Abstract: Embodiments for providing single-producer-multiple consumers synchronization and multicast data transfer by a processor are disclosed. Multicast data transfer is synchronized based on an identification tag and a request from each one of a plurality of recipients for the multicast data. The multicast data is transferred to each of the plurality of recipients based on the identification tag, the request from each one of the plurality of recipients, and a list of the plurality of recipients.

Abstract: A system, computer program product, and a computer implemented method are provided for interfacing with a virtual dialog environment to dynamically and optimally collected context for problem diagnosis and resolution. A context model is leveraged to identify context entities, and one or more corresponding context collection mechanisms. The context model is implemented in real-time to facilitate dynamic selection of one or more of the identified context collection mechanisms, which are selectively subject to execution to resolve the problem diagnosis.

Abstract: Learning and correcting errors in text input fields to an artificial intelligence (AI) system includes receiving, by the AI system from a target system, an input text. The AI system executes a text processing operation on the input text by applying at least one transformer from a library of transformers to the input text to generate transformed text. At least one proposed correction to the input text is output by the AI system based on an analysis of the transformed text. Feedback data, associated with the at least one proposed correction, is then received from a user of the target system to iteratively learn, by the AI system, which of the transformers need be applied on future input text to accurately generate future proposed corrections on the future input text.

Abstract: Embodiments for providing an intelligent media data service in a computing environment by a processor. One or more sections of media data are identified and annotated (e.g., tagged) for a user based on a degree of relevancy between a user profile and the media data, wherein the media data include media classification, topic detection, speaker detection and noise detection. The one or more sections of media data are selected for the user based on the tagging of the or more sections.

Abstract: Embodiments are provided for providing predictive computing and data analytics for project management in a computing system by a processor. A lifecycle of each of a plurality of objects may be monitored based on data received from a plurality of data sources. Predictive analytics for project management of each of the plurality of objects may be provide based on monitoring the lifecycle of each of the plurality of objects.

Abstract: Embodiments for providing enhanced data protection for storage systems in a computing environment by a processor. One or more queries received by a storage system may be identified. Approval or denial of transmission of data with the storage system may be regulated in relation to the one or more queries based a queried metadata and a plurality of rules and administrative policies.

Abstract: Controlling compute process access to shared data and compute resources includes, responsive to a compute process determining that access to at least one of shared resources and shared data is necessary to perform a compute task, creating, by the compute process, a ticket file belonging to the compute process in a ticket queue directory. The compute process is allowed to proceed performing the compute task upon determining that the ticket file is first in line in a ticket queue of the ticket queue directory, according to a ticket ordering algorithm independently applied by the compute process. Subsequent to completing the compute task, the compute process removes the ticket from the ticket queue directory.

Abstract: Intelligent classification for product pedigree identification are presented. A transaction agreement request may be received from a user. A revised transaction agreement request may be generated based on one or more user profiles, a multi-party entity feedback loop, one or more constraints relating to the transaction agreement request, and a transaction agreement fulfillment requirements of the entity.

Abstract: Using a digital twin model of a user, a digital twin model of a geographical location, a digital twin model of an event venue located at the geographical location, and a plurality of digital twin models of clothing items, a product recommendation customized to the user and a planned event is generated, the planned event planned to occur at the event venue. A product recommendation depiction is generated, the product recommendation depiction comprising a depiction of the product recommendation being worn by the user at the planned event. An answer to a natural language query regarding the product recommendation depiction is generated.

Abstract: An embodiment includes generating a partition schema for a distributed database based on historical usage data indicative of usage of the distributed database, where the generating of the partition schema comprises determining a partition range of a partition of the partition schema. The embodiment also includes generating a node identifier for the partition using a hash function and a first weight value assigned to the partition. The embodiment also includes monitoring performance data indicative of a performance of the distributed database, the monitoring comprising detecting a failure of the performance to satisfy a performance threshold. The embodiment also includes initiating, responsive to detecting the failure, a redistribution procedure by changing the node identifier of the partition by replacing the first weight value with a second weight value.

Abstract: Embodiments are provided that related to a computer system, a computer program product, and a computer-implemented method for dynamically managing knowledge graphs and their corresponding datasets. Embodiments include identifying a neologism from a virtual environment, and leveraging a virtual environment exploration to resolve a meaning of the identified neologism. The resolved meaning of the neologism is applied to a dynamic expansion of a dataset and a corresponding knowledge graph.

Abstract: Embodiments for providing an enhanced codebase in a computing environment by a processor. One or more container specification files may be automatically updated with one or more changes to a codebase.

Abstract: Various embodiments are provided for dynamically factoring and composing workflows in a computing environment by one or more processors in a computing system. Subgraphs (e.g., blocks) of workflows stored in a workflow library may be identified. The subgraphs may be functional blocks such as, for example, the functional blocks may perform a logical task. Similarities and relationships may be identified between one or more of the blocks of one or more workflows. One or more blocks may be suggested for use in workflow opportunities of target workflows based on the identified associated similarities and relationships.

Abstract: Embodiments are provided for providing enhanced routing in a computing system by a processor. One or more of a plurality of short nets in a cell of an integrated circuit may be aligned for executing a routing operation, wherein a short net is a two-pin net having two gates on adjacent rows having a horizontal distance less than a selected threshold.

Abstract: A first input transaction is classified into a first input space cluster in a set of input space clusters. It is determined that the first input space cluster maps to a single explainability space cluster in a set of explainability space clusters. Using an interpretable model corresponding to the single explainability space cluster, a first machine learning model prediction is explained, the first machine learning model prediction resulting from processing, by a machine learning model, the first input transaction.

Abstract: Embodiments for providing enhanced endpoint multicast emulation in a computing environment. One or more multicast operations may be executed on an overlay network using endpoint multicast emulation by using an overlay layer or a virtual extensible LAN (“VXLAN”) layer to maintain control over one or more multicast groups.

Abstract: A method for preparing for a failure in a multi-site data replication environment is disclosed. In one embodiment, such a method includes detecting, at a primary site of a multi-site data replication environment, conditions indicating that a failure is impending at the primary site. The method further determines a probability that the impending failure will occur. The method sends, from the primary site to at least one other site of the multi-site data replication environment, a message informing the at least one other site of the impending failure and its probability. In the event the probability has reached a threshold, the method prepares the at least one other site for the impending failure before it actually occurs. A corresponding computer program product and system are also disclosed.

Abstract: A computer-implemented method according to one aspect includes creating an initialization vector, utilizing an instance of plaintext and a secret key; encrypting the instance of plaintext, utilizing the initialization vector, the secret key, and the instance of plaintext; combining the initialization vector and the encrypted instance of plaintext to create a ciphertext string; and outputting the ciphertext string.

Abstract: Embodiments for providing an enhanced codebase in a computing environment by a processor. One or more container specification files may be automatically generated for a codebase based on one or more extracted attribute names and values.

Abstract: Computation, placement, and accessing of error correcting codes (ECC) in a computer system data cache enabling partial reads and writes to each line of data in the cache. For storing multiple compressed blocks, received at differing time periods, in a single cache line, the ECC for the first compressed block is stored in the ECC field of the cache and the ECC for the second and subsequently received compressed blocks is appended to the compressed data. Additionally, an auxiliary ECC cache may be constructed for temporarily holding a partial ECC for a partial read/write, and a new ECC for the partial read/write is computed using the partial ECC.

Abstract: A phased array antenna (1) includes: a plurality of antenna elements (11a to 11d); a plurality of signal paths (R11 and R12) that are connected to each of the antenna elements; a storage unit (M) configured to store a set values of at least one of amplitudes or phases of a signal passed through at least one predefined reference path among the plurality of signal paths with regard to at least one of the antenna elements, and an amplitude and phase control unit (22 or 26) configured to control at least one of the amplitude or the phase of the signal passed through the reference path connected to the antenna element by using the set value stored in the storage unit, and configured to control amplitude or phase of signal passed through the signal path other than the reference path.

Abstract: Embodiments for providing enhanced data anonymity protection by a processor are disclosed. Selected portions of data intended for distribution in a communication channel or currently distributed on one or more data sources having a potential for revealing identify of a user in a public domain (and/or private domain) may be identified, where an assessment is provided indicating a current status of an amount of data currently exposing the identity of the user in the public domain. The selected portions of the data may be transformed into anonymous data by applying a one or more data corrective operations to prevent further exposure of the identity of the user into the public domain.

Abstract: A method, apparatus and computer program product to defend learning models that are vulnerable to adversarial example attack. It is assumed that data (a “dataset”) is available in multiple modalities (e.g., text and images, audio and images in video, etc.). The defense approach herein is premised on the recognition that the correlations between the different modalities for the same entity can be exploited to defend against such attacks, as it is not realistic for an adversary to attack multiple modalities. To this end, according to this technique, adversarial samples are identified and rejected if the features from one (the attacked) modality are determined to be sufficiently far away from those of another un-attacked modality for the same entity. In other words, the approach herein leverages the consistency between multiple modalities in the data to defend against adversarial attacks on one modality.

Abstract: An embodiment includes retrofitting an existing control device with an automation panel that senses manual actuation of a control element of the control device, and automatically actuates the control element in response to a specified control signal. The embodiment collects state data indicative of an actuation state of the control element and context data of conditions at a time that the state data is collected, and generates a training dataset comprising collected state data and sensor data. It then uses this data to train a classification model to predict a control element actuation state based on sensor data. The embodiment deploys the trained classification model to process sensor data and upon detecting a mismatch between a predicted actuation state output from the trained classification model and an actual actuation state of the control element, the embodiment transmits the specified control signal to the automation panel to actuate the control element.

Abstract: An embodiment includes parsing geographical data into a path graph having a plurality of nodes and edges, and identifying first and second subsets of the nodes as source nodes and destination nodes, respectively. The embodiment generates path data for a candidate delivery route from a source node to a destination node and along an edge between the source and destination nodes. The embodiment processes the path data using first and second evaluation techniques based on respective metrics. The embodiment compares evaluation values from the evaluation techniques to evaluation values associated with another candidate delivery route, and selects the candidate delivery route as a finalized delivery route based on the comparison results. The embodiment then generates a route plan that includes the finalized delivery route.

Abstract: An overloaded period of a first service is forecast. A first transaction is predicted to arrive at the first service during the overloaded period. At a second service, a transaction sequence including the first transaction is delayed, the delaying resulting in a delayed transaction sequence, the delayed transaction sequence delaying arrival of the first transaction at the first service until after the overloaded period.

Abstract: Embodiments for providing enhanced edge-based forecasting in a computing environment by a processor. Data from received from one or more data sources may be incorporated into a graph neural network. A forecast of one or more future conditions may be generated based the graph neural network using one or more forecasting models.

Abstract: Embodiments for providing expert-in-the-loop training of machine learning models in a computing environment by a processor. A performance of a machine learning model may be learned. Feedback for the machine learning model may be received based on learning the performance the machine learning model, where the feedback includes domain knowledge provided by a domain expert. The machine learning model may be trained or updated based the feedback of the performance of the machine learning model.

Abstract: From a set of point data, a set of scattered rays is constructed. From the set of scattered rays, a set of ray slopes is computed. The set of ray slopes is mapped to a corresponding set of trigonometric functions. Using an optimization method, a parameter of the set of trigonometric functions is selected. Using an inverse of the set trigonometric functions, a vehicle mass corresponding to the set of point data is computed. Based on the vehicle mass, a threshold braking distance of a collision avoidance system of the vehicle is adjusted, the threshold braking distance comprising a distance from an object predicted to collide with the vehicle. By braking the vehicle at least the threshold braking distance from the object, a predicted collision between the vehicle and the object is avoided.

Abstract: Embodiments for providing enhanced generative models based assistance for design and creativity in a computing environment by a processor. A partially completed design of an object may be received. A set of recommendations may be generated for completing the partially completed design based on one or more generative models.

Abstract: Embodiments are provided for providing increased efficiency of various industrial systems and processes in a computing system by a processor. One or more anomalies may be monitored and detected for a plurality of processes of an industrial system using a machine learning operation, wherein the one or more anomalies are localized. A diagnosis is generated to address the one or more anomalies.

Abstract: Embodiments for providing memory access operations for graph analytics by a processor are disclosed. An entire chunk of load and store instructions may be atomically and concurrently executed, where the entire chunk of the load and store instructions are delineated from a plurality of alternative load and store instructions.

Abstract: A computer-implemented method according to one embodiment includes determining, using a nanoservice in a first cluster, whether a microservice of a second cluster has restarted. In response to a determination that the microservice has restarted, an external job service is informed about the restart of the microservice and a job associated with the microservice is caused to be reset. A computer program product according to another embodiment includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: Embodiments for learning semantic description of data based on physical knowledge in a computing environment by a processor. Physical knowledge data and semantic labels associated with data from one or more data sources may be learned. Source attributes of the one or more data sources may be associated with one or more classes and concepts of a plurality of ontologies based on the physical knowledge data and the semantic labels to generate textual descriptors of the data.

Abstract: A continuously compounded return of an asset is converted into a set of past per time period returns of the asset. Using the set of past per time period returns of the asset and a probability distribution defined by a parameter, a future per time period return of the asset is estimated. Using the future per time period return of the asset and a set of covariances of the asset with a plurality of other assets, an ownership position of the asset is adjusted.

Abstract: A set of streams of time series data is mapped to a corresponding set of drawing coordinates of an image, wherein a first stream of time series data in the set of streams of time series data comprises data of a first executing application component, wherein a first drawing coordinate in the set of drawing coordinates represents a first state of the first executing application component at a first time. The set of drawing coordinates is drawn, wherein a line between the first drawing coordinate and a second drawing coordinate represents a dependency between the first executing application component and a second executing application component.

Abstract: Using a set of menu to key process mappings, historical menu usage data for an application is aggregated into aggregated key process usage data. A set of key process association rules, each comprising a consequent key process given a particular antecedent key process, is generated. From the set of key process association rules and a set of ranked menus by frequency of usage within each key process, a set of model menu recommendations is generated. According to an application usage history, a menu frequency ratio, and a confidence value of a modelled next menu, the set of menu recommendations is scored. A scored menu recommendation having a rank below a threshold rank is pruned from a set of menu items of the application ranked according to their scores. The pruned set of scored menu recommendations is presented for selection instead of the set of menu items.

Abstract: Design rule violations (“DRVs”) may be predicted using a design rule check (“DRC”) density map during a physical synthesis operation prior to executing a routing operation.

Abstract: A quantum computer includes a refrigeration system under vacuum including a containment vessel, a qubit chip contained within a refrigerated vacuum environment defined by the containment vessel. The quantum computer further includes a plurality of interior electromagnetic waveguides and a plurality of exterior electromagnetic waveguides. The quantum computer further includes a hermetic connector assembly operatively connecting the interior electromagnetic waveguides to the exterior electromagnetic waveguides while maintaining the refrigerated vacuum environment. The hermetic connector assembly includes an exterior multi-waveguide connector, an interior multi-waveguide connector, and a dielectric plate arranged between and hermetically sealed with the exterior multi-waveguide connector and the interior multi-waveguide connector. The dielectric plate permits electromagnetic energy when carried by the interior and exterior pluralities of electromagnetic waveguides to pass therethrough.

Abstract: Embodiments for analysis and summarization of current knowledge of data by a processor. A topic of a knowledge domain may be identified and extracted from one or more one or more data sources. A list of candidate subtopics, summaries, and a plurality of related data associated with the topic may be generated.

Abstract: An embodiment includes tokenizing an input passage into an n-gram sequence of tokens. The embodiment also includes evaluating the input passage using a trained classification model that generates an output indicative of a classification of the input passage. The embodiment also includes generating a first token vector for a first token of the sequence of tokens and projecting the first token vector to a higher dimensional space, resulting in a first projected token vector. The embodiment also includes generating a first similarity score for the first projected token vector based on comparisons of the first projected token vector to each of a plurality of class representations. The embodiment also includes generating a ranked list of the tokens, wherein the generating of the ranked list includes ranking the first token among others of the tokens based on the first similarity score.

Abstract: Various embodiments are provided for correlating regulatory data in a computing environment by a processor. A rule may be associated with one or more textual paragraphs extracted from a policy document that describes at least a portion of the rule.

Abstract: Embodiments relate to a computer platform to support processing of informational logs and corresponding performance data to detect and mitigate occurrence of anomalous behavior. Metrics are extracted from the informational logs and correlated with performance data, and in an exemplary embodiment golden signal metrics. A window or block of the logs is classified as potential candidates or indicators of anomalous behavior, which in an embodiment is indicative of potential failure or service outage. A control signal is dynamically issued to an operatively coupled device associated with the window or block of logs. The control signal is configured to selectively control a state of a physical device or process controlled by software, with the control directed at mitigating or eliminating the effect(s) of the anomalous behavior.

Abstract: Embodiments are provided for providing power staple avoidance during routing in a computing system by a processor. One or more transistor gates may be shifted in each row of an integrated circuit to avoid alignment of cell pins and power staples for executing a routing operation, where the circuit row is partitioned into segments based on one or more fixed objects.

Abstract: By analyzing a test case in a set of test cases, the test case is classified into a test type. Using a result of analyzing a test execution environment, a flake parameter is set, the flake parameter comprising an execution environment characteristic capable of causing an inconclusive result of execution of the test case. Responsive to determining that the test type maps to the flake parameter, the test case is removed from the set of test cases, the removing resulting in a filtered set of test cases, the determining performed using a predefined set of mappings. The filtered set of test cases is executed in the test execution environment.

Abstract: From a first set of natural language documents describing a demand for a movable physical item, a set of demand features is extracted. From a second set of natural language documents describing a supply of the movable physical item, a set of supply features is extracted. A correlation quantifying a relationship between the set of demand features and the set of supply features is computed. Using the correlation and the correlation trend, an attraction between the set of demand features and the set of supply features is modeled as a gravitational force. Using a routing determined according to the attraction, the movable physical item is caused to be transported.

Abstract: An embodiment includes analyzing a first digital image using a first trained neural network that classifies the first image as having a first context based on a plurality of characteristics of the first image. The embodiment generates a data structure that associates first and second elements depicted in the first image based on an affinity detected between the first and second elements in the first context. The embodiment executes a querying process that searches for information requested by a user, and detects that a search result from the querying process conveys a second context that is different from the first context. The embodiment identifies a third element in the data structure having an affinity with the first element in the second context. The embodiment renders a machine-generated image that is generated using a second trained neural network and depicts the first element and the third element in the second context.

Abstract: An embodiment includes executing a querying process that returns database documents containing text associated with a database environment. The embodiment tokenizes the database documents into a series of n-gram tokens and groups the tokens into topic classes using natural language processing (NLP). The embodiment also generates a feature map by applying a convolution layer to an image that depicts a database structure graph of the database environment. The embodiment detects an architectural element in the image by applying a region proposal network (RPN) to the feature map and classifies the architectural element into one of the plurality of topic classes using a trained neural network. The embodiment renders, responsive to a user selection of the architectural element, an overlay depicting information about the architectural element using text and other architectural elements that are in a same topic class as the user-selected architectural element.

Abstract: Embodiments for managing an as-a-service (aaS) computing system by a processor are provided. Input provided by at least one computing device to a cloud platform is monitored. Output provided by the cloud platform to the at least one computing device in response to the input provided by the at least one computing device is monitored. At least one local model is generated based on the input provided to the cloud platform and the output provided to the at least one computing device.

Abstract: An embodiment includes tokenizing a code segment generated by an integrated development environment responsive to user input, the tokenizing resulting in a tokenized code segment. The embodiment generates a search query by analyzing the tokenized code segment using a trained neural network. The embodiment executes a querying process that searches a knowledge base using the search query for a hardware requirement associated with the code segment, and detects a search result that conveys the hardware requirement as including a specialized hardware resource. The embodiment generates a time allotment associated with execution of the code segment using a second trained neural network that predicts the time allotment based on the tokenized code segment. The embodiment issues an instruction associated with the code segment to a hardware scheduler causing the hardware scheduler to allocate the specialized hardware resource for an amount of time corresponding to the time allotment.