Abstract: A tunable nonvolatile resistive element, wherein the device conductance is modulated by changing the length of a contact between a phase change material and a resistive liner. By choosing the contact length to be less than the transfer length a linear modulation of the conductance is obtained.

Abstract: An electronic structure includes a first substrate having a first under bump metallization (UBM) region and a second UBM region formed thereon. One or more solder bumps is deposited onto the first UBM region. A downstop formed on the second UBM region is wider, shallower and more rigid than any one of the solder bumps formed on the first UBM region. A second substrate is joined to the first substrate by the one or more solder bumps located on the first UBM region, and a height of the downstop limits a distance between at least one of the first substrate and the second substrate, or between an object and at least one of the first substrate and the second substrate.

Abstract: A stored energy discharge apparatus for discharging electrical charge from a first component prior to being installed into a second component. The apparatus includes at least one mounting component adapted to a desired voltage potential used in the second component, and at least one discharge component adapted to receive the first component and discharge electrical charge from the first component to the second component through the at least one mounting component prior to the first component being installed in the second component.

Abstract: An integrated circuit includes a field effect transistor (FET) and a phase change memory (PCM) cell. The PCM cell includes a heater, wherein a bottom surface of the heater is at or below a top surface of the FET.

Abstract: Embodiments of present invention provide a ferroelectric random-access memory (FeRAM) cell. The FeRAM cell includes a vertical channel between a bottom source/drain region and a top source/drain region; a gate oxide surrounding the vertical channel; and a ferroelectric layer surrounding the gate oxide, wherein the ferroelectric layer has two or more sections of different horizontal thicknesses between the bottom source/drain region and the top source/drain region. A method of manufacturing the FeRAM cell is also provided.

Abstract: A computer-implemented method, a computer program product, and a computer system for reflecting metadata annotated in crawled documents to original data sources. In response to one or more internal documents in an application being annotated with metadata, the computer system converts a metadata format handled in the application to a metadata format handled in one or more data sources. The computer system posts, to one or more original documents in the one or more data sources, the metadata in the metadata format handled in the one or more data sources.

Abstract: System and method herein interpret results of a semantic clustering Structured Query Language (SQL) Cognitive Intelligence (CI) query by identifying dominant traits of a query input to determine a ranking of query results by identifying influential tokens of the query input based on data statistics and observing the dominant traits in influential tokens of a query output, wherein the identifying the dominant traits of the query input comprises incorporating co-occurrence measurements.

Abstract: A system comprises a superconducting quantizing inductor and superconducting control circuitry, which is coupled to the superconducting quantizing inductor to form a superconducting loop, and which is configured to selectively inject a quantized amount of positive or negative current into the superconducting loop to generate a quantized circulating current in the superconducting loop. The quantized circulating current comprises a time-varying or static circulating current. The superconducting control circuitry comprises first and second current generator circuits which comprise a first and second plurality of Josephson junctions, respectively, which are configured to inject quantized amounts of positive current and negative current into the superconducting loop in response to single flux quantum pulses.

Abstract: An apparatus used for analysis of a fluid-based system that includes a main chamber consisting of an optically transparent high strength material that ensures transmission of infrared and ultraviolet wavelengths and is capable of withstanding high pressures. The apparatus also includes first and second fluid tight endcaps attached to first and second ends of the main chamber, wherein the first endcap permits entry of a fluid into the main chamber and the second endcap permits the fluid to exit the main chamber. The apparatus further includes a fixed filter guide rail located inside the main chamber and attached to one of the end caps, and a filter located inside the main chamber and configured to removably attach to the fixed filter guide rail, wherein the filter is capable of capturing residue or contaminants in the fluid.

Abstract: According to one embodiment of the present invention, a computer-implemented method for autocorrelation based security monitoring and detection is disclosed. The computer-implemented method includes determining that input signal data transmitted to a white noise generator autocorrelates with itself at one or more time lags. The computer-implemented method further includes, responsive to determining that the input signal data transmitted to the white noise generator autocorrelates with itself at one or more time lags, determining whether an autocorrelation in the input signal data transmitted to the white noise generator matches one or more predetermined input signal data patterns associated with a known event or individual.

Abstract: An approach to harvesting electrical energy from a user blinking is disclosed. The approach uses an apparatus that includes a piezoelectric film attaching to a user's eyelid, a wire connecting the piezoelectric film to an electronic component; and an antenna surrounding an eye of the user connecting to the electronic component. The approach includes harvesting electrical energy from a user blinking with the piezoelectric film and the antenna wirelessly transmitting the electrical energy to smart contact lens worn by the user.

Abstract: In an approach to meeting summarization for disconnected participants, one or more computer processors detect a start of a collaborative meeting. One or more computer processors monitor a connection to the collaborative meeting of each of one or more participants. One or more computer processors determine a first participant of the one or more participants has disconnected from the collaborative meeting. One or more computer processors record the collaborative meeting. One or more computer processors determine the first participant has re-connected with the collaborative meeting. One or more computer processors synthesize, a first summary of a portion of the collaborative meeting missed by the first participant. One or more computer processors to synthesize, a second summary of a portion of the collaborative meeting recorded after the first participant re-connected with the collaborative meeting. One or more computer processors present the first summary and the second summary to the first participant.

Abstract: Mechanisms are provided for processing a sequential database natural language query. A process model is preprocessed to generate mapping data structure(s). The mapping data structure(s) map elements of the sequential process to other elements of the sequential process to thereby identify sequential and dependent characteristics of the sequential process. A sequential database natural language (SDNL) query interpretation engine is configured with the mapping data structure(s) and natural language processing is performed on a query to generate extracted features. The configured SDNL query interpretation engine operates on the extracted features and the mapping data structure(s) to generate intent information for the query. Executable database queries are generated based on the intent and executed on a database to return a response to the query.

Abstract: Techniques for verifying the identity of users transferring between devices are disclosed. An example method includes receiving device usage data by monitoring user-device interactions of a first set of users interacting with a first device and a second set of users interacting with a second device. The method also includes extracting features from the data and aggregating feature samples from the user-device interactions for first set of users and the second set of users. The method also includes generating a score for each feature based on an analysis the feature samples. The feature score indicates a degree to which the first set of feature samples and the second set of feature samples differentiate between the devices. The method also includes identifying features as transferrable if the score is below a specified threshold, and generating a new behavior model by modifying existing user behavior data according to the transferrable features.

Abstract: An example operation may include one or more of receiving a request to modify a reliability value of an off-chain data source to generate a modified reliability value, determining whether a consensus on the modified reliability value has been received among a plurality of peer nodes, and in response to a determination that the consensus has been received, updating a storage to reflect the modified reliability value associated with the off-chain data source, and storing an identification of the modified reliability value within a block among a hash-linked chain of blocks on a distributed ledger shared among the plurality of peer nodes.

Abstract: A method, system and apparatus for provisioning a computation into a trusted execution environment, including verifying the trusted execution environment, generating integrity information of the computation, generating sealed data, sending information of the computation, the sealed data, and integrity information to the trusted execution environment, confirming the sealed data, and verifying integrity of the computation information from the integrity information and the computation information.

Abstract: Embodiments are directed to elliptic curve cryptography scalar multiplications in a generic field with heavy pipelining between field operations. A bit width is determined of operands in data to be processed by a modular hardware block. It is checked whether the bit width of the operands matches a fixed bit width of the modular hardware block. In response to there being a match, the modular hardware block processes the operands. In response to there being a mismatch, the operands are modified to be accommodated by the fixed bit width of the modular hardware block.

Abstract: Techniques for using stark tone pulses to mitigate cross-resonance collision in qubits are presented. A tone management component can control application of pulses to qubits by a tone generator component to mitigate undesirable frequency collisions between qubits. The tone generator component (TGC) can apply an off-resonant tone pulse to a qubit during a gate to induce a stark shift. TGC can apply a cross-resonance tone pulse to a control qubit at a frequency associated with the qubit, wherein the frequency can be stark shifted based on the off-resonant tone pulse. The qubit can be a target qubit, the control qubit itself, or a spectator qubit that can be coupled to the target qubit or the control qubit. The gate can be a cross-resonance gate, a two-qubit gate, or a measurement gate that can utilize an echo sequence, a target rotary, or active cancellation.

Abstract: An example operation may include one or more of receiving, via a user interface, a feature set, querying a repository of application programming interfaces (APIs) to identify an API in the repository that corresponds to the received feature set based on a comparison of features in the feature set to features of the API stored in the repository, identifying criteria of the identified API that is published in the repository, and displaying a recommendation with the identified API including the identified criteria of the identified API via the user interface.

Abstract: An instruction that includes an operation code indicating a diagnose operation is obtained and executed within a computing environment. The executing the instruction includes retrieving selected data from a dump save area to be used to restore machine state and restoring the machine state. The restoring includes storing the selected data in a selected location. One or more storage keys used to protect access to the selected data are restored.

Abstract: Embodiments of the present disclosure are directed to an efficient and uniform process for generating multiple outputs for different generated test cases for an input request that share a common section in a pseudo-random software system. An enhanced disclosed method comprises processing an input request and a sequence of instructions until a state or condition of interest is reached in a first process. The condition of interest is marked as a split point in the first process. At the split point, a next process for generating multiple outputs is created to include a common section of the first process from the input request to the split point, an added form of randomization, and at least one instruction after the split point. The common section is generated only once in the first process, which can provide significantly enhanced performance.

Abstract: A method, including: identifying static application features of an application; identifying resource access features of the application; labeling a translation lookaside buffer (TLB) miss threshold of a runtime feature of the application; determining utilization of larger pages during the runtime based on the TLB miss threshold; and setting the TLB miss threshold based on the determined utilization of the larger pages.

Abstract: An example operation may include one or more of detecting, by a blockchain (BC) node, a contract update on a blockchain, determining, by the BC node, at least one charge affected by the contract update, executing, by the BC node, a smart contract to re-generate an invoice based on the at least one charge, and recording the invoice on a ledger of the blockchain.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include generating a content page and selecting an annotation container for the content page. The operations may include configuring the annotation container and inputting content into the annotation container. The operations may include submitting at least one attribute to the annotation container to associate the attribute with the content. The operations may include including the content and the at least one attribute in container data and extracting a model from the container data. The operations may include importing the model into a dialog skill and embedding the dialog skill into a user interface.

Abstract: In an approach for smart test data workload generation, a processor receives a plurality of expected image frames for a user interface application to be tested. The plurality of expected image frames is pre-defined and represents a series of workflows and operations of the user interface application to be expected based on a design requirement. A processor calculates a first set of hash-values for each corresponding expected image frame. A processor samples the user interface application with a frequency to a plurality of testing image frames during a test run on the user interface application. A processor calculates a second set of hash-values for each sampled testing image frame. A processor compares the first set of hash-values to the second set of hash-values. A processor verifies that the second set of hash-values matches the first set of hash-values.

Abstract: Provided are computer program product, system, and method for using a machine learning module to determine a group of execution paths of program code and a computational resource allocation to use to execute the group of execution paths. Information on activity steps in program code and a system load of a system in which the program code is executed are provided as inputs to a resource allocation machine learning module. The resource allocation machine learning module processes the provided inputs to output computational resource allocations for execution paths of activity steps in the program code to execute in parallel, including memory and processing resource allocations optimized according to an optimization criteria. The outputted computational resource allocations are allocated to execute the activity steps in the execution paths in parallel.

Abstract: An example operation may include one or more of connecting, by a migration server, to a legacy system configured to store legacy data, identifying, by the migration server, artifacts of the legacy system subject to a migration to a blockchain, generating, by the migration server, transactions that correspond to the artifacts of the legacy system, mapping the artifacts of the legacy system to artifacts of the blockchain based on the transactions, and executing, by the migration server, a smart contract to migrate the legacy data corresponding to the mapped artifacts into the blockchain.

Abstract: Mechanisms are provided for generating electronic data interchange mapping source code. A source code generator, comprising a machine learning trained neural network computer model, receives input data comprising a source document data structure in a first format and a destination document data structure in a second format, different from the first format. The source code generator processes the input data to generate a source code sequence output vector. A source code is generated that maps contents of source documents in the first format to contents of destination documents in the second format based on the source code sequence output vector. The source code is output to a computing device for execution on other source documents that utilize the first format to thereby automatically generate corresponding destination documents in the second format.

Abstract: A relational database migration process is provided which includes migrating a relational database of a source relational database management system to a target relational database of a target relational database management system. The migrating includes identifying user-defined data objects of the relational database in the source relational database management system and generating statements to recreate the identified user-defined data objects of the source relational database in the target relational database management system. In addition, the migrating includes initiating execution of the statements to recreate the user-defined data objects of the relational database in the target relational database management system.

Abstract: Methods, systems, and computer program products for localization-based test generation for individual fairness testing of AI models are provided herein. A computer-implemented method includes obtaining at least one artificial intelligence model and training data related to the at least one artificial intelligence model; identifying one or more boundary regions associated with the at least one artificial intelligence model based at least in part on results of processing at least a portion of the training data using the at least one artificial model; generating, in accordance with at least one of the one or more identified boundary regions, one or more synthetic data points for inclusion with the training data; and executing one or more fairness tests on the at least one artificial intelligence model using at least a portion of the one or more generated synthetic data points and at least a portion of the training data.

Abstract: One or more computer processors determine a runtime feature set for a first container, wherein the runtime feature set includes aggregated temporally collocated container behavior. The one or more computer processors cluster the first container with one or more peer containers or peer pods based on a shared container purpose, similar container behaviors, and similar container file structure. The one or more computer processors determine an additional runtime feature set for each peer container. The one or more computer processors calculate a variance between the first container and each peer container. The one or more computer processors, responsive to the calculated variance exceeding a variance threshold, identify the first container as anomalous.

Abstract: Mechanisms for performing intelligent federated machine learning (ML) model updates are provided. A plurality of ML model updates, and a plurality of dataset sketch commitment data structures (sketches), are received from a plurality of participant computing systems. Each sketch provides statistical characteristics of a corresponding local dataset used by a corresponding participant to train a local ML model. A potentially malicious participant identification operation is performed based on an analysis of the plurality of sketches to identify one or more potentially malicious participants based on differences in sketches. ML model updates received from participant computing systems identified as potentially malicious participants are discarded to thereby generate a modified set of updates. The federated ML computer model is updated based on the modified set of updates.

Abstract: Embodiments are disclosed for a method for a security model. The method includes identifying a plurality of primary semantic relationships between a plurality of initial incident artifacts for a security domain based on a plurality of historical incidents. The method further includes identifying a plurality of parsed incident artifacts from a security encyclopedia based on the initial incident artifacts. Additionally, the method includes determining a plurality of secondary semantic relationships between the parsed incident artifacts based on a natural language processing of the security encyclopedia. Also, the method includes determining a plurality of influence directions corresponding to the secondary semantic relationships based on the secondary semantic relationships and the historical incidents.

Abstract: An approach for training a recurrent neural network to create a model for anomaly detection in the topology of a network is disclosed. The approach comprises, creating an embedding vector for each resource in the network based on applying an embedding algorithm to each resource of the network. A feature vector is then created for each change to a resource in the network based on one or more properties of the change. A recurrent neural network can thus be trained with the embedding vectors and the feature vectors to create a model for anomaly detection in the topology of the network.

Abstract: Aspects of the present disclosure relate generally to software development environments and, more particularly, to systems, computer program products, and methods of automating software development, security, and operations (DevSecOps). For example, a computer-implemented method includes receiving, by a processor, a plurality of infrastructure as code files specifying a configuration of a runtime environment for a deployable image of source code in a continuous integration and continuous delivery pipeline for a cloud platform; generating, by the processor, compliance code for at least one file of the plurality of infrastructure as code files; building, by the processor, the deployable image of the source code in the continuous integration and continuous delivery pipeline according to the configuration specified by the plurality of infrastructure as code files and the compliance code; and deploying, by the processor, an instance of the image in the runtime environment.

Abstract: A digital transaction ledger with a DNA-related parameter is provided by obtaining DNA-based data unique to a particular entity, and establishing a DNA-related ledger parameter using the DNA-based data. Further, the method includes associating the DNA-based ledger parameter with a digital transaction ledger, making the digital transaction ledger related, at least in part, to the obtained DNA-based data.

Abstract: In an approach to improve converting conversation to user stories, embodiments capture keywords from a captured discussion, and identify the probability of the keywords being an object attribute or action behavior. Further, responsive to identifying, based on the probability, that the keywords are the object attribute or the action behavior, embodiments determine that the object attribute or the action behavior are not new to a first user story. Additionally, embodiments determine that the attribute or the action behavior are associated with an existing object in a first user story, and update the first user story with the attribute or the action behavior.

Abstract: A method, apparatus and computer program for detecting natural language (NL) bias by a conversational system is described. Embodiments of the invention determine an NL bias in a set of training questions used to train a machine learning model used by the conversational system to select a user intent. Other embodiments of the invention determine an NL bias in a user question received by the conversation system as compared to the set of training questions. The NL bias causes the machine learning to preferentially associate user queries to a user intent. In respective embodiments, the system takes a corrective action to adjust the NL bias of the training questions or the user question.

Abstract: A method comprises: installing the target software version on a first node of the storage appliance; restarting the first node of the storage appliance while also running the current software version on other nodes of the storage system; subsequent to said installing the target software version and said restarting of the first node, determining if all hosts of the storage system have discovered paths to volumes on the first node; responsive to determining that all hosts of the storage system have discovered paths to volumes on the first node, permitting the CCU of the nodes to continue to upgrade one of the other nodes of the storage system from the current software version to the target software version; and responsive to determining that not all hosts of the storage system have discovered paths to volumes on the first node, preventing the CCU of the nodes from continuing.

Abstract: A computer-implemented method, a computer program product, and a computer system for log anomaly detection. A computer receives a windowed log of incoming raw log messages. A computer compares statistical distribution metrics of entities in the windowed log with a statistical distribution extracted from a real-time statistical model for the entities. In response to the statistical distribution metrics being statistically different from the statistical distribution extracted from the real-time statistical model for the entities, a computer tags the windowed log as an entity anomaly. A computer computes a distance between an average word embedding vector in the windowed log and a statistical distribution extracted form a real-time statistical model for word embeddings. In response to the distance being greater than a predetermined threshold, a computer tags the windowed log as a word embedding anomaly. A computer sends to a user an alert with an anomaly severity level.

Abstract: The present invention may include a computing device that receives root data, where the root data comprises a plurality of datasets. The computing device determines a context of each dataset within the plurality of datasets. The computing device identifies one or more users based on monitoring behavior of the one or more users related to each dataset. The computing device appends metadata associated with each dataset within the plurality of datasets with the determined context and the one or more identified users and setts access restrictions to each dataset in the metadata based on the context and the one or more identified users.

Abstract: A memory cell in a backside of a wafer and methods of forming the memory cell are described. A buried metal structure can be formed through a frontside of a substrate. At least one device can be formed on the frontside of a substrate, where the at least one device can be connected to the buried metal structure in the substrate. A through silicon via (TSV) can be formed through a backside of the substrate, where the TSV can be connected to the buried metal structure. A memory cell can be formed on the backside of the substrate, where the memory cell can be connected to the TSV.

Abstract: A temperature-aware task scheduling method, system, and computer program product for facilitating a task in a multi-graphical processing unit (GPU) environment, includes executing the task to a GPU in the multi-GPU environment based on a thermal characteristic of the GPU as compared to the other GPUs in the multi-GPU environment.

Abstract: In an approach to provide consistent job descriptions for global entities, computer-implemented methods, computer program products, and computer systems for standardizing global entity job descriptions are described. The computer-implemented method for standardizing global entity job descriptions may include one or more processors configured for receiving first job identifier data corresponding to a job posting having a plurality of job descriptions, generating second job identifier data by removing duplicate job descriptions and outlier job descriptions from the plurality of job descriptions, determining job description intents for the plurality of job descriptions based at least on the second job identifier data, generating third job identifier data corresponding to job description similarity groupings based on the job description intents and the second job identifier data, and generating fourth job identifier data comprising a standard job description based on the third job identifier data.

Abstract: A method performs a Differentiable Point Process (DPP). Generate a first sample sk by sampling from a Poisson process with reference to an upper bound ? of a conditional intensity function representing the DPP given a first set of samples S. Determine whether sk>T, output a second set of samples and train a probabilistic model using when sk>T, and perform the next four steps (generate a second sample, add, add, update) and return to the first step (generate a first sample) when sk?T, where T denotes an observation length. Generate a second sample [ p k r k ] by sampling from a concrete distribution with reference to a parameter of the distribution defined by the conditional intensity function and a temperature ?, given a second set of samples . Add a pair of sk and pk to and discard rk. Add sk to S. Update k to k+1.

Abstract: A method, in accordance with one aspect of the present invention, includes writing, by a tape drive, data tracks to a data band of a magnetic tape having servo bands flanking the data band, the writing being performed using a magnetic head that is not designed for a format of the magnetic tape. An effective pitch of servo readers of the magnetic head used simultaneously during the writing matches a servo reader pitch specification of the format of the magnetic tape. An average effective pitch of write transducers of the magnetic head is greater than a data track pitch specification of the format of the magnetic tape.

Abstract: Described are techniques for predictive microservice activation. The techniques include training a machine learning model using a plurality of sequences of coordinates, where the plurality of sequences of coordinates are respectively based upon a corresponding plurality of series of vectors generated from historical usage data for an application and its associated microservices. The techniques further include inputting a new sequence of coordinates representing a series of application operations to the machine learning model. The techniques further include identifying a predicted microservice for future utilization based on an output vector generated by the machine learning model. The techniques further include activating the predicted microservice prior to the predicted microservice being called by the application.

Abstract: A semiconductor component includes an area of dielectric material extending below an uppermost surface of a substrate. The semiconductor component further includes a trench formed so as to extend from above the uppermost surface of the substrate into the area of dielectric material. The semiconductor component further includes a non-metal liner coating interior surfaces of the trench. The semiconductor component further includes a metal liner coating interior surfaces of the non-metal liner. The semiconductor component further includes a power rail formed in the trench in direct contact with at least one of the metal liner or the non-metal liner such that the power rail extends into the area of dielectric material and above the uppermost surface of the substrate.

Abstract: Fabrication of superconducting devices that combine or separate direct currents and microwave signals is provided. A method can comprise forming a direct current circuit that supports a direct current, a microwave circuit that supports a microwave signal, and a common circuit that supports the direct current and the microwave signal. The method can also comprise operatively coupling a first end of the direct current circuit and a first end of the microwave circuit to a first end of the common circuit. The direct current circuit can comprise a bandstop circuit and the microwave circuit can comprise a capacitor. Alternatively, the direct current circuit can comprise a bandstop circuit and the microwave circuit can comprise a bandpass circuit. Alternatively, the microwave circuit can comprise a capacitor and the direct current circuit can comprise one or more quarter-wavelength transmission lines.

Abstract: Mechanisms are provided for performing machine learning training of a computer model. A perturbation generator generates a modified training data comprising perturbations injected into original training data, where the perturbations cause a data corruption of the original training data. The modified training data is input into a prediction network of the computer model and processing the modified training data through the prediction network to generate a prediction output. Machine learning training is executed of the prediction network based on the prediction output and the original training data to generate a trained prediction network of a trained computer model. The trained computer model is deployed to an artificial intelligence computing system for performance of an inference operation.