Abstract: A method, a computer system, and a computer program product for restoration time predictions and optimized recovery solutions is provided. Embodiments of the present invention may include selecting a dataset based on time series data. Embodiments of the present invention may include building one or more models, wherein the one or more models include a classification and regression tree model, a cross validated decision tree model or a bootstrap aggregating model. Embodiments of the present invention may include selecting a model for predictions using decision trees to reduce a variance of the model. Embodiments of the present invention may include rebuilding the model based on additional data attributes. Embodiments of the present invention may include determining an outage prioritization for each outage node. Embodiments of the present invention may include transmitting results of the outage prioritization.

Abstract: Methods, computer program products, and systems are presented.

Abstract: A computer-implemented method for providing a framework to identify questions and answers dynamically from a dataset based on previous learning and an evaluation score of a user. The method includes creating a library of potential questions and answers from the dataset based on the previous learning and evaluation score of the user, and generating a set of personalized questions, for the user, related to the dataset by utilizing sentence-based machine translation (SBMT) and natural language processing (NLP) tools. The method further includes identifying a plurality of answers for the set of personalized questions for the user, based on collective information available in the dataset, and providing, to the user, the plurality of answers for the set of personalized questions for verification and evaluation.

Abstract: A computer-implemented method according to one embodiment includes defining a micro-operative of a first network. The first network has non-obligatory nodes, and the micro-operative includes rankings assigned to each of the nodes of the first network. Activated core covalences (ACCs) are established for the nodes. Each ACC defines a minimum number of neighboring nodes of the node associated with the ACC that, upon the minimum number of neighboring nodes being disconnected from the first network, cause the ranking of the associated node to decrease. An aggregated activated core covalence (A-ACC) is established, and the A-ACC corresponds to a sum of at least some of the ACCs of the nodes. The method further includes determining, based on the A-ACC, whether to perform a communication operation using a path that includes the nodes in the first network.

Abstract: A user-initiated request from a user device of a user is detected. The user-initiated request is directed to a product provider, the user-initiated request includes one or more parameters. an anonymized request is created based on the one or more parameters. The anonymized request is sent to the product provider. A provider response is received from the product provider. A targeted response is generated based on the one or more parameters of the user-initiated request and based on the provider response. The targeted response is transmitted to the user device of the user.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining historical data of demand response programs and demand response agreements respective to each of the users regarding a subject energy. Training dataset for a DR user pooling model includes attributes of the demand response data collected that are relevant to responsivities of the demand response programs. The DR user pooling model is trained by the training dataset by machine learning. A DR user pool is identified amongst users of the demand response program by the DR user pooling model. Users in the DR user pool respond to demands as a group and the DR user pool is adjusted to improve responsivities of the demand response programs.

Abstract: Embodiments of the present invention provide computer-implemented methods, computer program products and computer systems. Embodiments of the present invention can identify an effective channel on a transmission stream framework comprising a plurality of channels and nodes using current capacity states and current transmission schedules.

Abstract: Cooperative session orchestration includes devising a crypt for pre-distribution of tokens, distributing the tokens to member nodes of the network, based on a request from a delegate node of the network for brokerage of a session between the delegate node and a supplier node of the network, creating and sending, for each of a plurality of potential supplier nodes of the network, a respective individual puzzle, receiving, from each of one or more potential supplier nodes of the plurality of potential supplier nodes, a respective result obtained by the potential supplier node from solving the individual puzzle using the token distributed to the potential supplier, identifying, based on the receiving, candidate supplier node(s) of the one or more potential supplier nodes as a potential supplier for the session with the delegate node, and identifying to the delegate node the candidate supplier node(s) for the session with the delegate node.

Abstract: Disclosed are techniques for training and utilizing a machine learning model for automatically accelerating technical incident triage. A historical dataset is combined from a plurality of sources corresponding to historical technical incidences and how they were resolved, including what persons or responders were involved in responding to the incident. This historical dataset is processed for input into a machine learning model which is trained to output a ranking of historical incidences based on similarity to an input incident. Machine logic then automatically selects a responder for the incident based on which available responders previously resolved the ranked historical incidences, selecting responders from the most similar historical incidences if they are available, and communicating information from the ranked historical incidences to assist in diagnosing and resolving the input incident.

Abstract: Hybrid edge computing that includes a nimble framework that identifies services for available in a marketplace. The nimble framework defines a location for computing the services selected from the group consisting of a center server, an edge provision server and an edge node. The hybrid edge computing further includes a third party provider making are request for a service to the nimble framework. The hybrid edge computing further includes a virtualized service being provided by the nimble framework to the third party provider including a matched service to the third party provider request for the service, and an optimal location for computing.

Abstract: A method, computer program product, and system include a processor(s) that obtains a request for a transaction to be processed by an application in a computing system. The processor(s) applies, to the request for the transaction, an outlier detection model, to determine whether the transaction comprises attributes matching transaction tuples of one or more historical transactions identified as triggering issues in the computing system when the application processed the historical transactions. The processor(s) classifies the transaction as being an outlier transaction or as being a standard transaction, based on applying the outlier detection model. Based on determining that the transaction is an outlier transaction, concurrently with the application processing the transaction, the processor(s) turn on the debug trace to debug trace the application processing of the transaction.

Abstract: Generating a model for evaluating organizational skills to determine cost of entering a new market includes training a machine learning model to define business capabilities, processes and required skills of an organization based on a current business strategy, training the machine learning model to define a plurality of skill classes of the required skills of the organization using the cognitive computing processor device, training the machine learning model to define skill profiles of the available talent of the organization based on the plurality of skill classes, determining skill gaps of the available talent of the organization by analyzing the required skills of the organization and the skill profiles, assessing skills required for a new business strategy for the organization, and determining a cost of the organization executing the new business strategy based on the skill profiles, the at least one skill gap and the new business strategy skills.

Abstract: An example operation may include one or more of receiving a request to store a skill-based attribute of a user at a database, temporarily storing the skill-based attribute and an identification of one or more storage nodes associated with the skill-based attribute in a temporary data structure of the database, determining whether a predetermined amount of the one or more storage nodes have authenticated the user as having the skill-based attribute, and, in response successful authentication of the skill-based attribute by the predetermined amount of storage nodes, transferring the authenticated skill-based attribute from the temporary data structure to a primary data structure of the database.

Abstract: A model is generating for predicting energy workloads to adjust electrical energy supply to meet varying short-term energy demands at a microcosm level. A model is developed, using a computer, to facilitate predicting energy workloads for adjusting energy supplies to meet an energy demand. The model includes receiving, at the computer, input parameters of dynamic values of workloads as historical data, and generating a predictive model by analyzing the input parameters. The model further includes predicting short-term energy demands based on the predictive model, the predicted short-term energy demands include identifying a predicted peak value. Also, the model includes initiating short term energy output in an electrical grid to a transformer level component in the electrical grid based on the predicted short term energy demands.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems. Embodiments of the present invention can. in response to receiving information, map an environment comprising one or more electronic devices. Embodiments of the present invention can then dynamically update the mapped environment based on the received information. Embodiments of the present invention can then display the updated environment on display areas of respective electronic devices of the one or more electronic devices.

Abstract: A method, system, and computer program product for implementing automated software application generation is provided. The method includes scanning source code for identifying missing elements of hardware and software parameters associated with functional operation of software for development. The hardware and software parameters are analyzed and converted into configurable digital bins. An automation parameter is generated. The automation parameter is associated with portions of the software configured for automatic development and generation. Corrective actions associated with automating development of the software are generated based on the automation parameter and it is determined that the automation parameter is within a specified range of the portions. The corrective actions are executed with respect to development of the software and the software is generated.

Abstract: A method includes receiving, by one or more processors of a computer system, historical data related to deployment characteristics and an architecture for past incidents occurring in a data warehouse, predicting, by the one or more processors of the computer system using neural network modeling, tickets related to a response to at least one incident occurring in the data warehouse, wherein the predicting is based on the deployment characteristics and the architecture of the data warehouse, considering, by the one or more processors of a computer system, a plurality of parameters to ascertain the predicted tickets, and providing, by the one or more processors of the computer system, incident ticket volume prediction including the predicted tickets to an incident management system interface reviewable by a user.

Abstract: Electronic circuit assemblies are provided, with an electronic circuit assembly including a transducer circuit to generate electrical energy based on applied pressure, and a static-electricity capture circuit to capture electrical energy from static-electrical charge. Further, the electronic circuit assembly includes a power management circuit electrically coupled to the transducer circuit and the static-electricity capture circuit to receive, at least in part, the generated electrical energy based on applied pressure at the transducer circuit and the electrical energy from static-electrical charge captured by the static-electricity capture circuit.

Abstract: Inadvertent data swaps can be prevented by measuring volume of transactions in distributed computing environment to determine locations for potential data swaps; and managing a correlation between a thread identification (ID) and transaction header (ID) for transactions in the distributed computing environment. In some embodiments, the prevention of data swaps can further include performing a data transmission interruption to avoid data swaps at the locations for potential data swaps. When the thread identification (ID) and transaction header (ID) do not match the potential for data swaps can be high.

Abstract: A method includes using, by one or more processors of a computer system, a cognitive model to estimate software development parameters for a software development project based on one or more similar past projects, and automatically assigning, by the one or more processors of the computer system, story points to sprints of the software development project based on the estimated software development parameters.