database query processing with database clients. According to the approach, a first set of queries are obtained from a plurality of clients in communication with a database server. A second set of queries are generated by normalizing the first set of queries. A set of access paths corresponding to the second set of queries are determined for retrieving data from at least one of the plurality of clients and the database server. Data is retrieved from at least one of the plurality of clients and the database server based on the set of access paths.

Abstract: A method for managing charging resources of a charging system for plug-in electric vehicles (PEVs), the charging system including a central recording center including a tracking database. The method including initiating a charging session to a first PEV based on detecting that the first PEV has been plugged into a charging station. The first PEV is associated with the charging session in the tracking database. The first PEV is associated, in the tracking database, to a first user and a first PEV profile. The first PEV is charged in accordance with information from the first PEV profile. Charging session data is monitored and stored in the tracking database during the charging session. A machine learning model is generated based on collective charging data. Charge completion time of the first PEV is predicted based on the machine learning model.

Abstract: A snapshot request for a selected database is obtained by a computing device of a computing environment. Based on obtaining the snapshot request, a snapshot of the selected database is taken. Based on taking the snapshot, a snapshot identifier is recorded in metadata of the selected database. The snapshot identifier identifies the snapshot request.

Abstract: A computer-implemented method, system and computer program product for generating rules to be utilized by a rule-based system. A parser analyzes a received string of words according to grammatical rules to generate a parse tree. The parse tree may then be reviewed by a user to determine if such a parse tree represents the appropriate syntactic structure of the string of words. If the user believes that the parse tree does not represent the appropriate syntactic structure of the string, then the user, who does not need to possess the expertise of natural language processing, may select the nodes and/or edges of the parse tree in a particular order that corresponds to the correct syntactic structure of the string of words. A grammatical rule is then created for parsing the string of words based on the user selection of nodes and/or edges of the parse tree in a particular order.

Abstract: A method for executing a query on a target database against the most recent source data is disclosed. The method comprises maintaining linked—i.e., at least partially synchronized—databases comprising a source and a target database. The method comprises receiving a direct query against a table in the target database, the query comprising a request for using the most recent source data and requesting by the target database from the source database a status about latest data regarding the table. Upon the status indicating that data in the table do not correspond to the most recent data, the method comprises waiting up to a predefined time period for the most recent data of the table to be synchronized from the source database to the target database, and upon the data of the table not being synchronized within the predefined time period, the method comprises issuing a timeout signal.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate quantum state measurement logic used in a quantum state measurement backend process are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a stage control register component that defines a data processing function corresponding to at least one storage element in at least one stage of a quantum state measurement pipeline.

Abstract: Modifying digital content based on predicted future user behavior is provided. Trends in propagation values corresponding to a layer of nodes in an artificial neural network are identified based on measuring the propagation values at each run of the artificial neural network. The trends in the propagation values are forecasted to generate predicted propagation values at a specified future point in time. The predicted propagation values are applied to the layer of nodes in the artificial neural network. Predicted website analytics values corresponding to a set of website variables of interest for the specified future point in time are generated based on running the artificial neural network with the predicted propagation values. A website corresponding to the set of website variables of interest is modified based on the predicted website analytics values corresponding to the set of website variables of interest for the specified future point in time.

Abstract: Systems and techniques that facilitate measurement aggregation in quantum programs are provided. In various embodiments, a system can comprise an input component that can access a quantum program. In various instances, the system can further comprise an aggregation component that can aggregate quantum measurement instructions that are listed in the quantum program. In various embodiments, the aggregation component can aggregate the quantum measurement instructions by: identifying a first quantum measurement instruction in the quantum program; identifying another quantum instruction in the quantum program that is adjacent to the first quantum measurement instruction; and swapping and/or merging the first quantum measurement instruction with the another quantum instruction based on determining whether the first quantum measurement instruction and the another quantum instruction share qubits and based on determining whether the another quantum instruction is a quantum measurement instruction.

Abstract: An integration flow can be improved with the use of a pattern identified from a pattern library. The identified pattern can include a snippet of nodes which are functionally equivalent to a subset of nodes in the integration flow. The pattern also lists an endpoint capable of performing the snippet of nodes. The integration flow can therefore be updated to cause the endpoint to perform the snippet of nodes.

Abstract: A computer-implemented method, system and computer program product for effectively searching for values in a multi-byte array of elements using an n-byte search instruction. Multiple values to be searched in an N-byte array of elements in a loop are received. The loop is optimized by searching the received search values at the starting address of the N-byte array of elements using the n-byte search instruction. A successful search is performed if the received return address points to an address found in the lowest n-bytes of the N-byte array of elements and an element of the address corresponds to a search value. Otherwise, a subsequent search for the search values at the address of the next element in the N-byte array of elements is performed if there are additional elements in the N-byte array of elements to be searched.

Abstract: Training a predict model with network traffic and data change messages generated by an existing web application running in a production environment. The predict model being is trained to predict data changes resulted from API calls embodied in network traffic. A stream of network traffic of the existing web application is replayed with an upgraded version of the existing web application to generate real data changes. The stream of network traffic is applied to the predict model to generate predicted data change messages. The predicted data change messages are comparing with real data change messages representing the real data changes. One or more existing APIs is identified as being possibly functionally degraded based on any inconsistency of the predicted data change messages with the real data change messages.

Abstract: Mechanisms are provided for performing an automated machine learning (AutoML) operation to configure parameters of a machine learning model. AutoML logic is configured based on an initial parameter sampling configuration for sampling values of parameter(s) of the machine learning (ML) model. An initial AutoML process is executed on the ML model based on a dataset utilizing the initially configured AutoML logic, to generate at least one learned value for the parameter(s) of the ML model. The dataset is analyzed to extract a set of dataset characteristics that define properties of a format and/or a content of the dataset which are stored in association with the at least one learned value as part of a training dataset. A ML prediction model is trained based on the training dataset to predict, for new datasets, corresponding new sampling configuration information based on characteristics of the new datasets.

Abstract: Securely executing instructions of software on a computerized device by accessing a software of a computerized device, wherein the software includes a plurality of instructions and respective reference message authentication codes (MACs), generating a cryptographic key based at least in part on a key derivation function, wherein arguments of the key derivation function are based at least in part on a unique identifier of the computerized device and a value extended from a measurement of a content of the software of an extension mechanism of a platform configuration register of the computerized device, verifying an instruction of the plurality of instructions of the software based at least in part on the cryptographic key and a reference MAC of the respective reference MACs, and in response to verifying the instruction of the plurality of instructions of the software, executing the instruction.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate multireference parallelization of variational quantum computing to achieve high accuracy with short circuit depths. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a trial component that prepares a multireference trial state based on a qubit operator, by applying a unitary circuit operator to a sum of selected initial configurations.

Abstract: A method, computer program product, and a system where a secure interface control configures a hardware security module for exclusive use by a secure guest. The secure interface control (“SC”) obtains a configuration request (via a hypervisor) to configure the hardware security module (HSM), from a given guest of guests managed by the hypervisor. The SC determines if the HSM is already configured to a specific guest of the one or more guests, but based on determining that the HSM is not configured to the and is a secure guest the SC forecloses establishing a configuration of the HSM by limiting accesses by guests to the HSM exclusively to the given guest. The SC logs the given guest into the HSM by utilizing a secret of the given guest. The SC obtains, from the HSM, a session code and retains the session code.

Abstract: Embodiments of present disclosure relate to a method for predicting a performance of a machine learning module (ML-Module). The method may comprise detecting a change in the performance of the ML-Module over a period of time on the basis of labeled input datasets for the ML-Module and detecting a change in a predicted performance of the ML-Module over the period of time computed using the drift module. A value of a first key figure is determined, the value of the first key figure indicating a correlation between the change in the performance of the ML-Module and the change in the predicted performance of the ML-Module. A signal is provided, the signal indicating the value of the first key figure.

Abstract: A method for validation and runtime estimation of a quantum algorithm includes receiving a quantum algorithm and simulating the quantum algorithm, the quantum algorithm forming a set of quantum gates. The method further includes analyzing a first set of parameters of the set of quantum gates and analyzing a second set of parameters of a set of qubits performing the set of quantum gates. The method further includes transforming, in response to determining at least one of the first set of parameters or the second set of parameters meets an acceptability criterion, the quantum algorithm into a second set of quantum gates.

Abstract: The present specification describes a computer-implemented method. According to the method, an object within a range of vision of a user is identified via a capture device on a wearable augmented reality (AR) system worn by the user. A user interaction with an identified object within the range of vision of the user is monitored. A notification related to the identified object is generated and presented on a display device of the wearable AR system.

Abstract: A computer implemented method of preparing process data for use in an artificial intelligence (AI) model includes collecting and storing raw data as episodic data for each episode of a process. An episode data generator assigns an episode identifier each set of episodic data. The raw data per episode is transformed into a standardized episodic data format that is usable by the AI model. Metrics are assigned to the episodic data and the episodic data is aggregated in an episode store. The data in the episode store is used by a feature extraction and learning module to extract and rank features.

Abstract: Provided are techniques for building and using a sparse Time Series Database (TSDB). Time series records are received from a native TSDB, where each of the time series records includes a timestamp and one or more tags. Timeslots are determined for shards for the sparse TSDB based on the timestamp included in each of the time series records. The sparse TSDB is built by creating the shards for the determined timeslots and storing the time series records in the shards, while filling in empty ranges in the shards. A query that specifies at least one of the one or more tags is received. It is determined whether to execute the query against the sparse TSDB, and, in response to a determination to execute the query against the sparse TSDB, the query is executed against the sparse TSDB to generate results that are returned.

Abstract: A computer-implemented method according to one embodiment includes receiving, at a scheduler, a training data instance and a target instance, generating, by the scheduler, an input sequence from the training data instance and the target instance, sending the input sequence from the scheduler to an encoder, mapping, by the encoder, the input sequence to a feature vector, sending the feature vector from the encoder to the scheduler, sending the feature vector from the scheduler to a predictor, and mapping, by the predictor, the feature vector to a class vector to create a label for the target instance.

Abstract: Systems and techniques that facilitate empathetic or emotional query response are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory that can execute the computer executable components stored in memory. The computer executable components can comprise a first machine learning model that generates a first response portion, wherein the first response portion comprises a technical response to the input query, and a second machine learning model that generates a second response portion, wherein the second response portion comprises an empathetic or emotional response to the emotion portion of the input query.

Abstract: A computer-implemented method according to one embodiment includes identifying a natural language query; translating the natural language query into an intermediate representation; converting the intermediate representation into one or more query triples; and performing relation linking between each of the one or more query triples and a plurality of knowledge base triples.

Abstract: A method, computer program product and computer system to track and test custom webpage components is provided. A processor retrieves a production webpage. A processor determines a custom component of the production webpage. A processor retrieves component metadata associated with the custom component. A processor generates a hidden element in the production webpage including the component metadata, wherein the production webpage is configured to make the hidden element visible in response to an event.

Abstract: In an approach to improve integration workflows by automatically generating convergent data mappings for branches in an integration workflow using a computer. A branch schema for each branch is generated, wherein the branch schema represents the union of all the individual node output schemas on the branch. A common output schema for a convergence point is generated, wherein the common output schema represents an intersection of all the branch schemas and generates branch mappings from each branch node to the common output schema.

Abstract: A computer-implemented method, computer program product and computer system to automatically perform file management operations is provided. A processor identifies a plurality of files to monitor. A processor generates tracking attributes for the plurality of files. A processor monitors user interactions with the plurality of files. A processor generates prediction vectors for a plurality of file interactions based on the user interactions with the plurality of files. A processor determines at least one file in the plurality of files with tracking attributes that correlate with at least one prediction vector. A processor performs an operation on the at least one file that corresponds with the at least one prediction vector.

Abstract: Provided are a computer program product, system, and method for using trap cache segments to detect malicious processes. A trap cache segment to the cache for data in the storage and indicated as a trap cache segment. Cache segments are added to the cache having data from the storage that are not indicated as trap cache segments. A memory function call from a process executing in the computer system reads data from a region of a memory device to output the read data to a buffer of the memory device. A determination is made as to whether the region of the memory device includes the trap cache segment. The memory function call is blocked and the process is treated as a potentially malicious process in response to determining that the region includes the trap cache segment.

Abstract: A plurality of containers can be configured for running applications associated to at least one node of a distributed computing environments. The containers of the plurality of containers includes integrated intelligence that provides an in memory state component that detects how container instances are running. A quorum synchronization component of the integrated intelligence can coordinate the activities of the containers. A first container can be initiated for running a first node application. The memory state component can determine if a topology exists in the plurality of containers that is running an existing application matching the first node application. The quorum synchronization component of the integrated intelligence can coordinate running of the first node application with the first container with the existing application.

Abstract: Embodiments are disclosed for a method. The method includes receiving feedback decision rules for multiple predictions by a trained machine learning model. generating a feedback rule set based on the feedback decision rules. The method further includes generating an updated training dataset based on an original training dataset and an updated feedback rule set. The updated feedback rule set resolves one or more conflicts of the feedback rule set, and the updated training dataset is configured to train the machine learning model to move a decision boundary. Generating the updated training dataset includes generating multiple updated training instances by applying one of the feedback decision rules to a training instance of the original training dataset.

Abstract: A computer implemented method determines a placement of an application being added to a network. The method includes determining a logical-physical mapping for the application. Sub-graphs in the logical-physical mapping are identified. A stored application in a catalog of applications previously used in the network is located. The stored application includes one of the sub-graphs in the logical-physical mapping. An experiment is generated, performed by a computing device running a neural network model, using the sub-graphs. The experiment includes inducing a physical node mapping for the sub-graph. A cost function associated with a placement of the application being added to the network to one or more physical nodes in the induced physical node mapping is determined.

Abstract: A tool for tape library hierarchical storage management. The tool determines there is available tape capacity on a tape cartridge mounted to a tape drive to migrate data from a migration queue during recall operations. The tool sends a locate end of data (EOD) command to the tape drive. The tool determines the migration queue is within a longitudinal position (LPOS) range. The tool writes data from the migration queue to the tape cartridge within the LPOS range.

Abstract: Methods that provide dynamic index management for a set of computing storage resources are disclosed herein. One method includes collecting, by a processor, a set of current performance data for a set of storage resources storing data and implementing a set of indexes for the data stored on the set of storage resources based on an optimized performance predicted for the set of storage resources based on the collected set of current performance data and a set of predicted performance data that identifies the set of indexes. Also disclosed herein are apparatus, systems, and computer program products that can include, perform, and/or implement the methods for providing dynamic index management for a set of computing storage resources.

Abstract: A semiconductor structure comprises a semiconductor substrate including a first silicon substrate component having a first crystalline orientation and a second silicon substrate component over the first silicon substrate and having a second crystalline orientation different from the first crystalline orientation. The semiconductor substrate defines a trench extending through the second silicon substrate component and at least partially within the first silicon substrate component. A gallium nitride structure is disposed within the trench of the semiconductor substrate.

Abstract: A phase change memory, a system, and a method to prevent high resistance drift within a phase change memory through a phase change memory cell with three terminals and self-aligned metal contacts. The phase change memory may include a bottom electrode. The phase change memory may also include a heater proximately connected to the bottom electrode. The phase change memory may also include a phase change material proximately connected to the heater. The phase change memory may also include metal proximately connected to at least two sides of the phase change material. The phase change memory may also include three terminals, where a bottom terminal is located at an area proximately connected to the heater and two top terminals are located at areas proximately connected to the metal.

Abstract: A method of manufacturing a semiconductor device is provided. The method includes forming a first recess partially through a substrate from a first side of the substrate, forming a dielectric layer in the first recess, forming a second recess partially through the dielectric layer from the first side of the substrate, and forming a buried power rail (BPR) in the second recess of the dielectric layer. The method also includes thinning the substrate from a second side of the substrate to a level of the dielectric layer, the second side of the substrate being opposite to the first side of the substrate.

Abstract: Data privacy for data associated with traveling in a vehicle that has access to passenger data, vehicle location data, vehicle navigation data, peripheral data; and/or itinerary data. Privacy is achieved by data classification and corresponding data security preferences and/or user selection including end of trip data disposition actions.

Abstract: A top pinned SAF-containing magnetic tunnel junction structure is provided that contains a coupling spacer composed of a paramagnetic hexagonal metal phase material that has a stoichiometric ratio of Me3X or Me2X, wherein Me is a magnetic metal having a magnetic moment and X is a metal that alloys with Me in a hexagonal phase and dilutes the magnetic moment of Me. In embodiments in which a Me3X coupling spacer is present, Me is cobalt, and X is vanadium, niobium, tantalum, molybdenum or tungsten. In embodiments in which a Me2X coupling spacer is present, Me is iron and X is tantalum or tungsten. The coupling spacer is formed by providing a material stack including at least a precursor paramagnetic hexagonal metal phase material forming multilayered structure that includes alternating layers of magnetic metal, Me, and metal, X, and then thermally soaking the material stack.

Abstract: According to one embodiment, a method, computer system, and computer program product for intrusion movement prediction is provided. The embodiment may include receiving environmental sensor data corresponding to a monitored space as captured by a plurality of sensors affixed to an airflow component. The embodiment may also include generating a three-dimensional model of the monitored space using the received environmental data. The method may further include, in response to determining a disturbance is present in the three-dimensional model, performing a security action.

Abstract: Systems and techniques that facilitate trimmable inductors for qubit frequency tuning are provided. In various embodiments, a device can comprise a Josephson junction. In various aspects, the Josephson junction can be shunted by a capacitor, and a trimmable inductor can couple the Josephson junction to a pad of the capacitor. In various cases, the trimmable inductor can comprise a first conductive path that includes a severable and/or weldable superconducting bridge and a second conductive path that is in parallel with the first conductive path. In various aspects, severing and/or welding the severable and/or weldable superconducting bridge can controllably change an inductance of the trimmable inductor, which can commensurately change a resonant frequency of a qubit formed by the Josephson junction and the capacitor.

Abstract: The present invention may include a processor that monitors location of a robot in an environment. The processor captures the environment with one or more environment sensors. The processor analyzes the captured environment to determine an exit location. The processor validates an exit route based on historical data and the exit location and communicates the exit route to the robot.

Abstract: A method, system, and computer program product to protect accelerators from malicious network functions. One embodiment of the method may comprise categorizing an application runtime into a plurality of operational phases, and enforcing one of a plurality of phase-specific security restrictions at each of the plurality of operational phases. The method may further comprise analyzing the application runtime to automatically generate the plurality of phase-specific security restrictions.